Project description:Introduction: Sepsis is a complex immunological response to infection characterized by early hyperinflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on SIRS differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing. Methods: This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes. Results: Based on preliminary microarray analyses comparing HC and sepsis groups. A panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. AUC ROC curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 - 92%. Conclusions: This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients. GEO Note: Data made available represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20). This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. The GEO data represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20).

Project description:Background: The role of viral infections as a mediator of systemic immune dysfunction leading to sepsis has received limited attention compared to the bacterial pathogens. The COVID-19 pandemic and the increased cases of sepsis in the absence of known bacterial pathogens have highlighted the clinical relevance of viruses as causative agents of sepsis. In this study, we investigated clinical, laboratory, proteomic, and metabolic characteristics to shed light on the molecular mechanisms underlying the pathological conditions of viral sepsis in COVID-19. Methods: We retrospectively analyzed data from 231 hospitalized patients with confirmed COVID-19 admitted to three hospitals in China. The presence of viral sepsis was diagnosed with SOFA score 2 in the absence of bacterial infection. Demographics, clinical, and laboratory parameters, as well as clinical outcomes, were obtained from electronic chart reviews. Plasma samples were obtained from a subset of these patients (23 patients in the Viral Non-Sepsis [VNS] group and 14 patients in the Viral Sepsis [VS] group) to analyze proteomic and metabolic profiles. Findings: The viral sepsis group exhibited severe disease, as indicated by elevated markers of both pulmonary (ARDS) and systemic disease (liver, kidney, and cardiac injury). Consistent with known immune paralysis observed in sepsis, subjects with viral sepsis were more susceptible to secondary infections by bacterial and fungal pathogens. Overall, viral sepsis led to an increased length of ICU stay, required invasive mechanical ventilation and a significant increase in mortality compared to the non-viral sepsis group. At the molecular levels, we identified unique metabolic and proteomic signatures that suggest a substantial contribution of the coagulation and platelet dysfunction pathways to systemic pathologies. Interpretation: Viral sepsis presents an underrecognized threat contributing to high mortality. Specific metabolic and proteomic changes demonstrated coagulation and platelet dysfunction as key pathological pathway in viral sepsis.

Project description:Background: Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. To date, no biomarker has shown sufficient evidence and ease of application in clinical routine to monitor the complexity of the sepsis-related immune alterations. Multiple levels of interaction of human endogenous retroviruses (HERVs) with the immune response led us to hypothesize that they may be relevant candidates both to contribute to the physiopathology of sepsis and to be part of a molecular signature. In this study, we used a recently described high-density microarray which allows exploring HERVs/MaLRs transcriptome in septic shock patients. Results: About 6.9% of the HERVs/MalRs repertoire is transcribed in whole blood. Concerning the functionality of LTRs, the majority of LTRs are silent (62.9%), 7.5% of LTRs present a putative constitutive promoter or polyA functions, while 20.4% of them may shift from silent to active. Evidence was given that a subset of HERVs/MaLRs and genes were modulated in septic shock patients according to the monocyte HLA-DR (mHLA-DR) expression level measured by flow cytometry, as a proxy of immunosuppression. We then identified a large signature consisting of 193 differentially expressed HERVs/MaLRs probesets further reduced to a smaller 10 HERVs/MaLRs signature. Both signatures, validated in an independent septic shock cohort, identified two groups of patients with different severity features including clinical criteria and the CD74 and CX3CR1 sepsis severity molecular markers. Conclusion: This microarray-based approach unveiled the expression of about 87,912 distinct HERV probesets and identified 764 putative promoter LTRs and 642 putative polyA LTRs in whole blood. HERV/MaLR expression was shown to be tightly modulated in septic shock patients according to mHLA-DR expression. We identified a set of potential molecular biomarkers in septic shock patients partially overlapping immunosuppression (mHLA-DR), and the risk of Health Care associated Infections (HAI) (CD74 ratio), complementary to existing molecular markers of a sepsis patients stratification. We identified a HERV/MaLR signature discriminating patients based on their immunosuppression state and severity.

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An Endotoxin Tolerance Signature Predicts Sepsis and Organ Dysfunction at Initial Clinical Presentation

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