Combination of two new biomarkers optimizes prognosis and therapy of MS

BU: Symbol image CSF sample.  MUI/Bullock
BU: Symbol image CSF sample. MUI/Bullock
The course of the chronic inflammatory nerve disease multiple sclerosis can vary greatly. Individualized therapies for MS sufferers require early and precise prediction of future disease activity. This is made possible by the combination of different biomarkers, as shown in a study by neuroimmunologist Harald Hegen at the University Clinic for Neurology.

Multiple sclerosis (MS) is a common neurological disease in young adulthood. Inflammatory changes in the central nervous system (brain and spinal cord) can lead to individually very variable symptoms with paralysis, sensory deficits, visual disturbances, balance problems, difficulty walking as well as cognitive impairments. Typically, these symptoms occur in the form of so-called disease episodes. Ultimately, there is a risk of suffering permanent disability at a young age as a result.

Early prognosis enables personalized therapy

Neuroimmunologist Harald Hegen from the University Department of Neurology (Director: Stefan Kiechl) knows that "when the next disease flare-up occurs varies greatly from patient to patient, ranging from several flare-ups per year to stable phases lasting for years. Progress in recent years in the development of disease-modifying therapies now makes it possible to effectively prevent disease relapses. These therapies differ not only in their effectiveness, but also in their potential side effects and risks. Accurate prediction of future disease activity is of great importance in order to be able to make a reasonable benefit/risk assessment before initiating a therapy tailored to the individual patient," says Hegen.

Harald Hegen, who has been active for many years in both research and clinical care with a focus on MS, was recently able, together with colleagues, to identify a protein detectable in cerebrospinal fluid (CSF) - the so-called --FLC (kappa free light chains) - as a biomarker for the prognosis of early MS activity. The utility of --FLC as a biomarker in MS was confirmed in an international consensus meeting organized in Vienna by the neuroimmunology working group (leader: Florian Deisenhammer) with the support of ECTRIMS (European Committee for Treatment and Research in MS).

Biomarker combination accurately predicts MS activity

In addition to our established inflammatory marker --FLC, there is another very promising biomarker in MS research, serum neurofilament light (sNfL), which is released from neurons after neuroxonal injury. For the first time, we have addressed the question of whether the combination of these two biomarkers further improves the predictive power of MS disease activity," explains Hegen.

The Innsbruck study, which was funded by a grant from the Austrian Multiple Sclerosis Society, conducted in cooperation with the Leopold Franzens University (Department of Statistics: J. Walde) and published in the journal eBioMedicine, included 86 patients with early-stage MS and followed them up for four years. Our results show that the combination of these two biomarkers allows an even more differentiated risk assessment of future disease activity. For example, in the case of high values for both the --FLC index and the sNfL Z score, the next relapse can be expected with a 98 percent probability within one year; whereas with normal values of both biomarkers, a relapse is unlikely in the next twelve months," Hegen reports.

With such an accurate prediction of future disease activity, it should be possible to select the most suitable individual therapy from the now wide range of different disease-modifying therapies. With the prognostic potential offered by the combination of both biomarkers, the risk-benefit analysis of the various immunotherapies will be simplified many times over," emphasizes Hegen. The results of a prospective, multicenter study under Innsbruck leadership to confirm these findings are eagerly awaited.

(23.05.2023, Text: D. Heidegger, Image: D. Bullock)