Septic shock is a major medical problem with high morbidity and mortality and incompletely understood biology. Integration of multiple data sets into a single analysis framework empowers discovery of new knowledge about the condition that may have been missed by individual analysis of each of these datasets. Electronic search was performed on medical literature and gene expression databases for selection of transcriptomic studies done in circulating leukocytes from human subjects suffering from septic shock. Gene-level meta-analysis was conducted on the six selected studies to identify the genes consistently differentially expressed in septic shock. This was followed by pathway-level analysis using three different algorithms (ORA, GSEA, SPIA). The identified up-regulated pathway, Osteoclast differentiation pathway (hsa04380) was validated in two independent cohorts. Of the pathway, 25 key genes were selected that serve as an expression signature of Septic Shock.

Background There is an urgent need to understand the key events driving pathogenesis of severe COVID-19 disease, so that precise treatment can be instituted. In this respect NETosis is gaining increased attention in the scientific community, as an important pathological process contributing to mortality. We sought to test if indeed there exists robust evidence of NETosis in multiple transcriptomic data sets from human subjects with severe COVID-19 disease. Gene set enrichment analysis was performed to test for up-regulation of gene set functional in NETosis in the blood of patients with COVID-19 illness. Results Blood gene expression functional in NETosis increased with severity of illness, showed negative correlation with blood oxygen saturation, and was validated in the lung of COVID-19 non-survivors. Temporal expression of IL-6 was compared between severe and moderate illness with COVID-19. Unsupervised clustering was performed to reveal co-expression of IL-6 with complement genes. In severe COVID-19 illness, there is transcriptional evidence of activation of NETosis, complement and coagulation cascade, and negative correlation between NETosis and respiratory function (oxygen saturation). An early spike in IL-6 is observed in severe COVID-19 illness that is correlated with complement activation. Conclusions Based on the transcriptional dynamics of IL-6 expression and its downstream effect on complement activation, we constructed a model that links early spike in IL-6 level with persistent and self-perpetuating complement activation, NETosis, immunothrombosis and respiratory dysfunction. Our model supports the early initiation of anti-IL6 therapy in severe COVID-19 disease before the life-threatening complications of the disease can perpetuate themselves autonomously.

Background: Sepsis and cancer are both leading causes of death, and occurrence of any one, increases the likelihood of the other. While cancer patients are susceptible to sepsis, survivors of sepsis are also susceptible to develop certain cancers. This mutual dependence for susceptibility suggests shared biology between the two disease categories. Earlier analysis had revealed a cancer-related pathway to be up-regulated in Septic Shock (SS), an advanced stage of sepsis. This has motivated a more comprehensive comparison of the transcriptomes of SS and cancer.

Comprehensive and unbiased re-analysis of published blood transcriptome data from patients of COVID-19 reveals significant up-regulation of the gene set functional in NETosis, but no evidence of general cytokine storm. In severe COVID-19 illness, there is significant up-regulation of complement and coagulation pathway, and negative correlation between NETosis and respiratory function (oxygen saturation). Interestingly, there is an early spike in the level of IL-6 gene expression in severe illness compared to moderate illness. With passing days post-onset, the level of IL-6 expression in severe illness approaches that in moderate illness. The data are consistent with IL-6 acting as a driver of NETosis in the early phase of severe COVID-19 illness, that results in a vicious cycle of NETosis-complement/coagulation-respiratory dysfunction. This has important consequence for timing of rational therapy with anti-IL-6 and NETosis inhibitors in severe COVID-19 illness.

Table of contentsP1 D-Dimer in adult patients with presumed sepsis and their clinical outcomesSurinder Kumar Sharma, Anurag Rohatgi, Mansi BajajP2 Diagnosis of infection utilizing Acellix CD64Charles L. Sprung, Ricardo Calderon Morales, Harvey Kasdan, Allon Reiter, Tobias Volker, Julien MeissonnierP3 High levels of phenylcarboxylic acids reflect the severity in ICU patients and affect phagocytic activity of neutrophilsNatalia Beloborodova, Viktor Moroz, Aleksandra Bedova, Yulia Sarshor, Artem Osipov, Katerina ChernevskayaP4 The role of bacterial phenolic metabolites in mitochondrial dysfunctionNadezhda Fedotcheva, Ekaterina Chernevskaya, Natalia BeloborodovaP5 The early diagnosis of severe sepsis and judgment of rapid transport to critical care center: better prognostic factorHisashi Imahase, Kosuke C Yamada, Yuichiro Sakamoto, Miho Ohta, Ryota Sakurai, Mayuko Yahata, Mitsuru Umeka, Toru Miike, Hiroyuki Koami, Futoshi Nagashima, Takashi Iwamura, Satoshi InoueP6 Translational neuromodulation of the immune systemZhifeng Li, Dennis Grech, Patrick Morcillo, Alex Bekker, Luis UlloaP7 Pathway-level meta-analysis reveals transcriptional signature of septic shockSamanwoy Mukhopadhyay, Abhay D Pandey, Samsiddhi Bhattacharjee, Saroj K MohapatraP8 Antibiotic dosing in septic patients on the critical care unit - a literature reviewJulie K WilsonP9 Pandemic of Escherichia coli clone O25: H4-ST131 producing CTX-M-15 extended spectrum- β- lactamase- as serious cause of multidrug resistance extraintestinal pathogenic E. coli infections in IndiaSavita Jadhav, Rabindra Nath Misra, Nageswari Gandham, Kalpana Angadi, Chanda Vywahare, Neetu Gupta, Deepali DesaiP10 Detection and characterization of meningitis using a DDA-based mass spectrometry approachAnahita Bakochi, Tirthankar Mohanty, Adam Linder, Johan MalmströmP11 Diagnostic usefulness of lipid profile and procalcitonin in sepsis and trauma patientsDimple Anand, Seema Bhargava, Lalit Mohan Srivastava, Sumit RayP12 Heparin – a novel therapeutic in sepsis?Jane Fisher, Peter Bentzer, Adam LinderP13 Hypothalamic impairment is associated with vasopressin deficiency during sepsisLuis Henrique Angenendt da Costa, Nilton Nascimentos dos Santos Júnior Carlos Henrique Rocha Catalão, Maria José Alves da RochaP14 Presepsin (soluble CD14 subtype) is a dependable prognostic marker in critical septic patientsAlfredo Focà, Cinzia Peronace, Giovanni Matera, Aida Giancotti, Giorgio Settimo Barreca, Angela Quirino, Maria Teresa Loria, Pio Settembre, Maria Carla Liberto, Bruno AmanteaP15 Safety and efficacy of gelatin-containing solutions versus crystalloids and albumin - a systematic review with quantitative and qualitative summariesChristiane Hartog, Christiane Hartog, Claudia Moeller, Carolin Fleischmann, Daniel Thomas-Rueddel, Vlasislav Vlasakov, Bram Rochwerg, Philip Theurer, Konrad ReinhartP16 Immunomodulatory properties of peripheral blood mesenchymal stem cells following endotoxin stimulation in an equine modelAnna E. Smith, Sandra D. TaylorP17 Frequency and outcome of early sepsis-associat...

Septic shock is a major medical problem with high morbidity and mortality and incompletely understood biology. Availability of genome-wide expression data from different studies on septic shock empowers the quest for hitherto unidentified pathways by integration and meta-analysis of multiple data sets. Electronic search was performed on medical literature and gene expression databases. Selection of studies was based on the organism (human subjects), tissue of origin (circulating leukocytes) and the platform technology (gene expression microarray).Gene-level meta-analysis was conducted on the six selected studies to identify the genes consistently differentially expressed in septic shock. These genes were then subjected to pathway analysis. The identified up-regulated pathway hsa04380 (Osteoclast Differentiation) was validated in an independent cohort of patients.A simplified model was generated showing the major gene-modules dysregulated in SS. 1All rights reserved. No reuse allowed without permission.was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint (which . http://dx.doi.org/10.1101/051706 doi: bioRxiv preprint first posted online May. 5, 2016; IntroductionSeptic shock (SS) is a serious medical condition that claims many lives every year worldwide. Approximately 2% of the patients admitted to the hospital are diagnosed with SS. Of these patients, half are treated in the intensive care unit (ICU), representing 10% of all ICU admissions (2,29). Approximately 40-60% of the SS patients die within 30 days (2). The number of cases in the USA exceeds 750,000 per year (2), but the incidence of SS is largely unknown in those parts of the world with scarce ICU care.Extrapolating from treated incidence rates in the USA, Adhikari et al. estimated up to 19 million cases worldwide per year (1). However, the true incidence is expected to be far higher. Incomplete grasp of SS biology is compounded by the lack of specific drug for treating the condition. With a number of failed clinical trials, there is urgent need for new directions in research (5). Genome-wide expression profiling offers a complete picture of the condition and enables identification of genes and pathways of diagnostic, prognostic or therapeutic relevance (37).The purpose of this study was to investigate genome-wide host response to SS by combining the power of multiple studies. Analysis was performed at two levels: genes and gene sets. A "gene set" or pathway consists of a set of functionally related genes, and provides higher-order information about gene expression and valuable insights into the biology of a disease. Accordingly, we have laid emphasis on discovery of pathway(s) enriched among the genes consistently differentially expressed among the multiple data sets from studies on SS.A biological process involves a group of genes. The principle of enrichment analysis is that if a biological process is abnormal in a given condition, the co-functioning...

Sepsis remains a lethal ailment with imprecise treatment and ill-understood biology. A clinical transcriptomic analysis of sepsis patients was performed for the first time in India and revealed large-scale change in blood gene expression in patients of severe sepsis and septic shock admitted to ICU. Three biological processes were quantified using scores derived from the corresponding transcriptional modules. Comparison of the module scores revealed that genes associated with immune response were more suppressed compared to the inflammation-associated genes. These findings will have great implication in the treatment and prognosis of severe sepsis/septic shock if it can be translated into a bedside tool.

AbstractBackgroundSepsis and cancer are both leading causes of death, and occurrence of any one, increases the likelihood of the other. While cancer patients are susceptible to sepsis, survivors of sepsis are also susceptible to develop certain cancers. This mutual dependence for susceptibility suggests shared biology between the two disease categories. Earlier analysis had revealed cancer-related pathway to be up-regulated in Septic Shock (SS), an advanced stage of sepsis. This has motivated a more comprehensive comparison of the transcriptomes of SS and cancer.MethodsGene Set Enrichment Analysis was performed to detect the pathways enriched in SS and cancer. Thereafter, hierarchical clustering was applied to identify relative segregation of 17 cancer types in to two groups vis-a-vis SS. Biological significance of the selected pathways was explored by network analysis. Clinical significance of the pathways was tested by survival analysis. A robust classifier of cancer groups was developed based on machine learning.ResultsA total of 66 pathways were observed to be enriched in both SS and cancer. However, clustering segregated cancer types into two categories based on the direction of transcriptomic change. In general, there was up-regulation in SS and one group of cancer (termed Sepsis-Like Cancers, or SLC), but not in other cancers. SLC group mainly consisted of malignancies of the gastrointestinal tract (head and neck, oesophagus, stomach, liver and biliary system) often associated with infection. Machine learning classifier successfully segregated the two cancer groups with high accuracy (> 98%). Additionally, pathway up-regulation was observed to be associated with survival in the SLC group of cancers.ConclusionTranscriptome-based systems biology approach segregates cancer into two groups (SLC and CA) based on similarity with SS. Host response to infection plays a key role in pathogenesis of SS and SLC. However, we hypothesize that some component of the host response is protective in both SS and SLC.