Genome-wide approach identifies a novel gene-maternal pre-pregnancy BMI interaction on preterm birth

Xiumei Hong, Ke Hao, Hongkai Ji, Shouneng Peng, Ben Sherwood, Antonio Di Narzo, Hui-Ju Tsai, Xin Liu, Irina Burd, Guoying Wang, Yuelong Ji, Deanna Caruso, Guangyun Mao, Tami R. Bartell, Zhongyang Zhang, Colleen Pearson, Linda Heffner, Sandra Cerda, Terri H. Beaty, M. Daniele Fallin, Aviva Lee-Parritz, Barry Zuckerman, Daniel E. Weeks and Xiaobin Wang ()
Additional contact information
Xiumei Hong: Center on the Early Life Origins of Disease, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health
Ke Hao: Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai
Hongkai Ji: Johns Hopkins University Bloomberg School of Public Health Baltimore
Shouneng Peng: Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai
Ben Sherwood: Johns Hopkins University Bloomberg School of Public Health Baltimore
Antonio Di Narzo: Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai
Hui-Ju Tsai: Feinberg School of Medicine, Northwestern University
Xin Liu: Feinberg School of Medicine, Northwestern University
Irina Burd: Integrated Research Center for Fetal Medicine, Johns Hopkins University School of Medicine
Guoying Wang: Center on the Early Life Origins of Disease, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health
Yuelong Ji: Center on the Early Life Origins of Disease, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health
Deanna Caruso: Center on the Early Life Origins of Disease, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health
Guangyun Mao: Center on the Early Life Origins of Disease, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health
Tami R. Bartell: Mary Ann & J. Milburn Smith Child Health Research Program, Stanley Manne Children’s Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago
Zhongyang Zhang: Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai
Colleen Pearson: Boston University School of Medicine and Boston Medical Center
Linda Heffner: Boston University School of Medicine
Sandra Cerda: Boston Medical Center, Boston University School of Medicine
Terri H. Beaty: Johns Hopkins University Bloomberg School of Public Health
M. Daniele Fallin: Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University Bloomberg School of Public Health
Aviva Lee-Parritz: Boston University School of Medicine
Barry Zuckerman: Boston University School of Medicine and Boston Medical Center
Daniel E. Weeks: Graduate School of Public Health, University of Pittsburgh
Xiaobin Wang: Center on the Early Life Origins of Disease, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health

Nature Communications, 2017, vol. 8, issue 1, 1-10

Abstract: Abstract Preterm birth (PTB) contributes significantly to infant mortality and morbidity with lifelong impact. Few robust genetic factors of PTB have been identified. Such ‘missing heritability’ may be partly due to gene × environment interactions (G × E), which is largely unexplored. Here we conduct genome-wide G × E analyses of PTB in 1,733 African-American women (698 mothers of PTB; 1,035 of term birth) from the Boston Birth Cohort. We show that maternal COL24A1 variants have a significant genome-wide interaction with maternal pre-pregnancy overweight/obesity on PTB risk, with rs11161721 (PG × E=1.8 × 10−8; empirical PG × E=1.2 × 10−8) as the top hit. This interaction is replicated in African-American mothers (PG × E=0.01) from an independent cohort and in meta-analysis (PG × E=3.6 × 10−9), but is not replicated in Caucasians. In adipose tissue, rs11161721 is significantly associated with altered COL24A1 expression. Our findings may provide new insight into the aetiology of PTB and improve our ability to predict and prevent PTB.

Date: 2017
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DOI: 10.1038/ncomms15608

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