Genomic and molecular characterization of preterm birth

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


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.

Original languageEnglish
Pages (from-to)5819-5827
Number of pages9
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number12
StatePublished - 2019
Externally publishedYes


  • Family trios
  • Genomic variants
  • Integrative computational analysis
  • Preterm birth
  • Whole genome sequencing


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