Untangling the Genetic Web of Multiple Sclerosis: How Brain Gene Activity Fuels Inflammation

Multiple sclerosis (MS) is one of the most complex immune-mediated diseases of the central nervous system (CNS). Characterized by chronic inflammation and demyelination, MS affects millions worldwide and varies widely in symptoms, progression, and response to therapy. Understanding what causes MS—beyond mere correlation—has remained one of biomedical research’s biggest challenges.

In a fascinating study published in Frontiers in Bioengineering and Biotechnology, Teresa Fazia and colleagues took an innovative route to untangle these causal relationships. Instead of traditional association studies, they applied a two-sample Mendelian Randomization (MR) approach—a powerful statistical tool that leverages genetics to infer causation rather than correlation.

A New Way to Ask “What Causes MS?”
Mendelian Randomization (MR) uses genetic variants as “natural experiments.” Because genes are randomly assorted at conception, they can serve as instrumental variables to test whether a biological factor (like gene expression) actually causes a disease, rather than just being associated with it.

In this case, the authors examined whether expression levels of five key NF-κB pathway–related genes in specific brain regions have a causal role in MS:

CCL2 (MCP-1) – a pro-inflammatory chemokine

NFKB1 – a core component of the NF-κB transcription complex

MAPK14 (p38α) – a regulator of inflammation and cytokine signaling

TNFRSF1A (TNF receptor 1) – a key immune pathway receptor

CXCL10 (IP-10) – a chemokine involved in T-cell recruitment

All five genes have previously been implicated in neuroinflammation and MS susceptibility, but it remained unclear whether their expression in the brain actually drives the disease.

The Data: From Families to Brains
The study combined two powerful data sources:

Genetic data from 20 multiplex Sardinian families, including both affected and unaffected individuals.

Brain tissue gene expression data from the United Kingdom Brain Expression Consortium (UKBEC), covering 10 distinct brain regions — from the cerebellum and hippocampus to the medulla and thalamus.

By linking genetic variants that influence gene expression (expression quantitative trait loci, or eQTLs) to MS risk, the team could infer causal relationships between gene expression in the brain and disease susceptibility.

The Analytical Approach
The researchers performed:

Univariable MR – testing one gene at a time for its total causal effect on MS.

Multivariable MR (MVMR) – accounting for the fact that these genes interact within the same NF-κB pathway, to isolate direct effects from indirect ones.

They also used robust methods like Inverse-Variance Weighted (IVW) estimation and sensitivity analyses (MR-Egger, Weighted Median Estimator) to ensure the validity of their findings, filtering out potentially biased or “pleiotropic” genetic instruments.

What They Found
Two genes stood out:

1. CCL2 in the Medulla
Higher CCL2 expression in the medulla was causally associated with increased MS risk.

A one-standard-deviation increase in CCL2 expression corresponded to about a 31% increase in odds of developing MS.

This makes biological sense—CCL2 attracts immune cells to sites of inflammation and can disrupt the blood–brain barrier, a hallmark event in MS pathology.

2. NFKB1 in the Cerebellum
Similarly, increased NFKB1 expression in the cerebellum was linked to a 39% higher risk of MS.

NFKB1 is a master regulator of inflammatory signaling, and its overactivation is known to exacerbate autoimmune responses.

Both effects were statistically robust, surviving multiple testing correction and bootstrap validation.

Multi-Gene, Multi-Tissue Insights
When the researchers extended their analysis to a multivariable framework, they found something even more intriguing:

In the cerebellum, NFKB1 and TNFRSF1A showed positive direct effects on MS risk, while CCL2 showed a protective (negative) effect once interactions were accounted for.

In the medulla, CCL2’s effect remained positively causal, reinforcing its role as a key driver of inflammation.

This suggests that the interplay between NF-κB–related genes differs across brain regions — some effects may amplify inflammation, while others may counterbalance it.

Why It Matters
This study highlights several important insights:

Gene expression in specific brain regions—not just immune cells—can causally influence MS risk.

The NF-κB signaling pathway emerges as a central hub in MS pathogenesis, offering potential therapeutic targets.

The combination of genetic data and tissue-specific transcriptomics through Mendelian Randomization opens a powerful avenue for exploring causal biology in complex diseases.

The Takeaway
Fazia et al.’s work elegantly demonstrates how integrating genetics, brain expression data, and advanced causal inference can deepen our understanding of neuroinflammatory diseases.

Their findings point toward NFKB1 and CCL2 as pivotal players in MS—genes whose altered expression in the brain’s medulla and cerebellum may trigger or modulate disease onset.

As precision medicine advances, such insights could inform targeted therapies that modulate specific signaling pathways within defined brain regions—bringing us one step closer to personalized treatments for MS.

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:
Fazia, T., Nova, A., Gentilini, D., Beecham, A., Piras, M., Saddi, V., Ticca, A., Bitti, P., McCauley, J.L., Berzuini, C., & Bernardinelli, L. (2020). Investigating the Causal Effect of Brain Expression of CCL2, NFKB1, MAPK14, TNFRSF1A, CXCL10 Genes on Multiple Sclerosis: A Two-Sample Mendelian Randomization Approach. Frontiers in Bioengineering and Biotechnology, 8:397. https://doi.org/10.3389/fbioe.2020.00397