ArticleAmerican journal of human genetics2010
Interpretation of association signals and identification of causal variants from genome-wide association studies.
Article in American journal of human genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 4 of them syntheses that pooled it.
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Who cites it
90 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.Nature genetics · 2021Pooled it
- Risk loci for chronic obstructive pulmonary disease: a genome-wide association study and meta-analysis.The Lancet. Respiratory medicine · 2014Pooled it
- Combined admixture mapping and association analysis identifies a novel blood pressure genetic locus on 5p13: contributions from the CARe consortium.Human molecular genetics · 2011Pooled it
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- Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues.Human genomics · 2025Review
- Genome-wide Association Study Identifies Novel Risk Loci for Apical Periodontitis.Journal of endodontics · 2023Article
- Fine mapping spatiotemporal mechanisms of genetic variants underlying cardiac traits and disease.Nature communications · 2023Article
- Genome-wide association study identifies novel risk loci for apical periodontitis.Research square · 2023Article
- Genetic and Non-genetic Determinants of Cardiovascular Disease in South Asians.Current diabetes reviews · 2021Review
- Exome Array Analysis of Early-Onset Ischemic Stroke.Stroke · 2020Article
- Systems Genetics for Mechanistic Discovery in Heart Diseases.Circulation research · 2020Review
- Convolutional neural network model to predict causal risk factors that share complex regulatory features.Nucleic acids research · 2019Article
- A clinal polymorphism in the insulin signaling transcription factor foxo contributes to life-history adaptation in Drosophila.Evolution; international journal of organic evolution · 2019Article
- Benefits and limitations of genome-wide association studies.Nature reviews. Genetics · 2019Review
- An evaluation of noncoding genome annotation tools through enrichment analysis of 15 genome-wide association studies.Briefings in bioinformatics · 2019Article
30 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
GWAS have been successful in identifying disease susceptibility loci, but it remains a challenge to pinpoint the causal variants in subsequent fine-mapping studies. A conventional fine-mapping effort starts by sequencing dozens of randomly selected samples at susceptibility loci to discover candidate variants, which are then placed on custom arrays or used in imputation algorithms to find the causal variants. We propose that one or several rare or low-frequency causal variants can hitchhike the same common tag SNP, so causal variants may not be easily unveiled by conventional efforts. Here, we first demonstrate that the true effect size and proportion of variance explained by a collection of rare causal variants can be underestimated by a common tag SNP, thereby accounting for some of the "missing heritability" in GWAS. We then describe a case-selection approach based on phasing long-range haplotypes and sequencing cases predicted to harbor causal variants. We compare this approach with conventional strategies on a simulated data set, and we demonstrate its advantages when multiple causal variants are present. We also evaluate this approach in a GWAS on hearing loss, where the most common causal variant has a minor allele frequency (MAF) of 1.3% in the general population and 8.2% in 329 cases. With our case-selection approach, it is present in 88% of the 32 selected cases (MAF = 66%), so sequencing a subset of these cases can readily reveal the causal allele. Our results suggest that thinking beyond common variants is essential in interpreting GWAS signals and identifying causal variants.
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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.