Baseline Neuroinflammation Stratifies TSPO-PET Response to Disease-Modifying Therapy in Multiple Sclerosis

To investigate which baseline clinical and imaging characteristics best predict TSPO-PET-measurable reduction in glial activation following treatment of multiple sclerosis (MS), to utilize this information for designing more efficient biomarker-based clinical trials targeting glial activation.

This study pooled data from 47 pwMS treated with various approved disease-modifying therapies and 18 untreated pwMS with TSPO-PET imaging before and after. Therapeutic response was quantified using [¹¹C]PK11195 distribution volume ratio and percentage of active voxels in seven brain regions. Variables predicting therapeutic response were identified using linear mixed-effect models. Power calculation was used to estimate the required sample size for predictor-enriched cohorts.

High baseline TSPO binding in the white matter (HOT-PET) was identified as the best predictor for reduction in glial activation following treatment in 6 of 14 (43%) PET variables. Internal validation confirmed that treated HOT-PET patients showed enhanced therapeutic response compared with non-HOT-PET patients in 9 of 14 (64%) PET variables. The percentage of active voxels in the white matter was the best PET variable at capturing a significant therapeutic effect, with a Cohen's d effect size of -0.779 (95% confidence interval -1.332; -0.207). In this cohort, enrichment for HOT-PET patients markedly reduced the sample size required to show a positive treatment effect.

HOT-PET patients are more likely to benefit from neuroinflammation-targeting treatments compared to non-HOT-PET patients. Accordingly, enriching trial cohorts for individuals with greater neuroinflammatory burden could improve statistical power and reduce the required number of participants in trials targeting harmful glial activation in MS.