The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Nonvalidation of Reported Genetic Risk Factors for Acute Coronary Syndrome in a Large-Scale Replication Study
Abstract
CONTEXT: Given the numerous, yet inconsistent, reports of genetic variants being associated with acute coronary syndromes (ACS), there is a need for comprehensive validation of ACS susceptibility genotypes. OBJECTIVE: To perform an extensive validation of putative genetic risk factors for ACS. DESIGN, SETTING, AND PARTICIPANTS: Through a systematic literature search of articles published before March 10, 2005, we identified genetic variants previously reported as significant susceptibility factors for atherosclerosis or ACS. Restricting our analysis to white patients to reduce confounding from racial admixture, we identified 811 patients who presented from March 2001 through June 2003 with ACS at 2 Kansas City, Mo, university-affiliated hospitals. During 2005-2006, we genotyped the 811 patients along with 650 age- and sex-matched controls for 85 variants in 70 genes and attempted to replicate previously reported associations. We further explored possible associations without prior assumption of specific risk models and used the Sign test to search for weak associations. MAIN OUTCOME MEASURES: Compare each prespecified gene variant associated with ACS risk among cases and controls. A surplus of associations would imply that some are associated with ACS. RESULTS: Of 85 variants tested, only 1 putative risk genotype (-455 promoter variant in beta-fibrinogen) was nominally statistically significant (P = .03). Only 4 additional genes were positive in model-free analysis. Neither number of associations was more frequent than expected by chance, given the number of comparisons. Finally, only 41 of 84 predefined risk variants were even marginally more frequent in cases than in controls (with 1 tie), representing a 48.8% "win rate" (95% confidence interval, 38.1%-59.5%) for the collective risk genotypes (P = .91, Sign test). CONCLUSIONS: Our null results provide no support for the hypothesis that any of the 85 genetic variants tested is a susceptibility factor for ACS. These results emphasize the need for robust replication of putative genetic risk factors before their introduction into clinical care.
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The International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057
The Structure of Haplotype Blocks in the Human Genome
Gabriel, S. B., Schaffner, S. F., Nguyen, H., Moore, J. M., Roy, J., Blumenstiel, B., Higgins, J., DeFelice, M., Lochner, A., Faggart, M., et al. (2002) · Science · doi:10.1126/science.1069424 · Cited by 5,863
The effects of human population structure on large genetic association studies
Marchini, J., Cardon, L. R., Phillips, M. S., & Donnelly, P. (2004) · Nature Genetics · doi:10.1038/ng1337 · Cited by 869
Obstacles and opportunities in meta-analysis of genetic association studies
Salanti, G., Sanderson, S., & Higgins, J. P. T. (2005) · Genetics in Medicine · doi:10.1097/01.gim.0000151839.12032.1a · Cited by 196
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Siontis, K. C. M., Patsopoulos, N. A., & Ioannidis, J. P. A. (2010) · European Journal of Human Genetics · doi:10.1038/ejhg.2010.26 · Cited by 117
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Metadata
- Authors
- Morgan, T. M., Krumholz, H. M., Lifton, R. P., & Spertus, J. A.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2007-04-11
- Volume
- 297
- Issue
- 14
- Pages
- 1551
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W2100705421
- Cited by
- 270
- References
- 4
- FWCI
- 23.28
- Type
- journal article
- Language
- en
- Open access
- closed
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