Integromic analysis of genetic variation and gene expression identifies networks for cardiovascular disease phenotypes

Chen Yao; Brian H Chen; Roby Joehanes; Burcak Otlu; Xiaoling Zhang; Chunyu Liu; Tianxiao Huan; Oznur Tastan; L Adrienne Cupples; James B Meigs; Caroline S Fox; Jane E Freedman; Paul Courchesne; Christopher J O'Donnell; Peter J Munson; Sunduz Keles; Daniel Levy

doi:10.1161/CIRCULATIONAHA.114.010696

Integromic analysis of genetic variation and gene expression identifies networks for cardiovascular disease phenotypes

Circulation. 2015 Feb 10;131(6):536-49. doi: 10.1161/CIRCULATIONAHA.114.010696. Epub 2014 Dec 22.

Authors

Chen Yao¹, Brian H Chen¹, Roby Joehanes¹, Burcak Otlu¹, Xiaoling Zhang¹, Chunyu Liu¹, Tianxiao Huan¹, Oznur Tastan¹, L Adrienne Cupples¹, James B Meigs¹, Caroline S Fox¹, Jane E Freedman¹, Paul Courchesne¹, Christopher J O'Donnell¹, Peter J Munson¹, Sunduz Keles¹, Daniel Levy²

Affiliations

¹ From the National Heart, Lung, and Blood Institute's Framingham Heart Study, National Institutes of Health, Bethesda, MD (C.Y., B.H.C., R.J., X.Z., C.L., T.H., L.A.C., C.S.F., P.C., C.J.O'D., D.L.); Population Sciences Branch, National Institutes of Health, National Heart, Lung, and Blood Institute, Bethesda, MD (C.Y., B.H.C., R.J., X.Z., C.L., T.H., P.C., D.L.); Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, MD (R.J., P.J.M.); Department of Computer Engineering, Middle East Technical University, Ankara, Turkey (B.O.); Department of Computer Engineering, Bilkent University, Ankara, Turkey (O.T.); Department of Biostatistics, Boston University School of Public Health, Boston, MA (L.A.C.); Harvard Medical School, Boston, MA (J.B.M.); Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (C.S.F.); Department of Medicine, University of Massachusetts Medical School, Worchester (J.E.F.); Division of Cardiology, Massachusetts General Hospital, Boston, MA (C.J.O'D.); and Departments of Statistics and of Biostatistics and Medical Informatics, University of Wisconsin-Madison (S.K.).
² From the National Heart, Lung, and Blood Institute's Framingham Heart Study, National Institutes of Health, Bethesda, MD (C.Y., B.H.C., R.J., X.Z., C.L., T.H., L.A.C., C.S.F., P.C., C.J.O'D., D.L.); Population Sciences Branch, National Institutes of Health, National Heart, Lung, and Blood Institute, Bethesda, MD (C.Y., B.H.C., R.J., X.Z., C.L., T.H., P.C., D.L.); Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, MD (R.J., P.J.M.); Department of Computer Engineering, Middle East Technical University, Ankara, Turkey (B.O.); Department of Computer Engineering, Bilkent University, Ankara, Turkey (O.T.); Department of Biostatistics, Boston University School of Public Health, Boston, MA (L.A.C.); Harvard Medical School, Boston, MA (J.B.M.); Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (C.S.F.); Department of Medicine, University of Massachusetts Medical School, Worchester (J.E.F.); Division of Cardiology, Massachusetts General Hospital, Boston, MA (C.J.O'D.); and Departments of Statistics and of Biostatistics and Medical Informatics, University of Wisconsin-Madison (S.K.). LevyD@nih.gov.

Abstract

Background: Cardiovascular disease (CVD) reflects a highly coordinated complex of traits. Although genome-wide association studies have reported numerous single nucleotide polymorphisms (SNPs) to be associated with CVD, the role of most of these variants in disease processes remains unknown.

Methods and results: We built a CVD network using 1512 SNPs associated with 21 CVD traits in genome-wide association studies (at P≤5×10(-8)) and cross-linked different traits by virtue of their shared SNP associations. We then explored whole blood gene expression in relation to these SNPs in 5257 participants in the Framingham Heart Study. At a false discovery rate <0.05, we identified 370 cis-expression quantitative trait loci (eQTLs; SNPs associated with altered expression of nearby genes) and 44 trans-eQTLs (SNPs associated with altered expression of remote genes). The eQTL network revealed 13 CVD-related modules. Searching for association of eQTL genes with CVD risk factors (lipids, blood pressure, fasting blood glucose, and body mass index) in the same individuals, we found examples in which the expression of eQTL genes was significantly associated with these CVD phenotypes. In addition, mediation tests suggested that a subset of SNPs previously associated with CVD phenotypes in genome-wide association studies may exert their function by altering expression of eQTL genes (eg, LDLR and PCSK7), which in turn may promote interindividual variation in phenotypes.

Conclusions: Using a network approach to analyze CVD traits, we identified complex networks of SNP-phenotype and SNP-transcript connections. Integrating the CVD network with phenotypic data, we identified biological pathways that may provide insights into potential drug targets for treatment or prevention of CVD.

Keywords: cardiovascular disease; gene expression/regulation network; genetic variation.

Publication types

Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't
Validation Study

MeSH terms

Adult
Cardiovascular Diseases / genetics*
Chromosome Mapping
Coronary Artery Disease / genetics
Diabetes Mellitus, Type 1 / genetics
Female
Gene Expression
Gene Regulatory Networks / genetics*
Genetic Variation
Genome-Wide Association Study
Humans
LDL-Receptor Related Protein-Associated Protein / genetics
Lipoproteins, HDL / genetics
Lipoproteins, LDL / genetics
Male
Phenotype
Polymorphism, Single Nucleotide / genetics*
Quantitative Trait Loci / genetics*
Risk Factors
Smoking / genetics

Substances

LDL-Receptor Related Protein-Associated Protein
Lipoproteins, HDL
Lipoproteins, LDL

Abstract

Publication types

MeSH terms

Substances

Grants and funding