WO2015136509A2 - Diagnostic and therapeutic targets for preeclampsia and closely related complications of pregnancy - Google Patents

Diagnostic and therapeutic targets for preeclampsia and closely related complications of pregnancy Download PDF

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WO2015136509A2
WO2015136509A2 PCT/IB2015/051906 IB2015051906W WO2015136509A2 WO 2015136509 A2 WO2015136509 A2 WO 2015136509A2 IB 2015051906 W IB2015051906 W IB 2015051906W WO 2015136509 A2 WO2015136509 A2 WO 2015136509A2
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WIPO (PCT)
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znf554
preeclampsia
lgals
pregnancy
expression
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PCT/IB2015/051906
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French (fr)
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WO2015136509A3 (en
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Nándor Gábor THAN
Tzu Hung CHUNG
Gábor JUHÁSZ
Adrienna Katalin KÉKESI
Manuel Krispin
Ron LEAVITT
Zoltán PAPP
Roberto Romero
Adi L. TARCA
Original Assignee
Genesis Theranostix Korlatolt Felelossegu Tarsasag
Semmelweis University
Wayne State University
The United States Of America As Represented By The Secretary, Department Of Health And Human Services Office Of Technology Transfer, National Institutes Of Health
Zymo Research Corporation
Eotvos Lorand University
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Application filed by Genesis Theranostix Korlatolt Felelossegu Tarsasag, Semmelweis University, Wayne State University, The United States Of America As Represented By The Secretary, Department Of Health And Human Services Office Of Technology Transfer, National Institutes Of Health, Zymo Research Corporation, Eotvos Lorand University filed Critical Genesis Theranostix Korlatolt Felelossegu Tarsasag
Publication of WO2015136509A2 publication Critical patent/WO2015136509A2/en
Publication of WO2015136509A3 publication Critical patent/WO2015136509A3/en

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/154—Methylation markers

Definitions

  • the present disclosure provides biomarkers and methods which can be used to predict and/or detect preeclampsia in pregnant women. More specifically, the DNA methylation of genes listed in the disclosure can be used as biomarkers for the early prediction and/or detection and/or clinical follow-up of preeclampsia. These biomarkers and methods may also allow early prediction, detection and/or clinical follow-up of complications of pregnancy closely related to preeclampsia wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
  • the present disclosure also provides molecular drug targets and/or candidate therapeutic molecules and methods to prevent or treat preeclampsia and related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
  • Preeclampsia is a syndrome defined by pregnancy-induced hypertension and proteinuria, which can lead to eclampsia (convulsions), and other serious maternal and/or fetal complications.
  • Preeclampsia is originated in early gestation from the failure of implantation mechanisms and/or placental development, and is thus closely related to complications of pregnancy in early gestation such as including but not limited to implantation failure, and threatened and spontaneous miscarriage, Preeclampsia affects approximately 5-7% of pregnant women (approximately 8,370,000 pregnant women worldwide per year) and is a major cause of maternal and perinatal mortality.
  • women with preeclampsia have an 8-fold higher risk of cardiovascular death later in their life, and offspring born from pregnancies affected by preeclampsia have an increased risk of metabolic and cardiovascular disease and mortality later in life.
  • preeclampsia set by the United States National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy include new-onset hypertension coupled with proteinuria that develops after 20 weeks of gestation in women with previously normal blood pressures. These criteria further define preeclampsia as systolic or diastolic blood pressures of >140 and/or >90 mmHg, respectively, measured at two or more different time points, at least 4 hours (h) but not more than 1 week apart, as well as proteinuria of >300 mg protein in a 24 h urine sample, or two random urine specimens obtained at least 4 h but not more than 1 week apart containing ⁇ 1+ protein on a dipstick.
  • preeclampsia Based on the timing of the clinical manifestation, preeclampsia has been historically classified into different sub-forms, such as “term” (>37 weeks) and “preterm” ( ⁇ 37 weeks) or by using an alternative terminology “late-onset” and “early-onset” preeclampsia.
  • the latter classification has not been uniformly used, but different studies have employed a range of gestational age cutoffs varying between 28 and 35 weeks for the distinction between early-onset and late-onset preeclampsia. Recently, it has been suggested to define 34 weeks as the gestational age cutoff between these two forms. It is important to note that preeclampsia may occur intrapartum or postpartum; thus, monitoring and evaluating the symptoms of preeclampsia should be continued during the postpartum period.
  • preeclampsia may be associated with haemolysis, abnormal liver function and thrombocytopenia. Initially accepted to be a severe variant of preeclampsia, this group of symptoms later was suggested to constitute a separate clinical entity termed Haemolysis, Elevated Liver enzymes and Low Platelets (HELLP) syndrome. Supporting the idea that HELLP syndrome is a distinct condition, up to 20% of HELLP syndrome patients do not develop hypertension, 5-15% have minimal or no proteinuria and 15% show neither hypertension nor proteinuria. Moreover, laboratory findings in HELLP syndrome rarely correlate with the severity of hypertension or proteinuria.
  • preeclampsia and HELLP syndrome cause approximately $7 billion in healthcare costs in the United States annually. Accordingly, there have been many attempts to provide a reliable predictive test for preeclampsia/HELLP syndrome. Previous attempts have involved assays for the concentrations of circulating biochemical markers in maternal blood but to date, the scientific literature on these approaches have been contradictory and inconclusive. There is a need in the art for new and improved methods of predicting and diagnosing these conditions.
  • preeclampsia is a multi-stage disease with placental origins in early pregnancy. Compared to normal human pregnancy where extravillous trophoblasts deeply invade uterine tissues and remodel the decidual and myometrial segments of maternal spiral arteries to provide a continuous and increased blood supply for the developing fetus, this process is impaired in the first stage of preeclampsia in most cases.
  • trophoblast invasion is the deepest among all species in humans, and preeclampsia occurs in humans and great apes with deep trophoblast invasion, supporting an evolutionary link between deep trophoblast invasion, its failure and preeclampsia.
  • a partial impairment in deep placentation leads to placental endoplasmic reticulum stress and intrauterine growth restriction, while a more severe, complete impairment in trophoblast invasion promotes placental oxidative stress superimposed on endoplasmic reticulum stress, leading to the release of toxins and the development of the maternal syndrome in preeclampsia.
  • the very early and severe manifestation of impaired trophoblast invasion will lead to the premature onset of maternal circulation in the placenta, a strong oxidative stress of the placenta, the regression of the trophoblast, and ultimately the termination of pregnancy in the first trimester. This is of major importance, since 70% of pregnancies fail in the first trimester, and in two thirds of these miscarriages anatomical evidence shows defective placentation characterized by impaired trophoblast invasion into uterine spiral arteries.
  • biomarker panel which is assembled from the best protein and RNA biomarkers identified in the placenta and maternal serum. These biomarkers are repeatedly detectable in 7-9th weeks of gestation and may enable the earliest and most sensitive prediction and clinical follow-up of patients with preeclampsia, as well as the molecular distinction of various subtypes of preeclampsia (PCT/US13/45709).
  • the present disclosure is built on some elements included in PCT/US13/45709, it contains several unique novel features that offer a multiplexed, DNA methylation-based diagnostic and prognostic tool and also therapeutic targets for preeclampsia and complications of pregnancy closely related to preeclampsia wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage before symptoms manifest in the female and/or fetus.
  • the aim of the present disclosure was achieved by the inclusion of a systems biological approach for the analysis of data obtained from various high-dimensional biology techniques: 1) whole-genome transcnptomics of the human placenta; 2) high-throughput qRT-PCR expressional profiling of the human placenta; 3) whole-genome transcnptomics and high-throughput qRT-PCR expressional profiling of human trophoblastic cells after in vitro experiments, and their investigation with functional assays; 4) multiplexed bisulfite next generation sequencing of human trophoblastic and non-trophoblastic DNA specimens; and 6) 2D-DIGE proteomics of first trimester human maternal sera.
  • the present disclosure provides biomarkers and methods which can be used to predict and/or detect preeclampsia in pregnant women. More specifically, the DNA methylation status of genes listed in the disclosure can be used as biomarkers for the early prediction, diagnosis, risk assessment and/or clinical follow-up of preeclampsia. Because of the overlapping placental pathologies in early pregnancy, these biomarkers and methods may also allow the early prediction, detection and/or clinical follow-up of complications of pregnancy closely related to preeclampsia wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
  • the present disclosure is the first to provide the definition for the "molecular phase" of preeclampsia, and to identify the early mechanisms of preeclampsia by defining new pathways of disease.
  • the dysregulation of these pathways i.e. the "ZNF554 pathway” and the "BCL6-ARNT2 pathway"
  • ZNF554 pathway and the "BCL6-ARNT2 pathway
  • BCL6-ARNT2 pathway is central to the early pathology of preeclampsia.
  • the present disclosure provides with key molecules that are central to these disease pathways.
  • the disclosure provides molecular drug targets and/or candidate therapeutic molecules and methods to prevent or treat preeclampsia and related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
  • HELLP syndrome intrauterine growth restriction
  • intrauterine fetal demise preterm premature rupture of the membranes
  • One embodiment includes a method for assessing the presence or risk of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in a female to determine the need for a treatment regimen comprising: determining DNA methylation status of one or more of ARNT2; BCL3; BCL6; BTG2; CDKN1A; CGB3; CLC; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1; ESRRG; FLT1 ; GATA2; GCM1 ; GH2; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; LEP; LGALS13; LGALS14; LGALS16; MAPK13; PAPPA2; PGF; PLAC1
  • the assaying is performed for the DNA methylation status of all markers described above.
  • the assaying is performed for the DNA methylation status of at least three biomarkers.
  • the assaying is performed for DNA methylation status of at least one marker described in the figures and examples described herein.
  • the sample is a blood sample.
  • sample is other body fluid, secretion or excretion (such as but not limited to cervicovaginal fluid, saliva, or urine) sample.
  • sample is an amniotic fluid sample.
  • the sample is fetal cells obtained invasively or non-invasively.
  • the sample is sperm or cells obtained from the embryo.
  • the sample is a placental sample.
  • the biological sample is obtained before the 20 week of pregnancy, before the 19 week of pregnancy,
  • the treatment regimen is a therapeutic intervention.
  • the therapeutic intervention prevents or reduces symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage before symptoms manifest in the female and/or fetus.
  • complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage before symptoms manifest in the female and/or fetus.
  • kits for assessing the presence or risk of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in a female to determine the need for a treatment regimen comprising: detection mechanisms for determining DNA methylation status of one or more of ARNT2; BCL3; BCL6; BTG2; CDKN1A; CGB3; CLC; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FLT1; GATA2; GCM1; GH2; HSD11 B2; HSD17B1 ; I KBKB; INSL4; JUNB; LEP; LGALS13; LGALS14; LGALS16; MAPK13; PAPPA2; PGF;
  • the kit includes detection mechanisms for all markers described above.
  • the kit includes detection mechanisms for at least three markers.
  • the methods and kits measure levels of at least one marker described in the figures and examples described herein.
  • the methods include evaluating DNA methylation status, expression, level or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1; I KBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; T
  • the said methods include evaluating DNA methylation status, expression, level or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG in a sample from a subject having preeclampsia or closely related complication of pregnancy before administering the treatment to the subject, to provide a baseline level for the subject.
  • the said methods include evaluating DNA methylation status, expression, level or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16 in a sample from a subject having preeclampsia or closely related complication of pregnancy before administering the treatment to the subject, to provide a baseline level for the subject.
  • the said methods include evaluating DNA methylation status, expression, level or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 in a sample from a subject having preeclampsia or closely related complication of pregnancy before administering the treatment to the subject, to provide a baseline level for the subject.
  • the invention provides therapeutic methods that prevent or reduce the symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising: the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD
  • the said therapeutic methods comprise the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG.
  • a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ARNT2; BCL
  • the said therapeutic methods comprise the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS 14; or LGALS16.
  • the said therapeutic methods comprise the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of AGT; ZNF554; BCL6; or ARNT2.
  • the invention provides methods of evaluating an effect of a treatment for preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
  • the methods include administering a treatment to the subject; evaluating DNA methylation status, expression, level or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; T
  • the said methods of evaluating an effect of a treatment include evaluating DNA methylation status, expression, level or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG in a sample from the subject after administration of the treatment.
  • the said methods of evaluating an effect of a treatment include administering a treatment to the subject; evaluating DNA methylation status, expression, level or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16 in a sample from the subject after administration of the treatment.
  • the said methods of evaluating an effect of a treatment include administering a treatment to the subject; evaluating DNA methylation status, expression, level or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 in a sample from the subject after administration of the treatment.
  • the methods include assigning a value to said subject for the effectiveness of the treatment. In some embodiments, the methods further include providing a record of that value, e. g., to the subject or to a health care provider. In some embodiments, the methods further include determining whether to continue to administer the treatment to the subject, or whether to administer the treatment to another subject.
  • the invention also provides methods for identifying candidate therapeutic agents for the treatment of preeclampsia and closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
  • the methods include providing a model of the disease, e.g., a non-human experimental animal model; contacting the model with a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; LGALS 17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1; SERPINE1
  • a positive effect on the model e.g., an improvement in a symptom of an animal model, modification of the DNA methylation status, expression, level, or activity of the target molecules, indicates that the candidate compound is a candidate therapeutic agent for the treatment of preeclampsia or closely related complication of pregnancy.
  • the said methods for identifying candidate therapeutic agents include providing a model of the disease, e.g., a non-human experimental animal model; contacting the model with a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; AP0A4; APOH; AP0L1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG identified by a method described herein; and
  • the said methods for identifying candidate therapeutic agents include providing a model of the disease, e.g., a non-human experimental animal model; contacting the model with a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16; identified by a method described herein; and evaluating the effect of the candidate compound on the model.
  • a model of the disease e.g., a non-human experimental animal model
  • a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16 identified by a method described herein
  • the said methods for identifying candidate therapeutic agents include providing a model of the disease, e.g., a non-human experimental animal model; contacting the model with a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 identified by a method described herein; and evaluating the effect of the candidate compound on the model.
  • a model of the disease e.g., a non-human experimental animal model
  • the invention also provides methods for identifying candidate therapeutic agents for the treatment of preeclampsia and closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
  • the methods also include administering candidate therapeutic agents identified by methods described herein that modifies the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM
  • the said methods for identifying candidate therapeutic agents also include administering candidate therapeutic agents identified by methods described herein that modifies the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG identified by a method described herein, to a subject having preeclampsia or closely related complication of pregnancy, and evaluating
  • the said methods for identifying candidate therapeutic agents also include administering candidate therapeutic agents identified by methods described herein that modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS 14; or LGALS 16 identified by a method described herein, to a subject having preeclampsia or closely related complication of pregnancy, and evaluating the effect of the candidate therapeutic agent on a symptom of the disorder.
  • the said methods for identifying candidate therapeutic agents also include administering candidate therapeutic agents identified by methods described herein that modifies the DNA methylation status, expression, level, or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 identified by a method described herein, to a subject having preeclampsia or closely related complication of pregnancy, and evaluating the effect of the candidate therapeutic agent on a symptom of the disorder.
  • the invention provides pharmaceutical composition that prevents or reduces the symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising specific "inhibitors", "activators” or “modulators” of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT;
  • Inhibitors are compounds that, e.g., bind to, partially or totally block activity, decrease, prevent, delay activation, inactivate, desensitize, or down-regulate the activity or expression of these molecules.
  • Activators are compounds that increase, open, activate, facilitate, enhance activation, sensitize, agonize, or up-regulate activity of these molecules, e.g., agonists.
  • “Inhibitors”, “activators”, or “modulators” also include genetically modified versions of these molecules, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
  • the said pharmaceutical composition comprises specific "inhibitors", “activators” or “modulators” of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG.
  • the said pharmaceutical composition comprises specific "inhibitors", “activators” or “modulators” of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS14; or LGALS16.
  • the said pharmaceutical composition comprises specific "inhibitors”, “activators” or “modulators” of one or more of AGT; ZNF554; BCL6; or ARNT2.
  • compositions for the treatment of preeclampsia or closely related complication of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, including therapeutic agents identified by a method described herein, and physiologically acceptable carriers, which modify the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; I
  • the said pharmaceutical compositions including therapeutic agents identified by a method described herein, and physiologically acceptable carriers, which modify the DNA methylation status, expression, level, or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16 identified by a method described herein.
  • compositions including therapeutic agents identified by a method described herein, and physiologically acceptable carriers, which modify the DNA methylation status, expression, level, or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 identified by a method described herein.
  • the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
  • the methods include providing a sample comprising of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH 1; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554;
  • the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample. In some embodiments, the methods further include identifying the test compound as a candidate compound based on the assigned value.
  • a test compound used in a method described herein is selected from the group consisting of genetically modified versions of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS 14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM
  • a test compound used in a method described herein is selected from the group consisting of genetically modified versions of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cycloeth Generation factor, and others.
  • a test compound used in a method described herein is selected from the group consisting of genetically modified versions of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS14; or LGALS16, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
  • a test compound used in a method described herein is selected from the group consisting of genetically modified versions of one or more of AGT; ZNF554; BCL6; or ARNT2, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
  • the test compound is a cell expressing exogenous therapeutic target molecule, e.g., a trophoblast expressing an increased or decreased level of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6;
  • the test compound is a cell expressing exogenous therapeutic target molecule, e.g., a trophoblast expressing an increased or decreased level of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG.
  • the test compound includes target molecule polypeptides or nucleic acids, or active fragments thereof.
  • the test compound is a cell expressing exogenous therapeutic target molecule, e.g., a trophoblast expressing an increased or decreased level of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS 14; or LGALS16.
  • the test compound includes target molecule polypeptides or nucleic acids, or active fragments thereof.
  • the test compound is a cell expressing exogenous therapeutic target molecule, e.g., a trophoblast expressing an increased or decreased level of one or more of AGT; ZNF554; BCL6; or ARNT2.
  • the test compound includes target molecule polypeptides or nucleic acids, or active fragments thereof.
  • the invention also provides methods for making pharmaceutical compositions for the treatment of preeclampsia or closely related complication of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, by formulating a therapeutic agent identified by a method described herein with a physiologically acceptable carrier.
  • the invention provides methods for evaluating a compound.
  • the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy.
  • the methods include providing a sample comprising of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN 1A; CGB3; CLC; CLDN1; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; I KBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; LGALS 17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5
  • a test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound.
  • the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample.
  • the methods further include identifying the test compound as a candidate compound based on the assigned value.
  • the invention provides methods for evaluating a compound.
  • the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy.
  • the methods include providing a sample comprising of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG; contacting the sample with a test compound; and determining if the test compound specifically mod
  • a test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound.
  • the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample.
  • the methods further include identifying the test compound as a candidate compound based on the assigned value.
  • the invention provides methods for evaluating a compound.
  • the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy.
  • the methods include providing a sample comprising of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16; contacting the sample with a test compound; and determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of these molecules in the sample.
  • a test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound.
  • the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample. In some embodiments, the methods further include identifying the test compound as a candidate compound based on the assigned value.
  • the invention provides methods for evaluating a compound.
  • the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy.
  • the methods include providing a sample comprising of one or more of AGT; ZNF554; BCL6; or ARNT2; contacting the sample with a test compound; and determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of these molecules in the sample.
  • a test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound.
  • the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample. In some embodiments, the methods further include identifying the test compound as a candidate compound based on the assigned value.
  • Figure 1A-B shows co-expression matrices of transcription regulatory genes and predominantly placenta expressed genes in the "red and green modules" in placental microarray data.
  • A Co-expression matrix shows that within the red module, BCL6, VDR, BHLHE40, ARNT2, JUNB and BTG2 transcription regulatory genes had their expression most correlated with FLT1 and predominantly placenta expressed genes. BCL6 and ARNT2 expression had the highest correlation with that of FLT1.
  • B Co-expression matrix shows that within the green module, ESRRG, POU5F1 , ZNF554, and HLF transcription regulatory genes had their expression most correlated with predominantly placenta expressed genes. ESRRG and ZNF554 expression had the highest correlation with that of CSH1 and HSD11 B2, genes strongly implicated in fetal growth.
  • FIG. 2A-B shows first trimester maternal serum proteomics changes in preterm preeclampsia.
  • A Venn diagram of proteomics data shows that the 19 differentially expressed maternal serum proteins in the first trimester in preterm preeclampsia belong to six functional groups, which are relevant for the pathophysiology of preeclampsia.
  • B These 19 serum proteins have connections with 121 differentially expressed placental genes in preeclampsia, among which 48 belong to the "red module” that is dysregulated in association with high blood pressure.
  • Figure 3A-B shows first trimester maternal serum proteomics changes in term preeclampsia.
  • A Venn diagram of proteomics data shows that the 14 differentially expressed maternal serum proteins in term preeclampsia belong to six functional groups, which are relevant for the pathophysiology of preeclampsia.
  • B These 14 serum proteins have connections with 116 differentially expressed placental genes in preeclampsia, among which 46 belong to the "red module” that is dysregulated in association with high blood pressure.
  • Figure 4A-E shows in vitro modeling of the placental dysregulation of gene modules in preeclampsia.
  • A Hierarchical clustering of expression data for 47 genes in 100 placental specimens and a heatmap representing differential gene expression in term or preterm subgroups of preeclampsia compared to respective controls.
  • B Preterm preeclampsia serum induced the up-regulation of seven placental dysregulated genes in primary trophoblasts, among which six were up-regulated in term and three in preterm preeclampsia.
  • C The overexpression of ARNT2 or BCL6 in normoxic BeWo cells induced the dysregulation of five genes dysregulated in preeclampsia.
  • Figure 5 shows BCL6 expression in BeWo cells after various treatments with 5-azacitidin and Forskolin. Decreased BCL6 expression was observed in BeWo cells upon treatment with 5-azacitidin (5-AZA) irrespective of Forskolin (FRSK) co-treatment.
  • Figure 6 summarizes the obtained data showing that serum factors and epigenetic changes modify BCL6 expression upstream of ARNT2, and the overexpression of these transcription factors leads to trophoblast sensitization to hypoxic/ischemic stress, and the consequent dysregulation of red and green modules, mostly in preterm preeclampsia.
  • Figure 7 shows tissue qRT-PCR array data that revealed the highest ZNF554 expression in the placenta among 48 human tissues.
  • Figure 8A-B shows ZNF554 expression in the placenta.
  • A In situ hybridization of a third trimester placenta (GW29) and
  • B immunohistochemistry of a first trimester placenta (GW12) shows mainly syncytiotrophoblastic ZNF554 expression (1400x and 400x magnifications).
  • Black or white arrowheads depict syncytiotrophoblast or cytotrophoblast, while black arrow depicts fetal endothelium, respectively.
  • Figure 9 shows qRT-PCR data depicting that ZNF554 expression is up-regulated during villous cytotrophoblast differentiation in parallel with CSH1.
  • Figure 10A-B shows ZNF554 expression in the placenta.
  • ZNF554 immunopositivity was faint in the syncytiotrophoblast in (B) preeclampsia (GW35) compared to (A) gestational-age matched controls (GW36).
  • Arrow and arrowhead depict syncytiotrophoblast and fetal endothelium, respectively (400x magnifications).
  • Figure 11A-E shows in vitro gene expression data of BeWo cells after ZNF554 knock-down.
  • B Nuclear and cytoplasmic ZNF554 immunofluorescence decreased in BeWo cells treated with ZNF554 siRNA compared to control cells.
  • C Bioinformatics analyses revealed the glycolysis / gluconeogenesis pathway, RNA, nucleic acid and activin binding to be affected in ZNF554 knock-down BeWo cells.
  • D qRT-PCR validated FSTL3 up-regulation (2.7-fold, p ⁇ 0.001) in BeWo cells upon ZNF554 knock-down.
  • Figure 12A-B shows ZNF554 immunostainings in first and third trimester placentas.
  • A Extravillous trophoblasts in the trophoblastic columns (GW12) and
  • B endovascular and intraluminal trophoblasts in the myometrium (GW36) were immunostained for cytokeratin-7 (left) and ZNF554 (right).
  • Figure 13A-B shows that ZNF554 immunostainings in decidual extravillous trophoblasts (arrowheads) and syncytiotrophoblats (arrows) were weaker in (B) preeclampsia (GW35) than in (A) controls (GW36) (serial sections, 200x magnifications).
  • Figure 14 shows in vitro gene expression data of HTR8/SVneo cells after ZNF554 knock-down.
  • A At 87% ZNF554 mRNA knock-down (p ⁇ 0.001)
  • B ZNF554 immunofluorescence was weaker in the nucleus and cytoplasm of ZNF554 knock-down (left) than control (right) HTR8/SVneo cells.
  • Figure 15 shows the effect of ZNF554 knock-down on cell proliferation in HTR8/SVneo cells.
  • Y-axis depicts viable cell number,
  • X-axis shows incubation time.
  • B The differential expression of CDKN1A and STK40 (genes involved in the regulation of cell cycle) upon ZNF554 knock-down was confirmed by qRT-PCR. Oxygen concentrations are shown below the bars.
  • Figure 16 shows the effect of ZNF554 knock-down on gene expression in HTR8/SVneo cells. The dysregulation of selected genes upon ZNF554 knock-down was confirmed by qRT-PCR. Oxygen concentrations are shown below the bars.
  • Figure 17 shows the effect of ZNF554 knock-down on protein secretion from HTR8/SVneo cells.
  • SERPINE PAI-1
  • TIMP3 SERPINE
  • Oxygen concentrations are shown below the bars.
  • Figure 18 shows the effect of ZNF554 knock-down on the migratory and invasive capacity of HTR8/SVneo cells. ZNF554 knock-down cells had remarkably decreased invasive (left) and migratory (right) characteristics. Oxygen concentrations are shown below the bars.
  • Figure 19A-D shows the evolutionary origins of deep trophoblast invasion in humans.
  • the ⁇ 3kb human ZNF554 5'UTR black line
  • HREs hypoxia-response elements
  • the macaque 5'UTR activity ratio did not differ between hypoxia and 8%02, the orangutan 5'UTR activity ratio was higher in hypoxia than in 8%02 (+28%, p ⁇ 0.01), and the human 5'UTR activity ratio was the highest in hypoxia (+60% vs. macaque, p ⁇ 0.00001; +22% vs. orangutan, p ⁇ 0.01).
  • Figure 20 shows the origins of impaired trophoblast invasion and preeclampsia.
  • the methylation of certain CpGs at two HREs in AluY in the trophoblast inhibits the mechanisms of deep trophoblast invasion, and promotes the development of preeclampsia.
  • Figure 21 shows gene expression changes in BeWo cells upon 5-azacitidin treatment and Forskolin co-treatment. There were 37 genes that had differential expression upon treatment with 5-azacitidin (5-AZA), with or without Forskolin (FRSK) co-treatment, suggesting their regulation by DNA methylation in the trophoblast.
  • 5-azacitidin 5-AZA
  • FRSK Forskolin
  • Figure 22 Figure 22. summarizes the identified epigenetic biomarker genes and biomarker candidate regions for preeclampsia and closely related complications of pregnancy.
  • the listed 37 genes had differential methylation and consequent differential expression upon 5-azacitidin treatment in BeWo cells. Five out of these 37 genes were further characterized for differential methylation in primary trophoblasts, cord blood cells, and laser captured trophoblasts. The genomic regions with differential methylation in the three comparisons are shown in the figure and treated as biomarker candidates.
  • Figure 23 summarizes the potential therapeutic target molecules identified by the proteomics study, their observed mechanism of dysregulation in preeclampsia, and the required effect of the therapeutics.
  • Figure 24 summarizes the potential therapeutic target molecules identified by the transcriptomics study, their observed mechanism of dysregulation in preeclampsia, and the required effect of the therapeutics.
  • Figure 25 describes pathologic pathways in preeclampsia.
  • characteristic alterations in the maternal proteome can be observed, supporting that the activation of the complement and renin-angiotensin systems as well as maternal metabolic pathways have key role in triggering early pathologic events.
  • These alterations in maternal blood can induce trophoblastic functional changes leading to the overproduction of sFlt-1 and an anti-angiogenic state through a trajectory that does not necessarily affect fetal growth.
  • ZNF554 The "ZNF554" pathway have evolved in great apes to support deep trophoblast invasion, and the epigenetic dysregulation of this pathway is a key component in impaired trophoblast invasion in preeclampsia.
  • the red gene module associated with blood pressure elevation is not only up-regulated by alterations in maternal blood proteome but also by the overproduction of BCL6 and ARNT2 due to epigenetic background.
  • the up-regulation of this "BCL6-ARNT2 pathway” sensitizes the trophoblast to ischemia, and increases FLT1 and decreases PIGF expression. These changes are only observed in the placenta in preterm preeclampsia, suggesting that the dysregulation of this pathway promotes the earlier development of the preclinical phase of preeclampsia in conjunction with the placental release of pro-inflammatory molecules and trophoblastic debris.
  • the interplay of these distinct pathomechanisms lead to the complex and "personalized" pathogenesis of preeclampsia.
  • DNA and RNA expression patterns can be evaluated by northern analysis, PCR, RT-PCR, quantitative real-time RT-PCR analysis with TaqMan assays, FRET detection, monitoring one or more molecular beacon, hybridization to an oligonucleotide array, hybridization to a cDNA array, hybridization to a polynucleotide array, hybridization to a liquid microarray, hybridization to a microelectric array, molecular beacons, cDNA sequencing, clone hybridization, cDNA fragment fingerprinting, serial analysis of gene expression (SAGE), subtractive hybridization, differential display and/or differential screening.
  • SAGE serial analysis of gene expression
  • Gene expression changes can be related to epigenetic variations (e.g. DNA methylation).
  • Epigenetic regulation mechanisms do not involve a change to the DNA sequence.
  • epigenetic variations include covalent modification of DNA, RNA, and the proteins associated with DNA. These in turn can result in changes to the conformation of DNA and accessibility of regulators to the DNA.
  • Such changes cannot be identified simply by gene sequencing. Janssen, B.G. et al., Particle and Fibre Toxicology, 10:22 (2013) studied methylation in placental tissue using methods published by Tabish, A.M. et al., PLoS ONE 2012, 7:e34674 and by Godderis, L. et al., Epigenomics 4:269-277 (2012).
  • MS-MLPA Metal-specific Multiplex ligation-dependent probe amplification
  • Protein expression patterns can be evaluated using any method that provides a quantitative measure and is suitable for evaluation of multiple markers extracted from samples.
  • Exemplary methods include: ELISA sandwich assays, mass spectrometric detection, calorimetric assays, binding to a protein array (e.g., antibody array), or fluorescent activated cell sorting (FACS).
  • Approaches can use labeled affinity reagents (e.g., antibodies, small molecules, etc.) that recognize epitopes of one or more protein products in an ELISA, antibody array, or FACS screen.
  • Protein activity can be measured by any known protein assay that are capable of reliably and specifically measuring the protein component.
  • the term high-throughput refers to a format that performs at least about 100 assays, or at least about 500 assays, or at least about 1000 assays, or at least about 5000 assays, or at least about 10,000 assays, or more per day.
  • high-throughput expression analysis methods involve a logical or physical array of either the subject samples, or the protein markers, or both.
  • Appropriate array formats include both liquid and solid phase arrays.
  • liquid phase arrays e.g., for hybridization of nucleic acids, binding of antibodies or other receptors to ligand, etc.
  • assays employing liquid phase arrays can be performed in multiwell or microtiter plates.
  • Microtiter plates with 96, 384, or 1536 wells are widely available, and even higher numbers of wells, e.g., 3456 and 9600 can be used.
  • the choice of microtiter plates is determined by the methods and equipment, e.g., robotic handling and loading systems, used for sample preparation and analysis.
  • a variety of solid phase arrays can also be employed to determine expression patterns.
  • Exemplary formats include membrane or filter arrays (e.g., nitrocellulose, nylon), pin arrays, and bead arrays (e.g., in a liquid "slurry").
  • any solid support capable of withstanding the reagents and conditions necessary for performing the particular expression assay can be utilized.
  • functionalized glass, silicon, silicon dioxide, modified silicon, any of a variety of polymers, such as (poly)tetrafluoroethylene, (poly)vinylidenedifluoride, polystyrene, polycarbonate, or combinations thereof can all serve as the substrate for a solid phase array.
  • quantitative data obtained about the markers of interest and other dataset components can be subjected to an analytic process with chosen parameters.
  • the parameters of the analytic process may be those disclosed herein or those derived using the guidelines described herein.
  • the analytic process used to generate a result may be any type of process capable of providing a result useful for classifying a sample, for example, comparison of the obtained dataset with a reference dataset, a linear algorithm, a quadratic algorithm, a decision tree algorithm, or a voting algorithm.
  • the analytic process may set a threshold for determining the probability that a sample belongs to a given class. The probability preferably is at least 50%, or at least 60%, or at least 70%, or at least 80%, or at least 90% or higher.
  • Inhibitors are used to refer to activating, inhibitory, or modulating molecules identified using in vitro and in vivo assays.
  • Inhibitors are compounds that, e.g., bind to, partially or totally block activity, decrease, prevent, delay activation, inactivate, desensitize, or down regulate the activity or expression of target molecules.
  • Activators are compounds that increase, open, activate, facilitate, enhance activation, sensitize, agonize, or up regulate activity of target molecules, e.g., agonists.
  • Inhibitors, activators, or modulators also include genetically modified versions of target molecules, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
  • Such assays for inhibitors and activators include, e.g., expressing target molecules in vitro, in cells, or cell extracts, applying putative modulator compounds, and then determining the functional effects on activity, as described above.
  • Samples or assays comprising target molecules that are treated with a potential activator, inhibitor, or modulator are compared to control samples without the inhibitor, activator, or modulator to examine the extent of inhibition.
  • Control samples (untreated with inhibitors) are assigned a relative protein activity value of 100%.
  • Inhibition of target molecules is achieved when the activity value relative to the control is about 80%, preferably 50%, more preferably 25-0%.
  • Activation of target molecules is achieved when the activity value relative to the control (untreated with activators) is 110%, more preferably 150%, more preferably 200-500% (i.e., two to five fold higher relative to the control), more preferably 1000-3000% higher.
  • test compound or “drug candidate” or “modulator” or grammatical equivalents as used herein describes any molecule, either naturally occurring or synthetic, e.g. antibody, protein, fusion protein, peptide (e.g., from about 5 to about 25 amino acids in length, preferably from about 10 to 20 or 12 to 18 amino acids in length, preferably 12, 15, or 18 amino acids in length), cyclic peptide, polynucleotide, oligonucleotide, antisense molecule, ribozyme, RNAi molecule, aptamer, sugar, polysaccharide, lipid, fatty acid, small organic molecule, small chemical compound, dendrimer, nanovesicle, microvesicle and the combination of any of these, etc., to be tested for the capacity to directly or indirectly modulate target molecules.
  • peptide e.g., from about 5 to about 25 amino acids in length, preferably from about 10 to 20 or 12 to 18 amino acids in length, preferably 12, 15, or 18 amino acids
  • the test compound can be in the form of a library of test compounds, such as a combinatorial or randomized library that provides a sufficient range of diversity.
  • Test compounds are optionally linked to a fusion partner, e.g., targeting compounds, rescue compounds, dimerization compounds, stabilizing compounds, addressable compounds, and other functional moieties.
  • a fusion partner e.g., targeting compounds, rescue compounds, dimerization compounds, stabilizing compounds, addressable compounds, and other functional moieties.
  • new chemical entities with useful properties are generated by identifying a test compound (called a "lead compound") with some desirable property or activity, e.g., inhibiting activity, creating variants of the lead compound, and evaluating the property and activity of those variant compounds.
  • HTS high throughput screening
  • a "small organic molecule” refers to an organic molecule, either naturally occurring or synthetic, that has a molecular weight of more than about 50 daltons and less than about 2500 daltons, preferably less than about 2000 daltons, preferably between about 100 to about 1000 daltons, more preferably between about 200 to about 500 daltons.
  • a variety of methods may be used to identify compounds that prevent or treat preeclampsia and closely related complications of pregnancy.
  • an assay that provides a readily measured parameter is adapted to be performed in the wells of multi-well plates in order to facilitate the screening of members of a library of test compounds as described herein.
  • an appropriate number of cells can be plated into the cells of a multi-well plate, and the effect of a test compound on the DNA methylation status, expression, level or activity of the target molecules can be determined.
  • the compounds to be tested can be any small chemical compound, or a macromolecule, such as a sugar, nucleic acid, protein or lipid.
  • test compounds will be small chemical molecules and peptides.
  • any chemical compound can be used as a test compound in this aspect of the invention, although most often compounds that can be dissolved in aqueous or organic (especially DMSO- based) solutions are used.
  • the assays are designed to screen large chemical libraries by automating the assay steps and providing compounds from any convenient source to assays, which are typically run in parallel (e.g., in microtiter formats on microtiter plates in robotic assays).
  • High throughput screening methods can be used which involve providing a combinatorial chemical or peptide library containing a large number of potential therapeutic compounds. Such “combinatorial chemical libraries” or “ligand libraries” are then screened in one or more assays, as described herein, to identify those library members (particular chemical species or subclasses) that display a desired characteristic activity. In this instance, such compounds are screened for their ability to reduce or increase the DNA methylation, expression, level or activity of the target molecules.
  • a combinatorial chemical library is a collection of diverse chemical compounds generated by either chemical synthesis or biological synthesis, by combining a number of chemical "building blocks” such as reagents.
  • a linear combinatorial chemical library such as a polypeptide library is formed by combining a set of chemical building blocks (amino acids) in every possible way for a given compound length (i.e., the number of amino acids in a polypeptide compound). Millions of chemical compounds can be synthesized through such combinatorial mixing of chemical building blocks.
  • combinatorial chemical libraries include, but are not limited to, peptide libraries (see, e.g., Houghton et al., Nature, 354:84-88 (1991), U.S. Pat. No. 5,010,175).
  • Other chemistries for generating chemical diversity libraries can also be used, which include, but are not limited to: peptoids (e.g., PCT Publication No. WO 91/19735), encoded peptides (e.g., PCT Publication No. WO 93/20242), random bio-oligomers (e.g., PCT Publication No.
  • each well of a microtiter plate can be used to run a separate assay against a selected potential modulator, or, if concentration or incubation time effects are to be observed, every 5-10 wells can test a single modulator.
  • a single standard microtiter plate can assay about 96 modulators. If 1536 well plates are used, then a single plate can easily assay from about 100- about 1500 different compounds. It is possible to assay many plates per day; assay screens for up to about 6,000, 20,000, 50,000, or 100,000 or more different compounds is possible using the integrated systems of the invention.
  • Example 1 Microarray study.
  • Preeclampsia was defined according to the criteria set by the American College of Obstetricians and Gynecologists (Blood pressure: 140 mm Hg or higher systolic or 90 mm Hg or higher diastolic after 20 weeks of gestation in a woman with previously normal blood pressure; proteinuria: 0.3 g or more of protein in a 24-hour urine collection (usually corresponds with 1+ or greater on a urine dipstick test).
  • Severe preeclampsia was defined according to Sibai et al., [Sibai, B et al. Pre-eclampsia. Lancet 2005;365:785-99].
  • Preterm controls had no medical complications, clinical or histological signs of chorioamnionitis, and delivered neonates with a birth weight appropriate-for-gestational age (AGA).
  • AGA birth weight appropriate-for-gestational age
  • probesets with intensity greater than log2 in at least two samples were assessed using a moderated t-test.
  • P-values were adjusted using the false discovery rate (FDR) method.
  • Target gene Entrez IDs for the probesets were determined using the R package "hgu4112a.db". For probesets without annotation in the package, Entrez IDs were taken from the array definition file (Agilent Technologies). Probesets remaining un-annotated (without Entrez ID and/or gene symbol) were removed from further analysis.
  • differential expression As used herein, “differential expression”, “significantly differentially expressed”, and similar terms generally mean that expression of a gene is significantly different based on a statistical power analysis, the results of which can be validated by qPCR at a 95% confidence interval.
  • WGCNA Weighted gene co-expression network analysis
  • Gene distance matrix was defined as 1-TOM, and used for average linkage hierarchical clustering.
  • a hybrid dynamic tree-cutting method was applied to obtain modules (tree clusters).
  • Gene modules identified with this approach were further tested for enrichment in PPE genes using a Fisher's exact test.
  • Preeclampsia was defined as hypertension that developed after 20 weeks (systolic or diastolic blood pressure >140 or >90 mmHg, respectively, measured at two different time points, 4h to 1 week apart) coupled with proteinuria (>300mg in a 24h urine collection or >2+ on a dipstick) according to the International Society for the Study of Hypertension in Pregnancy.
  • Preeclampsia was defined severe, if 1) severe hypertension (systolic or diastolic blood pressure >160 or >110 mmHg) was coupled with proteinuria; 2) if hypertension was coupled with severe proteinuria (>5g/24h or >3 on a dipstick), or 3) if maternal multi-organ involvement was present, such as pulmonary edema, oliguria, abnormal liver function, epigastric or right upper-quadrant pain, thrombocytopenia, or severe central nervous symptoms including seizures.
  • Small-for gestational age was defined as neonatal birth weight below the 10 th percentile for gestational age. Healthy controls had no medical or obstetric complications and delivered a neonate with a birth-weight appropriate for gestational age.
  • RT room temperature
  • Diastolic BP (mmHg) 60 (60-70) 100 (100-100) 67 (63-68) 100 (90-100)
  • Sera were immunodepleted at Biosystems International Ltd. (Debrecen, Hungary) for 14 highly abundant serum proteins on an Agilent 1100 HPLC system using Multiple Affinity Removal LC Column -Human 14 (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer's protocol.
  • Agilent 1100 HPLC system using Multiple Affinity Removal LC Column -Human 14 (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer's protocol.
  • immunodepleted serum samples were liophylized, and then delipidated and salt depleted at Proteome Services, Ltd. (Budapest, Hungary). Briefly, one volume of all samples was mixed with four volumes of methanol and was thoroughly vortexed.
  • IPG strips were loaded onto 10% polyacrylamide gels (24 ⁇ 20cm) and SDS-PAGE was conducted at 10W/gel in the second dimension. Then, gels were scanned in a Typhoon TRIO+ scanner (GE Healthcare) using appropriate lasers and filters with the PMT biased at 600V. Images in different channels were overlaid using selected colors and the differences were visualized using Image Quant software (GE Healthcare). Differential protein analysis was performed using the Differential In-gel Analysis (DIA) and Biological Variance (BVA) modules of the DeCyder 6.0 software package (GE Healthcare).
  • DIA Differential In-gel Analysis
  • BVA Biological Variance
  • the density of spots in the case of Colloidal Coomassie Blue labeling depends only the concentration of protein in the sample, however the density of spots in the case of saturation dyes labeling depends on the number of cysteines of the labeled proteins too, because the saturation dyes labeling method labels all available cysteines on each protein. This results in the same pattern with different density among samples on the analytical and the preparative gels rendering identification more difficult.
  • the preparative 2D electrophoresis was performed using CyDye saturation fluorescent labeling and Colloidal Coomassie Blue labeling in the same gel. A total of 800 g of proteins per each of the two gels ran.
  • the 10-10 immunodepleted serum samples in the "preterm” and “term” comparisons were pooled together and the salt-depletion step was repeated three-times.
  • Five g protein from each of these two pooled samples was labeled with Cy3, merged with 800 g of unlabeled proteins from the same sample and resolved in the dry-strip.
  • focused proteins were first reduced by equilibrating with a buffer containing 1% mercaptoethanol for 20min, and then alkylated with a buffer containing 2.5% iodoacetamide for 20min.
  • solvent B 0.1 % formic acid in acetonitrile.
  • Raw data files were converted into searchable peak list Mascot generic files (*.mgf) with the Mascot Distiller software v2.1.1.0. (Matrix Science, Inc, London, U K).
  • the resulting peak lists were searched against a human subdatabase of the non-redundant protein database of the National Center for Biotechnology Information (NCBInr 2008.07.18., Bethesda, MD, USA; 6,833,826 sequences) in MS/MS ion search mode on an in-house Mascot server v2.2.04 using Mascot Daemon software v2.2.2. (Matrix Science Inc).
  • Monoisotopic masses with peptide mass tolerance of ⁇ 50ppm and fragment mass tolerance of ⁇ 0.1 Da were submitted.
  • Carbamidomethylation of Cys was set as fixed modification, and acetylation of protein N-termini, methionine oxidation, and pyroglutamic acid formation from peptide N-terminal Gin residues were permitted as variable modifications. Acceptance criteria was set to at least two significant (peptide score>40, p ⁇ 0.05) individual peptides per protein.
  • the Fisher's exact test was used to test for the enrichment of the connections between differentially expressed serum proteins and 1) differentially expressed genes in individual modules, taking the connections between the proteins and differentially expressed genes in all modules as a background; and 2) differentially expressed placental genes, taking the connections between the proteins and all genes tested on the array as a background.
  • the Ingenuity Pathway Analysis software QIAGEN Redwood City, Redwood City, CA, USA was used.
  • Labor was defined by the presence of regular uterine contractions at a frequency of at least two contractions every 10 minutes with cervical changes resulting in delivery.
  • Preeclampsia was defined according to the criteria set by the American College of Obstetricians and Gynecologists. Severe preeclampsia was defined according to Sibai et al., see above. SGA was defined as neonatal birth-weight below the 10 th percentile for gestational age. C-section was performed in all preeclampsia cases due to severe symptoms and in controls due to previous C-section or Representation. Table 3
  • Washed and resuspended cells were layered over 20-50% Percoll gradients and centrifuged for 20min at 1 ,200g. Trophoblast containing bands were collected and non-trophoblastic cells were excluded by negative selection with anti-CD9 (20 g/ml) and anti-CD14 (20 g/ml) mouse monoclonal antibodies (R&D Systems, Minneapolis, MN, USA) and MACS anti-mouse IgG microbeads (Miltenyi Biotec, Auburn, CA, USA).
  • IMDM Iscove's modified Dulbecco's medium
  • FBS fetal bovine serum
  • P/S penicillin/streptomycin
  • BeWo cells (American Type Culture Collection, Manassas, VA, USA) were incubated in T-25 flasks or 6-well plates with F12 medium (Invitrogen) supplemented with 10% FBS and 1 % P/S in a humidified incubator (5%C0 2 , 20%O 2 ) at 37°C until reaching 50-80% confluence.
  • ARNT2 or BCL6 overexpression were transiently transfected with ARNT2, BCL6, or control (GFP) vectors. Briefly, 4 g expression plasmid (OriGene Technologies, Inc., Rockville, MD, USA) and 12 ⁇ FuGENE HD transfection reagent (Promega) were mixed with 180 ⁇ F12 medium (10% FBS, 1% P/S), incubated at RT for 15min and added to cell cultures with 1.8ml medium in each well of 6-well plates.
  • F12 medium % FBS, 1% P/S
  • HTR8/SVneo extravillous trophoblastic cells (kindly provided by Dr. Charles H. Graham, Queen's University, guitarist, Ontario, Canada) were incubated in 6-well plates with or RPMI-1640 medium (Gibco) supplemented with 10% FBS and 1 % P/S in a humidified incubator (5%C0 2 , 20%O 2 ) at 37°C until reaching 50% confluence.
  • Cells were collected for functional assays after 24h, while cells were collected for RNA isolation, microarray, qRT-PCR or confocal microscopy and their supernatants for ELISA after 48h. Cell culture supernatants were collected after Oh, 24h and 48h for proliferation assays.
  • ZNF554 5'UTRs using matrix and core similarity cut-offs of 0.9.
  • ZNF554 5'UTRs were either synthesized (GenScript, Piscataway, NJ, USA) or amplified from genomic DNA and inserted into a GLuc-ONTM promoter reporter vector (Genecopoeia, Rockville, MD, USA).
  • Reporter constructs were transfected into HTR8/SVneo cells using FuGENE HD reagent (Promega). Briefly, 4 g of reporter constructs and 12 ⁇ FuGENE HD reagent were mixed with 180 ⁇ RPMI-1640 medium (Gibco) supplemented with 10% FBS and 1% P/S, incubated at RT for 15min, and then added to the cells along with 1.8ml RPMI-1640 medium.
  • FuGENE HD reagent Promega.
  • RNA was isolated from snap-frozen placental villous tissues (n 100), primary trophoblast, Bewo and HTR8/SVneo cell cultures with TRIzol reagent (Invitrogen, Carlsbad, CA, USA) and RNeasy kit (QIAGEN, Valencia, CA, USA) according to the manufacturers' recommendations.
  • the 28S/18S ratios and the RNA integrity numbers were assessed using an Agilent Bioanalyzer 2100 (Agilent Technologies), RNA concentrations were measured with NanoDrop1000 (Thermo Scientific).
  • RNA from BeWo and HTR8/SVneo cells 500ng was amplified and biotin-labeled with the lllumina TotalPrep RNA Amplification Kit (Ambion). Labeled cRNAs were hybridized to a HumanHT-12v4 Expression BeadChip (lllumina, Inc., San Diego, CA). BeadChips were imaged using a BeadArray Reader (lllumina, Inc.), and raw data were obtained with BeadStudio Software V.3.4.0 (lllumina, Inc.).
  • RNA 500ng was also reverse transcribed with High Capacity cDNA Reverse Transcription Kit using random hexamers (Applied Biosystems, Foster City, CA, USA).
  • TaqMan Assays (Applied Biosystems) were used for high-throughput gene expression profiling on the Biomark qRT-PCR system (Fluidigm, San Francisco, CA, USA) according to the manufacturers' instructions.
  • TaqMan assays (Applied Biosystems) for ZNF554 and RPLP0 were run in triplicate for expression profiling of the Human Major Tissue qPCR Array (OriGene Technologies, Inc.) that contains cDNAs from 48 different pooled tissues.
  • Cells were mounted with ProLong Gold antifade reagent and 4',6-diamidino-2-phenylindole (DAPI; Invitrogen), followed by confocal microscopy using a Leica TCS SP5 MP spectral confocal system (Leica Microsystems).
  • DAPI 4',6-diamidino-2-phenylindole
  • HTR8/SVneo cells The migratory capacity of HTR8/SVneo cells was examined with 8pm-pore transwell inserts (Corning, NY, USA) inserted in 12-well plates similar to described previously. After transfection with ZNF554 or scrambled siRNAs for 24h, 5x10 5 HTR8/SVneo cells were plated in the upper chambers in a serum-free RPMI-1640 medium, whereas the lower chambers contained a RPMI-1640 medium supplemented with 10% FBS.
  • Genomic DNA was isolated from primary trophoblasts, umbilical cord blood leukocytes and laser captured villous trophoblasts with the EZ1 Advanced Nucleic Acid Isolation System using EZ1 DNA Tissue and EZ1 DNA Blood Kits (QIAGEN), and quantified with Quantifiler Human DNA Quantification Kit (Applied Biosystems).
  • Primer design and validation [000219] Whole genome shotgun bisulfite sequencing data and MEDIP-Seq data (University of California, San Diego; University of California, San Francisco; Human Reference Epigenome Mapping Project) were visualized by the Epigenome Browser (www.epigenomebrowser.org) and used for the selection of regions of interest. Primer design, targeted amplification and sequencing were done as targeted sequencing service of Zymo Research Corporation (Irvine, CA, USA). For targeted bisulfite sequencing 68 primer pairs were designed and validated. Primers were synthesized by Integrated DNA Technologies, Inc.
  • QC quality control
  • Genomic DNA samples from laser captured villous trophoblasts, primary trophoblasts, and umbilical cord blood cells as well as control samples were subjected to sodium bisulfite treatment using the EZ DNA Methylation-Direct Kit (Zymo Research Corp.).
  • human DNA was extracted and purified with Quick-gDNA Miniprep Kit (Zymo Research Corp., Irvine, CA, USA) from the HCT116 cell line, which is double knock-out for both DNA methyltransferases DNMT1 (-/-) and DNMT3b (-/-), and thus, contains low level ( ⁇ 5%) of DNA methylation.
  • human DNA was purified similarly from the HCT116 cell line and was enzymatically methylated at all cytosine positions comprising CG dinucleotides by CpG Methylase (Zymo Research Corp.).
  • the number of mismatches in the induced alignment was then counted between the unconverted read and reference, ignoring cases in which a T in the unconverted read was matched to a C in the unconverted reference. For a given read, only the best scored alignment was kept. If there were more than one best read, then only one of them was kept arbitrarily.
  • the methylation level of each sampled cytosine was estimated as the number of reads reporting a C, divided by the total number of reads reporting a C or T. CpGs with coverage of less than four reads were removed from the analysis.
  • the developed sensitive and robust bisulfite sequencing assays yielded a median total sequencing read of 533 (range: 30-1725) per CpG in the trophoblast-fetal blood cell comparison and a median total sequencing read of 136 (range: 4-2609) per CpG in the clinical sample comparison.
  • Placental microarray Enrichment analysis of repeat elements present in the 10,000bp upstream region of differentially expressed genes was performed separately for each gene module in preeclampsia versus all genes present on the microarray using the Fisher's exact test. The locations of repeat elements, families and classes were obtained from the "RepeatMasker" table of the UCSC Table Browser (http://genome.ucsc.edu ). P-values of ⁇ 0.05 were considered significant.
  • Placental qRT-PCR Data were analyzed using the AACt method. The data were first normalized to the reference gene (RPLPO), and the batch effect was adjusted through calibrator samples. Log2 mRNA relative concentrations were obtained for each sample as - The surrogate gene expression values (-ACtgene) were used to perform a hierarchical clustering with 1-Pearson correlation distance and average linkage. Between group comparisons (in which groups were predefined based on the clinical characteristics of the patients) were performed by fitting a linear model on -ACt values, using as covariates the group variable indicator while allowing for an interaction between the group variable and the maturity status of the fetus (term vs. preterm).
  • Tissue qRT-PCR array The expression of ZNF554 relative to RPLPO in the placenta was compared to 47 other human tissues using the Student's t-test. P-values of ⁇ 0.05 were considered significant.
  • BeWo and HTR8/SVneo cell microarray Data were analyzed using the Bioconductor packages in R following methodologies described previously. Raw microarray gene expression data was normalized by a quantile normalization approach. A moderated t-test was used to select differentially expressed genes using a cutoff of >1.5 fold-change and ⁇ 0.1 false discovery rate (FDR). Gene ontology analysis and pathway analysis on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was also performed.
  • KEGG Kyoto Encyclopedia of Genes and Genomes
  • BeWo cell qRT-PCR Data were analyzed to compare the effect of ARNT2 or BCL6 overexpression with the effect of control vector overexpression on gene expression in normoxic conditions using a one-way ANOVA model. The same model was used to access the differential effect of ARNT2, BCL6 or GFP overexpression on gene expression in hypoxic or ischemic conditions vs. normoxia. P-values of ⁇ 0.05 were considered significant. A permutation test was used to measure the statistical significance of the matching between differential gene expression patterns in in vitro and in vivo conditions. Genes were discretized into three states, i.e. up-regulated (UP), down-regulated (DN) or unchanged (NS).
  • UP up-regulated
  • DN down-regulated
  • NS unchanged
  • a score of 1 was assigned for a perfect match of UP/UP or DN/DN, 0 for a neutral match of NS/NS, -1 for a perfect mismatch of UP/DN or DN/UP, and -0.5 for all other patterns.
  • the matching score for any pair of conditions was computed as the sum of all scores for each individual gene. The significance of the scores was assessed via a permutation test. Permutations were exhaustive when feasible, limited to a random sample of 5000 otherwise. The Student's t-test was used to evaluate ZNF554 knock-down efficiency, and the effect of ZNF554 knock-down on gene expression in BeWo cells.
  • HTR8/SVneo cell qRT-PCR, immunoassay, cell proliferation, migration and invasion qRT-PCR data were analyzed using the AACt method relative to RPLPO expression.
  • the Student's t-test was used to evaluate ZNF554 knock-down efficiency in HTR8/SVneo cells, and the effect of ZNF554 knock-down on gene expression and cell proliferation.
  • a linear model was built to quantify the effects of ZNF554 knock-down and various O2 concentrations on the gene expression and protein secretion of HTR8/SVneo cells, as well as their migratory and invasive capacity. O2 concentration was treated as a continuous variable, and the interaction between ZNF554 knock-down and O2 concentrations were included in the model when determined to be significant according to ANOVA. P-values of ⁇ 0.05 were considered significant.
  • Luciferase assays When analyzing the effect of O2 concentration or ZEB1 overexpression on ZNF554 5'UTR activities, relative luciferase activities were computed normalizing to the GAPDH promoter and presented as relative fold-changes. The Students t-test and ANOVA F-test were used to evaluate statistical significance. A linear model was built to analyze the difference in GAPDH normalized luciferase activities in response to ZEB1 overexpression compared to GFP overexpression among various ZNF554 promoters at different O2 concentrations. P-values of ⁇ 0.05 were considered significant.
  • Microarray data analyses revealed transcription factors with high co-expression with predominantly placental expressed genes differentially expressed in the placenta. Transcription factors that were expressed at high levels (average log2 intensity >9) and co-expressed (absolute Pearson coefficient >0.8) with the most genes among predominantly placental expressed genes (BCL6, VDR, BHLHE40, ARNT2, JUNB, BTG2, ESRRG, POU5F1 , ZNF554, HLF) were treated as candidates for hub-genes in the module.
  • BCL6, VDR, BHLHE40, ARNT2, JUNB and BTG2 transcription factor genes had their expression levels most correlated with FLT1 and predominantly placental expressed genes (e.g. LEP, CRH, SIGLEC6).
  • ESRRG Within the "green module" of differentially expressed genes in the placenta in preeclampsia (which is associated with low birth weight), ESRRG, POU5F1 , ZNF554, and HLF transcription factor genes had their expression level most correlated with predominantly placental expressed genes (e.g. PLAC1 , LGALS14, HSD17B1).
  • Figure 1A-B shows co-expression matrices of transcription regulatory genes and predominantly placenta expressed genes in the "red and green modules" in placental microarray data.
  • A Co-expression matrix shows that within the red module, BCL6, VDR, BHLHE40, ARNT2, JUNB and BTG2 transcription regulatory genes had their expression most correlated with FLT1 and predominantly placenta expressed genes. BCL6 and ARNT2 expression had the highest correlation with that of FLT1.
  • B Co-expression matrix shows that within the green module, ESRRG, POU5F1 , ZNF554, and HLF transcription regulatory genes had their expression most correlated with predominantly placenta expressed genes. ESRRG and ZNF554 expression had the highest correlation with that of CSH1 and HSD11 B2, genes strongly implicated in fetal growth.
  • FIG. 2A-B shows first trimester maternal serum proteomics changes in preterm preeclampsia.
  • A Venn diagram of proteomics data shows that the 19 differentially expressed maternal serum proteins in the first trimester in preterm preeclampsia belong to six functional groups, which are relevant for the pathophysiology of preeclampsia.
  • B These 19 serum proteins have connections with 121 differentially expressed placental genes in preeclampsia, among which 48 belong to the "red module” that is dysregulated in association with high blood pressure.
  • Figure 3A-B shows first trimester maternal serum proteomics changes in term preeclampsia.
  • A Venn diagram of proteomics data shows that the 14 differentially expressed maternal serum proteins in term preeclampsia belong to six functional groups, which are relevant for the pathophysiology of preeclampsia.
  • B These 14 serum proteins have connections with 116 differentially expressed placental genes in preeclampsia, among which 46 belong to the "red module” that is dysregulated in association with high blood pressure.
  • BeWo cells Because of the dynamically changing transcriptome of primary trophoblasts in culture and the difficulties in transfecting these cells, we used BeWo cells to test the effect of hypoxia or ischemia alone or in combination with the overexpression of transcription factors up- regulated in the placenta in preterm preeclampsia.
  • ARNT2 and BCL6 overexpression in normoxic BeWo cells or hypoxia itself induced the dysregulation of only five placental differentially expressed genes.
  • Ischemia induced the dysregulation of only three genes in BeWo cells similar to that in preeclampsia.
  • a permutation test showed that ARNT2 overexpression, both in hypoxia or ischemia, mimicked the up-regulation of red module genes in preeclampsia.
  • BCL6 overexpression in ischemia mimicked the overall expression changes of red and green module genes in preterm preeclampsia.
  • ARNT2 was up-regulated, probably mediating the up-regulation of red module genes.
  • Figure 4A-E shows in vitro modeling of the placental dysregulation of gene modules in preeclampsia.
  • A Hierarchical clustering of expression data for 47 genes in 100 placental specimens and a heatmap representing differential gene expression in term or preterm subgroups of preeclampsia compared to respective controls.
  • B Preterm preeclampsia serum induced the up-regulation of seven placental dysregulated genes in primary trophoblasts, among which six were up-regulated in term and three in preterm preeclampsia.
  • C The overexpression of ARNT2 or BCL6 in normoxic BeWo cells induced the dysregulation of five genes dysregulated in preeclampsia.
  • Figure 5 shows BCL6 expression in BeWo cells after various treatments with 5-azacitidin and Forskolin. Decreased BCL6 expression was observed in BeWo cells upon treatment with 5-azacitidin (5-AZA) irrespective of Forskolin (FRSK) co-treatment.
  • 5-azacitidin 5-AZA
  • FRSK Forskolin
  • Figure 6 summarizes the obtained data showing that serum factors and epigenetic changes modify BCL6 expression upstream of ARNT2, and the overexpression of these transcription factors leads to trophoblast sensitization to hypoxic/ischemic stress, and the consequent dysregulation of red and green modules, mostly in preterm preeclampsia.
  • LTR1 OA-fragments were found in the 10kb5'UTR of ZNF554, one of the hub-genes in the green module. Since LTR10A drives placenta-specific expression of NOS3, we hypothesized that ZNF554 may also have placenta-specific expression.
  • ZNF554 expression was up-regulated during villous trophoblast differentiation similar to CSH1.
  • FSTL3 The up-regulation of FSTL3 was confirmed by qRT-PCR (2.7-fold, p ⁇ 0.001).
  • FSTL3 encodes a secreted glycoprotein, which binds and inactivates activin and other TGF ligands, and it's up-regulation in the preeclamptic placenta is associated with low birth- weight.
  • Figure 7 shows tissue qRT-PCR array data that revealed the highest ZNF554 expression in the placenta among 48 human tissues.
  • Figure 8A-B shows ZNF554 expression in the placenta.
  • A In situ hybridization of a third trimester placenta (GW29) and
  • B immunohistochemistry of a first trimester placenta (GW12) shows mainly syncytiotrophoblastic ZNF554 expression (1400x and 400x magnifications).
  • Black or white arrowheads depict syncytiotrophoblast or cytotrophoblast, while black arrow depicts fetal endothelium, respectively.
  • Figure 9 shows qRT-PCR data depicting that ZNF554 expression is up-regulated during villous cytotrophoblast differentiation in parallel with CSH1.
  • Figure 10A-B shows ZNF554 expression in the placenta.
  • ZNF554 immunopositivity was faint in the syncytiotrophoblast in (B) preeclampsia (GW35) compared to (A) gestational-age matched controls (GW36).
  • Arrow and arrowhead depict syncytiotrophoblast and fetal endothelium, respectively (400x magnifications).
  • Figure 11A-E shows in vitro gene expression data of BeWo cells after ZNF554 knock-down.
  • B Nuclear and cytoplasmic ZNF554 immunofluorescence decreased in BeWo cells treated with ZNF554 siRNA compared to control cells.
  • C Bioinformatics analyses revealed the glycolysis / gluconeogenesis pathway, RNA, nucleic acid and activin binding to be affected in ZNF554 knock-down BeWo cells.
  • D qRT-PCR validated FSTL3 up-regulation (2.7-fold, p ⁇ 0.001) in BeWo cells upon ZNF554 knock-down.
  • Microarray analysis showed 185 differentially expressed genes including 18 differentially expressed placental genes in preeclampsia. Importantly, only 18 out of 185 genes were also dysregulated in ZNF554-silenced BeWo cells, suggesting that ZNF554 is involved in the regulation of different functions in villous and extravillous trophoblast.
  • Pathway analyses showed 16 molecular functions dysregulated, including 'cyclin-dependent protein kinase regulator activity', 'metalloendopeptidase inhibitor activity', and 'insulin-like growth factor binding'.
  • the 67 enriched biological processes included 'regulation of growth', 'smooth muscle cell migration', 'smooth muscle cell-matrix adhesion', 'response to oxygen levels', all relevant to trophoblast invasion and placental pathogenesis of preeclampsia.
  • TIMP-3 is the major tissue metalloproteinase inhibitor at the maternal-fetal interface, which is up-regulated in preeclampsia.
  • Figure 12A-B shows ZNF554 immunostainings in first and third trimester placentas.
  • A Extravillous trophoblasts in the trophoblastic columns (GW12) and
  • B endovascular and intraluminal trophoblasts in the myometrium (GW36) were immunostained for cytokeratin-7 (left) and ZNF554 (right).
  • Figure 13A-B shows that ZNF554 immunostainings in decidual extravillous trophoblasts (arrowheads) and syncytiotrophoblats (arrows) were weaker in (B) preeclampsia (GW35) than in (A) controls (GW36) (serial sections, 200x magnifications).
  • Figure 14 shows in vitro gene expression data of HTR8/SVneo cells after ZNF554 knock-down.
  • Figure 15 shows the effect of ZNF554 knock-down on cell proliferation in HTR8/SVneo cells.
  • Y-axis depicts viable cell number,
  • X-axis shows incubation time.
  • B The differential expression of CDKN1A and STK40 (genes involved in the regulation of cell cycle) upon ZNF554 knock-down was confirmed by qRT-PCR. Oxygen concentrations are shown below the bars.
  • Figure 16 shows the effect of ZNF554 knock-down on gene expression in HTR8/SVneo cells. The dysregulation of selected genes upon ZNF554 knock-down was confirmed by qRT-PCR. Oxygen concentrations are shown below the bars.
  • Figure 17 shows the effect of ZNF554 knock-down on protein secretion from HTR8/SVneo cells.
  • SERPINE PAI-1
  • TIMP3 TIMP3 from ZNF554 knock-down cells
  • Figure 18 shows the effect of ZNF554 knock-down on the migratory and invasive capacity of HTR8/SVneo cells. ZNF554 knock-down cells had remarkably decreased invasive (left) and migratory (right) characteristics. Oxygen concentrations are shown below the bars.
  • AluY and LTR10A contains a large number of predicted ZEB1 binding sites and hypoxia response elements (HREs), suggesting that human ZNF554 is regulated by hypoxia and ZEB1 , a TF involved in epithelial-mesenchymal transition and invasion of the trophoblast.
  • HREs hypoxia response elements
  • ZNF554 5'UTR activity (Fig. 6b). Although the change in O2 levels itself did not affect luciferase activity, hypoxia compared to 8%02 increased it (+25%, p ⁇ 0.01) when ZEB1 was overexpressed, suggesting ZEB1-HIFa interaction in human ZNF554 regulation.
  • Figure 19A-D shows the evolutionary origins of deep trophoblast invasion in humans.
  • the ⁇ 3kb human ZNF554 5'UTR black line
  • HREs hypoxia-response elements
  • GFP co-transfection there were higher luciferase activity ratios of the human than the macaque (22%, p ⁇ 0.01) or orangutan (25%, p ⁇ 0.01) 5'UTRs at 8%02.
  • the macaque 5'UTR activity ratio did not differ between hypoxia and 8%02, the orangutan 5'UTR activity ratio was higher in hypoxia than in 8%02 (+28%, p ⁇ 0.01), and the human 5'UTR activity ratio was the highest in hypoxia (+60% vs. macaque, p ⁇ 0.00001; +22% vs. orangutan, p ⁇ 0.01).
  • these genes (ARNT2, BCL3, BCL6, BTG2, CDKN1A, CGB3, CLC, CSH1 , CYP19A1 , DUSP1 , ENG, ERVFRDE1 , ERVWE1 , ESRRG, FLT1, GATA2, GCM1 , GH2, HSD11 B2, HSD17B1 , IKBKB, INSL4, JUNB, LEP, LGALS13, LGALS14, LGALS16, MAPK13, PAPPA2, PGF, PLAC1 , SIGLEC6, TFAM, TFAP2A, TPBG, VDR, ZNF554) were identified as potential epigenetic biomarker candidates.
  • DMRs included chr19:40093255-chr19:40093612, chr19:40094910-chr19:40094949 and chr19:40095758-chr19:40095887 (LGALS13); chr19:40193506-chr19:40193558, chr19:40194326-chr19:40194732 and chr19 :40199590-chr19 :40199946 (LGALS14); chr19:40148945- chr19:40149035 and chr19:40150504-chr19:40151073 (LGALS16).
  • the chr19:2818789-chr19:2818880 region was differentially methulated between cytotrophoblast and syncytiotrophoblast.
  • Figure 20 shows the origins of impaired trophoblast invasion and preeclampsia.
  • the methylation of certain CpGs at two HREs in AluY in the trophoblast inhibits the mechanisms of deep trophoblast invasion, and promotes the development of preeclampsia.
  • Figure 21 shows gene expression changes in BeWo cells upon 5-azacitidin treatment and Forskolin co-treatment. There were 37 genes that had differential expression upon treatment with 5-azacitidin (5-AZA), with or without Forskolin (FRSK) co-treatment, suggesting their regulation by DNA methylation in the trophoblast.
  • 5-azacitidin 5-AZA
  • FRSK Forskolin
  • Figure 22 Figure 22. summarizes the identified epigenetic biomarker genes and biomarker candidate regions for preeclampsia and closely related complications of pregnancy.
  • the listed 37 genes had differential methylation and consequent differential expression upon 5-azacitidin treatment in BeWo cells. Five out of these 37 genes were further characterized for differential methylation in primary trophoblasts, cord blood cells, and laser captured trophoblasts. The genomic regions with differential methylation in the three comparisons are shown in the figure and treated as biomarker candidates.
  • differentially expressed maternal serum proteins with the most connections with differentially expressed genes in the placenta, as well as differentially expressed serum proteins with functions most relevant to the pathogenesis of preeclampsia were identified key therapeutic targets, since they are located in pathways or upstream of pathways important in the pathogenesis of preeclampsia.
  • the inhibition or activation of their differential expression or function can be the basis of preventive or therapeutic approaches.
  • Figure 23 summarizes the potential therapeutic target molecules identified by the proteomics study, their observed mechanism of dysregulation in preeclampsia, and the required effect of the therapeutics.
  • Figure 24 summarizes the potential therapeutic target molecules identified by the transcriptomics study, their observed mechanism of dysregulation in preeclampsia, and the required effect of the therapeutics.
  • Preeclampsia has various etiologies and phenotypes, and the lack of insights into the molecular mechanisms of the origins of this complex syndrome has prevented the development of early diagnostic, preventive and therapeutic tools.
  • Our systems biology study identified and modeled early molecular pathways leading to the hallmark pathologies of preeclampsia, and paved the way for its molecular taxonomy.
  • Figure 25 describes pathologic pathways in preeclampsia.
  • characteristic alterations in the maternal proteome can be observed, supporting that the activation of the complement and renin-angiotensin systems as well as maternal metabolic pathways have key role in triggering early pathologic events.
  • These alterations in maternal blood can induce trophoblastic functional changes leading to the overproduction of sFlt-1 and an anti-angiogenic state through a trajectory that does not necessarily affect fetal growth.
  • ZNF554 The "ZNF554" pathway have evolved in great apes to support deep trophoblast invasion, and the epigenetic dysregulation of this pathway is a key component in impaired trophoblast invasion in preeclampsia.
  • the red gene module associated with blood pressure elevation is not only up-regulated by alterations in maternal blood proteome but also by the overproduction of BCL6 and ARNT2 due to epigenetic background.
  • the up-regulation of this "BCL6-ARNT2 pathway” sensitizes the trophoblast to ischemia, and increases FLT1 and decreases PIGF expression. These changes are only observed in the placenta in preterm preeclampsia, suggesting that the dysregulation of this pathway promotes the earlier development of the preclinical phase of preeclampsia in conjunction with the placental release of pro-inflammatory molecules and trophoblastic debris.
  • the interplay of these distinct pathomechanisms lead to the complex and "personalized" pathogenesis of preeclampsia.

Abstract

Disclosed are specific biomarkers and therapeutic targets that allow for early testing and treatment of preeclampsia and closely related complications of pregnancy. Thus methods are provided for predicting, diagnosing, treating, and following-up preeclampsia and closely related complications of pregnancy in a pregnant woman. Also disclosed are diagnostic kits comprising means for assaying a sample from a pregnant woman for specific biomarkers.

Description

DIAGNOSTIC AND THERAPEUTIC TARGETS FOR PREECLAMPSIA AND CLOSELY RELATED COMPLICATIONS OF PREGNANCY
FIELD OF THE DISCLOSURE
[0001] The present disclosure provides biomarkers and methods which can be used to predict and/or detect preeclampsia in pregnant women. More specifically, the DNA methylation of genes listed in the disclosure can be used as biomarkers for the early prediction and/or detection and/or clinical follow-up of preeclampsia. These biomarkers and methods may also allow early prediction, detection and/or clinical follow-up of complications of pregnancy closely related to preeclampsia wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
[0002] The present disclosure also provides molecular drug targets and/or candidate therapeutic molecules and methods to prevent or treat preeclampsia and related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
BACKGROUND OF THE DISCLOSURE
[0003] Preeclampsia is a syndrome defined by pregnancy-induced hypertension and proteinuria, which can lead to eclampsia (convulsions), and other serious maternal and/or fetal complications. Preeclampsia is originated in early gestation from the failure of implantation mechanisms and/or placental development, and is thus closely related to complications of pregnancy in early gestation such as including but not limited to implantation failure, and threatened and spontaneous miscarriage, Preeclampsia affects approximately 5-7% of pregnant women (approximately 8,370,000 pregnant women worldwide per year) and is a major cause of maternal and perinatal mortality. Furthermore, women with preeclampsia have an 8-fold higher risk of cardiovascular death later in their life, and offspring born from pregnancies affected by preeclampsia have an increased risk of metabolic and cardiovascular disease and mortality later in life.
[0004] The present diagnostic criteria for preeclampsia set by the United States National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy include new-onset hypertension coupled with proteinuria that develops after 20 weeks of gestation in women with previously normal blood pressures. These criteria further define preeclampsia as systolic or diastolic blood pressures of >140 and/or >90 mmHg, respectively, measured at two or more different time points, at least 4 hours (h) but not more than 1 week apart, as well as proteinuria of >300 mg protein in a 24 h urine sample, or two random urine specimens obtained at least 4 h but not more than 1 week apart containing≥1+ protein on a dipstick.
[0005] Based on the timing of the clinical manifestation, preeclampsia has been historically classified into different sub-forms, such as "term" (>37 weeks) and "preterm" (<37 weeks) or by using an alternative terminology "late-onset" and "early-onset" preeclampsia. The latter classification has not been uniformly used, but different studies have employed a range of gestational age cutoffs varying between 28 and 35 weeks for the distinction between early-onset and late-onset preeclampsia. Recently, it has been suggested to define 34 weeks as the gestational age cutoff between these two forms. It is important to note that preeclampsia may occur intrapartum or postpartum; thus, monitoring and evaluating the symptoms of preeclampsia should be continued during the postpartum period.
[0006] In 1954, it was first reported that preeclampsia may be associated with haemolysis, abnormal liver function and thrombocytopenia. Initially accepted to be a severe variant of preeclampsia, this group of symptoms later was suggested to constitute a separate clinical entity termed Haemolysis, Elevated Liver enzymes and Low Platelets (HELLP) syndrome. Supporting the idea that HELLP syndrome is a distinct condition, up to 20% of HELLP syndrome patients do not develop hypertension, 5-15% have minimal or no proteinuria and 15% show neither hypertension nor proteinuria. Moreover, laboratory findings in HELLP syndrome rarely correlate with the severity of hypertension or proteinuria.
[0007] In addition to the medical complications suffered by mothers and risks to the offspring, preeclampsia and HELLP syndrome cause approximately $7 billion in healthcare costs in the United States annually. Accordingly, there have been many attempts to provide a reliable predictive test for preeclampsia/HELLP syndrome. Previous attempts have involved assays for the concentrations of circulating biochemical markers in maternal blood but to date, the scientific literature on these approaches have been contradictory and inconclusive. There is a need in the art for new and improved methods of predicting and diagnosing these conditions.
[0008] In 85% of cases the symptoms and laboratory findings characteristic for preeclampsia and HELLP syndrome are both present. In addition, placental histopathological changes consistent with maternal vascular underperfusion are present both in preeclampsia and HELLP syndrome, and the placental transcriptomic changes in preeclampsia and HELLP syndrome largely overlap. These findings are important in demonstrating the shared placental pathologies of the two syndromes.
[0009] In this context it is important that preeclampsia is a multi-stage disease with placental origins in early pregnancy. Compared to normal human pregnancy where extravillous trophoblasts deeply invade uterine tissues and remodel the decidual and myometrial segments of maternal spiral arteries to provide a continuous and increased blood supply for the developing fetus, this process is impaired in the first stage of preeclampsia in most cases. Of importance, trophoblast invasion is the deepest among all species in humans, and preeclampsia occurs in humans and great apes with deep trophoblast invasion, supporting an evolutionary link between deep trophoblast invasion, its failure and preeclampsia. In the second stage, especially in early-onset disease, the consequent ischemia of the placenta with the release of harmful placental substances (e.g. anti-angiogenic proteins, cytokines, syncytiotrophoblast debris) follows. Finally, an exaggerated systemic maternal inflammatory condition occurs, which may be coupled with severe damage to the maternal endothelium and kidneys, liver, and the central nervous system in the clinical stage. Although the pathophysiologic events in these finals stages of preeclampsia are relatively well uncovered, the pathologic pathways in the origins of preeclampsia are still obscure.
[00010] Of importance, the defects of extravillous trophoblast invasion and deep placentation have also been observed in other complications of pregnancy including preterm premature rupture of the membranes, intrauterine growth restriction, intrauterine fetal demise, spontaneous miscarriages, and placental abruption. Based on the histopathological evaluations of placental bed biopsies it was suggested that defects in deep placentation can be classified into three types. In preterm premature rupture of the membranes and intrauterine growth restriction, the defects in trophoblast invasion and deep placentation are only partial. In preeclampsia, there is a complete impairment of trophoblast invasion and spiral artery transformation. In preeclampsia associated with intrauterine growth restriction and intrauterine fetal demise, the complete defects in trophoblast invasion are often associated with obstructive lesions in the spiral arteries. As a consequence, this spectrum of trophoblastic invasion problems has various downstream molecular pathways and clinical outcomes.
[00011] For example, a partial impairment in deep placentation leads to placental endoplasmic reticulum stress and intrauterine growth restriction, while a more severe, complete impairment in trophoblast invasion promotes placental oxidative stress superimposed on endoplasmic reticulum stress, leading to the release of toxins and the development of the maternal syndrome in preeclampsia. The very early and severe manifestation of impaired trophoblast invasion will lead to the premature onset of maternal circulation in the placenta, a strong oxidative stress of the placenta, the regression of the trophoblast, and ultimately the termination of pregnancy in the first trimester. This is of major importance, since 70% of pregnancies fail in the first trimester, and in two thirds of these miscarriages anatomical evidence shows defective placentation characterized by impaired trophoblast invasion into uterine spiral arteries.
[00012] Distinct studies revealed certain genetic predispositions or risk factors for preeclampsia. Since factors that increase the risk for preeclampsia are also associated with abnormal implantation, it is suggested that the impairment of the same molecular pathways in the trophoblast may lead to a spectrum of complications of pregnancy from implantation failure to preeclampsia (e.g. HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, and threatened and spontaneous miscarriage), and the clinical phenotypes and outcomes are dependent on the extent and timing of the placental injury, maternal and fetal genetic and epigenetic makeup, as well as environmental factors.
[00013] Unfortunately, the placental pathologic pathways of obstetrical syndromes including preeclampsia in early pregnancy still have not been possible to identify because of the limitations in sample collection and the complexity of the pathologies. In spite of the large research efforts in the past to develop and validate biomarkers for the early prediction and detection of preeclampsia, as well as to utilize novel drugs for the prevention or treatment of preeclampsia, these attempts have not yielded satisfactory results. A possible reason for this is that the early diagnosis and treatment of a syndrome with a heterogeneous molecular background cannot be solved with the utilization of only one or two biomarker molecules and drugs with non-specific effects. As a consequence, preeclampsia is still an enigmatic disease with no early diagnosis and with the only definitive therapy of the delivery of the fetus and the placenta.
[00014] Therefore, there is a huge need for the identification of molecular disease pathways in early pregnancy in preeclampsia and in other complications of pregnancy. Also, the development of multiplex biomarkers that would enable the early and molecular signature-based diagnosis and prediction of these complications of pregnancy, as well as the development of drugs with specific effects on the pathologic pathways would be of major societal and economic importance.
SUMMARY OF THE DISCLOSURE
[00015] Our multidisciplinary, first trimester maternal blood proteomics and placental transcnptomics study has recently led to the discovery of a biomarker panel, which is assembled from the best protein and RNA biomarkers identified in the placenta and maternal serum. These biomarkers are repeatedly detectable in 7-9th weeks of gestation and may enable the earliest and most sensitive prediction and clinical follow-up of patients with preeclampsia, as well as the molecular distinction of various subtypes of preeclampsia (PCT/US13/45709).
[00016] Although the present disclosure is built on some elements included in PCT/US13/45709, it contains several unique novel features that offer a multiplexed, DNA methylation-based diagnostic and prognostic tool and also therapeutic targets for preeclampsia and complications of pregnancy closely related to preeclampsia wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage before symptoms manifest in the female and/or fetus.
[00017] The aim of the present disclosure was achieved by the inclusion of a systems biological approach for the analysis of data obtained from various high-dimensional biology techniques: 1) whole-genome transcnptomics of the human placenta; 2) high-throughput qRT-PCR expressional profiling of the human placenta; 3) whole-genome transcnptomics and high-throughput qRT-PCR expressional profiling of human trophoblastic cells after in vitro experiments, and their investigation with functional assays; 4) multiplexed bisulfite next generation sequencing of human trophoblastic and non-trophoblastic DNA specimens; and 6) 2D-DIGE proteomics of first trimester human maternal sera.
[00018] Systems biology analyses of whole-genome transcnptomics study of 17 placentas from women with preeclampsia and gestational age-matched controls identified a set of transcription factor genes differentially expressed in the placenta in preeclampsia, which are in central position in differentially expressed placental gene modules. Therefore, these are important diagnostic and therapeutic target genes.
[00019] As described in PCT/US 13/45709, high-throughput qRT-PCR expressional profiling as well as tissue microarray and immunohistochemistry of 100 placentas validated differential gene expression on the microarray.
[00020] Systems biology analysis of whole-genome transcnptomics and qRT-PCR studies of trophoblastic cells after in vitro experiments validated molecular pathways disturbed in the placenta in preeclampsia, identified placental biomarker genes regulated by DNA methylation, and identified target genes for novel types of targeted therapies.
[00021] Multiplexed bisulfite next generation sequencing assays identified potential diagnostic and prognostic biomarkers in the human epigenome that show differential DNA methylation in human trophoblasts versus non-trophoblastic cells as well as in human trophoblasts from patients diagnosed with preeclampsia versus controls.
[00022] Systems biology analysis of whole-genome transcriptomics study of 17 placentas and 2D-DIGE proteomics study of 20 first trimester maternal sera identified a set of maternal serum proteins that have important role in the dysregulation of placental gene modules in preeclampsia.
[00023] In summary, the present disclosure provides biomarkers and methods which can be used to predict and/or detect preeclampsia in pregnant women. More specifically, the DNA methylation status of genes listed in the disclosure can be used as biomarkers for the early prediction, diagnosis, risk assessment and/or clinical follow-up of preeclampsia. Because of the overlapping placental pathologies in early pregnancy, these biomarkers and methods may also allow the early prediction, detection and/or clinical follow-up of complications of pregnancy closely related to preeclampsia wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage.
[00024] As summarized in Figure 25, the present disclosure is the first to provide the definition for the "molecular phase" of preeclampsia, and to identify the early mechanisms of preeclampsia by defining new pathways of disease. The dysregulation of these pathways, i.e. the "ZNF554 pathway" and the "BCL6-ARNT2 pathway", is central to the early pathology of preeclampsia. Besides defining new pathologic pathways in the origins of preeclampsia, the present disclosure provides with key molecules that are central to these disease pathways. As key molecules in the newly described disease pathways, the disclosure provides molecular drug targets and/or candidate therapeutic molecules and methods to prevent or treat preeclampsia and related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage. The identification of these pathways and key molecular targets enable the molecular phenotyping and personalized drug treatment before the clinical phase of the disease.
[00025] One embodiment includes a method for assessing the presence or risk of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in a female to determine the need for a treatment regimen comprising: determining DNA methylation status of one or more of ARNT2; BCL3; BCL6; BTG2; CDKN1A; CGB3; CLC; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1; ESRRG; FLT1 ; GATA2; GCM1 ; GH2; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; LEP; LGALS13; LGALS14; LGALS16; MAPK13; PAPPA2; PGF; PLAC1 ; SIGLEC6; TFAM; TFAP2A; TPBG; VDR; or ZNF554 in a biological sample obtained from the female; generating a dataset based on the determined DNA methylation status; assessing the presence or risk of developing preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in the female based on the dataset; and determining a treatment regimen based on the assessed presence or risk.
[00026] In another embodiment, the assaying is performed for the DNA methylation status of all markers described above.
[00027] In another embodiment, the assaying is performed for the DNA methylation status of at least three biomarkers.
[00028] In another embodiment, the assaying is performed for DNA methylation status of at least one marker described in the figures and examples described herein.
[00029] In another embodiment, the sample is a blood sample.
[00030] In another embodiment the sample is other body fluid, secretion or excretion (such as but not limited to cervicovaginal fluid, saliva, or urine) sample. [00031] In another embodiment the sample is an amniotic fluid sample.
[00032] In another embodiment the sample is fetal cells obtained invasively or non-invasively.
[00033] In another embodiment the sample is sperm or cells obtained from the embryo.
[00034] In another embodiment, the sample is a placental sample.
th th
[00035] In another embodiment, the biological sample is obtained before the 20 week of pregnancy, before the 19 week of pregnancy,
th th th th
before the 18 week of pregnancy, before the 17 week of pregnancy, before the 16 week of pregnancy, before the 15 week of pregnancy,
th th th th
before the 14 week of pregnancy, before the 13 week of pregnancy, before the 12 week of pregnancy, before the 11 week of pregnancy,
th th th th
before the 10 week of pregnancy, before the 9 week of pregnancy, before the 8 week of pregnancy, before the 7 week of pregnancy, th
before the 6 week of pregnancy, or after delivery.
[00036] In another embodiment, the treatment regimen is a therapeutic intervention.
[00037] In another embodiment, the therapeutic intervention prevents or reduces symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage before symptoms manifest in the female and/or fetus.
[00038] Another embodiment includes a kit for assessing the presence or risk of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in a female to determine the need for a treatment regimen comprising: detection mechanisms for determining DNA methylation status of one or more of ARNT2; BCL3; BCL6; BTG2; CDKN1A; CGB3; CLC; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FLT1; GATA2; GCM1; GH2; HSD11 B2; HSD17B1 ; I KBKB; INSL4; JUNB; LEP; LGALS13; LGALS14; LGALS16; MAPK13; PAPPA2; PGF; PLAC1 ; SIGLEC6; TFAM; TFAP2A; TPBG; VDR; or ZNF554 in a biological sample obtained from the female; instructions how to (i) generate a dataset based on the determined DNA methylation status; (ii) assess the presence or risk of developing preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in the female based on the dataset; and (iii) determine a treatment regimen based on the assessed presence or risk.
[00039] In another embodiment, the kit includes detection mechanisms for all markers described above.
[00040] In another embodiment, the kit includes detection mechanisms for at least three markers.
[00041] In another embodiment, the methods and kits measure levels of at least one marker described in the figures and examples described herein.
[00042] In another embodiment, the methods include evaluating DNA methylation status, expression, level or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1; I KBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC; in a sample from a subject having preeclampsia or closely related complication of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage before administering the treatment to the subject, to provide a baseline level for the subject.
[00043] In a preferred embodiment, the said methods include evaluating DNA methylation status, expression, level or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG in a sample from a subject having preeclampsia or closely related complication of pregnancy before administering the treatment to the subject, to provide a baseline level for the subject.
[00044] In a preferred embodiment, the said methods include evaluating DNA methylation status, expression, level or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16 in a sample from a subject having preeclampsia or closely related complication of pregnancy before administering the treatment to the subject, to provide a baseline level for the subject.
[00045] In a more preferred embodiment, the said methods include evaluating DNA methylation status, expression, level or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 in a sample from a subject having preeclampsia or closely related complication of pregnancy before administering the treatment to the subject, to provide a baseline level for the subject.
[00046] In another embodiment the invention provides therapeutic methods that prevent or reduce the symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising: the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; I KBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC.
[00047] In a preferred embodiment the said therapeutic methods comprise the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG.
[00048] In a preferred embodiment the said therapeutic methods comprise the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS 14; or LGALS16.
[00049] In a more preferred embodiment the said therapeutic methods comprise the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of AGT; ZNF554; BCL6; or ARNT2.
[00050] In another embodiment, the invention provides methods of evaluating an effect of a treatment for preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage. The methods include administering a treatment to the subject; evaluating DNA methylation status, expression, level or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; AP0A4; AP0L1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC in a sample from the subject after administration of the treatment; and optionally comparing the DNA methylation status, expression, level or activity of these molecules in the sample to a reference value, e.g., a baseline level for the subject. Wherein if the DNA methylation status, expression, level or activity of these molecules in the sample has a predetermined relationship to the reference value, e.g., is less than the value, the treatment has a positive effect on the disease in the subject.
[00051] In a preferred embodiment, the said methods of evaluating an effect of a treatment include evaluating DNA methylation status, expression, level or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG in a sample from the subject after administration of the treatment.
[00052] In a preferred embodiment, the said methods of evaluating an effect of a treatment include administering a treatment to the subject; evaluating DNA methylation status, expression, level or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16 in a sample from the subject after administration of the treatment.
[00053] In a more preferred embodiment, the said methods of evaluating an effect of a treatment include administering a treatment to the subject; evaluating DNA methylation status, expression, level or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 in a sample from the subject after administration of the treatment.
[00054] In another embodiment, the methods include assigning a value to said subject for the effectiveness of the treatment. In some embodiments, the methods further include providing a record of that value, e. g., to the subject or to a health care provider. In some embodiments, the methods further include determining whether to continue to administer the treatment to the subject, or whether to administer the treatment to another subject.
[00055] In another embodiment, the invention also provides methods for identifying candidate therapeutic agents for the treatment of preeclampsia and closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage. The methods include providing a model of the disease, e.g., a non-human experimental animal model; contacting the model with a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; LGALS 17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC identified by a method described herein; and evaluating the effect of the candidate compound on the model. For example, a positive effect on the model, e.g., an improvement in a symptom of an animal model, modification of the DNA methylation status, expression, level, or activity of the target molecules, indicates that the candidate compound is a candidate therapeutic agent for the treatment of preeclampsia or closely related complication of pregnancy.
[00056] In a preferred embodiment, the said methods for identifying candidate therapeutic agents include providing a model of the disease, e.g., a non-human experimental animal model; contacting the model with a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; AP0A4; APOH; AP0L1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG identified by a method described herein; and evaluating the effect of the candidate compound on the model.
[00057] In a preferred embodiment, the said methods for identifying candidate therapeutic agents include providing a model of the disease, e.g., a non-human experimental animal model; contacting the model with a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16; identified by a method described herein; and evaluating the effect of the candidate compound on the model.
[00058] In a more preferred embodiment, the said methods for identifying candidate therapeutic agents include providing a model of the disease, e.g., a non-human experimental animal model; contacting the model with a candidate compound that modifies the DNA methylation status, expression, level, or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 identified by a method described herein; and evaluating the effect of the candidate compound on the model.
[00059] In another embodiment, the invention also provides methods for identifying candidate therapeutic agents for the treatment of preeclampsia and closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage. The methods also include administering candidate therapeutic agents identified by methods described herein that modifies the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC identified by a method described herein, to a subject having preeclampsia or closely related complication of pregnancy, and evaluating the effect of the candidate therapeutic agent on a symptom of the disorder.
[00060] In a preferred embodiment, the said methods for identifying candidate therapeutic agents also include administering candidate therapeutic agents identified by methods described herein that modifies the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG identified by a method described herein, to a subject having preeclampsia or closely related complication of pregnancy, and evaluating the effect of the candidate therapeutic agent on a symptom of the disorder.
[00061] In a preferred embodiment, the said methods for identifying candidate therapeutic agents also include administering candidate therapeutic agents identified by methods described herein that modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS 14; or LGALS 16 identified by a method described herein, to a subject having preeclampsia or closely related complication of pregnancy, and evaluating the effect of the candidate therapeutic agent on a symptom of the disorder.
[00062] In a more preferred embodiment, the said methods for identifying candidate therapeutic agents also include administering candidate therapeutic agents identified by methods described herein that modifies the DNA methylation status, expression, level, or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 identified by a method described herein, to a subject having preeclampsia or closely related complication of pregnancy, and evaluating the effect of the candidate therapeutic agent on a symptom of the disorder.
[00063] In another embodiment, the invention provides pharmaceutical composition that prevents or reduces the symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising specific "inhibitors", "activators" or "modulators" of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC. "Inhibitors" are compounds that, e.g., bind to, partially or totally block activity, decrease, prevent, delay activation, inactivate, desensitize, or down-regulate the activity or expression of these molecules. "Activators" are compounds that increase, open, activate, facilitate, enhance activation, sensitize, agonize, or up-regulate activity of these molecules, e.g., agonists. "Inhibitors", "activators", or "modulators" also include genetically modified versions of these molecules, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
[00064] In a preferred embodiment, the said pharmaceutical composition comprises specific "inhibitors", "activators" or "modulators" of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG.
[00065] In a preferred embodiment, the said pharmaceutical composition comprises specific "inhibitors", "activators" or "modulators" of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS14; or LGALS16.
[00066] In a more preferred embodiment, the said pharmaceutical composition comprises specific "inhibitors", "activators" or "modulators" of one or more of AGT; ZNF554; BCL6; or ARNT2.
[00067] Also provided herein are pharmaceutical compositions for the treatment of preeclampsia or closely related complication of pregnancy, wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, including therapeutic agents identified by a method described herein, and physiologically acceptable carriers, which modify the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; I KBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; LGALS 17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC identified by a method described herein.
[00068] In a preferred embodiment the said pharmaceutical compositions of including therapeutic agents identified by a method described herein, and physiologically acceptable carriers, which modify the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG identified by a method described herein.
[00069] In a preferred embodiment the said pharmaceutical compositions including therapeutic agents identified by a method described herein, and physiologically acceptable carriers, which modify the DNA methylation status, expression, level, or activity of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16 identified by a method described herein.
[00070] In a more preferred embodiment the said pharmaceutical compositions including therapeutic agents identified by a method described herein, and physiologically acceptable carriers, which modify the DNA methylation status, expression, level, or activity of one or more of AGT; ZNF554; BCL6; or ARNT2 identified by a method described herein.
[00071] In some embodiments, the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage. The methods include providing a sample comprising of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH 1; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC; contacting the sample with a test compound; and determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of these molecules in the sample. A test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound.
[00072] In some embodiments, the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample. In some embodiments, the methods further include identifying the test compound as a candidate compound based on the assigned value.
[00073] In other embodiments, a test compound used in a method described herein is selected from the group consisting of genetically modified versions of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS 14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
[00074] In a preferred embodiment, a test compound used in a method described herein is selected from the group consisting of genetically modified versions of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
[00075] In a preferred embodiment, a test compound used in a method described herein is selected from the group consisting of genetically modified versions of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS14; or LGALS16, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
[00076] In a more preferred embodiment, a test compound used in a method described herein is selected from the group consisting of genetically modified versions of one or more of AGT; ZNF554; BCL6; or ARNT2, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these.
[00077] In other embodiments, the test compound is a cell expressing exogenous therapeutic target molecule, e.g., a trophoblast expressing an increased or decreased level of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC. In some embodiments, the test compound includes target molecule polypeptides or nucleic acids, or active fragments thereof.
[00078] In a preferred embodiment, the test compound is a cell expressing exogenous therapeutic target molecule, e.g., a trophoblast expressing an increased or decreased level of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG. In some embodiments, the test compound includes target molecule polypeptides or nucleic acids, or active fragments thereof.
[00079] In a preferred embodiment, the test compound is a cell expressing exogenous therapeutic target molecule, e.g., a trophoblast expressing an increased or decreased level of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS 14; or LGALS16. In some embodiments, the test compound includes target molecule polypeptides or nucleic acids, or active fragments thereof.
[00080] In a more preferred other embodiment, the test compound is a cell expressing exogenous therapeutic target molecule, e.g., a trophoblast expressing an increased or decreased level of one or more of AGT; ZNF554; BCL6; or ARNT2. In some embodiments, the test compound includes target molecule polypeptides or nucleic acids, or active fragments thereof.
[00081] The invention also provides methods for making pharmaceutical compositions for the treatment of preeclampsia or closely related complication of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, by formulating a therapeutic agent identified by a method described herein with a physiologically acceptable carrier.
[00082] In another embodiment, the invention provides methods for evaluating a compound. In some embodiments, the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy. The methods include providing a sample comprising of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN 1A; CGB3; CLC; CLDN1; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; I KBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; LGALS 17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC; contacting the sample with a test compound; and determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of these molecules in the sample. A test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound. In some embodiments, the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample. In some embodiments, the methods further include identifying the test compound as a candidate compound based on the assigned value.
[00083] In a preferred embodiment, the invention provides methods for evaluating a compound. In some embodiments, the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy. The methods include providing a sample comprising of one or more of ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; ZNF554; AGT; APOA4; APOH; APOL1 ; C1QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG; contacting the sample with a test compound; and determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of these molecules in the sample. A test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound. In some embodiments, the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample. In some embodiments, the methods further include identifying the test compound as a candidate compound based on the assigned value.
[00084] In a preferred embodiment, the invention provides methods for evaluating a compound. In some embodiments, the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy. The methods include providing a sample comprising of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS13; LGALS14; or LGALS16; contacting the sample with a test compound; and determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of these molecules in the sample. A test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound. In some embodiments, the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample. In some embodiments, the methods further include identifying the test compound as a candidate compound based on the assigned value.
[00085] In a more preferred embodiment, the invention provides methods for evaluating a compound. In some embodiments, the methods include identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy. The methods include providing a sample comprising of one or more of AGT; ZNF554; BCL6; or ARNT2; contacting the sample with a test compound; and determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of these molecules in the sample. A test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound. In some embodiments, the methods include assigning a value to the test compound for the effectiveness of the test compound in modifying the DNA methylation status, expression, level, or activity of these molecules in the sample. In some embodiments, the methods further include identifying the test compound as a candidate compound based on the assigned value.
[00086] As used herein, to "specifically modify" the DNA methylation status, expression, level, or activity of one or more of ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; ZNF554; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC means to statistically significantly modify the DNA methylation status, expression, level, or activity of the target molecule without significantly modifying the expression, level, or activity of closely related molecules, e.g. gene family members. [00087] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Materials and methods are described herein for use in the present invention; other, suitable materials and methods known in the art can also be used. The materials, methods, and examples are illustrative only and not intended to be limiting. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control.
[00088] Other features and advantages of the invention will be apparent from the following detailed description and figures, and from the claims.
BRIEF DESCRIPTION OF THE FIGURES
[00089] Figure 1. Figure 1A-B shows co-expression matrices of transcription regulatory genes and predominantly placenta expressed genes in the "red and green modules" in placental microarray data. (A) Co-expression matrix shows that within the red module, BCL6, VDR, BHLHE40, ARNT2, JUNB and BTG2 transcription regulatory genes had their expression most correlated with FLT1 and predominantly placenta expressed genes. BCL6 and ARNT2 expression had the highest correlation with that of FLT1. (B) Co-expression matrix shows that within the green module, ESRRG, POU5F1 , ZNF554, and HLF transcription regulatory genes had their expression most correlated with predominantly placenta expressed genes. ESRRG and ZNF554 expression had the highest correlation with that of CSH1 and HSD11 B2, genes strongly implicated in fetal growth.
[00090] Figure 2. Figure 2A-B shows first trimester maternal serum proteomics changes in preterm preeclampsia. (A) Venn diagram of proteomics data shows that the 19 differentially expressed maternal serum proteins in the first trimester in preterm preeclampsia belong to six functional groups, which are relevant for the pathophysiology of preeclampsia. (B) These 19 serum proteins have connections with 121 differentially expressed placental genes in preeclampsia, among which 48 belong to the "red module" that is dysregulated in association with high blood pressure. Angiotensinogen has more connections than other proteins (OR:1.9, p=4.9x105), and the most connections with red module genes (n=35) including LEP, CRH and FLT1. Seventy seven out of 86 connections of angiotensinogen has a directional effect towards the gene.
[00091] Figure 3. Figure 3A-B shows first trimester maternal serum proteomics changes in term preeclampsia. (A) Venn diagram of proteomics data shows that the 14 differentially expressed maternal serum proteins in term preeclampsia belong to six functional groups, which are relevant for the pathophysiology of preeclampsia. (B) These 14 serum proteins have connections with 116 differentially expressed placental genes in preeclampsia, among which 46 belong to the "red module" that is dysregulated in association with high blood pressure. Angiotensinogen has more connections than other proteins (OR:2.5, p=1.6x108) and the most with red module genes (n=35). Seventy seven out of 86 connections of angiotensinogen have a directional effect towards the gene.
[00092] Figure 4. Figure 4A-E shows in vitro modeling of the placental dysregulation of gene modules in preeclampsia. (A) Hierarchical clustering of expression data for 47 genes in 100 placental specimens and a heatmap representing differential gene expression in term or preterm subgroups of preeclampsia compared to respective controls. (B) Preterm preeclampsia serum induced the up-regulation of seven placental dysregulated genes in primary trophoblasts, among which six were up-regulated in term and three in preterm preeclampsia. (C) The overexpression of ARNT2 or BCL6 in normoxic BeWo cells induced the dysregulation of five genes dysregulated in preeclampsia. (D) Hypoxia induced the dysregulation of five genes dysregulated in preeclampsia. Hypoxia combined with ARNT2 or BCL6 overexpression led to the dysregulation of a large number of genes. (E) Ischemia itself induced the dysregulation of only three genes in BeWo cells similar to that in the placenta in preeclampsia. Ischemia combined with ARNT2 or BCL6 overexpression led to the dysregulation of 11 genes similar to preeclampsia. (D) and (E) represents comparisons of gene expressions between hypoxia/ischemia vs. normoxia. In (A-E), stars depict significant changes, "O" depicts "overexpressed", and color bar encodes signed (up or down)-fold changes. Black boxes depict genes with similar expression changes in vitro as in the placenta in preeclampsia. [00093] Figure 5. Figure 5 shows BCL6 expression in BeWo cells after various treatments with 5-azacitidin and Forskolin. Decreased BCL6 expression was observed in BeWo cells upon treatment with 5-azacitidin (5-AZA) irrespective of Forskolin (FRSK) co-treatment.
[00094] Figure 6. Figure 6 summarizes the obtained data showing that serum factors and epigenetic changes modify BCL6 expression upstream of ARNT2, and the overexpression of these transcription factors leads to trophoblast sensitization to hypoxic/ischemic stress, and the consequent dysregulation of red and green modules, mostly in preterm preeclampsia.
[00095] Figure 7. Figure 7 shows tissue qRT-PCR array data that revealed the highest ZNF554 expression in the placenta among 48 human tissues.
[00096] Figure 8. Figure 8A-B shows ZNF554 expression in the placenta. (A) In situ hybridization of a third trimester placenta (GW29) and (B) immunohistochemistry of a first trimester placenta (GW12) shows mainly syncytiotrophoblastic ZNF554 expression (1400x and 400x magnifications). Black or white arrowheads depict syncytiotrophoblast or cytotrophoblast, while black arrow depicts fetal endothelium, respectively.
[00097] Figure 9. Figure 9 shows qRT-PCR data depicting that ZNF554 expression is up-regulated during villous cytotrophoblast differentiation in parallel with CSH1.
[00098] Figure 10. Figure 10A-B shows ZNF554 expression in the placenta. ZNF554 immunopositivity was faint in the syncytiotrophoblast in (B) preeclampsia (GW35) compared to (A) gestational-age matched controls (GW36). Arrow and arrowhead depict syncytiotrophoblast and fetal endothelium, respectively (400x magnifications).
[00099] Figure 11. Figure 11A-E shows in vitro gene expression data of BeWo cells after ZNF554 knock-down. (A) ZNF554 mRNA expression was 74% lower in ZNF554 siRNA-treated BeWo cells compared to control cells used for the microarray (p=5.24x10 6). (B) Nuclear and cytoplasmic ZNF554 immunofluorescence decreased in BeWo cells treated with ZNF554 siRNA compared to control cells. (C) Bioinformatics analyses revealed the glycolysis / gluconeogenesis pathway, RNA, nucleic acid and activin binding to be affected in ZNF554 knock-down BeWo cells. (D) qRT-PCR validated FSTL3 up-regulation (2.7-fold, p<0.001) in BeWo cells upon ZNF554 knock-down.
[000100] Figure 12. Figure 12A-B shows ZNF554 immunostainings in first and third trimester placentas. (A) Extravillous trophoblasts in the trophoblastic columns (GW12) and (B) endovascular and intraluminal trophoblasts in the myometrium (GW36) were immunostained for cytokeratin-7 (left) and ZNF554 (right). Arrows depict the direction of trophoblst invasion in trophoblastic columns, black and white arrowheads point to trophoblasts in the wall and lumen of a spiral artery (serial sections, 200x magnifications).
[000101] Figure 13. Figure 13A-B shows that ZNF554 immunostainings in decidual extravillous trophoblasts (arrowheads) and syncytiotrophoblats (arrows) were weaker in (B) preeclampsia (GW35) than in (A) controls (GW36) (serial sections, 200x magnifications).
[000102] Figure 14. Figure 14 shows in vitro gene expression data of HTR8/SVneo cells after ZNF554 knock-down. (A) At 87% ZNF554 mRNA knock-down (p<0.001), (B) ZNF554 immunofluorescence was weaker in the nucleus and cytoplasm of ZNF554 knock-down (left) than control (right) HTR8/SVneo cells.
[000103] Figure 15. Figure 15 shows the effect of ZNF554 knock-down on cell proliferation in HTR8/SVneo cells. (A) ZNF554 knock-down slightly but significantly decreased cell proliferation after 48h (-14%, p=0.02). Y-axis depicts viable cell number, X-axis shows incubation time. (B) The differential expression of CDKN1A and STK40 (genes involved in the regulation of cell cycle) upon ZNF554 knock-down was confirmed by qRT-PCR. Oxygen concentrations are shown below the bars.
[000104] Figure 16. Figure 16 shows the effect of ZNF554 knock-down on gene expression in HTR8/SVneo cells. The dysregulation of selected genes upon ZNF554 knock-down was confirmed by qRT-PCR. Oxygen concentrations are shown below the bars.
[000105] Figure 17. Figure 17 shows the effect of ZNF554 knock-down on protein secretion from HTR8/SVneo cells. The increased secretion of SERPINE (PAI-1) and TIMP3 from ZNF554 knock-down cells was confirmed by ELISA. Oxygen concentrations are shown below the bars. [000106] Figure 18. Figure 18 shows the effect of ZNF554 knock-down on the migratory and invasive capacity of HTR8/SVneo cells. ZNF554 knock-down cells had remarkably decreased invasive (left) and migratory (right) characteristics. Oxygen concentrations are shown below the bars.
[000107] Figure 19. Figure 19. Figure 19A-D shows the evolutionary origins of deep trophoblast invasion in humans. (A) The ~3kb human ZNF554 5'UTR (black line) contains an AluSq2, AluY and several LTR10A fragments (shown below). These TEs harbor several predicted hypoxia-response elements (HREs, shown above) and ZEB1 binding sites. (B) Luciferase assays showed that ZEB1 vs. GFP co-transfection led to a 3.3-fold increase (p=0.001) in human ZNF554 5'UTR activity, while 02 concentration itself did not affect the human 5'UTR activity. (C) The AluY was inserted into ZNF554 5'UTR in apes, expanding HREs and fragmenting LTR10A. An LTR10A fragment multiplicated to 16 copies in humans, expanding ZEB1 binding sites. (D) Hypoxia vs. 8%02 increased the human 5'UTR activity (+25%, p<0.01) when ZEB1 was overexpressed, suggesting ZEB1-HIFa interaction in ZNF554 regulation. Upon ZEB1 vs. GFP co-transfection, there were higher luciferase activity ratios of the human than the macaque (22%, p<0.01) or orangutan (25%, p<0.01) 5'UTRs at 8%02. The macaque 5'UTR activity ratio did not differ between hypoxia and 8%02, the orangutan 5'UTR activity ratio was higher in hypoxia than in 8%02 (+28%, p<0.01), and the human 5'UTR activity ratio was the highest in hypoxia (+60% vs. macaque, p<0.00001; +22% vs. orangutan, p<0.01).
[000108] Figure 20. Figure 20 shows the origins of impaired trophoblast invasion and preeclampsia. The insertion of the AluY in the ZNF554 5'UTR, along with additional evolutionary changes, introduced several putative HREs and ZEB1 binding sites, contributing to the increased invasiveness of extravillous trophoblasts and deep trophoblast invasion. The methylation of certain CpGs at two HREs in AluY in the trophoblast inhibits the mechanisms of deep trophoblast invasion, and promotes the development of preeclampsia.
[000109] Figure 21. Figure 21 shows gene expression changes in BeWo cells upon 5-azacitidin treatment and Forskolin co-treatment. There were 37 genes that had differential expression upon treatment with 5-azacitidin (5-AZA), with or without Forskolin (FRSK) co-treatment, suggesting their regulation by DNA methylation in the trophoblast.
[000110] Figure 22. Figure 22. summarizes the identified epigenetic biomarker genes and biomarker candidate regions for preeclampsia and closely related complications of pregnancy. The listed 37 genes had differential methylation and consequent differential expression upon 5-azacitidin treatment in BeWo cells. Five out of these 37 genes were further characterized for differential methylation in primary trophoblasts, cord blood cells, and laser captured trophoblasts. The genomic regions with differential methylation in the three comparisons are shown in the figure and treated as biomarker candidates.
[000111] Figure 23. Figure 23 summarizes the potential therapeutic target molecules identified by the proteomics study, their observed mechanism of dysregulation in preeclampsia, and the required effect of the therapeutics.
[000112] Figure 24. Figure 24 summarizes the potential therapeutic target molecules identified by the transcriptomics study, their observed mechanism of dysregulation in preeclampsia, and the required effect of the therapeutics.
[000113] Figure 25. Figure 25 describes pathologic pathways in preeclampsia. In the newly defined "molecular phase" of preeclampsia, characteristic alterations in the maternal proteome can be observed, supporting that the activation of the complement and renin-angiotensin systems as well as maternal metabolic pathways have key role in triggering early pathologic events. These alterations in maternal blood can induce trophoblastic functional changes leading to the overproduction of sFlt-1 and an anti-angiogenic state through a trajectory that does not necessarily affect fetal growth. This phenomenon is explained by that distinct placental gene modules are associated with changes in blood pressure and birth-weight, implying that different molecular pathways are responsible for impaired trophoblast invasion and trophoblastic overproduction of anti-angiogenic molecules. The "ZNF554" pathway have evolved in great apes to support deep trophoblast invasion, and the epigenetic dysregulation of this pathway is a key component in impaired trophoblast invasion in preeclampsia. The down- regulation of ZNF554 and other green module genes involved in the regulation of fetal growth and metabolism imply impaired villous trophoblast functions in fetal growth restriction besides pathways originated from abnormal trophoblast invasion and consequent placental endoplasmic reticulum stress. The red gene module associated with blood pressure elevation is not only up-regulated by alterations in maternal blood proteome but also by the overproduction of BCL6 and ARNT2 due to epigenetic background. The up-regulation of this "BCL6-ARNT2 pathway" sensitizes the trophoblast to ischemia, and increases FLT1 and decreases PIGF expression. These changes are only observed in the placenta in preterm preeclampsia, suggesting that the dysregulation of this pathway promotes the earlier development of the preclinical phase of preeclampsia in conjunction with the placental release of pro-inflammatory molecules and trophoblastic debris. The interplay of these distinct pathomechanisms lead to the complex and "personalized" pathogenesis of preeclampsia.
DETAILED DESCRIPTION
[000114] A number of methods for obtaining expression data can be used singly or in combination for determining expression patterns and profiles in the context of the present disclosure. For example, DNA and RNA expression patterns can be evaluated by northern analysis, PCR, RT-PCR, quantitative real-time RT-PCR analysis with TaqMan assays, FRET detection, monitoring one or more molecular beacon, hybridization to an oligonucleotide array, hybridization to a cDNA array, hybridization to a polynucleotide array, hybridization to a liquid microarray, hybridization to a microelectric array, molecular beacons, cDNA sequencing, clone hybridization, cDNA fragment fingerprinting, serial analysis of gene expression (SAGE), subtractive hybridization, differential display and/or differential screening.
[000115] Gene expression changes can be related to epigenetic variations (e.g. DNA methylation). Epigenetic regulation mechanisms do not involve a change to the DNA sequence. Instead, epigenetic variations include covalent modification of DNA, RNA, and the proteins associated with DNA. These in turn can result in changes to the conformation of DNA and accessibility of regulators to the DNA. Such changes cannot be identified simply by gene sequencing. Janssen, B.G. et al., Particle and Fibre Toxicology, 10:22 (2013) studied methylation in placental tissue using methods published by Tabish, A.M. et al., PLoS ONE 2012, 7:e34674 and by Godderis, L. et al., Epigenomics 4:269-277 (2012). MS-MLPA (Methylation-specific Multiplex ligation-dependent probe amplification) can be used to study methylation status of specific genes, for example in Proctor, M. et al., Clin. Chem. 52:1276-1283 (2006). Materials and methods for MS- MLPA as used in published studies can be obtained from MRC-Holland, Amsterdam, The Netherlands. Additional methods are reviewed and compared in Shen, L. et al., Curr. Opin. Clin. Nutr. Metab. Care. 10:576-81 (2007); Gu H et al., Nature Methods 7:133-138 (2010); Bock C et al., Nature Biotech. 28:1106-1114 (2010); Harris RA et al., Nature Biotech. 28:1097-1105 (2010).
[000116] Protein expression patterns can be evaluated using any method that provides a quantitative measure and is suitable for evaluation of multiple markers extracted from samples. Exemplary methods include: ELISA sandwich assays, mass spectrometric detection, calorimetric assays, binding to a protein array (e.g., antibody array), or fluorescent activated cell sorting (FACS). Approaches can use labeled affinity reagents (e.g., antibodies, small molecules, etc.) that recognize epitopes of one or more protein products in an ELISA, antibody array, or FACS screen.
[000117] Protein activity can be measured by any known protein assay that are capable of reliably and specifically measuring the protein component.
[000118] Typically, the term high-throughput refers to a format that performs at least about 100 assays, or at least about 500 assays, or at least about 1000 assays, or at least about 5000 assays, or at least about 10,000 assays, or more per day. When enumerating assays, either the number of samples or the number of protein markers assayed can be considered. Generally high-throughput expression analysis methods involve a logical or physical array of either the subject samples, or the protein markers, or both. Appropriate array formats include both liquid and solid phase arrays. For example, assays employing liquid phase arrays, e.g., for hybridization of nucleic acids, binding of antibodies or other receptors to ligand, etc., can be performed in multiwell or microtiter plates. Microtiter plates with 96, 384, or 1536 wells are widely available, and even higher numbers of wells, e.g., 3456 and 9600 can be used. In general, the choice of microtiter plates is determined by the methods and equipment, e.g., robotic handling and loading systems, used for sample preparation and analysis. [000119] Alternatively, a variety of solid phase arrays can also be employed to determine expression patterns. Exemplary formats include membrane or filter arrays (e.g., nitrocellulose, nylon), pin arrays, and bead arrays (e.g., in a liquid "slurry"). Essentially any solid support capable of withstanding the reagents and conditions necessary for performing the particular expression assay can be utilized. For example, functionalized glass, silicon, silicon dioxide, modified silicon, any of a variety of polymers, such as (poly)tetrafluoroethylene, (poly)vinylidenedifluoride, polystyrene, polycarbonate, or combinations thereof can all serve as the substrate for a solid phase array.
[000120] In one embodiment, quantitative data obtained about the markers of interest and other dataset components can be subjected to an analytic process with chosen parameters. The parameters of the analytic process may be those disclosed herein or those derived using the guidelines described herein. The analytic process used to generate a result may be any type of process capable of providing a result useful for classifying a sample, for example, comparison of the obtained dataset with a reference dataset, a linear algorithm, a quadratic algorithm, a decision tree algorithm, or a voting algorithm. The analytic process may set a threshold for determining the probability that a sample belongs to a given class. The probability preferably is at least 50%, or at least 60%, or at least 70%, or at least 80%, or at least 90% or higher.
[000121] Inhibitors," "activators," and "modulators" of the target molecules are used to refer to activating, inhibitory, or modulating molecules identified using in vitro and in vivo assays. Inhibitors are compounds that, e.g., bind to, partially or totally block activity, decrease, prevent, delay activation, inactivate, desensitize, or down regulate the activity or expression of target molecules. "Activators" are compounds that increase, open, activate, facilitate, enhance activation, sensitize, agonize, or up regulate activity of target molecules, e.g., agonists. Inhibitors, activators, or modulators also include genetically modified versions of target molecules, e.g., versions with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, proteins, fusion proteins, peptides, cyclic peptides, polynucleotides, oligonucleotides, antisense molecules, ribozymes, RNAi molecules, aptamers, sugars, polysaccharides, lipids, fatty acids, small organic molecules, small chemical compounds, dendrimers, nanovesicles, microvesicles and the combinations of any of these. Such assays for inhibitors and activators include, e.g., expressing target molecules in vitro, in cells, or cell extracts, applying putative modulator compounds, and then determining the functional effects on activity, as described above.
[000122] Samples or assays comprising target molecules that are treated with a potential activator, inhibitor, or modulator are compared to control samples without the inhibitor, activator, or modulator to examine the extent of inhibition. Control samples (untreated with inhibitors) are assigned a relative protein activity value of 100%. Inhibition of target molecules is achieved when the activity value relative to the control is about 80%, preferably 50%, more preferably 25-0%. Activation of target molecules is achieved when the activity value relative to the control (untreated with activators) is 110%, more preferably 150%, more preferably 200-500% (i.e., two to five fold higher relative to the control), more preferably 1000-3000% higher.
[000123] The term "test compound" or "drug candidate" or "modulator" or grammatical equivalents as used herein describes any molecule, either naturally occurring or synthetic, e.g. antibody, protein, fusion protein, peptide (e.g., from about 5 to about 25 amino acids in length, preferably from about 10 to 20 or 12 to 18 amino acids in length, preferably 12, 15, or 18 amino acids in length), cyclic peptide, polynucleotide, oligonucleotide, antisense molecule, ribozyme, RNAi molecule, aptamer, sugar, polysaccharide, lipid, fatty acid, small organic molecule, small chemical compound, dendrimer, nanovesicle, microvesicle and the combination of any of these, etc., to be tested for the capacity to directly or indirectly modulate target molecules.
[000124] The test compound can be in the form of a library of test compounds, such as a combinatorial or randomized library that provides a sufficient range of diversity. Test compounds are optionally linked to a fusion partner, e.g., targeting compounds, rescue compounds, dimerization compounds, stabilizing compounds, addressable compounds, and other functional moieties. Conventionally, new chemical entities with useful properties are generated by identifying a test compound (called a "lead compound") with some desirable property or activity, e.g., inhibiting activity, creating variants of the lead compound, and evaluating the property and activity of those variant compounds. Often, high throughput screening (HTS) methods are employed for such an analysis.
[000125] A "small organic molecule" refers to an organic molecule, either naturally occurring or synthetic, that has a molecular weight of more than about 50 daltons and less than about 2500 daltons, preferably less than about 2000 daltons, preferably between about 100 to about 1000 daltons, more preferably between about 200 to about 500 daltons.
[000126] A variety of methods may be used to identify compounds that prevent or treat preeclampsia and closely related complications of pregnancy. Typically, an assay that provides a readily measured parameter is adapted to be performed in the wells of multi-well plates in order to facilitate the screening of members of a library of test compounds as described herein. Thus, in one embodiment, an appropriate number of cells can be plated into the cells of a multi-well plate, and the effect of a test compound on the DNA methylation status, expression, level or activity of the target molecules can be determined.
[000127] The compounds to be tested can be any small chemical compound, or a macromolecule, such as a sugar, nucleic acid, protein or lipid. Typically, test compounds will be small chemical molecules and peptides. Essentially any chemical compound can be used as a test compound in this aspect of the invention, although most often compounds that can be dissolved in aqueous or organic (especially DMSO- based) solutions are used. The assays are designed to screen large chemical libraries by automating the assay steps and providing compounds from any convenient source to assays, which are typically run in parallel (e.g., in microtiter formats on microtiter plates in robotic assays).
[000128] High throughput screening methods can be used which involve providing a combinatorial chemical or peptide library containing a large number of potential therapeutic compounds. Such "combinatorial chemical libraries" or "ligand libraries" are then screened in one or more assays, as described herein, to identify those library members (particular chemical species or subclasses) that display a desired characteristic activity. In this instance, such compounds are screened for their ability to reduce or increase the DNA methylation, expression, level or activity of the target molecules.
[000129] A combinatorial chemical library is a collection of diverse chemical compounds generated by either chemical synthesis or biological synthesis, by combining a number of chemical "building blocks" such as reagents. For example, a linear combinatorial chemical library such as a polypeptide library is formed by combining a set of chemical building blocks (amino acids) in every possible way for a given compound length (i.e., the number of amino acids in a polypeptide compound). Millions of chemical compounds can be synthesized through such combinatorial mixing of chemical building blocks.
[000130] Preparation and screening of combinatorial chemical libraries are well known to those of skill in the art. Such combinatorial chemical libraries include, but are not limited to, peptide libraries (see, e.g., Houghton et al., Nature, 354:84-88 (1991), U.S. Pat. No. 5,010,175). Other chemistries for generating chemical diversity libraries can also be used, which include, but are not limited to: peptoids (e.g., PCT Publication No. WO 91/19735), encoded peptides (e.g., PCT Publication No. WO 93/20242), random bio-oligomers (e.g., PCT Publication No. WO 92/00091), nonpeptidal peptidomimetics with glucose scaffolding (Hirschmann et al., J. Amer. Chem. Soc, 114:9217- 9218 (1992)), analogous organic syntheses of small compound libraries (Chen et al., J. Amer. Chem. Soc, 1 16:2661 (1994)), nucleic acid libraries (see Ausubel, Berger and Sambrook, all supra), peptide nucleic acid libraries (see, e.g., U.S. Pat. No. 5,539,083), antibody libraries (see, e.g., Vaughn et al., Nature Biotechnology, 14(3):309-314 (1996) and PCT/US96/10287), carbohydrate libraries (see, e.g., Liang et al., Science, 274:1520-1522 (1996) and U.S. Pat. No. 5,593,853), small organic molecule libraries (see, e.g., isoprenoids, U.S. Pat. No. 5,569,588; morpholino compounds, U.S. Pat. No. 5,506,337 and the like).
[000131] Devices for the preparation of combinatorial libraries are commercially available (see, e.g., 433A Applied Biosystems, Foster City, Calif., 9050 Plus, Millipore, Bedford, Mass.). In addition, numerous combinatorial libraries are themselves commercially available (see, e.g., ComGenex, Princeton, N.J., Tripos, Inc., St. Louis, Mo., 3D Pharmaceuticals, Exton, Pa., Martek Biosciences, Columbia, Md., etc.).
[000132] In the high throughput assays of the invention, it is possible to screen up to several thousand different modulators or ligands in a single day. In particular, each well of a microtiter plate can be used to run a separate assay against a selected potential modulator, or, if concentration or incubation time effects are to be observed, every 5-10 wells can test a single modulator. Thus, a single standard microtiter plate can assay about 96 modulators. If 1536 well plates are used, then a single plate can easily assay from about 100- about 1500 different compounds. It is possible to assay many plates per day; assay screens for up to about 6,000, 20,000, 50,000, or 100,000 or more different compounds is possible using the integrated systems of the invention.
[000133] The following examples further illustrate the present disclosure but should not be construed as limiting its scope in any way. EXAMPLES
[000134] Example 1. Microarray study.
[000135] The research described in this Example was approved by the Health Science Board of Hungary and the Human Investigation Committee of Wayne State University. After obtaining informed consent, placental tissue samples were collected from Caucasian women at the First Department of Obstetrics and Gynecology, Semmelweis University. Specimens and data were stored anonymously. Pregnancies were dated to be between 8-12 weeks of gestation according to ultrasound scans. Patients with multiple pregnancies (twins, triplets, etc.) or fetuses having congenital or chromosomal abnormalities were excluded. Women were enrolled in the following homogenous groups: (1) preterm severe preeclampsia, with or without HELLP syndrome (n=12) and (2) preterm controls (n=5) (Table 1). Preeclampsia was defined according to the criteria set by the American College of Obstetricians and Gynecologists (Blood pressure: 140 mm Hg or higher systolic or 90 mm Hg or higher diastolic after 20 weeks of gestation in a woman with previously normal blood pressure; proteinuria: 0.3 g or more of protein in a 24-hour urine collection (usually corresponds with 1+ or greater on a urine dipstick test). Severe preeclampsia was defined according to Sibai et al., [Sibai, B et al. Pre-eclampsia. Lancet 2005;365:785-99]. Preterm controls had no medical complications, clinical or histological signs of chorioamnionitis, and delivered neonates with a birth weight appropriate-for-gestational age (AGA). C-section was performed in all preeclampsia cases due to severe symptoms, as well as in all controls due to previous C-section or Representation before 37 weeks of gestation.
Table 1
Figure imgf000020_0001
RNA isolation and microarray experiments
[000136] Placentas (n=17) were obtained immediately after delivery. Tissue specimens were excised from central cotyledons close to the umbilical cord in order to reduce the possible bias due to regional differences in gene expression, dissected from the choriodecidua on dry ice and stored at -80°C. Tissues were homogenized using a ThermoSavant FastPrep FP120 Homogenizer (Thermo Scientific, Wilmington, DE, USA) with Lysing MatrixD (MP Biomedicals, lllkirch, France). Total RNA was isolated using RNeasy Fibrous Tissue Mini Kit (Qiagen GmbH, Hilden, Germany), quantified with NanoDroplOOO (Thermo Scientific) and assessed by Agilent 2100 Bioanalyzer (Matriks AS, Oslo, Norway). Total RNAs (controls, n=5; preeclampsia, n=12) were labeled, and Cy3-RNAs were fragmented and hybridized to the Whole Human Genome Oligo Microarray G4112A on an Agilent scanner, (Agilent Technologies, Santa Clara, CA, USA), and processed with Agilent Feature Extraction software v9.5 according to the manufacturer's guidelines. Data analysis Demographics data were compared by the Fisher's exact test and Mann-Whitney test using SPSS version 12.0 (SPSS Inc., Chicago, IL, USA). Microarray data analysis was performed using the R statistical language and environment (website r-project.org). Microarray expression intensities were background-corrected using the "minimum" method in the "backgroundCorrect" function of the "limma" package. After log2 transformation, data were quantile-normalized. From the 41 ,093 probesets on the array, 93 were removed before differential expression analysis because of lacking annotation in the array definition file (Agilent Technologies). Subsequently, an expression filter was applied to retain probesets with intensity greater than log2 in at least two samples, yielding a final matrix of 30,027 probesets (15,939 unique genes). Differential gene expression was assessed using a moderated t-test. P-values were adjusted using the false discovery rate (FDR) method. Target gene Entrez IDs for the probesets were determined using the R package "hgu4112a.db". For probesets without annotation in the package, Entrez IDs were taken from the array definition file (Agilent Technologies). Probesets remaining un-annotated (without Entrez ID and/or gene symbol) were removed from further analysis. Probesets were defined as differentially expressed (n=1409) in this example if they had a FDR of ≤0.2 and a fold-change of >1.5. As used herein, "differential expression", "significantly differentially expressed", and similar terms generally mean that expression of a gene is significantly different based on a statistical power analysis, the results of which can be validated by qPCR at a 95% confidence interval.
[000137] Example 2. Systems biology analyses of placental whole-genome transcriptomics data
[000138] From the differentially expressed genes in preeclampsia, those encoding for proteins with functions in transcription regulation (n=137) were identified using the Metacore (GeneGo Inc., Saint Joseph, Ml, USA) and GeneCards v3 (www.genecards.org) databases.
[000139] The human U133A/GNF1 H microarray data on 79 human tissues, cells and cell lines from Symatlas microarray database [Su, Al et al. A gene atlas of the mouse and human protein-encoding transcriptomes. PNAS 2004;101 :6062-67] was downloaded to search for human genes with predominant placental expression. A probeset was defined as having predominant placental expression, if its placental
th
expression was 1) >1 ,000 fluorescence units; 2) six times higher than the 75 quantile of values in 78 other tissue and cell sources; and 3) two times higher than its expression in the tissue with the second highest expression. The resulting 215 probesets corresponded to 153 unique genes. An additional eleven genes not present on the microarray platform (Affymetrix, Santa Clara, CA, USA) used by Symatlas were added to this list based on their potential relevance. Out of 164 predominantly placental expressed genes, 157 were present on our Agilent array. These genes were tested for enrichment in differentially expressed genes compared to all genes on the array (1 ,409 out of 15,939) using Fisher's exact tests.
[000140] Chromosomal locations for all genes tested on the Agilent array were obtained from the R package "org.Hs.eg.db". Out of the 15,939 unique and 1 ,409 differentially expressed genes on the array, 15,935 and 1 ,408 could be assigned to chromosomes, respectively. Mapping the microarray probe sets on the Affymetrix human U133A GNF1 H chips to ENTREZ identifiers was performed using the Bioconductor hgu133a.db and hgfocus.db packages. Chromosomal locations of the resulting list of genes were obtained from the package org.Hs.eg.db and from NCBI for the eleven additional genes. Enrichment analyses for chromosomes among PPE genes, differentially expressed genes, and differentially expressed genes encoding for transcriptional regulators were tested by Fisher's exact test. Chromosomal locations of PPE genes and differentially expressed genes (transcription regulators and non-transcription regulators) were visualized by Circos.
[000141] Weighted gene co-expression network analysis (WGCNA) was applied on the 1 ,409 differentially expressed genes across 17 samples to identify distinct regulation modules and prioritize candidate genes for qPCR verification. Gene pair-wise similarity (absolute Pearson correlation) matrix was first computed, then soft-thresholded by raising to the power of 10 (chosen based on the scalefree topology criterion) to obtain an adjacency matrix. The topology overlap matrix (TOM) was then derived from the adjacency matrix. The topology overlap measures the node interconnectedness within a network and was generalized to a weighted co-expression network. This measure defines similarity between two genes based on both correlations within themselves and outside with other genes. Gene distance matrix was defined as 1-TOM, and used for average linkage hierarchical clustering. A hybrid dynamic tree-cutting method was applied to obtain modules (tree clusters). Gene modules identified with this approach were further tested for enrichment in PPE genes using a Fisher's exact test.
[000142] Transcription regulatory genes that were expressed at high levels (average log2 intensity >9) and co-expressed (absolute Pearson coefficient >0.8) with the most genes among PPE genes were treated as candidates for hub-genes in the module.
[000143] Example 3. Maternal serum proteomics
[000144] Study groups, clinical definitions and sample collection
[000145] All women were enrolled in a prospective, longitudinal, multicenter study in prenatal community clinics of the Maccabi Healthcare Services, Israel between August 2002 and March 2003. Pregnancies were dated according to the last menstrual period and verified by first trimester ultrasound. Patients with multiple pregnancies (twins, triplets, etc.) or fetuses having congenital or chromosomal abnormalities were excluded. The collection and investigation of human clinical samples were approved by the Maccabi Institutional Review Board, experimental procedures and data analyses were approved by the Health Science Board of Hungary and the Human Investigation Committee of Wayne State University. Informed consent was obtained from women prior to sample collection. Specimens and data were stored anonymously.
[000146] Preeclampsia was defined as hypertension that developed after 20 weeks (systolic or diastolic blood pressure >140 or >90 mmHg, respectively, measured at two different time points, 4h to 1 week apart) coupled with proteinuria (>300mg in a 24h urine collection or >2+ on a dipstick) according to the International Society for the Study of Hypertension in Pregnancy. Preeclampsia was defined severe, if 1) severe hypertension (systolic or diastolic blood pressure >160 or >110 mmHg) was coupled with proteinuria; 2) if hypertension was coupled with severe proteinuria (>5g/24h or >3 on a dipstick), or 3) if maternal multi-organ involvement was present, such as pulmonary edema, oliguria, abnormal liver function, epigastric or right upper-quadrant pain, thrombocytopenia, or severe central nervous symptoms including seizures. Small-for gestational age was defined as neonatal birth weight below the 10th percentile for gestational age. Healthy controls had no medical or obstetric complications and delivered a neonate with a birth-weight appropriate for gestational age.
[000147]
Peripheral blood samples were obtained by venipuncture in the first trimester from women who subsequently developed preterm severe preeclampsia (<36 weeks; n=5), term severe preeclampsia (>37 weeks; n=5), as well as healthy controls (>37 weeks; n=10) matched for gestational age at blood draw (Table 2). Samples were kept for 1— 2h at room temperature (RT) and then centrifuged at 10,000g for 10min. Sera were collected, stored at 2-8oC for up to 48h until transferred to the Maccabi Central Laboratory, and then stored in aliquots at -20oC until shipped on dry ice to Hungary.
Table 2.
Figure imgf000022_0001
Diastolic BP (mmHg) 60 (60-70) 100 (100-100) 67 (63-68) 100 (90-100)
Proteinuria 0 4 (3-4) - 3 (3-4)
Birth weight (gram) 2955 (2900-3100) 1720 (975-1800) 2955 (2900-3100) 3200 (3150-3210)
Median (IQR)
[000148] I. Discovery phase
[000149] Sample preparations, immunodepletion of high-abundance serum proteins
[000150] Sera were immunodepleted at Biosystems International Ltd. (Debrecen, Hungary) for 14 highly abundant serum proteins on an Agilent 1100 HPLC system using Multiple Affinity Removal LC Column -Human 14 (Agilent Technologies, Santa Clara, CA, USA) according to the manufacturer's protocol. To improve the resolution of 2D gels, immunodepleted serum samples were liophylized, and then delipidated and salt depleted at Proteome Services, Ltd. (Budapest, Hungary). Briefly, one volume of all samples was mixed with four volumes of methanol and was thoroughly vortexed. Subsequently, one volume of chloroform was added to these mixtures, which were vortexed again followed by the incorporation of three volumes of water (HPLC grade). After centrifugation at 14,000rpm for 5min at 4°C, the upper phases were discarded. Three volumes of methanol were then added and the resultant mixtures were vortexed and centrifuged again. The supernatants were discarded and the pellets containing the precipitated plasma proteins were air-dried for 10min. The delipidated and salt- depleted plasma protein samples were dissolved in lysis buffer (7M urea; 2M thiourea; 20mM Tris; 5mM magnesium acetate, 4% CHAPS) and their pH was adjusted to 8.0.
[000151] Fluorescent labeling and two-dimensional differential in-gel electrophoresis (2D-DIGE)
[000152] Protein concentrations of the immunodepleted, desalted and delipidated serum samples were between 2-4 g/ l as determined with PlusOne Quant Kit (GE Healthcare, Pittsburgh, PA, USA). Samples were equalized for protein content, and then 5 g of each protein sample was labeled with CyDye DIGE Fluor Labeling kit for Scarce Samples (saturation dye) (GE Healthcare) at a concentration of 4nmol/5 g protein according to the manufacturer's instructions. Individual samples from cases (n=10) and controls (n=10) were labeled with Cy5. An internal standard reference sample was pooled from equal amounts (2.5 g) of all individual samples in this experimental set and was labeled with Cy3. Then, 5 g of each Cy5-labeled individual sample was merged with 5 g of the Cy3-labeled reference sample, and these 20 mixtures were run in 2x10 gels simultaneously. Briefly, labeled proteins were dissolved in IEF buffer containing 0.5% ampholytes, 0.5% DTT, 8M urea, 30% glycerin, 2% CHAPS and were rehydrated passively onto 24cm IPG 20 strips (pH3-10, GE Healthcare) for at least 14h at RT. After rehydration, the IPG strips were subjected to first dimension IEF for 24h to attain a total of 80kVh. Focused proteins were reduced by equilibrating with a buffer containing 1 % mercaptoethanol for 20min. After reduction, IPG strips were loaded onto 10% polyacrylamide gels (24 <20cm) and SDS-PAGE was conducted at 10W/gel in the second dimension. Then, gels were scanned in a Typhoon TRIO+ scanner (GE Healthcare) using appropriate lasers and filters with the PMT biased at 600V. Images in different channels were overlaid using selected colors and the differences were visualized using Image Quant software (GE Healthcare). Differential protein analysis was performed using the Differential In-gel Analysis (DIA) and Biological Variance (BVA) modules of the DeCyder 6.0 software package (GE Healthcare).
[000153] Identification of differentially expressed protein spots
[000154] The internal standard reference sample representative of every protein present in all experiments was loaded equally in all gels, and thus, provided an average image for the normalization of individual samples. The determination of the relative abundance of the fluorescent signal between internal standards across all gels provided standardization between the gels, removing experimental variations and reducing gel-to-gel variations. According to the standard proteomic protocol, the threshold for differential expression was set at 1.05-fold minimum fold-change. A p-value was determined for each protein spot using the Student's t-test by the BVA module of the DeCyder software (GE Healthcare). A p-value of <0.05 was considered statistically significant. [000155] II. Preparative phase
[000156] Sample preparation, fluorescent labeling, 2D-DIGE
[000157] The density of spots in the case of Colloidal Coomassie Blue labeling depends only the concentration of protein in the sample, however the density of spots in the case of saturation dyes labeling depends on the number of cysteines of the labeled proteins too, because the saturation dyes labeling method labels all available cysteines on each protein. This results in the same pattern with different density among samples on the analytical and the preparative gels rendering identification more difficult. To eliminate this problem for the exact identification of proteins in spots of interest, the preparative 2D electrophoresis was performed using CyDye saturation fluorescent labeling and Colloidal Coomassie Blue labeling in the same gel. A total of 800 g of proteins per each of the two gels ran. Briefly, the 10-10 immunodepleted serum samples in the "preterm" and "term" comparisons were pooled together and the salt-depletion step was repeated three-times. Five g protein from each of these two pooled samples was labeled with Cy3, merged with 800 g of unlabeled proteins from the same sample and resolved in the dry-strip. After separation of the first dimension, focused proteins were first reduced by equilibrating with a buffer containing 1% mercaptoethanol for 20min, and then alkylated with a buffer containing 2.5% iodoacetamide for 20min. Following electrophoresis, gels were scanned in a Typhoon TRIO+ scanner as described above, the differentially expressed spots were matched among the "master" analytical and the fluorescent preparative gel image using Biological Variance (BVA) modules of the DeCyder 6.0 software package (GE Healthcare). The resolved protein spots were visualized by the Colloidal Coomassie Blue G-250 staining protocol. Differentially expressed individual spots were excised from the gels to compare the images.
[000158] III. Identification phase
[000159] ln-gel digestion
[000160] The excised protein spots were analyzed at the Proteomics Research Group of the Biological Research Center of the Hungarian Academy of Sciences (Szeged, Hungary); the detailed protocol is entitled "In-Gel Digest Procedure" described in the website "msfacility.ucsf.edu/ingel.html" and reproduced below: Briefly, salts, SDS and Coomassie brilliant blue were washed out, disulfide bridges were reduced with dithiothreitol, and then free sulfhydryls were alkylated with iodoacetamide. Digestion with side-chain protected porcine trypsin (Promega) proceeded at 37°C for 4h, and the resulting peptides were extracted.
[000161] LC-MS/MS
[000162] Samples were analyzed on a Waters Acquity nanoUPLC system on-line coupled to an ion trap tandem mass spectrometer (LCQ Fleet, ThermoScientific) in information-dependent acquisition mode, where MS acquisitions (1s survey scans) were followed by CID analyses (3s MS/MS scans) on computer-selected multiply charged ions. HPLC conditions included in-line trapping onto a nanoACQUITY UPLC trapping column (Symmetry, C18 5 m, 180 m x 20 mm) (15 μΙ/min with 3% solvent B) followed by a linear gradient of solvent B (10 to 50% in 40min, flow rate: 250nl/min; nanoACQUITY UPLC BEH C18 Column, 1.7μίτι, 75μπι x 200mm). Solvent A: 0.1 % formic acid in water, solvent B: 0.1 % formic acid in acetonitrile. LC-MS/MS analysis was performed in "triple play" mode in the mass range of m/z: 450- 1600.
[000163] Database search and data interpretation
[000164] Raw data files were converted into searchable peak list Mascot generic files (*.mgf) with the Mascot Distiller software v2.1.1.0. (Matrix Science, Inc, London, U K). The resulting peak lists were searched against a human subdatabase of the non-redundant protein database of the National Center for Biotechnology Information (NCBInr 2008.07.18., Bethesda, MD, USA; 6,833,826 sequences) in MS/MS ion search mode on an in-house Mascot server v2.2.04 using Mascot Daemon software v2.2.2. (Matrix Science Inc). Monoisotopic masses with peptide mass tolerance of ±50ppm and fragment mass tolerance of ±0.1 Da were submitted. Carbamidomethylation of Cys was set as fixed modification, and acetylation of protein N-termini, methionine oxidation, and pyroglutamic acid formation from peptide N-terminal Gin residues were permitted as variable modifications. Acceptance criteria was set to at least two significant (peptide score>40, p<0.05) individual peptides per protein.
[000165] Example 4. Systems biology analyses of maternal serum proteomics and placental whole-genome transcriptomics data
[000166] Biological functions of differentially expressed serum proteins were retrieved from Pathway Studio 9.0 software (Ariadne Genomics, Inc, Rockville, MD, USA), and from the open-access Gene Ontology (GO) database (http://www.geneontology.org ).
[000167] To elucidate possible interactions between differentially expressed serum proteins and placental genes in the microarray data, bioinformatics analysis was performed using the same software. Molecular networks between differentially expressed serum proteins in preterm (n=19) or term preeclampsia (n=14) and differentially expressed placental genes annotated in the GO database (n=1142) were built separately with a non-linear literature processing search engine, and the resulting connections were manually validated by reading full text publications. The Fisher's exact test was used to test for the enrichment of the connections between differentially expressed serum proteins and 1) differentially expressed genes in individual modules, taking the connections between the proteins and differentially expressed genes in all modules as a background; and 2) differentially expressed placental genes, taking the connections between the proteins and all genes tested on the array as a background. To reveal the pathways enriched among the differentially expressed genes connected to angiotensinogen, the Ingenuity Pathway Analysis software (QIAGEN Redwood City, Redwood City, CA, USA) was used.
[000168] Example 5. Transcriptomic validation study and epigenetics study
[000169] Study groups, clinical definitions and sample collection
[000170] For immunostainings, first trimester placentas (n=18) were collected prospectively from healthy Caucasian women and processed at the Maternity Clinic and Semmelweis University. Pregnancies were dated according to ultrasound scans between 5-13 weeks of gestation. Patients with multiple pregnancies were excluded. The research was approved by the Health Science Board of Hungary and the Human Investigation Committee of Wayne State University. Informed consent was obtained from women prior to sample collection. Specimens and data were stored anonymously.
[000171] For in vitro trophoblast experiments, placentas (n=6) were collected prospectively at the Perinatology Research Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD, NIH, DHHS) from normal pregnant women at term who delivered an AGA neonate with Cesarean section.
[000172] For qRT-PCR, mRNA in situ hybridization, and laser capture microdissection, third trimester placentas (n=100) were retrieved from the Bank of Biological Specimens of the Perinatology Research Branch. Pregnancies were dated according to ultrasound scans between 8- 12 weeks. Patients with multiple pregnancies or fetuses having congenital or chromosomal abnormalities were excluded. The research was approved by the Institutional Review Boards of the NICHD and Wayne State University. Informed consent was obtained from women prior to sample collection. Specimens and data were stored anonymously.
[000173] Placentas were used from women selected from a large cohort into the following, homogenous patient groups: (1) preterm severe preeclampsia (PE;≤36 weeks; n=20); (2) preterm severe preeclampsia associated with small-for-gestational age (SGA) (PE-SGA;≤36 weeks; n=20); (3) preterm controls (PTC;≤36 weeks; n=20); (4) term severe preeclampsia (TPE; >37 weeks; n=10); (5) term severe preeclampsia associated with SGA (TPESGA; >37 weeks; n=10); and (6) term controls (TC; >37 weeks; n=20). Women in these groups were predominantly of African American origin (Table 3). Term controls, consisting of normal pregnant women with (n=10) or without (n=10) labor, and preterm controls with preterm labor and delivery (n=20) had no medical complications or clinical or histological signs of chorioamnionitis, and delivered AGA neonates. Labor was defined by the presence of regular uterine contractions at a frequency of at least two contractions every 10 minutes with cervical changes resulting in delivery. Preeclampsia was defined according to the criteria set by the American College of Obstetricians and Gynecologists. Severe preeclampsia was defined according to Sibai et al., see above. SGA was defined as neonatal birth-weight below the 10th percentile for gestational age. C-section was performed in all preeclampsia cases due to severe symptoms and in controls due to previous C-section or Representation. Table 3
Figure imgf000026_0001
3 Percentage; b Median (IQR); ° p<0.001 ; d p<0.05
[000174] Histopathologic evaluation of the placenta
[000175] Placental tissue samples (n=100) were taken by systematic random sampling, fixed in 10% neutral-buffered formalin, and embedded in paraffin. Five μπι sections were cut from the villous tissue blocks, stained with hematoxylin and eosin, and examined using bright-field light microscopy by two anatomic pathologists blinded to the clinical information. Histopathologic changes were defined according to published criteria. "Maternal underperfusion" and "fetal vascular thrombo-occlusive disease" scores were calculated by summing the number of different pathologic lesions consistent with these lesion categories present in a given placenta.
[000176] mRNA in situ hybridization
[000177] In situ hybridization on third trimester FFPE placental tissues (n=6) was carried out using the RNAscope 2.0 FFPE Assay-Brown (Advanced Cell Diagnostics, Hayward, CA, USA) on a HybEZ Hybridization System. Tissue sections were incubated with ZNF554 target probe (Cat.No.: 423831 , Advanced Cell Diagnostics) for 2h at 40°C. After rinsing with 1X Wash Buffer, slides underwent a six-step amplification procedure at 40°C and were washed with 1X Wash Buffer between amplification steps. Chromogenic detection was performed using a 1 :1 mixture of Brown-A and Brown-B solutions. Slides were counterstained with hematoxylin, dehydrated in graded ethanol, and mounted in xylene.
[000178] Immunohistochemistry
[000179] Five μπι sections of first and third trimester FFPE placental tissues were placed on silanized slides and stained using anti-ZNF554 or anti-cytokeratin-7 antibodies Leica BOND-MAX (Leica Microsystems, Wetzlar, Germany) autostainers.
[000180] Primary villous trophoblast cultures
[000181] Cytotrophoblast were isolated from normal term placentas (n=6) by the modified method of Kliman et al. Briefly, 100g villous tissues were cut, rinsed in PBS, and sequentially digested with Trypsin (0.25%; Invitrogen) and DNAse I (60U/ml; Sigma-Aldrich, St. Louis, MO, USA) for 90min at 37°C. Dispersed cells were filtered through 100 m Falcon nylon mesh cell strainers (BD Biosciences, San Jose, CA, USA), and then erythrocytes were lysed with 5ml NH4CI solution (Stemcell Technologies, Vancouver, BC, Canada). Washed and resuspended cells were layered over 20-50% Percoll gradients and centrifuged for 20min at 1 ,200g. Trophoblast containing bands were collected and non-trophoblastic cells were excluded by negative selection with anti-CD9 (20 g/ml) and anti-CD14 (20 g/ml) mouse monoclonal antibodies (R&D Systems, Minneapolis, MN, USA) and MACS anti-mouse IgG microbeads (Miltenyi Biotec, Auburn, CA, USA). Then, primary trophoblasts were plated on collagen-coated 12-well plates (BD Biosciences; 3x106 cells/well) in Iscove's modified Dulbecco's medium (IMDM; Invitrogen) supplemented with 10% fetal bovine serum (FBS) and 1 % penicillin/streptomycin (P/S).
[000182] To test the effect of trophoblast differentiation on selected genes' expression, primary trophoblasts were kept in IMDM containing 5% non-pregnant human serum (SeraCare, Milford, MA, USA) and 1% P/S. The medium was replenished every 24h, and cells were harvested for total RNA every 24h between days 1-7.
[000183] To test the effect of preeclampsia serum on trophoblast differentiation, primary trophoblasts were kept in IMDM containing 1 % P/S and 10% first trimester maternal sera from control and preeclamptic women. Medium was replenished after 48h, and cells were harvested for total RNA 24h and 72h after the start of the human serum treatment. All experiments were run in triplicate.
[000184] BeWo cell cultures
[000185] BeWo cells (American Type Culture Collection, Manassas, VA, USA) were incubated in T-25 flasks or 6-well plates with F12 medium (Invitrogen) supplemented with 10% FBS and 1 % P/S in a humidified incubator (5%C02, 20%O2) at 37°C until reaching 50-80% confluence.
[000186] To test the effect of ARNT2 or BCL6 overexpression on gene expression, cells were transiently transfected with ARNT2, BCL6, or control (GFP) vectors. Briefly, 4 g expression plasmid (OriGene Technologies, Inc., Rockville, MD, USA) and 12μΙ FuGENE HD transfection reagent (Promega) were mixed with 180μΙ F12 medium (10% FBS, 1% P/S), incubated at RT for 15min and added to cell cultures with 1.8ml medium in each well of 6-well plates. Twenty-four hours after transfection, cells were split into three treatment groups and kept under either normoxic (20%O2), hypoxic (2%02), or ischemic (1% and 20% O2 alternating for 6h) conditions for 48h before cell harvest in an Oxycycler C42 (BioSpherix, Lacona, NY, USA).
[000187] To test the effect of ZNF554 knockdown on gene expression, cells were treated either with 100nM ZNF554 siRNA (Ambion, LifeTechnologies, Foster City, CA, USA) or 100nM scrambled (control) siRNA (Ambion) using X-tremeGENE siRNA transfection reagent (Roche, Mississauga, ON, Canada), and incubated at 37°C in 2ml serum-free Opti-MEM (Gibco) medium. After 6h, the medium was replaced with 2ml F12 medium (Invitrogen) supplemented with 10% FBS. After 48h, cells were collected for RNA isolation, microarray and qRT-PCR, as well as confocal microscopy.
[000188] To test the effect of DNA methylation on gene expression, BeWo cells were treated with 5μΜ or 10μΜ 5-azacitidin (Sigma), while control cells with DMSO. This experiment was also performed when both 5-azacitidin-treated and control cells received 25μΜ Forskolin. After 24h incubation, cells were harvested for RNA isolation and qRT-PCR. The experiment was performed in six replicates.
[000189] HTR8/SVneo cell cultures
[000190] HTR8/SVneo extravillous trophoblastic cells (kindly provided by Dr. Charles H. Graham, Queen's University, Kingston, Ontario, Canada) were incubated in 6-well plates with or RPMI-1640 medium (Gibco) supplemented with 10% FBS and 1 % P/S in a humidified incubator (5%C02, 20%O2) at 37°C until reaching 50% confluence.
[000191] To test the effect of ZNF554 knockdown on gene expression, trophoblast proliferation and functions, cells were treated either with 100nM ZNF554 siRNA (Ambion) or 100nM scrambled (control) siRNA (Ambion) using X-tremeGENE siRNA transfection reagent (Roche), and incubated at 37°C in 2ml serum-free Opti-MEM (Gibco) medium. After 6h, the medium was replaced with 2ml RPMI-1640 medium (Gibco) supplemented with 10% FBS. Starting the following day, cells were kept in various O2 concentrations (2%, 8%, or 20%) in an Oxycycler C42 (BioSpherix). Cells were collected for functional assays after 24h, while cells were collected for RNA isolation, microarray, qRT-PCR or confocal microscopy and their supernatants for ELISA after 48h. Cell culture supernatants were collected after Oh, 24h and 48h for proliferation assays.
[000192] For ZNF554 5'UTR analyses and 5'UTR luciferase construct design, genomic sequences that did not contain annotation gap in the
ZNF554 5'UTR were obtained from the UCSC Genome Browser (http://genome.ucsc.edu ). The Biobase Knowledge Library (BIOBASE
Corp., Beverly, MA, USA) was used to predict putative TF binding sites in the human, orangutan, gibbon, macaque, and baboon ZNF554
5'UTRs using matrix and core similarity cut-offs of 0.9. ZNF554 5'UTRs were either synthesized (GenScript, Piscataway, NJ, USA) or amplified from genomic DNA and inserted into a GLuc-ONTM promoter reporter vector (Genecopoeia, Rockville, MD, USA).
[000193] Reporter constructs were transfected into HTR8/SVneo cells using FuGENE HD reagent (Promega). Briefly, 4 g of reporter constructs and 12μΙ FuGENE HD reagent were mixed with 180μΙ RPMI-1640 medium (Gibco) supplemented with 10% FBS and 1% P/S, incubated at RT for 15min, and then added to the cells along with 1.8ml RPMI-1640 medium.
[000194] To test the effect of oxygen on ZNF expression, cells were kept in various (2%, 8%, or 20%) O2 concentrations.
[000195] To test the effect of ZEB1 overexpression on ZNF554 expression, cells were transiently co-transfected with ZEB1 or GFP expression vectors (OriGene Technologies) and then kept in various (2% or 8%) O2 concentrations. Transfected cells were incubated at
37°C for 48h and then supernatants were collected.
[000196] Total RNA isolation, microarray and qRT-PCR
[000197] Total RNA was isolated from snap-frozen placental villous tissues (n=100), primary trophoblast, Bewo and HTR8/SVneo cell cultures with TRIzol reagent (Invitrogen, Carlsbad, CA, USA) and RNeasy kit (QIAGEN, Valencia, CA, USA) according to the manufacturers' recommendations. The 28S/18S ratios and the RNA integrity numbers were assessed using an Agilent Bioanalyzer 2100 (Agilent Technologies), RNA concentrations were measured with NanoDrop1000 (Thermo Scientific).
[000198] DNase-treated RNA from BeWo and HTR8/SVneo cells (500ng) was amplified and biotin-labeled with the lllumina TotalPrep RNA Amplification Kit (Ambion). Labeled cRNAs were hybridized to a HumanHT-12v4 Expression BeadChip (lllumina, Inc., San Diego, CA). BeadChips were imaged using a BeadArray Reader (lllumina, Inc.), and raw data were obtained with BeadStudio Software V.3.4.0 (lllumina, Inc.).
[000199] Total RNA (500ng) was also reverse transcribed with High Capacity cDNA Reverse Transcription Kit using random hexamers (Applied Biosystems, Foster City, CA, USA). TaqMan Assays (Applied Biosystems) were used for high-throughput gene expression profiling on the Biomark qRT-PCR system (Fluidigm, San Francisco, CA, USA) according to the manufacturers' instructions.
[000200] Tissue qRT-PCR array expression profiling
[000201] TaqMan assays (Applied Biosystems) for ZNF554 and RPLP0 were run in triplicate for expression profiling of the Human Major Tissue qPCR Array (OriGene Technologies, Inc.) that contains cDNAs from 48 different pooled tissues.
[000202] Confocal microscopy
[000203] ZNF554 knock-down and control BeWo and HTR8/SVneo cells cultured in 6-well plates were detached with 0.05% Trypsin (Life Technologies Inc.), washed and resuspended in PBS, and then 4x104 cells were cytospined to Superfrost Plus slides (Fisher Scientific). Then, cells were fixed with 4% paraformaldehyde (Electron Microscopy Sciences, Hatfield, PA, USA), blocked with Protein Block (Dako North America, Inc., Carpinteria, CA, USA), and immunostained with anti-ZNF554 mouse polyclonal antibody (1 :100 dilution, overnight; Abnova) and an AlexaFluor-488 goat anti-mouse antibody (1 :1 ,000 dilution; Life Technologies Inc.). Cells were mounted with ProLong Gold antifade reagent and 4',6-diamidino-2-phenylindole (DAPI; Invitrogen), followed by confocal microscopy using a Leica TCS SP5 MP spectral confocal system (Leica Microsystems).
[000204] Enzyme-linked immunosorbent assays for PAI-1 and TIMP-3
[000205] Concentrations of human plasminogen activator inhibitor-1 (PAI-1) and tissue inhibitor of metalloproteinases-3 (TIMP-3) in HTR8/SVneo cell culture supernatants were measured with sensitive and specific immunoassays (Human PAI-1 ELISA Kit, Invitrogen; TIMP-3 Human ELISA Kit, Abeam Inc., Cambridge, MA, USA) according to the manufacturers' instructions. Standard curves were generated, and sample assay values were extrapolated. The sensitivities of the assays were <30 pg/mL (PAI-1) and <2 pg/ml (TIMP3).
[000206] Cell proliferation assays
[000207] Cell culture supernatants of control and ZNF554 siRNA treated HTR8/SVneo cells were assayed using the CellTiter 96 Aqueous Non-radioactive Cell Proliferation Assay (Promega) according to the manufacturer's instructions.
[000208] Cell migration assay
[000209] The migratory capacity of HTR8/SVneo cells was examined with 8pm-pore transwell inserts (Corning, NY, USA) inserted in 12-well plates similar to described previously. After transfection with ZNF554 or scrambled siRNAs for 24h, 5x105 HTR8/SVneo cells were plated in the upper chambers in a serum-free RPMI-1640 medium, whereas the lower chambers contained a RPMI-1640 medium supplemented with 10% FBS. After incubation for 36h in 2%, 8%, or 20% O2 concentrations, cells on the upper side of the membranes were removed by cotton swab, and the inserts were fixed in methanol for 10min at RT, and washed once with PBS. Then, the membranes were cut out and mounted on Superfrost Plus slides (Fisher Scientific) with ProLong Gold antifade reagent and DAPI (Invitrogen). Comprehensive images of each membrane were taken using a Leica TCS SP5 MP spectral confocal system (Leica Microsystems). The number of invaded cells was quantified using Image-Pro Premier v9.0.2 (Media Cybernetics, Inc., Rockville, MD, USA). The experiment was performed in six replicates.
[000210] Cell invasion assay
[000211] The invasiveness of HTR8/SVneo cells was examined with a Matrigel invasion assay using 8pm-pore cell culture inserts (BD Falcon, Franklin Lakes, NJ, USA) pre-coated with Matrigel (125ng/ml; BD Biosciences, Bedford, MA, USA) and inserted in 24-well plates similar to described previously(60). After transfection with ZNF554 or scrambled siRNAs for 24h, 2x105 cells were plated in the upper chambers in a serum-free RPMI-1640 medium, whereas a RPMI-1640 medium supplemented with 10% FBS was added to the lower chambers. After incubation for 48h in 2%, 8%, or 20% O2 concentrations, cells on the Matrigel side of the membranes were removed by cotton swab, and the membranes were processed as in the migration assay. Comprehensive images taken using the Leica TC5 SP5 spectral confocal system were quantified using Image-Pro Plus 6.2 (Media Cybernetics, Inc.). The experiment was performed in triplicate.
[000212] 5'UTR luciferase assays
[000213] Secreted luciferase activity in HTR8/SVneo cell supernatants was determined by the Secrete-Pair Gaussia Luciferase Assay (Genecopoeia) by mixing 10μΙ of supernatants with 100μΙ of Gaussia Luciferase Assay reagent. The luminescence was immediately measured in a Veritas Microplate Luminometer (Turner BioSystems, Sunnyvale, CA, USA) for 15s/well following a 10s delay in the dark, recorded as relative light units.
[000214] Laser capture microdissection
[000215] Fifteen m sections were cut from snap-frozen placentas (n=100) taken from women in patient groups shown in Table 3 on 2 m Glass Foiled PEN slides (Leica Microsystems). The trophoblast layer of 300-350 villi in each specimen was laser captured by a Leica DM6000B microscope (Leica Microsystems) into 0.5ml microcentrifuge tubes. Captured material was digested with Proteinase K (PicoPure DNA Extraction Kit, Applied Biosystems) at 56°C by overnight incubation. Digestions were stopped at 95°C, and samples were stored at - 70°C until DNA isolation.
[000216] Genomic DNA isolation
[000217] Genomic DNA was isolated from primary trophoblasts, umbilical cord blood leukocytes and laser captured villous trophoblasts with the EZ1 Advanced Nucleic Acid Isolation System using EZ1 DNA Tissue and EZ1 DNA Blood Kits (QIAGEN), and quantified with Quantifiler Human DNA Quantification Kit (Applied Biosystems).
[000218] Primer design and validation [000219] Whole genome shotgun bisulfite sequencing data and MEDIP-Seq data (University of California, San Diego; University of California, San Francisco; Human Reference Epigenome Mapping Project) were visualized by the Epigenome Browser (www.epigenomebrowser.org) and used for the selection of regions of interest. Primer design, targeted amplification and sequencing were done as targeted sequencing service of Zymo Research Corporation (Irvine, CA, USA). For targeted bisulfite sequencing 68 primer pairs were designed and validated. Primers were synthesized by Integrated DNA Technologies, Inc. (Coralville, IA, USA) and underwent quality control (QC), which included duplicate testing for specific amplification of 1ng bisulfite DNA using bisulfite converted human DNA. QC criteria included robust and specific amplification (Cp values <40 cycles and CV <10% for duplicates) of the bisulfite primers on real-time RT-PCR (LightCycler 480 (Roche Diagnostics Corp. Indianapolis, IN, USA).
[000220] Bisulfite conversion, multiplex amplification, bar-coding and adapterization PCR, and next generation sequencing
[000221] Genomic DNA samples from laser captured villous trophoblasts, primary trophoblasts, and umbilical cord blood cells as well as control samples were subjected to sodium bisulfite treatment using the EZ DNA Methylation-Direct Kit (Zymo Research Corp.). For non- methylated control, human DNA was extracted and purified with Quick-gDNA Miniprep Kit (Zymo Research Corp., Irvine, CA, USA) from the HCT116 cell line, which is double knock-out for both DNA methyltransferases DNMT1 (-/-) and DNMT3b (-/-), and thus, contains low level (<5%) of DNA methylation. For methylated control, human DNA was purified similarly from the HCT116 cell line and was enzymatically methylated at all cytosine positions comprising CG dinucleotides by CpG Methylase (Zymo Research Corp.).
[000222] Bisulfite-treated samples and 68 validated primer pairs were subjected to targeted amplification on the 48.48 Access Array System (Fluidigm), using the targeted sequencing service protocol of Zymo Research Corp. Fluidigm's protocols were used for sample loading, harvesting, and pooling, 1 :100 dilution of amplicon pools for each sample, and for amplification using barcoded adapter-linkers (Fluidigm). Reactions were cleaned up using the DNA Clean and Concentrator-5 (Zymo Research Corp.), and products were normalized by concentration and pooled. The Sequencing library was denatured, diluted, and sequenced with a 150-base paired-end run on the MiSeq Benchtop Sequencer (lllumina, San Diego, CA, USA) according to lllumina's protocols.
[000223] Sequence alignment and data analysis
[000224] Sequence reads from bisulphite-treated libraries were identified using standard lllumina base-calling software, and then analyzed using a Zymo Research Corporation's proprietary analysis pipeline. Residual cytosines (Cs) in each read were first converted to thymines (Ts), with each such conversion noted for subsequent analysis. Reads were aligned by Bismark, a Bowtie-based alignment tool for bisulfite converted reads (http:/A/vww.bioinformatics.babraham.ac.uk/projects/download. html#bismark). The number of mismatches in the induced alignment was then counted between the unconverted read and reference, ignoring cases in which a T in the unconverted read was matched to a C in the unconverted reference. For a given read, only the best scored alignment was kept. If there were more than one best read, then only one of them was kept arbitrarily. The methylation level of each sampled cytosine was estimated as the number of reads reporting a C, divided by the total number of reads reporting a C or T. CpGs with coverage of less than four reads were removed from the analysis. The developed sensitive and robust bisulfite sequencing assays yielded a median total sequencing read of 533 (range: 30-1725) per CpG in the trophoblast-fetal blood cell comparison and a median total sequencing read of 136 (range: 4-2609) per CpG in the clinical sample comparison.
[000225] Statistical analyses
[000226] Demographics data were compared by the Fisher's exact test and Mann-Whitney test using SPSS version 12.0 (SPSS). All other data were analyzed in the R statistical environment (www.r-proiect.org).
[000227] Placental microarray: Enrichment analysis of repeat elements present in the 10,000bp upstream region of differentially expressed genes was performed separately for each gene module in preeclampsia versus all genes present on the microarray using the Fisher's exact test. The locations of repeat elements, families and classes were obtained from the "RepeatMasker" table of the UCSC Table Browser (http://genome.ucsc.edu ). P-values of <0.05 were considered significant.
[000228] Placental qRT-PCR: Data were analyzed using the AACt method. The data were first normalized to the reference gene (RPLPO), and the batch effect was adjusted through calibrator samples. Log2 mRNA relative concentrations were obtained for each sample as -
Figure imgf000031_0001
The surrogate gene expression values (-ACtgene) were used to perform a hierarchical clustering with 1-Pearson correlation distance and average linkage. Between group comparisons (in which groups were predefined based on the clinical characteristics of the patients) were performed by fitting a linear model on -ACt values, using as covariates the group variable indicator while allowing for an interaction between the group variable and the maturity status of the fetus (term vs. preterm). Besides these group comparisons, we extended our analysis to include all 100 patients in the validation phase to test for the association between gene expression and mean arterial blood pressure as well as birth-weight percentile while adjusting for gestational age. All variables in the latter analysis were treated as continuous. The association between qRT-PCR gene expression and "maternal underperfusion" score was tested using a linear model. P-values of <0.05 were considered significant. Either at term or preterm, the effect of preeclampsia (with or without SGA) on gene expression was compared with respective controls using the Student's t-test.
[000229] Tissue qRT-PCR array: The expression of ZNF554 relative to RPLPO in the placenta was compared to 47 other human tissues using the Student's t-test. P-values of <0.05 were considered significant.
[000230] Primary trophoblast qRT-PCR: Data were analyzed using the Student's t-test to compare the effect of preeclampsia serum with the effect of control serum on gene expression at Days 1 and 3 of trophoblast differentiation. P-values of <0.05 were considered significant.
[000231] BeWo and HTR8/SVneo cell microarray: Data were analyzed using the Bioconductor packages in R following methodologies described previously. Raw microarray gene expression data was normalized by a quantile normalization approach. A moderated t-test was used to select differentially expressed genes using a cutoff of >1.5 fold-change and <0.1 false discovery rate (FDR). Gene ontology analysis and pathway analysis on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was also performed.
[000232] BeWo cell qRT-PCR: Data were analyzed to compare the effect of ARNT2 or BCL6 overexpression with the effect of control vector overexpression on gene expression in normoxic conditions using a one-way ANOVA model. The same model was used to access the differential effect of ARNT2, BCL6 or GFP overexpression on gene expression in hypoxic or ischemic conditions vs. normoxia. P-values of <0.05 were considered significant. A permutation test was used to measure the statistical significance of the matching between differential gene expression patterns in in vitro and in vivo conditions. Genes were discretized into three states, i.e. up-regulated (UP), down-regulated (DN) or unchanged (NS). For each gene in the two conditions, a score of 1 was assigned for a perfect match of UP/UP or DN/DN, 0 for a neutral match of NS/NS, -1 for a perfect mismatch of UP/DN or DN/UP, and -0.5 for all other patterns. The matching score for any pair of conditions was computed as the sum of all scores for each individual gene. The significance of the scores was assessed via a permutation test. Permutations were exhaustive when feasible, limited to a random sample of 5000 otherwise. The Student's t-test was used to evaluate ZNF554 knock-down efficiency, and the effect of ZNF554 knock-down on gene expression in BeWo cells.
[000233] HTR8/SVneo cell qRT-PCR, immunoassay, cell proliferation, migration and invasion: qRT-PCR data were analyzed using the AACt method relative to RPLPO expression. The Student's t-test was used to evaluate ZNF554 knock-down efficiency in HTR8/SVneo cells, and the effect of ZNF554 knock-down on gene expression and cell proliferation. A linear model was built to quantify the effects of ZNF554 knock-down and various O2 concentrations on the gene expression and protein secretion of HTR8/SVneo cells, as well as their migratory and invasive capacity. O2 concentration was treated as a continuous variable, and the interaction between ZNF554 knock-down and O2 concentrations were included in the model when determined to be significant according to ANOVA. P-values of <0.05 were considered significant.
[000234] Luciferase assays: When analyzing the effect of O2 concentration or ZEB1 overexpression on ZNF554 5'UTR activities, relative luciferase activities were computed normalizing to the GAPDH promoter and presented as relative fold-changes. The Students t-test and ANOVA F-test were used to evaluate statistical significance. A linear model was built to analyze the difference in GAPDH normalized luciferase activities in response to ZEB1 overexpression compared to GFP overexpression among various ZNF554 promoters at different O2 concentrations. P-values of <0.05 were considered significant.
[000235] Next generation sequencing of bisulfite treated genomic DNA: multiple sequencing counts (total and methylated) were summed for each sample at each CpG site, and samples with a total count <4 were dropped from the analysis. The mean methylation ratio in each group was computed for genomic visualization. In the comparison of methylation levels between trophoblasts and cord blood cells, a group sample size of two was considered as a minimum. In order to fit the count data, we used a generalized linear model of Poisson distribution with log link. When all samples in any of the two groups being compared had zero methylation counts, the maximum likelihood estimation of the Poisson model went to infinity. In such cases the Students t-test was used alternatively. For comparisons of methylation levels between the clinical groups, only comparisons with a minimum group sample size of four were considered, and the Wilcoxon rank-sum test was used. Differential methylation was considered to be mild, moderate or strong when p was <0.05 and the difference in methylation ratios was >0.125, >0.25 or >0.5, respectively. The correlation between methylation levels on each CpG in clinical samples and various demographical, clinical or histopathological variables were evaluated by the Pearson, Spearman and Kendall statistics. Since Kendall statistics can also handle the tied values, a Kendall p<0.05 was considered significant.
[000236] RESULTS
[000237] Differentially expressed genes in preeclampsia cluster into major regulatory modules
[000238] Because the pathogenesis of preeclampsia originates from the placenta, new biomarker candidates predominantly expressed in the placenta as well as gene-regulatory networks involved in the placental pathogenesis of preeclampsia with a systems biological approach were sought. Analysis of a microarray dataset revealed 1 ,409 differentially expressed unique genes in preterm preeclampsia compared to preterm controls. From these differentially expressed genes, 137 were found to encode for proteins with functions in transcription regulation (transcription factors, co-activators, or co-repressors). Analysis of BioGPS microarray data and previous evidence revealed 164 genes predominantly expressed in the placenta, from which 157 were present on our microarray platform.
[000239] To identify gene modules and transcription regulatory genes that drive dysregulated placental gene expression, we conducted a WGCNA analysis among differentially expressed genes, and assigned 1 ,403 genes to four major modules containing 506 (green), 442 (red), 381 (blue), and 74 (orange) genes. Most predominantly placental expressed genes belonged to the green (n=22) and red (n=11) modules. The green module was enriched in down-regulated (OR=1.88, p=2.59x10 8) while the red module was enriched in up-regulated genes (OR=6.47, p<2.2x10"16), suggesting the presence of distinct dysregulated gene-networks in preterm preeclampsia.
[000240] Key transcription factors may drive differential expression of placental gene modules associated with high blood pressure and low birth-weight
[000241] Microarray data analyses revealed transcription factors with high co-expression with predominantly placental expressed genes differentially expressed in the placenta. Transcription factors that were expressed at high levels (average log2 intensity >9) and co-expressed (absolute Pearson coefficient >0.8) with the most genes among predominantly placental expressed genes (BCL6, VDR, BHLHE40, ARNT2, JUNB, BTG2, ESRRG, POU5F1 , ZNF554, HLF) were treated as candidates for hub-genes in the module.
[000242] Within the "red module" of differentially expressed genes in the placenta in preeclampsia (which is associated with high blood pressure), BCL6, VDR, BHLHE40, ARNT2, JUNB and BTG2 transcription factor genes had their expression levels most correlated with FLT1 and predominantly placental expressed genes (e.g. LEP, CRH, SIGLEC6). BCL6, a gene implicated in preeclampsia without functional explanation, and ARNT2, part of the hypoxia-inducible transcription regulatory protein complex implicated in the pathogenesis of preeclampsia, were most correlated with FLT1. [000243] Within the "green module" of differentially expressed genes in the placenta in preeclampsia (which is associated with low birth weight), ESRRG, POU5F1 , ZNF554, and HLF transcription factor genes had their expression level most correlated with predominantly placental expressed genes (e.g. PLAC1 , LGALS14, HSD17B1).
[000244] Figure 1. Figure 1A-B shows co-expression matrices of transcription regulatory genes and predominantly placenta expressed genes in the "red and green modules" in placental microarray data. (A) Co-expression matrix shows that within the red module, BCL6, VDR, BHLHE40, ARNT2, JUNB and BTG2 transcription regulatory genes had their expression most correlated with FLT1 and predominantly placenta expressed genes. BCL6 and ARNT2 expression had the highest correlation with that of FLT1. (B) Co-expression matrix shows that within the green module, ESRRG, POU5F1 , ZNF554, and HLF transcription regulatory genes had their expression most correlated with predominantly placenta expressed genes. ESRRG and ZNF554 expression had the highest correlation with that of CSH1 and HSD11 B2, genes strongly implicated in fetal growth.
[000245] Differentially expressed maternal serum proteins may affect placental gene modules
[000246] We examined alterations in maternal serum proteome in early pregnancy in distinct phenotypes of preeclampsia and the potential effects of these changes on the placental transcriptome. Comparing samples from women with preterm preeclampsia and SGA and their respective controls, 19 differentially expressed protein spots could be identified by LC-MS/MS. Many of these proteins function in immune response, blood clotting, lipid transport and metabolism, angiogenesis, blood pressure regulation, and ion transport. Comparing samples from women with term preeclampsia and their respective controls, 14 differentially expressed protein spots could be identified. Many of the identified differentially expressed proteins overlap with those found in preterm preeclampsia, and function in the same pathways. These pathways and 24 out of the 26 differentially expressed proteins identified in total have already been implicated in preeclampsia. However, this is the first proteomics study to detect the activation of the renin-angiotensin system and complement cascade, as well as proinflammatory and metabolic changes in the maternal circulation so early in preeclampsia. It is remarkable that there is a common dysregulation of the maternal serum proteome in term and preterm preeclampsia; however, the extent of changes is larger in the latter in accord with the more fulminant pathogenesis.
[000247] As a link between changes in maternal proteome and placental transcriptome, network analysis revealed connections between 19 differentially expressed serum proteins in preterm preeclampsia and 121 differentially expressed placental genes that were marginally enriched with red module genes (48/121 , OR=1.4, p=0.057). Angiotensinogen had the most connections with differentially expressed genes (n=86, OR=1.9, p=4.9x10 5) and also with red module genes (n=35) including BCL6, followed by plasminogen (n=11) and kininogen-1 (n=9), all involved in blood pressure regulation. Pathway analysis revealed the "renin-angiotensin signaling" as the second top pathway (p=5.2x10- 8) among angiotensinogen-connected differentially expressed genes. We found connections between 14 differentially expressed serum proteins in term preeclampsia and 116 differentially expressed placental genes, which were marginally enriched with red module genes (46/116, OR=1.4, p=0.063). Supporting its key role in the early pathogenesis, angiotensinogen here also had the most connections with differentially expressed genes (n=86, OR=2.5, p=1.6x108) and red module genes (n=35).
[000248] Figure 2. Figure 2A-B shows first trimester maternal serum proteomics changes in preterm preeclampsia. (A) Venn diagram of proteomics data shows that the 19 differentially expressed maternal serum proteins in the first trimester in preterm preeclampsia belong to six functional groups, which are relevant for the pathophysiology of preeclampsia. (B) These 19 serum proteins have connections with 121 differentially expressed placental genes in preeclampsia, among which 48 belong to the "red module" that is dysregulated in association with high blood pressure. Angiotensinogen has more connections than other proteins (OR:1.9, p=4.9x105), and the most connections with red module genes (n=35) including LEP, CRH and FLT1. Seventy seven out of 86 connections of angiotensinogen has a directional effect towards the gene.
[000249] Figure 3. Figure 3A-B shows first trimester maternal serum proteomics changes in term preeclampsia. (A) Venn diagram of proteomics data shows that the 14 differentially expressed maternal serum proteins in term preeclampsia belong to six functional groups, which are relevant for the pathophysiology of preeclampsia. (B) These 14 serum proteins have connections with 116 differentially expressed placental genes in preeclampsia, among which 46 belong to the "red module" that is dysregulated in association with high blood pressure. Angiotensinogen has more connections than other proteins (OR:2.5, p=1.6x108) and the most with red module genes (n=35). Seventy seven out of 86 connections of angiotensinogen have a directional effect towards the gene.
[000250] Validation of placental differential expression of transcription factors and target genes
[000251] To validate microarray results on a large patient population with different ethnic origin and with various subtypes of preeclampsia (preterm and term, with or without SGA), 47 genes for high throughput expression profiling were selected as described in PCT/US13/45709. It was found that qRT-PCR data validated microarray results in 72% (34/47 genes).
[000252] Factors that drive the dysregulation of red and green modules in the trophoblast
[000253] To test the effect of maternal blood on the trophoblast at various phases of differentiation, we treated primary trophoblasts with first trimester sera from women with preterm preeclampsia or controls. Preeclampsia vs. control serum induced the up-regulation of seven placental differentially expressed genes on Days 1 and 3 of trophoblast differentiation, including FLT1 , JUNB and LEP. Six of these genes were up-regulated in the placenta in term preeclampsia and three in preterm preeclampsia.
[000254] Because of the dynamically changing transcriptome of primary trophoblasts in culture and the difficulties in transfecting these cells, we used BeWo cells to test the effect of hypoxia or ischemia alone or in combination with the overexpression of transcription factors up- regulated in the placenta in preterm preeclampsia.
[000255] ARNT2 and BCL6 overexpression in normoxic BeWo cells or hypoxia itself induced the dysregulation of only five placental differentially expressed genes.
[000256] Hypoxia combined with ARNT2 or BCL6 overexpression led to the dysregulation of a large number of genes. There were 9 genes (6 in the red and 3 in the green modules) dysregulated in BeWo cells, including FLT1, ARNT2, and ZNF554, similarly as in the placenta in preeclampsia. In addition, 12 genes were dysregulated in BeWo cells but not in the placenta and 6 genes were dysregulated in BeWo cells in the opposite direction as in the placenta.
[000257] Ischemia induced the dysregulation of only three genes in BeWo cells similar to that in preeclampsia.
[000258] However, ischemia combined with ARNT2 or BCL6 overexpression led to the similar dysregulation of 11 genes (5 in the red and 3 in the green modules), including LEP, FLT1 , ENG, and ARNT2, similar to that in preeclampsia.
[000259] A permutation test showed that ARNT2 overexpression, both in hypoxia or ischemia, mimicked the up-regulation of red module genes in preeclampsia. BCL6 overexpression in ischemia mimicked the overall expression changes of red and green module genes in preterm preeclampsia. In this condition ARNT2 was up-regulated, probably mediating the up-regulation of red module genes.
[000260] In summary, our data suggest that 1) serum factors up-regulate red module genes in preeclampsia; 2) BCL6 induces ARNT2 overexpression; 3) the up-regulation of these transcription regulatory genes sensitize the trophoblast to ischemia and lead to the dysregulation of red and green gene modules in preterm preeclampsia; and 4) altered trophoblastic DNA methylation may be upstream to these changes, since 5-azacitidin treatment down-regulated BCL6 in BeWo cells.
[000261] Figure 4. Figure 4A-E shows in vitro modeling of the placental dysregulation of gene modules in preeclampsia. (A) Hierarchical clustering of expression data for 47 genes in 100 placental specimens and a heatmap representing differential gene expression in term or preterm subgroups of preeclampsia compared to respective controls. (B) Preterm preeclampsia serum induced the up-regulation of seven placental dysregulated genes in primary trophoblasts, among which six were up-regulated in term and three in preterm preeclampsia. (C) The overexpression of ARNT2 or BCL6 in normoxic BeWo cells induced the dysregulation of five genes dysregulated in preeclampsia. (D) Hypoxia induced the dysregulation of five genes dysregulated in preeclampsia. Hypoxia combined with ARNT2 or BCL6 overexpression led to the dysregulation of a large number of genes. (E) Ischemia itself induced the dysregulation of only three genes in BeWo cells similar to that in the placenta in preeclampsia. Ischemia combined with ARNT2 or BCL6 overexpression led to the dysregulation of 11 genes similar to preeclampsia. (D) and (E) represents comparisons of gene expressions between hypoxia/ischemia vs. normoxia. In (A-E), stars depict significant changes, "0" depicts "overexpressed", and color bar encodes signed (up or down)-fold changes. Black boxes depict genes with similar expression changes in vitro as in the placenta in preeclampsia.
[000262] Figure 5. Figure 5 shows BCL6 expression in BeWo cells after various treatments with 5-azacitidin and Forskolin. Decreased BCL6 expression was observed in BeWo cells upon treatment with 5-azacitidin (5-AZA) irrespective of Forskolin (FRSK) co-treatment.
[000263] Figure 6. Figure 6 summarizes the obtained data showing that serum factors and epigenetic changes modify BCL6 expression upstream of ARNT2, and the overexpression of these transcription factors leads to trophoblast sensitization to hypoxic/ischemic stress, and the consequent dysregulation of red and green modules, mostly in preterm preeclampsia.
[000264] The effect of ZNF554 down-regulation in the villous trophoblast
[000265] We also looked for regulatory elements in the genome that may additionally drive placental dysregulation of gene networks in preeclampsia. Since the insertion of transposable elements into genes and their regulatory regions can lead to transcriptional changes, and the placenta is a frequent site of transposable elements co-option, we analyzed placental microarray data for the enrichment of transposable elements in the 10kb 5'UTRs of differentially expressed genes in the red and green modules. Interestingly, endogenous retroviral elements had top enrichments in both comparisons. Among the red module genes, the MER34-int element had the highest odds for preeclampsia (OR=20.3, p=1.27x10-5), while the LTR10A element had the highest odds among the green module (OR=17.4, p=1.27x10 7).
[000266] Of note, several copies of LTR1 OA-fragments were found in the 10kb5'UTR of ZNF554, one of the hub-genes in the green module. Since LTR10A drives placenta-specific expression of NOS3, we hypothesized that ZNF554 may also have placenta-specific expression.
[000267] Indeed, tissue qRT-PCR array revealed that ZNF554 had predominant placental expression, remarkably higher than in 46 tissues except the brain (=89% of placental expression).
[000268] In situ hybridization and immunostainings of third and first trimester villous placentas showed dominant ZNF554 expression in the cytoplasm and nucleus of the syncytiotrophoblast.
[000269] In accord, ZNF554 expression was up-regulated during villous trophoblast differentiation similar to CSH1.
[000270] Of importance, ZNF554 immunostaining was faint in the syncytiotrophoblast in preeclampsia compared to controls.
[000271] To characterize the loss of syncytiotrophoblastic ZNF554 function, we silenced ZNF554 in BeWo cells. At 74% ZNF554 knockdown (p=5.24x10 6), decreased nuclear and cytoplasmic ZNF554 immunostainings were found.
[000272] Microarray analyses revealed 123 differentially expressed genes including 9 differentially expressed placental genes in preeclampsia, and the dysregulation of the 'glycolysis/gluconeogenesis' pathway (OR:7.8, FDR=0.06) and 18 molecular functions including 'RNA binding' (down) and 'activin binding' (up).
[000273] The up-regulation of FSTL3 was confirmed by qRT-PCR (2.7-fold, p<0.001). Of note, FSTL3 encodes a secreted glycoprotein, which binds and inactivates activin and other TGF ligands, and it's up-regulation in the preeclamptic placenta is associated with low birth- weight.
[000274] Figure 7. Figure 7 shows tissue qRT-PCR array data that revealed the highest ZNF554 expression in the placenta among 48 human tissues.
[000275] Figure 8. Figure 8A-B shows ZNF554 expression in the placenta. (A) In situ hybridization of a third trimester placenta (GW29) and (B) immunohistochemistry of a first trimester placenta (GW12) shows mainly syncytiotrophoblastic ZNF554 expression (1400x and 400x magnifications). Black or white arrowheads depict syncytiotrophoblast or cytotrophoblast, while black arrow depicts fetal endothelium, respectively. [000276] Figure 9. Figure 9 shows qRT-PCR data depicting that ZNF554 expression is up-regulated during villous cytotrophoblast differentiation in parallel with CSH1.
[000277] Figure 10. Figure 10A-B shows ZNF554 expression in the placenta. ZNF554 immunopositivity was faint in the syncytiotrophoblast in (B) preeclampsia (GW35) compared to (A) gestational-age matched controls (GW36). Arrow and arrowhead depict syncytiotrophoblast and fetal endothelium, respectively (400x magnifications).
[000278] Figure 11. Figure 11A-E shows in vitro gene expression data of BeWo cells after ZNF554 knock-down. (A) ZNF554 mRNA expression was 74% lower in ZNF554 siRNA-treated BeWo cells compared to control cells used for the microarray (ρ=5.24χ10 6). (B) Nuclear and cytoplasmic ZNF554 immunofluorescence decreased in BeWo cells treated with ZNF554 siRNA compared to control cells. (C) Bioinformatics analyses revealed the glycolysis / gluconeogenesis pathway, RNA, nucleic acid and activin binding to be affected in ZNF554 knock-down BeWo cells. (D) qRT-PCR validated FSTL3 up-regulation (2.7-fold, p<0.001) in BeWo cells upon ZNF554 knock-down.
[000279] The effect of ZNF554 down-regulation in the extravillous trophoblast
[000280] Interestingly, immunostainings also showed that cytokeratin-7 positive invasive extravillous trophoblasts in first and third trimester maternal decidua express ZNF554. Importantly, ZNF554 positive intraluminal and endovascular trophoblasts were found in the wall of transformed spiral arteries, and ZNF554 immunostainings in extravillous trophoblasts were weaker in preeclampsia than in controls.
[000281] To characterize the loss of extravillous trophoblastic ZNF55 function, we silenced ZNF554 in HTR8/SVneo extravillous trophoblastic cells. At 87% knock-down (p<0.001), we observed decreased nuclear and cytoplasmic ZNF554 immunostainings.
[000282] Microarray analysis showed 185 differentially expressed genes including 18 differentially expressed placental genes in preeclampsia. Importantly, only 18 out of 185 genes were also dysregulated in ZNF554-silenced BeWo cells, suggesting that ZNF554 is involved in the regulation of different functions in villous and extravillous trophoblast.
[000283] Pathway analyses showed 16 molecular functions dysregulated, including 'cyclin-dependent protein kinase regulator activity', 'metalloendopeptidase inhibitor activity', and 'insulin-like growth factor binding'. The 67 enriched biological processes included 'regulation of growth', 'smooth muscle cell migration', 'smooth muscle cell-matrix adhesion', 'response to oxygen levels', all relevant to trophoblast invasion and placental pathogenesis of preeclampsia.
[000284] The dysregulation of eight selected genes was confirmed by qRT-PCR. Two genes (CDKN1A, STK40) are involved in the regulation of cell proliferation and differentiation, and proliferation assays indeed showed that ZNF554 knock-down slightly decreased cell proliferation after 48h (-14%, p=0.02). Six other genes (FSTL3, ITGB5, MYL12A, SDC1 , SERPINE1, TIMP3) encode for proteins involved in cell-adhesion, migration and invasion. Interestingly, the effect of ZNF554 knock-down was significant regardless of O2 concentrations in case of four genes, while there was a significant interaction between O2 concentrations and ZNF554 silencing in case of two genes.
[000285] The up-regulation of PAI-1 and TIMP-3 was also confirmed at the protein level in supernatants of ZNF554-silenced cells. Both proteins have an inhibitory function on cell migration and invasion, and TIMP-3 is the major tissue metalloproteinase inhibitor at the maternal-fetal interface, which is up-regulated in preeclampsia.
[000286] All these data suggested reduced migratory and invasive functions of ZNF554-silenced cells. Indeed, functional assays revealed that ZNF554 silencing had a strong inhibitory effect on trophoblast migration (p=1.9x10 10) and invasion (p<0.001).
[000287] Figure 12. Figure 12A-B shows ZNF554 immunostainings in first and third trimester placentas. (A) Extravillous trophoblasts in the trophoblastic columns (GW12) and (B) endovascular and intraluminal trophoblasts in the myometrium (GW36) were immunostained for cytokeratin-7 (left) and ZNF554 (right). Arrows depict the direction of trophoblst invasion in trophoblastic columns, black and white arrowheads point to trophoblasts in the wall and lumen of a spiral artery (serial sections, 200x magnifications).
[000288] Figure 13. Figure 13A-B shows that ZNF554 immunostainings in decidual extravillous trophoblasts (arrowheads) and syncytiotrophoblats (arrows) were weaker in (B) preeclampsia (GW35) than in (A) controls (GW36) (serial sections, 200x magnifications). [000289] Figure 14. Figure 14 shows in vitro gene expression data of HTR8/SVneo cells after ZNF554 knock-down. (A) At 87% ZNF554 mRNA knock-down (p<0.001), (B) ZNF554 immunofluorescence was weaker in the nucleus and cytoplasm of ZNF554 knock-down (left) than control (right) HTR8/SVneo cells.
[000290] Figure 15. Figure 15 shows the effect of ZNF554 knock-down on cell proliferation in HTR8/SVneo cells. (A) ZNF554 knock-down slightly but significantly decreased cell proliferation after 48h (-14%, p=0.02). Y-axis depicts viable cell number, X-axis shows incubation time. (B) The differential expression of CDKN1A and STK40 (genes involved in the regulation of cell cycle) upon ZNF554 knock-down was confirmed by qRT-PCR. Oxygen concentrations are shown below the bars.
[000291] Figure 16. Figure 16 shows the effect of ZNF554 knock-down on gene expression in HTR8/SVneo cells. The dysregulation of selected genes upon ZNF554 knock-down was confirmed by qRT-PCR. Oxygen concentrations are shown below the bars.
[000292] Figure 17. Figure 17 shows the effect of ZNF554 knock-down on protein secretion from HTR8/SVneo cells. The increased secretion of SERPINE (PAI-1) and TIMP3 from ZNF554 knock-down cells was confirmed by ELISA. Oxygen concentrations are shown below the bars.
[000293] Figure 18. Figure 18 shows the effect of ZNF554 knock-down on the migratory and invasive capacity of HTR8/SVneo cells. ZNF554 knock-down cells had remarkably decreased invasive (left) and migratory (right) characteristics. Oxygen concentrations are shown below the bars.
[000294] The evolutionary origins of deep trophoblast invasion in humans and its failure in preeclampsia
[000295] Because of the critical role of ZNF554 in trophoblast invasion, we investigated the mechanisms regulating ZNF554 expression and the evolutionary changes in this pathway leading to deep trophoblast invasion in humans. Comparison of genomic sequences from 100 species showed a rapid evolution of the ZNF554 5'UTR in simians compared to prosimians mediated by the insertion of an LTR10A and three primate-specific Alu TEs. Among these, AluY was inserted in apes, fragmenting LTR10A. Manual annotation revealed 16 copies of an LTR10A-fragment expanded in humans. AluY and LTR10A contains a large number of predicted ZEB1 binding sites and hypoxia response elements (HREs), suggesting that human ZNF554 is regulated by hypoxia and ZEB1 , a TF involved in epithelial-mesenchymal transition and invasion of the trophoblast.
[000296] In accord with these, luciferase assays showed that ZEB1 vs. GFP co-transfection led to a 3.3-fold increase (p=0.001) in human
ZNF554 5'UTR activity (Fig. 6b). Although the change in O2 levels itself did not affect luciferase activity, hypoxia compared to 8%02 increased it (+25%, p<0.01) when ZEB1 was overexpressed, suggesting ZEB1-HIFa interaction in human ZNF554 regulation.
[000297] In agreement with the expansion of putative ZEB1 binding sites in the human ZNF554 5'UTR, the overexpression of ZEB1 led to a higher luciferase activity of the human than the macaque (22%, p<0.01) and orangutan (25%, p<0.01) 5'UTRs at 8%02.
[000298] In accord with the expansion of putative HREs in ape and human 5'UTRs compared to old world monkeys, the macaque 5'UTR activity did not differ between hypoxia and 8%02, while the orangutan 5'UTR activity was higher in hypoxia than in 8%02 (+28%, p<0.01), and the human 5'UTR activity was the highest in hypoxia (+60% vs. macaque, p<0.00001 ; +22% vs. orangutan, p<0.01).
[000299] Our data support the findings on the deeper endovascular trophoblast invasion (~8%02) in humans than in old world monkeys, and the deep interstitial trophoblast invasion in humans and great apes (~2%02) and its lack in old world monkeys.
[000300] Figure 19. Figure 19. Figure 19A-D shows the evolutionary origins of deep trophoblast invasion in humans. (A) The ~3kb human ZNF554 5'UTR (black line) contains an AluSq2, AluY and several LTR10A fragments (shown below). These TEs harbor several predicted hypoxia-response elements (HREs, shown above) and ZEB1 binding sites. (B) Luciferase assays showed that ZEB1 vs. GFP co-transfection led to a 3.3-fold increase (p=0.001) in human ZNF554 5'UTR activity, while O2 concentration itself did not affect the human 5'UTR activity. (C) The AluY was inserted into ZNF554 5'UTR in apes, expanding HREs and fragmenting LTR10A. An LTR10A fragment multiplicated to 16 copies in humans, expanding ZEB1 binding sites. Position of two HREs located on hypermethylated CpGs in preeclampsia are shown with asterisk; one is only conserved in humans and orangutan. (D) Hypoxia vs. 8%02 increased the human 5'UTR activity (+25%, p<0.01) when ZEB1 was overexpressed, suggesting ZEB1-HIFa interaction in ZNF554 regulation. Upon ZEB1 vs. GFP co-transfection, there were higher luciferase activity ratios of the human than the macaque (22%, p<0.01) or orangutan (25%, p<0.01) 5'UTRs at 8%02. The macaque 5'UTR activity ratio did not differ between hypoxia and 8%02, the orangutan 5'UTR activity ratio was higher in hypoxia than in 8%02 (+28%, p<0.01), and the human 5'UTR activity ratio was the highest in hypoxia (+60% vs. macaque, p<0.00001; +22% vs. orangutan, p<0.01).
[000301] Identification of differentially methylated genes and genomic regions in preeclampsia
[000302] Next, we tested whether the expression of the investigated 47 genes in our study or their differential expression in preeclampsia can be regulated by DNA methylation in the trophoblast. BeWo cells were treated with 5-azacitidin, and gene expression changes compared to control cells were tested with qRT-PCR. From the 47 investigated genes, the expression of 37 was changed significantly by the DNA methylase inhibitor, suggesting their regulation through DNA methylation in the trophoblast. Therefore, these genes (ARNT2, BCL3, BCL6, BTG2, CDKN1A, CGB3, CLC, CSH1 , CYP19A1 , DUSP1 , ENG, ERVFRDE1 , ERVWE1 , ESRRG, FLT1, GATA2, GCM1 , GH2, HSD11 B2, HSD17B1 , IKBKB, INSL4, JUNB, LEP, LGALS13, LGALS14, LGALS16, MAPK13, PAPPA2, PGF, PLAC1 , SIGLEC6, TFAM, TFAP2A, TPBG, VDR, ZNF554) were identified as potential epigenetic biomarker candidates.
[000303] We selected five genes (BCL6, LGALS13, LGALS14, LGALS16, ZNF554) for further testing in order to get insights where the differential methylation occurred in these genes. Whole genome shotgun bisulfite sequencing data and MEDIP-Seq data (University of California, San Diego; University of California, San Francisco; Human Reference Epigenome Mapping Project) were visualized by the Epigenome Browser (www.epigenomebrowser.org) and used for the selection of regions of interest.
[000304] We investigated differentially methylated regions (DMRs) in the intragenic regions of LGALS13, LGALS14 and LGALS16 between primary trophoblasts and cord blood cells to reveal the impact of trophoblastic development on DNA methylation marks and potential sites for differential methylation in preeclampsia. We designed amplicons for the most methylated intragenic regions of the three cluster galectin genes, and developed sensitive and robust bisulfite sequencing assays.
[000305] The regions surrounding the transcription start sites (chr19:40092733-40094949, chr19:40195141-40195294, chr19:40146432- 40146582) and the 3' ends (chr19:40097498-40097938, chr19:40199604-40199946, chr19:40150504-40151073) of LGALS13, LGALS14 and LGALS16 were strongly or moderately hypomethylated in cytotrophoblasts compared to cord blood cells. In addition, the regions chr19:40095887-chr19:40095964 (LGALS13), chr19:40196517-chr19:40196520 (LGALS14), and chr19:40148945-chr19:40149412 (LGALS16) were also differentially methylated.
[000306] There was mainly mild difference in methylation in all three genes between the cytotrophoblast and syncytiotrophoblast. DMRs included chr19:40093255-chr19:40093612, chr19:40094910-chr19:40094949 and chr19:40095758-chr19:40095887 (LGALS13); chr19:40193506-chr19:40193558, chr19:40194326-chr19:40194732 and chr19 :40199590-chr19 :40199946 (LGALS14); chr19:40148945- chr19:40149035 and chr19:40150504-chr19:40151073 (LGALS16).
[000307] These results suggest that the hypomethylation of DMRs around the transcription start sites in these genes may allow active transcription. This permissive status is already present in the cytotrophoblast, and the increase in the expression of key transcription factors during trophoblast differentiation drives mainly the expression of cluster galectin genes.
[000308] Next, we tested whether the developmental differences in galectin gene DNA methylation may play a role in their dysregulated expression in preeclampsia. We laser-captured villous trophoblasts from the same placentas that were examined by qRT-PCR, isolated genomic DNA and subjected to bisulfite sequencing.
[000309] We compared DNA methylation status of samples from women in various group comparisons (preeclampsia with or without SGA, term or preterm and gestational age matched controls), and found differential methylation for five CpGs in LGALS13 (chr19:40093427, chr19:40093547, chr19:40093612, chr19:40095758, chr19:40097901), six CpGs in LGALS14 (chr19:40195294, chr19:40196416, chr19:40196625, chr19:40199675, chr19:40196610, chr19:40199582), and five CpGs in LGALS16 (chr19:40149169, chr19:40149184, chr19:40149187, chr19:40149205, chr19:40150916).
[000310] Subsequently, we aimed to reveal DMRs in the first intron of BCL6 between trophoblasts and non-trophoblastic fetal cells, cytotrophoblast and syncytiotrophoblast, and trophoblast samples obtained from women with preeclampsia and gestational age-matched controls.
[000311] Next generation bisulfite sequencing revealed that within this region, chr3: 187458083-187458651 contains 10 hypermethylated CpGs and chr3:187460304-187460374 contains two hypermethylated CpGs between cytotrophoblasts compared to fetal whole blood cells. We also found differentially methylated CpGs in the following regions: chr3:187456334-chr3:187456336, chr3:187458163-chr3:187458589.
[000312] Subsequent sequencing of genomic DNA isolated from laser captured villous trophoblasts from placentas used in the validation qRT-PCR study revealed three CpGs (Chr3:187458095, Chr3: 187458163, Chr3:187458327) to be differentially methylated between preeclampsia patients and controls. Out of these, the differential methylation of CpG at Chr3:187458163 was relevant to preterm preeclampsia. Interestingly, the correlation between methylation levels and gene expression was significant in case of another CpG at Chr3: 187458584 (R=-0.41 , p<0.001). These results collectively suggested that the differential methylation may have a role in the dysregulation of BCL6 in preeclampsia.
[000313] Next, we aimed to reveal DMRs in the 5'UTR of ZNF554 between trophoblasts and non-trophoblastic fetal cells, cytotrophoblast and syncytiotrophoblast, and trophoblast samples obtained from women with preeclampsia and gestational age-matched controls.
[000314] Next generation bisulfite sequencing revealed DMRs in the chr19:2818782-chr19:2819449 and chr19:2819980-chr19 :2819993 regions between fetal whole blood cells and the trophoblast.
[000315] The chr19:2818789-chr19:2818880 region was differentially methulated between cytotrophoblast and syncytiotrophoblast.
[000316] Sequencing of genomic DNA isolated from laser captured villous trophoblasts from placentas used in the validation qRT-PCR study revealed four CpGs (chr19:2818823, 2818864, 2818868 and 2818876) hypermethylated in preeclampsia patients compared to controls, with highest methylation in cases associated with SGA. Importantly, we found correlation between Chr19:2818823 CpG methylation and ZNF554 expression (R=-0.30, p=0.04), maternal underpefusion score of the placenta (R=0.36, p=0.03), and birth-weight percentile (R=- 0.41 , p<0.01).
[000317] Notable, these four CpGs hypermethylated in preeclampsia are located on or around two putative HREs, out of which the one located on Chr19:2818823 CpG is conserved in humans and orangutan. These data collectively provide evidence that AluY insertion, along with additional evolutionary changes in the ZNF554 5'UTR, have been key for the ZNF554-mediated deep trophoblast invasion, and the hypermethylation of AluY interfering with these mechanisms results in low ZNF554 expression, impaired trophoblast invasion, and preeclampsia.
[000318] Figure 20. Figure 20 shows the origins of impaired trophoblast invasion and preeclampsia. The insertion of the AluY in the ZNF554 5'UTR, along with additional evolutionary changes, introduced several putative HREs and ZEB1 binding sites, contributing to the increased invasiveness of extravillous trophoblasts and deep trophoblast invasion. The methylation of certain CpGs at two HREs in AluY in the trophoblast inhibits the mechanisms of deep trophoblast invasion, and promotes the development of preeclampsia.
[000319] Figure 21. Figure 21 shows gene expression changes in BeWo cells upon 5-azacitidin treatment and Forskolin co-treatment. There were 37 genes that had differential expression upon treatment with 5-azacitidin (5-AZA), with or without Forskolin (FRSK) co-treatment, suggesting their regulation by DNA methylation in the trophoblast.
[000320] Figure 22. Figure 22. summarizes the identified epigenetic biomarker genes and biomarker candidate regions for preeclampsia and closely related complications of pregnancy. The listed 37 genes had differential methylation and consequent differential expression upon 5-azacitidin treatment in BeWo cells. Five out of these 37 genes were further characterized for differential methylation in primary trophoblasts, cord blood cells, and laser captured trophoblasts. The genomic regions with differential methylation in the three comparisons are shown in the figure and treated as biomarker candidates.
[000321] Identification of potential targets for therapies of preeclampsia and closely related complications of pregnancy
[000322] Differentially expressed maternal serum proteins with the most connections with differentially expressed genes in the placenta, as well as differentially expressed serum proteins with functions most relevant to the pathogenesis of preeclampsia were identified key therapeutic targets, since they are located in pathways or upstream of pathways important in the pathogenesis of preeclampsia. The inhibition or activation of their differential expression or function can be the basis of preventive or therapeutic approaches.
[000323] Differentially expressed transcription factors with the most co-expressions with predominantly placental expressed genes differentially expressed in the placenta as well as differentially expressed genes with functions most relevant to the pathogenesis of preeclampsia were identified as key therapeutic targets, since they may drive differential placental gene expression in preeclampsia. The inhibition or activation of their differential expression or function can be the basis of preventive or therapeutic approaches.
[000324] Figure 23. Figure 23 summarizes the potential therapeutic target molecules identified by the proteomics study, their observed mechanism of dysregulation in preeclampsia, and the required effect of the therapeutics.
[000325] Figure 24. Figure 24 summarizes the potential therapeutic target molecules identified by the transcriptomics study, their observed mechanism of dysregulation in preeclampsia, and the required effect of the therapeutics.
[000326] The definition of new pathways of disease and molecular mechanisms in preeclampsia
[000327] Preeclampsia has various etiologies and phenotypes, and the lack of insights into the molecular mechanisms of the origins of this complex syndrome has prevented the development of early diagnostic, preventive and therapeutic tools. Our systems biology study identified and modeled early molecular pathways leading to the hallmark pathologies of preeclampsia, and paved the way for its molecular taxonomy.
[000328] Here we define the "molecular phase" of preeclampsia, where early pathologic events can already be detected by maternal blood and trophoblast-derived biomarkers, and targeted preventive and therapeutic approaches can be tailored by molecular phenotyping using multi-biomarker profiles.
[000329] In this phase, characteristic alterations in the maternal proteome can already be observed in preterm and term preeclampsia, suggesting a paradigm shift, as pro-inflammatory pathways in the maternal circulation are upstream of placental injury and dysfunction, not only downstream as described before. Our in silico and in vivo data corroborate evidence from experimental data, suggesting that the activation of the complement and renin-angiotensin systems in early pregnancy has key role in the pathology. In addition, the observed dysregulation of maternal metabolic pathways supports previous predictions on antenatal metabolic syndrome as a trigger of preeclampsia.
[000330] Our in vitro data confirm that these proteomic alterations in maternal blood can induce trophoblastic functional changes leading to the overproduction of sFlt-1 and an anti-angiogenic state through a trajectory that does not necessarily affect fetal growth. Indeed, epidemiologic and placental histopathological studies showed that placental anatomy and fetal growth is mostly not affected in term preeclampsia, while severely impacting cases of early-onset preeclampsia.
[000331] This phenomenon is also explained by another key observation of this study showing that distinct placental gene modules are associated with changes in blood pressure and birth-weight, implying that different molecular pathways are responsible for the trophoblastic dysfunction leading to impaired trophoblast invasion and the overproduction of anti-angiogenic molecules.
[000332] This study identified a central molecular pathway of deep trophoblast invasion in humans and its evolutionary roots in the insertion of TEs and the consequent co-option of HREs and ZEB1 binding sites into the 5'UTR of ZNF554. In accordance with ENCODE project discoveries, these findings point to the importance of the formerly known "junk DNA" in shaping the transcriptomic landscape and function of the trophoblast, leading to unique characteristics of human pregnancy. [000333] These data do not only elucidate why interstitial trophoblast invasion is the deepest in humans among anthropoids, but also provide evidence for the epigenetic dysregulation of this "ZNF554 pathway" as key component in impaired trophoblast invasion. Since we observed that the hypermethylation of CpGs at or around putative HREs conserved in humans and great apes are in strong correlation with placental pathology and birth-weight, the role of hypoxia regulating trophoblast invasion is proposed.
[000334] Another key observation is that several down-regulated green module genes besides ZNF554 are regulators of fetal growth and metabolism, implying impaired villous trophoblast functions in fetal growth restriction besides pathways originated from abnormal trophoblast invasion and consequent placental endoplasmic reticulum stress. The down-regulation of some of the affected green module genes in the first trimester confirms that this pathologic pathway is operational in early pregnancy.
[000335] Our in vivo and in vitro data that the red gene module associated with blood pressure elevation is not only up-regulated by alterations in maternal blood proteome but also by the overproduction of BCL6 and ARNT2 due to epigenetic background is also of importance. In vitro data showed that the up-regulation of this "BCL6-ARNT2 pathway" sensitizes the trophoblast to ischemia, and increases FLT1 and decreases PIGF expression. These changes are only observed in the placenta in preterm preeclampsia, suggesting that the dysregulation of this pathway promotes the earlier development of the preclinical phase of preeclampsia in conjunction with the placental release of pro-inflammatory molecules and trophoblastic debris.
[000336] In conclusion, our study suggest that the interplay of the described distinct pathomechanisms, and also others that have not been investigated herein, lead to the complex and "personalized" pathogenesis of preeclampsia. The effect of maternal immune, metabolic, hormonal and nutritional milieu, the offspring's genetic and epigenetic makeup, the local environment in the gestational sac, infections and other environmental factors are all pivotal in determining the exact pathogenesis and phenotype. Because of the complexity of the problem, only systems biological approaches such as ours can further characterize in details the uncovered molecular pathways of preeclampsia.
[000337] Figure 25. Figure 25 describes pathologic pathways in preeclampsia. In the newly defined "molecular phase" of preeclampsia, characteristic alterations in the maternal proteome can be observed, supporting that the activation of the complement and renin-angiotensin systems as well as maternal metabolic pathways have key role in triggering early pathologic events. These alterations in maternal blood can induce trophoblastic functional changes leading to the overproduction of sFlt-1 and an anti-angiogenic state through a trajectory that does not necessarily affect fetal growth. This phenomenon is explained by that distinct placental gene modules are associated with changes in blood pressure and birth-weight, implying that different molecular pathways are responsible for impaired trophoblast invasion and trophoblastic overproduction of anti-angiogenic molecules. The "ZNF554" pathway have evolved in great apes to support deep trophoblast invasion, and the epigenetic dysregulation of this pathway is a key component in impaired trophoblast invasion in preeclampsia. The down- regulation of ZNF554 and other green module genes involved in the regulation of fetal growth and metabolism imply impaired villous trophoblast functions in fetal growth restriction besides pathways originated from abnormal trophoblast invasion and consequent placental endoplasmic reticulum stress. The red gene module associated with blood pressure elevation is not only up-regulated by alterations in maternal blood proteome but also by the overproduction of BCL6 and ARNT2 due to epigenetic background. The up-regulation of this "BCL6-ARNT2 pathway" sensitizes the trophoblast to ischemia, and increases FLT1 and decreases PIGF expression. These changes are only observed in the placenta in preterm preeclampsia, suggesting that the dysregulation of this pathway promotes the earlier development of the preclinical phase of preeclampsia in conjunction with the placental release of pro-inflammatory molecules and trophoblastic debris. The interplay of these distinct pathomechanisms lead to the complex and "personalized" pathogenesis of preeclampsia.
[000338] Unless otherwise indicated, all numbers expressing quantities of ingredients, properties such as molecular weight, reaction conditions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term "about." Accordingly, unless indicated to the contrary, the numerical parameters set forth in the specification and attached claims are approximations that may vary depending upon the desired properties sought to be obtained by the present disclosure. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. Any numerical value, however, inherently contains certain errors necessarily resulting from the standard deviation found in their respective testing measurements.
[000339] The terms "a," "an," "the" and similar referents used in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. Recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., "such as") provided herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
[000340] Groupings of alternative elements or embodiments of the invention disclosed herein are not to be construed as limitations. Each group member may be referred to and claimed individually or in any combination with other members of the group or other elements found herein. It is anticipated that one or more members of a group may be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is deemed to contain the group as modified thus fulfilling the written description of all Markush groups used in the appended claims.
[000341] Certain embodiments of this invention are described herein, including the best mode known to the inventors for carrying out the invention. Of course, variations on these described embodiments will become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventor expects skilled artisans to employ such variations as appropriate, and the inventors intend for the invention to be practiced otherwise than specifically described herein. Accordingly, this invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context.
[000342] Specific embodiments disclosed herein may be further limited in the claims using consisting of or consisting essentially of language. When used in the claims, whether as filed or added per amendment, the transition term "consisting of excludes any element, step, or ingredient not specified in the claims. The transition term "consisting essentially of limits the scope of a claim to the specified materials or steps and those that do not materially affect the basic and novel characteristic(s). Embodiments of the invention so claimed are inherently or expressly described and enabled herein.
[000343] Furthermore, numerous references have been made to patents and printed publications throughout this specification. Each of the above-cited references and printed publications are individually incorporated herein by reference in their entirety.
[000344] In closing, it is to be understood that the embodiments of the invention disclosed herein are illustrative of the principles of the present invention. Other modifications that may be employed are within the scope of the invention. Thus, by way of example, but not of limitation, alternative configurations of the present invention may be utilized in accordance with the teachings herein. Accordingly, the present invention is not limited to that precisely as shown and described.

Claims

1. A method for assessing the presence or risk of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in a female to determine the need for a treatment regimen comprising:
a) determining DNA methylation status of one or more of ZNF554; ARNT2; BCL3; BCL6; BTG2; CDKN1A; CGB3; CLC; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FLT1 ; GATA2; GCM1 ; GH2; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; LEP; LGALS13; LGALS14; LGALS16; MAPK13; PAPPA2; PGF; PLAC1; SIGLEC6; TFAM; TFAP2A; TPBG; or VDR in a biological sample obtained from the female;
b) generating a dataset based on the determined DNA methylation status;
c) assessing the presence or risk of developing preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in the female based on the dataset; and
d) determining a treatment regimen based on the assessed presence or risk.
2. A method according to claim 1 , wherein the assaying is performed for the levels of all markers described above.
3. A method according to claim 1 , wherein the assaying is performed for the levels of at least three biomarkers.
4. A method according to claim 1, wherein the assaying is performed for the levels of at least one marker described in the figures and examples described herein.
5. A method according to claim 1 , 2, 3, or 4 wherein the sample is a blood sample.
6. A method according to claim 1, 2, 3, or 4 wherein the sample is other body fluid, secretion or excretion (such as but not limited to cervicovaginal fluid, saliva, or urine) sample.
7. A method according to claim 1 , 2, 3, or 4 wherein the sample is amniotic fluid sample.
8. A method according to claim 1 , 2, 3, or 4 wherein the sample is fetal cells obtained invasively or non-invasively.
9. A method according to claim 1 , 2, 3, or 4 wherein the sample is sperm or cells obtained from the embryo.
10. A method according to claim 1 , 2, 3, or 4 wherein the sample is a placental sample.
th
11. A method according to claim 1, 2, 3, 4, 5, 6 or 7, wherein the biological sample is obtained before the 20 week of pregnancy, before the th th th th
19 week of pregnancy, before the 18 week of pregnancy, before the 17 week of pregnancy, before the 16 week of pregnancy, before the th th th th
15 week of pregnancy, before the 14 week of pregnancy, before the 13 week of pregnancy, before the 12 week of pregnancy, before the th th th th
11 week of pregnancy, before the 10 week of pregnancy, before the 9 week of pregnancy, before the 8 week of pregnancy, before the th th
7 week of pregnancy, before the 6 week of pregnancy or after delivery.
12. A kit for assessing the presence or risk of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in a female to determine the need for a treatment regimen comprising:
a) detection mechanisms for determining DNA methylation status of one or more of ZNF554; ARNT2; BCL3; BCL6; BTG2; CDKN1A; CGB3; CLC; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1; ESRRG; FLT1 ; GATA2; GCM1 ; GH2; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; LEP; LGALS13; LGALS14; LGALS16; MAPK13; PAPPA2; PGF; PLAC1 ; SIGLEC6; TFAM; TFAP2A; TPBG; or VDR in a biological sample obtained from the female;
b) instructions how to (i) generate a dataset based on the determined DNA methylation status; (ii) assess the presence or risk of developing preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in the female based on the dataset; and (iii) determine a treatment regimen based on the assessed presence or risk.
13. A kit according to claim 11 wherein the kit includes detection mechanisms for all markers of claim 11.
14. A kit according to claim 11 wherein the kit includes detection mechanisms for at least three markers.
15. A kit according to claim 11 wherein the kit includes detection mechanisms for at least one marker of claim 11.
16. A method of identifying candidate compounds for the treatment of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising:
a) providing a sample comprising of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC;
b) contacting the sample with a test compound;
c) determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; LGALS 17A; MAP K 13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC in the sample; where the test compound that modifies the DNA methylation status, expression, level, or activity of these molecules is a candidate compound.
17. A method according to claim 15, comprising:
a) providing a sample comprising one or more of ZNF554; ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1; FSTL3; GCM1; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG;
b) contacting the sample with a test compound;
c) determining if the test compound specifically modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG in the sample as depicted on Figure 23 or Figure 24;
where the test compound that shows the activity as depicted on Figure 23 or Figure 24 is a candidate compound.
18. A method of identifying a candidate therapeutic agent for the treatment of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in a female disorders, comprising:
a) providing a model of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage in a female;
b) contacting the model with a candidate compound that specifically modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC in the sample,
c) evaluating an effect of the candidate compound on the model;
where a positive effect on the model indicates that the candidate compound is a candidate therapeutic agent for the treatment.
19. A method according to claim 17, the method characterized in step b) contacting the model with a candidate compound that specifically modifies the DNA methylation status, expression, level, or activity of one or more of ZNF554; ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG as depicted on Figure 23 or Figure 24;
20. Therapeutic methods that prevent or reduce the symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising:
a) the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS14; LGALS 16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC.
21. A method of evaluating the effect of a treatment for preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising:
a) administering a treatment to the subject;
b) evaluating the DNA methylation status, expression, level or activity of one or more of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS 16; LGALS 17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC in a sample from the subject after administration of the treatment;
c) and optionally comparing the DNA methylation status, expression, level or activity of these molecules in the sample to a reference value, e.g., a baseline level for the subject;
wherein if the DNA methylation status, expression, level or activity of these molecules in the sample has a predetermined relationship to the reference value, the treatment has a positive effect on the disease in the subject.
22. A pharmaceutical composition that prevents or reduces the symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising specific "inhibitors", "activators" or "modulators" of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC.
23. Methods for producing pharmaceutical compositions for the treatment of preeclampsia or closely related complication of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage by formulating a therapeutic agent identified by a method according to claim 17 with a physiologically acceptable carrier.
24. Therapeutic methods that prevent or reduce the symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising:
a) evaluating the DNA methylation status, expression, level or activity of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1 QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC in a sample from a subject before administering the treatment to the subject, to provide a baseline level for the subject.
b) administering a therapeutically effective amount of a pharmaceutical composition to the subject that decreases, increases or modulates the DNA methylation status, expression, level or activity of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1 ; FSTL3; GATA2; GCM1; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS14; LGALS 16; LGALS 17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC;
c) evaluating the effect of the treatment including evaluating the DNA methylation status, expression, level or activity of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1 ; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS13; LGALS14; LGALS16; LGALS17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1 ; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; AP0A4; AP0L1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC in a sample from the subject after administration of the treatment;
d) optionally comparing the DNA methylation status, expression, level or activity of these molecules in the sample to a reference value, e.g., a baseline level for the subject;
e) assigning a value to said subject for the effectiveness of the treatment including providing a record of that value;
f) and determining whether to continue to administer the treatment to the subject, or whether to administer the treatment to another subject.
25. Therapeutic methods according to claim 23, wherein the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity include one or more of ZNF554; ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG.
26. Therapeutic methods according to claim 23, wherein the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity include one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS14; or LGALS16.
27. Therapeutic methods according to claim 23, wherein the administration to the subject a therapeutically effective amount of a pharmaceutical composition that decreases, increases or modulates the DNA methylation status, expression, level or activity include one or more of ZNF554; AGT; BCL6; or ARNT2.
28. A pharmaceutical composition that prevents or reduces the symptoms of preeclampsia or closely related complications of pregnancy wherein said complications are selected from, but not limited to, HELLP syndrome, intrauterine growth restriction, intrauterine fetal demise, preterm premature rupture of the membranes, implantation failure, and threatened and spontaneous miscarriage, comprising specific "inhibitors", "activators" or "modulators" of one or more of ZNF554; ARNT2; BCL3; BCL6; BHLHE40; BTG2; CDKN1A; CGB3; CLC; CLDN1 ; CRH; CSH1 ; CYP19A1 ; DUSP1 ; ENG; ERVFRDE1; ERVWE1 ; ESRRG; FBLN1 ; FLT1; FSTL3; GATA2; GCM1 ; GH2; HLF; HSD11 B2; HSD17B1 ; IKBKB; INSL4; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; LGALS 17A; MAPK13; NANOG; PAPPA; PAPPA2; PGF; PLAC1 ; POU5F1; SERPINE1 ; SIGLEC6; STK40; TEAD3; TFAM; TFAP2A; TIMP3; TPBG; VDR; a CGB; an LGALS; a PSG; a HSD11 B; A1 BG; AGT; APOA4; APOL1 ; C1QB; C4; CFH; HPX; HRG; IGFALS; KNG1 ; PAEP; APOH; SERPINA3; CP; C7; HRNR; ITIH2; CFB; FETUB; GSN; ITIH4; CD14; PEDF; PLG; or GC.
29. A pharmaceutical composition according to claim 27 comprising specific "inhibitors", "activators" or "modulators" of one or more of ZNF554; ARNT2; BCL6; BHLHE40; BTG2; CLC; ENG; ESRRG; FLT1 ; FSTL3; GCM1 ; HLF; HSD11 B2; HSD17B1 ; JUNB; KIT; LEP; LGALS 13; LGALS 14; LGALS16; PAPPA2; SERPINE1 ; STK40; TIMP3; TPBG; VDR; AGT; APOA4; APOH; APOL1 ; C1 QB; C4; C7; CFB; FETUB; GC; GSN; HPX; HRG; KNG1 ; PEDF; or PLG.
30. A pharmaceutical composition according to claim 27 comprising specific "inhibitors", "activators" or "modulators" of one or more of ZNF554; BCL6; ARNT2; AGT; LGALS 13; LGALS 14; or LGALS16.
31. A pharmaceutical composition according to claim 27 comprising specific "inhibitors", "activators" or "modulators" of one or more of ZNF554; AGT; BCL6; or ARNT2.
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