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A combined transcriptomic and genomic analysis identifies a gene signature associated with the response to anti-TNF therapy in rheumatoid arthritis

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http://hdl.handle.net/2183/25159
Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España
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Title
A combined transcriptomic and genomic analysis identifies a gene signature associated with the response to anti-TNF therapy in rheumatoid arthritis
Author(s)
Aterido, Adriá
Cañete, Juan D.
Tornero, Jesús
Blanco García, Francisco J
Fernández-Gutiérrez, Benjamín
Pérez, Carolina
Alperi-López, Mercedes
Olivé, Alex
Corominas, Héctor
Martínez-Taboada, Víctor
González, Isidoro
Fernández-Nebro, Antonio
Erra, Alba
López Lasanta, María
López-Corbeto, Mireia
Palau, Núria
Juliá, Antonio
Marsal, Sara
Date
2019-07-02
Citation
Aterido A, Cañete JD, Tornero J, Blanco F, Fernández-Gutiérrez B, Pérez C, et al. A combined transcriptomic and genomic analysis identifies a gene signature associated with the response to anti-TNF therapy in rheumatoid arthritis. Front Immunol. 2019;10
Abstract
[Abstract] Background: Rheumatoid arthritis (RA) is the most frequent autoimmune disease involving the joints. Although anti-TNF therapies have proven effective in the management of RA, approximately one third of patients do not show a significant clinical response. The objective of this study was to identify new genetic variation associated with the clinical response to anti-TNF therapy in RA. Methods: We performed a sequential multi-omic analysis integrating different sources of molecular information. First, we extracted the RNA from synovial biopsies of 11 RA patients starting anti-TNF therapy to identify gene coexpression modules (GCMs) in the RA synovium. Second, we analyzed the transcriptomic association between each GCM and the clinical response to anti-TNF therapy. The clinical response was determined at week 14 using the EULAR criteria. Third, we analyzed the association between the GCMs and anti-TNF response at the genetic level. For this objective, we used genome-wide data from a cohort of 348 anti-TNF treated patients from Spain. The GCMs that were significantly associated with the anti-TNF response were then tested for validation in an independent cohort of 2,706 anti-TNF treated patients. Finally, the functional implication of the validated GCMs was evaluated via pathway and cell type epigenetic enrichment analyses. Results: A total of 149 GCMs were identified in the RA synovium. From these, 13 GCMs were found to be significantly associated with anti-TNF response (P < 0.05). At the genetic level, we detected two of the 13 GCMs to be significantly associated with the response to adalimumab (P = 0.0015) and infliximab (P = 0.021) in the Spain cohort. Using the independent cohort of RA patients, we replicated the association of the GCM associated with the response to adalimumab (P = 0.0019). The validated module was found to be significantly enriched for genes involved in the nucleotide metabolism (P = 2.41e-5) and epigenetic marks from immune cells, including CD4+ regulatory T cells (P = 0.041). Conclusions: These findings show the existence of a drug-specific genetic basis for anti-TNF response, thereby supporting treatment stratification in the search for response biomarkers in RA.
Keywords
Rheumatoid arthritis
Genomics
Transcriptomics
Multi-omics association analysis
Anti-TNF therapy
 
Editor version
https://doi.org/10.3389/fimmu.2019.01459
Rights
Atribución 3.0 España
ISSN
1664-3224

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