Integrating TSPO-PET imaging with metabolomics for enhanced prognostic accuracy in multiple sclerosis

Area of Science:

• Neuroscience
• Biomarker Discovery
• Medical Imaging

Background:

• Multiple sclerosis (MS) disease progression prediction remains a significant clinical challenge.
• Translocator protein (TSPO) positron emission tomography (PET) imaging detects glial activation, showing predictive value for MS progression.
• Nuclear magnetic resonance (NMR)-based metabolomics has previously distinguished MS subtypes.

Purpose of the Study:

• To investigate if combining TSPO imaging with metabolomics enhances the prediction of MS disease progression.
• To assess the predictive accuracy of individual and combined biomarkers for MS progression.

Main Methods:

• Blood samples from 87 MS patients were analyzed using serum metabolomics (NMR).
• Patients underwent TSPO-PET imaging with 11C-PK11195.
• Expanded Disability Status Scale (EDSS) was used to assess disability at baseline and 1-year follow-up.

Main Results:

• Higher TSPO availability correlated with increased EDSS scores.
• Serum metabolites glutamate, glutamine, and glucose individually predicted MS progression with accuracy comparable to TSPO-PET imaging (AUC 0.78).
• Combining serum metabolite data with TSPO-PET imaging significantly improved predictive power (AUC 0.98).

Conclusions:

• Measuring three specific serum metabolites is as effective as TSPO imaging for predicting MS progression.
• Integrating TSPO imaging with serum metabolite analysis substantially enhances predictive accuracy.
• This combined approach offers a simple, affordable, and accurate method for personalized MS management and clinical trial stratification.