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New strategies for identifying gene-gene interactions in hypertension
Open accessAbstract
Essential hypertension is a common disease that has a complex multifactorial etiology. For this reason, it is not surprising that studies of the effects of single genes on hypertension have often failed to replicate the original findings. We propose, as a working hypothesis, that the failure to replicate some single locus results is because the impact of single alleles on the risk of hypertension is dependent on genetic variations at other loci (i.e. gene-gene interactions) and on environmental factors (i.e. gene-environment interactions). Thus, studies that do not consider the appropriate genetic and/or environmental contexts may not identify important susceptibility loci. The identification and characterization of such gene-gene and gene-environment interactions have been limited by a lack of powerful statistical methods and/or a lack of large enough sample sizes. Here, we review the general problem of identifying gene-gene interactions and describe several traditional and several newer methods that are being used to assess complex genetic interactions in essential hypertension.
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(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305
A simulation study of the number of events per variable in logistic regression analysis
Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(96)00236-3 · Cited by 9,655
Cellular automata as models of complexity
Wolfram, S. (1984) · Nature · doi:10.1038/311419a0 · Cited by 1,507
Clark, A. G., Weiss, K. M., Nickerson, D. A., Taylor, S. L., Buchanan, A., Stengård, J., Salomaa, V., Vartiainen, E., Perola, M., Boerwinkle, E., et al. (1998) · The American Journal of Human Genetics · doi:10.1086/301977 · Cited by 435
Cited by
Detecting gene–gene interactions that underlie human diseases
Cordell, H. J. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2579 · Cited by 1,350
Genetic architecture of learning and delayed recall: A twin study of episodic memory.
Panizzon, M. S., Lyons, M. J., Jacobson, K. C., Franz, C. E., Grant, M. D., Eisen, S. A., Xian, H., & Kremen, W. S. (2011) · Neuropsychology · doi:10.1037/a0022569 · Cited by 34
Moore, J. H., Boczko, E. M., & Summar, M. L. (2005) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2004.10.006 · Cited by 32
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Metadata
- Authors
- Moore, J. H., & Williams, S. M.
- Venue
- Annals of Medicine
- Publisher
- Informa UK Limited
- Published
- 2002-01
- Volume
- 34
- Issue
- 2
- Pages
- 88-95
- ISSN
- 0785-3890 (ISSN-L)
- 1365-2060
- OpenAlex
- W2104605543
- Cited by
- 393
- References
- 4
- FWCI
- 10.84
- 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).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.