A polygenic risk score improves risk stratification of coronary artery disease: a large-scale prospective Chinese cohort study

Abstract Aims To construct a polygenic risk score (PRS) for coronary artery disease (CAD) and comprehensively evaluate its potential in clinical utility for primary prevention in Chinese populations. Methods and results Using meta-analytic approach and large genome-wide association results for CAD and CAD-related traits in East Asians, a PRS comprising 540 genetic variants was developed in a training set of 2800 patients with CAD and 2055 controls, and was further assessed for risk stratification for CAD integrating with the guideline-recommended clinical risk score in large prospective cohorts comprising 41 271 individuals. During a mean follow-up of 13.0 years, 1303 incident CAD cases were identified. Individuals with high PRS (the highest 20%) had about three-fold higher risk of CAD than the lowest 20% (hazard ratio 2.91, 95% confidence interval 2.43–3.49), with the lifetime risk of 15.9 and 5.8%, respectively. The addition of PRS to the clinical risk score yielded a modest yet significant improvement in C-statistic (1%) and net reclassification improvement (3.5%). We observed significant gradients in both 10-year and lifetime risk of CAD according to the PRS within each clinical risk strata. Particularly, when integrating high PRS, intermediate clinical risk individuals with uncertain clinical decision for intervention would reach the risk levels (10-year of 4.6 vs. 4.8%, lifetime of 17.9 vs. 16.6%) of high clinical risk individuals with intermediate (20–80%) PRS. Conclusion The PRS could stratify individuals into different trajectories of CAD risk, and further refine risk stratification for CAD within each clinical risk strata, demonstrating a great potential to identify high-risk individuals for targeted intervention in clinical utility.

[1]  A. Editorial.  Comments on the 2021 ESC guidelines on cardiovascular disease prevention in clinical practice. , 2022, Revista espanola de cardiologia.

[2]  Steffen E. Petersen,et al.  2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. , 2016, European journal of preventive cardiology.

[3]  R. Mägi,et al.  Population Bias in Polygenic Risk Prediction Models for Coronary Artery Disease , 2020, Circulation. Genomic and precision medicine.

[4]  H. Aburatani,et al.  Population-specific and trans-ancestry genome-wide analyses identify distinct and shared genetic risk loci for coronary artery disease , 2020, Nature Genetics.

[5]  A. Khera,et al.  Genome-Wide Polygenic Score, Clinical Risk Factors, and Long-Term Trajectories of Coronary Artery Disease , 2020, Arteriosclerosis, thrombosis, and vascular biology.

[6]  Judy H. Cho,et al.  Limitations of Contemporary Guidelines for Managing Patients at High Genetic Risk of Coronary Artery Disease. , 2020, Journal of the American College of Cardiology.

[7]  P. Natarajan,et al.  Polygenic Scores to Assess Atherosclerotic Cardiovascular Disease Risk , 2020, Circulation research.

[8]  P. Elliott,et al.  Predictive Accuracy of a Polygenic Risk Score-Enhanced Prediction Model vs a Clinical Risk Score for Coronary Artery Disease. , 2020, JAMA.

[9]  C. Robinson-Cohen,et al.  Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease. , 2020, JAMA.

[10]  Marco Valgimigli,et al.  2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. , 2019, European heart journal.

[11]  Benjamin Neale,et al.  Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults Implications for Primary Prevention , 2019 .

[12]  P. Ellinor,et al.  Predicting Benefit From Evolocumab Therapy in Patients With Atherosclerotic Disease Using a Genetic Risk Score , 2019, Circulation.

[13]  G. Abecasis,et al.  Patients With High Genome-Wide Polygenic Risk Scores for Coronary Artery Disease May Receive Greater Clinical Benefit From Alirocumab Treatment in the ODYSSEY OUTCOMES Trial , 2019, Circulation.

[14]  A. Khera,et al.  2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. , 2019, Journal of the American College of Cardiology.

[15]  M. Feldman,et al.  Analysis of polygenic risk score usage and performance in diverse human populations , 2019, Nature Communications.

[16]  J. Danesh,et al.  Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke , 2019, Nature Communications.

[17]  E. Zeggini,et al.  Genomics of disease risk in globally diverse populations , 2019, Nature Reviews Genetics.

[18]  S. Grundy,et al.  2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. , 2019, Journal of the American College of Cardiology.

[19]  Alicia R. Martin,et al.  Clinical use of current polygenic risk scores may exacerbate health disparities , 2019, Nature Genetics.

[20]  H. Krumholz,et al.  Characteristics of High Cardiovascular Risk in 1.7 Million Chinese Adults , 2019, Annals of Internal Medicine.

[21]  Helen E. Parkinson,et al.  The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 , 2018, Nucleic Acids Res..

[22]  [Guideline on the assessment and management of cardiovascular risk in China]. , 2019, Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine].

[23]  E. Topol,et al.  The personal and clinical utility of polygenic risk scores , 2018, Nature Reviews Genetics.

[24]  Pim van der Harst,et al.  Associations of Combined Genetic and Lifestyle Risks With Incident Cardiovascular Disease and Diabetes in the UK Biobank Study , 2018, JAMA cardiology.

[25]  Mary E. Haas,et al.  Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations , 2018, Nature Genetics.

[26]  Xueli Yang,et al.  Predicting lifetime risk for developing atherosclerotic cardiovascular disease in Chinese population: the China-PAR project. , 2018, Science bulletin.

[27]  Christopher R. Gignoux,et al.  Human demographic history impacts genetic risk prediction across diverse populations , 2016, bioRxiv.

[28]  Dermot F. Reilly,et al.  Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting , 2017, Circulation.

[29]  E. Boerwinkle,et al.  Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease. , 2016, The New England journal of medicine.

[30]  Ashutosh Kumar Singh,et al.  Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015 , 2016, The Lancet.

[31]  Xueli Yang,et al.  Predicting the 10-Year Risks of Atherosclerotic Cardiovascular Disease in Chinese Population: The China-PAR Project (Prediction for ASCVD Risk in China) , 2016, Circulation.

[32]  Xueli Yang,et al.  Risk stratification of atherosclerotic cardiovascular disease in Chinese adults , 2016, Chronic diseases and translational medicine.

[33]  Markus Perola,et al.  Genomic prediction of coronary heart disease , 2016, bioRxiv.

[34]  Olle Melander,et al.  Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials , 2015, The Lancet.

[35]  V. Salomaa,et al.  Genetic Risk Prediction and a 2-Stage Risk Screening Strategy for Coronary Heart Disease , 2013, Arteriosclerosis, thrombosis, and vascular biology.

[36]  D. Goff,et al.  Comparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals. , 2012, JAMA.

[37]  Udo Hoffmann,et al.  A Genetic Risk Score Is Associated With Incident Cardiovascular Disease and Coronary Artery Calcium: The Framingham Heart Study , 2012, Circulation. Cardiovascular genetics.

[38]  Ewout W Steyerberg,et al.  Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers , 2011, Statistics in medicine.

[39]  L. Peltonen,et al.  A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses , 2010, The Lancet.

[40]  M. Pencina,et al.  Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation , 2004, Statistics in medicine.

[41]  Hugo A. Katus,et al.  Myocardial infarction redefined--a consensus document of The Joint European Society of Cardiology/American College of Cardiology Committee for the redefinition of myocardial infarction. , 2000, European heart journal.

[42]  Robert Gray,et al.  A Proportional Hazards Model for the Subdistribution of a Competing Risk , 1999 .