ArticleFrontiers in genetics2013
Evaluation of genetic risk score models in the presence of interaction and linkage disequilibrium.
Article in Frontiers in genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis of genome-wide association study identifies FBN2 as a novel locus associated with systemic lupus erythematosus in Thai population.Arthritis research & therapy · 2020Pooled it
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- Analysis of Pancreatic Cancer Genetic Risk Factors in a Multi-Ethnic Population Sample.World journal of oncology · 2024Article
- Comparative analysis of genetic risk scores for predicting biochemical recurrence in prostate cancer patients after radical prostatectomy.BMC urology · 2024Article
- Interplay of the Mediterranean diet and genetic hypertension risk on blood pressure in European adolescents: Findings from the HELENA study.European journal of pediatrics · 2024Article
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- Genetic risk assessment based on association and prediction studies.Scientific reports · 2023Article
- Efficient gene-environment interaction testing through bootstrap aggregating.Scientific reports · 2023Article
- Development of a genetic risk score to predict the risk of hypertension in European adolescents from the HELENA study.Frontiers in cardiovascular medicine · 2023Article
- Article
- Evaluation of tree-based statistical learning methods for constructing genetic risk scores.BMC bioinformatics · 2022Article
- Development of a Genetic Risk Score to predict the risk of overweight and obesity in European adolescents from the HELENA study.Scientific reports · 2021Article
- Machine and Deep Learning in Molecular and Genetic Aspects of Sleep Research.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2021Review
- Polygenic Score for β-Blocker Survival Benefit in European Ancestry Patients With Reduced Ejection Fraction Heart Failure.Circulation. Heart failure · 2020Article
- The genetic risk for hypertension is lower among the Hungarian Roma population compared to the general population.PloS one · 2020Article
- A Weighted Genetic Risk Score Based on Four APOE-Independent Alzheimer's Disease Risk Loci May Supplement APOE E4 for Better Disease Prediction.Journal of molecular neuroscience : MN · 2019Article
- Machine Learning SNP Based Prediction for Precision Medicine.Frontiers in genetics · 2019Review
- Comparison of weighting approaches for genetic risk scores in gene-environment interaction studies.BMC genetics · 2017Article
- Article
- Validating the role of the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI) and a genetic risk score in progression to cognitive impairment in a population-based cohort of older adults followed for 12 years.Alzheimer's research & therapy · 2017Article
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2 authors.
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Abstract
In the area of genetic epidemiology, genetic risk predictive modeling is becoming an important area of translational success. As an increasing number of genetic variants are successfully discovered, the use of multiple genetic variants in constructing a genetic risk score (GRS) for modeling has been widely applied using a variety of approaches. Previously, we compared the performance of a simple, additive GRS with weighted GRS approaches, but our initial simulation experiment assumed very simple models without many of the complications found in real genetic studies. In particular, interactions between variants and linkage disequilibrium (LD) (indirect mapping) remain important and challenging problems for GRS modeling. In the present study, we applied two simulation strategies to mimic various types of epistasis to evaluate their impact on the performance of the GRS models. We simulated a range of models demonstrating statistical interaction and linkage disequilibrium. Three genetic risk models were compared in terms of power, type I error, C-statistic and AIC, including a simple count GRS (SC-GRS), an odds ratio weighted GRS (OR-GRS) and an explained variance weighted GRS (EV-GRS). Simulation factors of interest included allele frequencies, effect sizes, strengths of interaction, degrees of LD and heritability. We extensively examined the extent to how these interactions could influence the performance of genetic risk models. Our results show that the weighted methods outperform simple count method in general even if interaction or LD is present, with well controlled type I error.
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