A community approach to mortality prediction in sepsis via gene expression analysis.

Improved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance is validated in five cohorts of community-onset sepsis patients in which the models show summary AUROCs ranging from 0.765-0.89. Similar performance is observed in four cohorts of hospital-acquired sepsis. Combining the new gene-expression-based prognostic models with prior clinical severity scores leads to significant improvement in prediction of 30-day mortality as measured via AUROC and net reclassification improvement index These models provide an opportunity to develop molecular bedside tests that may improve risk stratification and mortality prediction in patients with sepsis.y NIGMS Glue Grant Legacy Award R24GM102656. J.F.B.-M., R.A., and E.T. were supported by Instituto de Salud Carlos III (grants EMER07/050, PI13/02110, PI16/01156). R.J.L. was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001417. The CAPSOD study was supported by NIH (U01AI066569, P20RR016480, HHSN266200400064C). P.K. is supported by grants from Bill Melinda Gates Foundation, R01 AI125197-01, 1U19AI109662, and U19AI057229, outside the submitted work. The GAinS study was supported by the National Institute for Health Research through the Comprehensive Clinical Research Network for patient recruitment; Wellcome Trust (Grants 074318 [to J.C.K.], and 090532/Z/09/Z [core facilities Wellcome Trust Centre for Human Genetics including High-Throughput Genomics Group]); European Research Council under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ERC Grant agreement no. 281824 (to J.C.K.), the Medical Research Council (98082 [to J.C.K.]); UK Intensive Care Society; and NIHR Oxford Biomedical Research Centre. The Duke HAI study was supported by a research agreement between Duke University and Novartis Vaccines and Diagnostics, Inc. According to the terms of the agreement, representatives of the sponsor had an opportunity to review and comment on a draft of the manuscript. The authors had full control of the analyses, the preparation of the manuscript, and the decision to submit the manuscript for publication. For the University of Florida ‘P50’ Study, data were obtained from the Sepsis and Critically Illness Research Center (SCIRC) at the University of Florida College of Medicine, which is supported in part by NIGMS P50 GM111152. This work was supported by Defense Advanced Research Projects Agency and the Army Research Office through Grant W911NF-15-1-0107.

NLRP3 Inflammasome Deficiency Protects against Microbial Sepsis via Increased Lipoxin B4 Synthesis.

RATIONALE: Sepsis, a life-threatening organ dysfunction caused by a dysregulated host response to infection, is a major public health concern with high mortality and morbidity. Although inflammatory responses triggered by infection are crucial for host defense against invading microbes, the excessive inflammation often causes tissue damage leading to organ dysfunction. Resolution of inflammation, an active immune process mediated by endogenous lipid mediators (LMs), is important to maintain host homeostasis. OBJECTIVES: We sought to determine the role of the nucleotide-binding domain, leucine-rich repeat-containing receptor, pyrin domain-containing-3 (NLRP3) inflammasome in polymicrobial sepsis and regulation of LM biosynthesis. METHODS: We performed cecal ligation and puncture (CLP) using mice lacking NLRP3 inflammasome-associated molecules to assess mortality. Inflammation was evaluated by using biologic fluids including plasma, bronchoalveolar, and peritoneal lavage fluid. Local acting LMs in peritoneal lavage fluid from polymicrobacterial septic mice were assessed by mass spectrometry-based metabololipidomics. MEASUREMENTS AND MAIN RESULTS: Genetic deficiency of NLRP3 inhibited inflammatory responses and enhanced survival of CLP-induced septic mice. NLRP3 deficiency reduced proinflammatory LMs and increased proresolving LM, lipoxin B4 (LXB4) in septic mice, and in macrophages stimulated with LPS and ATP. Activation of the NLRP3 inflammasome induced caspase-7 cleavage and pyroptosis. Caspase-7 deficiency similarly reduced inflammation and mortality in CLP-induced sepsis, and increased LXB4 production in vivo and in vitro. Exogenous application of LXB4 reduced inflammation, pyroptosis, and mortality of mice after CLP. CONCLUSIONS: Genetic deficiency of NLRP3 promoted resolution of inflammation in polymicrobial sepsis by relieving caspase-7-dependent repression of LXB4 biosynthesis, and increased survival potentially via LXB4 production and inhibition of proinflammatory cytokines.Supported by National Institutes of Health grants P01 HL108801, R01-HL60234, R01-HL55330, and R01-HL079904; a FAMRI Clinical Innovator Award(A.M.K.C.); and a Department of Medicine Seed Grant for Innovative Research (Weill Cornell Medicine, K.N.)

Data-driven adult asthma phenotypes based on clinical characteristics are associated with asthma outcomes twenty years later

Research based on cluster analyses led to the identification of particular phenotypes confirming phenotypic heterogeneity of asthma. The long-term clinical course of asthma phenotypes defined by clustering analysis remains unknown, although it is a key aspect to underpin their clinical relevance. We aimed to estimate risk of poor asthma events between asthma clusters identified 20 years earlier.; The study relied on two cohorts of adults with asthma with 20-year follow-up, ECRHS (European Community Respiratory Health Survey) and EGEA (Epidemiological study on Genetics and Environment of Asthma). Regression models were used to compare asthma characteristics (current asthma, asthma exacerbations, asthma control, quality of life, and FEV; 1; ) at follow-up and the course of FEV; 1; between seven cluster-based asthma phenotypes identified 20 years earlier.; The analysis included 1325 adults with ever asthma. For each asthma characteristic assessed at follow-up, the risk for adverse outcomes differed significantly between the seven asthma clusters identified at baseline. As compared with the mildest asthma phenotype, ORs (95% CI) for asthma exacerbations varied from 0.9 (0.4 to 2.0) to 4.0 (2.0 to 7.8) and the regression estimates (95% CI) for FEV; 1; % predicted varied from 0.6 (-3.5 to 4.6) to -9.9 (-14.2 to -5.5) between clusters. Change in FEV; 1; over time did not differ significantly across clusters.; Our findings show that the long-term risk for poor asthma outcomes differed between comprehensive adult asthma phenotypes identified 20 years earlier, and suggest a strong tracking of asthma activity and impaired lung function over time