The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Pathway analysis of seven common diseases assessed by genome-wide association
Open accessAbstract
Recent genome wide association studies (GWAS) have identified DNA sequence variations that exhibit unequivocal statistical associations with many common chronic diseases. However, the vast majority of these studies identified variations that explain only a very small fraction of disease burden in the population at large, suggesting that other factors, such as multiple rare or low-penetrance variations and interacting environmental factors, are major contributors to disease susceptibility. Identifying multiple low penetrance variations (or ‘polygenes’) contributing to disease susceptibility will be difficult. We present a pathway analysis approach to characterizing the likely polygenic basis of seven common diseases using the Wellcome Trust Case Control Consortium (WTCCC) GWAS results. We identify numerous pathways implicated in disease predisposition that would have not been revealed using standard single-locus GWAS statistical analysis criteria. Many of these pathways have long been assumed to contain polymorphic genes that lead to disease predisposition. Additionally, we analyze the genetic relationships between the seven diseases, and based upon similarities with respect to the associated genes and pathways affected in each, propose a new way of categorizing the diseases.
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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
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Inflammation, Hypertension, and the Metabolic Syndrome
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“1 [30], and is identified as another associated gene in this pathway (CSNK2B).”
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Cited by
Analysing biological pathways in genome-wide association studies
Wang, K., Li, M., & Hakonarson, H. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2884 · Cited by 766
Prioritizing GWAS Results: A Review of Statistical Methods and Recommendations for Their Application
Cantor, R. M., Lange, K., & Sinsheimer, J. S. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.11.017 · Cited by 622
Nylander, A., & Hafler, D. A. (2012) · Journal of Clinical Investigation · doi:10.1172/jci58649 · Cited by 495
Mechanisms maintaining peripheral tolerance
Mueller, D. L. (2010) · Nature Immunology · doi:10.1038/ni.1817 · Cited by 461
Pathway and network-based analysis of genome-wide association studies in multiple sclerosis
Baranzini, S. E., Galwey, N. W., Wang, J., Khankhanian, P., Lindberg, R., Pelletier, D., Wu, W., Uitdehaag, B. M. J., Kappos, L., GeneMSA Consortium, et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp120 · Cited by 383
Metadata
- Authors
- Torkamani, A., Topol, E. J., & Schork, N. J.
- Venue
- Genomics
- Publisher
- Elsevier BV
- Published
- 2008-11
- Volume
- 92
- Issue
- 5
- Pages
- 265-272
- ISSN
- 0888-7543 (ISSN-L)
- OpenAlex
- W2108172198
- Cited by
- 345
- References
- 6
- FWCI
- 14.52
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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