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Utilising multi-large omics data to elucidate biological mechanisms within multiple sclerosis genetic susceptibility loci

Zhou, Y ORCID: 0000-0003-1962-2574, Cuellar-Partida, G, Simpson Yap, S ORCID: 0000-0001-6521-3056, Lin, X, Claflin, S ORCID: 0000-0001-6545-946X, Burdon, K ORCID: 0000-0001-8217-1249, Charlesworth, J ORCID: 0000-0001-6201-3518 and Taylor, B 2021 , 'Utilising multi-large omics data to elucidate biological mechanisms within multiple sclerosis genetic susceptibility loci' , Multiple Sclerosis Journal , doi: 10.1177/13524585211004422.

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Abstract

Background: Genome-wide association studies (GWAS) have succeeded in identifying over 200 susceptibility loci for multiple sclerosis (MS). However, the potential functional variants and the mechanisms by which these loci affect MS risk remain largely unexplained.Objectives: We used summary data-based Mendelian randomisation to prioritise risk genes and infer potential biological mechanisms for MS risk loci.Methods: The data used consisted of DNA methylation (n = 1980) QTL (mQTL) and gene expression (n = 31,684) QTL (eQTL) derived from whole blood as well as MS GWAS summary statistics (14,802 cases, 26,703 controls). The findings were further evaluated using data derived from independent brain mQTL (n = 1160) and eQTL (n = 1194).Results: In whole blood, we identified two independent genomic loci (lincRNA: RP11-326C3.13 and TNFSF14) with consistent genome-wide significant pleiotropic associations across different omics layers. In brain tissue, a similar effect for the RP11-326C3.13 locus was observed but not for TNFSF14, indicating a potential tissue-specific effect for the TNFSF14 locus.Conclusion: We provide in silico evidence for the putative biological mechanisms by which the identified DNA methylation sites and target genes are functionally relevant to MS development in different tissues. Future research targeting these genes and DNA methylation sites will determine their roles in the pathophysiology of MS.

Item Type: Article
Authors/Creators:Zhou, Y and Cuellar-Partida, G and Simpson Yap, S and Lin, X and Claflin, S and Burdon, K and Charlesworth, J and Taylor, B
Keywords: Multiple sclerosis, genetics, genomics, multiomics
Journal or Publication Title: Multiple Sclerosis Journal
Publisher: Arnold
ISSN: 1352-4585
DOI / ID Number: 10.1177/13524585211004422
Copyright Information:

© The Author(s), 2021

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