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

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...

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Detalles Bibliográficos
Autores: Aterido, Adrià|||0000-0003-1810-410X, Cañete, Juan D.|||0000-0003-2606-0573, Tornero, Jesús, Blanco-García, F.J.|||0000-0001-9821-7635, Fernández-Gutiérrez, Benjamín, Pérez-García, Carolina|||0000-0002-6695-6406, Alperi-López, Mercedes, Olivé Marqués, Alejandro|||0000-0002-6707-8043, Corominas, Hèctor|||0000-0002-7738-6787, Martínez-Taboada, Víctor, González, Isidoro, Fernández-Nebro, Antonio|||0000-0002-2962-9844, Erra Duran, Alba|||0000-0001-7806-1098, López Lasanta, María|||0000-0002-8462-8406, López-Corbeto, Mireia|||0000-0003-1166-1456, Palau, Núria, Marsal, Sara|||0000-0001-5515-3854, Julià Cano, Antonio|||0000-0001-6064-3620
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:223117
Acceso en línea:https://ddd.uab.cat/record/223117
https://dx.doi.org/urn:doi:10.3389/fimmu.2019.01459
Access Level:acceso abierto
Palabra clave:Rheumatoid arthritis
Genomics
Transcriptomics
Multi-omics association analysis
Anti-TNF therapy
Descripción
Sumario: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.