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. 2023 Feb 1;8(2):130-137.
doi: 10.1001/jamacardio.2022.4466.

Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention

Affiliations

Predictive Utility of a Coronary Artery Disease Polygenic Risk Score in Primary Prevention

Nicholas A Marston et al. JAMA Cardiol. .

Abstract

Importance: The clinical utility of polygenic risk scores (PRS) for coronary artery disease (CAD) has not yet been established.

Objective: To investigate the ability of a CAD PRS to potentially guide statin initiation in primary prevention after accounting for age and clinical risk.

Design, setting, and participants: This was a longitudinal cohort study with enrollment starting on January 1, 2006, and ending on December 31, 2010, with data updated to mid-2021, using data from the UK Biobank, a long-term population study of UK citizens. A replication analysis was performed in Biobank Japan. The analysis included all patients without a history of CAD and who were not taking lipid-lowering therapy. Data were analyzed from January 1 to June 30, 2022.

Exposures: Polygenic risk for CAD was defined as low (bottom 20%), intermediate, and high (top 20%) using a CAD PRS including 241 genome-wide significant single-nucleotide variations (SNVs). The pooled cohort equations were used to estimate 10-year atherosclerotic cardiovascular disease (ASCVD) risk and classify individuals as low (<5%), borderline (5-<7.5%), intermediate (7.5-<20%), or high risk (≥20%).

Main outcomes and measures: Myocardial infarction (MI) and ASCVD events (defined as incident clinical CAD [including MI], stroke, or CV death).

Results: A total of 330 201 patients (median [IQR] age, 57 [40-74] years; 189 107 female individuals [57%]) were included from the UK Biobank. Over the 10-year follow-up, 4454 individuals had an MI. The CAD PRS was significantly associated with the risk of MI in all age groups but had significantly stronger risk prediction at younger ages (age <50 years: hazard ratio [HR] per 1 SD of PRS, 1.72; 95% CI, 1.56-1.89; age 50-60 years: HR, 1.46; 95% CI, 1.38-1.53; age >60 years: HR, 1.42; 95% CI, 1.37-1.48; P for interaction <.001). In patients younger than 50 years, those with high PRS had a 3- to 4-fold increased associated risk of MI compared with those in the low PRS category. A significant interaction between CAD PRS and age was replicated in Biobank Japan. When CAD PRS testing was added to the clinical ASCVD risk score in individuals younger than 50 years, 591 of 4373 patients (20%) with borderline risk were risk stratified into intermediate risk, warranting initiation of statin therapy and 3198 of 7477 patients (20%) with both borderline or intermediate risk were stratified as low risk, thus not warranting therapy.

Conclusions and relevance: Results of this cohort study suggest that the predictive ability of a CAD PRS was greater in younger individuals and can be used to better identify patients with borderline and intermediate clinical risk who should initiate statin therapy.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Marston reported receiving presentation fees from Amgen; nonfinancial support from Ionis and Pfizer; grants from the National Institutes of Health; and participating in clinical trials with Amgen, Pfizer, Novartis, and AstraZeneca without personal fees, payments, or increase in salary. Dr Pirruccello reported receiving grant support from the National Institutes of Health; personal fees from Maze Therapeutics; and research support from IBM Research outside the submitted work. Dr Kamanu reported being a member of the TIMI Study Group, which has received institutional research grant support through Brigham and Women's Hospital from Abbott, Amgen, Aralez, AstraZeneca, Bayer HealthCare Pharmaceuticals Inc, Brahms, Daiichi Sankyo, Eisai, GlaxoSmithKline, Intarcia, Janssen, MedImmune, Merck, Novartis, Pfizer, Poxel, Quark Pharmaceuticals, Roche, Takeda, The Medicines Company, and Zora Biosciences. Dr Weng reported receiving grants from the American Heart Association, the National Institutes of Health, and IBM outside the submitted work. Dr Roselli reported receiving a grant from Bayer AG to the Broad Institute. Dr Butterworth reported receiving grants from Bayer, Biogen, BioMarin, AstraZeneca, Novartis, Sanofi, Bioverativ, Merck; research funding from the National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Genomics, UK Medical Research Council, British Heart Foundation, the National Institute for Health and Care Research Cambridge BRC, Health Data Research UK, Bioverativ, Merck, Novartis, and Sanofi; and personal fees from Novartis outside the submitted work. Dr Lubitz reported receiving grants from the National Institutes of Health, the American Heart Association, Boehringer Ingelheim, Fitbit, IBM, Bristol Myers Squibb /Pfizer, and Bayer AG; and personal fees from Bristol Myers Squibb /Pfizer, INVITAE, Blackstone Life Sciences, and Bayer AG outside the submitted work. Dr Ellinor reported receiving grants from Bayer AG and IBM Health and personal fees from Bayer AG, Novartis, and MyoKardia outside the submitted work. Dr Sabatine reported receiving institutional grants from Abbott, Amgen, Anthos Therapeutics, Aralez, AstraZeneca, Bayer, Daiichi Sankyo, Eisai, GlaxoSmithKline, Intarcia, Ionis, Medicines Company, MedImmune, Merck, Novartis, Pfizer, Poxel, Quark Pharmaceuticals, Takeda, and additional grant support through Brigham and Women’s Hospital from ARCA Biopharma Inc, Janssen Research and Development, Siemens Healthcare Diagnostics Inc, Softcell Medical Limited, Regeneron, Roche, and Zora Biosciences; and consulting fees from Althera, Amgen, Anthos Therapeutics, AstraZeneca, Beren Therapeutics, Bristol Myers Squibb, CVS Caremark, DalCor, Dr Reddy's Laboratories, Dyrnamix, Esperion, IFM Therapeutics, Fibrogen, Ionis, Intarcia, Janssen, MedImmune, Merck, Moderna, Novartis, Novo Nordisk, and Silence Therapeutics outside the submitted work. Dr Ruff reported receiving grants from Boehringer Ingelheim, Daiichi Sankyo, MedImmune, and National Institute of Health; being a member of the TIMI Study Group, which has received institutional research grant support from Abbott, Amgen, Aralez, AstraZeneca, Bayer HealthCare Pharmaceuticals Inc, Brahms, Daiichi Sankyo, Eisai, GlaxoSmithKline, Intarcia, Janssen, MedImmune, Merck, Novartis, Pfizer, Poxel, Quark Pharmaceuticals, Roche, Takeda, The Medicines Company, and Zora Biosciences; and receiving personal fees from Bayer, Bristol Myers Squibb, Boehringer Ingelheim, Daiichi Sankyo, Janssen, MedImmune, Pfizer, Portola, and Anthos outside the submitted work. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Hazard Ratio (HR) for Myocardial Infarction (MI) as a Function of Age at Baseline
A, HR for MI per 1-SD increase in the coronary artery disease (CAD) polygenic risk score (PRS) (P for interaction <.001). B, HR for MI by CAD genetic risk categories. High PRS represents the top 20% of the distribution, intermediate the middle 60%, and low the bottom 20%.
Figure 2.
Figure 2.. Proportion of Myocardial Infarction (MI) Risk Attributable to the Coronary Artery Disease Polygenic Risk Score (PRS) as a Function of Age at Baseline
Moving windows of 5 years were used to estimate the hazard ratio and its 95% CI at every age point and then smoothed into a penalized spline curve (P for interaction <.001).
Figure 3.
Figure 3.. Observed 10-Year Rate of Atherosclerotic Cardiovascular Disease (ASCVD) Events Stratified by ASCVD Risk Group and Polygenic Risk Score (PRS) in Primary Prevention
Data shown for participants younger than 50 years (A), between age 50 and 60 years (B), and older than 60 years (C). Error bars represent the Kaplan-Meier rate 95% CI. ACA indicates American College of Cardiology; AHA indicates American Heart Association; LDL, low-density lipoprotein.

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References

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