The DOI matches its Crossref record; 127 of the 128 references it cites were found in a registry or an index.
Genome-wide association studies for complex traits: consensus, uncertainty and challenges
Abstract
The past year has witnessed substantial advances in understanding the genetic basis of many common phenotypes of biomedical importance. These advances have been the result of systematic, well-powered, genome-wide surveys exploring the relationships between common sequence variation and disease predisposition. This approach has revealed over 50 disease-susceptibility loci and has provided insights into the allelic architecture of multifactorial traits. At the same time, much has been learned about the successful prosecution of association studies on such a scale. This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
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In the citing paper
“As yet, the function of most variants identified in GWASs is unknown, and most of these variants reside outside of coding sequence (9).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [9]
In the citing paper
“Each study was first subject to GWAS quality control filters (customized taking into account study specific features21 as detailed in Supplementary Table 2) and standardized to the HapMap reference panel and statistical genotype imputation22–25.”
From Seven new loci associated with age-related macular degeneration (2013) · cites this paper as [21]
Citations
Cites
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Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248
Genome-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-citationDavey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882
A haplotype map of the human genome
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The Future of Genetic Studies of Complex Human Diseases
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Self-citationMinimum information about a microarray experiment (MIAME)-toward standards for microarray data
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The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration
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1 of the 128 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Lettre, G. et al. Genome-wide association studies identify 10 novel loci for height and highlight new biological pathways in human growth. Nature Genet. (in the press).
- Loos, R. J. F. et al. Association studies involving over 90,000 people demonstrate that common variants near to MC4R influence fat mass, weight and risk of obesity. Nature Genet. (in the press).
Cited by
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Wojcik, G. L., Kao, W. L., & Duggal, P. (2015) · BMC Genetics · doi:10.1186/s12863-015-0191-2 · Cited by 33
Binia, A., Van Stiphout, N., Liang, L., Michel, S., Bhavsar, P. K., Fan Chung, K., Brightling, C. E., Barnes, P. J., Kabesch, M., Bush, A., et al. (2013) · Human Mutation · doi:10.1002/humu.22340 · Cited by 24
Trait-associated noncoding variant regions affect TBX3 regulation and cardiac conduction
van Weerd, J. H., Mohan, R. A., van Duijvenboden, K., Hooijkaas, I. B., Wakker, V., Boukens, B. J., Barnett, P., & Christoffels, V. M. (2020) · eLife · doi:10.7554/elife.56697 · Cited by 12
Genetic variation within transcriptional regulatory elements and its implications for human disease
Rada-Iglesias, A. (2014) · Biological Chemistry · doi:10.1515/hsz-2014-0109 · Cited by 7
Interpreting noncoding genetic variation in complex traits and human disease
Ward, L. D., & Kellis, M. (2012) · Nature Biotechnology · doi:10.1038/nbt.2422 · Cited by 6
Metadata
- Authors
- McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P. A., & Hirschhorn, J. N.
- Affiliations
- Centre for Human Genetics (GB)
- University of Michigan (US)
- Duke University (US)
- University of Ottawa (CA)
- Tufts University (US)
- Broad Institute (US)
- Corresponding author
- McCarthy, Mark I.
- ORCID
- Venue
- Nature Reviews Genetics
- Published
- 2008-05
- Volume
- 9
- Issue
- 5
- Pages
- 356-369
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W2041467022
- Cited by
- 2,891
- References
- 128
- Citations by year
- 2026: 38 · 2025: 57 · 2024: 90 · 2023: 68 · 2022: 61 · 2021: 85 · 2020: 94 · 2019: 129 · 2018: 127 · 2017: 160 · 2016: 170 · 2015: 171 · 2014: 200 · 2013: 235 · 2012: 257
- FWCI
- 29.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Genetics (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, disease susceptibility loci, multifactorial traits, common diseases, genetic basis of disease, clinical translation
- MeSH terms
- Alleles, Animals, Humans, Genetic Variation, Genome, Human, Quantitative Trait, Heritable, Genetic Predisposition to Disease, Genetic Diseases, Inborn, Quantitative Trait Loci
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