Genetic subtypes associated with multiple sclerosis severity and response to treatment

Area of Science:

• Genetics
• Neurology
• Precision Medicine

Background:

• Predicting multiple sclerosis (MS) progression and treatment response is difficult.
• Genetic risk variants can define endophenotypes in complex diseases, but this hasn't been applied to MS.

Purpose of the Study:

• To apply genomic risk score clustering to identify MS subtypes.
• To investigate if these subtypes correlate with disease progression and treatment response.

Main Methods:

• Unsupervised hierarchical clustering of genomic risk scores in two MS cohorts (Welsh n=1455, NBB-MS n=272).
• Survival analysis used to assess time to Expanded Disability Status Scale (EDSS) milestones.
• Analysis of T2 lesion load and treatment effects within identified clusters.

Main Results:

• Three distinct genomic clusters were identified, with Cluster 1 showing slower progression to EDSS 6 and 8.
• Cluster 1 demonstrated a significant delay in disability milestones compared to Clusters 2 and 3.
• Cluster 2 exhibited increased T2 lesion load and showed a treatment benefit from disease-modifying therapies, unlike Clusters 1 and 3.

Conclusions:

• Genomic clustering effectively identifies clinically relevant MS subtypes.
• These subtypes possess distinct prognoses and differential responses to treatment.
• This strategy shows promise for personalized medicine approaches in managing MS.