Five Years of GWAS Discovery
Open accessAbstract
The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.
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The absence of positive genome-wide association results is most likely explained by low statistical power to detect small effects.
“This lack of positive results from GWAS is most likely due to low statistical power to detect small effects”
From Genome-Wide Association Studies of a Broad Spectrum of Antisocial Behavior (2017) · cites this paper as Visscher, Brown, McCarthy, & Yang, 2012
Many of the gene variants identified in GWAS are located in non-coding regions of DNA.
“Many of the gene variants identified in GWAS are located in non-coding regions of DNA [92].”
From Polycystic Ovary Syndrome: An Evolutionary Adaptation to Lifestyle and the Environment (2022) · cites this paper as [92]
The genes or functional DNA elements through which these variants exert their effects are often unknown.
“The genes or functional DNA elements through which these variants exert their effects are often unknown.”
From Polycystic Ovary Syndrome: An Evolutionary Adaptation to Lifestyle and the Environment (2022) · cites this paper as [92]
The large-scale impact of large numbers of common variants may be a general feature of human complex traits.
“Indeed, the large-scale impact of large numbers of common variants may be a general feature of human complex traits 70–77”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [71]
Hypothesized genetic architectures consisting entirely of rare variants are inconsistent with the data for AD, ASD, BIP, and SCZ (as well as for multiple other complex biomedical diseases).
“Hypothesized genetic architectures consisting entirely of rare variants are inconsistent with the data for AD, ASD, BIP, and SCZ (as well as for multiple other complex biomedical diseases). 70–77”
From Genetic architectures of psychiatric disorders: the emerging picture and its implications (2012) · cites this paper as [71]
Evidence from many complex traits shows that the number of variants discovered is strongly correlated with experimental sample size.
“Evidence from many complex traits show that the number of variants discovered is strongly correlated with experimental sample size.51”
From Defining Future Directions for Endometriosis Research: Workshop Report From the 2011 World Congress of Endometriosis in Montpellier, France (2013) · cites this paper as [51]
Above a given threshold for each disease, doubling study size doubles the number of genes or regions identified.
“Above a given threshold for each disease, doubling study size doubles the number of genes or regions identified.”
From Defining Future Directions for Endometriosis Research: Workshop Report From the 2011 World Congress of Endometriosis in Montpellier, France (2013) · cites this paper as [51]
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- Authors
- Visscher, P. M., Brown, M. A., McCarthy, M. I., & Yang, J.
- Affiliations
- The University of Queensland (AU)
- Centre for Human Genetics (GB)
- QIMR Berghofer Medical Research Institute (AU)
- Corresponding author
- Visscher, Peter M.
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 90
- Issue
- 1
- Pages
- 7-24
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC3257326
- OpenAlex
- W2163924952
- Cited by
- 2,425
- References
- 218
- Citations by year
- 2026: 52 · 2025: 97 · 2024: 120 · 2023: 130 · 2022: 133 · 2021: 154 · 2020: 176 · 2019: 166 · 2018: 181 · 2017: 246 · 2016: 259 · 2015: 250 · 2014: 196 · 2013: 178 · 2012: 81
- FWCI
- 27.66
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- Funders
- Wellcome Trust (090532)
- Australian Research Council
- National Health and Medical Research Council
- National Medical Research Council
- 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, single nucleotide polymorphisms, complex traits, autoimmune disease, metabolic disorders, heart disease, diabetes mellitus, mental illness, genetic association
- MeSH terms
- Autoimmune Diseases, Female, Humans, Genetic Linkage, Male, Metabolic Diseases, Genetic Predisposition to Disease, History, 21st Century, Genome-Wide Association Study, Genetic Loci, Translational Research, Biomedical
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