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Genetic Biomarker Predicts Optimal Treatment for Multiple Sclerosis

Digital DNA strand with data visualization representing genetic biomarkers for multiple sclerosis.
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Treatment with interferon or with glatiramer acetate? This question arises for many patients who receive a diagnosis of multiple sclerosis (MS) for the first time. Until now, the choice between the two could practically be made at random: both preparations are considered established basic therapies, both have relatively low side effects and both are relatively well tolerated. And finally: as with all immunomodulatory therapies, both do not help all people equally well. However, thanks to a study led by the University of Münster, there is now a clear criterion for choosing the medication.


The international research group has identified a genetic biomarker that predicts whether MS patients will respond particularly well to treatment with glatiramer acetate (GA). People with the tissue type HLA-A*03:01 benefit significantly more from GA than from interferon beta (IFN-β). The results of the multicentre analysis of more than 3,000 MS patients have now been published in the journal eBioMedicine.


"Our study shows for the first time that a genetic marker is linked to the treatment success of an MS medication," explains study leader Professor Nicholas Schwab of the University of Münster. "This allows us to predict before starting therapy whether glatiramer acetate or interferon is likely to be the better choice." In about one in three MS patients, the decision falls on GA, and in the other two cases, interferon beta is likely to be more effective. "This is a significant advance for personalised MS treatment," says Professor Heinz Wiendl, Spokesperson of the German Competence Network on Multiple Sclerosis who designed the study.

Clinical benefit confirmed in five independent cohorts

GA leads to specific T-cell responses in patients, which the team examined more closely. The researchers analysed the T-cell receptor sequences (TCR) in the blood of 3,021 MS patients, whose samples were provided from several separate international cohorts. T-cell clones were identified that were found after GA therapy only in patients who also carried specific HLA molecules, namely HLA-A*03:01 or HLA-DRB1*15:01. If one of these two HLA molecules is present, the immune system thus reacts to GA therapy. Practically, however, patients benefit only in one of the two cases: only MS patients with the HLA-A*03:01 gene variant have a proven clinical treatment benefit, i.e. they improve due to GA therapy.


To ensure that the results are also relevant in clinical application, the team examined five large cohorts and study populations from the USA, France and Germany, including the NationMS cohort of the German Competence Network Multiple Sclerosis. In all analyses, carriers of the HLA-A*03:01 gene variant showed significantly fewer symptoms of the disease under GA therapy compared to IFN-β treatment. Statistically, this affects about 30 to 35% of European MS patients as they carry the HLA-A*03:01 allele.

Personalised therapy decision possible through simple genetic testing

What is special about this discovery is that the new research result can already be applied in therapy consultation in the short term - because an HLA test, which is already established for transplants or drug safety, for example, detects the relevant gene variant.


However, the knowledge gained from the study reaches even further. It not only provides a clinically relevant biomarker but also new clues about the mechanism of action of GA – the observed public T-cell responses suggest that GA does not need all of its protein components to work. Instead, only few fragments of the GA mixture play a dominant role, perhaps even just one. In future, this could lead to the targeted further development of the drug.


Reference: Zhang BC, Schneider-Hohendorf T, Elyanow R, et al. HLA-A03:01 as predictive genetic biomarker for glatiramer acetate treatment response in multiple sclerosis: a retrospective cohort analysis. eBioMedicine. 2025;118:105873. doi: 10.1016/j.ebiom.2025.105873


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