TY - JOUR
T1 - Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease
AU - Mäkinen, Ville Petteri
AU - Civelek, Mete
AU - Meng, Qingying
AU - Zhang, Bin
AU - Zhu, Jun
AU - Levian, Candace
AU - Huan, Tianxiao
AU - Segrè, Ayellet V.
AU - Ghosh, Sujoy
AU - Vivar, Juan
AU - Nikpay, Majid
AU - Stewart, Alexandre F.R.
AU - Nelson, Christopher P.
AU - Willenborg, Christina
AU - Erdmann, Jeanette
AU - Blakenberg, Stefan
AU - O'Donnell, Christopher J.
AU - März, Winfried
AU - Laaksonen, Reijo
AU - Epstein, Stephen E.
AU - Kathiresan, Sekar
AU - Shah, Svati H.
AU - Hazen, Stanley L.
AU - Reilly, Muredach P.
AU - Lusis, Aldons J.
AU - Samani, Nilesh J.
AU - Schunkert, Heribert
AU - Quertermous, Thomas
AU - McPherson, Ruth
AU - Yang, Xia
AU - Assimes, Themistocles L.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions.
AB - The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions.
UR - http://www.scopus.com/inward/record.url?scp=84905491435&partnerID=8YFLogxK
U2 - 10.1371/journal.pgen.1004502
DO - 10.1371/journal.pgen.1004502
M3 - Journal articles
C2 - 25033284
AN - SCOPUS:84905491435
SN - 1553-7390
VL - 10
JO - PLoS Genetics
JF - PLoS Genetics
IS - 7
M1 - e1004502
ER -