Can We Predict Who Benefits from Glatiramer Acetate in MS?

Glatiramer acetate (GA) has long been a foundational therapy for individuals living with relapsing-remitting multiple sclerosis (RRMS). Its ability to reduce relapse frequency and slow progression has made it a staple in MS treatment. But despite its broad use, one major limitation remains: we can’t predict in advance who will benefit from the drug and who won’t.

A research poster presented by Saar Anis and colleagues at the 2013 AAN meeting aimed to tackle that very challenge. Their study, “Gene Expression Biomarkers for Glatiramer Acetate Treatment Response in Relapsing-Remitting Multiple Sclerosis,” sheds light on a potential biomarker-based approach to tailor treatment for MS patients — even before they begin therapy.

Why Predictive Biomarkers Matter in MS
Multiple sclerosis is a highly heterogeneous disease. What works for one patient might not work for another. Being able to predict treatment response can:

Reduce time lost on ineffective treatments

Minimize unnecessary side effects

Improve long-term disease outcomes

Help guide clinicians toward more personalized therapy decisions

This is especially important in a chronic disease like MS, where delays in effective therapy can result in irreversible neurological damage.

Study Design: A Closer Look at Blood-Based Gene Expression
The team analyzed peripheral blood samples from 37 RRMS patients before they started treatment with GA. Using Affymetrix gene expression microarrays (HG-U133A2), they scanned the expression of thousands of genes, hoping to find a molecular signature that could distinguish responders from non-responders.

Patients were followed for two years after starting GA. A “good treatment response” was defined as:

At least 1 fewer relapse compared to the two years before treatment

And no more than a 0.5-point increase in the Expanded Disability Status Scale (EDSS)

Of the 37 patients, 25 (67%) were classified as good responders.

The Breakthrough: A 3-Gene Signature That Predicts Response
The researchers identified a signature of 762 transcripts that differed between responders and non-responders — with genes significantly enriched for roles in apoptosis (cell death) and inflammation, both key processes in MS pathophysiology.

From this larger pool, they honed in on three genes with strong individual and combined predictive power:

ACTR5
WDR45
PPP1R13B

All three are involved in apoptosis regulation, which may suggest that patients with more active apoptotic signaling in peripheral immune cells may respond better to the immune-modulating effects of GA.

How Well Does It Work?
The performance of the 3-gene classifier was striking:

Accuracy: 93.8%

Sensitivity (detecting true responders): 96%

Specificity (correctly identifying non-responders): 100%

AUC (Area Under Curve, a measure of prediction strength): 0.865–0.902

This suggests that just these three genes could reliably predict which patients will respond to GA therapy — a powerful step toward individualized medicine in MS.

What This Means for the Future of MS Treatment
If validated in larger, independent cohorts, this 3-gene biomarker panel could become a routine pre-treatment test. That would mean:

MS patients could start treatment with higher confidence that it will work for them.

Clinicians could avoid the trial-and-error approach that currently dominates MS treatment selection.

Research might expand to see if similar apoptotic pathways predict response to other MS drugs — or even other autoimmune diseases.

Final Thoughts
The work by Anis et al. is a prime example of precision medicine in action. While it's still early-stage research, the potential impact is enormous. This 3-gene classifier may one day help ensure that the right patients receive the right MS therapy at the right time — improving lives and outcomes in the process.

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:
Anis S, Sonis P, Hanael E, Gurevich M, Achiron A. Gene Expression Biomarkers for Glatiramer Acetate Treatment Response in Relapsing-Remitting Multiple Sclerosis. Neurology. 2013;80(7_suppl):P05.142. https://doi.org/10.1212/WNL.80.7_supplement.P05.142