Stochastic epigenetic mutation profiles as biomarkers of clinical activity in juvenile idiopathic arthritis: a multi-omic machine learning approach for gene prioritization
We 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.
Authors
- Anna L. Duncan (ORCID: https://orcid.org/0000-0001-9873-4552)
- Boris Novakovic (ORCID: https://orcid.org/0000-0002-5623-9008)
- Jane Munro (ORCID: https://orcid.org/0000-0003-3018-2194)
- Alessandro Consolaro (ORCID: https://orcid.org/0000-0002-0065-7614)
- Giacomo Cavalca (ORCID: https://orcid.org/0000-0003-3622-3516)
- Angelo Ravelli (ORCID: https://orcid.org/0000-0001-9658-0385)
- Paolo Uva (ORCID: https://orcid.org/0000-0002-9524-8492)
- Davide Cangelosi (ORCID: https://orcid.org/0000-0002-6010-5619)
- Michela Vergani
- Giovanni Fiorito (ORCID: https://orcid.org/0000-0002-7651-5452)
- Marco Gattorno
Institutions
- Royal Children's Hospital (AU)
- The University of Melbourne (AU)
- Istituto Giannina Gaslini (IT)
- Murdoch Children's Research Institute (AU)
- Istituti di Ricovero e Cura a Carattere Scientifico (IT)
- University of Bologna (IT)
Publication Details
- Journal
- Molecular Medicine
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1186/s10020-025-01348-6
- Primary Topic
- Autoimmune and Inflammatory Disorders Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministero della Salute