Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome

Temporal changes of gene expression in health, schizophrenia, bipolar disorder, and major depressive disorder

The molecular events underlying the development, manifestation, and course of schizophrenia, bipolar disorder, and major depressive disorder span from embryonic life to advanced age. However, little is known about the early dynamics of gene expression in these disorders due to their relatively late manifestation. To address this, we conducted a secondary analysis of post-mortem prefrontal cortex datasets using bioinformatics and machine learning techniques to identify differentially expressed gene modules associated with aging and the diseases, determine their time-perturbation points, and assess enrichment with expression quantitative trait loci (eQTL) genes. Our findings revealed early, mid, and late deregulation of expression of functional gene modules involved in neurodevelopment, plasticity, homeostasis, and immune response. This supports the hypothesis that multiple hits throughout life contribute to disease manifestation rather than a single early-life event. Moreover, the time-perturbed functional gene modules were associated with genetic loci affecting gene expression, highlighting the role of genetic factors in gene expression dynamics and the development of disease phenotypes. Our findings emphasize the importance of investigating time-dependent perturbations in gene expression before the age of onset in elucidating the molecular mechanisms of psychiatric disorders.

A simplified machine learning model utilizing platelet-related genes for predicting poor prognosis in sepsis

Background

Thrombocytopenia is a known prognostic factor in sepsis, yet the relationship between platelet-related genes and sepsis outcomes remains elusive. We developed a machine learning (ML) model based on platelet-related genes to predict poor prognosis in sepsis. The model underwent rigorous evaluation on six diverse platforms, ensuring reliable and versatile findings.

Methods

A retrospective analysis of platelet data from 365 sepsis patients confirmed the predictive role of platelet count in prognosis. We employed COX analysis, Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine (SVM) techniques to identify platelet-related genes from the GSE65682 dataset. Subsequently, these genes were trained and validated on six distinct platforms comprising 719 patients, and compared against the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ-Failure Assessment (SOFA) score.

Results

A PLT count <100×109/L independently increased the risk of death in sepsis patients (OR = 2.523; 95% CI: 1.084-5.872). The ML model, based on five platelet-related genes, demonstrated impressive area under the curve (AUC) values ranging from 0.5 to 0.795 across various validation platforms. On the GPL6947 platform, our ML model outperformed the APACHE II score with an AUC of 0.795 compared to 0.761. Additionally, by incorporating age, the model's performance was further improved to an AUC of 0.812. On the GPL4133 platform, the initial AUC of the machine learning model based on five platelet-related genes was 0.5. However, after including age, the AUC increased to 0.583. In comparison, the AUC of the APACHE II score was 0.604, and the AUC of the SOFA score was 0.542.

Conclusion

Our findings highlight the broad applicability of this ML model, based on platelet-related genes, in facilitating early treatment decisions for sepsis patients with poor outcomes. Our study paves the way for advancements in personalized medicine and improved patient care.

Shock drives a STAT3 and JunB-mediated coordinated transcriptional and DNA methylation response in the endothelium

Endothelial dysfunction is a crucial factor in promoting organ failure during septic shock. However, the underlying mechanisms are unknown. Here, we show that kidney injury after lipopolysaccharide (LPS) insult leads to strong endothelial transcriptional and epigenetic responses. Furthermore, SOCS3 loss leads to an aggravation of the responses, demonstrating a causal role for the STAT3-SOCS3 signaling axis in the acute endothelial response to LPS. Experiments in cultured endothelial cells demonstrate that IL-6 mediates this response. Furthermore, bioinformatics analysis of in vivo and in vitro transcriptomics and epigenetics suggests a role for STAT, AP1 and interferon regulatory family (IRF) transcription factors. Knockdown of STAT3 or the AP1 member JunB partially prevents the changes in gene expression, demonstrating a role for these transcription factors. In conclusion, endothelial cells respond with a coordinated response that depends on overactivated IL-6 signaling via STAT3, JunB and possibly other transcription factors. Our findings provide evidence for a critical role of IL-6 signaling in regulating shock-induced epigenetic changes and sustained endothelial activation, offering a new therapeutic target to limit vascular dysfunction.

Whole-Blood Gene Expression Profiles Associated with Mortality in Community-Acquired Pneumonia

(1) Background: Information regarding gene expression profiles and the prognosis of community-acquired pneumonia (CAP) is scarce. We aimed to examine the differences in the gene expression profiles in peripheral blood at hospital admission between patients with CAP who died during hospitalization and those who survived. (2) Methods: This is a multicenter study of nonimmunosuppressed adult patients who required hospitalization for CAP. Whole blood samples were obtained within 24 h of admission for genome-expression-profile analysis. Gene expression profiling identified both differentially expressed genes and enriched gene sets. (3) Results: A total of 198 samples from adult patients who required hospitalization for CAP were processed, of which 13 were from patients who died. Comparison of gene expression between patients who died and those who survived yielded 49 differentially expressed genes, 36 of which were upregulated and 13 downregulated. Gene set enrichment analysis (GSEA) identified four positively enriched gene sets in survivors, mainly associated with the interferon-alpha response, apoptosis, and sex hormone pathways. Similarly, GSEA identified seven positively enriched gene sets, associated with the oxidative stress, endoplasmic reticulum stress, oxidative phosphorylation, and angiogenesis pathways, in the patients who died. Protein-protein-interaction-network analysis identified FOS, CDC42, SLC26A10, EIF4G2, CCND3, ASXL1, UBE2S, and AURKA as the main gene hubs. (4) Conclusions: We found differences in gene expression profiles at hospital admission between CAP patients who died and those who survived. Our findings may help to identify novel candidate pathways and targets for potential intervention and biomarkers for risk stratification.

Global DNA hypomethylation and the expression profile of DNA methyltransferase genes in late-onset neonatal sepsis

Aim: Infectious organisms tend to cause DNA methylation changes. Thus, this paper aims to study global DNA methylation and the expression of DNA methyltransferase (DNMT) genes in late-onset neonatal sepsis (LONS). Methods: Global and Alu DNA methylation and expression levels of DNMT were performed using 5mc ELISA, methylation-specific PCR and quantitative real-time-PCR, respectively for LONS and controls. Results: Significant hypomethylation of global DNA and Alu DNA methylation and lower expression of DNMT1 and DNMT3a were observed in LONS compared with controls. Receiver operating characteristic analysis of global and Alu DNA methylation showed good discrimination for the identification of LONS. Conclusion: The hypomethylation of global DNA and Alu elements is evident in neonates with LONS. This may be clinically useful for the prognosis of LONS.

Role of Myeloid Tet Methylcytosine Dioxygenase 2 in Pulmonary and Peritoneal Inflammation Induced by Lipopolysaccharide and Peritonitis Induced by Escherichia coli

Tet methylcytosine dioxygenase 2 (Tet2) mediates demethylation of DNA. We here sought to determine the expression and function of Tet2 in macrophages upon exposure to lipopolysaccharide (LPS), and in the host response to LPS induced lung and peritoneal inflammation, and during Escherichia (E.) coli induced peritonitis. LPS induced Tet2 expression in mouse macrophages and human monocytes in vitro, as well as in human alveolar macrophages after bronchial instillation in vivo. Bone marrow-derived macrophages from myeloid Tet2 deficient (Tet2^fl/flLysM^Cre) mice displayed enhanced production of IL-1β, IL-6 and CXCL1 upon stimulation with several Toll-like receptor agonists; similar results were obtained with LPS stimulated alveolar and peritoneal macrophages. Histone deacetylation was involved in the effect of Tet2 on IL-6 production, whilst methylation at the Il6 promoter was not altered by Tet2 deficiency. Tet2^fl/flLysM^Cre mice showed higher IL-6 and TNF levels in bronchoalveolar and peritoneal lavage fluid after intranasal and intraperitoneal LPS administration, respectively, whilst other inflammatory responses were unaltered. E. coli induced stronger production of IL-1β and IL-6 by Tet2 deficient peritoneal macrophages but not in peritoneal lavage fluid of Tet2^fl/flLysM^Cre mice after in vivo intraperitoneal infection. Tet2^fl/flLysM^Cre mice displayed enhanced bacterial growth during E. coli peritonitis, which was associated with a reduced capacity of Tet2^fl/flLysM^Cre peritoneal macrophages to inhibit the growth of E. coli in vitro. Collectively, these data suggest that Tet2 is involved in the regulation of macrophage functions triggered by LPS and during E. coli infection.

Sirtuins and Sepsis: Cross Talk between Redox and Epigenetic Pathways

Sepsis and septic shock are the leading causes of death among hospitalized patients in the US. The immune response in sepsis transitions from a pro-inflammatory and pro-oxidant hyper-inflammation to an anti-inflammatory and cytoprotective hypo-inflammatory phase. While 1/3rd sepsis-related deaths occur during hyper-, a vast majority of sepsis-mortality occurs during the hypo-inflammation. Hyper-inflammation is cytotoxic for the immune cells and cannot be sustained. As a compensatory mechanism, the immune cells transition from cytotoxic hyper-inflammation to a cytoprotective hypo-inflammation with anti-inflammatory/immunosuppressive phase. However, the hypo-inflammation is associated with an inability to clear invading pathogens, leaving the host susceptible to secondary infections. Thus, the maladaptive immune response leads to a marked departure from homeostasis during sepsis-phases. The transition from hyper- to hypo-inflammation occurs via epigenetic programming. Sirtuins, a highly conserved family of histone deacetylators and guardians of homeostasis, are integral to the epigenetic programming in sepsis. Through their anti-inflammatory and anti-oxidant properties, the sirtuins modulate the immune response in sepsis. We review the role of sirtuins in orchestrating the interplay between the oxidative stress and epigenetic programming during sepsis.

The Role of Host Cell DNA Methylation in the Immune Response to Bacterial Infection

Host cells undergo complex transcriptional reprogramming upon infection. Epigenetic changes play a key role in the immune response to bacteria, among which DNA modifications that include methylation have received much attention in recent years. The extent of DNA methylation is well known to regulate gene expression. Whilst historically DNA methylation was considered to be a stable epigenetic modification, accumulating evidence indicates that DNA methylation patterns can be altered rapidly upon exposure of cells to changing environments and pathogens. Furthermore, the action of proteins regulating DNA methylation, particularly DNA methyltransferases and ten-eleven translocation methylcytosine dioxygenases, may be modulated, at least in part, by bacteria. This review discusses the principles of DNA methylation, and recent insights about the regulation of host DNA methylation during bacterial infection.

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.

High-Resolution Cartography of the Transcriptome and Methylome Landscapes of Diffuse Gliomas

Molecular mechanisms of lower-grade (II-III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context.

Epigenetics of Sepsis

OBJECTIVES

Recent evidence from the fields of microbiology and immunology, as well as a small number of human sepsis studies, suggest that epigenetic regulation may play a central role in the pathogenesis of sepsis. The term "epigenetics" refers to regulatory mechanisms that control gene expression but are not related to changes in DNA sequence. These include DNA methylation, histone modifications, and regulation of transcription via non-coding RNAs. Epigenetic modifications, occurring in response to external stressors, lead to changes in gene expression, and thus lie at the intersection between genetics and the environment. In this review, we examine data from in vitro studies, animal studies, and the existing human sepsis studies in epigenetics to demonstrate that epigenetic mechanisms are likely central to the pathogenesis of sepsis and that epigenetic therapies may have potential in the treatment of sepsis and its associated organ failures.

DATA SOURCES

Online search of published scientific literature via Pubmed using the term "epigenetics" in combination with the terms "sepsis", "infection", "bacterial infection", "viral infection", "critical illness", "acute respiratory distress syndrome", and "acute lung injury".

STUDY SELECTION

Articles were chosen for inclusion based on their relevance to sepsis, acute inflammation, sepsis-related immune suppression, and sepsis-related organ failure. Reference lists were reviewed to identify additional relevant articles.

DATA EXTRACTION

Relevant data was extracted and synthesized for narrative review.

DATA SYNTHESIS

Epigenetic regulation is a key determinant of gene expression in sepsis. At the onset of infection, host-pathogen interactions often result in epigenetic alterations to host cells that favor pathogen survival. In parallel, the host inflammatory response is characterized by epigenetic modifications in key regulatory genes, including tumor necrosis factor and interleukin-1β. In human sepsis patients, multiple epigenetic modifying enzymes show differential expression in early sepsis, suggesting a role for epigenetics in coordinating the response to infection. In the later stages of sepsis, epigenetic modifications accompany endotoxin tolerance and the immune-suppressed state. In animal models, treatment with epigenetic modifiers can mitigate the effects of sepsis and improve survival as well as reverse sepsis-associated organ injury.

CONCLUSIONS

Epigenetic modifications are associated with key phases of sepsis, from the host-pathogen interaction, to acute inflammation, to immune suppression. Epigenetic markers show promise in the diagnosis and prognosis of sepsis and epigenetic modifying agents show promise as therapeutic tools in animal models of sepsis. Human studies in the area of epigenetics are sorely lacking and should be a priority for sepsis researchers.

Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies

Coeliac disease (CD) is a clinically heterogeneous autoimmune disease with variable presentation and progression triggered by gluten intake. Molecular or genetic factors contribute to disease heterogeneity, but the reasons for different outcomes are poorly understood. Transcriptome studies of tissue biopsies from CD patients are scarce. Here, we present a high-resolution analysis of the transcriptomes extracted from duodenal biopsies of 24 children and adolescents with active CD and 21 individuals without CD but with intestinal afflictions as controls. The transcriptomes of CD patients divide into three groups-a mixed group presenting the control cases, and CD-low and CD-high groups referring to lower and higher levels of CD severity. Persistence of symptoms was weakly associated with subgroup, but the highest marsh stages were present in subgroup CD-high, together with the highest cell cycle rates as an indicator of virtually complete villous atrophy. Considerable variation in inflammation-level between subgroups was further deciphered into immune cell types using cell type de-convolution. Self-organizing maps portrayal was applied to provide high-resolution landscapes of the CD-transcriptome. We find asymmetric patterns of miRNA and long non-coding RNA and discuss the effect of epigenetic regulation. Expression of genes involved in interferon gamma signaling represent suitable markers to distinguish CD from non-CD cases. Multiple pathways overlay in CD biopsies in different ways, giving rise to heterogeneous transcriptional patterns, which potentially provide information about etiology and the course of the disease.

The Human Blood Transcriptome in a Large Population Cohort and Its Relation to Aging and Health

Background: The blood transcriptome is expected to provide a detailed picture of an organism's physiological state with potential outcomes for applications in medical diagnostics and molecular and epidemiological research. We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration.

Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features.

Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes.

Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications.

oposSOM-Browser: an interactive tool to explore omics data landscapes in health science

BACKGROUND

oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and visualization.

RESULTS

These functionalities are now available as interactive web-browser application for a broader user audience interested in extracting detailed information from high-throughput omics data sets pre-processed by oposSOM. It enables interactive browsing of single-gene and gene set profiles, of molecular 'portrait landscapes', of associated phenotype diversity, and signalling pathway activation patterns.

CONCLUSION

The oposSOM-Browser makes available interactive data browsing for five transcriptome data sets of cancer (melanomas, B-cell lymphomas, gliomas) and of peripheral blood (sepsis and healthy individuals) at www.izbi.uni-leipzig.de/opossom-browser .

Developmental scRNAseq Trajectories in Gene- and Cell-State Space-The Flatworm Example

Single-cell RNA sequencing has become a standard technique to characterize tissue development. Hereby, cross-sectional snapshots of the diversity of cell transcriptomes were transformed into (pseudo-) longitudinal trajectories of cell differentiation using computational methods, which are based on similarity measures distinguishing cell phenotypes. Cell development is driven by alterations of transcriptional programs e.g., by differentiation from stem cells into various tissues or by adapting to micro-environmental requirements. We here complement developmental trajectories in cell-state space by trajectories in gene-state space to more clearly address this latter aspect. Such trajectories can be generated using self-organizing maps machine learning. The method transforms multidimensional gene expression patterns into two dimensional data landscapes, which resemble the metaphoric Waddington epigenetic landscape. Trajectories in this landscape visualize transcriptional programs passed by cells along their developmental paths from stem cells to differentiated tissues. In addition, we generated developmental "vector fields" using RNA-velocities to forecast changes of RNA abundance in the expression landscapes. We applied the method to tissue development of planarian as an illustrative example. Gene-state space trajectories complement our data portrayal approach by (pseudo-)temporal information about changing transcriptional programs of the cells. Future applications can be seen in the fields of tissue and cell differentiation, ageing and tumor progression and also, using other data types such as genome, methylome, and also clinical and epidemiological phenotype data.

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

Sepsis is a life-threatening condition that occurs when the body responds to an infection damaging its own tissues. Sepsis survivors sometimes suffer from immunosuppression increasing the risk of death. To our best knowledge, there is no 'gold standard' for defining immunosuppression except for a composite clinical end point. As the immune system is exposed to epigenetic changes during and after sepsis, research that focuses on identifying new biomarkers to detect septic patients with immunoparalysis could offer new epigenetic-based strategies to predict short- and long-term pathological events related to this life-threatening state. This review describes the most relevant epigenetic mechanisms underlying alterations in the innate and adaptive immune responses described in sepsis and septic shock, and their consequences for immunosuppression states, providing several candidates to become epigenetic biomarkers that could improve sepsis management and help predict immunosuppression in postseptic patients.

Genetics in community-acquired pneumonia

PURPOSE OF REVIEW

Host defense against community-acquired pneumonia depends on an intact innate and acquired immune system. This review analyses the correlation between specific defects and polymorphisms of immunity genes with susceptibility for pneumonia.

RECENT FINDINGS

Mutations in BTK, Bruton's tyrosine kinase, lead to X-linked agammaglobulinemia, a disease characterized by recurrent respiratory tract infections, including pneumonia. BTK inhibitors, which are used for treatment of leukemia, have pneumonia as side effect. Polymorphisms in B lymphocyte growth and differentiation factors, including IL-6 and IL-10, Fcg RIIa receptors, as well as genetic variants of ACE, angiotensin-converting enzyme, also are associated with increased susceptibility for pneumonia.

SUMMARY

Delineation of underlying genetic defects and polymorphisms may add in diagnosis, therapy, and prognosis of community-acquired pneumonia. In case of humoral immunodeficiency, antibody replacement therapy may be indicated.

DNA methylation of a NF-κB binding site in the aquaporin 5 promoter impacts on mortality in sepsis

Altered aquaporin 5 (AQP5) expression in immune cells impacts on key mechanisms of inflammation and is associated with sepsis survival. Since epigenetic regulation via DNA methylation might contribute to a differential AQP5 expression in sepsis, we tested the hypotheses that DNA methylation of the AQP5 promotor (1) influences AQP5 expression, (2) is associated with the 30-day survival of septic patients, and (3) alters the nuclear transcription factor NF-κB binding. AQP5 mRNA expression was quantified by real-time PCR in whole blood samples of 135 septic patients. In silico computer analysis of the AQP5 promoter (nt-567 to nt-975) revealed seven putative inflammatory transcription factor binding sites and methylation of these sites was analyzed. Electrophoretic mobility shift assays were performed to assess the binding of nuclear NF-κB to the AQP5 promoter region nt-937. After adjustment for multiple testing, a greater methylation rate was found at cytosine site nt-937 in the AQP5 promoter linked to NF-κB binding in non-survivors compared to survivors (p = 0.002, p_adj = 0.014). This was associated with greater AQP5 mRNA expression in non-survivors (p = 0.037). Greater (≥16%) promoter methylation at nt-937 was also associated with an independently increased risk of death within 30 days (HR: 3.31; 95% CI: 1.54–6.23; p = 0.002). We detected a functionally important AQP5 promoter cytosine site (nt-937) linked to the binding of the inflammatorily acting nuclear transcription factor NF-κB, with increased methylation in sepsis non-survivors. Thus, nt-937 APQ5 promoter methylation, presumably related to NF-κB binding, is prognostically relevant in sepsis and demonstrates that epigenetic changes impact on sepsis outcome.

Differential expression of genes associated with T lymphocytes function in septic patients with hypoxemia challenge

Background

This study aimed to assess gene expression alterations related to T lymphocytes function and explore their potential association with hypoxemia among septic patients.

Methods

This is a retrospective cohort clinical study with laboratory investigations. We studied patients enrolled in sepsis biological specimen bank from Department of Critical Care Medicine, Zhongda Hospital, fulfilling consensus criteria for sepsis without any documented immune comorbidity admitted in ICU within 48 h after onset with whole blood samples drawn within 24 h of admission. Whole genome expression by microarray assay (Human LncRNA Microarray V4.0) was compared in hypoxemia cohort versus without. Differentially expressed (DE) genes with >1 log₂[fold change (FC)] and false discovery rate (FDR) <0.20 that enriched in T cell related biological process entered the adjusted analysis to identify the candidate genes. The correlation analysis within candidate genes or with clinical parameters were performed. We assessed candidate expression ex vivo in co-culture system with RAW246.7 cells and validated genes identified in prior studies of sepsis-ARDS/hypoxemia within our present study.

Results

Septic patients (n=9) with hypoxemic phenotype held higher illness severity, serum lactate and creatine, and incidence of lymphopenia compared with non-hypoxemic group (n=6). Several gene signatures related to apoptosis, inhibitory receptors, T cell immunoreceptor, transcriptions factors, toll-like receptors and cytokine and effector molecules were upregulated in hypoxemic group. Candidate genes were identified after adjustment for age, sex and presence of lymphopenia with significantly negative correlations with partial pressure of O₂ in an arterial blood (PaO₂) and fraction of inspiration O₂ (FiO₂) ratio, among which NLRP3, SOS1, ELF1 and STAT3 held an increasing expression in ex vivo validation while the others, PSMA5, CLEC4D, CD300A, PRKD2 and PSMA2 showed the opposite alteration from those in vivo.

Conclusions

Higher illness severity and incidence of lymphopenia was observed following hypoxemia in sepsis and T cell-related gene signatures were associated with hypoxemia during sepsis.

Telomere Length Maintenance and Its Transcriptional Regulation in Lynch Syndrome and Sporadic Colorectal Carcinoma

Background: Activation of telomere maintenance mechanisms (TMMs) is a hallmark of most cancers, and is required to prevent genome instability and to establish cellular immortality through reconstitution of capping of chromosome ends. TMM depends on the cancer type. Comparative studies linking tumor biology and TMM have potential impact for evaluating cancer onset and development. Methods: We have studied alterations of telomere length, their sequence composition and transcriptional regulation in mismatch repair deficient colorectal cancers arising in Lynch syndrome (LS-CRC) and microsatellite instable (MSI) sporadic CRC (MSI s-CRC), and for comparison, in microsatellite stable (MSS) s-CRC and in benign colon mucosa. Our study applied bioinformatics analysis of whole genome DNA and RNA sequencing data and a pathway model to study telomere length alterations and the potential effect of the "classical" telomerase (TEL-) and alternative (ALT-) TMM using transcriptomic signatures. Results: We have found progressive decrease of mean telomere length in all cancer subtypes compared with reference systems. Our results support the view that telomere attrition is an early event in tumorigenesis. TMM gets activated in all tumors studied due to concerted overexpression of a large fraction of genes with direct relation to telomere function, where only a very small fraction of them showed recurrent mutations. TEL-related transcriptional state was dominating in all CRC subtypes, showing, however, subtype-specific activation patterns; while contribution of the ALT-TMM was slightly more prominent in the hypermutated MSI s-CRC and LS-CRC. TEL-TMM is mainly activated by over-expression of DKC1 and/or TERT genes and their interaction partners, where DKC1 is more prominent in MSS than in MSI s-CRC and can serve as a transcriptomic marker of TMM activity. Conclusions: Our results suggest that transcriptional patterns are indicative for TMM pathway activation with subtle differences between TEL and ALT mechanisms in a CRC subtype-specific fashion. Sequencing data potentially provide a suited measure to study alterations of telomere length and of underlying transcriptional regulation. Further studies are needed to improve this method.

Simultaneous Depression of Immunological Synapse and Endothelial Injury is Associated with Organ Dysfunction in Community-Acquired Pneumonia

Rationale: A depressed expression of antigen presentation is, along with endothelial dysfunction, a recognized signature of severe community-acquired pneumonia (CAP). We aimed to evaluate the expression of a number of genes involved in the immunological synapse in non-critically ill CAP patients with or without organ dysfunction and to profile endothelial biomarkers such as proendothelin-1 (proET1) and proadrenomedullin (proADM). Methods: A nested study in a prospective cohort in CAP patients was performed. Expression levels of major histocompatibility complex class II DR alpha (HLA-DRA), CD40 ligand (CD40LG), CD3E, CD28, and inducible T-cell costimulator (ICOS) were quantified by using droplet digital polymerase chain reaction and endothelial biomarkers by immunofluorescence. Results: Ninety-four patients were included, 44.7% of whom had organ failure in one or more organs. A significant decrease in the expression of the five genes with increased levels of proadrenomedullin (proADM) and proendothelin-1 (proET1) was found in CAP with organ failure. The depressed expression of HLA-DRA (odds ratio (OR), 2.94), CD40LG (OR, 3.90), and CD28 (OR, 3.48) was independently associated with organ failure after adjustment for age, Charlson score, and severity. Conclusions. CAP with organ failure showed depressed expression of immunological synapse genes with increased levels of biomarkers denoting endothelial damage. Simultaneous profiling of immunological and endothelial signatures could help in the early identification of organ failure in CAP and in the implementation of personalized treatment.

Teratogenic Rubella Virus Alters the Endodermal Differentiation Capacity of Human Induced Pluripotent Stem Cells

The study of congenital virus infections in humans requires suitable ex vivo platforms for the species-specific events during embryonal development. A prominent example for these infections is rubella virus (RV) which most commonly leads to defects in ear, heart, and eye development. We applied teratogenic RV to human induced pluripotent stem cells (iPSCs) followed by differentiation into cells of the three embryonic lineages (ecto-, meso-, and endoderm) as a cell culture model for blastocyst- and gastrulation-like stages. In the presence of RV, lineage-specific differentiation markers were expressed, indicating that lineage identity was maintained. However, portrait analysis of the transcriptomic expression signatures of all samples revealed that mock- and RV-infected endodermal cells were less related to each other than their ecto- and mesodermal counterparts. Markers for definitive endoderm were increased during RV infection. Profound alterations of the epigenetic landscape including the expression level of components of the chromatin remodeling complexes and an induction of type III interferons were found, especially after endodermal differentiation of RV-infected iPSCs. Moreover, the eye field transcription factors RAX and SIX3 and components of the gene set vasculogenesis were identified as dysregulated transcripts. Although iPSC morphology was maintained, the formation of embryoid bodies as three-dimensional cell aggregates and as such cellular adhesion capacity was impaired during RV infection. The correlation of the molecular alterations induced by RV during differentiation of iPSCs with the clinical signs of congenital rubella syndrome suggests mechanisms of viral impairment of human development.

Population Levels Assessment of the Distribution of Disease-Associated Variants With Emphasis on Armenians - A Machine Learning Approach

Background: During the last decades a number of genome-wide association studies (GWASs) has identified numerous single nucleotide polymorphisms (SNPs) associated with different complex diseases. However, associations reported in one population are often conflicting and did not replicate when studied in other populations. One of the reasons could be that most GWAS employ a case-control design in one or a limited number of populations, but little attention was paid to the global distribution of disease-associated alleles across different populations. Moreover, the majority of GWAS have been performed on selected European, African, and Chinese populations and the considerable number of populations remains understudied. Aim: We have investigated the global distribution of so far discovered disease-associated SNPs across worldwide populations of different ancestry and geographical regions with a special focus on the understudied population of Armenians. Data and Methods: We have used genotyping data from the Human Genome Diversity Project and of Armenian population and combined them with disease-associated SNP data taken from public repositories leading to a final dataset of 44,234 markers. Their frequency distribution across 1039 individuals from 53 populations was analyzed using self-organizing maps (SOM) machine learning. Our SOM portrayal approach reduces data dimensionality, clusters SNPs with similar frequency profiles and provides two-dimensional data images which enable visual evaluation of disease-associated SNPs landscapes among human populations. Results: We find that populations from Africa, Oceania, and America show specific patterns of minor allele frequencies of disease-associated SNPs, while populations from Europe, Middle East, Central South Asia, and Armenia mostly share similar patterns. Importantly, different sets of SNPs associated with common polygenic diseases, such as cancer, diabetes, neurodegeneration in populations from different geographic regions. Armenians are characterized by a set of SNPs that are distinct from other populations from the neighboring geographical regions. Conclusion: Genetic associations of diseases considerably vary across populations which necessitates health-related genotyping efforts especially for so far understudied populations. SOM portrayal represents novel promising methods in population genetic research with special strength in visualization-based comparison of SNP data.