Decoding Multiple Sclerosis Susceptibility Through Cell-Resolved Epigenomics and 3D Genome Architecture
Multiple sclerosis (MS) is a complex autoimmune disorder of the central nervous system in which genetic susceptibility is substantial, yet mechanistic interpretation of genome-wide association study (GWAS) loci remains difficult because most signals map to noncoding regulatory DNA rather than protein-coding sequence. Ma and colleagues address this interpretability gap by integrating MS GWAS summary statistics with cell-resolved epigenomic annotations and three-dimensional (3D) chromatin interaction data to infer which cell types and regulatory programs most plausibly mediate inherited risk. Their central objective is explicitly translational: to move from statistical associations toward a biologically grounded map of disease-critical cell types and genes, and then evaluate whether cell-specific genetic burden relates not only to MS risk but also to quantitative clinical phenotypes.
Data Integration Strategy: From GWAS Loci to Cell-Specific Regulatory Context
The authors combine multiple layers of functional genomics, including single-cell ATAC-seq (scATAC-seq) and bulk chromatin accessibility assays, histone modification (ChIP-seq) profiles, and reference catalogs of candidate cis-regulatory elements (cCREs). Enrichment analyses are performed with GARFIELD, which is designed to control key confounders (e.g., minor allele frequency, distance to transcription start sites, linkage disequilibrium proxies) when asking whether GWAS signals preferentially fall within regulatory annotations from particular cell types. This design choice is important because naïve overlap analyses can be inflated by genomic structure and annotation density rather than true biology.
Regulatory Enrichment Points to B Cells, Monocytes, and Microglia
A consistent signal emerging from the enrichment layer is that MS-associated variants concentrate in active regulatory regions—particularly enhancer-like elements—within peripheral immune compartments and microglia. Using histone marks and ENCODE cCRE signatures, the study reports pronounced enrichment in enhancer and promoter-associated chromatin, with B cells repeatedly appearing as the most enriched immune cytotype and monocytes also strongly represented. In the central nervous system, microglia stand out relative to other brain cell types, strengthening the case that MS susceptibility is not exclusively peripheral but reflects convergent immune–CNS regulatory architecture.
Assigning Putative Causal Genes via 3D Chromatin Linking
To convert regulatory-variant enrichment into actionable gene hypotheses, the authors apply H-MAGMA, leveraging promoter capture Hi-C and H3K4me3 HiChIP interaction maps generated in B cells, monocytes, and microglia. This step produces large but structured gene sets (on the order of ~1.1–1.2k genes per cell type) and partitions them into shared versus unique components: 717 genes shared across the three cell types and hundreds of cell-type-specific candidates (e.g., 234 B-cell-unique; 136 monocyte-unique; 281 microglia-unique). Functional enrichment of the shared set highlights canonical immune pathways (e.g., cytokine signaling, leukocyte activation), whereas unique sets implicate more cell-specific processes, including an epigenetic axis in microglia (e.g., PRC2-linked categories) with DNMT3A among the notable microglial candidates.
Cell-Specific Polygenic Risk Scores as a Quantitative Test of “Cell-Type Burden”
A major methodological contribution is the construction of cell-specific polygenic risk scores (CPRS), computed from SNPs assigned to each cell-type gene set (B cell, monocyte, microglia), plus a combined score. Using PRSice-2 and optimizing across standard GWAS P-value thresholds, the authors evaluate performance in UK Biobank (phase 1 and 2) and an independent clinically curated cohort (UCSF-EPIC). CPRS models show statistically strong associations with MS status; when focusing on “unique” SNP subsets per cell type, monocyte- and B-cell-based scores show particularly prominent risk associations, replicated across cohorts. Furthermore, stratification by CPRS percentiles indicates that individuals in the top 5% of CPRS distributions exhibit approximately 3–5× increased odds of MS relative to median strata, with monocyte-specific tails showing especially elevated risk.
Linking Genetic Burden to MRI and Clinical Disease Activity
Beyond case–control discrimination, the study probes whether CPRS correlates with neuroimaging markers and relapse activity—an important step because it tests whether inferred cell-type genetic burden has phenotypic relevance within established MS pathology. In the UCSF-EPIC cohort, CPRS associations are evaluated against baseline MRI volumetrics (brain volume, white matter volume, gray matter volume, CSF volume) while adjusting for age, sex, and disease duration. The most robust findings center on white matter volume (WMV): monocyte-specific CPRS shows the strongest association, and microglia-specific unique-SNP CPRS also associates significantly with WMV; the paper also reports that excluding the MHC can differentially affect susceptibility vs phenotype associations, suggesting distinct mechanisms for MHC effects on risk versus progression-related traits. Additionally, increased B-cell- and microglia-specific genetic burden is associated with relapse activity over a 5-year interval.
Interpretation, Limitations, and Translational Outlook
The results consolidate a coherent mechanistic narrative: inherited MS risk is enriched in active regulatory DNA in B cells and monocytes (peripheral immune axis) and in microglia (CNS-resident immune axis), with 3D chromatin-informed mapping nominating both shared immune genes and cell-specific regulatory programs. Clinically, the alignment with the success of B-cell-depleting anti-CD20 therapies reinforces biological plausibility, while the microglial enrichment supports growing evidence that CNS innate immunity contributes to susceptibility rather than representing only downstream inflammation. Key limitations acknowledged by the authors include the absence of scATAC-seq data directly from MS patient tissues—an important constraint given that disease-state chromatin landscapes can diverge from healthy references—thereby motivating future patient-derived single-cell epigenomic profiling and functional validation of nominated regulatory networks.
Disclaimer: This blog post is based on the provided research article and is intended for informational purposes only. It is not intended to provide medical advice. Please consult with a healthcare professional for any health concerns.
References:
Ma, Q., Shams, H., Didonna, A., Baranzini, S. E., Cree, B. A., Hauser, S. L., ... & Oksenberg, J. R. (2023). Integration of epigenetic and genetic profiles identifies multiple sclerosis disease-critical cell types and genes. Communications biology, 6(1), 342.
