Two novel sub-types of multiple sclerosis (MS) have been identified, a discovery potentially paving the way for new treatments.
Researchers employed artificial intelligence (AI) to assess brain scans and levels of serum neurofilament light chain (sNfL), a blood marker for nerve cell injury.
Experts from Queen Square Analytics and University College London analysed 634 MS patients, identifying two “biologically informed MS sub-types”.
One, termed ‘early-sNfL’, showed high levels of the blood biomarker early in the disease, alongside damage to the corpus callosum – a brain region crucial for thought, memory, and movement coordination.
The other sub-type, late-sNfL, showed a later rise in sNfL and is coupled with “early volume loss in the cortical and deep grey matter volumes”, the authors wrote in the journal Brain.
Lead author of the study Dr Arman Eshaghi, from the UCL Queen Square Institute of Neurology and UCL Hawkes Institute at Department of Computer Science, said: “Using routine brain images and a blood marker of nerve-cell injury (neurofilament light), we identified two distinct biological trajectories in multiple sclerosis.
“This helps explain why people living with MS can follow different paths and it’s a step toward more personalised monitoring and treatment.
“Current labels of relapsing-remitting, secondary progressive and primary progressive fail to provide this stratification, and this work at University College London and Queen Square Analytics, amongst others, is helping to change our understanding and definition of MS types and their treatment in the near future.”
MS is a condition which affects the brain and spinal cord. A protective membrane that wraps around nerve cells becomes damaged in MS and causes symptoms such as fatigue, pain, spasms and problems with walking.
Caitlin Astbury, senior research communications manager at the MS Society, told the Guardian: “This study used machine learning to look at MRI and biomarker data from people with relapsing-remitting and secondary progressive MS.
“By combining this data, they were able to identify two new biological subtypes of MS.
“Over recent years, we’ve developed a better understanding of the biology of the condition.
“But, currently, definitions are based on the clinical symptoms a person experiences.
“MS is complex and these categories often don’t accurately reflect what is going on in the body, which can make it difficult to treat effectively.”
She added: “The more we learn about the condition, the more likely we will be able to find treatments that can stop disease progression.”