Network-based enrichment analysis of differentially methylated regions in pediatric multiple sclerosis reveals key regulators of immune response and Epstein-Barr virus infection
Abstract
Data di Pubblicazione:
2025
Citazione:
Network-based enrichment analysis of differentially methylated regions in pediatric multiple sclerosis reveals key regulators of immune response and Epstein-Barr virus infection / A. Corona, M. Tosi, A. Zollo, N. Barizzone, N. Pomella, M. Simone, A. Protti, A. Berardinelli, A. Gallo, C. Canavese, D. Vecchio, E. Cocco, L. Moiola, M.Z. Conti, M. Borghi, M. Viri, A. Mingione, P. Annovazzi, O. Oddo, R. Lanzillo, S. Rasia, S.M. Bova, V. Torri Clerici, S. Sotgiu, A. Priori, M. Troiano, M.P. Amato, R. Bergamaschi, S. Pilotto, C. Pozzilli, S. Cottone, G. Santangelo, G. De Luca, M. Pugliatti, A. Ghezzi, S. D’Alfonso, F. Martinelli Boneschi. - In: MULTIPLE SCLEROSIS. - ISSN 1352-4585. - 31:3 suppl. 41(2025), pp. P632.550-P632.551. ( 41. ECTRIMS Barcelona 2025).
Abstract:
Introduction: Pediatric multiple sclerosis (PedMS) poses unique challenges in diagnosis and understanding the underlying disease mechanisms, given its complexity and the importance of early identification of the involved factors.
Objectives/Aims: Leveraging epigenetic signatures, specifically highly informative differentially methylated regions (DMRs), that permit to identify genes involved in transcriptional regulation and disease, this study aims to elucidate the epigenetic mechanisms mediating the interplay between genetic susceptibility and environmental factors in PedMS onset, employing a network-based approach to investigate joint association signals.
Methods: This multi-center retrospective study included 175 Italian subjects (122 PedMS patients and 53 healthy controls matched for age, sex, and ethnicity) from the PEDIGREE study group. Genomic DNA was extracted from peripheral blood. DNA methylation was analyzed using the Infinium Methylation EPIC Array v2. Bioinformatic analysis was performed in R environment and DMRs were identified using the DMRCate method. Using the NDEx tool, we performed a sub-network detection analysis, projecting genes overlapping with DMRs onto the high-confidence (combined score >95%) STRING v12 reference interactome. Specifically, we explored the network using the one-step neighborhood method to identify modules defined by the group of nodes connected to the query term(s) and all edges between these nodes. The results were imported into the Cytoscape 3.10.3 environment, where the g:Profiler tool was used to perform gene set enrichment analysis (GSEA) of the sub-network nodes against the Gene Ontology Biological Process (GOBP) and KEGG databases.
Results: Analyses identified 55 DMRs, overlapping with 91 genes, 33 of which were included in downstream analyses. NDEx revealed a sub-network of 165 nodes and 680 edges. GSEA indicated “Epstein-Barr virus infection” as the top ranked term (KEGG, FDR adjusted p-value = 6.38*10-40). Other enriched terms among the top ten best ranking were “immune system process” (GOBP, FDR adjusted p-value = 1.63*10-32) and “positive regulation of lymphocyte activation” (GOBP, FDR adjusted p-value = 1.26*10-20).
Conclusion: Our findings highlight the potential role of epigenetic modifications, particularly DMRs, in mediating the complex interplay between genetic predisposition and environmental triggers, such as Epstein-Barr virus infection, in the onset of PedMS in this Italian cohort. The identified sub-network and enriched biological processes underscore the involvement of immune system dysregulation and lymphocyte activation in the disease pathogenesis.
Objectives/Aims: Leveraging epigenetic signatures, specifically highly informative differentially methylated regions (DMRs), that permit to identify genes involved in transcriptional regulation and disease, this study aims to elucidate the epigenetic mechanisms mediating the interplay between genetic susceptibility and environmental factors in PedMS onset, employing a network-based approach to investigate joint association signals.
Methods: This multi-center retrospective study included 175 Italian subjects (122 PedMS patients and 53 healthy controls matched for age, sex, and ethnicity) from the PEDIGREE study group. Genomic DNA was extracted from peripheral blood. DNA methylation was analyzed using the Infinium Methylation EPIC Array v2. Bioinformatic analysis was performed in R environment and DMRs were identified using the DMRCate method. Using the NDEx tool, we performed a sub-network detection analysis, projecting genes overlapping with DMRs onto the high-confidence (combined score >95%) STRING v12 reference interactome. Specifically, we explored the network using the one-step neighborhood method to identify modules defined by the group of nodes connected to the query term(s) and all edges between these nodes. The results were imported into the Cytoscape 3.10.3 environment, where the g:Profiler tool was used to perform gene set enrichment analysis (GSEA) of the sub-network nodes against the Gene Ontology Biological Process (GOBP) and KEGG databases.
Results: Analyses identified 55 DMRs, overlapping with 91 genes, 33 of which were included in downstream analyses. NDEx revealed a sub-network of 165 nodes and 680 edges. GSEA indicated “Epstein-Barr virus infection” as the top ranked term (KEGG, FDR adjusted p-value = 6.38*10-40). Other enriched terms among the top ten best ranking were “immune system process” (GOBP, FDR adjusted p-value = 1.63*10-32) and “positive regulation of lymphocyte activation” (GOBP, FDR adjusted p-value = 1.26*10-20).
Conclusion: Our findings highlight the potential role of epigenetic modifications, particularly DMRs, in mediating the complex interplay between genetic predisposition and environmental triggers, such as Epstein-Barr virus infection, in the onset of PedMS in this Italian cohort. The identified sub-network and enriched biological processes underscore the involvement of immune system dysregulation and lymphocyte activation in the disease pathogenesis.
Tipologia IRIS:
01 - Articolo su periodico
Elenco autori:
A. Corona, M. Tosi, A. Zollo, N. Barizzone, N. Pomella, M. Simone, A. Protti, A. Berardinelli, A. Gallo, C. Canavese, D. Vecchio, E. Cocco, L. Moiola, M.Z. Conti, M. Borghi, M. Viri, A. Mingione, P. Annovazzi, O. Oddo, R. Lanzillo, S. Rasia, S.M. Bova, V. Torri Clerici, S. Sotgiu, A. Priori, M. Troiano, M.P. Amato, R. Bergamaschi, S. Pilotto, C. Pozzilli, S. Cottone, G. Santangelo, G. De Luca, M. Pugliatti, A. Ghezzi, S. D’Alfonso, F. Martinelli Boneschi
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