TY - JOUR
T1 - Defining a Contemporary Ischemic Heart Disease Genetic Risk Profile Using Historical Data
AU - Mosley, Jonathan D.
AU - Van Driest, Sara L.
AU - Wells, Quinn S.
AU - Shaffer, Christian M.
AU - Edwards, Todd L.
AU - Bastarache, Lisa
AU - McCarty, Catherine A.
AU - Thompson, Will
AU - Chute, Christopher G.
AU - Jarvik, Gail P.
AU - Crosslin, David R.
AU - Larson, Eric B.
AU - Kullo, Iftikhar J.
AU - Pacheco, Jennifer A.
AU - Peissig, Peggy L.
AU - Brilliant, Murray H.
AU - Linneman, James G.
AU - Denny, Josh C.
AU - Roden, Dan M.
N1 - Funding Information:
This work was supported by a career development award from the Vanderbilt Faculty Research Scholars Fund (Dr Mosley), American Heart Association (15MCPRP25620006 and 16FTF30130005; Dr Mosley), and PGRN (P50-GM115305) and R01 LM010685. BioVU is supported by institutional funding and by Clinical and Translational Science Awards grant UL1 TR000445 from National Center for Advancing Translational Sciences/National Institutes of Health. The Electronic Medical Records and Genomics (eMERGE) Network is funded by National Human Genome Research Institute and National Institute of General Medical Sciences: U01-HG8672 and U01-HG006378 (VUMC); U01-HG-004610 (Group Health Cooperative/University of Washington); U01-HG-004608 (Marshfield Clinic Research Foundation and VUMC); U01-HG-04599 (Mayo Clinic); U01HG004609 (Northwestern University); U01-HG-006378 and U01-HG-04603 (VUMC Coordinating Center); U01HG004438 (Center for Inherited Disease Research); and U01HG004424 (the Broad Institute) serving as Genotyping Centers. ARIC study (Atherosclerosis Risk in Communities) is supported by National Heart, Lung and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268 201100007C, HHSN268201100008C, HHSN268201100009C, HHSN 268201100010C, HHSN268201100011C, andHHSN268201100012C). Funding for GENEVA was provided by National Human Genome Research Institute grant U01HG004402 (E. Boerwinkle).
Publisher Copyright:
© 2016 American Heart Association, Inc.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Background-Continued reductions in morbidity and mortality attributable to ischemic heart disease (IHD) require an understanding of the changing epidemiology of this disease. We hypothesized that we could use genetic correlations, which quantify the shared genetic architectures of phenotype pairs and extant risk factors from a historical prospective study to define the risk profile of a contemporary IHD phenotype. Methods and Results-We used 37 phenotypes measured in the ARIC study (Atherosclerosis Risk in Communities; n=7716, European ancestry subjects) and clinical diagnoses from an electronic health record (EHR) data set (n=19 093). All subjects had genome-wide single-nucleotide polymorphism genotyping. We measured pairwise genetic correlations (rG) between the ARIC and EHR phenotypes using linear mixed models. The genetic correlation estimates between the ARIC risk factors and the EHR IHD were modestly linearly correlated with hazards ratio estimates for incident IHD in ARIC (Pearson correlation [r]=0.62), indicating that the 2 IHD phenotypes had differing risk profiles. For comparison, this correlation was 0.80 when comparing EHR and ARIC type 2 diabetes mellitus phenotypes. The EHR IHD phenotype was most strongly correlated with ARIC metabolic phenotypes, including total:high-density lipoprotein cholesterol ratio (rG=-0.44, P=0.005), high-density lipoprotein (rG=-0.48, P=0.005), systolic blood pressure (rG=0.44, P=0.02), and triglycerides (rG=0.38, P=0.02). EHR phenotypes related to type 2 diabetes mellitus, atherosclerotic, and hypertensive diseases were also genetically correlated with these ARIC risk factors. Conclusions-The EHR IHD risk profile differed from ARIC and indicates that treatment and prevention efforts in this population should target hypertensive and metabolic disease.
AB - Background-Continued reductions in morbidity and mortality attributable to ischemic heart disease (IHD) require an understanding of the changing epidemiology of this disease. We hypothesized that we could use genetic correlations, which quantify the shared genetic architectures of phenotype pairs and extant risk factors from a historical prospective study to define the risk profile of a contemporary IHD phenotype. Methods and Results-We used 37 phenotypes measured in the ARIC study (Atherosclerosis Risk in Communities; n=7716, European ancestry subjects) and clinical diagnoses from an electronic health record (EHR) data set (n=19 093). All subjects had genome-wide single-nucleotide polymorphism genotyping. We measured pairwise genetic correlations (rG) between the ARIC and EHR phenotypes using linear mixed models. The genetic correlation estimates between the ARIC risk factors and the EHR IHD were modestly linearly correlated with hazards ratio estimates for incident IHD in ARIC (Pearson correlation [r]=0.62), indicating that the 2 IHD phenotypes had differing risk profiles. For comparison, this correlation was 0.80 when comparing EHR and ARIC type 2 diabetes mellitus phenotypes. The EHR IHD phenotype was most strongly correlated with ARIC metabolic phenotypes, including total:high-density lipoprotein cholesterol ratio (rG=-0.44, P=0.005), high-density lipoprotein (rG=-0.48, P=0.005), systolic blood pressure (rG=0.44, P=0.02), and triglycerides (rG=0.38, P=0.02). EHR phenotypes related to type 2 diabetes mellitus, atherosclerotic, and hypertensive diseases were also genetically correlated with these ARIC risk factors. Conclusions-The EHR IHD risk profile differed from ARIC and indicates that treatment and prevention efforts in this population should target hypertensive and metabolic disease.
KW - atherosclerosis
KW - blood pressure
KW - coronary artery disease
KW - risk factors
KW - triglycerides
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U2 - 10.1161/CIRCGENETICS.116.001530
DO - 10.1161/CIRCGENETICS.116.001530
M3 - Article
C2 - 27780847
AN - SCOPUS:85007236786
SN - 1942-325X
VL - 9
SP - 521
EP - 530
JO - Circulation: Cardiovascular Genetics
JF - Circulation: Cardiovascular Genetics
IS - 6
ER -