Genome-wide study of alcoholism using COGA data
Author Information
Author(s): Zhu Xiaofeng, Cooper Richard, Kan Donghui, Cao Guichan, Wu Xiaodong
Primary Institution: Loyola University Medical Center
Hypothesis
Can genome-wide linkage and association analyses identify genetic variants associated with alcoholism?
Conclusion
Association analysis could hold more promise in identifying genetic variants responsible for alcoholism compared to linkage analysis.
Supporting Evidence
- Nonparametric linkage analysis revealed weak linkage evidence on chromosome 7.
- Association analysis identified SNP tsc0515272 on chromosome 3 as significantly associated with alcoholism.
- Linkage analysis did not reveal significant evidence around SNP tsc0515272, where significant association was found.
Takeaway
The study looked at families to find genes related to alcoholism, and found that some specific genetic markers are linked to it.
Methodology
Genome-wide linkage analysis was performed using microsatellite markers, followed by association analysis using SNPs.
Potential Biases
Type I error risks exist in both linkage and association analyses due to potential inconsistencies.
Limitations
Linkage analysis may require large sample sizes and high-quality genotyping, which can be challenging.
Participant Demographics
1,294 White individuals from 119 families.
Statistical Information
P-Value
0.000006
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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