Dataset Information

Teriflunomide slows BVL in relapsing MS: A reanalysis of the TEMSO MRI data set using SIENA.

ABSTRACT: To assess, using structural image evaluation using normalization of atrophy (SIENA), the effect of teriflunomide, a once-daily oral immunomodulator, on brain volume loss (BVL) in patients with relapsing forms of MS enrolled in the phase 3 TEMSO study.TEMSO MR scans were analyzed (study personnel masked to treatment allocation) using SIENA to assess brain volume changes between baseline and years 1 and 2 in patients treated with placebo or teriflunomide. Treatment group comparisons were made via rank analysis of covariance.Data from 969 patient MRI visits were included in this analysis: 808 patients had baseline and year 1 MRI; 709 patients had baseline and year 2 MRI. Median percentage BVL from baseline to year 1 and year 2 for placebo was 0.61% and 1.29%, respectively, and for teriflunomide 14 mg, 0.39% and 0.90%, respectively. BVL was lower for teriflunomide 14 mg vs placebo at year 1 (36.9% relative reduction, p = 0.0001) and year 2 (30.6% relative reduction, p = 0.0001). Teriflunomide 7 mg was also associated with significant reduction in BVL vs placebo over the 2-year study. The significant effects of teriflunomide 14 mg on BVL were observed in both patients with and without on-study disability worsening.The significant reduction of BVL vs placebo over 2 years achieved with teriflunomide is consistent with its effects on delaying disability worsening and suggests a neuroprotective potential.Class II evidence shows that teriflunomide treatment significantly reduces BVL over 2 years vs placebo.NCT00134563.

SUBMITTER: Radue EW

PROVIDER: S-EPMC5550381 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Teriflunomide slows BVL in relapsing MS: A reanalysis of the TEMSO MRI data set using SIENA.

Radue Ernst-Wilhelm EW Sprenger Till T Gaetano Laura L Mueller-Lenke Nicole N Cavalier Steve S Thangavelu Karthinathan K Panzara Michael A MA Donaldson Jessica E JE Woodward Fiona M FM Wuerfel Jens J Wolinsky Jerry S JS Kappos Ludwig L

Neurology(R) neuroimmunology & neuroinflammation 20170809 5

<h4>Objective</h4>To assess, using structural image evaluation using normalization of atrophy (SIENA), the effect of teriflunomide, a once-daily oral immunomodulator, on brain volume loss (BVL) in patients with relapsing forms of MS enrolled in the phase 3 TEMSO study.<h4>Methods</h4>TEMSO MR scans were analyzed (study personnel masked to treatment allocation) using SIENA to assess brain volume changes between baseline and years 1 and 2 in patients treated with placebo or teriflunomide. Treatmen ...[more]

PMID: 28828394

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Project description:One of our new major finding among the genes that contributes to MS susceptibility is ICSBP1. The so called disease modifying therapies like interferon-beta (IFN-β), possibly acting on the peripheral T-cells, reduce the disease activity and the clinical progression, with a MRI-detectable effect in preventing lesion burden and cerebral atrophy development in RR-MS. It suggests a critical role of peripheral blood mononuclear cells (PBMCs) immune response and modulation in developing inflammation in the brain. We tested the hypothesis that the genetic effect of the susceptible allele ICSBP1 can impact the gene expression profile of molecules belonging to the interferon pathway. We therefore interrogated the PBMC for changes in gene expression profile. We correlate those changes with the minor allele frequency for ICSBP1, performing independent quantitative trait analysis for each treatment category. Expression Quantitative Trait Loci Association with a p value < 0.05 have been used in follow up analysis. The regression coefficient of the Quantitative trait association represents the degree of correlation between the gene expression for each interrogated target gene and the minor allele frequency of the SNP for our gene of interest. This coefficient has been used as input in the subsequent Gene Set Enrichment Analysis performed in a pre-ranked approach. The resulting GSEA-SNP method rests on the assumption that SNPs underlying a disease phenotype might affect genes constituting a signaling pathway or genes with a common regulation. Therefore, GSEA-SNP can facilitate the identification of pathways or of underlying biological mechanisms. We used microarrays to capture gene expression profile of untreated subjects and of subjects under disease modyfing treatment (Interferon Beta and Glatiramer Acetate), in order to correlate gene expression and genotype data and in order to identify sets of genes specifically regulated in the different treatment categories.

Dataset Information

Teriflunomide slows BVL in relapsing MS: A reanalysis of the TEMSO MRI data set using SIENA.

Publications

Teriflunomide slows BVL in relapsing MS: A reanalysis of the TEMSO MRI data set using SIENA.

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