Highlights d Screening of gut microbiota metabolomes against hundreds of G protein-coupled receptors d Phylogenetically diverse gut microbes produce agonists for many GPCRs including orphans d Bioactivity-based screening reveals diet-microbe-host and microbe-microbe-host axes d Microbiota-derived GPCR ligands impact local and systemic host physiology
Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10−8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10−11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry.
Genome-wide association studies (GWASs) have identified hundreds of loci harboring genetic variation influencing inflammatory-disease susceptibility in humans. It has been hypothesized that present day inflammatory diseases may have arisen, in part, due to pleiotropic effects of host resistance to pathogens over the course of human history, with significant selective pressures acting to increase host resistance to pathogens. The extent to which genetic factors underlying inflammatory-disease susceptibility has been influenced by selective processes can now be quantified more comprehensively than previously possible. To understand the evolutionary forces that have shaped inflammatory-disease susceptibility and to elucidate functional pathways affected by selection, we performed a systems-based analysis to integrate (1) published GWASs for inflammatory diseases, (2) a genome-wide scan for signatures of positive selection in a population of European ancestry, (3) functional genomics data comprised of protein-protein interaction networks, and (4) a genome-wide expression quantitative trait locus (eQTL) mapping study in peripheral blood mononuclear cells (PBMCs). We demonstrate that loci for inflammatory-disease susceptibility are enriched for genomic signatures of recent positive natural selection, with selected loci forming a highly interconnected protein-protein interaction network. Further, we identify 21 loci for inflammatory-disease susceptibility that display signatures of recent positive selection, of which 13 also show evidence of cis-regulatory effects on genes within the associated locus. Thus, our integrated analyses highlight a set of susceptibility loci that might subserve a shared molecular function and has experienced selective pressure over the course of human history; today, these loci play a key role in influencing susceptibility to multiple different inflammatory diseases, in part through alterations of gene expression in immune cells.
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