Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.
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- dc.contributor.author Sieberts, Solveig K.ca
- dc.contributor.author García-García, Javier, 1982-ca
- dc.contributor.author Aguilar, Danielca
- dc.contributor.author Anton, Bernatca
- dc.contributor.author Bonet Martínez, Jaume, 1982-ca
- dc.contributor.author Fornés Crespo, Oriol, 1983-ca
- dc.contributor.author Marín López, Manuel Alejandro, 1987-ca
- dc.contributor.author Planas Iglesias, Joan, 1980-ca
- dc.contributor.author Poglayen, Daniel, 1984-ca
- dc.contributor.author Oliva Miguel, Baldomeroca
- dc.contributor.author Mangravite, Lara M.ca
- dc.date.accessioned 2016-12-22T08:36:44Z
- dc.date.available 2016-12-22T08:36:44Z
- dc.date.issued 2016
- dc.description.abstract Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widelyused to reduce disease progression, treatment fails inBone-third of patients. No biomarkercurrently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RApatients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictionsdeveloped by 73 research groups using the most comprehensive available data and covering awide range of state-of-the-art modelling methodologies. Despite a significant geneticheritability estimate of treatment non-response trait (h2¼0.18,Pvalue¼0.02), nosignificant genetic contribution to prediction accuracy is observed. Results formally confirmthe expectations of the rheumatology community that SNP information does not significantlyimprove predictive performance relative to standard clinical traits, thereby justifying arefocusing of future efforts on collection of other dataca
- dc.description.sponsorship G.P. is partially supported by NIH grant# R01GM114434 and an IBM faculty award. E.S. is funded by NIH R01GM105857. The Corrona CERTAIN study is sponsored by Corrona, LLC with support from the Agency for Healthcare Research and Quality (R01HS018517). The majority of funding for the planning and implementation of/nCERTAIN was derived from Genentech, with additional support for substudies from Eli Lilly, Momenta harmaceuticals and Pfizer. CERTAIN investigators also receive support from the National Institute of Health (JRC AR053351, JDG AR054 412).
- dc.format.mimetype application/pdfca
- dc.identifier.citation Sieberts SK, Zhu F, García-García J, Stahl E, Pratap A, Pandey G, et al. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis. Nat Commun. 2016 Aug 23;7:12460. doi: 10.1038/ncomms12460ca
- dc.identifier.doi http://dx.doi.org/10.1038/ncomms12460
- dc.identifier.issn 2041-1723
- dc.identifier.uri http://hdl.handle.net/10230/27819
- dc.language.iso engca
- dc.publisher Nature Publishing Groupca
- dc.relation.ispartof Nature Communications. 2016 Aug 23;7:12460
- dc.rights © 2016, The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ca
- dc.rights.accessRights info:eu-repo/semantics/openAccessca
- dc.rights.uri https://creativecommons.org/licenses/by/4.0/ca
- dc.subject.other Artritis reumatoide -- Tractamentca
- dc.title Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.ca
- dc.type info:eu-repo/semantics/articleca
- dc.type.version info:eu-repo/semantics/publishedVersionca