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

dc.contributor.authorVarathan, Pradeep
dc.contributor.authorGorijala, Priyanka
dc.contributor.authorJacobson, Tanner
dc.contributor.authorChasioti, Danai
dc.contributor.authorNho, Kwangsik
dc.contributor.authorRisacher, Shannon L.
dc.contributor.authorSaykin, Andrew J.
dc.contributor.authorYan, Jingwen
dc.contributor.departmentRadiology and Imaging Sciences, School of Medicineen_US
dc.date.accessioned2023-06-08T18:47:49Z
dc.date.available2023-06-08T18:47:49Z
dc.date.issued2022-04-23
dc.description.abstractBackground: 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.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.citationVarathan P, Gorijala P, Jacobson T, et al. Integrative analysis of eQTL and GWAS summary statistics reveals transcriptomic alteration in Alzheimer brains. BMC Med Genomics. 2022;15(Suppl 2):93. Published 2022 Apr 23. doi:10.1186/s12920-022-01245-5en_US
dc.identifier.urihttps://hdl.handle.net/1805/33551
dc.language.isoen_USen_US
dc.publisherBMCen_US
dc.relation.isversionof10.1186/s12920-022-01245-5en_US
dc.relation.journalBMC Medical Genomicsen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourcePMCen_US
dc.subjectAlzheimer’s diseaseen_US
dc.subjectGenetic predisposition to diseaseen_US
dc.subjectQuantitative trait locien_US
dc.subjectSingle nucleotide polymorphismen_US
dc.titleIntegrative analysis of eQTL and GWAS summary statistics reveals transcriptomic alteration in Alzheimer brainsen_US
dc.typeArticleen_US
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