Computational genetics analysis of grey matter density in Alzheimer's disease.

ABSTRACT:

Background

Alzheimer's disease is the most common form of progressive dementia and there is currently no known cure. The cause of onset is not fully understood but genetic factors are expected to play a significant role. We present here a bioinformatics approach to the genetic analysis of grey matter density as an endophenotype for late onset Alzheimer's disease. Our approach combines machine learning analysis of gene-gene interactions with large-scale functional genomics data for assessing biological relationships.

Results

We found a statistically significant synergistic interaction among two SNPs located in the intergenic region of an olfactory gene cluster. This model did not replicate in an independent dataset. However, genes in this region have high-confidence biologica

SUBMITTER: Zieselman AL 

PROVIDER: S-EPMC4145360 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature