Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 141 risk genes for Alzheimer's disease dementia

Abstract

Background: Transcriptome-wide association study (TWAS) is an influential tool for identifying genes associated with complex diseases whose genetic effects are likely mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate effect sizes of genetic variants on gene expression (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are employed as variant weights in gene-based association tests, facilitating the mapping of risk genes with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia are limited to studying only cis-eQTL proximal to the test gene. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method to leveraging both cis- and trans- eQTL of brain and blood tissues, in order to enhance mapping risk genes for AD dementia.

Methods: We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis- and trans- eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per gene per tissue type. Then we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene.

Results: We identified 85 significant genes in prefrontal cortex, 82 in cortex, and 76 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 141 significant risk genes including 34 genes primarily due to trans-eQTL and 35 mapped risk genes in GWAS Catalog. With these 141 significant risk genes, we detected functional clusters comprised of both known mapped GWAS risk genes of AD in GWAS Catalog and our identified TWAS risk genes by protein-protein interaction network analysis, as well as several enriched phenotypes related to AD.

Conclusion: We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis- and trans- eQTL data of brain and blood tissues with GWAS summary data, identifying 141 TWAS risk genes of AD dementia. These identified risk genes provide novel insights into the underlying biological mechanisms of AD dementia and potential gene targets for therapeutics development.

Keywords: Cis-eQTL; Trans-eQTL; Aggregated cauchy association test; Alzheimer’s disease dementia; Bayesian genome-wide TWAS.

Fig. 1

Study workflow

Fig. 2

Manhattan plot of ACAT-O TWAS p-values for studying AD dementia. The horizontal dashed line represents the Bonferroni corrected significance threshold of the p-values. Orange dots indicate genes that were significant in only one tissue, while red dots highlight genes that were significant in more than one tissue

Fig. 3

Scatter plots of eQTL weights estimated by BGW-TWAS of example TWAS risk genes. Column A: gene ACE (chr17) in three tissues; Column B: gene SNORD22 (chr11), AP001350.4 (chr11), and SLC3A2 (chr11), in prefrontal cortex, cortex, and whole blood tissues, respectively. Y-axis depicts the values of eQTL weights estimated by BGW-TWAS, and the x-axis shows the order of base pair position of the corresponding eQTL. Solid circles denote cis-eQTL, and triangles refer to trans-eQTL. Color legend denotes the -log (GWAS p-value) of the corresponding eQTL

Fig. 4

Protein-protein interaction networks identified with 141 significant TWAS risk genes by the STRING tool. Edge colors show different sources of the identified protein-protein interactions

Fig. 5

Phenotype enrichment analysis with 141 significant TWAS risk genes by the STRING tool. The -log10 of the false discovery rates (FDR, x-axis) for testing the enrichment of known risk genes of the corresponding phenotype (y-axis) were plotted