Integrative Multi-Omics Analysis of Multiple Sclerosis Reveals Cell-Type-Specific Regulatory Landscapes and Discordant Methylation-Expression Coupling

Abstract

Multiple sclerosis (MS) is an immune-mediated central nervous system disease with mapped genetic risk loci but unresolved cross-layer regulatory mechanisms. We harmonised 30 primary public MS datasets spanning bulk transcriptomics (552 samples, 367 MS/185 healthy control [HC]), DNA methylation arrays (475 samples, 244 MS/231 HC) with sorted-cell whole-genome bisulfite sequencing (WGBS) assessment, single-cell RNA sequencing (RNA-seq; 517,533 cells from 81 donors), and cerebrospinal fluid (CSF) and brain white-matter proteomes, and UK Biobank Pharma Proteomics Project (UK Biobank-PPP) plasma proteomic statistics (407 MS/39,979 HC) for external validation. We prioritised MS-associated genes showing inverse-concordant, cohort-level methylation-expression associations and orthogonal support across layers. After harmonised reprocessing and per-stratum differential testing, a bulk-RNA & times; methylation inverse-concordance filter followed by an independent proteomic and/or donor-level single-cell anchor identified two Tier-1 candidates (IKZF1's anchor is a candidate-panel-adjusted donor-level pseudobulk association, not transcriptome-wide significance): ITGB2 and IKZF1. ITGB2 showed the strongest cross-layer support: RNA down-regulation, promoter hypermethylation and reduced plasma abundance in UK Biobank MS cases, a pattern consistent with altered leukocyte-integrin adhesion. Pathway and network analyses linked the candidates predominantly to leukocyte and lymphocyte activation and differentiation, leukocyte-integrin adhesion, and interferon and cytokine-signalling immune modules. These findings nominate MS-relevant regulatory candidates and provide a reusable multi-omics framework for hypothesis generation and validation.