Distinguishing septic shock from non-septic shock in postsurgical patients using gene expression

Martínez-Paz, Pedro; Aragón-Camino, Marta; Gómez-Sánchez, Esther; Lorenzo-López, Mario; Gómez-Pesquera, Estefanía; Fuentes, A. Fadrique; Liu, Pilar; Tamayo-Velasco, Álvaro; Ortega-Loubón, Christian; Martín-Fernández, Marta; Gonzalo-Benito, Hugo; García‐Morán, Emilio; Heredia-Rodríguez, María; Tamayo, Eduardo

doi:10.1016/j.jinf.2021.05.039

Cited by 34 publications

(28 citation statements)

References 43 publications

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“…To identify potential gene signatures associated with sepsis, we got two gene expression datasets (GSE154918 and GSE131761) [ 20 , 21 ] from the GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ), GSE154918 dataset as primary research data and GES131761 as supplementary data.…”

Section: Methodsmentioning

confidence: 99%

Identification of Nine mRNA Signatures for Sepsis Using Random Forest

Zhou

Dong²,

Wang

et al. 2022

Computational and Mathematical Methods in Medicine

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Sepsis has high fatality rates. Early diagnosis could increase its curating rates. There were no reliable molecular biomarkers to distinguish between infected and uninfected patients currently, which limit the treatment of sepsis. To this end, we analyzed gene expression datasets from the GEO database to identify its mRNA signature. First, two gene expression datasets (GSE154918 and GSE131761) were downloaded to identify the differentially expressed genes (DEGs) using Limma package. Totally 384 common DEGs were found in three contrast groups. We found that as the condition worsens, more genes were under disorder condition. Then, random forest model was performed with expression matrix of all genes as feature and disease state as label. After which 279 genes were left. We further analyzed the functions of 279 important DEGs, and their potential biological roles mainly focused on neutrophil threshing, neutrophil activation involved in immune response, neutrophil-mediated immunity, RAGE receptor binding, long-chain fatty acid binding, specific granule, tertiary granule, and secretory granule lumen. Finally, the top nine mRNAs (MCEMP1, PSTPIP2, CD177, GCA, NDUFAF1, CLIC1, UFD1, SEPT9, and UBE2A) associated with sepsis were considered as signatures for distinguishing between sepsis and healthy controls. Based on 5-fold cross-validation and leave-one-out cross-validation, the nine mRNA signature showed very high AUC.

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Section: Methodsmentioning

confidence: 99%

Identification of Nine mRNA Signatures for Sepsis Using Random Forest

Zhou

Dong²,

Wang

et al. 2022

Computational and Mathematical Methods in Medicine

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“…Overall, patients with sepsis and septic shock experience a sharp decline in health-related quality of life during ICU stays and increased rates of death in long-term care (9)(10)(11). Despite significant improvements in the diagnosis and management of sepsis, it remains a challenging clinical entity due to its variable aetiology and presentation, and diagnosis is often documented only after clinical deterioration during a hospital stay (12,13). Differential diagnosis is also difficult in patients with circulatory shock, especially when accompanied by other conditions, such as cardiac injury and hypovolemia and trauma, or in the absence of archetypal signs of infection, e.g., in young infants, the elderly, and the immunocompromised (14)(15)(16)(17).…”

Section: Introductionmentioning

confidence: 99%

Lactylated Histone H3K18 as a Potential Biomarker for the Diagnosis and Predicting the Severity of Septic Shock

Chu

Chang

et al. 2022

Front. Immunol.

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ObjectiveTo date, there are no studies regarding the lactylation profile and its role in critically ill patients. Thus, we aimed to examine expression of histone H3 lysine 18 (H3K18) lactylation and its role in patients with septic shock.MethodsThirteen healthy volunteers and 35 critically ill patients from the Department of Surgical Intensive Care Medicine, Beijing Hospital were enrolled in our study. Baseline information and clinical outcomes were obtained prospectively. Lactylation levels of all proteins and H3K18 from peripheral blood mononuclear (PBMC) were determined by western blotting and serum levels of inflammatory cytokines by flow cytometry. Arginase-1 (Arg1) and Krüppel-like factor-4 (Klf4) mRNA expression was evaluated by quantitative real-time PCR (qRT-PCR).ResultsLactylation was found to be an all-protein post-translational modification and was detected in PBMCs from both healthy volunteers and critically ill patients, with a significantly higher relative density in shock patients (t=2.172, P=0.045). H3K18la was expressed in all subjects, including healthy volunteers, with the highest level in septic shock patients (compared with non-septic shock patients, critically ill without shock patients and healthy volunteers P=0.033, 0.000 and 0.000, respectively). Furthermore, H3K18la protein expression correlated positively with APACHE II scores, SOFA scores on day 1, ICU stay, mechanical ventilation time and serum lactate (ρ=0.42, 0.63, 0.39, 0.51 and 0.48, respectively, ρ=0.012, 0.000, 0.019, 0.003 and 0.003, respectively). When we matched patients with septic shock and with non-septic shock according to severity, we found higher H3K18la levels in the former group (t=-2.208, P =0.040). Moreover, H3K18la exhibited a close correlation with procalcitonin levels (ρ=0.71, P=0.010). Patients with high H3K18la expression showed higher IL-2, IL-5, IL-6, IL-8, IL-10, IL-17, IFN-α levels (ρ=0.33, 0.37, 0.62, 0.55, 0.65, 0.49 and 0.374 respectively, P=0.024, 0.011, 0.000, 0.000, 0.000 and 0.000 respectively). H3K18la expression also displayed a positive correlation with the level of Arg1 mRNA (ρ=0.561, P=0.005).ConclusionsLactylation is an all-protein post-translational modification occurring in both healthy subjects and critically ill patients. H3K18la may reflect the severity of critical illness and the presence of infection. H3K18la might mediate inflammatory cytokine expression and Arg1 overexpression and stimulate the anti-inflammatory function of macrophages in sepsis.

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“…In a recent notable study on whole blood gene expression in postoperative patients admitted to the ICU, cases fulfilled sepsis-3 criteria for septic shock with microbiological culture confirmation of infection, and controls met the same criteria for shock but were not infected ( 62 ). Sequential discovery by microarray and validation by RT-PCR in independent cohorts identified a six-gene classifier, including the specific granule genes LCN2 , LTF , OLFM4 , and MMP8 , that was superior to CRP, PCT, and neutrophil counts.…”

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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Distinguishing septic shock from non-septic shock in postsurgical patients using gene expression

Cited by 34 publications

References 43 publications

Identification of Nine mRNA Signatures for Sepsis Using Random Forest

Identification of Nine mRNA Signatures for Sepsis Using Random Forest

Lactylated Histone H3K18 as a Potential Biomarker for the Diagnosis and Predicting the Severity of Septic Shock

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

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