Researchers of GRIB participate in a crowdsourced assessment of the treatment response in rheumatoid arthritis

The researchers of the Structural Bioinformatics group of GRIB (IMIM-UPF), led by Baldo Oliva, recently participated in the Reumatoid Arthritis (RA) Responder challenge in which participants had to identify individuals most likely to fail response to RA therapies. The study was awarded with the first prize, it was presented at the Seventh Annual RECOMB/ ISCB Conference and has been eventually published at the Nature Communications magazine. 

Rheumatoid Arthritis (RA) is a debilitating autoimmune disease that affects millions world-wide and manifests through proinflammatory joint damage. Reducing inflammation is essential to prevent long-term deleterious effects in RA. 

Standard treatment includes a class of drugs that block the inflammatory cytokine tumor necrosis factor-a (anti-TNF therapies) but nearly a third of patients fail to respond to these therapies. While it is known that patients with more severe disease tend to exhibit stronger response, there is not sufficient information available to develop prognostic biomarkers capable of predicting response 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 the Reumatoid Arthritis Responder Challege. The challenge enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive data available and covered a wide range of state-of-the-art modelling methodologies. Although there is significant genetic difference between responders and non-responders quantified by point mutations, the difference in genetic background is not sufficient to improve the accuracy for responder prediction. 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 the collection of other data.

The RA Responder Challege is one of the DREAM Challenges that pose fundamental questions about systems biology and translational medicine. Designed and run by a community of researchers from a variety of organizations, the challenges invite participants to propose solutions - fostering collaboration and building communities during the process. Expertise and institutional support are provided by Sage Bionetworks, along with the infrastructure to host challenges via their Synapse platform. Together, all the participants share a vision allowing individuals and groups to collaborate openly so that the  "wisdom of the crowd" provides the greatest impact on science and human health.

Article reference: Sieberts SK, Zhu F, García-García J, Stahl E, Pratap A, Pandey G, Pappas D, Aguilar D, Anton B, Bonet J, Eksi R,Fornés O, Guney E, Li H, Marín MA, Panwar B, Planas-Iglesias J, Poglayen D, Cui J, Falcao AO et al (including Oliva B). Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis. Nature Communications, 2016; 7: 12460. DOI: doi:10.1038/ncomms12460.

Ver noticia en castellano en la web de la UPF

Veure notícia en català a la web de la UPF