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ABSTRACT: Introduction
Genome-wide association studies (GWAS) have successfully identified multiple independent genetic loci that harbour variants associated with Alzheimer's disease, but the exact causal genes and biological pathways are largely unknown.Methods
To prioritise likely causal genes associated with Alzheimer's disease, we used S-PrediXcan to integrate expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression (GTEx) study and CommonMind Consortium (CMC) with Alzheimer's disease GWAS summary statistics. We meta-analysed the GTEx results using S-MultiXcan, prioritised disease-implicated loci using a computational fine-mapping approach, and performed a biological pathway analysis on the gene-based results.Results
We identified 126 tissue-specific
SUBMITTER: Gerring ZF
PROVIDER: S-EPMC7164172 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature