ArticleGenome medicine2021
Highly elevated polygenic risk scores are better predictors of myocardial infarction risk early in life than later.
Article in Genome medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed, 58 citations in OpenAlex.
- Multidomain risk profiles and documented polyvascular involvement across atherosclerotic vascular beds.American journal of preventive cardiology · 2026Article
- Pervasive interactions between exposures and polygenic risk can inform more effective clinical and behavioral interventions.Nature genetics · 2026Article
- The oligogenic inheritance test GCOD detects risk genes and their interactions in congenital heart defects.Genome research · 2026Article
- Insights from GWAS, TWAS, and DEG analysis: CDKN2B-AS1, MAP3K4, and P2RX2-encoded P2X2 receptor identified as potential therapeutic targets for ischemic heart disease in Russian adults and long-living individuals.Frontiers in cardiovascular medicine · 2026Article
- Assessing individual genetic susceptibility to metabolic syndrome: interpretable machine learning method.Annals of medicine · 2025Article
- Risk prediction of early-onset myocardial infarction using plasma proteomics, conventional risk factors, and polygenic risk score.Nutrition & metabolism · 2025Article
- Greater value add from electronic health records than polygenic risk scores for predicting myocardial infarction in machine learning.Communications medicine · 2025Article
- Investigation of the characteristics of LDLR gene rs688 polymorphism and its association with dyslipidemia in patients at high to very high cardiovascular risk.BMC cardiovascular disorders · 2025Article
- Meta-prediction of coronary artery disease risk.Nature medicine · 2025Article
- Article
- Genetic association of NEAT1 gene polymorphism with the progression of colorectal cancer.Journal of Cancer · 2025Article
- Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations.Human reproduction update · 2024Review
- Identifying and characterizing disease subpopulations that most benefit from polygenic risk scores.Scientific reports · 2024Article
- Functional variants of the pentraxin 3 gene are associated with the metastasis and progression of prostate cancer.Journal of cellular and molecular medicine · 2024Article
- Dual exposure-by-polygenic score interactions highlight disparities across social groups in the proportion needed to benefit.medRxiv : the preprint server for health sciences · 2024Article
- Recent advances in polygenic scores: translation, equitability, methods and FAIR tools.Genome medicine · 2024Review
- Polygenic risk score predicts all-cause death in East Asian patients with prior coronary artery disease.Frontiers in cardiovascular medicine · 2024Article
- Risk of adverse cardiovascular events based on common genetic variants in 8-year follow-up of the LIPIDOGEN2015 population using the polygenic risk score (PRS): study design and methodology.Archives of medical science : AMS · 2024Article
- Implementing Reporting Standards for Polygenic Risk Scores for Atherosclerotic Cardiovascular Disease.Current atherosclerosis reports · 2023Review
- Genetic Risk Score for Prediction of Coronary Heart Disease in the Korean Genome and Epidemiology Study.Reviews in cardiovascular medicine · 2023Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundSeveral polygenic risk scores (PRS) have been developed for cardiovascular risk prediction, but the additive value of including PRS together with conventional risk factors for risk prediction is questionable. This study assesses the clinical utility of including four PRS generated from 194, 46K, 1.5M, and 6M SNPs, along with conventional risk factors, to predict risk of ischemic heart disease (IHD), myocardial infarction (MI), and first MI event on or before age 50 (early MI).
methodsA cross-validated logistic regression (LR) algorithm was trained either on ~ 440K European ancestry individuals from the UK Biobank (UKB), or the full UKB population, including as features different combinations of conventional established-at-birth risk factors (ancestry, sex) and risk factors that are non-fixed over an individual's lifespan (age, BMI, hypertension, hyperlipidemia, diabetes, smoking, family history), with and without also including PRS. The algorithm was trained separately with IHD, MI, and early MI as prediction labels.
resultsWhen LR was trained using risk factors established-at-birth, adding the four PRS significantly improved the area under the curve (AUC) for IHD (0.62 to 0.67) and MI (0.67 to 0.73), as well as for early MI (0.70 to 0.79). When LR was trained using all risk factors, adding the four PRS only resulted in a significantly higher disease prevalence in the 98th and 99th percentiles of both the IHD and MI scores.
conclusionsPRS improve cardiovascular risk stratification early in life when knowledge of later-life risk factors is unavailable. However, by middle age, when many risk factors are known, the improvement attributed to PRS is marginal for the general population.
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