Trial reportPloS one2012
Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts.
Trial report in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02146872 (Premature Coronary Artery Disease - Clinical and Molecular Genetic Aspects), which is not on this map. Cited by 47 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Premature Coronary Artery Disease - Clinical and Molecular Genetic Aspects
Who cites it
47 citing papers in PubMed, 3 syntheses or guidelines pooled it, 122 citations in OpenAlex.
- Genomic prediction of coronary heart disease.European heart journal · 2016Pooled it
- Guideline
- Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials.Lancet (London, England) · 2015Pooled it
- Assessing genetic risk factors for early-onset coronary artery disease in Iranians.Research and practice in thrombosis and haemostasis · 2026Article
- Article
- Genetic Risk Score for Prediction of Coronary Heart Disease in the Korean Genome and Epidemiology Study.Reviews in cardiovascular medicine · 2023Article
- Genetic and modifiable risk factors combine multiplicatively in common disease.Clinical research in cardiology : official journal of the German Cardiac Society · 2023Article
- Advances and Applications of Polygenic Scores for Coronary Artery Disease.Annual review of medicine · 2023Review
- Prognostic Modelling Studies of Coronary Heart Disease-A Systematic Review of Conventional and Genetic Risk Factor Studies.Journal of cardiovascular development and disease · 2022Review
- Risk Prediction of Cardiovascular Events by Exploration of Molecular Data with Explainable Artificial Intelligence.International journal of molecular sciences · 2021Review
- The effect of CYP7B1 polymorphisms on the risk of coronary heart disease in Hainan Han population.BMC medical genomics · 2021Article
- Coronary Artery Disease Genetics Enlightened by Genome-Wide Association Studies.JACC. Basic to translational science · 2021Review
- Risk prediction of atrial fibrillation in the community combining biomarkers and genetics.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2021Article
- Genetic Risk Score for Coronary Heart Disease: Review.Journal of personalized medicine · 2020Review
- Polygenic Scores to Assess Atherosclerotic Cardiovascular Disease Risk: Clinical Perspectives and Basic Implications.Circulation research · 2020Review
- [Meaningful diagnostics: genetics].Herz · 2020Article
- Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction?Journal of the American Heart Association · 2019Article
- Genetic risk factors identified in populations of European descent do not improve the prediction of osteoporotic fracture and bone mineral density in Chinese populations.Scientific reports · 2019Article
- Electronic health record access by patients as an indicator of information seeking and sharing for cardiovascular health promotion in social networks: Secondary analysis of a randomized clinical trial.Preventive medicine reports · 2019Article
- Genetic susceptibility of five tagSNPs in the endothelin-1 (Bioscience reports · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
27 authors at 12 institutions in 6 countries.
Funding
Abstract
backgroundMore accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.
methodsUsing data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.
resultsBoth scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.
conclusionsGenetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.