3 August 2026
New findings from the research group led by Jens Kuhle (DKF, DBM, and RC2NB) show that elevated levels of the blood marker glial fibrillary acidic protein (GFAP) are associated with an increased risk of worsening disease-related impairments. This could mean that, in the future, GFAP blood levels could be used to monitor and predict the course of the disease in people with MS more precisely.
The findings could help monitor and predict disease progression more accurately in the future, thereby enabling more personalised treatment and accelerating the development of new treatment strategies for people with MS.
Nearly 19,000 blood samples analysed
For the study, the research team analysed a total of 18,629 blood samples from 2,329 people with multiple sclerosis. The data came from two large international long-term cohorts: the Swiss Multiple Sclerosis Cohort (SMSC) and the EPIC study at the University of California, San Francisco. The focus was on determining whether changes in blood GFAP levels could indicate progression independent of relapse activity (known as PIRA). This form of disease progression is considered one of the most important factors in the long-term development of disability in multiple sclerosis.
Elevated GFAP levels are associated with a higher risk of progression
The analyses showed that individuals with elevated GFAP levels had a significantly higher risk of subsequent increases in disability. At the same time, the researchers observed that declining GFAP concentrations following the initiation of therapy were associated with more favorable clinical outcomes. The results suggest that repeated measurement of GFAP in the blood can provide important information about disease progression. This means the biomarker could help identify patients at increased risk of disease progression at an early stage in the future.

Maximilian Einsiedler, MD, first author of the study

Prof. Jens Kuhle, MD, PhD
A complement to already established biomarkers
GFAP (https://shiny.dkfbasel.ch/baselgfapreference) complements the already well-established biomarker neurofilament light chain (NfL; https://shiny.dkfbasel.ch/baselnflreference), which primarily reflects neuroaxonal damage resulting from acute inflammatory activity and relapses. While NfL thus provides evidence specifically of relapses and inflammatory processes, GFAP appears to be more strongly linked to the biological mechanisms of long-term disease progression. Combining both markers could therefore provide a more nuanced insight into the processes underlying the disease and improve the clinical assessment of disease progression.
Potential for clinical studies and personalised medicine
The researchers view GFAP not only as a promising biomarker for clinical care but also for the development of new therapies. By specifically identifying individuals at increased risk of disease progression, future studies could be designed more efficiently, and new treatment approaches could be investigated in a more targeted manner. The study thus represents an important step toward precision medicine for multiple sclerosis. Blood-based biomarkers such as GFAP could help predict individual disease courses more accurately in the future, support treatment decisions, and advance the development of effective treatments to slow disease progression.

As of July 16, 2026 (actively recruiting)
Centres
8 (Aarau, Basel (Data Center), Bern, Geneva, Lausanne, Lugano, St. Gallen, Zurich)
Data
- 2,218 patients
- 19,572 visits (median follow-up: 6 years)
- More than 93% of visits involved sample collection
- 15,947 NfL and GFAP measurements
- 801 documented prospective relapses
- 13,232 standardized and evaluated brain MRI scans
- 440,200 biological samples
Supported by the DKF through
Data Analysis, Regulatory Affairs, Data Center, Data Science, Monitoring
Website
SMSC - Swiss MS Cohort
As of July 29, 2026 (actively recruiting)
Centres
1 (Sandler Neurosciences Center, San Francisco, CA, USA)
Data
- Over 500 patients
- Since 2004, with follow-up of more than 10 years
- Annual visits
- MRI scans, blood samples, genetic analyses, microbiome analyses, and other biological tests
Website
UCSF MS EPIC Study