Genomic and molecular characterization of preterm birth

Author:

Knijnenburg Theo A.,Vockley Joseph G.,Chambwe NyashaORCID,Gibbs David L.,Humphries Crystal,Huddleston Kathi C.,Klein Elisabeth,Kothiyal Prachi,Tasseff Ryan,Dhankani Varsha,Bodian Dale L.,Wong Wendy S. W.,Glusman GustavoORCID,Mauldin Denise E.,Miller Michael,Slagel Joseph,Elasady Summer,Roach Jared C.,Kramer Roger,Leinonen Kalle,Linthorst Jasper,Baveja Rajiv,Baker Robin,Solomon Benjamin D.,Eley Greg,Iyer Ramaswamy K.,Maxwell George L.,Bernard Brady,Shmulevich IlyaORCID,Hood Leroy,Niederhuber John E.

Abstract

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.

Funder

Inova Health System Foundation

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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