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Transcriptome data predicts long-term outcomes in untreated PPMS patients

AAN 2023
According to a recent study, analysing RNA sequences in peripheral blood can accurately predict disability progression and brain volume change in patients with untreated primary progressive multiple sclerosis (PPMS). Predicting severe disease outcomes can help to identify those PPMS patients who could benefit most from early intervention.

Until now, predicting severe disease progression in untreated PPMS patients has proven to be a challenging task. Aiming to develop a blood transcriptome-based prognostic model, the presenting Israelian group exploited their biobank of peripheral blood samples of patients with PPMS who were included in the placebo arm of the clinical ORATORIO trial (NCT01194570), which evaluated ocrelizumab in PPMS. RNA samples were sequenced on the Illumina NovaSeq S2. The researchers then predicted 12-weeks confirmed disability progression (12W CDP) during 120 weeks of follow-up by applying a 2-level cross-validation algorithm. This analysis also allowed them to predict the percentage of patients with brain volume change at weeks 24, 48, and 120.

The researchers analysed RNA samples from 65 patients with PPMS. The median age was 44 years, 21 were women, and the Expanded Disability Status Scale (EDSS) at baseline was 4.5. Of these 65 patients, 24 (37%) had 12W CDP. This was correctly classified in 90.8% of patients (95% CI 80.6–100.0) with a 10-gene classifier. At week 24, 63% of patients presented with brain volume change, followed by 57% at week 48, and 64% at week 120. Brain volume change was correctly classified in 74.0% (65.1%–83.0%), 84.0%, (75.1%–93.1%) and 82.9% (73.8%–95.6%) at weeks 24, 48, and 120, respectively.

  1. Gurevich M, et al. Peripheral Blood Gene Expression Transcriptional Profiling Predicts Disease Progression in Primary Progressive Multiple Sclerosis. ES1.010, AAN 2023 Annual Meeting, 22–27 April, Boston, USA.

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