Epigenetic biomarkers for human sepsis and septic shock: insights from immunosuppression

ncRS: A resource of non-coding RNAs in sepsis

Sepsis, a life-threatening condition triggered by the body's response to infection, presents a significant global healthcare challenge characterized by disarrayed host responses, widespread inflammation, organ impairment, and heightened mortality rates. This study introduces the ncRS database (http://www.ncrdb.cn), a meticulously curated repository housing 1144 experimentally validated non-coding RNAs (ncRNAs) intricately linked with sepsis. ncRS offers comprehensive RNA data, exhaustive experimental insights, and integrated annotations from diverse databases. This resource empowers researchers and clinicians to decipher ncRNAs' roles in sepsis pathogenesis, potentially identifying vital biomarkers for early diagnosis and prognosis, thus facilitating personalized treatments.

Nanomaterial-based methods for sepsis management

Sepsis is a serious disease caused by an impaired host immune response to infection, resulting in organ dysfunction, tissue damage and is responsible for high in-hospital mortality (approximately 20%). Recently, WHO documented sepsis as a global health priority. Nevertheless, there is still no effective and specific therapy for clinically detecting sepsis. Nanomaterial-based approaches have appeared as promising tools for identifying bacterial infections. In this review, recent biosensors are introduced and summarized as nanomaterial-based platforms for sepsis management and severe complications. Biosensors can be used as tools for the diagnosis and treatment of sepsis and as nanocarriers for drug delivery. In general, diagnostic methods for sepsis-associated bacteria, biosensors developed for this purpose are presented in detail, and their strengths and weaknesses are discussed. In other words, readers of this article will gain a comprehensive understanding of biosensors and their applications in sepsis management.

Alterations in leukocyte DNA methylome are associated to immunosuppression in severe clinical phenotypes of septic patients

Introduction

Sepsis patients experience a complex interplay of host pro- and anti-inflammatory processes which compromise the clinical outcome. Despite considering the latest clinical and scientific research, our comprehension of the immunosuppressive events in septic episodes remains incomplete. Additionally, a lack of data exists regarding the role of epigenetics in modulating immunosuppression, subsequently impacting patient survival.

Methods

To advance the current understanding of the mechanisms underlying immunosuppression, in this study we explored the dynamics of DNA methylation using the Infinium Methylation EPIC v1.0 BeadChip Kit in leukocytes from patients suffering from sepsis, septic shock, and critically ill patients as controls, within the first 24 h after admission in the Intensive Care Unit of a tertiary hospital.

Results and discussion

Employing two distinct analysis approaches (DMRcate and mCSEA) in comparing septic shock and critically ill patients, we identified 1,256 differentially methylated regions (DMRs) intricately linked to critical immune system pathways. The examination of the top 100 differentially methylated positions (DMPs) between septic shock and critically ill patients facilitated a clear demarcation among the three patient groups. Notably, the top 6,657 DMPs exhibited associations with organ dysfunction and lactate levels. Among the individual genes displaying significant differential methylation, IL10, TREM1, IL1B, and TNFAIP8 emerged with the most pronounced methylation alterations across the diverse patient groups when subjected to DNA bisulfite pyrosequencing analysis. These findings underscore the dynamic nature of DNA methylation profiles, highlighting the most pronounced alterations in patients with septic shock, and revealing their close association with the disease.

Identification of Potential Biomarkers of Septic Shock Based on Pathway and Transcriptome Analyses of Immune-Related Genes

Immunoregulation is crucial to septic shock (SS) but has not been clearly explained. Our aim was to explore potential biomarkers for SS by pathway and transcriptional analyses of immune-related genes to improve early detection. GSE57065 and GSE95233 microarray data were used to screen differentially expressed genes (DEGs) in SS. Gene Ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses of DEGs were performed, and correlations between immune cell and pathway enrichment scores were analyzed. The predictive value of candidate genes was evaluated by receiver operating characteristic (ROC) curves. GSE66099, GSE4607, and GSE13904 datasets were used for external validation. Blood samples from six patients and six controls were collected for validation by qRT-PCR and western blotting. In total, 550 DEGs in SS were identified; these genes were involved in the immune response, inflammation, and infection. Immune-related pathways and levels of infiltration of CD4 + TCM, CD8 + T cells, and preadipocytes differed between SS cases and controls. Seventeen genes were identified as potential biomarkers of SS (areas under ROC curves >0.9). The downregulation of CD8A, CD247, CD3G, LCK, and HLA-DRA in SS was experimentally confirmed. We identified several immune-related biomarkers in SS that may improve early identification of disease risk.

Identification and validation of a novel mitochondrion-related gene signature for diagnosis and immune infiltration in sepsis

Background

Owing to the complex pathophysiological features and heterogeneity of sepsis, current diagnostic methods are not sufficiently precise or timely, causing a delay in treatment. It has been suggested that mitochondrial dysfunction plays a critical role in sepsis. However, the role and mechanism of mitochondria-related genes in the diagnostic and immune microenvironment of sepsis have not been sufficiently investigated.

Methods

Mitochondria-related differentially expressed genes (DEGs) were identified between human sepsis and normal samples from GSE65682 dataset. Least absolute shrinkage and selection operator (LASSO) regression and the Support Vector Machine (SVM) analyses were carried out to locate potential diagnostic biomarkers. Gene ontology and gene set enrichment analyses were conducted to identify the key signaling pathways associated with these biomarker genes. Furthermore, correlation of these genes with the proportion of infiltrating immune cells was estimated using CIBERSORT. The expression and diagnostic value of the diagnostic genes were evaluated using GSE9960 and GSE134347 datasets and septic patients. Furthermore, we established an in vitro sepsis model using lipopolysaccharide (1 µg/mL)-stimulated CP-M191 cells. Mitochondrial morphology and function were evaluated in PBMCs from septic patients and CP-M191 cells, respectively.

Results

In this study, 647 mitochondrion-related DEGs were obtained. Machine learning confirmed six critical mitochondrion-related DEGs, including PID1, CS, CYP1B1, FLVCR1, IFIT2, and MAPK14. We then developed a diagnostic model using the six genes, and receiver operating characteristic (ROC) curves indicated that the novel diagnostic model based on the above six critical genes screened sepsis samples from normal samples with area under the curve (AUC) = 1.000, which was further demonstrated in the GSE9960 and GSE134347 datasets and our cohort. Importantly, we also found that the expression of these genes was associated with different kinds of immune cells. In addition, mitochondrial dysfunction was mainly manifested by the promotion of mitochondrial fragmentation (p<0.05), impaired mitochondrial respiration (p<0.05), decreased mitochondrial membrane potential (p<0.05), and increased reactive oxygen species (ROS) generation (p<0.05) in human sepsis and LPS-simulated in vitro sepsis models.

Conclusion

We constructed a novel diagnostic model containing six MRGs, which has the potential to be an innovative tool for the early diagnosis of sepsis.

The epigenetic legacy of ICU feeding and its consequences

PURPOSE OF REVIEW

Many critically ill patients face physical, mental or neurocognitive impairments up to years later, the etiology remaining largely unexplained. Aberrant epigenetic changes have been linked to abnormal development and diseases resulting from adverse environmental exposures like major stress or inadequate nutrition. Theoretically, severe stress and artificial nutritional management of critical illness thus could induce epigenetic changes explaining long-term problems. We review supporting evidence.

RECENT FINDINGS

Epigenetic abnormalities are found in various critical illness types, affecting DNA-methylation, histone-modification and noncoding RNAs. They at least partly arise de novo after ICU-admission. Many affect genes with functions relevant for and several associate with long-term impairments. As such, de novo DNA-methylation changes in critically ill children statistically explained part of their disturbed long-term physical/neurocognitive development. These methylation changes were in part evoked by early-parenteral-nutrition (early-PN) and statistically explained harm by early-PN on long-term neurocognitive development. Finally, long-term epigenetic abnormalities beyond hospital-discharge have been identified, affecting pathways highly relevant for long-term outcomes.

SUMMARY

Epigenetic abnormalities induced by critical illness or its nutritional management provide a plausible molecular basis for their adverse effects on long-term outcomes. Identifying treatments to further attenuate these abnormalities opens perspectives to reduce the debilitating legacy of critical illness.

A summary of the current diagnostic methods for, and exploration of the value of microRNAs as biomarkers in, sepsis-associated encephalopathy

Sepsis-associated encephalopathy (SAE) is an acute neurological deficit caused by severe sepsis without signs of direct brain infection, characterized by the systemic inflammation and disturbance of the blood-brain barrier. SAE is associated with a poor prognosis and high mortality in patients with sepsis. Survivors may exhibit long-term or permanent sequelae, including behavioral changes, cognitive impairment, and decreased quality of life. Early detection of SAE can help ameliorate long-term sequelae and reduce mortality. Half of the patients with sepsis suffer from SAE in the intensive care unit, but its physiopathological mechanism remains unknown. Therefore, the diagnosis of SAE remains a challenge. The current clinical diagnosis of SAE is a diagnosis of exclusion; this makes the process complex and time-consuming and delays early intervention by clinicians. Furthermore, the scoring scales and laboratory indicators involved have many problems, including insufficient specificity or sensitivity. Thus, a new biomarker with excellent sensitivity and specificity is urgently needed to guide the diagnosis of SAE. MicroRNAs have attracted attention as putative diagnostic and therapeutic targets for neurodegenerative diseases. They exist in various body fluids and are highly stable. Based on the outstanding performance of microRNAs as biomarkers for other neurodegenerative diseases, it is reasonable to infer that microRNAs will be excellent biomarkers for SAE. This review explores the current diagnostic methods for sepsis-associated encephalopathy (SAE). We also explore the role that microRNAs could play in SAE diagnosis and if they can be used to make the SAE diagnosis faster and more specific. We believe that our review makes a significant contribution to the literature because it summarizes some of the important diagnostic methods for SAE, highlighting their advantages and disadvantages in clinical use, and could benefit the field as it highlights the potential of miRNAs as SAE diagnostic markers.

Cross-tissue correlations of genome-wide DNA methylation in Japanese live human brain and blood, saliva, and buccal epithelial tissues

Neuroepigenetics considers genetic sequences and the interplay with environmental influences to elucidate vulnerability risk for various neurological and psychiatric disorders. However, evaluating DNA methylation of brain tissue is challenging owing to the issue of tissue specificity. Consequently, peripheral surrogate tissues were used, resulting in limited progress compared with other epigenetic studies, such as cancer research. Therefore, we developed databases to establish correlations between the brain and peripheral tissues in the same individuals. Four tissues, resected brain tissue, blood, saliva, and buccal mucosa (buccal), were collected from 19 patients (aged 13-73 years) who underwent neurosurgery. Moreover, their genome-wide DNA methylation was assessed using the Infinium HumanMethylationEPIC BeadChip arrays to determine the cross-tissue correlation of each combination. These correlation analyses were conducted with all methylation sites and with variable CpGs, and with when these were adjusted for cellular proportions. For the averaged data for each CpG across individuals, the saliva-brain correlation (r = 0.90) was higher than that for blood-brain (r = 0.87) and buccal-brain (r = 0.88) comparisons. Among individual CpGs, blood had the highest proportion of CpGs correlated to the brain at nominally significant levels (19.0%), followed by saliva (14.4%) and buccal (9.8%). These results were similar to the previous IMAGE-CpG results; however, cross-database correlations of the correlation coefficients revealed a relatively low (brain vs. blood: r = 0.27, saliva: r = 0.18, and buccal: r = 0.24). To the best of our knowledge, this is the fifth study in the literature initiating the development of databases for correlations between the brain and peripheral tissues in the same individuals. We present the first database developed from an Asian population, specifically Japanese samples (AMAZE-CpG), which would contribute to interpreting individual epigenetic study results from various Asian populations.

Histone Citrullination Mediates a Protective Role in Endothelium and Modulates Inflammation

NETosis is a key host immune process against a pathogenic infection during innate immune activation, consisting of a neutrophil "explosion" and, consequently, NET formation, containing mainly DNA, histones, and other nuclear proteins. During sepsis, an exacerbated immune host response to an infection occurs, activating the innate immunity and NETosis events, which requires histone H3 citrullination. Our group compared the circulating histone levels with those citrullinated H3 levels in plasma samples of septic patients. In addition, we demonstrated that citrullinated histones were less cytotoxic for endothelial cells than histones without this post-translational modification. Citrullinated histones did not affect cell viability and did not activate oxidative stress. Nevertheless, citrullinated histones induced an inflammatory response, as well as regulatory endothelial mechanisms. Furthermore, septic patients showed elevated levels of circulating citrullinated histone H3, indicating that the histone citrullination is produced during the first stages of sepsis, probably due to the NETosis process.

FCGR2C: An emerging immune gene for predicting sepsis outcome

Background

Sepsis is a life-threatening disease associated with immunosuppression. Immunosuppression could ultimately increase sepsis mortality. This study aimed to identify the prognostic biomarkers related to immunity in sepsis.

Methods

Public datasets of sepsis downloaded from the Gene Expression Omnibus (GEO) database were divided into the discovery cohort and the first validation cohort. We used R software to screen differentially expressed genes (DEGs) and analyzed DEGs' functional enrichment in the discovery dataset. Immune-related genes (IRGs) were filtered from the GeneCards website. A Lasso regression model was used to screen candidate prognostic genes from the intersection of DEGs and IRGs. Then, the candidate prognostic genes with significant differences were identified as prognostic genes in the first validation cohort. We further validated the expression of the prognostic genes in the second validation cohort of 81 septic patients recruited from our hospital. In addition, we used four immune infiltration methods (MCP-counter, ssGSEA, ImmuCellAI, and CIBERSORT) to analyze immune cell composition in sepsis. We also explored the correlation between the prognostic biomarker and immune cells.

Results

First, 140 genes were identified as prognostic-related immune genes from the intersection of DEGs and IRGs. We screened 18 candidate prognostic genes in the discovery cohort with the lasso regression model. Second, in the first validation cohort, we identified 4 genes (CFHR2, FCGR2C, GFI1, and TICAM1) as prognostic immune genes. Subsequently, we found that FCGR2C was the only gene differentially expressed between survivors and non-survivors in 81 septic patients. In the discovery and first validation cohorts, the AUC values of FCGR2C were 0.73 and 0.67, respectively. FCGR2C (AUC=0.84) had more value than SOFA (AUC=0.80) and APACHE II (AUC=0.69) in evaluating the prognosis of septic patients in our recruitment cohort. Moreover, FCGR2C may be closely related to many immune cells and functions, such as B cells, NK cells, neutrophils, cytolytic activity, and inflammatory promotion. Finally, enrichment analysis showed that FCGR2C was enriched in the phagosome signaling pathway.

Conclusion

FCGR2C could be an immune biomarker associated with prognosis, which may be a new direction of immunotherapy to reduce sepsis mortality.

Construction of Autophagy-Related Gene Classifier for Early Diagnosis, Prognosis and Predicting Immune Microenvironment Features in Sepsis by Machine Learning Algorithms

Background

The immune system plays a fundamental role in the pathophysiology of sepsis, and autophagy and autophagy-related molecules are crucial in innate and adaptive immune responses; however, the potential roles of autophagy-related genes (ARGs) in sepsis are not comprehensively understood.

Methods

A systematic search was conducted in ArrayExpress and Gene Expression Omnibus (GEO) cohorts from July 2005 to May 2022. Machine learning approaches, including modified Lasso penalized regression, support vector machine, and artificial neural network, were applied to identify hub ARGs, thereby developing a prediction model termed ARG classifier. Diagnostic and prognostic performance of the model was comprehensively analyzed using multi-transcriptome data. Subsequently, we systematically correlated the ARG classifier/hub ARGs with immunological characteristics of multiple aspects, including immune cell infiltration, immune and molecular pathways, cytokine levels, and immune-related genes. Further, we collected clinical specimens to preliminarily investigate ARG expression levels and to assess the diagnostic performance of ARG classifier.

Results

A total of ten GEO and three ArrayExpress datasets were included in this study. Based on machine learning algorithms, eight key ARGs (ATG4C, BAX, BIRC5, ERBB2, FKBP1B, HIF1A, NCKAP1, and NFKB1) were integrated to establish ARG classifier. The model exhibited excellent diagnostic values (AUC > 0.85) in multiple datasets and multiple points in time and superiorly distinguished sepsis from other critical illnesses. ARG classifier showed significant correlations with clinical characteristics or endotypes and performed better in predicting mortality (AUC = 0.70) than other clinical characteristics. Additionally, the identified hub ARGs were significantly associated with immune cell infiltration (B, T, NK, dendritic, T regulatory, and myeloid-derived suppressor cells), immune and molecular pathways (inflammation-promoting pathways, HLA, cytolytic activity, apoptosis, type-II IFN response, complement and coagulation cascades), levels of several cytokines (PDGFRB, IL-10, IFNG, and TNF), which indicated that ARG classifier/hub ARGs adequately reflected the immune microenvironment during sepsis. Finally, using clinical specimens, the expression levels of key ARGs in patients with sepsis were found to differ significantly from those of control patients, and ARG classifier exhibited superior diagnostic performance, compared to procalcitonin and C-reactive protein.

Conclusion

Collectively, a diagnostic and prognostic model (ARG classifier) based on eight ARGs was developed which may assist clinicians in diagnosis of sepsis and recognizing patient at high risk to guide personalized treatment. Additionally, the ARG classifier effectively reflected the immune microenvironment diversity of sepsis and may facilitate personalized counseling for specific therapy.

Characterization of Early Peripheral Immune Responses in Patients with Sepsis and Septic Shock

(1) Background: Sepsis is a life-threatening condition caused by an abnormal host response to infection that produces altered physiological responses causing tissue damage and can result in organ dysfunction and, in some cases, death. Although sepsis is characterized by a malfunction of the immune system leading to an altered immune response and immunosuppression, the high complexity of the pathophysiology of sepsis requires further investigation to characterize the immune response in sepsis and septic shock. (2) Methods: This study analyzes the immune-related responses occurring during the early stages of sepsis by comparing the amounts of cytokines, immune modulators and other endothelial mediators of a control group and three types of severe patients: critically ill non-septic patients, septic and septic shock patients. (3) Results: We showed that in the early stages of sepsis the innate immune system attempts to counteract infection, probably via neutrophils. Conversely, the adaptive immune system is not yet fully activated, either in septic or in septic shock patients. In addition, immunosuppressive responses and pro-coagulation signals are active in patients with septic shock. (4) Conclusions: The highest levels of IL-6 and pyroptosis-related cytokines (IL-18 and IL-1α) were found in septic shock patients, which correlated with D-dimer. Moreover, endothelial function may be affected as shown by the overexpression of adhesion molecules such as s-ICAM1 and E-Selectin during septic shock.

Role of myeloid derived suppressor cells in sepsis

Sepsis is a serious and menacing organ dysfunction that occur due to dysregulated response of the host towards the infection. This organ dysfunction may lead to sepsis with intense cellular, metabolic and circulatory dysregulation, multiple organ failure and high mortality. Lymphopenia is observed in two-third of sepsis patients and a significant depletion of lymphocytes occurs in non-survivors compared to sepsis survivors. Myeloid derived suppressor cells (MDSCs) gave new insights into sepsis-associated lymphopenia. If MDSC expansion and its tissue-infiltration persist, it can induce significant pathophysiology including lymphopenia, host immunosuppression and immune-paralysis that contributes to worsened patient outcomes. This review focuses on MDSCs and its subsets, the role of MDSCs in infection, sepsis and septic shock.

Comparative Analysis of Chromatin-Delivered Biomarkers in the Monitoring of Sepsis and Septic Shock: A Pilot Study

Sepsis management remains one of the most important challenges in modern clinical practice. Rapid progression from sepsis to septic shock is practically unpredictable, hence the critical need for sepsis biomarkers that can help clinicians in the management of patients to reduce the probability of a fatal outcome. Circulating nucleoproteins released during the inflammatory response to infection, including neutrophil extracellular traps, nucleosomes, and histones, and nuclear proteins like HMGB1, have been proposed as markers of disease progression since they are related to inflammation, oxidative stress, endothelial damage, and impairment of the coagulation response, among other pathological features. The aim of this work was to evaluate the actual potential for decision making/outcome prediction of the most commonly proposed chromatin-related biomarkers (i.e., nucleosomes, citrullinated H3, and HMGB1). To do this, we compared different ELISA measuring methods for quantifying plasma nucleoproteins in a cohort of critically ill patients diagnosed with sepsis or septic shock compared to nonseptic patients admitted to the intensive care unit (ICU), as well as to healthy subjects. Our results show that all studied biomarkers can be used to monitor sepsis progression, although they vary in their effectiveness to separate sepsis and septic shock patients. Our data suggest that HMGB1/citrullinated H3 determination in plasma is potentially the most promising clinical tool for the monitoring and stratification of septic patients.

Mechanisms of Ataxia Telangiectasia Mutated (ATM) Control in the DNA Damage Response to Oxidative Stress, Epigenetic Regulation, and Persistent Innate Immune Suppression Following Sepsis

Cells have evolved extensive signaling mechanisms to maintain redox homeostasis. While basal levels of oxidants are critical for normal signaling, a tipping point is reached when the level of oxidant species exceed cellular antioxidant capabilities. Myriad pathological conditions are characterized by elevated oxidative stress, which can cause alterations in cellular operations and damage to cellular components including nucleic acids. Maintenance of nuclear chromatin are critically important for host survival and eukaryotic organisms possess an elaborately orchestrated response to initiate repair of such DNA damage. Recent evidence indicates links between the cellular antioxidant response, the DNA damage response (DDR), and the epigenetic status of the cell under conditions of elevated oxidative stress. In this emerging model, the cellular response to excessive oxidants may include redox sensors that regulate both the DDR and an orchestrated change to the epigenome in a tightly controlled program that both protects and regulates the nuclear genome. Herein we use sepsis as a model of an inflammatory pathophysiological condition that results in elevated oxidative stress, upregulation of the DDR, and epigenetic reprogramming of hematopoietic stem cells (HSCs) to discuss new evidence for interplay between the antioxidant response, the DNA damage response, and epigenetic status.

Epigenetic Regulation in Sepsis, Role in Pathophysiology and Therapeutic Perspective

Sepsis is characterized by an initial hyperinflammatory response, with intense cell activation and cytokine storm. In parallel, a prolonged compensatory anti-inflammatory response, known as immunological tolerance, can lead to immunosuppression. Clinically, this condition is associated with multiple organ failure, resulting in the patient's death. The mechanisms underlying the pathophysiology of sepsis are not yet fully understood, but evidence is strong showing that epigenetic changes, including DNA methylation and post-translational modifications of histones, modulate the inflammatory response of sepsis. During the onset of infection, host cells undergo epigenetic changes that favor pathogen survival. Besides, epigenetic changes in essential genes also orchestrate the patient's inflammatory response. In this review, we gathered studies on sepsis and epigenetics to show the central role of epigenetic mechanisms in various aspects of the pathogenesis of sepsis and the potential of epigenetic interventions for its treatment.

Biocompatible valproic acid-coupled nanoparticles attenuate lipopolysaccharide-induced inflammation

Inflammatory diseases like sepsis are associated with dysregulated gene expression, often caused by an imbalance of epigenetic regulators, such as histone acetyltransferases (HATs) and histone deacetylases (HDACs), and consequently, altered epigenetic chromatin signatures or aberrant posttranslational modifications of signalling proteins and transcription factors. Thus, HDAC inhibitors (HDACi) are a promising class of anti-inflammatory drugs. Recently, an efficient drug delivery system carrying the class I/IIa selective HDACi valproic acid (VPA) was developed to circumvent common disadvantages of free drug administration, e.g. short half-life and side effects. The cellulose-based sulphated VPA-coupled (CV-S) nanoparticles (NPs) are rapidly taken up by cells, do not cause any toxic effects and are fully biocompatible. Importantly, VPA is intracellularly cleaved from the NPs and HDACi activity could be proven. Here, we demonstrate that CV-S NPs exhibit overall anti-inflammatory effects in primary human macrophages and are able to attenuate the lipopolysaccharide-induced inflammatory response. CV-S NPs show superior potential to free VPA to suppress the TLR-MyD88-NF-κB signalling axis, leading to decreased TNF-α expression and secretion.

DNA Methylation Analysis to Unravel Altered Genetic Pathways Underlying Early Onset and Late Onset Neonatal Sepsis. A Pilot Study

Background: Neonatal sepsis is a systemic condition widely affecting preterm infants and characterized by pro-inflammatory and anti-inflammatory responses. However, its pathophysiology is not yet fully understood. Epigenetics regulates the immune system, and its alteration leads to the impaired immune response underlying sepsis. DNA methylation may contribute to sepsis-induced immunosuppression which, if persistent, will cause long-term adverse effects in neonates.

Objective: To analyze the methylome of preterm infants in order to determine whether there are DNA methylation marks that may shed light on the pathophysiology of neonatal sepsis.

Design: Prospective observational cohort study performed in the neonatal intensive care unit (NICU) of a tertiary care center.

Patients: Eligible infants were premature ≤32 weeks admitted to the NICU with clinical suspicion of sepsis. The methylome analysis was performed in DNA from blood using Infinium Human Methylation EPIC microarrays to uncover methylation marks.

Results: Methylation differential analysis revealed an alteration of methylation levels in genomic regions involved in inflammatory pathways which participate in both the innate and the adaptive immune response. Moreover, differences between early and late onset sepsis as compared to normal controls were assessed.

Conclusions: DNA methylation marks can serve as a biomarker for neonatal sepsis and even contribute to differentiating between early and late onset sepsis.

miRNA-23b as a biomarker of culture-positive neonatal sepsis

BACKGROUND

Neonatal sepsis remains an important cause of morbidity and mortality. The ability to quickly and accurately diagnose neonatal sepsis based on clinical assessments and laboratory blood tests remains difficult, where haemoculture is the gold standard for detecting bacterial sepsis in blood culture. It is also very difficult to study because neonatal samples are lacking.

METHODS

Forty-eight newborns suspected of sepsis admitted to the Neonatology Department of the Mother-Child Specialized Hospital of Tlemcen. From each newborn, a minimum of 1-2 ml of blood was drawn by standard sterile procedures for blood culture. The miRNA-23b level in haemoculture was evaluated by RT-qPCR.

RESULTS

miR-23b levels increased in premature and full-term newborns in early onset sepsis (p < 0.001 and p < 0.005 respectively), but lowered in late onset sepsis in full-term neonates (p < 0.05) compared to the respective negative controls. miR-23b levels also increased in late sepsis in the negative versus early sepsis negative controls (p < 0.05). miR-23b levels significantly lowered in the newborns who died from both sepsis types (p < 0.0001 and p < 0.05 respectively). In early sepsis, miR-23b and death strongly and negatively correlated (correlation coefficient = - 0.96, p = 0.0019). In late sepsis, miRNA-23b and number of survivors (correlation coefficient = 0.70, p = 0.506) positively correlated.

CONCLUSIONS

Lowering miR-23b levels is an important factor that favours sepsis development, which would confirm their vital protective role, and strongly suggest that they act as a good marker in molecular diagnosis and patient monitoring.