Decoding Multiple Sclerosis: How Our Genes and Epigenetics Reveal the Cells Behind the Disease

Multiple sclerosis (MS) is one of the most enigmatic autoimmune disorders of our time. It attacks the central nervous system (CNS), disrupting the delicate communication between brain and body. Despite decades of research, one question continues to challenge scientists: which cells and genes truly drive the disease?

A study led by Qin Ma, Hengameh Shams, and Jorge R. Oksenberg from the University of California, San Francisco, has taken a groundbreaking approach to this problem. Published in Communications Biology (Nature Portfolio), their research integrates genome-wide association studies (GWAS) with epigenetic and 3D chromatin mapping to pinpoint the exact cells and regulatory regions that shape MS risk.

Their conclusion is striking: B cells, monocytes, and microglia—cells from both the immune system and the brain—sit at the heart of MS genetics.

Why Genetics Alone Isn’t Enough
Over the past decade, GWAS has identified more than 200 MS-associated genetic variants, highlighting the strong heritable component of the disease. However, most of these variants fall within noncoding regions of the genome—areas that don’t directly code for proteins but instead regulate when and where genes are expressed.

The challenge is to translate these “genetic dots” into meaningful biology: Which genes do these variants affect? And in which cells are these effects most important? This is where the UCSF team innovated. Integrating Epigenetics: The Map Behind the Code
The researchers combined GWAS results with chromatin accessibility (ATAC-seq and DNase-seq) and histone modification data—essentially, molecular markers that reveal which parts of the genome are “open” and active in different cell types.

By analyzing both single-cell and bulk datasets from healthy human immune and brain cells, they found that MS-associated variants are strongly enriched in open chromatin regions of B cells, monocytes, and microglia. These are the same cell types known to orchestrate immune and inflammatory responses in the CNS.

In simpler terms, the genetic variants linked to MS tend to fall within regulatory DNA regions that are active in these cell types—like switches that can turn disease-driving genes on or off.

The Brain’s Immune Cells Join the Story
While B cells and monocytes are peripheral immune cells, microglia are the brain’s resident immune sentinels. For years, researchers have suspected that microglia play a role in MS, but direct genetic evidence was limited.

This study provided that evidence: MS risk variants were significantly enriched in microglial regulatory regions, confirming that the brain’s own immune cells contribute to disease susceptibility. This finding bridges the gap between peripheral immune dysfunction and CNS pathology—a hallmark of MS.

Enhancers and 3D Chromatin: Linking Variants to Genes
Not all genes are regulated in a linear fashion; many are controlled through long-range chromatin interactions, where distant DNA regions loop together. Using a computational framework called H-MAGMA, the researchers mapped these 3D genomic contacts to link noncoding MS variants to their potential target genes in each cell type.

This approach identified over 1,200 candidate genes in each of the three major cell types (B cells, monocytes, and microglia), including 717 genes shared across all three. Many of these genes are involved in cytokine signaling, immune activation, and antigen presentation—core pathways in autoimmune disease.

A particularly interesting finding was the identification of DNMT3A as a microglia-specific risk gene. This gene encodes a DNA methyltransferase enzyme involved in epigenetic regulation and histone modification, suggesting that epigenetic dysregulation in microglia could contribute to MS risk.

Polygenic Risk, Personalized
The team went a step further and developed cell-specific polygenic risk scores (CPRS)—a way to calculate an individual’s genetic risk based on variants active in specific cell types. When tested in large human cohorts (UK Biobank and UCSF’s EPIC MS study), these scores reliably predicted MS susceptibility.

Individuals in the top 5% of monocyte- or B cell–specific scores had a 3–5 times higher risk of MS than average.

Even more intriguing, these cell-based scores correlated with MRI brain metrics: higher monocyte and microglia CPRS were associated with lower white matter volume, suggesting a direct genetic influence on neurodegeneration in MS.

What This Means for MS Research and Therapy
This study represents a major leap forward in connecting genetic signals to cellular function in MS. It supports a model where:

B cells act as antigen-presenting and antibody-producing drivers of inflammation.

Monocytes amplify immune signaling and infiltrate the CNS.

Microglia modulate the local inflammatory environment and neuronal damage.

Therapies targeting B cells (such as anti-CD20 antibodies) have already proven effective in MS, and these findings reinforce why. The identification of microglia-specific risk genes like DNMT3A opens new therapeutic avenues—perhaps targeting the epigenetic machinery that governs immune activation in the brain.

The Road Ahead
While powerful, this integrative analysis relies heavily on data from healthy individuals. Future work will need single-cell epigenomic data from MS patients to reveal disease-state–specific chromatin changes.

Still, by blending the worlds of genomics, epigenetics, and neuroimmunology, this study lays the foundation for a new era of precision medicine in MS—where treatments can be tailored to the cell types and regulatory networks that truly drive disease.

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. et al. Integration of epigenetic and genetic profiles identifies multiple sclerosis disease-critical cell types and genes. Commun Biol 6, 342 (2023). https://doi.org/10.1038/s42003-023-04713-5