The DOI matches its Crossref record; 217 of the 218 references it cites were found in a registry or an index.
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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Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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]
Citations
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
Self-citationGenome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
Self-citationFinding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
Self-citationA map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Effectiveness of Antipsychotic Drugs in Patients with Chronic Schizophrenia
Lieberman, J. A., Stroup, T. S., McEvoy, J. P., Swartz, M. S., Rosenheck, R. A., Perkins, D. O., Keefe, R. S. E., Davis, S. M., Davis, C. E., Lebowitz, B. D., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa051688 · Cited by 5,892
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
The Future of Genetic Studies of Complex Human Diseases
Risch, N., & Merikangas, K. (1996) · Science · doi:10.1126/science.273.5281.1516 · Cited by 5,355
Principles of Population Genetics.
Cormack, R. M., Hartl, D. L., & Clark, A. G. (1990) · Biometrics · doi:10.2307/2531471 · Cited by 5,283
Common polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
Research works printed but not linked: 1
- Danoy, 2010, Association of variants at 1q32 and STAT3 with ankylosing spondylitis suggests genetic overlap with Crohn's disease, PLoS Genet., 6, e1001195, 10.1371/journal.pgen.1001195 · DOI
Cited by
Sorted by citations
The Ensembl Variant Effect Predictor
McLaren, W., Gil, L., Hunt, S. E., Riat, H. S., Ritchie, G. R. S., Thormann, A., Flicek, P., & Cunningham, F. (2016) · Genome Biology · doi:10.1186/s13059-016-0974-4 · Cited by 8,099
The MR-Base platform supports systematic causal inference across the human phenome
Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., Laurin, C., Burgess, S., Bowden, J., Langdon, R., et al. (2018) · eLife · doi:10.7554/elife.34408 · Cited by 7,959
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559
Self-citationThe Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062
Self-citationGenetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
Self-citation
Metadata
- 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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