dbPTB: a database for preterm birth

Integrative analysis of noncoding mutations identifies the druggable genome in preterm birth

Preterm birth affects ~10% of pregnancies in the US. Despite familial associations, identifying at-risk genetic loci has been challenging. We built deep learning and graphical models to score mutational effects at base resolution via integrating the pregnant myometrial epigenome and large-scale patient genomes with spontaneous preterm birth (sPTB) from European and African American cohorts. We uncovered previously unidentified sPTB genes that are involved in myometrial muscle relaxation and inflammatory responses and that are regulated by the progesterone receptor near labor onset. We studied genomic variants in these genes in our recruited pregnant women administered progestin prophylaxis. We observed that mutation burden in these genes was predictive of responses to progestin treatment for preterm birth. To advance therapeutic development, we screened ~4000 compounds, identified candidate molecules that affect our identified genes, and experimentally validated their therapeutic effects on regulating labor. Together, our integrative approach revealed the druggable genome in preterm birth and provided a generalizable framework for studying complex diseases.

A Data Mining Approach Reveals Chemicals Detected at Higher Levels in Non-Hispanic Black Women Target Preterm Birth Genes and Pathways

Preterm birth occurs disproportionately in the USA non-Hispanic Black population. Black women also face disproportionate exposure to certain environmental chemicals. The goal of this study was to use publicly available toxicogenomic data to identify chemical exposures that may contribute to preterm birth disparities. We tested 19 chemicals observed at higher levels in the blood or urine of non-Hispanic Black women compared to non-Hispanic White women. We obtained chemical-gene interactions from the Comparative Toxicogenomics Database and a list of genes involved in preterm birth from the Preterm Birth Database. We tested chemicals for enrichment with preterm birth genes using chi-squared tests. We then conducted pathway enrichment analysis for the preterm birth genes using DAVID software and identified chemical impacts on genes involved in these pathways. Genes annotated to all 19 chemicals were enriched with preterm birth genes (FDR-adjusted p value < 0.05). Preterm birth enriched chemicals that were detected at the highest levels in non-Hispanic Black women included methyl mercury, methylparaben, propylparaben, diethyl phthalate, dichlorodiphenyldichloroethylene, and bisphenol S. The preterm birth genes were enriched for pathways including "inflammatory response" (FDR-adjusted p value = 3 × 10-19), "aging" (FDR-adjusted p value = 4 × 10-8) and "response to estradiol" (FDR-adjusted p value = 2 × 10-4). Chemicals enriched with preterm birth genes impacted genes in all three pathways. This study adds to the body of knowledge suggesting that exposures to environmental chemicals contribute to racial disparities in preterm birth and that multiple chemicals drive these effects. These chemicals affect genes involved in biological processes relevant to preterm birth such as inflammation, aging, and estradiol pathways.

Identifying Candidate Genes for Short Gestation Length Trait in Chinese Qingping Pigs by Whole-Genome Resequencing and RNA Sequencing

Gestation length is a complex polygenic trait that affects pig fetal development. The Qingping (QP) pig, a Chinese native black pig breed, is characterized by short gestation length. However, the genetic architecture of short gestation length is still not clear. The present study aimed to explore the genetic architecture of short gestation length in QP pigs. In this study, selective sweep analyses were performed to detect selective sweep signatures for short gestation length traits between 100 QP pigs and 219 pigs from 15 other breeds. In addition, differentially expressed genes for the short gestation length between QP pigs and Large White pigs were detected by RNA sequencing. Comparing candidate genes from these methods with known genes for preterm birth in the database, we obtained 111 candidate genes that were known preterm birth genes. Prioritizing other candidate genes, 839 novel prioritized candidate genes were found to have significant functional similarity to preterm birth genes. In particular, we highlighted EGFR, which was the most prioritized novel candidate relative to preterm birth genes. Experimental validations in placental and porcine trophectoderm cells suggest that EGFR is highly expressed in the QP pigs with short gestation length and could regulate the NF-κΒ pathway and downstream expression of PTGS2. These findings comprehensively identified candidate genes for short gestation length trait at the genomic and transcriptomic levels. These candidate genes provide an important new resource for further investigation and genetic improvement of gestation length.

Protein interaction networks define the genetic architecture of preterm birth

The likely genetic architecture of complex diseases is that subgroups of patients share variants in genes in specific networks sufficient to express a shared phenotype. We combined high throughput sequencing with advanced bioinformatic approaches to identify such subgroups of patients with variants in shared networks. We performed targeted sequencing of patients with 2 or 3 generations of preterm birth on genes, gene sets and haplotype blocks that were highly associated with preterm birth. We analyzed the data using a multi-sample, protein–protein interaction (PPI) tool to identify significant clusters of patients associated with preterm birth. We identified shared protein interaction networks among preterm cases in two statistically significant clusters, p < 0.001. We also found two small control-dominated clusters. We replicated these data on an independent, large birth cohort. Separation testing showed significant similarity scores between the clusters from the two independent cohorts of patients. Canonical pathway analysis of the unique genes defining these clusters demonstrated enrichment in inflammatory signaling pathways, the glucocorticoid receptor, the insulin receptor, EGF and B-cell signaling, These results support a genetic architecture defined by subgroups of patients that share variants in genes in specific networks and pathways which are sufficient to give rise to the disease phenotype.

Biomarker discovery for predicting spontaneous preterm birth from gene expression data by regularized logistic regression

In this work, we provide a computational method of regularized logistic regression for discovering biomarkers of spontaneous preterm birth (SPTB) from gene expression data. The successful identification of SPTB biomarkers will greatly benefit the interference of infant gestational age for reducing the risks of pregnant women and preemies. In recent years, various approaches have been proposed for the feature selection of identifying the subset of meaningful genes that can achieve accurate classification for disease samples from controls. Here, we comprehensively summarize the regularized logistic regression with seven effective penalties developed for the selection of strongly indicative genes of SPTB from microarray data. We compare their properties and assess their classification performances in multiple datasets. It shows that elastic net, lasso,L 1 / 2 and SCAD penalties get the better performance than others and can be successfully used to identify biomarkers of SPTB. Particularly, we make a functional enrichment analysis on these biomarkers and construct a logistic regression classifier based on them. The classifier generates an indicator of preterm risk score (PRS) for predicting SPTB. Based on the trained predictor, we verify the identified biomarkers on an independent dataset. The biomarkers achieve the AUC value of 0.933 in the SPTB classification. The results demonstrate the effectiveness and efficiency of the built-up strategy of biomarker discovery with regularized logistic regression. Obviously, the proposed method of discovering biomarkers for SPTB can be easily extended for other complex diseases.

Transcriptome analysis of early pregnancy vitamin D status and spontaneous preterm birth

Background

We conducted a literature review on the studies that investigated the relationship of preterm birth, including spontaneous preterm birth (sPTB), with vitamin D status. Overall, these studies demonstrated that the incidence of sPTB was associated with maternal vitamin D insufficiency in early pregnancy. However, the potential mechanisms and biological pathways are unknown.

Objectives

To investigate early pregnancy gene expression signatures associated with both vitamin D insufficiency and sPTB. We further constructed a network of these gene signatures and identified the common biological pathways involved.

Study design

We conducted peripheral blood transcriptome profiling at 10–18 weeks of gestation in a nested case-control cohort of 24 pregnant women who participated in the Vitamin D Antenatal Asthma Reduction Trial (VDAART). In this cohort, 8 women had spontaneous preterm delivery (21–32 weeks of gestation) and 17 women had vitamin D insufficiency (25-hydroxyvitamin D < 30 ng/mL). We separately identified vitamin D-associated and sPTB gene signatures at 10 to 18 weeks and replicated the overlapping signatures in the mid-pregnancy peripheral blood of an independent cohort with sPTB cases.

Result

At 10–18 weeks of gestation, 146 differentially expressed genes (25 upregulated) were associated with both vitamin D insufficiency and sPTB in the discovery cohort (FDR < 0.05). Of these genes, 43 (25 upregulated) were replicated in the independent cohort of sPTB cases and controls with normal pregnancies (P < 0.05). Functional enrichment and network analyses of the replicated gene signatures suggested several highly connected nodes related to inflammatory and immune responses.

Conclusions

Our gene expression study and network analyses suggest that the dysregulation of immune response pathways due to early pregnancy vitamin D insufficiency may contribute to the pathobiology of sPTB.

Epigenetic biomarkers and preterm birth

Preterm birth (PTB) is a major public health challenge, and novel, sensitive approaches to predict PTB are still evolving. Epigenomic markers are being explored as biomarkers of PTB because of their molecular stability compared to gene expression. This approach is also relatively new compared to gene-based diagnostics, which relies on mutations or single nucleotide polymorphisms. The fundamental principle of epigenome diagnostics is that epigenetic reprogramming in the target tissue (e.g. placental tissue) might be captured by more accessible surrogate tissue (e.g. blood) using biochemical epigenome assays on circulating DNA that incorporate methylation, histone modifications, nucleosome positioning, and/or chromatin accessibility. Epigenomic-based biomarkers may hold great potential for early identification of the majority of PTBs that are not associated with genetic variants or mutations. In this review, we discuss recent advances made in the development of epigenome assays focusing on its potential exploration for association and prediction of PTB. We also summarize population-level cohort studies conducted in the USA and globally that provide opportunities for genetic and epigenetic marker development for PTB. In addition, we summarize publicly available epigenome resources and published PTB studies. We particularly focus on ongoing genome-wide DNA methylation and epigenome-wide association studies. Finally, we review the limitations of current research, the importance of establishing a comprehensive biobank, and possible directions for future studies in identifying effective epigenome biomarkers to enhance health outcomes for pregnant women at risk of PTB and their infants.

Transcriptomic analysis of fetal membranes reveals pathways involved in preterm birth

Background

Preterm birth (PTB), defined as infant delivery before 37 weeks of completed gestation, results from the interaction of both genetic and environmental components and constitutes a complex multifactorial syndrome. Transcriptome analysis of PTB has proven challenging because of the multiple causes of PTB and the numerous maternal and fetal gestational tissues that must interact to facilitate parturition. The transcriptome of the chorioamnion membranes at the site of rupture in PTB and term fetuses may reflect the molecular pathways of preterm labor.

Methods

In this work, chorioamnion membranes from severe preterm and term fetuses were analyzed using RNA sequencing. Functional annotations and pathway analysis of differentially expressed genes were performed with the GAGE and GOSeq packages. A subset of differentially expressed genes in PTB was validated in a larger cohort using qRT-PCR and by comparing our results with genes and pathways previously reported in the literature.

Results

A total of 270 genes were differentially expressed (DE): 252 were upregulated and 18 were down-regulated in severe preterm births relative to term births. Inflammatory and immunological pathways were upregulated in PTB. Both types of pathways were previously suggested to lead to PTB. Pathways that were not previously reported in PTB, such as the hemopoietic pathway, appeared upregulated in preterm membranes. A group of 18 downregulated genes discriminated between term and severe preterm cases. These genes potentially characterize a severe preterm transcriptome pattern and therefore are candidate genes for understanding the syndrome. Some of the downregulated genes are involved in the nervous system, morphogenesis (WNT1, DLX5, PAPPA2) and ion channel complexes (KCNJ16, KCNB1), making them good candidates as biomarkers of PTB.

Conclusions

The identification of this DE gene pattern will help with the development of a multi-gene disease classifier. These markers were generated in an admixed South American population in which PTB has a high incidence. Since the genetic background may differentially impact different populations, it is necessary to include populations such as those from South America and Africa, which are usually excluded from high-throughput approaches. These classifiers should be compared to those in other populations to obtain a global landscape of PTB.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0498-3) contains supplementary material, which is available to authorized users.

Genomic and molecular characterization of preterm birth

Preterm birth (PTB) complications are the leading cause of long-term morbidity and mortality in children. By using whole blood samples, we integrated whole-genome sequencing (WGS), RNA sequencing (RNA-seq), and DNA methylation data for 270 PTB and 521 control families. We analyzed this combined dataset to identify genomic variants associated with PTB and secondary analyses to identify variants associated with very early PTB (VEPTB) as well as other subcategories of disease that may contribute to PTB. We identified differentially expressed genes (DEGs) and methylated genomic loci and performed expression and methylation quantitative trait loci analyses to link genomic variants to these expression and methylation changes. We performed enrichment tests to identify overlaps between new and known PTB candidate gene systems. We identified 160 significant genomic variants associated with PTB-related phenotypes. The most significant variants, DEGs, and differentially methylated loci were associated with VEPTB. Integration of all data types identified a set of 72 candidate biomarker genes for VEPTB, encompassing genes and those previously associated with PTB. Notably, PTB-associated genes RAB31 and RBPJ were identified by all three data types (WGS, RNA-seq, and methylation). Pathways associated with VEPTB include EGFR and prolactin signaling pathways, inflammation- and immunity-related pathways, chemokine signaling, IFN-γ signaling, and Notch1 signaling. Progress in identifying molecular components of a complex disease is aided by integrated analyses of multiple molecular data types and clinical data. With these data, and by stratifying PTB by subphenotype, we have identified associations between VEPTB and the underlying biology.

Machine learning approach to literature mining for the genetics of complex diseases

To generate a parsimonious gene set for understanding the mechanisms underlying complex diseases, we reasoned it was necessary to combine the curation of public literature, review of experimental databases and interpolation of pathway-associated genes. Using this strategy, we previously built the following two databases for reproductive disorders: The Database for Preterm Birth (dbPTB) and The Database for Preeclampsia (dbPEC). The completeness and accuracy of these databases is essential for supporting our understanding of these complex conditions. Given the exponential increase in biomedical literature, it is becoming increasingly difficult to manually maintain these databases. Using our curated databases as reference data sets, we implemented a machine learning-based approach to optimize article selection for manual curation. We used logistic regression, random forests and neural networks as our machine learning algorithms to classify articles. We examined features derived from abstract text, annotations and metadata that we hypothesized would best classify articles with genetically relevant content associated to the disorder of interest. Combinations of these features were used build the classifiers and the performance of these feature sets were compared to a standard 'Bag-of-Words'. Several combinations of these genetic based feature sets outperformed 'Bag-of-Words' at a threshold such that 95% of the curated gene set obtained from the original manual curation of all articles were extracted from the articles classified by machine learning as 'considered'. The performance was superior in terms of the reduction of required manual curation and two measures of the harmonic mean of precision and recall. The reduction in workload ranged from 0.814 to 0.846 for the dbPTB and 0.301 to 0.371 for the dbPEC. Additionally, a database of metadata and annotations is generated which allows for rapid query of individual features. Our results demonstrate that machine learning algorithms can identify articles with relevant data for databases of genes associated with complex diseases.

Enabling precision medicine in neonatology, an integrated repository for preterm birth research

Preterm birth, or the delivery of an infant prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. In the last decade, the advent and continued development of molecular profiling technologies has enabled researchers to generate vast amount of 'omics' data, which together with integrative computational approaches, can help refine the current knowledge about disease mechanisms, diagnostics, and therapeutics. Here we describe the March of Dimes' Database for Preterm Birth Research (http://www.immport.org/resources/mod), a unique resource that contains a variety of 'omics' datasets related to preterm birth. The database is open publicly, and as of January 2018, links 13 molecular studies with data across tens of thousands of patients from 6 measurement modalities. The data in the repository are highly diverse and include genomic, transcriptomic, immunological, and microbiome data. Relevant datasets are augmented with additional molecular characterizations of almost 25,000 biological samples from public databases. We believe our data-sharing efforts will lead to enhanced research collaborations and coordination accelerating the overall pace of discovery in preterm birth research.

Genetic variations and risk of placental abruption: A genome-wide association study and meta-analysis of genome-wide association studies

INTRODUCTION

Accumulating epidemiological evidence points to strong genetic susceptibility to placental abruption (PA). However, characterization of genes associated with PA remains incomplete. We conducted a genome-wide association study (GWAS) of PA and a meta-analysis of GWAS.

METHODS

Participants of the Placental Abruption Genetic Epidemiology (PAGE) study, a population based case-control study of PA conducted in Lima, Peru, were genotyped using the Illumina HumanCore-24 BeadChip platform. Genotypes were imputed using the 1000 genomes reference panel, and >4.9 million SNPs that passed quality control were analyzed. We performed a GWAS in PAGE participants (507 PA cases and 1090 controls) and a GWAS meta-analysis in 2512 participants (959 PA cases and 1553 controls) that included PAGE and the previously reported Peruvian Abruptio Placentae Epidemiology (PAPE) study. We fitted population stratification-adjusted logistic regression models and fixed-effects meta-analyses using inverse-variance weighting.

RESULTS

Independent loci (linkage-disequilibrium<0.80) suggestively associated with PA (P-value<5e-5) included rs4148646 and rs2074311 in ABCC8, rs7249210, rs7250184, rs7249100 and rs10401828 in ZNF28, rs11133659 in CTNND2, and rs2074314 and rs35271178 near KCNJ11 in the PAGE GWAS. Similarly, independent loci suggestively associated with PA in the GWAS meta-analysis included rs76258369 near IRX1, and rs7094759 and rs12264492 in ADAM12. Functional analyses of these genes showed trophoblast-like cell interaction, as well as networks involved in endocrine system disorders, cardiovascular diseases, and cellular function.

CONCLUSIONS

We identified several genetic loci and related functions that may play a role in PA risk. Understanding genetic factors underlying pathophysiological mechanisms of PA may facilitate prevention and early diagnostic efforts.

IL-1 signaling mediates intrauterine inflammation and chorio-decidua neutrophil recruitment and activation

Neutrophil infiltration of the chorioamnion-decidua tissue at the maternal-fetal interface (chorioamnionitis) is a leading cause of prematurity, fetal inflammation, and perinatal mortality. We induced chorioamnionitis in preterm rhesus macaques by intraamniotic injection of LPS. Here, we show that, during chorioamnionitis, the amnion upregulated phospho-IRAK1-expressed neutrophil chemoattractants CXCL8 and CSF3 in an IL-1-dependent manner. IL-1R blockade decreased chorio-decidua neutrophil accumulation, neutrophil activation, and IL-6 and prostaglandin E2 concentrations in the amniotic fluid. Neutrophils accumulating in the chorio-decidua had increased survival mediated by BCL2A1, and IL-1R blockade also decreased BCL2A1+ chorio-decidua neutrophils. Readouts for inflammation in a cohort of women with preterm delivery and chorioamnionitis were similar to findings in the rhesus macaques. IL-1 is a potential therapeutic target for chorioamnionitis and associated morbidities.

A genome-wide association study identifies only two ancestry specific variants associated with spontaneous preterm birth

Preterm birth (PTB), or the delivery prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. Although twin studies estimate that maternal genetic contributions account for approximately 30% of the incidence of PTB, and other studies reported fetal gene polymorphism association, to date no consistent associations have been identified. In this study, we performed the largest reported genome-wide association study analysis on 1,349 cases of PTB and 12,595 ancestry-matched controls from the focusing on genomic fetal signals. We tested over 2 million single nucleotide polymorphisms (SNPs) for associations with PTB across five subpopulations: African (AFR), the Americas (AMR), European, South Asian, and East Asian. We identified only two intergenic loci associated with PTB at a genome-wide level of significance: rs17591250 (P = 4.55E-09) on chromosome 1 in the AFR population and rs1979081 (P = 3.72E-08) on chromosome 8 in the AMR group. We have queried several existing replication cohorts and found no support of these associations. We conclude that the fetal genetic contribution to PTB is unlikely due to single common genetic variant, but could be explained by interactions of multiple common variants, or of rare variants affected by environmental influences, all not detectable using a GWAS alone.

The transformative potential of an integrative approach to pregnancy

BACKGROUND

Complex traits typically involve diverse biological pathways and are shaped by numerous genetic and environmental factors. Pregnancy-associated traits and pathologies are further complicated by extensive communication across multiple tissues in two individuals, interactions between two genomes-maternal and fetal-that obscure causal variants and lead to genetic conflict, and rapid evolution of pregnancy-associated traits across mammals and in the human lineage. Given the multi-faceted complexity of human pregnancy, integrative approaches that synthesize diverse data types and analyses harbor tremendous promise to identify the genetic architecture and environmental influences underlying pregnancy-associated traits and pathologies.

METHODS

We review current research that addresses the extreme complexities of traits and pathologies associated with human pregnancy.

RESULTS

We find that successful efforts to address the many complexities of pregnancy-associated traits and pathologies often harness the power of many and diverse types of data, including genome-wide association studies, evolutionary analyses, multi-tissue transcriptomic profiles, and environmental conditions.

CONCLUSION

We propose that understanding of pregnancy and its pathologies will be accelerated by computational platforms that provide easy access to integrated data and analyses. By simplifying the integration of diverse data, such platforms will provide a comprehensive synthesis that transcends many of the inherent challenges present in studies of pregnancy.

Placental transcriptome co-expression analysis reveals conserved regulatory programs across gestation

BACKGROUND

Mammalian development in utero is absolutely dependent on proper placental development, which is ultimately regulated by the placental genome. The regulation of the placental genome can be directly studied by exploring the underlying organisation of the placental transcriptome through a systematic analysis of gene-wise co-expression relationships.

RESULTS

In this study, we performed a comprehensive analysis of human placental co-expression using RNA sequencing and intergrated multiple transcriptome datasets spanning human gestation. We identified modules of co-expressed genes that are preserved across human gestation, and also identifed modules conserved in the mouse indicating conserved molecular networks involved in placental development and gene expression patterns more specific to late gestation. Analysis of co-expressed gene flanking sequences indicated that conserved co-expression modules in the placenta are regulated by a core set of transcription factors, including ZNF423 and EBF1. Additionally, we identified a gene co-expression module enriched for genes implicated in the pregnancy pathology preeclampsia. By using an independnet transcriptome dataset, we show that these co-expressed genes are differentially expressed in preeclampsia.

CONCLUSIONS

This study represents a comprehensive characterisation of placental co-expression and provides insight into potential transcriptional regulators that govern conserved molecular programs fundamental to placental development.

Structural and genomic variation in preterm birth

BACKGROUND

Runs of homozygosity (ROH) are consecutive homozygous genotypes, which may result from population inbreeding or consanguineous marriages. ROH enhance the expression of recessive traits.

METHODS

We mapped ROH in a case control study of women delivering at term compared with women delivering at or before 34 wk gestation. Gene sets known to be important in risk of preterm birth were examined for their overlap with identified ROH segments.

RESULTS

While we found no evidence of increased burden of ROH or copy number variations in mothers delivering at or before 34 wk compared with term, we identified 424 genome-wide 50 kb segments with significant difference in abundance of overlapping ROH segments in cases vs. controls, P < 0.05. These regions overlap 199 known genes. We found preterm birth associated genes (CXCR4, MYLK, PAK1) and genes shown to have an evolutionary link to preterm (CXCR4, PPP3CB, C6orf57, DUSP13, and SLC25A45) with significant differences in abundance of overlapping ROH blocks in cases vs. controls, P < 0.001.

CONCLUSION

We conclude, while we found no significant burden of ROH, we did identify genomic regions with significantly greater abundance of ROH blocks in women delivering preterm that overlapped genes known to be involved in preterm birth.

Targeted Sequencing and Meta-Analysis of Preterm Birth

Understanding the genetic contribution(s) to the risk of preterm birth may lead to the development of interventions for treatment, prediction and prevention. Twin studies suggest heritability of preterm birth is 36-40%. Large epidemiological analyses support a primary maternal origin for recurrence of preterm birth, with little effect of paternal or fetal genetic factors. We exploited an "extreme phenotype" of preterm birth to leverage the likelihood of genetic discovery. We compared variants identified by targeted sequencing of women with 2-3 generations of preterm birth with term controls without history of preterm birth. We used a meta-genomic, bi-clustering algorithm to identify gene sets coordinately associated with preterm birth. We identified 33 genes including 217 variants from 5 modules that were significantly different between cases and controls. The most frequently identified and connected genes in the exome library were IGF1, ATM and IQGAP2. Likewise, SOS1, RAF1 and AKT3 were most frequent in the haplotype library. Additionally, SERPINB8, AZU1 and WASF3 showed significant differences in abundance of variants in the univariate comparison of cases and controls. The biological processes impacted by these gene sets included: cell motility, migration and locomotion; response to glucocorticoid stimulus; signal transduction; metabolic regulation and control of apoptosis.

The genomics of prematurity in an era of more precise clinical phenotyping: A review

Spontaneous preterm birth is a major public health problem, with a clear genetic component. Genetic association studies have evolved substantially in recent years, moving away from the traditional candidate gene analyses to newer approaches utilizing sophisticated analysis platforms to examine sequencing data, and shifting towards functional studies including methylation analysis. It is becoming increasingly evident that careful clinical phenotyping is crucial to high quality genetic association studies regardless of the assay or platform being used. Nonetheless, genetic studies of prematurity are hampered by numerous challenges including small sample sizes, incomplete phenotying, population stratification, and multiple comparisons. As the costs of sequencing and functional analyses continue to decrease, unbiased genome-wide assays will be more widely available. Researchers have met improved success recently when critically applying clinical phenotyping knowledge to group women prior to analyzing genotyping results. Eventually, as the analytic approaches evolve, it is likely that this methodology (combining precisely clinically phenotyped subjects with genome-wide data) will provide key information regarding the pathophysiology of prematurity, and provide potential new avenues for exploring innovative therapeutic strategies.

dbPEC: a comprehensive literature-based database for preeclampsia related genes and phenotypes

Preeclampsia is one of the most common causes of fetal and maternal morbidity and mortality in the world. We built a Database for Preeclampsia (dbPEC) consisting of the clinical features, concurrent conditions, published literature and genes associated with Preeclampsia. We included gene sets associated with severity, concurrent conditions, tissue sources and networks. The published scientific literature is the primary repository for all information documenting human disease. We used semantic data mining to retrieve and extract the articles pertaining to preeclampsia-associated genes and performed manual curation. We deposited the articles, genes, preeclampsia phenotypes and other supporting information into the dbPEC. It is publicly available and freely accessible. Previously, we developed a database for preterm birth (dbPTB) using a similar approach. Using the gene sets in dbPTB, we were able to successfully analyze a genome-wide study of preterm birth including 4000 women and children. We identified important genes and pathways associated with preterm birth that were not otherwise demonstrable using genome-wide approaches. dbPEC serves not only as a resources for genes and articles associated with preeclampsia, it is a robust source of gene sets to analyze a wide range of high-throughput data for gene set enrichment analysis. Database URL: http://ptbdb.cs.brown.edu/dbpec/.

GEneSTATION 1.0: a synthetic resource of diverse evolutionary and functional genomic data for studying the evolution of pregnancy-associated tissues and phenotypes

Mammalian gestation and pregnancy are fast evolving processes that involve the interaction of the fetal, maternal and paternal genomes. Version 1.0 of the GEneSTATION database (http://genestation.org) integrates diverse types of omics data across mammals to advance understanding of the genetic basis of gestation and pregnancy-associated phenotypes and to accelerate the translation of discoveries from model organisms to humans. GEneSTATION is built using tools from the Generic Model Organism Database project, including the biology-aware database CHADO, new tools for rapid data integration, and algorithms that streamline synthesis and user access. GEneSTATION contains curated life history information on pregnancy and reproduction from 23 high-quality mammalian genomes. For every human gene, GEneSTATION contains diverse evolutionary (e.g. gene age, population genetic and molecular evolutionary statistics), organismal (e.g. tissue-specific gene and protein expression, differential gene expression, disease phenotype), and molecular data types (e.g. Gene Ontology Annotation, protein interactions), as well as links to many general (e.g. Entrez, PubMed) and pregnancy disease-specific (e.g. PTBgene, dbPTB) databases. By facilitating the synthesis of diverse functional and evolutionary data in pregnancy-associated tissues and phenotypes and enabling their quick, intuitive, accurate and customized meta-analysis, GEneSTATION provides a novel platform for comprehensive investigation of the function and evolution of mammalian pregnancy.

Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy Phenotypes

Progress in understanding complex genetic diseases has been bolstered by synthetic approaches that overlay diverse data types and analyses to identify functionally important genes. Pre-term birth (PTB), a major complication of pregnancy, is a leading cause of infant mortality worldwide. A major obstacle in addressing PTB is that the mechanisms controlling parturition and birth timing remain poorly understood. Integrative approaches that overlay datasets derived from comparative genomics with function-derived ones have potential to advance our understanding of the genetics of birth timing, and thus provide insights into the genes that may contribute to PTB. We intersected data from fast evolving coding and non-coding gene regions in the human and primate lineage with data from genes expressed in the placenta, from genes that show enriched expression only in the placenta, as well as from genes that are differentially expressed in four distinct PTB clinical subtypes. A large fraction of genes that are expressed in placenta, and differentially expressed in PTB clinical subtypes (23–34%) are fast evolving, and are associated with functions that include adhesion neurodevelopmental and immune processes. Functional categories of genes that express fast evolution in coding regions differ from those linked to fast evolution in non-coding regions. Finally, there is a surprising lack of overlap between fast evolving genes that are differentially expressed in four PTB clinical subtypes. Integrative approaches, especially those that incorporate evolutionary perspectives, can be successful in identifying potential genetic contributions to complex genetic diseases, such as PTB.

The genetics of preterm birth: Progress and promise

Preterm birth is the single leading cause of mortality for neonates and children less than 5 years of age. Compared to other childhood diseases, such as infections, less progress in prevention of prematurity has been made. In large part, the continued high burden of prematurity results from the limited understanding of the mechanisms controlling normal birth timing in humans, and how individual genetic variation and environmental exposures disrupt these mechanisms to cause preterm birth. In this review, we summarize the outcomes and limitations from studies in model organisms for birth timing in humans, the evidence that genetic factors contribute to birth timing and risk for preterm birth, and recent genetic and genomic studies in women and infants that implicate specific genes and pathways. We conclude with discussing areas of potential high impact in understanding human parturition and preterm birth in the future.

Insights from physiology into myometrial function and dysfunction

NEW FINDINGS

What is the topic of this review? I focus on clinical aspects of uterine physiology, specifically, myometrial contractility. I bring together and contrast findings using physiological approaches and those using newer techniques, 'omics'. What advances does it highlight? Physiological studies have recently shed light on the myometrium in twin pregnancies, but there have been no 'omic' approaches. In contrast, studies of preterm delivery using newer approaches are generating new research avenues, whereas traditional approaches have not flourished. Finally, I describe significant advances in understanding of 'slow-to-progress' labours, achieved using physiological and clinical approaches. Advances in molecular, genetic and 'omic' technologies are fuelling the thirst for better understanding of the uterus and application of this information to problems in pregnancy and labour. Progress has, however, been limited while we still have an incomplete understanding of some of the basic physiology of uterine smooth muscle (myometrium). In this review and opinion piece, I explore some of the fascinating findings from selected recent studies and see how these may provide new avenues for physiological and clinical research. It is also the case, however, that there is still limited mechanistic understanding about physiological and pathophysiological processes in the myometrium. This lack of understanding limits the usefulness of some findings from genomic and allied studies. By focusing on some key recent findings and relating these to two important clinical problems in childbirth that involve myometrial activity, namely preterm delivery and difficult labours, the interplay between our physiological knowledge and the information provided by newer technologies is explored. My opinion is that physiology has provided much more new mechanistic insight into difficult births and that the newer technologies may lead to breakthroughs in preterm birth research, but that this has not yet happened.

Genomics of preterm birth

The molecular mechanisms controlling human birth timing at term, or resulting in preterm birth, have been the focus of considerable investigation, but limited insights have been gained over the past 50 years. In part, these processes have remained elusive because of divergence in reproductive strategies and physiology shown by model organisms, making extrapolation to humans uncertain. Here, we summarize the evolution of progesterone signaling and variation in pregnancy maintenance and termination. We use this comparative physiology to support the hypothesis that selective pressure on genomic loci involved in the timing of parturition have shaped human birth timing, and that these loci can be identified with comparative genomic strategies. Previous limitations imposed by divergence of mechanisms provide an important new opportunity to elucidate fundamental pathways of parturition control through increasing availability of sequenced genomes and associated reproductive physiology characteristics across diverse organisms.

Genes and post-term birth: late for delivery

Background

Recent evidence suggests that prolonged pregnancies beyond 42 weeks of gestation (post-term births) are associated with long-term adverse health outcomes in the offspring.

Discussion

There is evidence that post-term birth has not only environmental causes, but also significant heritability, suggesting genetic and/or epigenetic influences interact with environmental cues to affect gestational length.

Summary

As prolonged gestation is associated with adverse short- and long-term outcomes in the offspring, further research into the underlying genetic and epigenetic causes of post-term birth could be of importance for improving obstetric management.

Bioinformatic approach to the genetics of preeclampsia

OBJECTIVE

To identify candidate genes and genetic variants for preeclampsia using a bioinformatic approach to extract and organize genes and variants from the published literature.

METHODS

Semantic data-mining and natural language processing were used to identify articles from the published literature meeting criteria for potential association with preeclampsia. Articles were manually reviewed by trained curators. Cluster analysis was used to aggregate the extracted genes into gene sets associated with preeclampsia or severe preeclampsia, early or late preeclampsia, maternal or fetal tissue sources, and concurrent conditions (ie, fetal growth restriction, gestational hypertension, or hemolysis, elevated liver enzymes, and low platelet count [HELLP]). Gene ontology was used to organize this large group of genes into ontology groups.

RESULTS

From more than 22 million records in PubMed, with 28,000 articles on preeclampsia, our data-mining tool identified 2,300 articles with potential genetic associations with preeclampsia-related phenotypes. After curation, 729 articles were "accepted" that contained "statistically significant" associations with 535 genes. We saw distinct segregation of these genes by severity and timing of preeclampsia, by maternal or fetal source, and with associated conditions (eg, gestational hypertension, fetal growth restriction, or HELLP syndrome).

CONCLUSION

The gene sets and ontology groups identified through our systematic literature curation indicate that preeclampsia represents several distinct phenotypes with distinct and overlapping maternal and fetal genetic contributions.

LEVEL OF EVIDENCE

III.

Predicting preterm birth in women with previous preterm birth and cervical length ≥ 25 mm

OBJECTIVE

To identify risk factors predicting subsequent spontaneous preterm birth or preterm prelabor rupture of membranes (PPROM) in a cohort of women with a history of spontaneous preterm birth and a cervical length of ≥ 25 mm at 20-24 weeks' gestation.

METHODS

We identified all pregnant women who attended our preterm labor clinic between January 2010 and December 2012 because of previous spontaneous preterm birth or PPROM before 34 weeks. Women with a normal cervical length (defined as ≥ 25 mm) between 20 and 24 weeks' gestation were identified and included in the analysis. Maternal characteristics, obstetric history, shortest cervical length and gestational age at shortest cervical length of women who delivered preterm (before 37 weeks) were compared with those who delivered at or after 37 weeks in the index pregnancy. Multiple regression analysis was planned to examine the relationship between significant clinical and cervical-length variables to identify significant clinical predictors of spontaneous preterm birth among high-risk patients with a normal cervix between 20 and 24 weeks' gestation.

RESULTS

Of 134 women with a normal cervix at 20-24 weeks, 28 (20.9%) delivered spontaneously or had PPROM before 37 weeks; of these 12 (9.0%) delivered before 34 weeks. None of the selected explanatory variables was predictive of recurrent preterm birth in this cohort. No correlation between absolute cervical length and gestational age at delivery was found (R = 0.01).

CONCLUSION

In high-risk women with a cervical length of ≥ 25 mm at 20-24 weeks' gestation, demographic characteristics and absolute cervical length are not useful in predicting subsequent spontaneous preterm birth.

Preterm birth and single nucleotide polymorphisms in cytokine genes

Preterm birth (PTB) is an important issue in neonates because of its complications as well as high morbidity and mortality. The prevalence of PTB is approximately 12-13% in USA and 5-9% in many other developed countries. China represents 7.8% (approximately one million) of 14.9 million babies born prematurely annually worldwide. The rate of PTB is still increasing. Both genetic susceptibility and environmental factors are the major causes of PTB. Inflammation is regarded as an enabling characteristic factor of PTB. The aim of this review is to summarize the current literatures to illustrate the role of single nucleotide polymorphisms (SNPs) of cytokine genes in PTB. These polymorphisms are different among different geographic regions and different races, thus different populations may have different risk factors of PTB. SNPs affect the ability to metabolize poisonous substances and determine inflammation susceptibility, which in turn has an influence on reproduction-related risks and on delivery outcomes after exposure to environmental toxicants and pathogenic organisms.

Single-nucleotide polymorphism associations with preterm delivery: a case-control replication study and meta-analysis

BACKGROUND

The aim of this study was to replicate single-nucleotide polymorphism (SNP) associations with preterm birth (PTB; birth at <37 completed weeks of gestation) and synthesize currently available evidence using meta-analysis.

METHODS

Spontaneous PTB cases and controls were selected from an existing cohort. Candidate SNPs were taken from an existing genotype panel. A systematic review was conducted for each SNP in the panel to determine suitability as a PTB candidate. Those with significant associations previously reported in Caucasians were selected for replication. Candidate SNPs were already genotyped in cases and controls and clinical data were accessed from state perinatal and cerebral palsy databases. Association analysis was conducted between each SNP and PTB, and meta-analysis was conducted if there were ≥ 3 studies in the literature. Maternal and fetal SNPs were considered as separate candidates.

RESULTS

A cohort of 170 cases and 583 controls was formed. Eight SNPs from the original panel of genotyped SNPs were selected as PTB candidates and for replication on the basis of systematic literature review results. In our cohort, fetal factor V Leiden (FVL) was significantly associated with PTB (odds ratio (OR): 2.6, 95% confidence interval (CI): 1.31-5.17), and meta-analysis confirmed this association (OR: 2.71, 95% CI: 1.15-6.4).

CONCLUSION

Replication and meta-analysis support an increased risk of PTB in Caucasians with the fetal FVL mutation.

The genomics of preterm birth: from animal models to human studies

Preterm birth (delivery at less than 37 weeks of gestation) is the leading cause of infant mortality worldwide. So far, the application of animal models to understand human birth timing has not substantially revealed mechanisms that could be used to prevent prematurity. However, with amassing data implicating an important role for genetics in the timing of the onset of human labor, the use of modern genomic approaches, such as genome-wide association studies, rare variant analyses using whole-exome or genome sequencing, and family-based designs, holds enormous potential. Although some progress has been made in the search for causative genes and variants associated with preterm birth, the major genetic determinants remain to be identified. Here, we review insights from and limitations of animal models for understanding the physiology of parturition, recent human genetic and genomic studies to identify genes involved in preterm birth, and emerging areas that are likely to be informative in future investigations. Further advances in understanding fundamental mechanisms, and the development of preventative measures, will depend upon the acquisition of greater numbers of carefully phenotyped pregnancies, large-scale informatics approaches combining genomic information with information on environmental exposures, and new conceptual models for studying the interaction between the maternal and fetal genomes to personalize therapies for mothers and infants. Information emerging from these advances will help us to identify new biomarkers for earlier detection of preterm labor, develop more effective therapeutic agents, and/or promote prophylactic measures even before conception.

Pathway-based genetic analysis of preterm birth

Preterm birth in the United States is now 12%. Multiple genes, gene networks, and variants have been associated with this disease. Using a custom database for preterm birth (dbPTB) with a refined set of genes extensively curated from literature and biological databases, we analyzed GWAS of preterm birth for complete genotype data on nearly 2000 preterm and term mothers. We used both the curated genes and a genome-wide approach to carry out a pathway-based analysis. There were 19 significant pathways, which withstood FDR correction for multiple testing that were identified using both the curated genes and the genome-wide approach. The analysis based on the curated genes was more significant than genome-wide in 15 out of 19 pathways. This approach demonstrates the use of a validated set of genes, in the analysis of otherwise unsuccessful GWAS data, to identify gene-gene interactions in a way that enhances statistical power and discovery.

Investigation of genetic risk factors for chronic adult diseases for association with preterm birth

Preterm birth (PTB) is the leading cause of infant mortality. PTB pathophysiology overlaps with those of adult cardiovascular, immune and metabolic disorders (CIMD), with mechanisms including inflammation, immunotolerance, thrombosis, and nutrient metabolism. Whereas many genetic factors for CIMD have been identified, progress in PTB has lagged. We hypothesized that highly validated genetic risk factors for CIMD may also be associated with PTB. We conducted case-control study of four female cohorts with spontaneous PTB (n = 673) versus term (n = 1119). Of 35 SNPs genotyped, there were 13 statistically significant associations (P < 0.05), which were more than expected (binomial test; P = 0.02). In US White (307 cases/342 controls), the G allele of HLA-DQA1 (A/G) rs9272346 was protective for PTB in the initial discovery cohort (P = 0.02; OR = 0.65; 95 % CI 0.46, 0.94). This protective association replicated (P = 0.02; OR = 0.85; 95 % CI 0.75, 0.97) nominally in the Danish Cohort (883 cases, 959 controls), but lost significance upon multiple testing correction. We observed more statistically significant associations than expected, suggesting that chance is an unlikely explanation for one or more of the associations. Particularly, a protective association of the G allele of HLA-DQA1 was found in two independent cohorts, and in previous studies, this same allele was found to protect against type-1-diabetes (meta-analysis P value 5.52 × 10(-219)). Previous investigations have implicated HLA phenotypic variation in recurrent fetal loss and in chronic chorioamnionitis. Given the limited sample size in his study, we suggest larger studies to further investigate possible HLA genetic involvement in PTB.