ArticleMolecular medicine (Cambridge, Mass.)2025
Stochastic epigenetic mutation profiles as biomarkers of clinical activity in juvenile idiopathic arthritis: a multi-omic machine learning approach for gene prioritization.
Article in Molecular medicine (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundJuvenile idiopathic arthritis (JIA) is a rare autoimmune disease arising from a complex interplay between genetic and environmental factors. Epigenetic modifications such as DNA methylation (DNAm) have been described as potential mediators in gene-environment interactions, contributing to immune system dysregulation. Emerging evidence suggests that DNAm profiles also predict therapeutic responses in autoimmune diseases. This study aims to identify epigenetic biomarkers and epigenetic-driven gene expression changes associated with JIA clinical activity.
methodsWe reanalyzed a publicly available dataset of 44 JIA patients, with whole-genome DNAm and gene expression from CD4 + T cells measured at two points: at anti-TNF therapy withdrawal (T
resultsWe found a higher mutation load in NO ID than ID patients, both at T
conclusionsWe described a significant association of epigenetic mutations with JIA clinical activity, indicating that epigenetic changes might precede clinical symptoms and may serve as biomarkers for early disease monitoring. Further, our results shed light on biomolecular mechanisms of JIA, supporting the development of more effective treatments.
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