1. Transcriptomic network analysis reveals key drivers of response to anti-TNF biologics in patients with rheumatoid arthritis.
- Author
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Yu CY, Lee HS, Joo YB, Cho SK, Choi CB, Sung YK, Kim TH, Jun JB, Yoo DH, Bae SC, Kim K, and Bang SY
- Subjects
- Humans, Female, Male, Middle Aged, Tumor Necrosis Factor-alpha antagonists & inhibitors, Gene Expression Profiling, Adult, Treatment Outcome, Arthritis, Rheumatoid drug therapy, Arthritis, Rheumatoid genetics, Antirheumatic Agents therapeutic use, Transcriptome, Biological Products therapeutic use
- Abstract
Objective: Anti-TNF biologics have been widely used to ameliorate disease activity in patients with RA. However, a large fraction of patients show a poor response to these agents. Moreover, no clinically applicable predictive biomarkers have been established. This study aimed to identify response-associated biomarkers using longitudinal transcriptomic data in two independent RA cohorts., Methods: RNA sequencing data from peripheral blood cell samples of Korean and Caucasian RA cohorts before and after initial treatment with anti-TNF biologics were analysed to assess treatment-induced expression changes that differed between highly reliable excellent responders and null responders. Weighted correlation network, immune cell composition, and key driver analyses were performed to understand response-associated transcriptomic networks and cell types and their correlation with disease activity indices., Results: In total, 305 response-associated genes showed significantly different treatment-induced expression changes between excellent and null responders. Co-expression network construction and subsequent key driver analysis revealed that 41 response-associated genes played a crucial role as key drivers of transcriptomic alteration in four response-associated networks involved in various immune pathways: type I IFN signalling, myeloid leucocyte activation, B cell activation, and NK cell/lymphocyte-mediated cytotoxicity. Transcriptomic response scores that we developed to estimate the individual-level degree of expression changes in the response-associated key driver genes were significantly correlated with the changes in clinical indices in independent patients with moderate or ambiguous response outcomes., Conclusion: This study provides response-specific treatment-induced transcriptomic signatures by comparing the transcriptomic landscape between patients with excellent and null responses to anti-TNF drugs at both gene and network levels., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
- Published
- 2024
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