A novel gene signature for forecasting time to next relapse in multiple sclerosis using peripheral blood mononuclear cells.

ABSTRACT:

Aim

The purpose of this research study was to develop and validate a gene signature based on peripheral blood mononuclear cells (PBMCs) for predicting the time to the next relapse in multiple sclerosis (MS).

Methods

The GSE15245 dataset (N = 94) was divided into a training set (N = 65) and a testing set (N = 29). First, the training set was analyzed using weighted gene co-expression network analysis (WGCNA) to identify key modules that were highly correlated with the timing of the next acute relapse. Subsequently, the hub genes within these key modules were subjected to univariate Cox regression analysis, and genes related to the recurrence time of MS were identified. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to refine the extraction

SUBMITTER: Zhang H 

PROVIDER: S-EPMC12210466 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature