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

Area of Science:

• Neuroimaging
• Neuroinflammation
• Clinical Trials

Background:

• Multiple sclerosis (MS) is characterized by neuroinflammation involving glial activation.
• Targeting glial activation is a key therapeutic strategy for MS.
• Predictive biomarkers are needed to optimize clinical trial design and patient selection.

Purpose of the Study:

• Identify baseline clinical and imaging characteristics that predict treatment-induced reduction in glial activation in MS.
• Utilize these predictors to design more efficient biomarker-based clinical trials.

Main Methods:

• Pooled data from 47 treated and 18 untreated MS patients with baseline and follow-up TSPO-PET imaging.
• Quantified therapeutic response using [¹¹C]PK11195 distribution volume ratio and percentage of active voxels.
• Identified predictive variables using linear mixed-effect models and power calculations for sample size estimation.

Main Results:

• High baseline TSPO binding in white matter (HOT-PET) was the strongest predictor of reduced glial activation.
• HOT-PET patients demonstrated significantly enhanced therapeutic response in multiple PET variables.
• Percentage of active voxels in white matter best captured treatment effect (Cohen's d = -0.779).
• Enriching cohorts with HOT-PET patients markedly reduced required sample size.

Conclusions:

• Patients with high baseline neuroinflammatory burden (HOT-PET) are more likely to benefit from neuroinflammation-targeting MS treatments.
• Enriching clinical trial cohorts with individuals showing greater neuroinflammatory burden can improve statistical power.
• This approach can reduce participant numbers in trials targeting glial activation in MS.