Short-Term Effects of Sepsis and the Impact of Aging on the Transcriptional Profile of Different Brain Regions

Evaluating early lymphocyte-to-monocyte ratio as a predictive biomarker for delirium in older adult patients with sepsis: insights from a retrospective cohort analysis

Background

This study aims to explore the value of the Lymphocyte-to-Monocyte Ratio (LMR) in predicting delirium among older adult patients with sepsis.

Methods

Retrospective data were obtained from the MIMIC-IV database in accordance with the STROBE guidelines. Patients aged 65 and above, meeting the Sepsis 3.0 criteria, were selected for this study. Delirium was assessed using the Confusion Assessment Method for the ICU (CAM-ICU). Demographic information, comorbid conditions, severity of illness scores, vital sign measurements, and laboratory test results were meticulously extracted. The prognostic utility of the Lymphocyte-to-Monocyte Ratio (LMR) in predicting delirium was assessed through logistic regression models, which were carefully adjusted for potential confounding factors.

Results

In the studied cohort of 32,971 sepsis patients, 2,327 were identified as meeting the inclusion criteria. The incidence of delirium within this subgroup was observed to be 55%. A univariate analysis revealed a statistically significant inverse correlation between the Lymphocyte-to-Monocyte Ratio (LMR) and the risk of delirium (p < 0.001). Subsequent multivariate analysis, which accounted for comorbidities and illness severity scores, substantiated the role of LMR as a significant predictive marker. An optimized model, achieving the lowest Akaike Information Criterion (AIC), incorporated 17 variables and continued to demonstrate LMR as a significant prognostic factor (p < 0.01). Analysis of the Receiver Operating Characteristic (ROC) curve indicated a significant enhancement in the Area Under the Curve (AUC) upon the inclusion of LMR (p = 0.035).

Conclusion

The Lymphocyte-to-Monocyte Ratio (LMR) serves as a significant, independent prognostic indicator for the occurrence of delirium in older adult patients with sepsis. Integrating LMR into existing predictive models markedly improves the identification of patients at elevated risk, thereby informing and potentially guiding early intervention strategies.

Identification of IL-8 in CSF as a potential biomarker in sepsis-associated encephalopathy

BACKGROUND

Sepsis-associated encephalopathy (SAE) is frequently present at the acute and chronic phase of sepsis, which is characterized by delirium, coma, and cognitive dysfunction. Despite the increased morbidity and mortality of SAE, the pathogenesis of SAE remains unclear. This study aims to discover the potential biomarkers, so as to clear the pathogenesis potentially contributing to the development of SAE and provide new therapeutic strategies for the treatment of SAE.

METHODS

The GSE135838 dataset was obtained from the Gene Expression Omnibus (GEO) database and utilized for analysis the differentially expressed genes (DEGs). The DEGs were analyzed by limma package of R language and the extracellular protein-differentially expressed genes (EP-DEGs) were screened by the Human Protein Atlas (HPA) and UniProt database. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Key EP-DEGs levels were detected in the cerebrospinal fluid (CSF) of SAE patients and non-sepsis patients with critical illness. ROC curve was used to evaluate the diagnostic of SAE.

RESULTS

We screened 82 EP-DEGs from DEGs. EP-DEGs were enriched in cytokine-cytokine receptor interaction, IL-17 signaling pathway and NOD-like receptor signaling pathway. We identified 2 key extracellular proteins IL-1B and IL-8. We clinically verified that IL-6 and IL-8 levels were increased in CSF of SAE patients and CSF IL-8 (AUC = 0.882, 95 % CI = 0.775-0.988) had a higher accuracy in the diagnosis of SAE than CSF IL-6 (AUC = 0.824, 95 % CI = 0.686-0.961). Furthermore, we found that the IL-8 levels in CSF might not associated with Glasgow Coma Scale (GCS) scores of SAE patients.

CONCLUSION

IL-8 may be the key extracellular cytokine in the pathogenesis of SAE. Bioinformatics methods were used to explore the biomarkers of SAE and validated the results in clinical samples. Our findings indicate that the IL-8 in CSF might be the potential diagnostic biomarker and therapeutic target in SAE.

S100A8/A9: An emerging player in sepsis and sepsis-induced organ injury

Sepsis, the foremost contributor to mortality in intensive care unit patients, arises from an uncontrolled systemic response to invading infections, resulting in extensive harm across multiple organs and systems. Recently, S100A8/A9 has emerged as a promising biomarker for sepsis and sepsis-induced organ injury, and targeting S100A8/A9 appeared to ameliorate inflammation-induced tissue damage and improve adverse outcomes. S100A8/A9, a calcium-binding heterodimer mainly found in neutrophils and monocytes, serves as a causative molecule with pro-inflammatory and immunosuppressive properties, which are vital in the pathogenesis of sepsis. Therefore, improving our comprehension of how S100A8/A9 acts as a pathological player in the development of sepsis is imperative for advancing research on sepsis. Our review is the first-to the best of our knowledge-to discuss the biology of S100A8/A9 and its release mechanisms, summarize recent advances concerning the vital roles of S100A8/A9 in sepsis and the consequential organ damage, and underscore its potential as a promising diagnostic biomarker and therapeutic target for sepsis.

Paediatric sepsis-associated encephalopathy (SAE): a comprehensive review

Sepsis-associated encephalopathy (SAE) is one of the most common types of organ dysfunction without overt central nervous system (CNS) infection. It is associated with higher mortality, low quality of life, and long-term neurological sequelae, its mortality in patients diagnosed with sepsis, progressing to SAE, is 9% to 76%. The pathophysiology of SAE is still unknown, but its mechanisms are well elaborated, including oxidative stress, increased cytokines and proinflammatory factors levels, disturbances in the cerebral circulation, changes in blood-brain barrier permeability, injury to the brain's vascular endothelium, altered levels of neurotransmitters, changes in amino acid levels, dysfunction of cerebral microvascular cells, mitochondria dysfunction, activation of microglia and astrocytes, and neuronal death. The diagnosis of SAE involves excluding direct CNS infection or other types of encephalopathies, which might hinder its early detection and appropriate implementation of management protocols, especially in paediatric patients where only a few cases have been reported in the literature. The most commonly applied diagnostic tools include electroencephalography, neurological imaging, and biomarker detection. SAE treatment mainly focuses on managing underlying conditions and using antibiotics and supportive therapy. In contrast, sedative medication is used judiciously to treat those showing features such as agitation. The most widely used medication is dexmedetomidine which is neuroprotective by inhibiting neuronal apoptosis and reducing a sepsis-associated inflammatory response, resulting in improved short-term mortality and shorter time on a ventilator. Other agents, such as dexamethasone, melatonin, and magnesium, are also being explored in vivo and ex vivo with encouraging results. Managing modifiable factors associated with SAE is crucial in improving generalised neurological outcomes. From those mentioned above, there are still only a few experimentation models of paediatric SAE and its treatment strategies. Extrapolation of adult SAE models is challenging because of the evolving brain and technical complexity of the model being investigated. Here, we reviewed the current understanding of paediatric SAE, its pathophysiological mechanisms, diagnostic methods, therapeutic interventions, and potential emerging neuroprotective agents.

Exploring molecular signatures related to the mechanism of aging in different brain regions by integrated bioinformatics

The mechanism of brain aging is not fully understood. Few studies have attempted to identify molecular changes using bioinformatics at the subregional level in the aging brain. This study aimed to identify the molecular signatures and key genes involved in aging, depending on the brain region. Differentially expressed genes (DEGs) associated with aging of the cerebral cortex (CX), hippocampus (HC), and cerebellum (CB) were identified based on five datasets from the Gene Expression Omnibus (GEO). The molecular signatures of aging were explored using functional and pathway analyses. Hub genes of each brain region were determined by protein-protein interaction network analysis, and commonly expressed DEGs (co-DEGs) were also found. Gene-microRNAs (miRNAs) and gene-disease interactions were constructed using online databases. The expression levels and regional specificity of the hub genes and co-DEGs were validated using animal experiments. In total, 32, 293, and 141 DEGs were identified in aging CX, HC, and CB, respectively. Enrichment analysis indicated molecular changes related to leukocyte invasion, abnormal neurotransmission, and impaired neurogenesis due to inflammation as the major signatures of the CX, HC, and CB. Itgax is a hub gene of cortical aging. Zfp51 and Zfp62 were identified as hub genes involved in hippocampal aging. Itgax and Cxcl10 were identified as hub genes involved in cerebellar aging. S100a8 was the only co-DEG in all three regions. In addition, a series of molecular changes associated with inflammation was observed in all three brain regions. Several miRNAs interact with hub genes and S100a8. The change in gene levels was further validated in an animal experiment. Only the upregulation of Zfp51 and Zfp62 was restricted to the HC. The molecular signatures of aging exhibit regional differences in the brain and seem to be closely related to neuroinflammation. Itgax, Zfp51, Zfp62, Cxcl10, and S100a8 may be key genes and potential targets for the prevention of brain aging.

Analysis of signature genes and association with immune cells infiltration in pediatric septic shock

Background

Early diagnosis of septic shock in children is critical for prognosis. This study committed to investigate the signature genes and their connection with immune cells in pediatric septic shock.

Methods

We screened a dataset of children with septic shock from the GEO database and analyzed differentially expressed genes (DEGs). Functional enrichment analysis was performed for these DEGs. Weighted gene co-expression network analysis (WCGNA) was used to screen the key modules. Least absolute shrinkage and selection operator (LASSO) and random forest analysis were finally applied to identify the signature genes. Then gene set enrichment analysis (GSEA) was exerted to explore the signaling pathways related to the hub genes. And the immune cells infiltration was subsequently classified via using CIBERSORT.

Results

A total of 534 DEGs were screened from GSE26440. The data then was clustered into 17 modules via WGCNA, which MEgrey module was significantly related to pediatric septic shock (cor=-0.62, p<0.0001). LASSO and random forest algorithms were applied to select the signature genes, containing UPP1, S100A9, KIF1B, S100A12, SLC26A8. The receiver operating characteristic curve (ROC) of these signature genes was 0.965, 0.977, 0.984, 0.991 and 0.989, respectively, which were verified in the external dataset from GSE13904. GSEA analysis showed these signature genes involve in positively correlated fructose and mannose metabolism and starch and sucrose metabolism signaling pathway. CIBERSORT suggested these signature genes may participate in immune cells infiltration.

Conclusion

UPP1, S100A9, KIF1B, S100A12, SLC26A8 emerge remarkable diagnostic performance in pediatric septic shock and involved in immune cells infiltration.

Identification of biomarkers and the mechanisms of multiple trauma complicated with sepsis using metabolomics

Sepsis after trauma increases the risk of mortality rate for patients in intensive care unit (ICUs). Currently, it is difficult to predict outcomes in individual patients with sepsis due to the complexity of causative pathogens and the lack of specific treatment. This study aimed to identify metabolomic biomarkers in patients with multiple trauma and those with multiple trauma accompanied with sepsis. Therefore, the metabolic profiles of healthy persons designated as normal controls (NC), multiple trauma patients (MT), and multiple trauma complicated with sepsis (MTS) (30 cases in each group) were analyzed with ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS)-based untargeted plasma metabolomics using collected plasma samples. The differential metabolites were enriched in amino acid metabolism, lipid metabolism, glycometabolism and nucleotide metabolism. Then, nine potential biomarkers, namely, acrylic acid, 5-amino-3-oxohexanoate, 3b-hydroxy-5-cholenoic acid, cytidine, succinic acid semialdehyde, PE [P-18:1(9Z)/16:1(9Z)], sphinganine, uracil, and uridine, were found to be correlated with clinical variables and validated using receiver operating characteristic (ROC) curves. Finally, the three potential biomarkers succinic acid semialdehyde, uracil and uridine were validated and can be applied in the clinical diagnosis of multiple traumas complicated with sepsis.

Discovery of novel targets in a complex regional pain syndrome mouse model by transcriptomics: TNF and JAK-STAT pathways

Complex Regional Pain Syndrome (CRPS) represents severe chronic pain, hypersensitivity, and inflammation induced by sensory-immune-vascular interactions after a small injury. Since the therapy is unsatisfactory, there is a great need to identify novel drug targets. Unbiased transcriptomic analysis of the dorsal root ganglia (DRG) was performed in a passive transfer-trauma mouse model, and the predicted pathways were confirmed by pharmacological interventions. In the unilateral L3-5 DRGs 125 genes were differentially expressed in response to plantar incision and injecting IgG of CRPS patients. These are related to inflammatory and immune responses, cytokines, chemokines and neuropeptides. Pathway analysis revealed the involvement of Tumor Necrosis Factor (TNF) and Janus kinase (JAK-STAT) signaling. The relevance of these pathways was proven by abolished CRPS IgG-induced hyperalgesia and reduced microglia and astrocyte markers in pain-associated central nervous system regions after treatment with the soluble TNF alpha receptor etanercept or JAK inhibitor tofacitinib. These results provide the first evidence for CRPS-related neuroinflammation and abnormal cytokine signaling at the level of the primary sensory neurons in a translational mouse model and suggest that etanercept and tofacitinib might have drug repositioning potentials for CRPS-related pain.

Revealing potential diagnostic gene biomarkers of septic shock based on machine learning analysis

Background

Sepsis is an inflammatory response caused by infection with pathogenic microorganisms. The body shock caused by it is called septic shock. In view of this, we aimed to identify potential diagnostic gene biomarkers of the disease.

Material and methods

Firstly, mRNAs expression data sets of septic shock were retrieved and downloaded from the GEO (Gene Expression Omnibus) database for differential expression analysis. Functional enrichment analysis was then used to identify the biological function of DEmRNAs (differentially expressed mRNAs). Machine learning analysis was used to determine the diagnostic gene biomarkers for septic shock. Thirdly, RT-PCR (real-time polymerase chain reaction) verification was performed. Lastly, GSE65682 data set was utilized to further perform diagnostic and prognostic analysis of identified superlative diagnostic gene biomarkers.

Results

A total of 843 DEmRNAs, including 458 up-regulated and 385 down-regulated DEmRNAs were obtained in septic shock. 15 superlative diagnostic gene biomarkers (such as RAB13, KIF1B, CLEC5A, FCER1A, CACNA2D3, DUSP3, HMGN3, MGST1 and ARHGEF18) for septic shock were identified by machine learning analysis. RF (random forests), SVM (support vector machine) and DT (decision tree) models were used to construct classification models. The accuracy of the DT, SVM and RF models were very high. Interestingly, the RF model had the highest accuracy. It is worth mentioning that ARHGEF18 and FCER1A were related to survival. CACNA2D3 and DUSP3 participated in MAPK signaling pathway to regulate septic shock.

Conclusion

Identified diagnostic gene biomarkers may be helpful in the diagnosis and therapy of patients with septic shock.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07056-4.

Acute Systemic Inflammatory Response Alters Transcription Profile of Genes Related to Immune Response and Ca2+ Homeostasis in Hippocampus; Relevance to Neurodegenerative Disorders

Acute systemic inflammatory response (SIR) triggers an alteration in the transcription of brain genes related to neuroinflammation, oxidative stress and cells death. These changes are also characteristic for Alzheimer’s disease (AD) neuropathology. Our aim was to evaluate gene expression patterns in the mouse hippocampus (MH) by using microarray technology 12 and 96 h after SIR evoked by lipopolysaccharide (LPS). The results were compared with microarray analysis of human postmortem hippocampal AD tissues. It was found that 12 h after LPS administration the expression of 231 genes in MH was significantly altered (FC > 2.0); however, after 96 h only the S100a8 gene encoding calgranulin A was activated (FC = 2.9). Gene ontology enrichment analysis demonstrated the alteration of gene expression related mostly to the immune-response including the gene Lcn2 for Lipocalin 2 (FC = 237.8), involved in glia neurotoxicity. The expression of genes coding proteins involved in epigenetic regulation, histone deacetylases (Hdac4,5,8,9,11) and bromo- and extraterminal domain protein Brd3 were downregulated; however, Brd2 was found to be upregulated. Remarkably, the significant increase in expression of Lcn2, S100a8, S100a9 and also Saa3 and Ch25h, was found in AD brains suggesting that early changes of immune-response genes evoked by mild SIR could be crucial in AD pathogenesis.

Antimicrobial peptides in the gut-brain axis: A straightforward review to unravel some missing links

Antimicrobial peptides (AMPs) are intriguing molecules, able to directly kill several microorganisms and to regulate multiple aspects of the immune response. Despite the extensive studies on the role of AMPs in the epithelial barrier, placing them as a pivotal line of defense against pathogen invasion, little attention has been directed to their role in the maintenance and modulation of the gut microbiota and, by consequence, of the homeostasis of extra intestinal tissues. Here, we review the recent literature about the microbiome-gut-brain axis, focusing on the role of AMPs in this scenario. We provide a straightforward revision of current data in order to provide an overview of the subject, discussing more in depth some points that, in our opinion, are crucial and have received little attention.

Sepsis-associated encephalopathy and septic encephalitis: an update

INTRODUCTION

Sepsis-associated encephalopathy (SAE) and septic encephalitis (SE) are associated with increased mortality, long-term cognitive impairment, and focal neurological deficits.

AREAS COVERED

The PUBMED database was searched 2016-2020. The clinical manifestation of SAE is delirium, SE additionally is characterized by focal neurological symptoms. SAE is caused by inflammation with endothelial/microglial activation, increase of permeability of the blood-brain-barrier, hypoxia, imbalance of neurotransmitters, glial activation, axonal, and neuronal loss. Septic-embolic (SEE) and septic-metastatic encephalitis (SME) are characterized by focal ischemia (SEE) and small abscesses (SME). The continuum between SAE, SME, and SEE is documented by imaging techniques and autopsies. The backbone of treatment is rapid optimum antibiotic therapy. Experimental approaches focus on modulation of inflammation, stabilization of the blood-brain barrier, and restoration of membrane/mitochondrial function.

EXPERT OPINION

The most promising diagnostic approaches are new imaging techniques. The most important measure to fight delirium remains establishment of daily structure and adequate sensory stimuli. Dexmedetomidine and melatonin appear to reduce the frequency of delirium, their efficacy in SAE and SE remains to be established. Drugs already licensed for other indications or available as food supplements which may be effective in SAE are statins, L-DOPA/benserazide, β-hydroxybutyrate, palmitoylethanolamide, and tetracyclines or other bactericidal non-lytic antibiotics.