Dataset Information

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France.

ABSTRACT: We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39-3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18-0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon.

SUBMITTER: Sormani MP

PROVIDER: S-EPMC8351392 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France.

Sormani Maria Pia MP Salvetti Marco M Labauge Pierre P Schiavetti Irene I Zephir Helene H Carmisciano Luca L Bensa Caroline C De Rossi Nicola N Pelletier Jean J Cordioli Cinzia C Vukusic Sandra S Moiola Lucia L Kerschen Philippe P Radaelli Marta M Théaudin Marie M Immovilli Paolo P Casez Olivier O Capobianco Marco M Ciron Jonathan J Trojano Maria M Stankoff Bruno B Créange Alain A Tedeschi Gioacchino G Clavelou Pierre P Comi Giancarlo G Thouvenot Eric E Battaglia Mario Alberto MA Moreau Thibault T Patti Francesco F De Sèze Jérôme J Louapre Celine C

Annals of clinical and translational neurology 20210707 8

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39-3.02, p < 0.001) ...[more]

PMID: 34240579

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Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.

Dataset Information

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France.

Publications

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France.

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