Integrative analysis of eQTL and GWAS summary statistics reveals transcriptomic alteration in Alzheimer brains
Year: 2022
Type: article
Abstract: BACKGROUND: Large-scale genome-wide association studies have successfully identified many genetic variants significantly associated with Alzheimer's disease (AD), such as rs429358, rs11038106, rs723804, rs13591776, and more. The next key step is to understand the function of these SNPs and the downstream biology through which they exert the effect on the development of AD. However, this remains a challenging task due to the tissue-specific nature of transcriptomic and proteomic data and the limited availability of brain tissue.In this paper, instead of using coupled transcriptomic data, we performed an integrative analysis of existing GWAS findings and expression quantitative trait loci (eQTL) results from AD-related brain regions to estimate the transcriptomic alterations in AD brain. RESULTS: We used summary-based mendelian randomization method along with heterogeneity in dependent instruments method and were able to identify 32 genes with potential altered levels in temporal cortex region. Among these, 10 of them were further validated using real gene expression data collected from temporal cortex region, and 19 SNPs from NECTIN and TOMM40 genes were found associated with multiple temporal cortex imaging phenotype. CONCLUSION: Significant pathways from enriched gene networks included neutrophil degranulation, Cell surface interactions at the vascular wall, and Regulation of TP53 activity which are still relatively under explored in Alzheimer's Disease while also encouraging a necessity to bind further trans-eQTL effects into this integrative analysis.
Source: BMC Medical Genomics
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,790
Awards: G104586243, Indiana Alzheimer Disease Center, THE AGES STUDY - THE REYKJAVIK STUDY OF HEALTHY AGING FOR THE NEW MILLENUM, CAREER: Computational strategies for incompleteness and heterogeneity in multi-omic data, G230712557, G2796891014, Gene co-expression underlying the connectomic alterations in Alzheimer's disease, National Alzheimer's Coordinating Center, G3516344715, Integrative Bioinformatics Approaches to Human Brain Genomics and Connectomics, Alzheimer's Disease Genetics Consortium, Alzheimer's Disease Neuroimaging Initiative, Informatics Algorithms for Genomic Analysis of Brain Imaging Data, CHARGE consortium: omics discovery for CVD and aging phenotypes, A Powerful, Genome-Wide Association Scan for Susceptibility Genes for late-onset Alzheimer's disease, G6671297155, CRII:SCH:Computational Methods to Mine Multi-omic Data for Systems Biology of Complex Diseases, Memory Circuitry in MCI and Early Alzheimerâs Disease Prodrome: Molecular Drivers, G7846307588, AD Gene Discovery: Exome Chip, New Endophenotypes & Functional Studies in CHARGE, Indiana Alzheimer's Disease Research Center, National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD)
OpenAlex ID: W4224861253