IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study.

Purpose: Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness. Methods: We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients. Results: We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients. Conclusion: These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

Blood transcriptome analysis of patients with uncomplicated bacterial infection and sepsis.

OBJECTIVES: Hospitalized patients who presented within the last 24 h with a bacterial infection were recruited. Participants were assigned into sepsis and uncomplicated infection groups. In addition, healthy volunteers were recruited as controls. RNA was prepared from whole blood, depleted from beta-globin mRNA and sequenced. This dataset represents a highly valuable resource to better understand the biology of sepsis and to identify biomarkers for severe sepsis in humans. DATA DESCRIPTION: The data presented here consists of raw and processed transcriptome data obtained by next generation RNA sequencing from 105 peripheral blood samples from patients with uncomplicated infections, patients who developed sepsis, septic shock patients, and healthy controls. It is provided as raw sequenced reads and as normalized log2 transformed relative expression levels. This data will allow performing detailed analyses of gene expression changes between uncomplicated infections and sepsis patients, such as identification of differentially expressed genes, co-regulated modules as well as pathway activation studies.

Prospective validation study of prognostic biomarkers to predict adverse outcomes in patients with COVID-19: a study protocol.

INTRODUCTION: Accurate triage is an important first step to effectively manage the clinical treatment of severe cases in a pandemic outbreak. In the current COVID-19 global pandemic, there is a lack of reliable clinical tools to assist clinicians to perform accurate triage. Host response biomarkers have recently shown promise in risk stratification of disease progression; however, the role of these biomarkers in predicting disease progression in patients with COVID-19 is unknown. Here, we present a protocol outlining a prospective validation study to evaluate the biomarkers' performance in predicting clinical outcomes of patients with COVID-19. METHODS AND ANALYSIS: This prospective validation study assesses patients infected with COVID-19, in whom blood samples are prospectively collected. Recruited patients include a range of infection severity from asymptomatic to critically ill patients, recruited from the community, outpatient clinics, emergency departments and hospitals. Study samples consist of peripheral blood samples collected into RNA-preserving (PAXgene/Tempus) tubes on patient presentation or immediately on study enrolment. Real-time PCR (RT-PCR) will be performed on total RNA extracted from collected blood samples using primers specific to host response gene expression biomarkers that have been previously identified in studies of respiratory viral infections. The RT-PCR data will be analysed to assess the diagnostic performance of individual biomarkers in predicting COVID-19-related outcomes, such as viral pneumonia, acute respiratory distress syndrome or bacterial pneumonia. Biomarker performance will be evaluated using sensitivity, specificity, positive and negative predictive values, likelihood ratios and area under the receiver operating characteristic curve. ETHICS AND DISSEMINATION: This research protocol aims to study the host response gene expression biomarkers in severe respiratory viral infections with a pandemic potential (COVID-19). It has been approved by the local ethics committee with approval number 2020/ETH00886. The results of this project will be disseminated in international peer-reviewed scientific journals.

Accuracy of Quick Sequential Organ Failure Assessment Score to Predict Sepsis Mortality in 121 Studies Including 1,716,017 Individuals: A Systematic Review and Meta-Analysis.

We performed a meta-analysis to assess whether the newly introduced quick Sequential Organ Failure Assessment score could predict sepsis outcomes and compared its performance to systematic inflammatory response syndrome, the previously widely used screening criteria for sepsis. DATA SOURCES: We searched multiple electronic databases including MEDLINE, the Cochrane Library, Embase, Web of Science, and Google Scholar (up to March 1, 2019) that evaluated quick Sequential Organ Failure Assessment score, systemic inflammatory response syndrome, or both (International Prospective Register of Systematic Reviews [PROSPERO]: CRD42018103327). STUDY SELECTION: Studies were included if the outcome was mortality, organ dysfunction, admission to ICU, ventilatory support, or prolonged ICU stay and if prediction performance was reported as either area under the curve, odds ratio, sensitivity, or specificity. DATA EXTRACTION: The criterion validity of the quick Sequential Organ Failure Assessment score and systemic inflammatory response syndrome criteria were assessed by measuring its predictive validity for primary (mortality) and secondary outcomes in pooled metrics as mentioned. The data were analyzed using random effects model, and heterogeneity was explored using prespecified subgroups analyses. DATA SYNTHESIS: We screened 1,340 studies, of which 121 studies (including data for 1,716,017 individuals) were analyzed. For mortality prediction, the pooled area under the curve was higher for quick Sequential Organ Failure Assessment score (0.702; 95% CI, 0.685-0.718; I 2 = 99.41%; p < 0.001) than for systemic inflammatory response syndrome (0.607; 95% CI, 0.589-0.624; I 2 = 96.49%; p < 0.001). Quick Sequential Organ Failure Assessment score consistently outperformed systemic inflammatory response syndrome across all subgroup analyses (area under the curve of quick Sequential Organ Failure Assessment vs. area under the curve of systemic inflammatory response syndrome p < 0.001), including patient populations (emergency department vs ICU), study design (retrospective vs prospective), and countries (developed vs resource-limited). Quick Sequential Organ Failure Assessment score was more specific (specificity, 74.58%; 95% CI, 73.55-75.61%) than systemic inflammatory response syndrome (specificity, 35.24%; 95% CI, 22.80-47.69%) but less sensitive (56.39%; 95% CI, 50.52-62.27%) than systemic inflammatory response syndrome (78.84%; 95% CI, 74.48-83.19%). CONCLUSIONS: Overall, quick Sequential Organ Failure Assessment score outperforms systemic inflammatory response syndrome in predicting sepsis outcome, but quick Sequential Organ Failure Assessment score has relative strengths/weaknesses (more specific but less sensitive) compared with systemic inflammatory response syndrome.