Researchers have discovered two previously unknown biological subtypes of multiple sclerosis (MS), a breakthrough that could allow doctors to tailor treatments more precisely to individual patients. The finding, based on MRI scans and blood tests, offers new insights into how the disease damages the brain.
MS, which affects millions of people worldwide, has long been treated based on symptoms rather than underlying biology. As a result, some patients may receive therapies that are less effective for their specific form of the disease. The new study, led by University College London (UCL) and Queen Square Analytics, examined data from around 600 people with MS.
Scientists focused on a blood protein called serum neurofilament light chain (sNfL), which is released when nerve cells are damaged and can indicate disease activity. Using a machine learning model known as SuStaIn, researchers combined sNfL measurements with MRI brain scans to detect patterns of disease progression.
The analysis revealed two distinct subtypes, named “early sNfL” and “late sNfL.” In patients with early sNfL MS, high levels of the protein appeared early in the disease, alongside damage to the corpus callosum, a structure connecting the two halves of the brain. These individuals also developed brain lesions more rapidly, suggesting a more aggressive form of MS.
Patients with late sNfL MS showed brain shrinkage in areas such as the limbic cortex and deep grey matter before sNfL levels rose. This pattern appears to progress more slowly, with nerve damage becoming evident later in the disease.
Identifying these biological patterns could help doctors predict how MS is likely to progress and select treatments accordingly. “MS is not one disease, and current subtypes fail to describe the underlying tissue changes, which we need to know to treat it,” said Dr Arman Eshaghi, the study’s lead author and a researcher at UCL.
“By using an AI model combined with a highly available blood marker and MRI, we have been able to show two clear biological patterns of MS for the first time,” he added. “This will help clinicians understand where a person sits on the disease pathway and who may need closer monitoring or earlier, targeted treatment.”
The findings mean that patients identified with early sNfL MS could be offered higher-efficacy treatments sooner, while those with late sNfL MS may benefit from therapies aimed at protecting brain cells and slowing degeneration.
Caitlin Astbury, senior research communications manager at the MS Society, described the study as an important step forward. “MS is complex, and current definitions based on clinical symptoms often don’t reflect what is happening biologically. This makes it harder to treat effectively,” she said.
Currently, about 20 treatment options exist for relapsing MS, with some therapies for progressive forms emerging. Researchers hope that understanding these biological subtypes will lead to more effective strategies to slow or stop disease progression. “The more we learn about the condition, the more likely we are to develop treatments that can truly change outcomes for patients,” Astbury said.
