Download population's GWAS association results: Download

Preterm Birth GWAS Data Visualization

Nadav Rappoport+, Jonathan Toung+, Dexter Hadley, Ronald J. Wong, Kazumichi Fujioka, Jason Reuter, Charles W Abbott, Sam Oh, Donglei Hu, Celeste Eng, Scott Huntsman, Dale L Bodian, John E Niederhuber, Xiumei Hong, Ge Zhang, Weronika Sikora-Wohfeld, Christopher R. Gignoux, Hui Wang, John Oehlert, Laura L. Jelliffe-Pawlowski, Jeffrey B. Gould, Gary L. Darmstadt, Xiaobin Wang, Carlos D. Bustamante, Michael P. Snyder, Elad Ziv, Nikolaos A. Patsopoulos, Louis J. Muglia, Esteban Burchard, Gary M. Shaw, Hugh M. O’Brodovich, David K. Stevenson, Atul J. Butte*, and Marina Sirota*

+these authors contributed equally to this work

Abstract

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: Africa (AFR), the Americas (AMR), Europe, South Asia, and East Asia. 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.


Developed by the Sirota Lab. Please contact Nadav Rappoport for any questions or suggestions.
Loading...
Loading...