This post was originally published on here
Scientists from UCL have used artificial intelligence to discover two new biological sub-types of multiple sclerosis
Scientists have uncovered two fresh sub-types of multiple sclerosis (MS) that could open doors to innovative treatments. Utilising artificial intelligence (AI), researchers examined brain scans alongside levels of a blood marker for nerve cell damage called serum neurofilament light chain (sNfL).
Analysis of 634 MS patients allowed specialists from Queen Square Analytics and University College London to pinpoint two “biologically informed MS sub-types”. The first sub-type, termed early-sNfL, featured patients with elevated levels of the blood biomarker during the disease’s initial stages, combined with harm to a brain region called the corpus callosum that influences thinking, memory and movement coordination.
The second sub-type, late-sNfL, displayed a delayed increase in sNfL alongside “early volume loss in the cortical and deep grey matter volumes”, according to the authors writing in the journal Brain, reports Surrey Live. Study lead 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.”
Caitlin Astbury, senior research communications manager at the MS Society, shared with 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.”
