An analysis of genetically regulated gene expression across multiple tissues implicates novel gene candidates in Alzheimer's disease

Alzheimers Res Ther. 2020 Apr 16;12(1):43. doi: 10.1186/s13195-020-00611-8.

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 gene-based associations across 48 GTEx tissues, targeting 50 unique genes. Meta-analysis of the tissue-specific associations identified 73 genes whose expression was associated with Alzheimer's disease. Additional analyses in the dorsolateral prefrontal cortex from the CMC identified 12 significant associations, 8 of which also had a significant association in GTEx tissues. Fine-mapping of causal gene sets prioritised gene candidates in 10 Alzheimer's disease loci with strong evidence for causality. Biological pathway analyses of the meta-analysed GTEx data and CMC data identified a significant enrichment of Alzheimer's disease association signals in plasma lipoprotein clearance, in addition to multiple immune-related pathways.

Conclusions: Gene expression data from brain and peripheral tissues can improve power to detect regulatory variation underlying Alzheimer's disease. However, the associations in peripheral tissues may reflect tissue-shared regulatory variation for a gene. Therefore, future functional studies should be performed to validate the biological meaning of these associations and whether they represent new pathogenic tissues.

Keywords: Alzheimer’s disease; Computational biology; Gene expression; Genetic epidemiology; Genetics; Genome-wide association study.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alzheimer Disease* / genetics
  • Gene Expression
  • Genome-Wide Association Study*
  • Humans
  • Polymorphism, Single Nucleotide / genetics
  • Quantitative Trait Loci / genetics