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. 2017 Aug 18;7:8727. doi: 10.1038/s41598-017-09301-2

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Receiver operating characteristic (ROC) curves for the multivariate logistic regression analysis for the three risk models. Roc curve analysis was performed with the data of probability predicted by the logistic regression models for each individual of the sample, in each of the models. The area under the ROC curve (AUC) is the discriminating power of the performed model. ROC curve analysis of: (A) Risk of susceptibility to MS. The predictive capacity was increased when LINE-1 methylation levels were included. The model 2, including LINE-1 methylation levels, had a larger AUC and a higher statistical significance than model 1 including age and gender, exclusively. (B) Risk of clinical activity in MS patients undergoing IFNβ therapy. LINE-1 methylation levels had a significant predictive capacity.