Application of LC-MS-based metabolomics method in differentiating septic survivors from non-survivors

Novel biomarkers to identify complicated course of febrile neutropenia in hematological patients receiving intensive chemotherapy

Febrile neutropenia (FN) is a common consequence of intensive chemotherapy in hematological patients. More than 90% of the patients with acute myeloid leukemia (AML) develop FN, and 5%-10% of them die from subsequent sepsis. FN is very common also in autologous stem cell transplant recipients, but the risk of death is lower than in AML patients. In this review, we discuss biomarkers that have been evaluated for diagnostic and prognostic purposes in hematological patients with FN. In general, novel biomarkers have provided little benefit over traditional inflammatory biomarkers, such as C-reactive protein and procalcitonin. The utility of most biomarkers in hematological patients with FN has been evaluated in only a few small studies. Although some of them appear promising, much more data is needed before they can be implemented in the clinical evaluation of FN patients. Currently, close patient follow-up is key to detect complicated course of FN and the need for further interventions such as intensive care unit admission. Scoring systems such as q-SOFA (Quick Sequential Organ Failure Assessment) or NEWS (National Early Warning Sign) combined with traditional and/or novel biomarkers may provide added value in the clinical evaluation of FN patients.

Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

Investigating the impact of human blood metabolites on the Sepsis development and progression: a study utilizing two-sample Mendelian randomization

Background

Existing data suggests a potential link between human blood metabolites and sepsis, yet the precise cause-and-effect relationship remains elusive. By using a two-sample Mendelian randomization (MR) analysis, this study aims to establish a causal link between human blood metabolites and sepsis.

Methods

A two-sample MR analysis was employed to investigate the relationship between blood metabolites and sepsis. To assess the causal connection between sepsis and human blood metabolites, five different MR methods were employed, A variety of sensitivity analyses were conducted, including Cochrane's Q test, MR-Egger intercept test, MR-PRESSO and leave-one-out (LOO) analysis. In order to ensure the robustness of the causal association between exposure and outcome, the Bonferroni adjustment was employed. Additionally, we conducted analyses of the metabolic pathways of the identified metabolites using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Small Molecule Pathway Database (SMPDB) database.

Results

The MR analysis revealed a total of 27 metabolites (16 known and 11 unknown) causally linked to the development and progression of sepsis. After applying the Bonferroni correction, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF) remained significant in relation to 28-day all-cause mortality in sepsis. By pathway enrichment analysis, we identified four significant metabolic pathways. Notably, the Alpha Linolenic Acid and Linoleic Acid metabolism pathway emerged as a pivotal contributor to the occurrence and progression of sepsis.

Conclusion

This study provides preliminary evidence of causal associations between human blood metabolites and sepsis, as ascertained by MR analysis. The findings offer valuable insights into the pathogenesis of sepsis and may provide insight into preventive and therapeutic approaches.

P2Y2 purinergic receptor gene deletion protects mice from bacterial endotoxin and sepsis-associated liver injury and mortality

The liver plays a significant role in regulating a wide range of metabolic, homeostatic, and host-defense functions. However, the impact of liver injury on the host's ability to control bacteremia and morbidity in sepsis is not well understood. Leukocyte recruitment and activation lead to cytokine and chemokine release, which, in turn, trigger hepatocellular injury and elevate nucleotide levels in the extracellular milieu. P2Y2 purinergic receptors, G protein-coupled and activated by extracellular ATP/UTP, are expressed at the cell surface of hepatocytes and nonparenchymal cells. We sought to determine whether P2Y2 purinergic receptor function is necessary for the maladaptive host response to bacterial infection and endotoxin-mediated inflammatory liver injury and mortality in mice. We report that P2Y2 purinergic receptor knockout mice (P2Y2-/-) had attenuated inflammation and liver injury, with improved survival in response to LPS/galactosamine (LPS/GalN; inflammatory liver injury) and cecal ligation and puncture (CLP; polymicrobial sepsis). P2Y2-/- livers had attenuated c-Jun NH2-terminal kinase activation, matrix metallopeptidase-9 expression, and hepatocyte apoptosis in response to LPS/GalN and attenuated inducible nitric oxide synthase and nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain containing 3 protein expression in response to CLP. Implicating liver injury in the disruption of amino acid homeostasis, CLP led to lower serum arginine and higher bacterial load and morbidity in the WT mice, whereas serum arginine levels were comparable to sham-operated controls in P2Y2-/- mice, which had attenuated bacteremia and improved survival. Collectively, our studies highlight the pathophysiological relevance of P2Y2 purinergic receptor function in inflammatory liver injury and dysregulation of systemic amino acid homeostasis with implications for sepsis-associated immune dysfunction and morbidity in mice.NEW & NOTEWORTHY Our studies provide experimental evidence for P2Y2 purinergic receptor-mediated potentiation of inflammatory liver injury, morbidity, and mortality, in two well-established animal models of inflammatory liver injury. Our findings highlight the potential to target P2Y2 purinergic signaling to attenuate the induction of "cytokine storm" and prevent its deleterious consequences on liver function, systemic amino acid homeostasis, host response to bacterial infection, and sepsis-associated morbidity and mortality.

Metabolic fingerprint of patients showing responsiveness to treatment of septic shock in intensive care unit

OBJECTIVE

An early metabolic signature associated with the responsiveness to treatment can be useful in the better management of septic shock patients. This would help clinicians in designing personalized treatment protocols for patients showing non-responsiveness to treatment.

METHODS

We analyzed the serum on Day 1 (n = 60), Day 3 (n = 47), and Day 5 (n = 26) of patients with septic shock under treatment using NMR-based metabolomics. Partial least square discriminant analysis (PLS-DA) was performed to generate the list of metabolites that can be identified as potential disease biomarkers having statistical significance (that is, metabolites that had a VIP score > 1, and p value < 0.05, False discovery rate (FDR) < 0.05).

RESULTS

Common significant metabolites amongst the three time points were obtained that distinguished the patients being responsive (R) and non-responsive (NR) to treatments, namely 3 hydroxybutyrate, lactate, and phenylalanine which were lower, whereas glutamate and choline higher in patients showing responsiveness.

DISCUSSION

The study gave these metabolic signatures identifying patients' responsiveness to treatment. The results of the study will aid in the development of targeted therapy for ICU patients.

Endothelial cell metabolism in sepsis

BACKGROUND

Endothelial dysfunction in sepsis is a pathophysiological feature of septic organ failure. Endothelial cells (ECs) exhibit specific metabolic traits and release metabolites to adapt to the septic state in the blood to maintain vascular homeostasis.

METHODS

Web of Science and PubMed were searched from inception to October 1, 2022. The search was limited to the English language only. Two reviewers independently identified studies related to EC metabolism in sepsis. The exclusion criteria were duplicate articles according to multiple search criteria.

RESULTS

Sixty articles were included, and most of them were cell and animal studies. These studies reported the role of glycolysis, oxidative phosphorylation, fatty acid metabolism, and amino acid metabolism in EC homeostasis. including glycolysis, oxidative phosphorylation, fatty acid metabolism and amino acid metabolism. However, dysregulation of EC metabolism can contribute to sepsis progression.

CONCLUSION

There are few clinical studies on EC metabolism in sepsis. Related research mainly focuses on basic research, but some scientific problems have also been clarified. Therefore, this review may provide an overall comprehension and novel aspects of EC metabolism in sepsis.

Clinical assessment of neutrophil gelatinase-associated lipocalin as a potential diagnostic marker for neonatal sepsis: a prospective cohort study

Sepsis is a life-threatening condition associated with high morbidity and mortality rates among neonates. Clinical diagnosis is limited due to the neonates' unspecific signs and symptoms as well as the long time required to obtain the blood culture results. Consequently, there is an urgent need for new biomarkers to early diagnose neonatal sepsis. We aimed to evaluate Neutrophil Gelatinase-Associated Lipocalin (NGAL) diagnostic performance to detect neonatal sepsis. We enrolled 30 neonates with sepsis admitted to the neonatal intensive care units and 30 age- and sex-matched healthy neonates recruited from the neonatal outpatient clinic during their routine follow-up visits. We measured NGAL levels by sandwich enzyme-linked immunosorbent assay, the C-reactive protein (CRP) with nephelometry technique using BN II nephelometer, and the complete blood count by Mindray BC-6800 analysers. NGAL, CRP, TLC, haemoglobin, and platelet levels showed significant differences between cases and control (all p < .001). Of the 30 neonates with sepsis, 17 neonates (56.7%) survived. At 0 h, the NGAL level showed no statistically significant difference between the non-survivors and survivors' groups; however, after 96 h, NGAL was significantly higher in the non-survivors group (p ˂ .001). Our diagnostic analysis showed that NGAL levels have strong discrimination power to early differentiate neonates with sepsis; at the 475.00 pg/ml cut-off value, NGAL showed both sensitivity and specificity of 100% with an area under curve of 100%. Conclusion: Our study suggests that NGAL could be a promising biomarker for neonatal sepsis detection. Further studies with larger sample sizes and survival analysis are warranted to confirm this finding and to clarify the efficacy of NGAL in survival prediction. Key findingsNGAL level was high in neonates with sepsisNGAL level was high in non-survived neonatesNGAL could be a promising diagnostic marker for sepsis.

Identifying potential biomarkers and therapeutic targets for dogs with sepsis using metabolomics and lipidomics analyses

Sepsis is a diagnostic and therapeutic challenge and is associated with morbidity and a high risk of death. Metabolomic and lipidomic profiling in sepsis can identify alterations in metabolism and might provide useful insights into the dysregulated host response to infection, but investigations in dogs are limited. We aimed to use untargeted metabolomics and lipidomics to characterize metabolic pathways in dogs with sepsis to identify therapeutic targets and potential diagnostic and prognostic biomarkers. In this prospective observational cohort study, we examined the plasma metabolomes and lipidomes of 20 healthy control dogs and compared them with those of 21 client-owned dogs with sepsis. Patient data including signalment, physical exam findings, clinicopathologic data and clinical outcome were recorded. Metabolites were identified using an untargeted mass spectrometry approach and pathway analysis identified multiple enriched metabolic pathways including pyruvaldehyde degradation; ketone body metabolism; the glucose-alanine cycle; vitamin-K metabolism; arginine and betaine metabolism; the biosynthesis of various amino acid classes including the aromatic amino acids; branched chain amino acids; and metabolism of glutamine/glutamate and the glycerophospholipid phosphatidylethanolamine. Metabolites were identified with high discriminant abilities between groups which could serve as potential biomarkers of sepsis including 13,14-Dihydro-15-keto Prostaglandin A₂; 12(13)-DiHOME (12,13-dihydroxy-9Z-octadecenoic acid); and 9-HpODE (9-Hydroxyoctadecadienoic acid). Metabolites with higher abundance in samples from nonsurvivors than survivors included 3-(2-hydroxyethyl) indole, indoxyl sulfate and xanthurenic acid. Untargeted lipidomic profiling revealed multiple sphingomyelin species (SM(d34:0)+H; SM(d36:0)+H; SM(d34:0)+HCOO; and SM(d34:1D3)+HCOO); lysophosphatidylcholine molecules (LPC(18:2)+H) and lipophosphoserine molecules (LPS(20:4)+H) that were discriminating for dogs with sepsis. These biomarkers could aid in the diagnosis of dogs with sepsis, provide prognostic information, or act as potential therapeutic targets.

Patient Stratification in Sepsis: Using Metabolomics to Detect Clinical Phenotypes, Sub-Phenotypes and Therapeutic Response

Infections are common and need minimal treatment; however, occasionally, due to inappropriate immune response, they can develop into a life-threatening condition known as sepsis. Sepsis is a global concern with high morbidity and mortality. There has been little advancement in the treatment of sepsis, outside of antibiotics and supportive measures. Some of the difficulty in identifying novel therapies is the heterogeneity of the condition. Metabolic phenotyping has great potential for gaining understanding of this heterogeneity and how the metabolic fingerprints of patients with sepsis differ based on survival, organ dysfunction, disease severity, type of infection, treatment or causative organism. Moreover, metabolomics offers potential for patient stratification as metabolic profiles obtained from analytical platforms can reflect human individuality and phenotypic variation. This article reviews the most relevant metabolomic studies in sepsis and aims to provide an overview of the metabolic derangements in sepsis and how metabolic phenotyping has been used to identify sub-groups of patients with this condition. Finally, we consider the new avenues that metabolomics could open, exploring novel phenotypes and untangling the heterogeneity of sepsis, by looking at advances made in the field with other -omics technologies.

Past Experiences for Future Applications of Metabolomics in Critically Ill Patients with Sepsis and Septic Shocks

A disruption of several metabolic pathways in critically ill patients with sepsis indicates that metabolomics might be used as a more precise tool for sepsis and septic shock when compared with the conventional biomarkers. This article provides information regarding metabolomics studies in sepsis and septic shock patients. It has been shown that a variety of metabolomic pathways are altered in sepsis and septic shock, including amino acid metabolism, fatty acid oxidation, phospholipid metabolism, glycolysis, and tricarboxylic acid cycle. Based upon this comprehensive review, here, we demonstrate that metabolomics is about to change the world of sepsis biomarkers, not only for its utilization in sepsis diagnosis, but also for prognosticating and monitoring the therapeutic response. Additionally, the future direction regarding the establishment of studies integrating metabolomics with other molecular modalities and studies identifying the relationships between metabolomic profiles and clinical characteristics to address clinical application are discussed in this article. All of the information from this review indicates the important impact of metabolomics as a tool for diagnosis, monitoring therapeutic response, and prognostic assessment of sepsis and septic shock. These findings also encourage further clinical investigations to warrant its use in routine clinical settings.

Gender-specific association of oxidative stress and immune response in septic shock mortality using NMR-based metabolomics

Background: Sepsis and septic shock are still associated with a high mortality rate. The early-stage prediction of septic shock outcomes would be helpful to clinicians for designing their treatment protocol. In addition, it would aid clinicians in patient management by understanding gender disparity in terms of clinical outcomes of septic shock by identifying whether there are sex-based differences in sepsis-associated mortality. Objective: This study aimed to test the hypothesis that gender-based metabolic heterogeneity is associated with sepsis survival and identify the biomarkers of mortality for septic shock in an Indian cohort. Method: The study was performed in an Indian population cohort diagnosed with sepsis/septic shock within 24 hours of admission. The study group was 50 patients admitted to intensive care, comprising 23 females and 27 males. Univariate and multivariate analysis were performed to identify the biomarkers for septic shock mortality and the gender-specific metabolic fingerprint in septic shock-associated mortality. Results: The energy-related metabolites, ketone bodies, choline, and NAG were found to be primarily responsible for differentiating survivors and non-survivors. The gender-based mortality stratification identified a female-specific association of the anti-inflammatory response, innate immune response, and β oxidation, and a male-specific association of the pro-inflammatory response to septic shock. Conclusion: The identified mortality biomarkers may help clinicians estimate the severity of a case, as well as predict the outcome and treatment efficacy. The study underlines that gender is one of the most significant biological factors influencing septic shock metabolomic profiles. This understanding can be utilized to identify novel gender-specific biomarkers and innovative targets relevant for gender medicine.

An analysis of urine and serum amino acids in critically ill patients upon admission by means of targeted LC-MS/MS: a preliminary study

Sepsis, defined as a dysregulated host response to infection, causes the interruption of homeostasis resulting in metabolic changes. An examination of patient metabolites, such as amino acids, during the early stage of sepsis may facilitate diagnosing and assessing the severity of the sepsis. The aim of this study was to compare patterns of urine and serum amino acids relative to sepsis, septic shock and survival. Urine and serum samples were obtained from healthy volunteers (n = 15) once or patients (n = 15) within 24 h of a diagnosis of sepsis or septic shock. Concentrations of 25 amino acids were measured in urine and serum samples with liquid chromatography-electrospray mass spectrometry. On admission in the whole cohort, AAA, ABA, mHis, APA, Gly-Pro and tPro concentrations were significantly lower in the serum than in the urine and Arg, Gly, His, hPro, Leu, Ile, Lys, Orn, Phe, Sarc, Thr, Tyr, Asn and Gln were significantly higher in the serum than in the urine. The urine Gly-Pro concentration was significantly higher in septic shock than in sepsis. The serum Cit concentration was significantly lower in septic shock than in sepsis. The urine ABA, mHis and Gly-Pro, and serum Arg, hPro and Orn concentrations were over two-fold higher in the septic group compared to the control group. Urine and serum amino acids measured in septic patients on admission to the ICU may shed light on a patient’s metabolic condition during sepsis or septic shock.

The role of skeletal muscle in the pathogenesis of altered concentrations of branched-chain amino acids (valine, leucine, and isoleucine) in liver cirrhosis, diabetes, and other diseases

The article shows that skeletal muscle plays a dominant role in the catabolism of branched-chain amino acids (BCAAs; valine, leucine, and isoleucine) and the pathogenesis of their decreased concentrations in liver cirrhosis, increased concentrations in diabetes, and nonspecific alterations in disorders with signs of systemic inflammatory response syndrome (SIRS), such as burn injury and sepsis. The main role of skeletal muscle in BCAA catabolism is due to its mass and high activity of BCAA aminotransferase, which is absent in the liver. Decreased BCAA levels in liver cirrhosis are due to increased use of the BCAA as a donor of amino group to alpha-ketoglutarate for synthesis of glutamate, which in muscles acts as a substrate for ammonia detoxification to glutamine. Increased BCAA levels in diabetes are due to alterations in glycolysis, citric acid cycle, and fatty acid oxidation. Decreased glycolysis and citric cycle activity impair BCAA transamination to branched-chain keto acids (BCKAs) due to decreased supply of amino group acceptors (alpha-ketoglutarate, pyruvate, and oxaloacetate); increased fatty acid oxidation inhibits flux of BCKA through BCKA dehydrogenase due to increased supply of NADH and acyl-CoAs. Alterations in BCAA levels in disorders with SIRS are inconsistent due to contradictory effects of SIRS on muscles. Specifically, increased proteolysis and insulin resistance tend to increase BCAA levels, whereas activation of BCKA dehydrogenase and glutamine synthesis tend to decrease BCAA levels. The studies are needed to elucidate the role of alterations in BCAA metabolism and the effects of BCAA supplementation on the outcomes of specific diseases.

Untargeted and Targeted Metabolomic Profiling of Preterm Newborns with EarlyOnset Sepsis: A Case-Control Study

Sepsis is a major concern in neonatology, but there are no reliable biomarkers for its early diagnosis. The aim of the study was to compare the metabolic profiles of plasma and urine samples collected at birth from preterm neonates with and without earlyonset sepsis (EOS) to identify metabolic perturbations that might orient the search for new early biomarkers. All preterm newborns admitted to the neonatal intensive care unit were eligible for this proof-of-concept, prospective case-control study. Infants were enrolled as “cases” if they developed EOS, and as “controls”if they did not. Plasma samples collected at birth and urine samples collected within 24 h of birth underwent untargeted and targeted metabolomic analysis using mass spectrometry coupled with ultra-performance liquid chromatography. Univariate and multivariate statistical analyses were applied. Of 123 eligible newborns, 15 developed EOS. These 15 newborns matched controls for gestational age and weight. Metabolomic analysis revealed evident clustering of the cases versus controls, with the glutathione and tryptophan metabolic pathways markedly disrupted in the former. In conclusion, neonates with EOS had a metabolic profile at birth that clearly distinguished them from those without sepsis, and metabolites of glutathione and tryptophan pathways are promising as new biomarkers of neonatal sepsis.

Serum metabolic profiles of septic shock patients based upon co-morbidities and other underlying conditions

Diagnosis and management of patients with septic shock is still a significant challenge for clinicians with its high mortality amongst hospitalized patients. Septic shock is a heterogeneous condition and is usually accompanied by various underlying disease conditions. Dissecting the specific metabolic changes induced by these underlying disease conditions through metabolomics has shown the potential to improve our understanding of the disease's relevant pathophysiological mechanisms, leading to improved treatment. This study has shown the metabolic alterations caused due to co-morbid conditions like diabetes, hypertension, CAD, and CKD in septic shock. It has also shown the distinct metabolic profiles of septic shock patients with underlying respiratory illnesses and encephalopathy. Metabolic profiling of sera obtained from 50 septic shock patients and 20 healthy controls was performed using high-resolution 1D ¹H CPMG and diffusion-edited NMR spectra. Univariate and multivariate statistical analyses were performed to identify the potential molecular biomarkers. Noted dysregulations in amino acids, carbohydrates, and lipid metabolism were observed in septic shock patients. Further stratification within the septic shock patients based on co-morbid conditions and primary diagnosis has shown their role in causing metabolic alterations. Evaluation of these compounds during treatment will help design a personalized treatment protocol for the patients, improving therapeutics.

Metabolomics: An emerging potential approach to decipher critical illnesses

Critical illnesses contribute to the maximum morbidity and mortality of hospitalized patients. Acute respiratory distress syndrome (ARDS) and sepsis/septic shock are the two most common acute illnesses associated with intensive care unit (ICU) admission. Once triggered, both have an identical underlying mechanism, portrayed by inflammation and endothelial dysfunction. The diagnosis of ARDS is based on clinical findings, laboratory tests, and radiological imaging. Blood cultures remain the gold standard for the diagnosis of sepsis, with the limitation of time delay and low positive yield. A combination of biomarkers has been proposed to diagnose and prognosticate these acute disorders with strengths and limitations, but still, the gold standard has been elusive to clinicians. In this review article, we illustrate the potential of metabolomics to unravel biomarkers that can be clinically utilized as a rapid prognostic and diagnostic tool associated with specific patient populations (ARDS and sepsis/septic shock) based on the available scientific data.

Title NMR-based metabolic profiling provides diagnostic and prognostic information in critically ill children with suspected infection

Sepsis, defined as life-threatening organ dysfunction caused by infection is difficult to distinguish clinically from infection or post-operative inflammation. We hypothesized that in a heterogeneous group of critically ill children, there would be different metabolic profiles between post-operative inflammation, bacterial and viral infection and infection with or without organ dysfunction. 1D ¹H nuclear magnetic resonance spectra were acquired in plasma samples from critically ill children. We included children with bacterial (n = 25) and viral infection (n = 30) and controls (n = 58) (elective cardiac surgery without infection). Principal component analysis was used for data exploration and partial least squares discriminant analysis models for the differences between groups. Area under receiver operating characteristic curve (AUC) values were used to evaluate the models. Univariate analysis demonstrated differences between controls and bacterial and viral infection. There was excellent discrimination between bacterial and control (AUC = 0.94), and viral and control (AUC = 0.83), with slightly more modest discrimination between bacterial and viral (AUC = 0.78). There was modest discrimination (AUC = 0.73) between sepsis with organ dysfunction and infection with no organ dysfunction. In critically ill children, NMR metabolomics differentiates well between those with a post-operative inflammation but no infection, and those with infection (bacterial and viral), and between sepsis and infection.

Metabolic Modulation and Potential Biomarkers of the Prognosis Identification for Severe Aortic Stenosis after TAVR by a Metabolomics Study

Objectives

To investigate the metabolic profile in patients with aortic stenosis (AS) after transcatheter aortic valve replacement (TAVR) and explore the potential biomarkers to predict prognosis after TAVR based on metabolomics.

Methods and Results

Fifty-nine consecutive AS patients were prospectively recruited. Blood samples from the ascending aorta, coronary sinus, and peripheral vein at before and after TAVR were collected, respectively. Liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry were performed to analyze the metabolic profile before and after TAVR. Influential metabolites were identified by integrating the univariate test, multivariate analysis, and weighted gene coexpression network analysis (WGCNA) algorithm. PLS-DA analysis revealed a significant extremely early (within 30 minutes after TAVR) alterations of metabolites in the ascending aorta, coronary sinus, and peripheral vein. The early (within 7 days after TAVR) changed metabolites in the peripheral vein were involved in purine metabolism, primary bile acid biosynthesis, glycerolipid metabolism, amino sugar and nucleotide sugar metabolism, one carbon pool by folate and alanine, and the aspartate and glutamate metabolism pathway. We used volcano plots to find that the cardiac-specific changed metabolites were enriched to the sphingolipid metabolism pathway after TAVR. Besides, WGCNA algorithm was performed to reveal that arginine and proline metabolites could reflect left ventricle regression to some extent.

Conclusion

This is the first study to reveal systemic and cardiac metabolites changed significantly in patients with AS after TAVR. Some altered metabolites involved in the arginine and proline metabolism pathway in the peripheral vein could predict left ventricle regression, which merited further study.

Differences in metabolic profiles between bicuspid and tricuspid aortic stenosis in the setting of transcatheter aortic valve replacement

Background

To explore why bicuspid aortic stenosis has certain clinical differences from the tricuspid morphology, we evaluated the metabolomics profile involved in bicuspid aortic valve (BAV) aortic stenosis prior to and after transcatheter aortic valve replacement (TAVR) in comparison with tricuspid aortic valve (TAV).

Methods

In this TAVR cohort with prospectively collected data, blood samples were obtained before TAVR valve deployment and at the 7th day after TAVR, which were then sent for liquid and gas chromatography-mass spectrometry detection. Besides comparisons between BAV and TAV, BAV patients were also divided in subgroups according to baseline hemodynamics (i.e. maximal transaortic velocity, V_max) and post-procedural reverse left ventricular (LV) remodeling (i.e. the change in LV mass index from baseline, ∆LVMI) for further analysis. Metabolic differences between groups were identified by integrating univariate test, multivariate analysis and weighted correlation network analysis algorithm.

Results

A total of 57 patients were enrolled including 33 BAV patients. The BAV group showed lower arginine and proline metabolism both before and post TAVR than TAV represented by decreased expression of L-Glutamine. In BAV subgroup analysis, patients with baseline V_max > 5 m/s (n = 11) or the 4^th quartile of change in ∆LVMI at one-year follow-up (i.e. poorly-recovered LV, n = 8) showed elevated arachidonic acid metabolism compared with V_max < 4.5 m/s (n = 12) or the 1^st quartile of ∆LVMI (i.e. well-recovered LV, n = 8) respectively.

Conclusions

Difference in arginine and proline metabolism was identified between BAV and TAV in TAVR recipients. Elevated arachidonic acid metabolism may reflect more severe baseline hemodynamics and worse LV reserve remodeling after TAVR in BAV.

Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation

BACKGROUND

Sepsis is a leading cause of death in intensive care units (ICUs), but outcomes of individual patients are difficult to predict. The recently developed clinical metabolomics has been recognized as a promising tool in the clinical practice of critical illness. The objective of this study was to identify the unique metabolic biomarkers and their pathways in the blood of sepsis nonsurvivors and to assess the prognostic value of these pathways.

METHODS

We searched PubMed, EMBASE, Cochrane, Web of Science, CNKI, Wangfang Data, and CQVIP from inception until July 2019. Eligible studies included the metabolomic analysis of blood samples from sepsis patients with the outcome. The metabolic pathway was assigned to each metabolite biomarker. The meta-analysis was performed using the pooled fold changes, area under the receiver operating characteristic curve (AUROC), and vote-counting of metabolic pathways. We also conducted a prospective cohort metabolomic study to validate the findings of our meta-analysis.

RESULTS

The meta-analysis included 21 cohorts reported in 16 studies with 2509 metabolite comparisons in the blood of 1287 individuals. We found highly limited overlap of the reported metabolite biomarkers across studies. However, these metabolites were enriched in several death-related metabolic pathways (DRMPs) including amino acids, mitochondrial metabolism, eicosanoids, and lysophospholipids. Prediction of sepsis death using DRMPs yielded a pooled AUROC of 0.81 (95% CI 0.76-0.87), which was similar to the combined metabolite biomarkers with a merged AUROC of 0.82 (95% CI 0.78-0.86) (P > 0.05). A prospective metabolomic analysis of 188 sepsis patients (134 survivors and 54 nonsurvivors) using the metabolites from DRMPs produced an AUROC of 0.88 (95% CI 0.78-0.97). The sensitivity and specificity for the prediction of sepsis death were 80.4% (95% CI 66.9-89.4%) and 78.8% (95% CI 62.3-89.3%), respectively.

CONCLUSIONS

DRMP analysis minimizes the discrepancies of results obtained from different metabolomic methods and is more practical than blood metabolite biomarkers for sepsis mortality prediction.

TRIAL REGISTRATION

The meta-analysis was registered on OSF Registries, and the prospective cohort study was registered on the Chinese Clinical Trial Registry (ChiCTR1800015321).

Nuclear magnetic resonance-based serum metabolomic analysis reveals different disease evolution profiles between septic shock survivors and non-survivors

Background

Septic shock is the most severe phase of sepsis and is associated with high rates of mortality. However, early stage prediction of septic shock outcomes remains difficult. Metabolomic techniques have emerged as a promising tool for improving prognosis.

Methods

Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models separating the serum metabolomes of survivors from those of non-survivors were established with samples obtained at the intensive care unit (ICU) admission (H0) and 24 h later (H24). For 51 patients with available H0 and H24 samples, multi-level modeling was performed to provide insight into different metabolic evolutions that occurred between H0 and H24 in the surviving and non-surviving patients. Relative quantification and receiver operational characteristic curves (ROC) were applied to estimate the predictability of key discriminatory metabolites for septic shock mortality.

Results

Metabolites that were involved in energy supply and protein breakdown were primarily responsible for differentiating survivors from non-survivors. This was not only seen in the H0 and H24 discriminatory models, but also in the H0-H24 paired models. Reanalysis of extra H0-H24 paired samples in the established multi-level model demonstrated good performance of the model for the classification of samplings. According to the ROC results, nine discriminatory metabolites defined consistently from the unpaired model and the H0-H24 time-trend change (Δ_H24-H0) show good prediction of mortality. These results suggest that NMR-based metabolomic analysis is useful for a better overall assessment of septic shock patients.

Conclusions

Dysregulation of the metabolites identified by this study is associated with poor outcomes for septic shock. Evaluation of these compounds during the first 24 h after ICU admission in the septic shock patient may be helpful for estimating the severity of cases and for predicting outcomes.

Trial registration

All human serum samples were collected and stored, provided by the “center of biologic resources for liver disease”, in Jean Verdier Hospital, Bondy, France (BB-0033-00027).

Electronic supplementary material

The online version of this article (10.1186/s13054-019-2456-z) contains supplementary material, which is available to authorized users.

Septic Shock Nonsurvivors Have Persistently Elevated Acylcarnitines Following Carnitine Supplementation

INTRODUCTION

Sepsis-induced metabolic disturbances include hyperlactatemia, disruption of glycolysis, protein catabolism, and altered fatty acid metabolism. It may also lower serum L-carnitine that supports the use of L-carnitine supplementation as a treatment to ameliorate several of these metabolic consequences.

METHODS

To further understand the association between L-carnitine-induced changes in serum acylcarnitines, fatty acid metabolism and survival, serum samples from (T0), 12 hfollowing completion (T24) of L-carnitine (n = 16) or placebo (n = 15) administration, and 48 h (T48) after enrollment from patients with septic shock enrolled in a randomized control trial were assayed for acylcarnitines, free fatty acids, and insulin. Data were analyzed comparing 1-year survivors and nonsurvivors within treatment groups.

RESULTS

Mortality was 8 of 16 (50%) and 12 of 15 (80%) at 1 year for L-carnitine and placebo-treated patients, respectively. Free carnitine, C2, C3, and C8 acylcarnitines were higher among nonsurvivors at enrollment. L-Carnitine treatment increased levels of all measured acylcarnitines; an effect that was sustained for at least 36 h following completion of the infusion and was more prominent among nonsurvivors. Several fatty acids followed a similar, though less consistent pattern. Glucose, lactate, and insulin levels did not differ based on survival or treatment arm.

CONCLUSIONS

In human patients with septic shock, L-Carnitine supplementation increases a broad range of acylcarnitine concentrations that persist after cessation of infusion, demonstrating both immediate and sustained effects on the serum metabolome. Nonsurvivors demonstrate a distinct metabolic response to L-carnitine compared with survivors, which may indicate preexisting or more profound metabolic derangement that constrains any beneficial response to treatment.

Metabolomics approach in lung tissue of septic rats and the interventional effects of Xuebijing injection using UHPLC-Q-Orbitrap-HRMS

Sepsis is the dysregulated host response to an infection which leads to life-threatening organ dysfunction. Metabolomic profiling in bio-fluid or tissue is vital for elucidating the pathogenesis of sepsis and evaluating therapeutic effects of medication. In this study, an untargeted metabolomics approach was applied to study the metabolic changes in lung tissue of septic rats induced by cecal ligation and puncture (CLP) and investigate the treatment effects of Xubijing injection (XBJ). Metabolomics analyses were performed on ultra-high performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q-Orbitrap-HRMS) together with multivariate statistical analysis. A total of 26 differential metabolites between CLP and sham-operated group were identified. The altered metabolic pathways included energy metabolism, amino metabolism, lipid metabolism, fatty acid metabolism and hormone metabolism. Among the 26-varied metabolites, 15 were significantly regulated after XBJ treatment. The metabolic pathway network of sepsis was drawn to interpret the pathological feature of lung damage caused by sepsis and the underlying regulating mechanism of XBJ on the molecular levels. Our findings display that LC-MS-based metabolomics is a useful tool for uncovering the underlying molecular mechanism of sepsis, and XBJ may exert therapeutic effect by regulating multiple metabolic pathways.

Energy Demands of Early Life Drive a Disease Tolerant Phenotype and Dictate Outcome in Neonatal Bacterial Sepsis

Bacterial sepsis is one of the leading causes of death in newborns. In the face of growing antibiotic resistance, it is crucial to understand the pathology behind the disease in order to develop effective interventions. Neonatal susceptibility to sepsis can no longer be attributed to simple immune immaturity in the face of mounting evidence that the neonatal immune system is tightly regulated and well controlled. The neonatal immune response is consistent with a "disease tolerance" defense strategy (minimizing harm from immunopathology) whereas adults tend toward a "disease resistance" strategy (minimizing harm from pathogens). One major advantage of disease tolerance is that is less energetically demanding than disease resistance, consistent with the energetic limitations of early life. Immune effector cells enacting disease resistance responses switch to aerobic glycolysis upon TLR stimulation and require steady glycolytic flux to maintain the inflammatory phenotype. Rapid and intense upregulation of glucose uptake by immune cells necessitates an increased reliance on fatty acid metabolism to (a) fuel vital tissue function and (b) produce immunoregulatory intermediates which help control the magnitude of inflammation. Increasing disease resistance requires more energy: while adults have fat and protein stores to catabolize, neonates must reallocate resources away from critical growth and development. This understanding of sepsis pathology helps to explain many of the differences between neonatal and adult immune responses. Taking into account the central role of metabolism in the host response to infection and the severe metabolic demands of early life, it emerges that the striking clinical susceptibility to bacterial infection of the newborn is at its core a problem of metabolism. The evidence supporting this novel hypothesis, which has profound implications for interventions, is presented in this review.

Metabolic systems analysis of LPS induced endothelial dysfunction applied to sepsis patient stratification

Endothelial dysfunction contributes to sepsis outcome. Metabolic phenotypes associated with endothelial dysfunction are not well characterised in part due to difficulties in assessing endothelial metabolism in situ. Here, we describe the construction of iEC2812, a genome scale metabolic reconstruction of endothelial cells and its application to describe metabolic changes that occur following endothelial dysfunction. Metabolic gene expression analysis of three endothelial subtypes using iEC2812 suggested their similar metabolism in culture. To mimic endothelial dysfunction, an in vitro sepsis endothelial cell culture model was established and the metabotypes associated with increased endothelial permeability and glycocalyx loss after inflammatory stimuli were quantitatively defined through metabolomics. These data and transcriptomic data were then used to parametrize iEC2812 and investigate the metabotypes of endothelial dysfunction. Glycan production and increased fatty acid metabolism accompany increased glycocalyx shedding and endothelial permeability after inflammatory stimulation. iEC2812 was then used to analyse sepsis patient plasma metabolome profiles and predict changes to endothelial derived biomarkers. These analyses revealed increased changes in glycan metabolism in sepsis non-survivors corresponding to metabolism of endothelial dysfunction in culture. The results show concordance between endothelial health and sepsis survival in particular between endothelial cell metabolism and the plasma metabolome in patients with sepsis.

Novel Biomarker Candidates for Febrile Neutropenia in Hematological Patients Using Nontargeted Metabolomics

Background

Novel potential small molecular biomarkers for sepsis were analyzed with nontargeted metabolite profiling to find biomarkers for febrile neutropenia after intensive chemotherapy for hematological malignancies.

Methods

Altogether, 85 patients were included into this prospective study at the start of febrile neutropenia after intensive chemotherapy for acute myeloid leukemia or after autologous stem cell transplantation. The plasma samples for the nontargeted metabolite profiling analysis by liquid chromatography-mass spectrometry were taken when fever rose over 38° and on the next morning.

Results

Altogether, 90 differential molecular features were shown to explain the differences between patients with complicated (bacteremia, severe sepsis, or fatal outcome) and noncomplicated courses of febrile neutropenia. The most differential compounds were an androgen hormone, citrulline, and phosphatidylethanolamine PE(18:0/20:4). The clinical relevance of the findings was evaluated by comparing them with conventional biomarkers like C-reactive protein and procalcitonin.

Conclusion

These results hold promise to find out novel biomarkers for febrile neutropenia, including citrulline. Furthermore, androgen metabolism merits further studies.

NMR-Based Plasma Metabolomics at Set Intervals in Newborn Dairy Calves with Severe Sepsis

The aim of this first study was to reveal the new potential biomarkers by a metabolomics approach in severe septic calves. Sepsis is a common cause of morbidity and mortality in newborn dairy calves. The main challenges with the use of biomarkers of sepsis in domestic animals are their availability, cost, and time required to obtain a result. Metabolomics may offer the potential to identify biomarkers that define calf sepsis in terms of combined clinical, physiological, and pathobiological abnormalities. To our knowledge, this is the first study presenting an NMR- (nuclear magnetic resonance-) based plasma metabolomics at set intervals in neonatal septic calves. Twenty neonatal dairy calves with severe sepsis and ten healthy calves were used. Hematological and biochemical health profiles were gathered in plasma samples at set intervals. Similarly, NMR spectra were acquired. All diseased animals (except one) died after 72 hours. Clinical and laboratory results were in accordance with those of severe septic animals. Multivariate analysis on NMR plasma spectra proved to be an excellent tool for faster identification of calves with severe sepsis from healthy animals. The NMR-based metabolomic profile may contribute to the better understanding of severe sepsis in newborn calves.

Determination of candidate metabolite biomarkers associated with recurrence of HCV-related hepatocellular carcinoma

Hepatitis C virus (HCV) infection is associated with a high risk of developing hepatocellular carcinoma (HCC) and HCC recurrence remains the primary threat to outcomes after curative therapy. In this study, we compared recurrent and non-recurrent HCC patients treated with radiofrequency ablation (RFA) in order to identify characteristic metabolic profile variations associated with HCC recurrence. Gas chromatography-mass spectrometry (GC-MS) -based metabolomic analyses were conducted on serum samples obtained before and after RFA therapy. Significant variations were observed in metabolites in the glycerolipid, tricarboxylic acid (TCA) cycle, fatty acid, and amino acid pathways between recurrent and non-recurrent patients. Observed differences in metabolites associated with recurrence did not coincide before and after treatment except for fatty acids. Based on the comparison of serum metabolomes between recurrent and non-recurrent patients, key discriminatory metabolites were defined by a random forest (RF) test. Two combinations of these metabolites before and after RFA treatment showed outstanding performance in predicting HCV-related HCC recurrence, they were further confirmed by an external validation set. Our study showed that the determined combination of metabolites may be potential biomarkers for the prediction of HCC recurrence before and after RFA treatment.

Metabolomics as a Driver in Advancing Precision Medicine in Sepsis

The objective of this review is to explain the science of metabolomics-a science of systems biology that measures and studies endogenous small molecules (metabolites) that are present in a single biological sample-and its application to the diagnosis and treatment of sepsis. In addition, we discuss how discovery through metabolomics can contribute to the development of precision medicine targets for this complex disease state and the potential avenues for those new discoveries to be applied in the clinical environment. A nonsystematic literature review was performed focusing on metabolomics, pharmacometabolomics, and sepsis. Human (adult and pediatric) and animal studies were included. Metabolomics has been investigated in the diagnosis, prognosis, and risk stratification of sepsis, as well as for the identification of drug target opportunities. Metabolomics elucidates a new level of detail when compared with other systems biology sciences, with regard to the metabolites that are most relevant in the pathophysiology of sepsis, as well as highlighting specific biochemical pathways at work in sepsis. Metabolomics also highlights biochemical differences between sepsis survivors and nonsurvivors at a level of detail greater than that demonstrated by genomics, transcriptomics, or proteomics, potentially leading to actionable targets for new therapies. The application of pharmacometabolomics and its integration with other systems pharmacology to sepsis therapeutics could be particularly helpful in differentiating drug responders and nonresponders and furthering knowledge of mechanisms of drug action and response. The accumulated literature on metabolomics suggests it is a viable tool for continued discovery around the pathophysiology, diagnosis and prognosis, and treatment of sepsis in both adults and children, and it provides a greater level of biochemical detail and insight than other systems biology approaches. However, the clinical application of metabolomics in sepsis has not yet been fully realized. Prospective validation studies are needed to translate metabolites from the discovery phase into the clinical utility phase.