News
16/9/2016

CEXS-UPF: Researchers of GRIB participate in a crowdsourced assessment of rheumatoid arthritis treatments

CEXS-UPF: Researchers of GRIB participate in a crowdsourced assessment of rheumatoid arthritis treatments


News from CEXS-UPF


The researchers of the Structural Bioinformatics group of GRIB, 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. 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. 

More information:
CEXS-UPF Website

Reference work:
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.