Background/Purpose: This study aimed to identify shared and distinct gene and protein expression profiles associated with clinical features in rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and SLE with antiphospholipid syndrome (SLE+APS) patients, using integrated multimodal analyses.

Methods: Advanced computational approaches combined clinical data, transcriptomic profiles from peripheral blood mononuclear cells (RNA sequencing), and serum proteomic profiles (proximity extension assays) in 257 RA and 66 SLE patients (20 with SLE+APS). Transcriptomic data were processed and normalized, followed by gene set variation analysis (GSVA) for pathway-level changes. Unsupervised hierarchical clustering identified patient subgroups and gene modules. Correlation analyses explored associations between gene modules, inflammatory protein profiles, and clinical parameters.

Results: Clustering identified three clusters with unique gene expression patterns across 11 gene modules, reflecting different biological pathways. Clinically, C1 was linked to increased cardiovascular (CV) risk in RA and higher disease activity / renal involvement in SLE. C2 exhibited high disease activity and lung involvement in RA and increased CV risk in SLE. C3 showed an intermediate profile, with autoantibody positivity and significant renal involvement, thrombosis and abortions in SLE+APS.Molecularly, C2 had heightened activity in myeloid cells and inflammation; C1 and C3 displayed increased T and B cell activity. Integrin-mediated cell adhesion pathways were commonly altered. Proteomic analysis supported these findings, revealing the greatest inflammatory protein changes in C2. Correlation analyses revealed relationships among modules related to myeloid cell activity, cell adhesion, inflammation, and T-cell activation correlating with several cytokines and chemokines. Specifically, the IFN response module linked with high IFN-gamma, CXCL10, and MCP-2 levels, while cell adhesion modules connected to several chemokines. Reduced T and B cell activity correlated negatively with increased levels of inflammatory proteins, suggesting different sources of inflammation and immune dysfunction.Shared genomic modules correlating with clinical profiles included cell cycle regulation with disease activity in RA and SLE, integrin-mediated cell adhesion with CV risk in RA, and myeloid cell activity with CV risk in SLE. Distinct correlations included inflammatory networks and IFN response with disease activity in RA and CV risk in SLE, T cell activity negatively with activity in RA and B cell activity with lung involvement in RA.

Conclusion: Overall, our integrated analysis reveals distinct transcriptomic clusters and molecular heterogeneity in RA, and SLE, driven by inflammation and immune dysregulation. These findings highlight both shared and disease-specific molecular signatures associated with clinical manifestations, providing insights into disease mechanisms and potential therapeutic targets. Supported by EU/EFPIA IMI-JU 3TR, ISCIII (PI24/00959, CD21/00187, and RICOR-24/0007/0019), co-financed by the European Union, MINECO (RYC2021-033828-I/PID2022-141500OA-I00).

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/unravelling-transcriptomic-landscapes-in-rheumatoid-arthritis-and-systemic-lupus-erythematosus-shared-and-unique-molecular-signatures-related-to-relevant-clinical-features/