Although more GWAS on sepsis

Although more GWAS on sepsis traits will be accomplished in the coming years, it is worth noting that these studies allow analyzing a modest fraction of all existing variants in our genome. In , present their results from a study using a promising alternative taking advantage of high-throughput DNA sequencing. The authors selected 59 patients from a roughly 4000 patient cohort, and classified them based on two extreme phenotypes: group A (=32) comprised the most favorable cases, including patients who survived sepsis despite the administration of inappropriate antibiotic therapy, whereas group B (=27) was composed of patients with the worst disease course despite being younger, received the appropriate treatment, and had no comorbidities. Those patients were sequenced for their exome, which roughly corresponds to the portion of DNA that codes for functional genes, in order to assess the role of rare single nucleotide variants (SNVs) in sepsis course. Based on advanced semantic classification algorithms and on the most likely damaging rare SNVs, the authors developed a model predicting disease course involving cell signaling and innate immunity genes. The model attained >75% accuracy, sensitivity and specificity, and was validated in an independent but smaller (=15) cohort. Strikingly, damaging rare SNVs conferred a protective effect to the disease course after sepsis. Extensive sequencing of further patients will be needed to independently validate and refine this finding, and will probably unravel novel FK506 with potential implications in sepsis prognosis. In addition, based on the reported ethnic disparities in sepsis incidence and mortality (), those studies should include samples of diverse ethnicity to verify the robustness of classification. Personalized information, including that provided by our genetic makeup, is profoundly changing the medical practice. For this to happen in the ICUs, many more genes of interest for sepsis risk and prognosis need to be discovered. Focusing on particular patient populations should provide optimal approaches. In addition, the application of multi-level clinical and genetic data analysis, as exemplified by and the accompanying study in (), illustrate a way to offer joint support to determine genes of interest for developing personalized interventions in sepsis. Conflict of Interest
Financial Support This work was supported by Instituto de Salud Carlos III (FIS PI14/00844) co-financed by the European Regional Development Funds, “A way of making Europe” from the European Union, and ACIISI (TESIS2015010057) co-funded by European Social Fund.
Sepsis triggers multiple parallel inflammatory signaling pathways. Of these pathways, which ones contribute most substantially to adverse outcomes and, therefore, are relevant targets for new therapies? >100 clinical trials of mediator modulators in sepsis patients have failed () suggesting that we need new information to direct our search. In other disease states a genome-wide association study design is an unbiased approach that has identified genes in key pathways (). For example, PCSK9 was discovered using genetic association analysis of patients who had LDL levels measured (). This has led to the introduction of PCSK9 inhibitors as a treatment for hypercholesterolemia where other treatments have failed. Can a similar genetic association strategy work in the complex milieu of sepsis? In the current issue of , conducted a genome-wide association study for 28-day mortality, initially in 740 septic patients. The authors followed standard quality control practices to limit any potential methodological errors in their discovery GWAS. From 644,699 SNPs they imputed 7,993,459 SNPs for their GWAS analysis. These investigators found that a missense genetic variant located within the VPS13A gene was associated with 28-day mortality in sepsis. This was the strongest association observed within the primary GWAS analysis (p=8.2×10). The minor allele, associated with adverse outcome, occurred only 1% of the time so this association is very susceptible to a false positive result since only a small number of patients would carry this adverse genetic variant – the conclusions are based on a few “affected” patients. Therefore, replication of this finding was essential. These investigators took the relatively rare (within the critical care community), but crucial, step of reaching out to previous investigators with large genotyped sepsis cohorts. This VPS13A finding replicated to a reasonable extent (associated with SOFA severity of illness score) in a second large cohort of patients from the PROGRESS study (: ). Finally, taking all genetic variants found by sequencing across the VPS13A gene, the VPS13A gene was also found to be associated with 28-day mortality. A bioinformatics analysis suggests that this protein-altering SNP (rs117983287) is predicted to be highly deleterious to VPS13A function. The original finding plus replication and further support from the sequencing study and analysis leads to the potentially important and exciting finding that a signaling pathway involving VPS13A is associated with sepsis outcome. Not much is known about VPS13A function as it relates to sepsis () so much work remains. Indeed, there are many other genes in this region so it is not yet certain that VPS13A causally impacts sepsis outcome.