Background: Genome-wide association studies (GWAS) have effectively identified genetic factors for many diseases. Many diseases, including Alzheimer's disease (AD), have epistatic causes, requiring more sophisticated analyses to identify groups of variants which together affect phenotype. Results: Based on the GWAS statistical model, we developed a multi-SNP GWAS analysis to identify pairs of variants whose common occurrence signaled the Alzheimer's disease phenotype. Conclusions: Despite not having sufficient data to demonstrate significance, our preliminary experimentation identified a high correlation between GRIA3 and HLA-DRB5 (an AD gene). GRIA3 has not been previously reported in association with AD, but is known to play a role in learning and memory.
|State||Published - Jul 25 2016|
Bibliographical noteFunding Information:
Publication of this article was funded by the Department of Biology and the College of Life Sciences at Brigham Young University. This article has been published as part of BMC Bioinformatics Volume 17 Supplement 7, 2016: Selected articles from the 12th Annual Biotechnology and Bioinformatics Symposium: bioinformatics. The full contents of the supplement are available online at https://bmcbioinformatics.biomedcentral. com/articles/supplements/volume-17-supplement-7.
© 2016 Bodily et al.
- Alzheimer's disease
- Multi-SNP GWAS
ASJC Scopus subject areas
- Structural Biology
- Molecular Biology
- Computer Science Applications
- Applied Mathematics