Brief Report: The Role of Rare Protein‐Coding Variants in Anti–Tumor Necrosis Factor Treatment Response in Rheumatoid Arthritis
Year: 2016
Type: article
Study design: Observational Study
Abstract: Objective In many rheumatoid arthritis (RA) patients, disease is controlled with anti–tumor necrosis factor (anti‐TNF) biologic therapies. However, in a significant number of patients, the disease fails to respond to anti‐TNF therapy. We undertook the present study to examine the hypothesis that rare and low‐frequency genetic variants might influence response to anti‐TNF treatment. Methods We sequenced the coding region of 750 genes in 1,094 RA patients of European ancestry who were treated with anti‐TNF. After quality control, 690 genes were included in the analysis. We applied single‐variant association and gene‐based association tests to identify variants associated with anti‐TNF treatment response. In addition, given the key mechanistic role of TNF, we performed gene set analyses of 27 TNF pathway genes. Results We identified 14,420 functional variants, of which 6,934 were predicted as nonsynonymous 2,136 of which were further predicted to be “damaging.” Despite the fact that the study was well powered, no single variant or gene showed study‐wide significant association with change in the outcome measures disease activity or European League Against Rheumatism response. Intriguingly, we observed 3 genes, of 27 with nominal signals of association (P < 0.05), that were involved in the TNF signaling pathway. However, when we performed a rigorous gene set enrichment analysis based on association P value ranking, we observed no evidence of enrichment of association at genes involved in the TNF pathway (Penrichment = 0.15, based on phenotype permutations). Conclusion Our findings suggest that rare and low‐frequency protein‐coding variants in TNF signaling pathway genes or other genes do not contribute substantially to anti‐TNF treatment response in patients with RA.
Source: Arthritis & Rheumatology
DOI: 10.1002/art.39966
Authors: Jing Cui, Dorothee Diogo, Eli A. Stahl, Helena Canhao, Xavier Mariette, Jeffrey D. Greenberg, Yukinori Okada, Dimitrios A. Pappas, Robert S. Fulton, Paul P. Tak, Michael T. Nurmohamed, Annette Lee, David E. Larson, Fina Kurreeman, Tracie L. Deluca, Michelle O'Laughlin, Catrina C. Fronick, Lucinda L. Fulton, Elaine R. Mardis, Irene E. van der Horst‐Bruinsma, Gert‐Jan Wolbink, Peter K. Gregersen, Joel M. Kremer, J. Bart A. Crusius, Niek de Vries, Tom W. J. Huizinga, João Eurico Fonseca, Corinne Miceli‐Richard, Elizabeth W. Karlson, Marieke J. H. Coenen, Anne Barton, Robert M. Plenge, Soumya Raychaudhuri
Institutions: Brigham and Women's Hospital, Harvard University, Broad Institute, Icahn School of Medicine at Mount Sinai, Universidade Nova de Lisboa, Université Paris-Sud, Inserm, Bicêtre Hospital, New York University Langone Orthopedic Hospital, New York University, The University of Osaka, Columbia University, Washington University in St. Louis, GlaxoSmithKline (United Kingdom), University of Amsterdam, Reade, Feinstein Institute for Medical Research, Leiden University, Leiden University Medical Center, Center for Rheumatology, Albany Medical College, Amsterdam UMC Location Vrije Universiteit Amsterdam, University of Lisbon, Hospital de Santa Maria, Hôpital Cochin, Radboud University Medical Center, Manchester Academic Health Science Centre, University of Manchester
Language: English
Subfield: Rheumatology
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: Amgen, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, GlaxoSmithKline, Sanofi, Brigham and Women's Hospital, Broad Institute, National Institute for Health and Care Research, National Institutes of Health, Genentech, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Arthritis and Musculoskeletal and Skin Diseases
Awards: Defining the influence of RA genetic susceptibility factors on T cell antigen specificity and functional state, G2219674684, G2802833643, G2862371588, Towards Evidence-Based Monitoring of Low Dose Methotrexate: CIRT Ancillary Study, Novel Biomarkers and Prediction Models for Rheumatoid Arthritis, G629174108, G6626909389, G731149954, G7457993948, G84984283, G9000063397, G9000074734, G9000081670, G9000084044, G9000085813, G9000086738, G9000235445, G9000264137, G9000290745, Joint Biology Consortium Resource-based Center, G932915660, G984938634
OpenAlex ID: W2542103279