ArticleGenetic epidemiology2015
Contemporary Considerations for Constructing a Genetic Risk Score: An Empirical Approach.
Article in Genetic epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genomic prediction of coronary heart disease.European heart journal · 2016Pooled it
- Validation of a genetic risk score for atrial fibrillation: A prospective multicenter cohort study.PLoS medicine · 2018Trial
- Polygenic predisposition modifies the associations of fish oil supplementation with circulating omega-3 fatty acids: a cross-sectional gene-diet interaction study in UK Biobank.medRxiv : the preprint server for health sciences · 2026Article
- The accuracy of polygenic score models for BMI and Type II diabetes in the Native Hawaiian population.Communications biology · 2025Article
- A partitioned polygenic risk score reveals distinct contributions to psoriasis clinical phenotypes across a multi-ethnic cohort.Journal of translational medicine · 2024Article
- Health economic analysis of polygenic risk score use in primary prevention of coronary artery disease - A system dynamics model.American journal of preventive cardiology · 2024Article
- Pruning and thresholding approach for methylation risk scores in multi-ancestry populations.Epigenetics · 2023Article
- Interaction between genetic susceptibility to obesity and food intake on BMI in Finnish school-aged children.Scientific reports · 2023Article
- Genetic studies in the Pakistani population reveal novel associations with ventricular septal defects (VSDs).BMC pediatrics · 2023Article
- A partitioned 88-loci psoriasis genetic risk score reveals HLA and non-HLA contributions to clinical phenotypes in a Newfoundland psoriasis cohort.Frontiers in genetics · 2023Article
- "GENYAL" Study to Childhood Obesity Prevention: Methodology and Preliminary Results.Frontiers in nutrition · 2022Article
- GWAS findings improved genomic prediction accuracy of lipid profile traits: Tehran Cardiometabolic Genetic Study.Scientific reports · 2021Article
- Clinical Application of a Novel Genetic Risk Score for Ischemic Stroke in Patients With Cardiometabolic Disease.Circulation · 2021Article
- A polygenic biomarker to identify patients with severe hypercholesterolemia of polygenic origin.Molecular genetics & genomic medicine · 2020Article
- Genetic Risk Scores.Current protocols in human genetics · 2019Review
- Polygenic approaches to detect gene-environment interactions when external information is unavailable.Briefings in bioinformatics · 2019Review
- Performing different kinds of physical exercise differentially attenuates the genetic effects on obesity measures: Evidence from 18,424 Taiwan Biobank participants.PLoS genetics · 2019Article
- Article
- Leveraging information from genetic risk scores of coronary atherosclerosis.Current opinion in lipidology · 2017Review
- Genetic cardiovascular risk prediction: are we already there?European heart journal · 2016Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Genetic risk scores are an increasingly popular tool for summarizing the cumulative risk of a set of Single Nucleotide Polymorphisms (SNPs) with disease. Typically only the set of the SNPs that have reached genome-wide significance compose these scores. However recent work suggests that including additional SNPs may aid risk assessment. In this paper, we used the Atherosclerosis Risk in Communities (ARIC) Study cohort to illustrate how one can choose the optimal set of SNPs for a genetic risk score (GRS). In addition to P-value threshold, we also examined linkage disequilibrium, imputation quality, and imputation type. We provide a variety of evaluation metrics. Results suggest that P-value threshold had the greatest impact on GRS quality for the outcome of coronary heart disease, with an optimal threshold around 0.001. However, GRSs are relatively robust to both linkage disequilibrium and imputation quality. We also show that the optimal GRS partially depends on the evaluation metric and consequently the way one intends to use the GRS. Overall the implications highlight both the robustness of GRS and a means to empirically choose the best set of GRSs.
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