Our results that pinpoint the G q signaling

Our results that pinpoint the Gαq signaling pathway as classificator for the different sepsis courses of patient groups A and B are also supported by a recent GWAS of common variants with respect to the 28-day mortality (Scherag et al., 2016). Among the identified 14 GWAS loci, three are related to Gαq signaling or G-coupled receptors. The top discovery GWAS association signal covers VPS13A (related to autophagy) and the 3′ end of the above mentioned GNA14. Therefore, both genes are promising functional candidates for the observed association. A second locus highlights HRH1 (histamine receptor H1), which is part of the Gαq signaling and interleukin receptor SHC pathways. Finally, GPR12 (G protein-coupled receptor 12) was also identified by the GWAS approach. It has to be noted, though, that the particular GWAS variants in HRH1 and near GPR12 were not supported by the GWAS validation data (Scherag et al., 2016). Although the study appears limited in size, the effort for its enrollment was large, as the investigated extreme disease phenotypes are rare and e.g. the 59 Greek samples were selected from almost 4000 patients. Furthermore, the robustness of our findings is supported by two facts. First, the classification model was trained and validated using samples derived from different ethnical groups. Second, the two groups of sepsis patients with either favorable (group A) or adverse (group B) disease course after sepsis were selected in the two ethnic groups by different criteria. The GR samples were chosen from medical patients to represent two qualitatively extremely different clinical phenotypes, whereas the DE groups represent opposite quantitative extremes among surgical patients. Our findings indicate that careful selection of extremely different clinical phenotypes enables the identification of rare variants underlying complex traits in heterogeneous populations and that respective studies are not limited to populations with reduced allele purchase ap4 like Icelanders (Helgadottir et al., 2016).
Funding Sources We acknowledge the support by the German Federal Ministry of Education and Research (BMBF) for the Center for Sepsis Control and Care, CSCC, (01EO1002, 01EO1502) and for the Popgen 2.0 Network, P2N, (01EY1103). The research leading to these results received funding from the European Community\'s Seventh Framework Programme (FP7/2007–2013) under grant agreement no602783, the German Research Foundation (DFG, SFB 1074 project Z1), and the BMBF (Gerontosys II, Forschungskern SyStaR, project ID 0315894A) all to HAK. Andre Franke and Britt-Sabina Petersen are both supported by the DFG Excellence Cluster 306 “Inflammation at Interfaces”.
Conflict of Interests
Author Contributions
Acknowledgement
Introduction Sepsis is the dysregulated host response to an infection which leads to life-threatening organ dysfunction according to the new Sepsis-3 definition (Singer et al., 2016; Seymour et al., 2016). It can result in 28day mortalities of up to 60% (Engel et al., 2007; Angus and Wax, 2001). Consequently, there is an urgent need for new therapies but results from recent large scale phase III randomized controlled intervention trials (e.g Food and Drug Administration, 2011) have been disappointing. It has been proposed to go “back to the drawing board” (Angus, 2011) taking a fresh look at the biology that drives the sepsis processes (Cohen et al., 2015). As part of this discussion, there is new interest in host genomic factors that are rooted in the landmark publication by Sørensen et al. (1988). These authors reported that if one biological parent died of an infection, the risk to die of an infection in the offspring was strongly increased (relative risk 4.52). This work stimulated the conduct of many candidate gene association studies for sepsis susceptibility with inconsistent and essentially weak results (e.g. reviewed in Clark and Baudouin, 2006). Moreover, focusing on sepsis susceptibility might be too challenging given that recent evidence strongly supported a stronger impact of the host genome to account for the variability during the clinical disease course after sepsis onset (Petersen et al., 2010). Thus, this and an accompanying report by Taudien et al. 2016 focus on host genomic factors related to differential clinical disease course after sepsis onset applying the new Sepsis-3 definition. While Taudien et al. 2016 report on deleterious single nucleotide variants and pathways, we describe a genome-wide association (GWA) study (GWAS) which by design is limited to common variants.