Genetic Puzzle of Multiple Sclerosis: How Tiny DNA Changes Might Shape Diagnosis and Treatment
Multiple sclerosis (MS) immune-mediated diseases affecting the central nervous system. It's unpredictable, varies widely from patient to patient, and often strikes young adults—particularly women. While its exact cause remains elusive, scientists are steadily uncovering pieces of the puzzle. One especially promising piece? Genetics—specifically, tiny variations in our DNA called single nucleotide polymorphisms (SNPs).
A team of researchers from Serbia, led by Dr. Vera Pravica and colleagues, reviewed the latest evidence about SNPs and how they may influence both who gets MS and how well they respond to treatment. Their review is a deep dive into the evolving world of MS genetics, exploring how these minute DNA changes could lead to more personalized and effective healthcare for MS patients.
What Are SNPs and Why Do They Matter?
SNPs (pronounced “snips”) are small variations in the DNA sequence that occur when a single nucleotide—A, T, C, or G—is altered. Though minor, these changes can influence how genes are expressed or how proteins function. In MS, SNPs can impact immune system activity, inflammation, and even response to medication.
While no single gene causes MS, combinations of SNPs in immune-related genes have been shown to modestly increase susceptibility. These same SNPs might also serve as biomarkers, helping doctors better diagnose MS, predict how it will progress, and tailor treatments for individual patients.
Immune System: The Double-Edged Sword
MS is an autoimmune disease, meaning the body’s immune system mistakenly attacks its own tissues—in this case, the protective myelin sheath surrounding nerves in the brain and spinal cord. The Serbian team highlights that T cells, B cells, and even innate immune cells like macrophages and dendritic cells all play roles in this misguided attack.
This immune complexity aligns with the variety in MS symptoms and disease course. Some people have relapsing-remitting MS (RRMS), others transition into a more progressive form, and still others show slow, steady progression from the start. Genetic differences may help explain why.
Genetic Signatures of MS Susceptibility
Dr. Pravica’s team summarizes findings from decades of genetic studies, from older “candidate gene” approaches to modern genome-wide association studies (GWAS). Here are a few key SNPs that consistently appear across studies:
IL7RA (Interleukin-7 receptor alpha) – Vital for T cell development, the rs6897932 SNP affects how much of the receptor’s soluble vs. membrane-bound forms are produced. This has been linked to MS risk.
IL2RA (Interleukin-2 receptor alpha) – This receptor plays a key role in regulatory T cell function. Certain SNPs here are associated with both MS and other autoimmune diseases.
CLEC16A – Highly expressed in antigen-presenting cells, variants in this gene may influence how the immune system recognizes pathogens.
CD40 and CD58 – These molecules help T cells activate. SNPs in these genes are associated with higher MS risk and may also influence disease severity.
Pharmacogenomics: Predicting Treatment Response
One of the most widely used MS treatments is interferon-beta (IFN-β). But not everyone benefits from it—about half of patients show little improvement. Could SNPs help predict who will respond?
Yes, says the Serbian team.
Among the most promising biomarkers is a SNP in the GPC5 gene (glypican-5), which is involved in neural repair and immune regulation. Carriers of a specific variant (rs10492503) are more likely to respond well to IFN-β therapy.
Other notable SNPs linked to treatment response include:
MX1 and OAS1 – These genes are involved in the interferon response pathway.
CD46 and CTSS – Related to immune modulation and antigen processing.
JAK2-IL10RB-GBP1-PIAS1 allele combinations – Identified in Irish patients as being more common among IFN-β responders.
Intriguingly, some SNPs also influence the likelihood of developing neutralizing antibodies (NABs) against IFN-β, which can reduce its effectiveness. This further underscores the need to consider genetics when choosing therapies.
Ethnic Differences: One Size Doesn’t Fit All
One of the most critical takeaways from this research is the role of ethnicity in SNP distribution. SNPs that are common and significant in one population may be rare or irrelevant in another. For instance, IL7RA SNPs show strong associations with MS in Europeans but not in African Americans.
This highlights the need for region-specific and ethnicity-focused studies, especially when developing genetic tests or tailoring treatments. What works in Western Europe might not apply in Serbia—or in India or South America, for that matter.
The Road Ahead: Toward Personalized MS Care
Genetic biomarkers hold immense promise, but the researchers stress that we’re not there yet. Many of the findings need further validation, especially through functional studies that clarify how each SNP affects immune behavior or drug metabolism.
Nonetheless, the direction is clear. We’re entering an era where a simple genetic test could guide neurologists in choosing the best treatment, avoiding ineffective options, and even predicting how a patient's MS might progress. Precision medicine is no longer a dream—it’s a developing reality.
Final Thoughts
Multiple sclerosis remains a challenging disease, but studies like this one remind us how far we've come in understanding it. Thanks to SNP research, we're beginning to see how our genes—tiny and seemingly insignificant variations—can shape our health in profound ways. The ultimate goal? A future where MS diagnosis and treatment are tailored, effective, and as unique as the patients themselves.
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).
