Polygenic risk scores for the prediction of cardiometabolic disease.
Jack William O'SullivanEuan A AshleyPerry Mark ElliottPublished in: European heart journal (2022)
Cardiometabolic diseases contribute more to global morbidity and mortality than any other group of disorders. Polygenic risk scores (PRSs), the weighted summation of individually small-effect genetic variants, represent an advance in our ability to predict the development and complications of cardiometabolic diseases. This article reviews the evidence supporting the use of PRS in seven common cardiometabolic diseases: coronary artery disease (CAD), stroke, hypertension, heart failure and cardiomyopathies, obesity, atrial fibrillation (AF), and type 2 diabetes mellitus (T2DM). Data suggest that PRS for CAD, AF, and T2DM consistently improves prediction when incorporated into existing clinical risk tools. In other areas such as ischaemic stroke and hypertension, clinical application appears premature but emerging evidence suggests that the study of larger and more diverse populations coupled with more granular phenotyping will propel the translation of PRS into practical clinical prediction tools.
Keyphrases
- atrial fibrillation
- coronary artery disease
- heart failure
- blood pressure
- type diabetes
- percutaneous coronary intervention
- metabolic syndrome
- glycemic control
- left atrial appendage
- left atrial
- magnetic resonance
- insulin resistance
- oral anticoagulants
- weight loss
- catheter ablation
- left ventricular
- magnetic resonance imaging
- computed tomography
- randomized controlled trial
- electronic health record
- acute coronary syndrome
- artificial intelligence
- coronary artery bypass grafting
- blood brain barrier
- venous thromboembolism
- aortic valve
- network analysis
- body mass index
- skeletal muscle