ArticleScientific reports2020
Genetic architecture of complex traits and disease risk predictors.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 32 citations in OpenAlex.
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- Research progress and challenges of preimplantation genetic testing for polygenic diseases.Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2023Review
- Human height: a model common complex trait.Annals of human biology · 2023Review
- Polygenic Health Index, General Health, and Pleiotropy: Sibling Analysis and Disease Risk Reduction.Scientific reports · 2022Article
- Genomic medicine on the frontier of precision medicine.Journal of diabetes and metabolic disorders · 2022Review
- Complementary Experimental Methods in Genetics Open Up New Avenues of Research to Elucidate the Pathogenesis of Periodontitis.Advances in experimental medicine and biology · 2022Article
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- From Genotype to Phenotype: Polygenic Prediction of Complex Human Traits.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Association between the APOE gene polymorphism and lipid profile and the risk of atrial fibrillation.Lipids in health and disease · 2021Article
- Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine.Non-coding RNA · 2021Review
- Embryo Screening for Polygenic Disease Risk: Recent Advances and Ethical Considerations.Genes · 2021Article
- Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank.Genes · 2021Article
- Predicting Complex Traits and Exposures From Polygenic Scores and Blood and Buccal DNA Methylation Profiles.Frontiers in psychiatry · 2021Article
- Sibling validation of polygenic risk scores and complex trait prediction.Scientific reports · 2020Article
- Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Genomic prediction of complex human traits (e.g., height, cognitive ability, bone density) and disease risks (e.g., breast cancer, diabetes, heart disease, atrial fibrillation) has advanced considerably in recent years. Using data from the UK Biobank, predictors have been constructed using penalized algorithms that favor sparsity: i.e., which use as few genetic variants as possible. We analyze the specific genetic variants (SNPs) utilized in these predictors, which can vary from dozens to as many as thirty thousand. We find that the fraction of SNPs in or near genic regions varies widely by phenotype. For the majority of disease conditions studied, a large amount of the variance is accounted for by SNPs outside of coding regions. The state of these SNPs cannot be determined from exome-sequencing data. This suggests that exome data alone will miss much of the heritability for these traits-i.e., existing PRS cannot be computed from exome data alone. We also study the fraction of SNPs and of variance that is in common between pairs of predictors. The DNA regions used in disease risk predictors so far constructed seem to be largely disjoint (with a few interesting exceptions), suggesting that individual genetic disease risks are largely uncorrelated. It seems possible in theory for an individual to be a low-risk outlier in all conditions simultaneously.
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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.