Sepsis

Chapter 27

Sepsis: future role of omics in diagnosis and therapy Hermes Vieira Barbeiro, Denise Frediani Barbeiro and Francisco Garcia Soriano Emergências Clínicas/LIM 51, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil

Introduction to sepsis The sepsis scenario has a very rapid evolution, and the inflammatory profile changes every hour. Sepsis-aiming precision medicine has to be fast. In a matter of hours, a patient may have died from an infection that has turned into sepsis. In this way, the Surviving Sepsis Campaign and intensive care associations proposed a therapeutic intervention to be performed during the first 4 h [1]. The protocol is similar for all patients, and improves global results. Despite the significant advances in our understanding of the pathobiology of sepsis, sepsis management remains largely supportive. Tailoring treatment according to clinical and laboratory findings will add further benefit. It is not clearly known why under similar circumstances some patients eliminate more easily an invading microorganism, whereas others develop sepsis and septic shock. A variable to consider is the host genetic, epigenetic, proteomic, metabolomic, and microbiomic factors (Fig. 27.1), which have been related to sepsis outcome. Sepsis can be an area of conflict between standardized, protocoled routines as currently adopted, and precision-based custom handling of each patient.

Genomicsegenomic variants The host activates production and release of many proteins and substances to fight bacteria [2,3]. Human genome contains genes that code proteins in response to infection. There are approximately 22,000 genes that code proteins and 5e10 times more proteins are formed (Fig. 27.1) as the final product [4]. The difference in genes from every person can determine an advantage against infection and less sepsis development [2,5]. Relation between genomics and infection was raised first in 1988. It was demonstrated that individuals with

biological parents who died from infectious diseases had a fivefold risk of dying from sepsis [6]. As a general rule, each person presents all the regular genes of the inflammatory cascade. What can change is polymorphisms (genomic variation). Several studies have attempted to associate polymorphisms with incidence or outcome of infectious disease, and its complications in critically ill patients [5,7,8].

Cytokines and other mediators Tumor Necrosis Factor (TNF) was the first cytokine demonstrated to be involved in sepsis. TNF gene polymorphisms showed association with adverse outcomes, as well as increased incidence of severe sepsis and septic shock [7]. Pro- and antiinflammatory cytokines like the interleukin-1 (IL-1) gene family, interleukin-6 (IL-6) and interleukin-10 (IL-10), can display different inflammatory profiles [9]. Cell signaling pathways activated in the response to a bacterium triggered the search for polymorphism of new genes candidates. Incidence, severity, and mortality of infectious complications in the critically ill are influenced as well by polymorphism of genes involved in pathogen recognition, and signal transduction of inflammatory pathways, such as cluster of differentiation 14 (CD14), tolllike receptors (TLRs), lipopolysaccharide binding protein (LBP), interleukin-1 receptor-associated kinase (IRAK 4), and IRAK 1 [10e16]. These genes can present polymorphisms with increased or decreased signal transduction, and consequently higher or lower inflammatory response to a pathogen. Tyrosine kinase is an enzyme, which catalyzes phosphorylation from nucleoside triphosphate (ATP) to the amino acid tyrosine in proteins. Nonreceptor tyrosine kinases (NRTKs) function in the cytoplasm, and transfer signals within the cell into the nucleus [17]. Feline sarcoma (Fes) or Fujinami poultry

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FIGURE 27.1 Schematic description of protein synthesis.

sarcoma protein (Fps), and its homologous-related protein FER, are the two members of a class of NRTKs. Fes signals downstream of receptors in regulation of hematopoietic cell development, survival, migration, inflammatory mediator release, and angiogenesis. Activated Fes is a potent inducer of myeloid differentiation. The FER gene affects leukocyte recruitment, and intestinal barrier dysfunction caused by lipopolysaccharide (LPS). A study identified a polymorphism of FER, which is associated with a reduced risk of death from sepsis caused by pneumonia [18]. Sepsis causes the activation of hundreds, or almost a 1000, genes. There are several other physiologic pathways involved in sepsis. For example, it has been recognized that protein cascades such as the coagulation cascade, represent important genomic candidate markers [19]. A genetic predisposition to produce high concentrations of plasminogen activator inhibitor-1 (PAI-1) is associated with poor outcome of meningococcal sepsis. This finding suggests that impaired fibrinolysis is an important factor in the pathophysiology of meningococcal sepsis.

Genome-wide association studies In a genome-wide association study (GWAS) of 740 adult septic patients, 243 autosomal variants were detected clustered in 14 loci, with suggestive evidence for an association with 28-day mortality. Converging evidence for three of them were unveiled in independent data sets. The authors propose vacuolar protein sorting-associated protein 13A (VPS13A), cysteine rich secretory protein LCCL domain containing 2 (CRISPLD2), and the locus of chromosome 13, as foci for future research [2]. The best

association signal (rs117983287; p ¼ 8.16  108) was observed for a missense variant located at chromosome 9q21.2 in the VPS13A gene. VPS13A was further supported by additional GWAS (p ¼ 0.03) and sequencing data (p ¼ 0.04). Furthermore, CRISPLD2 (p ¼ 5.99  106) and a region on chromosome 13q21.33 (p ¼ 3.34  107) were supported by both author data and external biological evidence.

Molecular diagnosis of sepsis The Molecular Diagnosis and Risk Stratification of Sepsis (MARS) provides a molecular classification of patients with sepsis according to four different endotypes, upon intensive care medicine (ICU) admission. Detection of septic endotypes is in the route for personalized patient management [3]. The authors identified 140 genes that classified the Mars1e4 endotypes. The worst survival outcome at 28 days corresponded to Mars1 endotype (39% did not survive). The same endotype exhibited the worst survival outcome at 1-year follow-up. Sepsis is a multifactorial disease, and molecular diagnosis with risk stratification cannot be performed with single genes, but with interpretation of several genes.

Epigenomic and transcriptomics Deoxyribonucleic acid (DNA) and histones can be modified by enzymes with epigenetic effect, which causes gene expression to vary without a change in DNA sequence [20]. Histone can be modified by methylation, acetylation, ubiquitination, and phosphorylation [21,22]. Previous epigenetic modifications can be due to habits, environment,

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and diet, and lead to different clinical scenarios. During an infectious disease, bacterium-induced epigenetic changes can interfere with host cell function, either promoting host defense or allowing pathogen persistence [23,24].

Transcriptomics Transcriptomics is the measurement of messenger ribonucleic acid (mRNA) levels for genes in specific cells or tissues (Fig. 27.1). This tool points out not only active genes in general, but can also track the effect of epigenomics on genes expression. Full blood and/or individual blood cell subpopulations are screened, because it is not possible to harvest tissue in septic patients. Whole blood, with all its immunocompetent cells, represents a robust and complex immunological system involved in sepsis pathogenesis [25]. Literature reports different gene expressions, depending on the subpopulation of immunocompetent cells [26]. Practically, no investigation has been performed that evaluated gene expression in individual organs during clinical sepsis, with the exception of experimental models [27].

Interpretation of transcriptomic observations A number of issues arise in these studies dealing with sepsis. The first one is the complex dynamics of disease progression in sepsis [28e31]. The clinical course of sepsis shows proinflammatory elements are dominant in early stages, later on shifting to functional immunosuppression. Therefore, gene expression differs over time [32].

Sepsis and inflammatory profile There is much interest to differentiate infectious and noninfectious systemic inflammatory syndrome. Some models evaluated gene expression in volunteers who received an endotoxin dose [33,34]. Target gene groups with their bonds in gene maps were thus identified. Experimental endotoxin injection is of course different from clinical sepsis with a living infectious agent. Clinical trials in sepsis confirmed different gene expression in systemic inflammatory response syndrome (SIRS) of infectious versus noninfectious etiology [4]. The results were confirmed by other studies [35e38]. The authors tested whether profiling transcription is applicable to sepsis diagnosis, using a microarray containing probes for 340 genes related to inflammation. Gene expression pattern was highly homogenous, resulting in 69% of differentially expressed genes. A list of 50 differentially expressed genes showed a positive predictive value of 98%. Regardless of the heterogeneity of the patients, there were a striking correlation between conventional diagnostic classification and the transcription approach [4,39].

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Disease etiology and severity Differences have been found with respect to the septic agent. One report did not reveal different gene expression in gram-positive (Gþ) and gram-negative (Ge) infections, but others did [40,41]. Different expressions of IL-2, IL-10, IL-23, IL-27, interferon-g (IFN g), and TNFa have been found when comparing infection to severe sepsis [42]. Gene expression difference between the two groups which predicts postoperative sepsis was observed for IL1b, TNF, CD3D molecule, delta (CD3-TCR complex), and perforin 1 (pore forming protein) (PRF1) [43]. The combination of TNF, IL1b, and CD3D expression had a sensitivity and specificity of 90% and 85%, respectively, with an estimated negative predictive value of 98.1% [43].

Immune dysfunction A different gene expression was demonstrated in bacterial and virus infections related to immune dysfunction. A Tcell-dominant gene-expression signature was associated with the host response to severe influenza pneumonia. Genes linked to the cell cycle and its regulation, were the main determinants of the host response in influenza infection. The search for an immune response specific pattern to bacterial pneumonia failed [44]. Confirming the abilities of a specific group of genes to differentiate between viral and bacterial infection would influence antibiotic consumption and resistance development, and is of major importance in clinical practice. Sepsis and organ dysfunction caused by community acquired pneumonia in ICU patients was addressed by gene expression in peripheral blood leukocytes [45]. Transcriptomic analysis defined two sepsis response signatures (SRS). SRS1 found in 41% of patients identified patients with an immunosuppression phenotype (endotoxin tolerance, T-cell exhaustion, and human leukocyte antigen (HLA) class II regulation disorder). This phenotype was associated with higher 14-day mortality [45].

Metaanalysis A metaanalysis of gene expression in severe sepsis and septic shock, with 45 series, suggested 352 genes as candidates (215 upregulated and 137 downregulated). Examples of upregulated genes were cluster of differentiation 177 (CD177), matrix metalloproteinase-8 (MMP8), haptoglobin (HP), arginase 1 (ARG1), and annexin A3 (ANXA3). The top downregulated genes were Fc fragment of IgE receptor Ia (FCER1A), human ortholog of yeast mitochondrial AAA metalloprotease (YMEI1L1), T cell receptor delta variable 3 (TRDV3), leucine-rich repeat neuronal protein 3 (LRRN3), and MYB proto-oncogene like 1 (MYBL1) [46].

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In response to a need for better sepsis diagnosis, several new gene expression classifiers have been recently published, including the 11-gene “Sepsis MetaScore,” the “FAIM3-to-PLAC8” ratio, and the Septicyte Lab. The three tools do not show significant differences in overall ability to distinguish noninfectious SIRS from sepsis [47].

Clinical applications for genomics and transcriptomics Most data of polymorphism and epigenetic changes are useful for prognostic evolution; however, these differences can indicate a different inflammatory and immunologic response. There are genomic and epigenomic patterns that produce a more proinflammatory response, with consequent organ damage. On the other hand, a lower proinflammatory response could mean a difficulty to fight bacteria. Patients presenting genomic or epigenomic proinflammatory features can be treated more aggressively, with volume expansion, antioxidants, and drugs that inhibit some parts of the inflammatory cascade. In hyperresponsive cases, antiinflammatory therapies can be tested, such as corticoids, anti-TNF drugs. In circumstances of lower response, anti PD-1 or anti PDL-1 pharmacotherapy could be considered, to unblock immune system check points. In addition, IL-7 and interferon-g are alternatives to improve immune response, in order to fight bacteria. There are ongoing clinical trials for checking the efficiency of these drugs; depending on the outcome, it could be convenient in the future to stratify therapy, depending on observed patterns of inflammation.

Proteomics Proteins are the final effectors of every function in human being. Many mRNAs are not converted into proteins, so the transcriptome cannot give the true picture of what is occurring in septic inflammation (Fig. 27.1). Maybe proteins can represent a better choice for new biomarkers, which will differentiate infectious systemic inflammation from noninfectious inflammation, and also to find pathogenic mechanisms and pathways that could guide diagnosis and treatment. Sepsis post liver transplant unveiled new proteins as possible biomarkers. This method was plasma profiling coupling protein chip array, with surface-enhanced laser desorption/ionization with time-of-flight (SELDI-TOF). There were 31 patients with infection and 34 without. Five peaks were differentially expressed and allowed sepsis diagnosis, with a positive likelihood ratio of 5.1, and Cstatistics of 0.74 (0.58e0.85) [48]. The new five proteins: CM10 4152.7, CM10 4627.2, CM10 5744.7, CM10 5812.9, and CM10 5912.3 were significantly different, in subjects who developed sepsis at postoperative day 5, in

comparison with nonseptic patients. The “septic” protein (CM10 4152) was also differentially expressed in patients with septic shock versus those with nonseptic shock. Other proteins differentially expressed in patients with systemic inflammatory response syndrome or sepsis encompass complement factor B, haptoglobin, clusterin, 1-B-glycoprotein, complement C4, C reactive protein (CRP) precursor, plasminogen precursor, and transthyretin precursor. After low-dose endotoxin challenge in healthy volunteers, the authors found profound changes of plasma proteome [49]. A new component of 4154 mass units was recognized as the activation peptide of the C1 esterase inhibitor. Resemblance in mass units to 4152 protein peak could reasonably represent the same peptide. Appearance of this peptide could be related to blood proteolytic degradation occurring in septic patients.

Animal models Experimental studies can standardize bacteria and study proteins in the blood and organs; however, in humans this can only be conducted a posteriori. The model of sepsis with virulent Streptococcus pyogenes in mice was used to map proteins in blood plasma and individual organs. Biomarkers grouped into categories can reflect sepsis-related characteristics such as acute phase proteins, coagulation, cytokines/ chemokines, vascular endothelial damage, and organ dysfunction. Human biomarkers mapped in the mouse orthologous model and in the protein tissue atlas confirm that the predominant localization of these proteins are plasma, tissues and cells. They are highly tissue and cell specific. Most biomarkers increase in concentration with disease severity. There was a different behavior for each biomarker group. For example, there was a dose-dependent elevation of acute phase proteins, coagulation proteins, and cytokines/ chemokines. However, biomarkers associated with vascular endothelial damage presented smaller increase with vascular damage. Contrasting with previous data, biomarkers linked to organ dysfunction presented only a noticeable increase in the highest infectious dose group. The hypothesis is that organ dysfunction is not a gradual process, but rather confined to some of the most infected animals [50,51]. Another aim of proteomics is to study infectious models and describe protein-protein interactions, using mass spectrometry. With S. pyogenes and adhered human plasma protein, a stoichiometric model of protein structure interaction was developed. A stoichiometric surface density model of host-pathogen interactions emerged, using data from proteomic and electron microscopy analysis. The model captured the large differences in network topology, between the surface structure of the wild-type and M1 strain, revealing a dense and a highly organized protein interaction network between S.s pyogenes and human plasma proteins [52].

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Clinical applications

Volatile metabolome (volatolome)

Proteomics as the final expression of either genomics or transcriptomics is a priority in clinical practice. As not all mRNA is converted to protein, proteomics can convey a more refined and reliable picture of sepsis dynamics.

Volatile organic compounds (VOC) are a promising tool for sepsis screening and diagnosis. VOC can be analyzed in plasma, blood, urine, feces, and respiratory exhaled air. VOC profiles from feces of infants (N ¼ 843), up to 3 days prior to clinical late onset sepsis (LOS), were compared with controls. VOC analysis discriminated between infants developing LOS and controls. Early detection of LOS may provide clinicians an opportunity for precocious therapeutic interventions, aimed at prevention of sepsis, possibly improving LOS-related morbidity and mortality [60]. In the emergency department (ED), tools for early screening and diagnosis of sepsis improve outcomes. Common metabolites and protein-mediators were validated as potential biomarkers for a sepsis screening model, to differentiate pediatric intensive care unit (PICU)-sepsis from pediatric emergency department (PED)-sepsis. Metabolomics achieved: sensitivity 0.71, specificity 0.93, and AUROC ¼ 0.90  0.03. The metabolomics-based biomarkers predicted which sepsis patients required care in a PICU versus those that could be safely cared for outside a PICU [61]. Neutropenic febrile patients are a high-risk population, and early diagnosis is crucial. Using metabolomics data, a 5-predictor model had an area under the receiver operating curve of 0.991 (95%CI: 0.972e1.000). Pregnenolone steroids were more abundant in bacteremic patients, and carnitine metabolites in controls. A 3-predictor gene expression model had corresponding results of 0.961 (95% CI: 0.896e1.000), 100%, and 86%. Genes involved in innate immunity were differentially expressed.

Metabolomics Metabolites are small molecules produced by the action of enzymes/proteins (Fig. 27.1). Metabolomics is the largescale study of such molecules, within cells, fluids, tissues, or organisms, as influenced by both genetic and environmental factors [53]. Metabolomics is the final expression of genes, mRNA, and protein activity; it represents the molecular phenotype, or deep phenotype [54,55]. The Human Metabolome Database contains records for more than 42,000 metabolites, from sugars and other macronutrients, to specific cofactors. Probably the total amount is higher, and several analytical methods struggle to capture the chemical diversity. The aims of metabolomics are the same as with other “omics” d diagnosis, prognosis, and identification of at-risk patients [54,55]. In a prospective study, blood samples from 65 patients with sepsis and 49 controls were compared using gas chromatography coupled to time-of-flight mass spectrometry. A predictive logistic regression model with six metabolites showed a sensitivity of 0.91 (95% confidence interval/CI 0.69e0.99), and a specificity of 0.84 (95% CI 0.58e0.94), with an area under curve (AUC) of 0.93 (95% CI 0.89e1.01). Myristic acid was the most predictive metabolite, with a sensitivity of 1.00 (95% CI 0.85e1.00) and specificity of 0.95 (95% CI 0.74e0.99) [56]. Changes in the plasma levels of low unsaturated longchain phosphatidylcholines and kynurenine were also associated with mortality in 20 patients with septic shock [57]. Urine samples from 64 patients with sepsis or septic shock were compared with respect to Sequential Organ Failure Assessment (SOFA) score. Higher amounts of ethanol, glucose, and hippurate, and lower levels of methionine, glutamine, arginine, and phenylalanine were associated to a negative prognosis [58]. The metabolic profile of normal patients and those with SIRS or sepsis was markedly different. Seven metabolites could potentially be used to diagnose sepsis [59]. A significant decrease in the levels of lactitol dehydrate and S-phenyl-D-cysteine and an increase in the levels of S(3-methylbutanoyl)-dihydrolipoamide-E and N-nonanoyl glycine were observed in sepsis, in comparison to patients with SIRS (P < 0.05). Patients with sepsis and septic shock displayed lower levels of glycerylphosphorylethanolamine, Ne, Ne dimethyllysine, phenylacetamide, and D-cysteine (P < 0.05) in their sera [59].

Direct breath analysis (exhaled air) Bacteria have a distinct metabolism, part of which results in the production of bacteria-specific volatile organic compounds (VOCs), which might be used for diagnostic purposes. Isopentanol, formaldehyde, methyl mercaptan, and trimethylamine are VOCs produced by the six most abundant and pathogenic bacteria in sepsis: Staphylococcus aureus, Streptococcus pneumoniae, Enterococcus faecalis, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli. Humans do not produce these VOCs, so these compounds are credible biomarkers for these pathogens. Isovaleric acid and 2-methyl-butanal were linked to St. aureus; 1-undecene, 2,4-dimethyl-1-heptane, 2-butanone, 4methyl-quinazoline, hydrogen cyanide, and methyl thiocyanide to P. aeruginosa; and methanol, pentanol, ethyl acetate, and indole to E. coli [62,63]. Ventilation associated pneumonia (VAP) is consistently underdetected in the hospital. Exhaled breath biomarkers, including measurement of volatile organic compounds, represent an approach [63,64].

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Microbiome Gut The gut can be a motor of multiple organ dysfunction in critical illness, due to bacterial translocation. It is a potential source of bacteria to precipitate and maintain sepsis. The gut microbial barrier encompasses epithelium, adaptive immune system, and microbiome. Each part plays a crucial role in the maintenance of health, and pathophysiology of critical illness. Serious illness can compromise gut integrity, increasing apoptosis, and permeability. Multiple preclinical studies have demonstrated that targeting gut barrier integrity results in improved survival in critical illness. Enteral nutrition is widely used in the intensive care unit, as a protective tool for gut mass and function.

Microbiota Bacterial commensals are divided into seven main phyla, which are physiologically dominated by Firmicutes and Bacteroidetes. Nevertheless, substantial inter- and intraindividual variations on genomic, dietary, and environmental factors are identified [65]. The whole gut microbiota, that is, bacteria, fungi, archaea, viruses, and protozoa that colonize the intestinal tract, compose a complex ecosystem. Gut microbiota is estimated to reach in healthy humans a total of 3.1013 microorganisms, a population that equals the host cells [66].

Dysbiosis in serious illness Metabolic diseases, autoimmune disorders, inflammatory bowel disease, neurocognitive impairment, and malignancies exhibit underlying intestinal dysbiosis [67]. A variety of both exogenous and patient-related factors may lead to ICU-acquired dysbiosis, for instance, drugs including antimicrobials, proton pump inhibitors, or depressors of gastrointestinal transit (e.g., opioids), artificial nutrition, sepsis, shock, or bowel ischemia [68]. Loss of diversity is commonly observed, and features deep depletion of potential health-promoting commensal genera like Faecalibacterium, Ruminococcus, or Pseudobutyrivibrio, along with overgrowth of a pathogenic and normally subdominant taxon, namely Enterobacteriaceae, and including Enterococcus and other pathogens [69e71].

Gut microbial signature Studies present discrepancies between case-mix, antimicrobial exposure, stool collection time during ICU stay, and analytical methods. ICU-based studies, which adopt routine selective digestive decontamination, further complicate interpretation of the data. Whether intestinal dysbiosis is an independent predictor of poor outcome, or just one more

marker of severity, is still speculative. Experimental studies suggest that the intestinal ecosystem modulates the risk of complications such as acute respiratory distress syndrome, ischemia/reperfusion-related acute kidney injury, or sepsisinduced muscle wasting [72e74]. The intestinal barrier may be impaired by dysbiosis and immunosuppression, thereby facilitating the occurrence of sepsis and multiple organ failure [68].

Clinical applications Preventing bacteria from becoming virulent or reprogramming them to a nonvirulent phenotype is one of the new approaches which may revolutionize the treatment of gutderived sepsis. There is species-specific colonization resistance: Clostridium bolteae and Blautia producta act synergistically to prevent vancomycin-resistant enterococci (VRE); Clostridium scindens appears to protect from Clostridium difficile infection; and Desulfovibrio, Oscillospira, Parabacteroides, and Coprococcus genera have been associated with the absence of carriage of extended spectrum beta-lactamase-producing Escherichia coli [75e77]. Resident anaerobes have the capacity to prevent intestinal colonization by exogenous microorganisms, via competition for nutrient intake, and induction of a targeted immune response [75,78]. To date, fecal transplant is not typically used in critically ill patients because of ongoing antibiotic use, which is common in the ICU. The most convincing data are in recurrent C. difficile infection, where cure rates are three times higher than seen with conventional medical therapy, without apparent side effects [75].

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