Dataset Information

Search for specific biomarkers of IFN? bioactivity in patients with multiple sclerosis.

ABSTRACT: Myxovirus A (MxA), a protein encoded by the MX1 gene with antiviral activity, has proven to be a sensitive measure of IFN? bioactivity in multiple sclerosis (MS). However, the use of MxA as a biomarker of IFN? bioactivity has been criticized for the lack of evidence of its role on disease pathogenesis and the clinical response to IFN?. Here, we aimed to identify specific biomarkers of IFN? bioactivity in order to compare their gene expression induction by type I IFNs with the MxA, and to investigate their potential role in MS pathogenesis. Gene expression microarrays were performed in PBMC from MS patients who developed neutralizing antibodies (NAB) to IFN? at 12 and/or 24 months of treatment and patients who remained NAB negative. Nine genes followed patterns in gene expression over time similar to the MX1, which was considered the gold standard gene, and were selected for further experiments: IFI6, IFI27, IFI44L, IFIT1, HERC5, LY6E, RSAD2, SIGLEC1, and USP18. In vitro experiments in PBMC from healthy controls revealed specific induction of selected biomarkers by IFN? but not IFN?, and several markers, in particular USP18 and HERC5, were shown to be significantly induced at lower IFN? concentrations and more selective than the MX1 as biomarkers of IFN? bioactivity. In addition, USP18 expression was deficient in MS patients compared with healthy controls (p?=?0.0004). We propose specific biomarkers that may be considered in addition to the MxA to evaluate IFN? bioactivity, and to further explore their implication in MS pathogenesis.

SUBMITTER: Malhotra S

PROVIDER: S-EPMC3160307 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Search for specific biomarkers of IFNβ bioactivity in patients with multiple sclerosis.

Malhotra Sunny S Bustamante Marta F MF Pérez-Miralles Francisco F Rio Jordi J Ruiz de Villa Mari Carmen MC Vegas Esteban E Nonell Lara L Deisenhammer Florian F Fissolo Nicolás N Nurtdinov Ramil N RN Montalban Xavier X Comabella Manuel M

PloS one 20110823 8

Myxovirus A (MxA), a protein encoded by the MX1 gene with antiviral activity, has proven to be a sensitive measure of IFNβ bioactivity in multiple sclerosis (MS). However, the use of MxA as a biomarker of IFNβ bioactivity has been criticized for the lack of evidence of its role on disease pathogenesis and the clinical response to IFNβ. Here, we aimed to identify specific biomarkers of IFNβ bioactivity in order to compare their gene expression induction by type I IFNs with the MxA, and to investi ...[more]

PMID: 21886806

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Project description:Background: Neutralizing anti-drug antibodies (ADA) can greatly reduce the efficacy of biopharmaceuticals used to treat patients with multiple sclerosis (MS). However, the biological factors pre-disposing an individual to develop ADA are poorly characterized. Thus, there is an unmet clinical need for biomarkers to predict the development of immunogenicity, and subsequent treatment failure. Up to 35% of MS patients treated with beta interferons (IFNβ) develop ADA. Here we use machine learning to predict immunogenicity against IFNβ utilizing serum metabolomics data. Methods: Serum samples were collected from 89 MS patients as part of the ABIRISK consortium-a multi-center prospective study of ADA development. Metabolites and ADA were quantified prior to and after IFNβ treatment. Thirty patients became ADA positive during the first year of treatment (ADA+). We tested the efficacy of six binary classification models using 10-fold cross validation; k-nearest neighbors, decision tree, random forest, support vector machine and lasso (Least Absolute Shrinkage and Selection Operator) logistic regression with and without interactions. Results: We were able to predict future immunogenicity from baseline metabolomics data. Lasso logistic regression with/without interactions and support vector machines were the most successful at identifying ADA+ or ADA- cases, respectively. Furthermore, patients who become ADA+ had a distinct metabolic response to IFNβ in the first 3 months, with 29 differentially regulated metabolites. Machine learning algorithms could also predict ADA status based on metabolite concentrations at 3 months. Lasso logistic regressions had the greatest proportion of correct classifications [F1 score (accuracy measure) = 0.808, specificity = 0.913]. Finally, we hypothesized that serum lipids could contribute to ADA development by altering immune-cell lipid rafts. This was supported by experimental evidence demonstrating that, prior to IFNβ exposure, lipid raft-associated lipids were differentially expressed between MS patients who became ADA+ or remained ADA-. Conclusion: Serum metabolites are a promising biomarker for prediction of ADA development in MS patients treated with IFNβ, and could provide novel insight into mechanisms of immunogenicity.

Dataset Information

Search for specific biomarkers of IFN? bioactivity in patients with multiple sclerosis.

Publications

Search for specific biomarkers of IFNβ bioactivity in patients with multiple sclerosis.

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