TY - JOUR
T1 - Genomic and molecular characterization of preterm birth
AU - Knijnenburg, Theo A.
AU - Vockley, Joseph G.
AU - Chambwe, Nyasha
AU - Gibbs, David L.
AU - Humphries, Crystal
AU - Huddleston, Kathi C.
AU - Klein, Elisabeth
AU - Kothiyal, Prachi
AU - Tasseff, Ryan
AU - Dhankani, Varsha
AU - Bodian, Dale L.
AU - Wong, Wendy S.W.
AU - Glusman, Gustavo
AU - Mauldin, Denise E.
AU - Miller, Michael
AU - Slagel, Joseph
AU - Elasady, Summer
AU - Roach, Jared C.
AU - Kramer, Roger
AU - Leinonen, Kalle
AU - Linthorst, Jasper
AU - Baveja, Rajiv
AU - Baker, Robin
AU - Solomon, Benjamin D.
AU - Eley, Greg
AU - Iyer, Ramaswamy K.
AU - Maxwell, George L.
AU - Bernard, Brady
AU - Shmulevich, Ilya
AU - Hood, Leroy
AU - Niederhuber, John E.
N1 - Publisher Copyright:
© 2019 National Academy of Sciences. All Rights Reserved.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Family trios
KW - Genomic variants
KW - Integrative computational analysis
KW - Preterm birth
KW - Whole genome sequencing
UR - http://www.scopus.com/inward/record.url?scp=85063264141&partnerID=8YFLogxK
U2 - 10.1073/pnas.1716314116
DO - 10.1073/pnas.1716314116
M3 - Article
C2 - 30833390
AN - SCOPUS:85063264141
SN - 0027-8424
VL - 116
SP - 5819
EP - 5827
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 12
ER -