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Circ Cardiovasc Genet. 2016 Dec;9(6):521-530. doi: 10.1161/CIRCGENETICS.116.001530. Epub 2016 Oct 25.

Defining a Contemporary Ischemic Heart Disease Genetic Risk Profile Using Historical Data.

Author information

1
From the Department of Medicine (J.D.M., S.L.v.D., Q.S.W., C.M.S., J.C.D., D.M.R.), Department of Pediatrics (S.L.v.D.), Vanderbilt Epidemiology Center (T.L.E.), Biomedical Informatics (L.B., J.C.D., D.M.R.), and Department of Pharmacology (D.M.R.), Vanderbilt University, Nashville, TN; Essentia Institute of Rural Health, Duluth, MN (C.A.M.); Center for Biomedical Research Informatics, North Shore University Health System, Evanston, IL (W.T.); Department of Health Policy and Management Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD (C.G.C.); Departments of Medicine (Medical Genetics) and Genome Sciences (G.P.J.) and Departments of Biomedical Informatics and Medical Education (D.R.C.), University of Washington, Seattle; Group Health Research Institute, Seattle, WA (E.B.L.); Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN (I.J.K.); Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (J.A.P.); and Biomedical Informatics Research Center (P.L.P., J.G.L.) and Center for Human Genetics (M.H.B.), Marshfield Clinic Research Foundation, WI. jonathan.d.mosley@vanderbilt.edu.
2
From the Department of Medicine (J.D.M., S.L.v.D., Q.S.W., C.M.S., J.C.D., D.M.R.), Department of Pediatrics (S.L.v.D.), Vanderbilt Epidemiology Center (T.L.E.), Biomedical Informatics (L.B., J.C.D., D.M.R.), and Department of Pharmacology (D.M.R.), Vanderbilt University, Nashville, TN; Essentia Institute of Rural Health, Duluth, MN (C.A.M.); Center for Biomedical Research Informatics, North Shore University Health System, Evanston, IL (W.T.); Department of Health Policy and Management Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, MD (C.G.C.); Departments of Medicine (Medical Genetics) and Genome Sciences (G.P.J.) and Departments of Biomedical Informatics and Medical Education (D.R.C.), University of Washington, Seattle; Group Health Research Institute, Seattle, WA (E.B.L.); Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN (I.J.K.); Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (J.A.P.); and Biomedical Informatics Research Center (P.L.P., J.G.L.) and Center for Human Genetics (M.H.B.), Marshfield Clinic Research Foundation, WI.

Abstract

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.

KEYWORDS:

atherosclerosis; blood pressure; coronary artery disease; risk factors; triglycerides

PMID:
27780847
PMCID:
PMC5177499
DOI:
10.1161/CIRCGENETICS.116.001530
[Indexed for MEDLINE]
Free PMC Article

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