Progress and promise of genome-wide association studies for human complex trait genetics
Open accessAbstract
Enormous progress in mapping complex traits in humans has been made in the last 5 yr. There has been early success for prevalent diseases with complex phenotypes. These studies have demonstrated clearly that, while complex traits differ in their underlying genetic architectures, for many common disorders the predominant pattern is that of many loci, individually with small effects on phenotype. For some traits, loci of large effect have been identified. For almost all complex traits studied in humans, the sum of the identified genetic effects comprises only a portion, generally less than half, of the estimated trait heritability. A variety of hypotheses have been proposed to explain why this might be the case, including untested rare variants, and gene–gene and gene–environment interaction. Effort is currently being directed toward implementation of novel analytic approaches and testing rare variants for association with complex traits using imputed variants from the publicly available 1000 Genomes Project resequencing data and from direct resequencing of clinical samples. Through integration with annotations and functional genomic data as well as by in vitro and in vivo experimentation, mapping studies continue to characterize functional variants associated with complex traits and address fundamental issues such as epistasis and pleiotropy. This review focuses primarily on the ways in which genome-wide association studies (GWASs) have revolutionized the field of human quantitative genetics.
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Over the past 15 years, genomic analyses have identified thousands of genetic variants that contribute statistically to variation in complex phenotypes, traits that have complex patterns of inheritance and that are affected by large numbers of genes in combination with environmental factors.
“Over the past 15 years, genomic analyses have identified thousands of genetic variants that contribute statistically to variation in complex phenotypes, traits that have complex patterns of inheritance and that are affected by large numbers of genes in combination with environmental factors [18–20].”
From Interpreting polygenic scores, polygenic adaptation, and human phenotypic differences (2019) · cites this paper as [18]
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- Authors
- Stranger, B. E., Stahl, E. A., & Raj, T.
- Affiliations
- Broad Institute (US)
- Corresponding author
- Stranger, Barbara E
- Venue
- Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-02-01
- Volume
- 187
- Issue
- 2
- Pages
- 367-383
- ISSN
- 0016-6731 (ISSN-L)
- 1943-2631
- PMC
- PMC3030483
- OpenAlex
- W2134755636
- Cited by
- 567
- References
- 28
- Citations by year
- 2026: 8 · 2025: 14 · 2024: 14 · 2023: 25 · 2022: 12 · 2021: 20 · 2020: 41 · 2019: 40 · 2018: 33 · 2017: 51 · 2016: 56 · 2015: 60 · 2014: 71 · 2013: 59 · 2012: 43
- FWCI
- 4.05
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Genetics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- genome-wide association study, complex traits, human genetics, heritability, rare variants, imputation, 1000 Genomes Project, gene-gene interaction, gene-environment interaction, epistasis, pleiotropy, functional variants, quantitative genetics
- MeSH terms
- Animals, Chromosome Mapping, Humans, Models, Genetic, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study
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