Amit V Khera1,2,3,4, Mark Chaffin3, Seyedeh M Zekavat3,5, Ryan L Collins1,4, Carolina Roselli3, Pradeep Natarajan2,3,4, Judith H Lichtman6, Gail D'Onofrio7, Jennifer Mattera8, Rachel Dreyer7, John A Spertus9, Kent D Taylor10,11, Bruce M Psaty12,13, Stephen S Rich14, Wendy Post15, Namrata Gupta3, Stacey Gabriel3, Eric Lander3,16,17, Yii-Der Ida Chen10,11, Michael E Talkowski1,4, Jerome I Rotter10,11, Harlan M Krumholz8, Sekar Kathiresan1,2,3,4. 1. Center for Genomic Medicine (A.V.K., R.L.C., M.E.T., S.K.), Massachusetts General Hospital, Boston. 2. Division of Cardiology (A.V.K., P.N., S.K.), Massachusetts General Hospital, Boston. 3. Cardio-vascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA (A.V.K., M.C., S.M.Z., C.R., P.N., N.G., S.G., E.L., S.K.). 4. Department of Medicine (A.V.K., R.L.C., P.N., M.E.T., S.K.), Harvard Medical School, Boston, MA. 5. Yale University School of Medicine, New Haven, CT (S.M.Z.). 6. Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT (J.H.L.). 7. Department of Emergency Medicine, Yale University, New Haven, CT (G.D., R.D.). 8. Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, CT (J.M., H.M.K.). 9. Department of Biomedical and Health Informatics, Saint Luke's Mid America Heart Institute, University of Missouri, Kansas City (J.A.S.). 10. Institute for Translational Genomics and Population Sciences, LABioMed, Torrance, CA (K.D.T., Y.-D.I.C., J.I.R.). 11. Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, CA (K.D.T., Y.-D.I.C., J.I.R.). 12. University of Washington and Kaiser Permanente, Seattle (B.M.P.). 13. Washington Health Research Institute, Seattle (B.M.P.). 14. Center for Public Health Genomics, University of Virginia School of Medicine, Richmond (S.S.R.). 15. Johns Hopkins University School of Medicine, Baltimore, MD (W.P.). 16. Program in Health Sciences and Technology (E.L.), Harvard Medical School, Boston, MA. 17. Department of Biology, Massachusetts Institute of Technology, Cambridge (E.L.).
Abstract
BACKGROUND: The relative prevalence and clinical importance of monogenic mutations related to familial hypercholesterolemia and of high polygenic score (cumulative impact of many common variants) pathways for early-onset myocardial infarction remain uncertain. Whole-genome sequencing enables simultaneous ascertainment of both monogenic mutations and polygenic score for each individual. METHODS: We performed deep-coverage whole-genome sequencing of 2081 patients from 4 racial subgroups hospitalized in the United States with early-onset myocardial infarction (age ≤55 years) recruited with a 2:1 female-to-male enrollment design. We compared these genomes with those of 3761 population-based control subjects. We first identified individuals with a rare, monogenic mutation related to familial hypercholesterolemia. Second, we calculated a recently developed polygenic score of 6.6 million common DNA variants to quantify the cumulative susceptibility conferred by common variants. We defined high polygenic score as the top 5% of the control distribution because this cutoff has previously been shown to confer similar risk to that of familial hypercholesterolemia mutations. RESULTS: The mean age of the 2081 patients presenting with early-onset myocardial infarction was 48 years, and 66% were female. A familial hypercholesterolemia mutation was present in 36 of these patients (1.7%) and was associated with a 3.8-fold (95% CI, 2.1-6.8; P<0.001) increased odds of myocardial infarction. Of the patients with early-onset myocardial infarction, 359 (17.3%) carried a high polygenic score, associated with a 3.7-fold (95% CI, 3.1-4.6; P<0.001) increased odds. Mean estimated untreated low-density lipoprotein cholesterol was 206 mg/dL in those with a familial hypercholesterolemia mutation, 132 mg/dL in those with high polygenic score, and 122 mg/dL in those in the remainder of the population. Although associated with increased risk in all racial groups, high polygenic score demonstrated the strongest association in white participants ( P for heterogeneity=0.008). CONCLUSIONS: Both familial hypercholesterolemia mutations and high polygenic score are associated with a >3-fold increased odds of early-onset myocardial infarction. However, high polygenic score has a 10-fold higher prevalence among patients presents with early-onset myocardial infarction. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00597922.
BACKGROUND: The relative prevalence and clinical importance of monogenic mutations related to familial hypercholesterolemia and of high polygenic score (cumulative impact of many common variants) pathways for early-onset myocardial infarction remain uncertain. Whole-genome sequencing enables simultaneous ascertainment of both monogenic mutations and polygenic score for each individual. METHODS: We performed deep-coverage whole-genome sequencing of 2081 patients from 4 racial subgroups hospitalized in the United States with early-onset myocardial infarction (age ≤55 years) recruited with a 2:1 female-to-male enrollment design. We compared these genomes with those of 3761 population-based control subjects. We first identified individuals with a rare, monogenic mutation related to familial hypercholesterolemia. Second, we calculated a recently developed polygenic score of 6.6 million common DNA variants to quantify the cumulative susceptibility conferred by common variants. We defined high polygenic score as the top 5% of the control distribution because this cutoff has previously been shown to confer similar risk to that of familial hypercholesterolemia mutations. RESULTS: The mean age of the 2081 patients presenting with early-onset myocardial infarction was 48 years, and 66% were female. A familial hypercholesterolemia mutation was present in 36 of these patients (1.7%) and was associated with a 3.8-fold (95% CI, 2.1-6.8; P<0.001) increased odds of myocardial infarction. Of the patients with early-onset myocardial infarction, 359 (17.3%) carried a high polygenic score, associated with a 3.7-fold (95% CI, 3.1-4.6; P<0.001) increased odds. Mean estimated untreated low-density lipoprotein cholesterol was 206 mg/dL in those with a familial hypercholesterolemia mutation, 132 mg/dL in those with high polygenic score, and 122 mg/dL in those in the remainder of the population. Although associated with increased risk in all racial groups, high polygenic score demonstrated the strongest association in white participants ( P for heterogeneity=0.008). CONCLUSIONS: Both familial hypercholesterolemia mutations and high polygenic score are associated with a >3-fold increased odds of early-onset myocardial infarction. However, high polygenic score has a 10-fold higher prevalence among patients presents with early-onset myocardial infarction. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00597922.
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