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Updated: Sep 21, 2025

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
Published on: January 9, 2020
Integrative analysis of summary data from GWAS and eQTL studies implicates genes differentially expressed in
Brian Lee1, Xiaohui Yao1, Li Shen2
1Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA.
Background:
Although genome-wide association studies (GWAS) have successfully located various genetic variants susceptible to Alzheimer's Disease (AD), it is still unclear how specific variants interact with genes and tissues to elucidate pathologies associated with AD. Summary-data-based Mendelian Randomization (SMR) addresses this problem through an instrumental variable approach that integrates data from independent GWAS and expression quantitative trait locus (eQTL) studies in order to infer a causal effect of gene expression on a trait.
Results:
Our study employed the SMR approach to integrate a set of meta-analytic cis-eQTL information from the Genotype-Tissue Expression (GTEx), CommonMind Consortium (CMC), and Religious Orders Study and Rush Memory and Aging Project (ROS/MAP) consortiums with three sets of meta-analysis AD GWAS results.
Conclusions:
Our analysis identified twelve total gene probes (associated with twelve distinct genes) with a significant association with AD. Four of these genes survived a test of pleiotropy from linkage (the HEIDI test).Three of these genes - RP11-385F7.1, PRSS36, and AC012146.7 - have not yet been reported differentially expressed in the brain in the context of AD, and thus are the novel findings warranting further investigation.
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