AccScience Publishing / AN / Online First / DOI: 10.36922/AN025150032
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ORIGINAL RESEARCH ARTICLE

Discovering genes associated with multiple sclerosis through cross-tissue integrative transcriptome-wide association studies

Xiaoyun Zhang1,2* ,  Zhen Liu3
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1 Jinan University, Guangzhou, Guangdong, China
2 Department of Rehabilitation, Shenzhen Longhua District Central Hospital, Shenzhen, Guangdong, China
3 Department of Pharmaceutical, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
Advanced Neurology, 025150032 https://doi.org/10.36922/AN025150032
Received: 13 April 2025 | Revised: 2 September 2025 | Accepted: 12 September 2025 | Published online: 14 November 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Genome-wide association studies (GWASs) have identified over 200 loci associated with multiple sclerosis (MS), yet these loci explain only a fraction of the genetic risk. Integrating GWAS with expression quantitative trait loci through transcriptome-wide association studies (TWAS) provides a powerful approach to pinpointing candidate genes underlying complex traits. We performed a TWAS using FUSION with Genotype-Tissue Expression version 8 expression weights, based on meta-analyzed summary statistics from large-scale MS GWAS datasets (5263 cases and 83,167 controls). To refine candidate genes and assess causality, we applied conditional analysis, Bayesian colocalization, summary-data-based Mendelian randomization (SMR), and fine-mapping strategies. TWAS identified 403 candidate genes, of which 15 were further supported by SMR analysis. Six of these genes (HLA-G, HLA-J, HLA-DRB1, TAP2, HLA-C, and HLA-B) overlapped with previously reported MS loci, and nine additional genes (e.g., MICF, USP8P1, PSORS1C3, HCG24, and HLA-DQB1-AS1) represented novel candidates requiring further validation. Through the integration of transcriptomic and GWAS data, our study unveiled established and novel genetic contributors to MS. These findings deepen our understanding of MS pathogenesis and highlight high-priority targets for future functional and therapeutic studies.

Keywords
Multiple sclerosis
Post-GWAS analysis
Transcriptome-wide association study
Summary Mendelian randomization
Funding
This work was supported by the Scientific Research Projects of Medical and Health Institutions in Longhua District, Shenzhen (ID: 2023034, PI: YXZ).
Conflict of interest
The authors declare that they have no competing interests.
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Advanced Neurology, Electronic ISSN: 2810-9619 Print ISSN: 3060-8589, Published by AccScience Publishing
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