Decoding Multiple Sclerosis DNA — a Friendly Guide to Today’s SNP Discoveries

Multiple sclerosis (MS) begins when an over-eager immune system chips away at the myelin that insulates nerve fibres. Environmental triggers such as low vitamin D, Epstein–Barr virus and smoking clearly matter, yet twin and family studies show that inheritance also tips the scales. Early linkage and candidate-gene screens revealed that several immunological genes—particularly those in the HLA region—mark people who go on to develop MS, setting the stage for genome-wide hunts for risk variants.

From one-gene hunts to genome-wide scans
Until the mid-2000 s, researchers chased plausible suspects one at a time, a strategy that often produced conflicting results. Genome-wide association studies (GWAS) changed the landscape by testing hundreds of thousands of single-nucleotide polymorphisms (SNPs) in a single sweep. GWAS quickly taught us that MS is polygenic: dozens of modest-effect variants, rather than one “master” mutation, collectively nudge disease risk.

The strongest non-HLA susceptibility signals
Across many GWAS, a handful of immune-related genes keep popping up. The T-cell cytokine-receptor genes IL7RA (rs6897932) and IL2RA (rs2104286) are the most consistently replicated; both influence how vigorously T cells respond to interleukins.

Variants in CLEC16A, CD58, CD6, CD40 and TNFRSF1A also emerge repeatedly, pointing to checkpoints that control antigen presentation, co-stimulation and inflammatory signalling.

Although each SNP alters risk by only a few percent, together they reinforce the view that MS is, at its core, an immune-mediated disorder.

A cautionary tale: the TNF-α promoter
One of the first MS SNPs studied was the –308 G/A change in the TNF-α promoter. The A-allele drives higher baseline TNF-α production, yet, paradoxically, appears less frequent in Serbian MS patients—an early reminder that the same cytokine can be friend or foe depending on biological context and population genetics.

Can your genome predict who benefits from interferon-β?
Interferon-β remains a first-line therapy, but roughly half of patients experience sub-optimal benefit or develop neutralising antibodies. Several pharmacogenomic screens point to the heparan-sulfate proteoglycan gene GPC5: carriers of the rs10492503 A-allele consistently show better clinical and MRI responses. Other promising, though smaller, signals lie in HAPLN1, COL25A1, GRIA3, CIT and ADAR. These results have yet to migrate into routine clinical testing, but they lay the groundwork for “test-before-treat” strategies.

One size does not fit all — the importance of ancestry
Meta-analyses show that both the size and sometimes even the direction of a SNP’s effect vary across European, Australian, African-American and Sardinian cohorts. For example, the IL2RA and IL7RA signals replicate strongly in northern Europeans but fade in some African-American studies. Similarly, different TNF promoter haplotypes dominate in Spanish, Hungarian and Turkish populations.

These disparities warn against over-generalising risk scores and highlight the need for region-specific research.

Where the field is heading
Larger international biobanks promise to capture rarer variants and better quantify gene–environment interactions. Functional follow-up—using CRISPR editing, single-cell RNA-seq and proteomics—aims to reveal how each risk allele rewires immune circuits. Finally, researchers are beginning to weave SNP data together with epigenetic marks, microbiome profiles and lifestyle factors, hoping to build integrated models that predict not just who gets MS but who will benefit from which therapy.

Key take-home messages
MS genetics is polygenic and immune-centric. Many small-effect SNPs, especially in cytokine and co-stimulatory pathways, collectively mould risk.

Population context matters. Always interpret genetic tests alongside ancestry and local allele frequencies.

Pharmacogenomics is emerging. Markers like GPC5 rs10492503 show promise for tailoring interferon-β therapy, but require validation in diverse cohorts.

We’re not done yet. Integrating genetics with functional studies and environmental data is the next leap toward personalised MS care.

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:
Pravica, V., Popadic, D., Savic, E. et al. Single nucleotide polymorphisms in multiple sclerosis: disease susceptibility and treatment response biomarkers. Immunol Res 52, 42–52 (2012). https://doi.org/10.1007/s12026-012-8273-y