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Abstract
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.
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Uzun A, Schuster J, McGonnigal B, Schorl C, Dewan A, Padbury J. Targeted Sequencing and Meta-Analysis of Preterm Birth. PLoS One 2016; 11:e0155021. [PMID: 27163930 PMCID: PMC4862658 DOI: 10.1371/journal.pone.0155021] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2015] [Accepted: 04/22/2016] [Indexed: 01/01/2023] Open
Abstract
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.
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Affiliation(s)
- Alper Uzun
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, Rhode Island, United States of America
- Brown Alpert Medical School, Providence, Rhode Island, United States of America
| | - Jessica Schuster
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, Rhode Island, United States of America
| | - Bethany McGonnigal
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, Rhode Island, United States of America
| | - Christoph Schorl
- Molecular Biology, Cell Biology & Biochemistry, Brown University, Providence, Rhode Island, United States of America
| | - Andrew Dewan
- Department of Epidemiology and Public Health, Yale University, New Haven, Connecticut, United States of America
| | - James Padbury
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, Rhode Island, United States of America
- Brown Alpert Medical School, Providence, Rhode Island, United States of America
- Center for Computational Molecular Biology, Brown University, Providence, Rhode Island, United States of America
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Mitsuya K, Singh N, Sooranna SR, Johnson MR, Myatt L. Epigenetics of human myometrium: DNA methylation of genes encoding contraction-associated proteins in term and preterm labor. Biol Reprod 2014; 90:98. [PMID: 24571989 DOI: 10.1095/biolreprod.113.113209] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Preterm birth involves the interaction of societal and environmental factors potentially modulating the length of gestation via the epigenome. An established form of epigenetic regulation is DNA methylation where promoter hypermethylation is associated with gene repression. We hypothesized we would find differences in DNA methylation in the myometrium of women with preterm labor of different phenotypes versus normal term labor. Myometrial tissue was obtained at cesarean section at term with or without labor, preterm without labor, idiopathic preterm labor, and twin gestations with labor. Genomic DNA was isolated, and samples in each group were combined and analyzed on a NimbleGen 2.1M human DNA methylation array. Differences in methylation from -8 to +3 kb of transcription start sites of 22 contraction-associated genes were determined. Cytosine methylation was not present in CpG islands of any gene but was present outside of CpG islands in shores and shelves in 19 genes. No differential methylation was found across the tissue groups for six genes (PTGES3L, PTGER2, PTGER4, PTGFRN, ESR2, and GJA1). For 13 genes, differential methylation occurred in several patterns between tissue groups. We find a correlation between hypomethylation and increased mRNA expression of PTGES/mPGES-1, indicating potential functional relevance of methylation, but no such correlation for PTGS2/COX-2, suggesting other regulatory mechanisms for PTGS2 at labor. The majority of differential DNA methylation of myometrial contraction-associated genes with different labor phenotypes occurs outside of CpG islands in gene promoters, suggesting that the entirety of DNA methylation across the genome should be considered.
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Affiliation(s)
- Kohzoh Mitsuya
- Center for Pregnancy and Newborn Research, Department of Obstetrics and Gynecology, University of Texas Health Science Center San Antonio, San Antonio, Texas
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Myatt L, Eschenbach DA, Lye SJ, Mesiano S, Murtha AP, Williams SM, Pennell CE. A standardized template for clinical studies in preterm birth. Reprod Sci 2012; 19:474-82. [PMID: 22344727 DOI: 10.1177/1933719111426602] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Preterm birth is a major societal and economic problem accounting for 80 to 90% of neonatal morbidity and mortality worldwide. It is recognized as a complex multifactorial condition comprising several distinct clinical phenotypes with different underlying etiologies. As animal models are expensive and fail to mimic the biology of spontaneous preterm birth in humans, understanding the pathophysiology requires detailed clinical studies. Meta-analyses and clinical translation of data, however, are limited by heterogeneity of study design and size, publication and reporting biases, definition of patient groups, and a lack of standard universal definitions. This article provides a harmonized open-source template for designing clinical studies addressing preterm birth. METHODS Recommendations are made for clinical definitions, choice and assignment to preterm birth phenotypes, selection of enriched populations and control pregnancies, and potential confounding factors. In addition, recommendations are made for study design, sample size and power calculations, the minimal data sets needed for any study of preterm birth, and the optimal data set of an ideal study. RESULTS Recommended patient phenotypes are infection, uterine overdistension, hemorrhage, stress (either maternal or fetal), and idiopathic. Confounding factors include medical conditions, obesity, antenatal glucocorticoids, multifetal pregnancies, and fetal sex. Guidelines regarding study design, sample size, and clinical data acquisition are provided to serve as a universal template for preterm birth studies. CONCLUSIONS Adoption of a harmonized template will allow generation of protocols and studies with a basic degree of compatibility and will allow data to be compared, and samples and data sets to be combined for meaningful meta-analyses.
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Affiliation(s)
- Leslie Myatt
- Department of Obstetrics and Gynecology, University of Texas Health Science Center San Antonio, San Antonio, TX 78229-3900, USA.
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Uzun A, Laliberte A, Parker J, Andrew C, Winterrowd E, Sharma S, Istrail S, Padbury JF. dbPTB: a database for preterm birth. Database (Oxford) 2012; 2012:bar069. [PMID: 22323062 PMCID: PMC3275764 DOI: 10.1093/database/bar069] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2011] [Revised: 12/28/2011] [Accepted: 12/29/2011] [Indexed: 02/07/2023]
Abstract
Genome-wide association studies (GWAS) query the entire genome in a hypothesis-free, unbiased manner. Since they have the potential for identifying novel genetic variants, they have become a very popular approach to the investigation of complex diseases. Nonetheless, since the success of the GWAS approach varies widely, the identification of genetic variants for complex diseases remains a difficult problem. We developed a novel bioinformatics approach to identify the nominal genetic variants associated with complex diseases. To test the feasibility of our approach, we developed a web-based aggregation tool to organize the genes, genetic variations and pathways involved in preterm birth. We used semantic data mining to extract all published articles related to preterm birth. All articles were reviewed by a team of curators. Genes identified from public databases and archives of expression arrays were aggregated with genes curated from the literature. Pathway analysis was used to impute genes from pathways identified in the curations. The curated articles and collected genetic information form a unique resource for investigators interested in preterm birth. The Database for Preterm Birth exemplifies an approach that is generalizable to other disorders for which there is evidence of significant genetic contributions.
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Affiliation(s)
- Alper Uzun
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, RI 02905, USA, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA and Brown Alpert Medical School, Providence, RI 02912, USA
| | - Alyse Laliberte
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, RI 02905, USA, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA and Brown Alpert Medical School, Providence, RI 02912, USA
| | - Jeremy Parker
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, RI 02905, USA, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA and Brown Alpert Medical School, Providence, RI 02912, USA
| | - Caroline Andrew
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, RI 02905, USA, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA and Brown Alpert Medical School, Providence, RI 02912, USA
| | - Emily Winterrowd
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, RI 02905, USA, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA and Brown Alpert Medical School, Providence, RI 02912, USA
| | - Surendra Sharma
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, RI 02905, USA, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA and Brown Alpert Medical School, Providence, RI 02912, USA
| | - Sorin Istrail
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, RI 02905, USA, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA and Brown Alpert Medical School, Providence, RI 02912, USA
| | - James F. Padbury
- Department of Pediatrics, Women & Infants Hospital of Rhode Island, Providence, RI 02905, USA, Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA and Brown Alpert Medical School, Providence, RI 02912, USA
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