Hyperglycaemia in critically ill patients: the immune system's sweet tooth.
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ABSTRACT:
SUBMITTER: van Niekerk G
PROVIDER: S-EPMC5541425 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:Objective: COVID19 is caused by the SARS-CoV-2 virus and has been associated with severe inflammation leading to organ dysfunction and mortality. Our aim was to profile the transcriptome in leukocytes from critically ill ICU patients positive for COVID19 vs. those negative for COVID19 to better understand the COVID19 associated host response. Design: Transcriptome profiling of buffy coat cells via ribonucleic acid sequencing (RNAseq) at the time of admission to the ICU. Setting: Tertiary care ICU and academic laboratory. Subjects: All patients admitted to the ICU suspected of being infected with SARS-CoV-2, using standardized hospital screening methodologies, had blood samples collected at the time of admission to the ICU. Interventions: None. Measurement and Main Results: Age- and sex-matched ICU patients that were either COVID19+ (PCR positive, 2 genes) or COVID19- (PCR negative) were enrolled. Cohorts were well-balanced with the exception that COVID19- patients had significantly higher total white blood cell counts and circulating neutrophils and COVID19+ patients were more likely to suffer bilateral pneumonia compared to COVID19- patients. Further, the mortality rate for this cohort of COVID19+ ICU patients was 29%. Transcriptional analysis revealed that when compared to COVID19- patients, the altered transcriptional responses of leukocytes in critically ill COVID19+ ICU patients appeared to be associated with multiple interrelated outcomes, including but not limited to robust interferon (IFN)-associated transcriptional responses, a marked decrease in the transcriptional activity of genes contributing to protein synthesis and the dysregulated expression of genes that contribute to coagulation, platelet activation, Toll-like receptor activation, neurotrophin signaling, and protein SUMOylation/ubiquitination. Conclusions: COVID19+ patients on day 1 of admission to the ICU display a unique leukocyte transcriptional profile that distinguishes them from COVID19- patients. Identification of this profile provides guidance for future targeted studies exploring novel prognostic/therapeutic aspects of COVID19.
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Project description:The host response in critically ill patients with sepsis, septic shock remains poorly defined. Considerable research has been conducted to accurately distinguish patients with sepsis from those with non-infectious causes of disease. Technological innovations have positioned systems biology at the forefront of biomarker discovery. Analysis of the whole-blood leukocyte transcriptome enables the assessment of thousands of molecular signals beyond simply measuring several proteins in plasma, which for use as biomarkers is important since combinations of biomarkers likely provide more diagnostic accuracy than the measurement of single ones or a few. Evidence suggests that genome-wide transcriptional profiling of blood leukocytes can assist in differentiating between infection and non-infectious causes of severe disease. Of importance, RNA biomarkers have the potential advantage that they can be measured reliably in rapid quantitative reverse transcriptase polymerase chain reaction (qRT-PCR)-based point of care tests. PAXgene blood RNA was isolated at intensive-care unit (ICU) admission and throughout ICU length-of-stay. Through the use of genome-wide microarrays we aimed to identify molecular features that enbale the adequate discrimination of infectious and non-infectious sources of critical illness. Moreover, biological pathway analysis was used to tease out the most relevant biological units in sepsis and septic shock.
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Project description:Hyperglycemia frequently occurs with acute medical illness, especially among patients with cardiovascular disease, and has been linked to increased morbidity and mortality in critically ill patients. Even patients who are normoglycemic can develop hyperglycemia in response to acute metabolic stress. An expanding body of literature describes the benefits of normalizing hyperglycemia with insulin therapy in hospitalized patients. As a result, both the American Diabetes Association and the American College of Endocrinology have developed guidelines for optimal control of hyperglycemia, specifically targeting critically ill, hospitalized patients. Conventional blood glucose values of 140-180 mg/dL are considered desirable and safely achievable in most patients. More aggressive control to <110 mg/dL remains controversial, but has shown benefits in certain patients, such as those in surgical intensive care. Intravenous infusion is often used for initial insulin administration, which can then be transitioned to subcutaneous insulin therapy in those patients who require continued insulin maintenance. This article reviews the data establishing the link between hyperglycemia and its risks of morbidity and mortality, and describes strategies that have proven effective in maintaining glycemic control in high-risk hospitalized patients.
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Project description:Hyperglycemia is common in critically ill patients and can be caused by various mechanisms, including nutrition, medications, and insufficient insulin. In the past, hyperglycemia was thought to be an adaptive response to stress, but hyperglycemia is no longer considered a benign condition in patients with critical illnesses. Indeed, hyperglycemia can increase morbidity and mortality in critically ill patients. Correction of hyperglycemia may improve clinical outcomes. To date, a definite answer with regard to glucose management in general intensive care unit patients, including treatment thresholds and glucose target is undetermined. Meta-analyses of randomized controlled trials suggested no survival benefit of tight glycemic control and a significantly increased incidence of hypoglycemia. Studies have shown a J- or U-shaped relationship between average glucose values and mortality; maintaining glucose levels between 100 and 150 mg/dL was likely to be associated with the lowest mortality rates. Recent studies have shown glycemic control < 180 mg/dL is not inferior to near-normal glycemia in critically ill patients and is clearly safer. Glycemic variability is also an important aspect of glucose management in the critically ill patients. Higher glycemic variability may increase the mortality rate, even in patients with the same mean glucose level. Decreasing glucose variability is an important issue for glycemic control in critically ill patients. Continuous measurements with automatic closed-loop systems could be considered to ensure that blood glucose levels are controlled within a specific range and with minimal variability.
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Project description:Sepsis is a frequent complication in critically ill patients and highly heterogeneous that is associated with high morbidity and mortality rates, especially in the elderly population. Utilizing RNA-Sequencing (RNA-Seq) to analysis biological pathways is widely used in clinical and molecular genetics studies, but in elderly patients with sepsis are still lacking. Hence, we aim to investigate the mortality-relevant biological features and transcriptomic features in elderly patients who were admitted to intensive care unit (ICU) for sepsis.
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Project description:The PREVAIL study was a Phase II/III randomized controlled trial examining the use of lactoferrin to prevent nosocomial infections in critically ill patients undergoing mechanical ventilation. Gene expression data was generated from a consecutive subset of patients at the lead study site. We used the Affymetrix PrimeView array to generate expression data at various time points during the ICU stay.
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Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. The study included seventy-two critically ill patients admitted to the intensive care unit (ICU) of Nepean Hospital, Sydney, Australia. Of these, fifty-five patients were diagnosed to have sepsis, as confirmed by microbiological culture. The remaining seventeen patients did not have sepsis and were therefore used as controls. The study was approved by the hospital ethics committee and informed consent was obtained from all patients or their relatives. Patient Samples. Whole blood was taken from each patient on admission to ICU. Neutrophils were separated from whole blood using density-gradient separation with Ficoll-PaqueP P(Amersham). Subsequent neutrophil RNA extraction was performed using guanidinium thiocyanate (Ambion). Microarray Experiment. The neutrophil RNA was converted to cDNA, fluorescently labeled and hybridized to its complimentary sequences on the microarray (Invitrogen). The fluorescent signals on each micrroarray were captured using the GenePix 4000B laser scanner (Axon Instruments). Expression level of each gene was represented by the intensity of its fluorescent signal. Data Extraction. All signal intensity values were processed using background-subtraction method. Prior to analysis, all values were log-transformed and normalized by fitting a print-tip group Lowess curve. Normalization minimizes bias due to dye chemistry, signal intensity or location of a gene on the array. It ensures the detection of genes that are truly differentially expressed, instead of those caused by experimental artifacts or variation in the hybridization process. After normalization, genes that had more than 50% of data missing were removed. We then selected genes that had at least 80% of the data showing two-fold changes from the geneâs median values. After filtering, 1617 genes were available for further analysis.
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