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Integrated multi-omics analysis identifies candidate eRNA-associated signatures shared between osteoarthritis and
Danni Huang1, Junying Wu2, Jinhua Chen3
1Division of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.
Background:
Osteoarthritis (OA) and type 2 diabetes mellitus (T2DM) frequently coexist and share inflammatory and metabolic disturbances, but the immune-epigenetic features that may overlap between these conditions remain incompletely defined. Enhancer RNAs (eRNAs) are increasingly recognized as regulators of enhancer activity and transcriptional programs, whereas eRNA-associated signatures shared between OA-related and T2DM-related datasets remain largely unexplored.
Methods:
Transcriptomic datasets from OA joint tissues and controls (63 OA, 35 controls) were analyzed together with an independent T2DM dataset of CD14+ monocytes (5 T2DM, 5 controls) to explore overlapping molecular features across distinct disease-related contexts. Differential expression analysis, exploratory Weighted Gene Co-expression Network Analysis (WGCNA), CIBERSORT-based estimation, and pathway analyses were used to prioritize eRNA-associated features, transcription factors (TFs), candidate genes, and immune-associated transcriptional patterns. Public ATAC-seq, ChIP-seq, and scRNA-seq datasets, together with a high-glucose stress model in rat chondrocytes, were used to provide epigenomic, cellular, and preliminary experimental context for the candidate associations.
Results:
We identified 473 annotated dysregulated eRNA-associated features in OA, with associated genes enriched in skeletal development, extracellular matrix remodeling, and PI3K-Akt signaling. CIBERSORT-based and pathway analyses suggested immune-associated transcriptional alterations and inflammatory pathway activation in OA. Integrative analysis prioritized TOB1 as a candidate eRNA-associated feature related to JUN, CCNL1, and inflammatory signaling within an inferred correlation-based network. Public ATAC-seq, ChIP-seq, and scRNA-seq datasets provided supportive epigenomic and cellular context for these candidate associations. Comparison with the T2DM monocyte dataset showed overlapping TNF-α/NF-κB and MAPK-related pathway alterations, with CCNL1 identified as a commonly downregulated candidate gene. In vitro, high-glucose stress was accompanied by reduced TOB1, JUN, and CCNL1 protein levels and increased TNF-α expression in chondrocytes.
Conclusion:
TOB1 was prioritized as a candidate eRNA-associated signal related to JUN, CCNL1, and inflammatory signaling across OA-related and T2DM-related datasets. These findings provide a bioinformatics-driven and correlation-based framework supported by public epigenomic context and preliminary in vitro data, offering potential directions for future studies of immune-metabolic overlap between OA and T2DM.
