TSPO-Detectable Chronic Active Lesions Predict Disease Progression in Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: In the multiple sclerosis (MS) brain, chronic active lesions can be detected using MRI- and PET-based methods. In this study, we investigated whether the frequency of TSPO-PET-detectable chronic active lesions associates with disease progression measured using the Expanded Disability Status Scale (EDSS) at 5-year follow-up. METHODS: Chronic lesion-associated innate immune cell activation was evaluated using TSPO-PET in 82 patients with MS. Chronic lesions were categorized into rim-active, inactive, and overall active lesion subtypes based on innate immune cell activation patterns in the lesion core and at the 2-mm perilesional rim. Logistic regression was used to identify best predictors of progression. RESULTS: Twenty-one patients experienced disability progression during the follow-up. These patients had a significantly higher proportion of rim-active lesions (p < 0.001) and a significantly lower proportion of inactive lesions (p = 0.001) compared with nonprogressed patients. The results were similar in the patient group having no relapses during the follow-up (60 patients, 14 experienced progression). In logistic regression modeling, the categorized variable "patients with >10% rim-active lesions and ≤50% inactive lesions of all chronic lesions" predicted disease progression in the entire cohort (OR = 26.8, p < 0.001) and in the group free of relapses (OR = 34.8, p = 0.002). DISCUSSION: The results show that single TSPO-PET-based in vivo lesion phenotyping of chronic MS lesions provides a strong predictor for MS disease progression. This emphasizes the significance of chronic active lesions in disability accumulation in MS.

Toward Precision Phenotyping of Multiple Sclerosis.

The classification of multiple sclerosis (MS) has been established by Lublin in 1996 and revised in 2013. The revision includes clinically isolated syndrome, relapsing-remitting, primary progressive and secondary progressive MS, and has added activity (i.e., formation of white matter lesions or clinical relapses) as a qualifier. This allows for the distinction between active and nonactive progression, which has been shown to be of clinical importance. We propose that a logical extension of this classification is the incorporation of additional key pathological processes, such as chronic perilesional inflammation, neuroaxonal degeneration, and remyelination. This will distinguish MS phenotypes that may present as clinically identical but are driven by different combinations of pathological processes. A more precise description of MS phenotypes will improve prognostication and personalized care as well as clinical trial design. Thus, our proposal provides an expanded framework for conceptualizing MS and for guiding development of biomarkers for monitoring activity along the main pathological axes in MS.