Decoding MS Treatment: How Genetics Could Guide the Choice Between Interferon and Glatiramer

Multiple sclerosis (MS) is a complex immune-mediated disease where the immune system attacks the central nervous system, damaging myelin and leading to progressive neurological symptoms. Over the past two decades, disease-modifying therapies (DMTs) have dramatically changed the outlook for patients, especially those with relapsing–remitting MS (RRMS).

Two of the earliest and most widely used first-line therapies are:

Interferon-beta (IFN-β) – shown to reduce relapse rates and slow progression in RRMS and in some cases of secondary progressive MS (SPMS).

Glatiramer acetate (GA) – particularly effective in RRMS, with a favorable safety profile.

While newer treatments (like fingolimod, natalizumab, and alemtuzumab) have entered the scene, IFN-β and GA remain important first-line options worldwide, largely because of their long-term safety.

But here’s the catch: not all patients respond equally well to these drugs. Some show remarkable improvement, while others see little to no benefit. So, how do we know which treatment will work best for a particular person?

This is where pharmacogenetics steps in.

Pharmacogenetics in MS: From Single Genes to Composite Biomarkers
Pharmacogenetics looks at how genetic differences influence the way individuals respond to drugs. In MS, many studies have linked variations in immune-related genes to treatment outcomes.

For IFN-β, genes in the type I interferon signaling pathway, cytokine genes, and extracellular matrix components have shown associations with treatment response.

For GA, certain immune-response genes and HLA class II alleles appear relevant.

However, most of these associations involve single genetic variants, which are often not strong or consistent enough to serve as reliable predictors in clinical practice. Since MS treatment response is influenced by many genes working together, scientists are now focusing on composite genetic markers — combinations of alleles that, together, give a clearer picture of whether a drug will work.

The Study: Comparing Responders to IFN-β and GA
Kulakova and colleagues (2014) introduced a comparative pharmacogenetics approach. Instead of looking at IFN-β and GA separately, they directly compared genetic profiles of:

Responders to IFN-β vs. responders to GA

Nonresponders to IFN-β vs. nonresponders to GA

This was done in a large Russian cohort:

253 MS patients treated with IFN-β

285 MS patients treated with GA

All were genotyped for nine immune-response genes thought to play roles in MS pathology or drug mechanisms: DRB1, IFNB1, IFNAR1, IFNG, TNF, TGFB1, IL7RA, CCR5, and CTLA4.

By analyzing allele combinations rather than single variants, the team identified discriminative genetic patterns — sets of markers that could point toward the better treatment choice for each patient.

Key Findings: Genetic Signatures of Drug Response
The results highlighted several important genetic players:

CCR5 (chemokine receptor gene) – stood out as central in nearly all predictive combinations.

A specific deletion variant (CCR5*d) was more common in IFN-β responders and GA nonresponders.

Meanwhile, patients with two normal copies (CCR5*w/w) were more likely to respond to GA.

This makes sense biologically: CCR5 regulates immune cell migration into the CNS, a process targeted differently by IFN-β and GA.

IFNAR1 (interferon receptor gene) –

Carriage of the G allele (together with CCR5*d) strongly pointed toward benefit from IFN-β.

This reflects IFNAR1’s role in the interferon signaling pathway.

TGFB1 (a cytokine gene) –

The T allele seemed to enhance IFN-β benefit, likely by reducing harmful immune cell migration into the CNS.

DRB1 (HLA gene) –

Certain variants (like DRB115) were enriched in IFN-β responders, while others (like DRB116) predicted poor IFN-β response.

CTLA4 (immune checkpoint gene) –

The G allele was enriched in IFN-β nonresponders, suggesting those patients may do better on GA.

One of the most reliable predictive combinations was:

CCR5d + IFNAR1G → strongly associated with better outcomes on IFN-β.

Why This Matters: Toward Personalized MS Therapy
This study demonstrates that composite genetic markers — not just single SNPs — can help discriminate which drug a patient is more likely to benefit from.

Practical implications:

A patient with CCR5d and IFNAR1G may be steered toward IFN-β.

A patient carrying CCR5w/w and CTLA4G might be better suited for GA.

Such insights could spare patients years of ineffective therapy and side effects.

Future outlook:

As more DMTs become available, comparative pharmacogenetics could guide not only first-line but also second-line therapy choices.

Validation in larger, multi-ethnic cohorts is needed before these markers can be used in clinical practice.

Eventually, a genetic test panel could help neurologists personalize MS treatment plans at diagnosis.

Conclusion
Kulakova and colleagues have provided an important step toward precision medicine in MS. By comparing genetic profiles across different treatment responders, they showed that CCR5, IFNAR1, TGFB1, DRB1, and CTLA4 carry predictive value for distinguishing between IFN-β and GA response.

While the work needs replication, the concept is powerful: instead of trial-and-error prescribing, doctors could one day tailor MS therapy to a patient’s genetic makeup — making treatment more effective, faster, and safer.

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:
Kulakova, O. G., Tsareva, E. Y., Lvovs, D., Favorov, A. V., Boyko, A. N., & Favorova, O. O. (2014). Comparative pharmacogenetics of multiple sclerosis: IFN-β versus glatiramer acetate. Pharmacogenomics, 15(5), 679-685.