A Combined Transcriptomic and Genomic Analysis Identifies a Gene Signature Associated With the Response to Anti-TNF Therapy in Rheumatoid Arthritis
Aterido, Adria; Canete, Juan D; Tornero, Jesus; BLANCO GARCIA, FRANCISCO JAVIER; Fernandez-Gutierrez, Benjamin; Perez, Carolina; Alperi-Lopez, Mercedes; Olive, Alex; Corominas, Hector; Martinez-Taboada, Victor; Gonzalez, Isidoro; Fernandez-Nebro, Antonio; Erra, Alba; Lopez-Lasanta, Maria; Lopez Corbeto, Mireia; Palau, Nuria; Marsal, Sara; Julia, Antonio
Identificadores
Identificadores
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Fecha de publicación
2019Título de revista
Frontiers in Immunology
Tipo de contenido
Artigo
DeCS
resultado del tratamiento | membrana sinovial | transcriptoma | factor de necrosis tumoral alfa | biopsia | humanos | estudio de asociación genómica completa | estudios de cohortes | antirreumáticos | redes génicas reguladoras | artritisMeSH
Tumor Necrosis Factor-alpha | Humans | Treatment Outcome | Antirheumatic Agents | Genome-Wide Association Study | Transcriptome | Biopsy | Synovial Membrane | Arthritis | Cohort Studies | Gene Regulatory NetworksResumen
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.