Integrated multi-omics insight into the molecular networks of oxidative stress in triggering multiple sclerosis

Oxidative stress (OS) is a key pathophysiological mechanism in multiple sclerosis (MS). However, the underlying mechanisms by which OS triggered MS remain unknown. To identify potential causal targets of 1216 OS-related genes for MS, a summary-data-based Mendelian randomization (SMR) method was applied. Given that genes can exert their biological functions through different omics levels, the multi-omics SMR integrating expression, methylation, and protein quantitative trait loci (eQTL, mQTL, and pQTL) of OS-related genes from blood and brain tissues was utilized. Bayesian colocalization test was conducted to examine potential regulatory mechanisms of QTL risk variation in MS. To verify the robustness of our results, we validated these findings in FinnGen cohort. Furthermore, the QTL evidence levels, colocalization findings, and replication cohort results were integrated and potential target genes were categorized into three levels. Consequently, three genes (BACH2, TRAF3, and MAPK3) were identified as potential contributors to MS in blood, and four genes (HMGCL, TSFM, TRAF3 and HLA-B) were identified as potential contributors to MS in brain tissue. Additionally, HMGCL and TSFM from brain tissue were supported by first-level evidence related to MS and were validated via in vitro experiments. This research not only contributed to fundamental research of OS in MS but also supported the identification of potential targets for clinical interventions in MS.

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Publication Details

Journal
Neurobiology of Disease
Published
2025-04-23
DOI
https://doi.org/10.1016/j.nbd.2025.106929
Citations
1
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.81

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article

Integrated multi-omics insight into the molecular networks of oxidative stress in triggering multiple sclerosis

Zhaokai Zhou, Xinwei Han, Hongxuan Ma, Huimin Liu et al.
1 citations
Neurobiology of Disease
Bioinformatics and Genomic Networks
0.81
article

Integrated multi-omics insight into the molecular networks of oxidative stress in triggering multiple sclerosis

Zhaokai Zhou, Xinwei Han, Hongxuan Ma, Huimin Liu, Xiaowei Zhang, Yuyuan Zhang, Yudi Xu, Hongzhuo Qin
article en
1 citations

Abstract

Oxidative stress (OS) is a key pathophysiological mechanism in multiple sclerosis (MS). However, the underlying mechanisms by which OS triggered MS remain unknown. To identify potential causal targets of 1216 OS-related genes for MS, a summary-data-based Mendelian randomization (SMR) method was applied. Given that genes can exert their biological functions through different omics levels, the multi-omics SMR integrating expression, methylation, and protein quantitative trait loci (eQTL, mQTL, and pQTL) of OS-related genes from blood and brain tissues was utilized. Bayesian colocalization test was conducted to examine potential regulatory mechanisms of QTL risk variation in MS. To verify the robustness of our results, we validated these findings in FinnGen cohort. Furthermore, the QTL evidence levels, colocalization findings, and replication cohort results were integrated and potential target genes were categorized into three levels. Consequently, three genes (BACH2, TRAF3, and MAPK3) were identified as potential contributors to MS in blood, and four genes (HMGCL, TSFM, TRAF3 and HLA-B) were identified as potential contributors to MS in brain tissue. Additionally, HMGCL and TSFM from brain tissue were supported by first-level evidence related to MS and were validated via in vitro experiments. This research not only contributed to fundamental research of OS in MS but also supported the identification of potential targets for clinical interventions in MS.

Neurobiology of DiseaseVol. 210
First Affiliated Hospital of Zhengzhou University (CN)
Science and Technology Department of Zhejiang Province
Openalex Percentile: Top 29%
Bioinformatics and Genomic Networks
0.81
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