The Optimization and Biological Significance of a 29-Host-Immune-mRNA Panel for the Diagnosis of Acute Infections and Sepsis

He, Yudong; Wohlford, Eric M.; Uhle, Florian; Buturović, Ljubomir; Liesenfeld, Oliver; Sweeney, Timothy E.

doi:10.3390/jpm11080735

Cited by 30 publications

(25 citation statements)

References 89 publications

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“…Detailed results on the development of the classifiers (including both gene selection and clinical threshold setting) and their validation across multiple cohorts have been published previously. 6 , 7 , 8 , 12 , 13 , 14 , 15 Transcripts were quantified from 200 ng of RNA input using a genomic analysis platform (510[k]-cleared nCounter FLEX; NanoString, Inc) according to a laboratory-developed standard operating protocol in a Clinical Laboratory Improvement Amendments–certified clinical and diagnostic laboratory. Measured mRNA counts were inputted into the IMX algorithms that generate absolute scores.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of a Multivalent Transcriptomic Metric for Diagnosing Surgical Sepsis and Estimating Mortality Among Critically Ill Patients

Brakenridge

Chen²,

Loftus

et al. 2022

JAMA Netw Open

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Key Points Question Can a whole-blood RNA transcriptomic metric (IMX) obtained in the first 12 hours after intensive care unit (ICU) admission accurately measure the presence of bacterial infection and risk for sepsis mortality? Findings In this diagnostic and prognostic study including 200 patients with critical illness enrolled from a surgical ICU, the IMX transcriptomic metric was equivalent to or significantly better than the sequential organ failure assessment score and existing biomarkers (procalcitonin and interleukin 6 levels) for the diagnosis of acute infections and estimation of 30-day mortality. Meaning These findings suggest that a single, rapid-turnaround, multivalent transcriptomic test could supplant existing metrics in identifying bacterial infection and estimating clinical outcomes among critically ill surgical patients.

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Section: Methodsmentioning

confidence: 99%

Evaluation of a Multivalent Transcriptomic Metric for Diagnosing Surgical Sepsis and Estimating Mortality Among Critically Ill Patients

Brakenridge

Chen²,

Loftus

et al. 2022

JAMA Netw Open

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“…A separate classifier, IMX-SEV-2, has been developed to predict the illness severity (Galtung et al, in revision). The identity and biological functions of the 29 host mRNAs have recently been published 19 , and the classifiers have been further updated (IMX-BVN-3 and IMX-SEV-3) based on additional clinical study data.…”

Section: Introductionmentioning

confidence: 99%

Detection of bacterial co-infections and prediction of fatal outcomes in COVID-19 patients presenting to the emergency department using a 29 mRNA host response classifier

Ram-Mohan¹,

Rogers²,

Blish³

et al. 2022

Preprint

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ObjectiveClinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial co-infection, and determining illness severity since current practices require separate workflows. Here we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting SARS-CoV-2 infection, bacterial co-infections, and predicting clinical severity of COVID-19.Methods161 patients with PCR-confirmed COVID-19 (52.2% female, median age 50.0 years, 51% hospitalized, 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene Blood RNA) and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter.ResultsThe IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrolment and the remaining oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial co-infection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e. Clostridioides difficile colitis (n=1), urinary tract infection (n=1), and clinically diagnosed bacterial infections (n=3) for a specificity of 99.4%. 2/101 (2.8%) patients in the IMX-SEV-3 Low and 7/60 (11.7%) in the Moderate severity classifications died within thirty days of enrollment.ConclusionsIMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19, bacterial co-infections, and predicted patients’ risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management including more accurate treatment decisions and optimized resource utilization.

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“…Whole blood transcriptomics in patients admitted to the ICU with sepsis and SIRS has resulted in the development of classifier signatures ranging from 2 to over 100 genes ( 9 , 11 , 46 ). Yet, the underlying differences in leukocyte subpopulation-specific responses to infection vs. sterile tissue damage remain to be dissected.…”

Section: Discussionmentioning

confidence: 99%

Key Signature Genes of Early Terminal Granulocytic Differentiation Distinguish Sepsis From Systemic Inflammatory Response Syndrome on Intensive Care Unit Admission

et al. 2022

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Infection can induce granulopoiesis. This process potentially contributes to blood gene classifiers of sepsis in systemic inflammatory response syndrome (SIRS) patients. This study aimed to identify signature genes of blood granulocytes from patients with sepsis and SIRS on intensive care unit (ICU) admission. CD15+ cells encompassing all stages of terminal granulocytic differentiation were analyzed. CD15 transcriptomes from patients with sepsis and SIRS on ICU admission and presurgical controls (discovery cohort) were subjected to differential gene expression and pathway enrichment analyses. Differential gene expression was validated by bead array in independent sepsis and SIRS patients (validation cohort). Blood counts of granulocyte precursors were determined by flow cytometry in an extension of the validation cohort. Despite similar transcriptional CD15 responses in sepsis and SIRS, enrichment of canonical pathways known to decline at the metamyelocyte stage (mitochondrial, lysosome, cell cycle, and proteasome) was associated with sepsis but not SIRS. Twelve of 30 validated genes, from 100 selected for changes in response to sepsis rather than SIRS, were endo-lysosomal. Revisiting the discovery transcriptomes revealed an elevated expression of promyelocyte-restricted azurophilic granule genes in sepsis and myelocyte-restricted specific granule genes in sepsis followed by SIRS. Blood counts of promyelocytes and myelocytes were higher in sepsis than in SIRS. Sepsis-induced granulopoiesis and signature genes of early terminal granulocytic differentiation thus provide a rationale for classifiers of sepsis in patients with SIRS on ICU admission. Yet, the distinction of this process from noninfectious tissue injury-induced granulopoiesis remains to be investigated.

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The Optimization and Biological Significance of a 29-Host-Immune-mRNA Panel for the Diagnosis of Acute Infections and Sepsis

Cited by 30 publications

References 89 publications

Evaluation of a Multivalent Transcriptomic Metric for Diagnosing Surgical Sepsis and Estimating Mortality Among Critically Ill Patients

Evaluation of a Multivalent Transcriptomic Metric for Diagnosing Surgical Sepsis and Estimating Mortality Among Critically Ill Patients

Detection of bacterial co-infections and prediction of fatal outcomes in COVID-19 patients presenting to the emergency department using a 29 mRNA host response classifier

Key Signature Genes of Early Terminal Granulocytic Differentiation Distinguish Sepsis From Systemic Inflammatory Response Syndrome on Intensive Care Unit Admission

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