Our goal in this proposal is to identify biological networks involved in synchronizing placental growth and maturity.Toaccomplishthisgoal,wehaveestablishedacollaborativeeffortbetweentheCenterforPrevention of Preterm Birth at Cincinnati Children?s Hospital Medical Center (CCHMC) and the Institute for Systems Biology(ISB)inSeattletoconductasystemslevelanalysisof?omics?data.Perturbedgrowthandmaturitycan lead to placental insufficiency, which underlies a significant proportion of adverse pregnancy outcomes, such aspretermbirth.Apaucityofknowledgeregardingnormalplacentaldevelopmentandmaturitygreatlyhinders any study of placental insufficiency. Placental growth and development occurs throughout gestation and reachesmaturityatterm.Therefore,itiscriticaltoidentifythenetworksinvolvedandtoassessthemoverthe lengthofgestation.Ourcentralhypothesisisthatkeybiologicalnetworksvitaltoplacentalgrowthand maturity can be identified through the intersection of transcriptomic, proteomic, and metabolomics data from term and preterm placentae. Furthermore, utilizing longitudinal proteomics and metabolomics data, we can determine how those pathways change over gestation and differ between normal and preterm placentae.Wewilltestthishypothesisthroughthefollowingaims:
Aim 1 : Identification of key gene and metabolite signatures involved in placental development by analyzing longitudinal ?omics? data. Using publically available transcriptomic data, we will generate a molecularprofileofexpressedgenesinplacentaldevelopmentthroughoutgestation.Wewillalsodetermine the placental secretome and identify biomarker signatures that appear in maternal urine that reflect placental maturation.
Aim 2 : Identification of molecular pathways associated with placental maturity. We will utilize network topologyalgorithmstoidentifychangesinmolecularpathwaysinpretermandtermplacentae.Thesedatawill be combined with publically available data to identify molecular pathways and genes within those pathways thatdifferbetweentermandpretermplacentaetoprovideinsightintoplacentalmaturity.
Aim3 :Generationofaplacenta-specifictranscriptionalnetworkforidentifyingregulatorymechanisms involved in placental maturity. We will construct genome-scale, tissue specific models of placental transcriptional regulatory networks using our newly-developed Transcriptional Regulatory Network Analysis (TRENA) approach, which leverages a wealth of information from the NIH?s ENCODE project. We will characterize which transcriptional regulators are most likely responsible for perturbed gene expression, their signalingpathwaysanddownstreamtargets.Previouslyunknownorunderstudiednetworksorgenesidentified targetedforfurtheranalysesinplacentalgrowthandmaturityandfutureprospectiveclinicalstudies.

Public Health Relevance

Thenormaldevelopmentoftheplacentalisessentialforoptimalpregnancyoutcomes,andunderstandingnormal and pathological placental development will allow new opportunities to prevent major public health concerns suchaspretermbirth,preeclampsia,andintrauterinegrowthrestriction.Thisworkwillseektodevelopnew,non- invasive strategies to monitor human placental maturation, reflecting normal development, against which deviationscanbedeterminedearlierinpregnancyformoreeffectiveinterventions.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZHD1)
Program Officer
Weinberg, David H
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Florida
Schools of Medicine
United States
Zip Code
Huusko, Johanna M; Karjalainen, Minna K; Graham, Britney E et al. (2018) Whole exome sequencing reveals HSPA1L as a genetic risk factor for spontaneous preterm birth. PLoS Genet 14:e1007394
Dunn-Fletcher, Caitlin E; Muglia, Lisa M; Pavlicev, Mihaela et al. (2018) Anthropoid primate-specific retroviral element THE1B controls expression of CRH in placenta and alters gestation length. PLoS Biol 16:e2006337
Paquette, Alison G; Chu, Tianjiao; Wu, Xiaogang et al. (2018) Distinct communication patterns of trophoblastic miRNA among the maternal-placental-fetal compartments. Placenta 72-73:28-35
Kearney, Paul; Boniface, J Jay; Price, Nathan D et al. (2018) The building blocks of successful translation of proteomics to the clinic. Curr Opin Biotechnol 51:123-129
Paquette, Alison; Baloni, Priyanka; Holloman, Anisa B et al. (2018) Temporal transcriptomic analysis of metabolic genes in maternal organs and placenta during murine pregnancy. Biol Reprod 99:1255-1265
Paquette, Alison G; Brockway, Heather M; Price, Nathan D et al. (2018) Comparative transcriptomic analysis of human placentae at term and preterm delivery. Biol Reprod 98:89-101