Xiangfeng Lu1, Xiaoge Niu2, Chong Shen2, Fangchao Liu2, Zhongying Liu2, Keyong Huang2, Laiyuan Wang2, Jianxin Li2, Dongsheng Hu2, Yingxin Zhao2, Xueli Yang2, Fanghong Lu1, Xiaoqing Liu2, Jie Cao2, Shufeng Chen2, Hongfan Li2, Wuzhuang Tang2, Zhanyun Ren2, Ling Yu2, Xianping Wu2, Xigui Wu2, Ying Li2, Huan Zhang2, Jianfeng Huang2, Zhibin Hu2, Hongbing Shen2, Cristen J Willer2, Dongfeng Gu2. 1. From the Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology (Xiangfeng Lu, X.N., Fangchao Liu, Z.L., K.H., L.W., J.L., J.C., S.C., H.L., Xigui Wu, Y.L., J.H., D.G.), State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing; Department of Epidemiology and Biostatistics (C.S., Z.H., H.S.), Center for Global Health, School of Public Health, Nanjing Medical University; Department of Biostatistics and Epidemiology (D.H.), School of Public Health, Shenzhen University Health Science Center, Guangdong; Cardio-Cerebrovascular Control and Research Center (Y.Z., Fanghong Lu), Institute of Basic Medicine, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan; Tianjin Key Laboratory of Environment, Nutrition and Public Health (X.Y.), Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin; Division of Epidemiology (Xiaoqing Liu), Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou; Department of Neurology (W.T., Z.R.), Affiliated Yixing People's Hospital of Jiangsu University, People's Hospital of Yixing City, Yixing; Department of Cardiology (L.Y.), Fujian Provincial Hospital, Fuzhou; Center for Chronic and Noncommunicable Disease Control and Prevention (Xianping Wu), Sichuan Center for Disease Control and Prevention, Chengdu; Center for Genetic Epidemiology and Genomics (H.Z.), School of Public Health and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou; Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancer (H.S.), Chinese Academy of Medical Sciences (2019RU038); and Department of Internal Medicine, Division of Cardiovascular Medicine (C.J.W.), and Department of Human Genetics (C.J.W.), University of Michigan, Ann Arbor. xiangfenglu@sina.com. 2. From the Key Laboratory of Cardiovascular Epidemiology and Department of Epidemiology (Xiangfeng Lu, X.N., Fangchao Liu, Z.L., K.H., L.W., J.L., J.C., S.C., H.L., Xigui Wu, Y.L., J.H., D.G.), State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing; Department of Epidemiology and Biostatistics (C.S., Z.H., H.S.), Center for Global Health, School of Public Health, Nanjing Medical University; Department of Biostatistics and Epidemiology (D.H.), School of Public Health, Shenzhen University Health Science Center, Guangdong; Cardio-Cerebrovascular Control and Research Center (Y.Z., Fanghong Lu), Institute of Basic Medicine, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan; Tianjin Key Laboratory of Environment, Nutrition and Public Health (X.Y.), Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin; Division of Epidemiology (Xiaoqing Liu), Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou; Department of Neurology (W.T., Z.R.), Affiliated Yixing People's Hospital of Jiangsu University, People's Hospital of Yixing City, Yixing; Department of Cardiology (L.Y.), Fujian Provincial Hospital, Fuzhou; Center for Chronic and Noncommunicable Disease Control and Prevention (Xianping Wu), Sichuan Center for Disease Control and Prevention, Chengdu; Center for Genetic Epidemiology and Genomics (H.Z.), School of Public Health and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou; Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancer (H.S.), Chinese Academy of Medical Sciences (2019RU038); and Department of Internal Medicine, Division of Cardiovascular Medicine (C.J.W.), and Department of Human Genetics (C.J.W.), University of Michigan, Ann Arbor.
Abstract
OBJECTIVE: To construct a polygenic risk score (PRS) for stroke and evaluate its utility in risk stratification and primary prevention for stroke. METHODS: Using a meta-analytic approach and large genome-wide association results for stroke and stroke-related traits in East Asians, we generated a combined PRS (metaPRS) by incorporating 534 genetic variants in a training set of 2,872 patients with stroke and 2,494 controls. We then validated its association with incident stroke using Cox regression models in large Chinese population-based prospective cohorts comprising 41,006 individuals. RESULTS: During a total of 367,750 person-years (mean follow-up 9.0 years), 1,227 participants developed stroke before age 80 years. Individuals with high polygenic risk had an about 2-fold higher risk of incident stroke compared with those with low polygenic risk (hazard ratio [HR] 1.99, 95% confidence interval [CI] 1.66-2.38), with the lifetime risk of stroke being 25.2% (95% CI 22.5%-27.7%) and 13.6% (95% CI 11.6%-15.5%), respectively. Individuals with both high polygenic risk and family history displayed lifetime risk as high as 41.1% (95% CI 31.4%-49.5%). Individuals with high polygenic risk achieved greater benefits in terms of absolute risk reductions from adherence to ideal fasting blood glucose and total cholesterol than those with low polygenic risk. Maintaining favorable cardiovascular health (CVH) profile could substantially mitigate the increased risk conferred by high polygenic risk to the level of low polygenic risk (from 34.6% to 13.2%). CONCLUSIONS: Our metaPRS has great potential for risk stratification of stroke and identification of individuals who may benefit more from maintaining ideal CVH. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that metaPRS is predictive of stroke risk.
OBJECTIVE: To construct a polygenic risk score (PRS) for stroke and evaluate its utility in risk stratification and primary prevention for stroke. METHODS: Using a meta-analytic approach and large genome-wide association results for stroke and stroke-related traits in East Asians, we generated a combined PRS (metaPRS) by incorporating 534 genetic variants in a training set of 2,872 patients with stroke and 2,494 controls. We then validated its association with incident stroke using Cox regression models in large Chinese population-based prospective cohorts comprising 41,006 individuals. RESULTS: During a total of 367,750 person-years (mean follow-up 9.0 years), 1,227 participants developed stroke before age 80 years. Individuals with high polygenic risk had an about 2-fold higher risk of incident stroke compared with those with low polygenic risk (hazard ratio [HR] 1.99, 95% confidence interval [CI] 1.66-2.38), with the lifetime risk of stroke being 25.2% (95% CI 22.5%-27.7%) and 13.6% (95% CI 11.6%-15.5%), respectively. Individuals with both high polygenic risk and family history displayed lifetime risk as high as 41.1% (95% CI 31.4%-49.5%). Individuals with high polygenic risk achieved greater benefits in terms of absolute risk reductions from adherence to ideal fasting blood glucose and total cholesterol than those with low polygenic risk. Maintaining favorable cardiovascular health (CVH) profile could substantially mitigate the increased risk conferred by high polygenic risk to the level of low polygenic risk (from 34.6% to 13.2%). CONCLUSIONS: Our metaPRS has great potential for risk stratification of stroke and identification of individuals who may benefit more from maintaining ideal CVH. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that metaPRS is predictive of stroke risk.
Authors: David D Berg; Stephen D Wiviott; Benjamin M Scirica; Yared Gurmu; Ofri Mosenzon; Sabina A Murphy; Deepak L Bhatt; Lawrence A Leiter; Darren K McGuire; John P H Wilding; Per Johanson; Peter A Johansson; Anna Maria Langkilde; Itamar Raz; Eugene Braunwald; Marc S Sabatine Journal: Circulation Date: 2019-08-31 Impact factor: 29.690
Authors: Chuanhui Dong; Tatjana Rundek; Clinton B Wright; Zane Anwar; Mitchell S V Elkind; Ralph L Sacco Journal: Circulation Date: 2012-05-22 Impact factor: 29.690
Authors: Gina M Peloso; Alexa S Beiser; Claudia L Satizabal; Vanessa Xanthakis; Ramachandran S Vasan; Matthew P Pase; Anita L Destefano; Sudha Seshadri Journal: Neurology Date: 2020-07-20 Impact factor: 9.910
Authors: L Duncan; H Shen; B Gelaye; J Meijsen; K Ressler; M Feldman; R Peterson; B Domingue Journal: Nat Commun Date: 2019-07-25 Impact factor: 14.919
Authors: Hayato Tada; Dov Shiffman; Sekar Kathiresan; Olle Melander; J Gustav Smith; Marketa Sjögren; Steven A Lubitz; Patrick T Ellinor; Judy Z Louie; Joseph J Catanese; Gunnar Engström; James J Devlin Journal: Stroke Date: 2014-08-14 Impact factor: 7.914