Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Solveig K. Sieberts(Sage Bionetworks), Fan Zhu(University of Michigan), Javier Garcı́a-Garcı́a(Universitat Pompeu Fabra), Eli A. Stahl(Icahn School of Medicine at Mount Sinai), Abhishek Pratap(Sage Bionetworks), Gaurav Pandey(Icahn School of Medicine at Mount Sinai), Dimitrios A. Pappas(Columbia University Irving Medical Center), Daniel Aguilar(Universitat Pompeu Fabra), Bernat Anton(Universitat Pompeu Fabra), Jaume Bonet(Universitat Pompeu Fabra), Ridvan Eksi(University of Michigan), Oriol Fornés(Universitat Pompeu Fabra), Emre Güney(Northeastern University), Hongdong Li(University of Michigan), Manuel Alejandro Marín-López(Universitat Pompeu Fabra), Bharat Panwar(University of Michigan), Joan Planas-Iglesias(Universitat Pompeu Fabra), Daniel Poglayen(Universitat Pompeu Fabra), Jing Cui(Brigham and Women's Hospital), André O. Falcão(University of Lisbon), Christine Suver(Sage Bionetworks), Bruce Hoff(Sage Bionetworks), Venkat S. K. Balagurusamy(IBM (United States)), Donna Dillenberger(IBM (United States)), Elias Chaibub Neto(Sage Bionetworks), Thea Norman(Sage Bionetworks), Tero Aittokallio(IBM (United States)), Muhammad Ammad-ud-din(Helsinki Institute for Information Technology), Chloé‐Agathe Azencott(Inserm), Víctor Bellón(Inserm), Valentina Boeva(Inserm), Kerstin Bunte(Helsinki Institute for Information Technology), Himanshu Chheda(University of Helsinki), Lu Cheng(University of Helsinki), Jukka Corander(Statistics Finland), Michel Dumontier(Stanford Medicine), Anna Goldenberg(University of Toronto), Peddinti Gopalacharyulu(University of Helsinki), Mohsen Hajiloo(SickKids Foundation), Daniel Hidru(University of Toronto), Alok Jaiswal(University of Helsinki), Samuel Kaski(University of Helsinki), Beyrem Khalfaoui(SickKids Foundation), Suleiman A. Khan(University of Helsinki), Eric R. Kramer(Scripps Research Institute), Pekka Marttinen(Helsinki Institute for Information Technology), Aziz M. Mezlini(University of Toronto), Bhuvan Molparia(Scripps Research Institute), Matti Pirinen(University of Helsinki), Janna Saarela(University of Helsinki), Matthias Samwald(Statistics Austria), Véronique Stoven(Inserm), Hao Tang(The University of Texas Southwestern Medical Center), Jing Tang(University of Helsinki), Ali Torkamani(Scripps Research Institute), Jean-Phillipe Vert(Inserm), Bo Wang(The University of Texas Southwestern Medical Center), Tao Wang(The University of Texas Southwestern Medical Center), Krister Wennerberg(University of Helsinki), Nathan E. Wineinger(Scripps Research Institute), Guanghua Xiao(The University of Texas Southwestern Medical Center), Yang Xie(The University of Texas Southwestern Medical Center), Rae S. M. Yeung(University of Toronto), Xiaowei Zhan(Southwestern Medical Center), Cheng Zhao(University of Toronto), Manuel Calaza(University of California, San Francisco), Haitham Elmarakeby(University of Pittsburgh), Lenwood S. Heath(University of Pittsburgh), Quan Long(Icahn School of Medicine at Mount Sinai), Jonathan D. Moore(Karolinska University Hospital), Stephen O. Opiyo(Northwell Health), Richard S. Savage(Merck & Co., Inc., Rahway, NJ, USA (United States)), Jun Zhu(Icahn School of Medicine at Mount Sinai), Jeff Greenberg(Sage Bionetworks), Joel Kremer(Albany Medical Center Hospital), Kaleb Michaud(Nebraska Medical Center), Anne Barton(Manchester Academic Health Science Centre), Marieke J. H. Coenen(Radboud University Nijmegen), Xavier Mariette(Université Paris-Sud), Corinne Miceli‐Richard(Université Paris-Sud), Nancy A. Shadick(Brigham and Women's Hospital), Michael E. Weinblatt(Brigham and Women's Hospital), Niek de Vries(Amsterdam UMC Location University of Amsterdam), Paul P. Tak(GlaxoSmithKline (United Kingdom)), Daniëlle M. Gerlag(GlaxoSmithKline (United Kingdom)), T. Huizinga(Leiden University Medical Center), Fina Kurreeman(Leiden University Medical Center), Cornelia F Allaart(Merck & Co., Inc., Rahway, NJ, USA (United States)), S. Louis Bridges(University of Alabama at Birmingham), Lindsey A. Criswell(University of California, San Francisco), Larry W. Moreland(University of Pittsburgh), Lars Klareskog(Karolinska University Hospital), Saedís Saevarsdóttir(Karolinska University Hospital), Leonid Padyukov(Karolinska University Hospital), Peter K. Gregersen(Northwell Health), Stephen Friend(Sage Bionetworks), Robert M. Plenge(Merck & Co., Inc., Rahway, NJ, USA (United States)), Gustavo Stolovitzky(University of Lisbon), Baldo Oliva(Universitat Pompeu Fabra), Yuanfang Guan(University of Michigan), Lara M. Mangravite(Sage Bionetworks)
Nature Communications
August 23, 2016
10.1038/ncomms12460
Cited by 87Open Access
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Abstract

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently 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 RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2)=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.

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