Mining cells and medical records for early signs of MS

Multiple Sclerosis (MS) is a disease that can cause nerve damage even before noticeable symptoms appear. For doctors, this early phase is like solving a puzzle with missing pieces—they see unexplained brain abnormalities but lack a full picture. This project aims to fill in these gaps using advanced blood tests, patient information, electronic health records and cutting-edge technologies such as artificial intelligence (AI).

Dr Seyhan Yazar and her team are focusing on the ‘prodromal phase’ of MS. This is the stage where vague symptoms may occur but don’t yet meet the criteria for a diagnosis of MS. These symptoms, such as mild neurological or cognitive issues such as migraines or confusion, occur within the general population as well, which can make it difficult to identify as a symptom of MS.

By analysing large datasets and identifying specific patterns, Dr Yazar and her research team hope to help doctors identify MS more accurately in its early stages.

One major goal of the project is to find signs in the blood, called biomarkers, that could reveal MS before typical symptoms appear. When combined with brain scans, these biomarkers could help doctors diagnose MS earlier, especially in people who are at higher risk, such as those with unusual findings on their brain scans.

By gaining a clearer understanding of MS during its early stages, doctors may be able to diagnose and treat patients sooner, potentially preventing long-term damage and improving their quality of life. This research may also open the door to new preventative measures for MS in the future.