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Article

Integrated multi-omics and machine learning prioritize key immune genes for multiple sclerosis risk prediction.

Mammalian genome : official journal of the International Mammalian Genome Society - 2 Mar 2026

Chen Ming, Zhao Duran, Fan Haiping, Zeng Xiaojun, Zhang Wei, Li Lijuan, Li Wei

Abstract excerpt

Multiple sclerosis (MS) is a complex autoimmune disease with strong genetic components, but its genetic mechanisms remain largely underexplored. We aimed to pinpoint causal genes and evaluate their utility for MS risk prediction. We integrated MS genome-wide association study summaries with brain-derived splicing quantitative trait loci (sQTLs) and expression quantitative trait loci (eQTLs) via summary-data-based...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

Identifiers

PMID: 41772215
DOI: 10.1007/s00335-026-10207-6

Genes

TRAF3
ZC2HC1A
ACP2
CD4
IL7
MYNN
RGS1
SAE1
SP140
TSPAN31
TYMP

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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