Transcriptome analysis to explore the shared and distinct immune signature between severe COVID-19 and bacterial sepsis
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ABSTRACT:
PROVIDER: PRJNA858262 | ENA |
REPOSITORIES: ENA
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Project description:Background: COVID-19 and sepsis represent formidable public health challenges, characterized by incompletely elucidated molecular mechanisms. Elucidating the interplay between COVID-19 and sepsis, particularly in geriatric patients suffering from sepsis-induced acute respiratory distress syndrome (ARDS), is of paramount importance for identifying potential therapeutic interventions to mitigate hospitalization and mortality risks.We employed bioinformatics and systems biology approaches to identify hub genes, shared pathways, molecular biomarkers, and candidate therapeutics for managing COVID-19, sepsis, and sepsis-induced ARDS. We corroborated these hub genes utilizing murine sepsis-ARDS models and blood samples derived from geriatric patients afflicted by sepsis-induced ARDS.Results: Our investigation revealed 189 differentially expressed genes (DEGs) shared among COVID-19 and sepsis datasets. We constructed a protein-protein interaction network, unearthing pivotal hub genes and modules. Notably, nine hub genes displayed significant alterations and correlations with critical inflammatory mediators of pulmonary injury in murine septic lungs. Simultaneously, 12 displayed significant changes and correlations with a neutrophil-recruiting chemokine in geriatric patients with sepsis-induced ARDS. Of these, six hub genes (CD247, CD2, CD40LG, KLRB1, LCN2, RETN) showed significant alterations across COVID-19, sepsis, and geriatric sepsis-induced ARDS. Our single-cell RNA sequencing analysis of hub genes across 3 diverse immune cell types furnished insights into disease pathogenesis. Functional analysis underscored the interconnection between sepsis/sepsis-ARDS and COVID-19, enabling us to pinpoint potential therapeutic targets, transcription factor-gene interactions, DEG-microRNA co-regulatory networks, and prospective drug and chemical compound interactions involving hub genes.Our investigation offers potential therapeutic targets/biomarkers, sheds light on the immune response in geriatric patients with sepsis-induced ARDS, emphasizes the association between sepsis/sepsis-ARDS and COVID-19, and proposes novel avenues for targeted therapies.
2023-09-01 | GSE242127 | GEO
Project description:Although some studies reported the comprehensive mRNA expression analysis of coronavirus disease 2019 (COVID-19) using blood samples to understand its pathogenesis, the characteristics of RNA expression in COVID-19 and sepsis have not been compared. We compared the transcriptome expression of whole blood samples from patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and patients with sepsis caused by other bacteria who entered the intensive care unit to clarify the COVID-19-specific RNA expression and understand its pathogenesis. Transcriptomes related to mitochondria were upregulated in COVID-19, whereas those related to neutrophils were upregulated in sepsis. However, the transcriptomes related to neutrophils were upregulated in both COVID-19 and sepsis compared to in healthy controls, whereas the mitochondrial transcriptomes were upregulated in COVID-19 and downregulated in sepsis compared to in healthy controls. Moreover, sepsis showed sub-optimal intrinsic apoptotic features compared with COVID-19. The transcriptome expression of COVID-19 has been examined in vitro but has not been widely validated using human specimens. This study improves the understanding of the pathogenesis of COVID-19 and can contribute to the development of treatments.
2022-11-29 | GSE199816 | GEO
Project description:Severely-afflicted COVID-19 patients can exhibit disease manifestations representative of sepsis, including acute respiratory distress syndrome and multiple organ failure. We hypothesized that diagnostic tools used in managing all-cause sepsis, such as clinical criteria, biomarkers, and gene expression signatures, should extend to COVID-19 patients. Here we analyzed the whole blood transcriptome of 124 early (1-5 days post-hospital admission) and late (6-20 days post-admission) sampled patients with confirmed COVID-19 infections from hospitals in Quebec, Canada. Mechanisms associated with COVID-19 severity were identified between severity groups (ranging from mild disease to the requirement for mechanical ventilation and mortality), and established sepsis signatures were assessed for dysregulation. Specifically, gene expression signatures representing pathophysiological events, namely cellular reprogramming, organ dysfunction, and mortality, were significantly enriched and predictive of severity and lethality in COVID-19 patients. Mechanistic endotypes reflective of distinct sepsis aetiologies and therapeutic opportunities were also identified in subsets of patients, enabling prediction of potentially-effective repurposed drugs. The expression of sepsis gene expression signatures in severely-afflicted COVID-19 patients indicates that these patients should be classified as having severe sepsis. Accordingly, in severe COVID-19 patients, these signatures should be strongly considered for the mechanistic characterization, diagnosis, and guidance of treatment using repurposed drugs.
2022-12-18 | GSE221234 | GEO
Project description:Rationale: Sepsis is a leading cause of morbidity and mortality; early diagnosis and prediction of progression is difficult to determine. The integration of metabolomic and transcriptomic data in an experimental model of sepsis may be a novel method to identify molecular signatures of clinical sepsis. Objectives: Develop a biomarker panel for earlier diagnosis and prognostic characterization of sepsis patients to inform personalized clinical management and improve understanding of the pathophysiology of sepsis progression. Methods: Mild to severe sepsis, lung injury and death was recapitulated in Macaca fascicularis by intravenous inoculation of Escherichia coli. Plasma samples were obtained at time of challenge and at one, three, and five days later or time of euthanasia. Necropsy was performed and blood, lung, kidney and spleen samples were obtained. An integrative analysis of comprehensive metabolomic and transcriptomic datasets was performed to identify and parameterize a biomarker panel. Measurements and Main Results: Pathogen invasion, respiratory distress, lethargy and mortality was dose dependent. Severe infection and death were associated with metabolomic and transcriptomic changes indicative of mitochondrial, peroxisomal and liver dysfunction. Analysis of reciprocal pulmonary transcriptome and plasma metabolome data revealed an integrated host response that suggested dysregulated fatty acid catabolism resulting from peroxisome-proliferator activated receptor signaling. A representative 4-metabolite model effectively diagnosed sepsis in primates (AUC 0.966) and in two human sepsis cohorts (AUC=0.78 and 0.82). Conclusion: A model to guide early management of patients with sepsis was developed by analysis of reciprocal metabolomic and transcriptomic data in primates that diagnosed sepsis in humans. Transcriptomic analysis of lungs from Cynomolgus macaques challenged with E. coli
2015-07-03 | E-GEOD-59075 | biostudies-arrayexpress
Project description:We assayed leukocyte global gene expression for a prospective discovery cohort of 265 adult patients admitted to UK intensive care units with severe sepsis due to community acquired pneumonia.
2016-02-25 | E-MTAB-4421 | biostudies-arrayexpress
Project description:We assayed leukocyte global gene expression for a prospective validation cohort of 106 adult patients admitted to UK intensive care units with severe sepsis due to community acquired pneumonia.
2016-02-25 | E-MTAB-4451 | biostudies-arrayexpress
Project description:Rationale: Sepsis is a leading cause of morbidity and mortality; early diagnosis and prediction of progression is difficult to determine. The integration of metabolomic and transcriptomic data in an experimental model of sepsis may be a novel method to identify molecular signatures of clinical sepsis. Objectives: Develop a biomarker panel for earlier diagnosis and prognostic characterization of sepsis patients to inform personalized clinical management and improve understanding of the pathophysiology of sepsis progression. Methods: Mild to severe sepsis, lung injury and death was recapitulated in Macaca fascicularis by intravenous inoculation of Escherichia coli. Plasma samples were obtained at time of challenge and at one, three, and five days later or time of euthanasia. Necropsy was performed and blood, lung, kidney and spleen samples were obtained. An integrative analysis of comprehensive metabolomic and transcriptomic datasets was performed to identify and parameterize a biomarker panel. Measurements and Main Results: Pathogen invasion, respiratory distress, lethargy and mortality was dose dependent. Severe infection and death were associated with metabolomic and transcriptomic changes indicative of mitochondrial, peroxisomal and liver dysfunction. Analysis of reciprocal pulmonary transcriptome and plasma metabolome data revealed an integrated host response that suggested dysregulated fatty acid catabolism resulting from peroxisome-proliferator activated receptor signaling. A representative 4-metabolite model effectively diagnosed sepsis in primates (AUC 0.966) and in two human sepsis cohorts (AUC=0.78 and 0.82). Conclusion: A model to guide early management of patients with sepsis was developed by analysis of reciprocal metabolomic and transcriptomic data in primates that diagnosed sepsis in humans.
2015-07-03 | GSE59075 | GEO
Project description:Sensing of microbial products by innate immune cells skew their transcriptional program to optimize anti-microbial defences. Chromatin remodeling by histone deacetylases (HDACs) plays a fundamental role in tailoring gene expression. HDAC inhibitors are among the most promising anti-cancer drugs and possess intrinsic anti-inflammatory properties. Yet, the influence of HDAC inhibition on innate immune responses to microbial infection is unknown. Here we show that HDAC inhibitors repress the expression of less than 10% of the genes expressed at baseline in BM-derived macrophages. In sharp contrast, HDAC inhibitors strongly interfere with transcriptome remodeling induced by LPS and Pam3CSK4, affecting the expression of 30-70% of genes modulated by microbial stimuli. Strikingly, HDAC inhibitors target the expression of numerous genes involved in anti-microbial host defences, encoding for microbial sensors, cytokines, chemokines, growth factors and their receptors, adhesion and signaling molecules, and molecules involved in antigen processing and presentation. At the molecular level, HDAC inhibitors do not impair mitogen-activated protein kinase, NF-kB, interferon-related factor signal and STAT1 transduction pathways, but inhibit NF-kB p65 recruitment to the promoter region of HDAC inhibitor-sensitive genes. HDAC inhibitors also inhibit the response of mouse and human DCs, splenocytes and whole blood to a broad range of microbial products and microorganisms. In agreement with these in vitro findings, HDAC inhibitors increase bacterial burden and sensitize mice to sub-lethal infection with Klebsiella pneumoniae and Candida albicans. Conversely, HDAC inhibitors confer protection in models of Pam3CSK4-induced fulminant toxic shock and severe sepsis following cecal ligation and puncture. Overall, these data substantiate the concept of immunomodulation by HDAC inhibitors, and suggest that these drugs could represent efficacious adjunctive therapy of severe sepsis. Mus musculus cells were grown in presence of LPS or LPS + TSA and pam or pam + TSA and hybrydised against a cRNA pool UMRR (from Mus musculus cells).
2011-01-01 | E-GEOD-22409 | biostudies-arrayexpress
Project description:Here we recorded serum proteome profiles of 33 COVID-19 patients admitted to the ICU. We received, for most patients, blood samples just after admission and at two more later timepoints. We focused on serum proteins different in abundance between the group of survivors and non-survivors and observed that a rather small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, HRG and KNG1 were all more abundant in the survivors. The family of inter-α-trypsin inhibitors, ITIH1, ITIH2, ITIH3 and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also did show opposite trends in protein abundance during disease progression. This panel of eight proteins, complemented with a few more, may represent a panel for mortality risk assessment and eventually even for treatment, by administration of exogenous proteins possibly aiding survival. Such administration is not unprecedented, as administration of exogenous inter-α-trypsin inhibitors is already used in the treatment of patients with severe sepsis and Kawasaki disease. The mortality risk panel defined here is in excellent agreement with findings in two recent COVID-19 serum proteomics studies on independent cohorts, supporting our findings. This panel may not be unique for COVID-19, as some of the proteins here annotated as mortality risk factors have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria.
2021-07-05 | PXD024707 | Pride