Integrative analysis of eQTL and GWAS summary statistics reveals transcriptomic alteration in Alzheimer brains.

In the last decade, several large-scale GWASs have helped reveal mutations significantly associated with AD and the related traits. Yet, the functional mechanism through which these SNPs contribute to the development of AD remains largely unknown. This knowledge gap could be partly narrowed by investigating the effect of these SNPs on the downstream transcriptomic and proteomic levels. But the limited availability of gene and protein expression data in the brain tissue makes this a very challenging task. Recent findings show that most GWAS findings overlap with expression quantitative trait loci (eQTL), indicating the potential role of disease-related variants in gene regulation [2]. Although GWAS does not necessarily reveal the causal variants associated with the disease, with eQTL that links the genomic data to the transcriptomic data, one can isolate the location that potentially affect the downstream expression profile. To understand the function of these SNPs and the downstream biology through which they exert the effect on the development of AD, we performed an integrative analysis of existing GWAS findings and eQTL results from AD-related brain regions to estimate the transcriptomic alterations in AD brain.

Article

Varathan, Pradeep, et al. “Integrative analysis of eQTL and GWAS summary statistics reveals transcriptomic alteration in Alzheimer brains.” BMC Medical Genomics 15.2 (2022): 1-10.

GWAS studies have greater limitation on replicability of the study on the same disease and also cannot describe the heritability of the variants. In this aim, having combined with eQTL in Alzheimer’s Disease, and concentrating on the regions of importance to the pathology of AD, we are able to isolate the most genetically impactful region of brain that also correlates not just with the genotype but also with the actual gene expression and the imaging phenotype. Having done the analysis over three different datasets as one of the first studies to validate the correlation between allele, variant and gene expression to the MRI imaging studies, we were able to isolate the best region of brain to target for research on hereditary outcomes in Alzheimer’s Disease.