Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach

Modulation of Metabolomic Profile in Sepsis According to the State of Immune Activation

OBJECTIVE

To investigate the metabolomic profiles associated with different immune activation states in sepsis patients.

DESIGN

Subgroup analysis of the PROVIDE (a Personalized Randomized trial of Validation and restoration of Immune Dysfunction in severe infections and Sepsis) prospective clinical study.

SETTING

Results of the PROVIDE study showed that patients with sepsis may be classified into three states of immune activation: 1) macrophage-activation-like syndrome (MALS) characterized by hyperinflammation, sepsis-induced immunoparalysis, and 3) unclassified or intermediate patients without severe immune dysregulation.

PATIENTS OR SUBJECTS

Two hundred ten patients from 14 clinical sites in Greece meeting the Sepsis-3 definitions with lung infection, acute cholangitis, or primary bacteremia.

INTERVENTIONS

During our comparison, we did not perform any intervention.

MEASUREMENTS AND MAIN RESULTS

Untargeted metabolomics analysis was performed on plasma samples from 210 patients (a total of 1394 products). Differential abundance analysis identified 221 significantly different metabolites across the immune states. Metabolites were enriched in pathways related to ubiquinone biosynthesis, tyrosine metabolism, and tryptophan metabolism when comparing MALS to immunoparalysis and unclassified patients. When comparing MALS to unclassified, 312 significantly different metabolites were found, and pathway analysis indicated enrichment in multiple pathways. Comparing immunoparalysis to unclassified patients revealed only two differentially regulated metabolites.

CONCLUSIONS

Findings suggest distinct metabolic dysregulation patterns associated with different immune dysfunctions in sepsis: the strongest metabolic dysregulation is associated with MALS.

Exploring the circulating metabolome of sepsis: metabolomic and lipidomic profiles sampled in the ambulance

BACKGROUND

Sepsis is defined as a dysfunctional host response to infection. The diverse clinical presentations of sepsis pose diagnostic challenges and there is a demand for enhanced diagnostic markers for sepsis as well as an understanding of the underlying pathological mechanisms involved in sepsis. From this perspective, metabolomics has emerged as a potentially valuable tool for aiding in the early identification of sepsis that could highlight key metabolic pathways and underlying pathological mechanisms.

OBJECTIVE

The aim of this investigation is to explore the early metabolomic and lipidomic profiles in a prospective cohort where plasma samples (n = 138) were obtained during ambulance transport among patients with infection according to clinical judgement who subsequently developed sepsis, patients who developed non-septic infection, and symptomatic controls without an infection.

METHODS

Multiplatform metabolomics and lipidomics were performed using UHPLC-MS/MS and UHPLC-QTOFMS. Uni- and multivariable analysis were used to identify metabolite profiles in sepsis vs symptomatic control and sepsis vs non-septic infection.

RESULTS

Univariable analysis disclosed that out of the 457 annotated metabolites measured across three different platforms, 23 polar, 27 semipolar metabolites and 133 molecular lipids exhibited significant differences between patients who developed sepsis and symptomatic controls following correction for multiple testing. Furthermore, 84 metabolites remained significantly different between sepsis and symptomatic controls following adjustment for age, sex, and Charlson comorbidity score. Notably, no significant differences were identified in metabolites levels when comparing patients with sepsis and non-septic infection in univariable and multivariable analyses.

CONCLUSION

Overall, we found that the metabolome, including the lipidome, was decreased in patients experiencing infection and sepsis, with no significant differences between the two conditions. This finding indicates that the observed metabolic profiles are shared between both infection and sepsis, rather than being exclusive to sepsis alone.

Persistence and Sexual Dimorphism of Gut Dysbiosis and Pathobiome after Sepsis and Trauma

OBJECTIVE

To evaluate the persistence of intestinal microbiome dysbiosis and gut-plasma metabolomic perturbations following severe trauma or sepsis weeks after admission in patients experiencing chronic critical illness (CCI).

SUMMARY

Trauma and sepsis can lead to gut dysbiosis and alterations in the plasma and fecal metabolome. However, the impact of these perturbations and correlations between gut dysbiosis and the plasma metabolome in chronic critical illness have not been studied.

METHODS

A prospective observational cohort study was performed with healthy subjects, severe trauma patients, and patients with sepsis residing in an intensive care unit for 2 to 3 weeks. A high-throughput multi-omics approach was utilized to evaluate the gut microbial and gut-plasma metabolite responses in critically ill trauma and sepsis patients 14 to 21 days after intensive care unit admission.

RESULTS

Patients in the sepsis and trauma cohorts demonstrated strikingly depleted gut microbiome diversity, with significant alterations and specific pathobiome patterns in the microbiota composition compared to healthy subjects. Further subgroup analyses based on sex revealed resistance to changes in microbiome diversity among female trauma patients compared to healthy counterparts. Sex--specific changes in fecal metabolites were also observed after trauma and sepsis, while plasma metabolite changes were similar in both males and females.

CONCLUSIONS

Dysbiosis induced by trauma and sepsis persists up to 14 to 21 days after onset and is sex-specific, underscoring the implication of pathobiome and entero-septic microbial-metabolite perturbations in post-sepsis and posttrauma chronic critical illness. This indicates resilience to infection or injury in females' microbiome and should inform and facilitate future precision/personalized medicine strategies in the intensive care unit.

High-resolution plasma metabolomics and thiamine status in critically Ill adult patients

INTRODUCTION

Thiamine (Vitamin B1) is an essential micronutrient and is classically considered a co-factor in energy metabolism. The association between thiamine status and whole-body metabolism in critical illness has not been studied.

OBJECTIVES

To determine association between whole blood thiamine pyrophosphate (TPP) concentrations and plasma metabolites and connected metabolic pathways using high resolution metabolomics (HRM) in critically ill patients.

METHODS

Cross-sectional study performed at Erciyes University Hospital, Kayseri, Turkey and Emory University, Atlanta, GA, USA. Participants were critically ill adults with an expected length of intensive care unit stay longer than 48 h and receiving chronic furosemide therapy. A total of 76 participants were included. Mean age was 69 years (range 33-92 years); 65% were female. Blood for TPP and metabolomics was obtained on the day of ICU admission. Whole blood TPP was measured by HPLC and plasma HRM was performed using liquid chromatography/mass spectrometry. Data was analyzed using regression analysis of TPP levels against all plasma metabolomic features in metabolome-wide association studies (MWAS). MWAS using the highest and lowest TPP concentration tertiles was performed as a secondary analysis.

RESULTS

Specific metabolic pathways associated with whole blood TPP levels in regression and tertile analysis included pentose phosphate, fructose and mannose, branched chain amino acid, arginine and proline, linoleate, and butanoate pathways.

CONCLUSIONS

Plasma HRM revealed that thiamine status, determined by whole blood TPP concentrations, was significantly associated with metabolites and metabolic pathways related to metabolism of energy, carbohydrates, amino acids, lipids, and the gut microbiome in adult critically ill patients.

Comparative analysis of lysophospholipid metabolism profiles and clinical characteristics in patients with high vs. low C-reactive protein levels in acute exacerbations of chronic obstructive pulmonary disease

BACKGROUND

The precise role of lysophospholipids (LysoPLs) in the pathogenesis of acute exacerbations of Chronic Obstructive Pulmonary Disease (AECOPD) remains unclear. In this study, we sought to elucidate the differences in serum LysoPL metabolite profiles and their correlation with clinical features between patients with low versus high CRP levels.

METHODS

A total of 58 patients with AECOPD were enrolled in the study. Patients were classified into two groups: low CRP group (CRP < 20 mg/L, n = 34) and high CRP group (CRP ≥ 20 mg/L, n = 24). Clinical data were collected, and the LysoPL metabolite profiles were analyzed using Liquid Chromatography-Mass Spectrometry (LC-MS) and identified by matching with the LipidBlast library.

RESULTS

Nineteen differential LysoPLs were initially identified through Student's t-test (p < 0.05 and VIP > 1). Subsequently, four LysoPLs, LPC(16:0), LPE(18:2), LPC(22:0), and LPC(24:0), were identified by FDR adjustment (adjusted p < 0.05). These four lysoPLs had a significant negative correlation with CRP. Integrative analysis revealed that LPC (16:0) and LPC (22:0) correlated with less hypercapnic respiratory failure and ICU admission.

CONCLUSION

AECOPD patients with high CRP levels demonstrated a distinctive LysoPL metabolism profile, with LPC (16:0), LPE(18:2), LPC(22:0), and LPC(24:0) being the most significantly altered lipid molecules. These alterations were associated with poorer clinical outcomes.

Association of Serum Metabolites with Serum Indices and Preanalytical Factors of Biobanked Serum Samples

Background: Serum indices (hemolysis, icterus, and lipemia; HIL) are known to impact clinical chemistry assay results. This study aimed to investigate the impact of HIL indices on serum metabolite profiles and the association of serum metabolite levels with pre-analytical factors of serum samples. Methods: A cohort of serum samples (n = 12,196) from the Korean Genome and Epidemiology Study (KoGES) was analyzed for HIL indices and the pre-analytical variables (SPRECs) which were generated in the process of serum collection. We further performed targeted metabolomics on a subset comprising hemolyzed (n = 60), icteric (n = 60), lipemic (n = 60) groups, and a common control group of non-HIL samples (n = 60) using the Absolute IDQ p180 kit. Results: We found 22 clinical chemistry analytes significantly associated with hemolysis, 25 with icterus, and 24 with lipemia (p < 0.0001). Serum metabolites (n = 27) were associated with all of hemolysis, icterus, and lipemia (p < 0.05). The PC ae C36 2 had exhibited a significant association with pre-analytical factors corresponding to the third (pre-centrifugation delay between processing) and sixth (post-centrifugation) elements of the SPREC. Conclusions: This study showed the association of the serum index and pre-analytical factors with serum metabolite profiles. In addition, the association of pre-analytical factors with serum metabolite concentrations would corroborate the utility of SPRECs for the quality control of biobanked serum samples.

Sepsis, Management & Advances in Metabolomics

Though there have been developments in clinical care and management, early and accurate diagnosis and risk stratification are still bottlenecks in septic shock patients. Since septic shock is multifactorial with patient-specific underlying co-morbid conditions, early assessment of sepsis becomes challenging due to variable symptoms and clinical manifestations. Moreover, the treatment strategies are traditionally based on their progression and corresponding clinical symptoms, not personalized. The complex pathophysiology assures that a single biomarker cannot identify, stratify, and describe patients affected by septic shock. Traditional biomarkers like CRP, PCT, and cytokines are not sensitive and specific enough to be used entirely for a patient's diagnosis and prognosis. Thus, the need of the hour is a sensitive and specific biomarker after comprehensive analysis that may facilitate an early diagnosis, prognosis, and drug development. Integration of clinical data with metabolomics would provide means to understand the patient's condition, stratify patients better, and predict the clinical outcome.

Plasma Metabolomics Reveals Distinct Biological and Diagnostic Signatures for Melioidosis

Rationale: The global burden of sepsis is greatest in low-resource settings. Melioidosis, infection with the gram-negative bacterium Burkholderia pseudomallei, is a frequent cause of fatal sepsis in endemic tropical regions such as Southeast Asia. Objectives: To investigate whether plasma metabolomics would identify biological pathways specific to melioidosis and yield clinically meaningful biomarkers. Methods: Using a comprehensive approach, differential enrichment of plasma metabolites and pathways was systematically evaluated in individuals selected from a prospective cohort of patients hospitalized in rural Thailand with infection. Statistical and bioinformatics methods were used to distinguish metabolomic features and processes specific to patients with melioidosis and between fatal and nonfatal cases. Measurements and Main Results: Metabolomic profiling and pathway enrichment analysis of plasma samples from patients with melioidosis (n = 175) and nonmelioidosis infections (n = 75) revealed a distinct immuno-metabolic state among patients with melioidosis, as suggested by excessive tryptophan catabolism in the kynurenine pathway and significantly increased levels of sphingomyelins and ceramide species. We derived a 12-metabolite classifier to distinguish melioidosis from other infections, yielding an area under the receiver operating characteristic curve of 0.87 in a second validation set of patients. Melioidosis nonsurvivors (n = 94) had a significantly disturbed metabolome compared with survivors (n = 81), with increased leucine, isoleucine, and valine metabolism, and elevated circulating free fatty acids and acylcarnitines. A limited eight-metabolite panel showed promise as an early prognosticator of mortality in melioidosis. Conclusions: Melioidosis induces a distinct metabolomic state that can be examined to distinguish underlying pathophysiological mechanisms associated with death. A 12-metabolite signature accurately differentiates melioidosis from other infections and may have diagnostic applications.

LASSO regression shows histidine and sphingosine 1 phosphate are linked to both sepsis mortality and endothelial damage

Sepsis is a major cause of death worldwide, with a mortality rate that has remained stubbornly high. The current gold standard of risk stratifying sepsis patients provides limited mechanistic insight for therapeutic targeting. An improved ability to predict sepsis mortality and to understand the risk factors would allow better treatment targeting. Sepsis causes metabolic dysregulation in patients; therefore, metabolomics offers a promising tool to study sepsis. It is also known that that in sepsis endothelial cells affecting their function regarding blood clotting and vascular permeability. We integrated metabolomics data from patients admitted to an intensive care unit for sepsis, with commonly collected clinical features of their cases and two measures of endothelial function relevant to blood vessel function, platelet endothelial cell adhesion molecule and soluble thrombomodulin concentrations in plasma. We used least absolute shrinkage and selection operator penalized regression, and pathway enrichment analysis to identify features most able to predict 30-day survival. The features important to sepsis survival include carnitines, and amino acids. Endothelial proteins in plasma also predict 30-day mortality and the levels of these proteins also correlate with a somewhat overlapping set of metabolites. Overall metabolic dysregulation, particularly in endothelial cells, may be a contributory factor to sepsis response. By exploring sepsis metabolomics data in conjunction with clinical features and endothelial proteins we have gained a better understanding of sepsis risk factors.

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.

Conceptual foundations of acetylcarnitine supplementation in neuropsychiatric long COVID syndrome: a narrative review

Post-acute sequelae of COVID-19 can present as multi-organ pathology, with neuropsychiatric symptoms being the most common symptom complex, characterizing long COVID as a syndrome with a significant disease burden for affected individuals. Several typical symptoms of long COVID, such as fatigue, depressive symptoms and cognitive impairment, are also key features of other psychiatric disorders such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and major depressive disorder (MDD). However, clinically successful treatment strategies are still lacking and are often inspired by treatment options for diseases with similar clinical presentations, such as ME/CFS. Acetylcarnitine, the shortest metabolite of a class of fatty acid metabolites called acylcarnitines and one of the most abundant blood metabolites in humans can be used as a dietary/nutritional supplement with proven clinical efficacy in the treatment of MDD, ME/CFS and other neuropsychiatric disorders. Basic research in recent decades has established acylcarnitines in general, and acetylcarnitine in particular, as important regulators and indicators of mitochondrial function and other physiological processes such as neuroinflammation and energy production pathways. In this review, we will compare the clinical basis of neuropsychiatric long COVID with other fatigue-associated diseases. We will also review common molecular disease mechanisms associated with altered acetylcarnitine metabolism and the potential of acetylcarnitine to interfere with these as a therapeutic agent. Finally, we will review the current evidence for acetylcarnitine as a supplement in the treatment of fatigue-associated diseases and propose future research strategies to investigate the potential of acetylcarnitine as a treatment option for long COVID.

A pilot study of alternative substrates in the critically Ill subject using a ketogenic feed

Bioenergetic failure caused by impaired utilisation of glucose and fatty acids contributes to organ dysfunction across multiple tissues in critical illness. Ketone bodies may form an alternative substrate source, but the feasibility and safety of inducing a ketogenic state in physiologically unstable patients is not known. Twenty-nine mechanically ventilated adults with multi-organ failure managed on intensive care units were randomised (Ketogenic n = 14, Control n = 15) into a two-centre pilot open-label trial of ketogenic versus standard enteral feeding. The primary endpoints were assessment of feasibility and safety, recruitment and retention rates and achievement of ketosis and glucose control. Ketogenic feeding was feasible, safe, well tolerated and resulted in ketosis in all patients in the intervention group, with a refusal rate of 4.1% and 82.8% retention. Patients who received ketogenic feeding had fewer hypoglycaemic events (0.0% vs. 1.6%), required less exogenous international units of insulin (0 (Interquartile range 0-16) vs.78 (Interquartile range 0-412) but had slightly more daily episodes of diarrhoea (53.5% vs. 42.9%) over the trial period. Ketogenic feeding was feasible and may be an intervention for addressing bioenergetic failure in critically ill patients. Clinical Trials.gov registration: NCT04101071.

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.

High-Resolution Plasma Metabolomics and Thiamine Status in Critically Ill Adult Patients

BACKGROUND AND AIM

Thiamine (Vitamin B1) is an essential micronutrient and a co-factor for metabolic functions related to energy metabolism. We determined the association between whole blood thiamine pyrophosphate (TPP) concentrations and plasma metabolites using high resolution metabolomics in critically ill patients. Methods Cross-sectional study performed in Erciyes University Hospital, Kayseri, Turkey and Emory University, Atlanta, GA, USA. Participants were ≥ 18 years of age, with an expected length of ICU stay longer than 48 hours, receiving furosemide therapy for at least 6 months before ICU admission. Results Blood for TPP and metabolomics was obtained on the day of ICU admission. Whole blood TPP concentrations were measured using high-performance liquid chromatography (HPLC). Liquid chromatography/mass spectrometry was used for plasma high-resolution metabolomics. Data was analyzed using regression analysis of TPP levels against all plasma metabolomic features in metabolome-wide association studies. We also compared metabolomic features from patients in the highest TPP concentration tertile to patients in the lowest TPP tertile as a secondary analysis. We enrolled 76 participants with a median age of 69 (range, 62.5-79.5) years. Specific metabolic pathways associated with whole blood TPP levels, using both regression and tertile analysis, included pentose phosphate, fructose and mannose, branched chain amino acid, arginine and proline, linoleate, and butanoate pathways. Conclusions Plasma high-resolution metabolomics analysis showed that whole blood TPP concentrations are significantly associated with metabolites and metabolic pathways linked to the metabolism of energy, amino acids, lipids, and the gut microbiome in adult critically ill patients.

Metabolomics Analysis of Mesenchymal Stem Cell (MSC) Therapy in a Phase I Clinical Trial of Septic Shock: An Exploratory Study

Sepsis is the result of an uncontrolled host inflammatory response to infection that may lead to septic shock with multiorgan failure and a high mortality rate. There is an urgent need to improve early diagnosis and to find markers identifying those who will develop septic shock and certainly a need to develop targeted treatments to prevent septic shock and its high mortality. Herein, we explore metabolic alterations due to mesenchymal stromal cell (MSC) treatment of septic shock. The clinical findings for this study were already reported; MSC therapy was well-tolerated and safe in patients in this phase I clinical trial. In this exploratory metabolomics study, 9 out of 30 patients received an escalating dose of MSC treatment, while 21 patients were without MSC treatment. Serum metabolomics profiling was performed to detect and characterize metabolite changes due to MSC treatment and to help determine the sample size needed for a phase II clinical trial and to define a metabolomic response to MSC treatment. Serum metabolites were measured using 1H-NMR and HILIC-MS at times 0, 24 and 72 h after MSC infusion. The results demonstrated the significant impact of MSC treatment on serum metabolic changes in a dose- and time-dependent manner compared to non-MSC-treated septic shock patients. This study suggests that plasma metabolomics can be used to assess the response to MSC therapy and that treatment-related metabolomics effects can be used to help determine the sample size needed in a phase II trial. As this study was not powered to detect outcome, how the treatment-induced metabolomic changes described in this study of MSC-treated septic shock patients are related to outcomes of septic shock in the short and long term will need to be explored in a larger adequately powered phase II clinical trial.

Plasma oxidative lipidomics reveals signatures for sepsis-associated acute kidney injury

BACKGROUND

Oxidized lipids are essential bioactive lipid mediators generated during infection that regulate oxidative stress and the inflammatory response, but their signatures in patients with sepsis-associated acute kidney injury (SA-AKI) are poorly understood. This study analyzed the oxidative lipidomics of plasma from patients with SA-AKI to reveal the underlying biomarkers and pathophysiological mechanisms involved in sepsis.

MATERIALS

A total of 67 patients with SA-AKI and 20 age- and sex-matched healthy controls (HCs) participated in this prospective cohort study. Among the patients with SA-AKI, 14 cases had stage I-II AKI and 53 cases had stage III AKI. Oxidative lipidomic analysis of plasma samples was conducted using ultra performance liquid chromatography coupled with tandem mass spectrometric (UPLC-MS /MS) detection.

RESULTS

Among 21 kinds of differentially oxidized lipids, 5(S),12(S)-DiHETE, 5-isoPGF2VI, 5,6-DiHETrE, 11,12-EET and 9,10-DiHOME showed the best performance. The prediction model incorporating them has shown highly sensitive and specific in distinguishing different stages of SA-AKI from HCs. The annotation of Kyoto Encyclopedia of Genes and Genomes illustrated that the overall downregulation of vascular smooth muscle contraction was closely related to the pathophysiological mechanism of SA-AKI.

CONCLUSION

This study revealed alterations in the characteristic oxidized lipids in the plasma of SA-AKI patients, and these lipids had high diagnostic efficiency and potential targeted intervention value for SA-AKI.

Prognostic biomarkers for sepsis mortality based on the literature and LC-MS-based metabolomics of sepsis patients

OBJECTIVES

The management of sepsis, a potentially lethal overreaction to infection, is limited by the lack of prognostic tools to guide its treatment. Our aim is to identify a novel metabolic biomarker panel for predicting sepsis mortality based on a literature review and liquid chromatography-mass spectrometry (LC-MS)-based metabolomics.

METHODS

In the literature, we found metabolomics biomarkers reported to predict sepsis mortality. We determined the classifications, reported frequency, and KEGG pathway enrichment of these markers. Using serum samples from 20 sepsis survivors and 20 non-survivors within 28 days after admission to the intensive care unit (ICU), we performed LC-MS-based metabolomics. Based on the literature review and metabolomics, a prognostic biomarker panel for sepsis was identified and its area under the curve (AUC) values was assessed.

RESULTS

Kynurenate, caffeine, and lysoPC 22:4 were selected as a prognostic biomarker panel for sepsis. The panel had an area under the curve (AUC) of 0.885 (95% CI, 0.694-1) evaluated by linear support vector machine (SVM) and 0.849 (0.699-1) by random forest (RF), which was higher than that of the Sequential Organ Failure Assessment (SOFA). A combination of kynurenate, caffeine, and lysoPC 22:4 and SOFA provided the best discriminating performance, with AUCs of 0.961 (0.878-1) for SVM and 0.916 (0.774-1) for RF.

CONCLUSIONS

The prognostic biomarker panel consisting of kynurenate, caffeine, and lysoPC 22:4 may aid in the identification of sepsis patients at a high risk of death, leading to personalized therapy in clinical practice that will improve sepsis survival.

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.

Parameters Predicting Microvascular Invasion and Poor Differentiation in Hepatocellular Carcinoma Patients with Normal Alpha-fetoprotein Level Before Liver Transplantation

BACKGROUND/AIMS

The aim of this study is to evaluate the parameters that might be associated with pathologically diagnosed microvascular invasion and poor differentiation, using complete blood count and routine clinical biochemistry test results, in hepatocellular carcinoma patients before liver transplantation.

MATERIALS AND METHODS

The data of patients who underwent liver transplantation for hepatocellular carcinoma at our institute, between March 2006 and November 2021, was researched retrospectively.

RESULTS

The incidence of microvascular invasion was 28.6%, poor differentiation rate was 9.3%, hepatocellular carcinoma recurrence rate after liver transplantation was 12.1%, and median time to recurrence was 13 months, in the patients with normal alpha-fetoprotein levels. After univariate and multivariate analysis, maximum tumor diameter >4.5 cm and the number of nodules (n > 5) were found to be independent risk factors for microvascular invasion, and number of nodules >4 and mean platelet volume ≤8.6 fL were found to be independent risk factors for poor differentiation. Serum alpha-fetoprotein levels were still within the normal range at the recurrence time, in 53% of the patients who had recurrence after liver transplantation, but surprisingly were elevated in 47% of the patients at time of hepatocellular carcinoma recurrence.

CONCLUSIONS

In hepatocellular carcinoma patients with normal alpha-fetoprotein levels before liver transplantation, independent risk factors of the presence of microvascular invasion were maximum tumor diameter and number of nodules, and independent risk factors of poor differentiation were mean platelet volume and number of nodules. Furthermore, serum alpha-fetoprotein levels were still normal at time of recurrence in 53% of hepatocellular carcinoma patients whose alpha-fetoprotein levels were normal before liver transplantation but were elevated in 47% of the patients at recurrence time, despite having normal levels before liver transplantation.

Predictive value of presepsin and acylcarnitines for severity and biliary drainage in acute cholangitis

BACKGROUND

Bacteremia, which is a major cause of mortality in patients with acute cholangitis, induces hyperactive immune response and mitochondrial dysfunction. Presepsin is responsible for pathogen recognition by innate immunity. Acylcarnitines are established mitochondrial biomarkers.

AIM

To clarify the early predictive value of presepsin and acylcarnitines as biomarkers of severity of acute cholangitis and the need for biliary drainage.

METHODS

Of 280 patients with acute cholangitis were included and the severity was stratified according to the Tokyo Guidelines 2018. Blood presepsin and plasma acylcarnitines were tested at enrollment by chemiluminescent enzyme immunoassay and ultra-high-performance liquid chromatography-mass spectrometry, respectively.

RESULTS

The concentrations of presepsin, procalcitonin, short- and medium-chain acylcarnitines increased, while long-chain acylcarnitines decreased with the severity of acute cholangitis. The areas under the receiver operating characteristic curves (AUC) of presepsin for diagnosing moderate/severe and severe cholangitis (0.823 and 0.801, respectively) were greater than those of conventional markers. The combination of presepsin, direct bilirubin, alanine aminotransferase, temperature, and butyryl-L-carnitine showed good predictive ability for biliary drainage (AUC: 0.723). Presepsin, procalcitonin, acetyl-L-carnitine, hydroxydodecenoyl-L-carnitine, and temperature were independent predictors of bloodstream infection. After adjusting for severity classification, acetyl-L-carnitine was the only acylcarnitine independently associated with 28-d mortality (hazard ratio 14.396; P < 0.001) (AUC: 0.880). Presepsin concentration showed positive correlation with direct bilirubin or acetyl-L-carnitine.

CONCLUSION

Presepsin could serve as a specific biomarker to predict the severity of acute cholangitis and need for biliary drainage. Acetyl-L-carnitine is a potential prognostic factor for patients with acute cholangitis. Innate immune response was associated with mitochondrial metabolic dysfunction in acute cholangitis.

Alterations in the gut microbiome and metabolome profiles of septic mice treated with Shen FuHuang formula

Sepsis has a high mortality rate, and treating sepsis remains a significant challenge worldwide. In former studies, our group found that traditional Chinese medicine, Shen FuHuang formula (SFH), is a promising medicine in treating coronavirus disease 2019 (COVID-19) patients with the septic syndrome. However, the underlying mechanisms remain elusive. In the present study, we first investigated the therapeutic effects of SFH on septic mice. To investigate the mechanisms of SFH-treated sepsis, we identified the gut microbiome profile and exploited untargeted metabolomics analyses. The results demonstrated that SFH significantly enhanced the mice’s 7-day survival rate and hindered the release of inflammatory mediators, i.e., TNF-α, IL-6, and IL-1β. 16S rDNA sequencing further deciphered that SFH decreased the proportion of Campylobacterota and Proteobacteria at the phylum level. LEfSe analysis revealed that the treatment of SFH enriched Blautia while decreased Escherichia_Shigella. Furthermore, serum untargeted metabolomics analysis indicated that SFH could regulate the glucagon signaling pathway, PPAR signaling pathway, galactose metabolism, and pyrimidine metabolism. Finally, we found the relative abundance of Bacteroides, Lachnospiraceae_NK4A136_group, Escherichia_Shigella, Blautia, Ruminococcus, and Prevotella were closely related to the enrichment of the metabolic signaling pathways, including L-tryptophan, uracil, glucuronic acid, protocatechuic acid, and gamma-Glutamylcysteine. In conclusion, our study demonstrated that SFH alleviated sepsis by suppressing the inflammatory response and hence reduced mortality. The mechanism of SFH for treating sepsis may be ascribed to the enrichment of beneficial gut flora and modulation in glucagon signaling pathway, PPAR signaling pathway, galactose metabolism, and pyrimidine metabolism. To sum up, these findings provide a new scientific perspective for the clinical application of SFH in treating sepsis.

A Nomogram for Early Diagnosis of Community-Acquired Pneumonia Based on Bronchoalveolar Lavage Fluid Metabolomics

Purpose

There is a high disease burden associated with community-acquired pneumonia (CAP) around the world. A timely and correct diagnosis of CAP can facilitate early treatment and prevent illness progression. The present study aimed to find some novel biomarkers of CAP by metabolic analysis and construct a nomogram model for precise diagnosis and individualized treatment of CAP patients.

Patients and Methods

42 CAP patients and 20 controls were enrolled in this study. The metabolic profiles of bronchoalveolar lavage fluid (BALF) samples were identified by untargeted LC-MS/MS analysis. With a VIP score ≥ 1 in OPLS-DA analysis and P < 0.05, the significantly dysregulated metabolites were estimated as potential biomarkers of CAP, which were further included in the construction of the diagnostic prediction model along with laboratory inflammatory indexes via stepwise backward regression analysis. Discrimination, calibration, and clinical applicability of the nomogram were evaluated by the C-index, the calibration curve, and the decision curve analysis (DCA) estimated by bootstrap resampling.

Results

The metabolic profiles differed obviously between CAP patients and healthy controls, as shown by PCA and OPLS-DA plots. Seven metabolites significantly dysregulated in CAP were established: dimethyl disulfide, oleic acid (d5), N-acetyl-a-neuraminic acid, pyrimidine, choline, LPC (12:0/0:0) and PA (20:4/2:0). Multivariate logistic regression revealed that the expression levels of PA (20:4/2:0), N-acetyl-a-neuraminic acid, and CRP were associated with CAP. After being validated by bootstrap resampling, this model showed satisfactory diagnostic performance.

Conclusion

A novel nomogram prediction model containing metabolic potential biomarkers in BALF that was developed for the early diagnosis of CAP offers insights into the pathogenesis and host response in CAP.

Skeletal Muscle Myokine Expression in Critical Illness, Association With Outcome and Impact of Therapeutic Interventions

Context

Muscle expresses and secretes several myokines that bring about benefits in distant organs.

Objective

We investigated the impact of critical illness on muscular expression of irisin, kynurenine aminotransferases, and amylase; association with clinical outcome; and impact of interventions that attenuate muscle wasting/weakness.

Methods

We studied critically ill patients who participated in 2 randomized controlled trials (EPaNIC/NESCI) and documented time profiles in critically ill mice. Included in the study were 174 intensive care unit (ICU) patients (day 8 ± 1) vs 19 matched controls, and 60 mice subjected to surgery/sepsis vs 60 pair-fed healthy mice. Interventions studied included 7-day neuromuscular electrical stimulation (NMES), and withholding parenteral nutrition (PN) in the first ICU week (late PN) vs early PN. The main outcome measures were FNDC5 (irisin- precursor), KYAT1, KYAT3, and amylase mRNA expression in skeletal muscle.

Results

Critically ill patients showed 34% to 80% lower mRNA expression of FNDC5, KYAT1, and amylases than controls (P < .0001). Critically ill mice showed time-dependent reductions in all mRNAs compared with healthy mice (P ≤ .04). The lower FNDC5 expression in patients was independently associated with a higher ICU mortality (P = .015) and ICU-acquired weakness (P = .012), whereas the lower amylase expression in ICU survivors was independently associated with a longer ICU stay (P = .0060). Lower amylase expression was independently associated with a lower risk of death (P = .048), and lower KYAT1 expression with a lower risk of weakness (P = .022). NMES increased FNDC5 expression compared with unstimulated muscle (P = .016), and late PN patients had a higher KYAT1 expression than early PN patients (P = .022).

Conclusion

Expression of the studied myokines was affected by critical illness and associated with clinical outcomes, with limited effects of interventions that attenuate muscle wasting or weakness.

EASY-FIA: A Readably Usable Standalone Tool for High-Resolution Mass Spectrometry Metabolomics Data Pre-Processing

Flow injection analysis coupled with high-resolution mass spectrometry (FIA-HRMS) is a fair trade-off between resolution and speed. However, free software available for data pre-processing is few, web-based, and often requires advanced user specialization. These tools rarely embedded blank and noise evaluation strategies, and direct feature annotation. We developed EASY-FIA, a free standalone application that can be employed for FIA-HRMS metabolomic data pre-processing by users with no bioinformatics/programming skills. We validated the tool's performance and applicability in two clinical metabolomics case studies. The main functions of our application are blank subtraction, alignment of the metabolites, and direct feature annotation by means of the Human Metabolome Database (HMDB) using a minimum number of mass spectrometry parameters. In a scenario where FIA-HRMS is increasingly recognized as a reliable strategy for fast metabolomics analysis, EASY-FIA could become a standardized and feasible tool easily usable by all scientists dealing with MS-based metabolomics. EASY-FIA was implemented in MATLAB with the App Designer tool and it is freely available for download.

Myristoyl lysophosphatidylcholine is a biomarker and potential therapeutic target for community-acquired pneumonia

There is no gold standard for evaluating the severity of community-acquired pneumonia (CAP), and it is still based on a score. This study aimed to use the metabolomics method to find promised biomarkers in assessing disease severity and potential therapeutic targets for CAP. The result found that the metabolites in the plasma samples of CAP patients had significantly different between the acute phase and the remission phase, especially lysophosphatidylcholine (LPCs) in glycerophospholipids, whose levels are negatively linked to the severity of the disease. Subsequently, the two key metabolites of myristoyl lysophosphatidylcholine (LPC 14:0) and LPC 16:1 were screened. We analyzed the predictive performance of the two metabolites using Spearman-related analysis and ROC curves, and LPC14:0 showed more satisfactory diagnostic performance than LPC16:1. Then we explored the protective role and mechanism of LPC 14:0 in animal and cell models. The results showed that LPC 14:0 could inhibit the LPS-induced secretion of IL-1β, IL-6, and TNF-α, lower the ROS and MDA levels, and decreased the depletion of SOD and GSH, thereby reducing lung tissue and cell damage, such as down-regulating the protein level in BALF, lung W/D ratio, MPO activity, and apoptosis. We found that LPC 14:0 inhibited LPS-induced inflammatory response and oxidative stress, and the above protection was achieved by inhibiting LPS-induced activation of the NLRP3 inflammasome. LPC 14:0 may serve as a novel biomarker for predicting the severity of CAP. In addition, our exploration of the role of LPC 14:0 in animal and cellular models has reinforced its promise as a therapeutic target to improve the clinical efficacy for CAP.

Using a multiomics approach to unravel a septic shock specific signature in skeletal muscle

Sepsis is defined as a dysregulated host response to infection leading to organs failure. Among them, sepsis induces skeletal muscle (SM) alterations that contribute to acquired-weakness in critically ill patients. Proteomics and metabolomics could unravel biological mechanisms in sepsis-related organ dysfunction. Our objective was to characterize a distinctive signature of septic shock in human SM by using an integrative multi-omics approach. Muscle biopsies were obtained as part of a multicenter non-interventional prospective study. Study population included patients in septic shock (S group, with intra-abdominal source of sepsis) and two critically ill control populations: cardiogenic shock (C group) and brain dead (BD group). The proteins and metabolites were extracted and analyzed by High-Performance Liquid Chromatography-coupled to tandem Mass Spectrometry, respectively. Fifty patients were included, 19 for the S group (53% male, 64 ± 17 years, SAPS II 45 ± 14), 12 for the C group (75% male, 63 ± 4 years, SAPS II 43 ± 15), 19 for the BD group (63% male, 58 ± 10 years, SAPS II 58 ± 9). Biopsies were performed in median 3 days [interquartile range 1-4]) after intensive care unit admission. Respectively 31 patients and 40 patients were included in the proteomics and metabolomics analyses of 2264 proteins and 259 annotated metabolites. Enrichment analysis revealed that mitochondrial pathways were significantly decreased in the S group at protein level: oxidative phosphorylation (adjusted p = 0.008); branched chained amino acids degradation (adjusted p = 0.005); citrate cycle (adjusted p = 0.005); ketone body metabolism (adjusted p = 0.003) or fatty acid degradation (adjusted p = 0.008). Metabolic reprogramming was also suggested (i) by the differential abundance of the peroxisome proliferator-activated receptors signaling pathway (adjusted p = 0.007), and (ii) by the accumulation of fatty acids like octanedioic acid dimethyl or hydroxydecanoic. Increased polyamines and depletion of mitochondrial thioredoxin or mitochondrial peroxiredoxin indicated a high level of oxidative stress in the S group. Coordinated alterations in the proteomic and metabolomic profiles reveal a septic shock signature in SM, highlighting a global impairment of mitochondria-related metabolic pathways, the depletion of antioxidant capacities, and a metabolic shift towards lipid accumulation.ClinicalTrial registration: NCT02789995. Date of first registration 03/06/2016.

Signatures of Mitochondrial Dysfunction and Impaired Fatty Acid Metabolism in Plasma of Patients with Post-Acute Sequelae of COVID-19 (PASC)

Exercise intolerance is a major manifestation of post-acute sequelae of severe acute respiratory syndrome coronavirus infection (PASC, or "long-COVID"). Exercise intolerance in PASC is associated with higher arterial blood lactate accumulation and lower fatty acid oxidation rates during graded exercise tests to volitional exertion, suggesting altered metabolism and mitochondrial dysfunction. It remains unclear whether the profound disturbances in metabolism that have been identified in plasma from patients suffering from acute coronavirus disease 2019 (COVID-19) are also present in PASC. To bridge this gap, individuals with a history of previous acute COVID-19 infection that did not require hospitalization were enrolled at National Jewish Health (Denver, CO, USA) and were grouped into those that developed PASC (n = 29) and those that fully recovered (n = 16). Plasma samples from the two groups were analyzed via mass spectrometry-based untargeted metabolomics and compared against plasma metabolic profiles of healthy control individuals (n = 30). Observational demographic and clinical data were retrospectively abstracted from the medical record. Compared to plasma of healthy controls or individuals who recovered from COVID-19, PASC plasma exhibited significantly higher free- and carnitine-conjugated mono-, poly-, and highly unsaturated fatty acids, accompanied by markedly lower levels of mono-, di- and tricarboxylates (pyruvate, lactate, citrate, succinate, and malate), polyamines (spermine) and taurine. Plasma from individuals who fully recovered from COVID-19 exhibited an intermediary metabolic phenotype, with milder disturbances in fatty acid metabolism and higher levels of spermine and taurine. Of note, depletion of tryptophan-a hallmark of disease severity in COVID-19-is not normalized in PASC patients, despite normalization of kynurenine levels-a tryptophan metabolite that predicts mortality in hospitalized COVID-19 patients. In conclusion, PASC plasma metabolites are indicative of altered fatty acid metabolism and dysfunctional mitochondria-dependent lipid catabolism. These metabolic profiles obtained at rest are consistent with previously reported mitochondrial dysfunction during exercise, and may pave the way for therapeutic intervention focused on restoring mitochondrial fat-burning capacity.

The role of proteomics and metabolomics in severe infections

PURPOSE OF REVIEW

Severe infections are a common cause of ICU admission, with a high morbidity and mortality. Omics, namely proteomics and metabolomics, aim to identify, characterize, and quantify biological molecules to achieve a systems-level understanding of disease. The aim of this review is to provide a clear overview of the current evidence of the role of proteomics and metabolomics in severe infections.

RECENT FINDINGS

Proteomics and metabolomics are technologies that are being used to explore new markers of diagnosis and prognosis, clarify mechanisms of disease, and consequently discover potential targets of therapy and finally of a better disease phenotyping. These technologies are starting to be used but not yet in clinical use.

SUMMARY

Our traditional way of approaching the disease as sepsis is believing that a process can be broken into its parts and that the whole can be explained by the sum of each part. This approach is highly reductionist and does not take the system complexity nor the nonlinear dynamics of the processes. Proteomics and metabolomics allow the analysis of several proteins and metabolites simultaneously, thereby generating diagnostic and prognostic signatures. An exciting future prospect for proteomics and metabolomics is their employment towards precision medicine.

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.

Dichloroacetate improves systemic energy balance and feeding behavior during sepsis

Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to an infection. The metabolic aberrations associated with sepsis underly an acute and organism-wide hyperinflammatory response and multiple organ dysfunction; however, crosstalk between systemic metabolomic alterations and metabolic reprogramming at organ levels remains unknown. We analyzed substrate utilization by the respiratory exchange ratio, energy expenditure, metabolomic screening, and transcriptional profiling in a cecal ligation and puncture model to show that sepsis increases circulating free fatty acids and acylcarnitines but decreases levels of amino acids and carbohydrates, leading to a drastic shift in systemic fuel preference. Comparative analysis of previously published metabolomics from septic liver indicated a positive correlation with hepatic and plasma metabolites during sepsis. In particular, glycine deficiency was a common abnormality of the plasma and liver during sepsis. Interrogation of the hepatic transcriptome in septic mice suggested that the septic liver may contribute to systemic glycine deficiency by downregulating genes involved in glycine synthesis. Interestingly, intraperitoneal injection of the pyruvate dehydrogenase kinase (PDK) inhibitor dichloroacetate reversed sepsis-induced anorexia, energy imbalance, inflammation, dyslipidemia, hypoglycemia, and glycine deficiency. Collectively, our data indicated that PDK inhibition rescued systemic energy imbalance and metabolic dysfunction in sepsis partly through restoration of hepatic fuel metabolism.

A global lipid map reveals host dependency factors conserved across SARS-CoV-2 variants

A comprehensive understanding of host dependency factors for SARS-CoV-2 remains elusive. Here, we map alterations in host lipids following SARS-CoV-2 infection using nontargeted lipidomics. We find that SARS-CoV-2 rewires host lipid metabolism, significantly altering hundreds of lipid species to effectively establish infection. We correlate these changes with viral protein activity by transfecting human cells with each viral protein and performing lipidomics. We find that lipid droplet plasticity is a key feature of infection and that viral propagation can be blocked by small-molecule glycerolipid biosynthesis inhibitors. We find that this inhibition was effective against the main variants of concern (alpha, beta, gamma, and delta), indicating that glycerolipid biosynthesis is a conserved host dependency factor that supports this evolving virus.

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.

Managing sepsis in the era of precision medicine: challenges and opportunities

INTRODUCTION

Precision medicine is a medical model in which decisions, practices, interventions and therapies are tailored to the individual patient based on their predicted response or risk of disease. Sepsis is a life-threatening condition characterized by immune system dysregulation whose pathophysiology remains incompletely understood. There is much hope that precision medicine can lead to better outcomes in patients with sepsis.

AREAS COVERED

In this review from a comprehensive literature search in PubMed for English-language studies conducted in adults, we highlight recent advances in the diagnosis and treatment of sepsis of bacterial origin in adults using precision medicine approaches including rapid diagnostic tests, predictive biomarkers, genomic methods, rapid antimicrobial susceptibility testing, and monitoring cell mediated immunity. Challenges and directions for future research are also discussed.

EXPERT OPINION

Current diagnostic testing in sepsis relies primarily on conventional cultures (e.g. blood cultures), which are time-consuming and may delay critical therapeutic decisions. Nonculture-based techniques including nucleic acid amplification technologies (NAAT), other molecular methods (biomarkers), and genomic sequencing offer promise to overcome some of the inherent limitations seen with culture-based techniques.

Serum Levels of Acylcarnitines and Amino Acids Are Associated with Liberation from Organ Support in Patients with Septic Shock

Sepsis-induced metabolic dysfunction is associated with mortality, but the signatures that differentiate variable clinical outcomes among survivors are unknown. Our aim was to determine the relationship between host metabolism and chronic critical illness (CCI) in patients with septic shock. We analyzed metabolomics data from mechanically ventilated patients with vasopressor-dependent septic shock from the placebo arm of a recently completed clinical trial. Baseline serum metabolites were measured by liquid chromatography-mass spectrometry and ¹H-nuclear magnetic resonance. We conducted a time-to-event analysis censored at 28 days. Specifically, we determined the relationship between metabolites and time to extubation and freedom from vasopressors using a competing risk survival model, with death as a competing risk. We also compared metabolite concentrations between CCI patients, defined as intensive care unit level of care ≥ 14 days, and those with rapid recovery. Elevations in two acylcarnitines and four amino acids were related to the freedom from organ support (subdistributional hazard ratio < 1 and false discovery rate < 0.05). Proline, glycine, glutamine, and methionine were also elevated in patients who developed CCI. Our work highlights the need for further testing of metabolomics to identify patients at risk of CCI and to elucidate potential mechanisms that contribute to its etiology.

Precision medicine in sepsis and septic shock: From omics to clinical tools

Sepsis is a heterogeneous disease with variable clinical course and several clinical phenotypes. As it is associated with an increased risk of death, patients with this condition are candidates for receipt of a very well-structured and protocolized treatment. All patients should receive the fundamental pillars of sepsis management, which are infection control, initial resuscitation, and multiorgan support. However, specific subgroups of patients may benefit from a personalized approach with interventions targeted towards specific pathophysiological mechanisms. Herein, we will review the framework for identifying subpopulations of patients with sepsis, septic shock, and multiorgan dysfunction who may benefit from specific therapies. Some of these approaches are still in the early stages of research, while others are already in routine use in clinical practice, but together will help in the effective generation and safe implementation of precision medicine in sepsis.

Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity

The implication of lipid dysregulation in diseases, toxic exposure outcomes, and inflammation has brought great interest to lipidomic studies. However, lipids have proven to be analytically challenging due to their highly isomeric nature and vast concentration ranges in biological matrices. Therefore, multidimensional techniques such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (LC-IMS-CID-MS) have been implemented to separate lipid isomers as well as provide structural information and increased identification confidence. These data sets are however extremely large and complex, resulting in challenges for data processing and annotation. Here, we have overcome these challenges by developing sample-specific multidimensional lipid libraries using the freely available software Skyline. Specifically, the human plasma library developed for this work contains over 500 unique lipids and is combined with adapted Skyline functions such as indexed retention time (iRT) for retention time prediction and IMS drift time filtering for enhanced selectivity. For comparison with other studies, this database was used to annotate LC-IMS-CID-MS data from a NIST SRM 1950 extract. The same workflow was then utilized to assess plasma and bronchoalveolar lavage fluid (BALF) samples from patients with varying degrees of smoke inhalation injury to identify lipid-based patient prognostic and diagnostic markers.

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.

Brain Kynurenine Pathway and Functional Outcome of Rats Resuscitated From Cardiac Arrest

Background Brain injury and neurological deficit are consequences of cardiac arrest (CA), leading to high morbidity and mortality. Peripheral activation of the kynurenine pathway (KP), the main catabolic route of tryptophan metabolized at first into kynurenine, predicts poor neurological outcome in patients resuscitated after out-of-hospital CA. Here, we investigated KP activation in hippocampus and plasma of rats resuscitated from CA, evaluating the effect of KP modulation in preventing CA-induced neurological deficit. Methods and Results Early KP activation was first demonstrated in 28 rats subjected to electrically induced CA followed by cardiopulmonary resuscitation. Hippocampal levels of the neuroactive metabolites kynurenine, 3-hydroxy-anthranilic acid, and kynurenic acid were higher 2 hours after CA, as in plasma. Further, 36 rats were randomized to receive the inhibitor of the first step of KP, 1-methyl-DL-tryptophan, or vehicle, before CA. No differences were observed in hemodynamics and myocardial function. The CA-induced KP activation, sustained up to 96 hours in hippocampus (and plasma) of vehicle-treated rats, was counteracted by the inhibitor as indicated by lower hippocampal (and plasmatic) kynurenine/tryptophan ratio and kynurenine levels. 1-Methyl-DL-tryptophan reduced the CA-induced neurological deficits, with a significant correlation between the neurological score and the individual kynurenine levels, as well as the kynurenine/tryptophan ratio, in plasma and hippocampus. Conclusions These data demonstrate the CA-induced lasting activation of the first step of the KP in hippocampus, showing that this activation was involved in the evolving neurological deficit. The degree of peripheral activation of KP may predict neurological function after CA.

A Metabolomics approach for the diagnosis Of SecondAry InfeCtions in COVID-19 (MOSAIC): a study protocol

Background

Critically ill patients with COVID-19 are at an increased risk of developing secondary bacterial infections. These are both difficult to diagnose and are associated with an increased mortality. Metabolomics may aid clinicians in diagnosing secondary bacterial infections in COVID-19 through identification and quantification of disease specific biomarkers, with the aim of identifying underlying causative microorganisms and directing antimicrobial therapy.

Methods

This is a multi-centre prospective diagnostic observational study. Patients with COVID-19 will be recruited from critical care units in three Scottish hospitals. Three serial blood samples will be taken from patients, and an additional sample taken if a patient shows clinical or microbiological evidence of secondary infection. Samples will be analysed using LC–MS and subjected to bioinformatic processing and statistical analysis to explore the metabolite changes associated with bacterial infections in COVID-19 patients. Comparisons of the data sets will be made with standard microbiological and biochemical methods of diagnosing infection.

Discussion

Metabolomics analyses may provide additional strategies for identifying secondary infections, which might permit faster initiation of specific tailored antimicrobial therapy to critically ill patients with COVID-19.

Survival Outcome of Sepsis in Recipients of Solid Organ Transplant

Sepsis is a complex disease stemming from a dysregulated immune response toward an infectious agent. In transplantation, sepsis remains one of the leading causes of morbidity and mortality. Solid organ transplant recipients have impaired adaptive immunity due to immunosuppression required to prevent rejection. Immunosuppression has unintended consequences, such as increasing the risk of infections and sepsis. Due to its high morbidity and mortality, early detection of sepsis is paramount to start aggressive treatment. Several biomarkers or combination of biomarkers of sepsis have emerged in the last decade, but they are not dependable for early diagnosis or for outcome prognosis.

Persistent hyperammonia and altered concentrations of urea cycle metabolites in a 5-day swine experiment of sepsis

We measured plasma and cerebrospinal fluid (CSF) metabolite concentrations in a 5-day porcine sepsis model of fecal peritonitis. The objectives were: (i) to verify whether the expected pathways that had emerged in previous studies pertain only to the early inflammatory response or persist for the subsequent days; (ii) to identify metabolic derangements that arise later; (iii) to verify whether CSF metabolite concentrations were altered and if these alterations were similar to those in the blood or delayed. We observed an early response to inflammation and cytokine storms with alterations in lipid and glucose metabolism. The arginine/asymmetric dimethylarginine (ADMA) and phenylalanine/tyrosine balances changed 24 h after resuscitation in plasma, and later in CSF. There was a rise in ammonia concentration, with altered concentrations of metabolites in the urea cycle. Whether persistent derangement of these pathways have a role not only on short-term outcomes but also on longer-term comorbidities, such as septic encephalopathy, should be addressed in further studies.

Phospholipases A2 as biomarkers in ARDS

Acute respiratory distress syndrome (ARDS) is a multifactorial life-threatening lung injury, characterized by diffuse lung inflammation and increased alveolocapillary barrier permeability. The different stages of ARDS have distinctive biochemical and clinical profiles. Despite the progress of our understanding on ARDS pathobiology, the mechanisms underlying its pathogenesis are still obscure. Herein, we review the existing literature about the implications of phospholipases 2 (PLA2s), a large family of enzymes that catalyze the hydrolysis of fatty acids at the sn-2 position of glycerophospholipids, in ARDS-related pathology. We emphasize on the versatile way of participation of different PLA2s isoforms in the distinct ARDS subgroup phenotypes by either potentiating lung inflammation and damage or by preserving the normal lung. Current research supports that PLA2s are associated with the progression and the outcome of ARDS. We herein discuss the transcellular communication of PLA2s through secreted extracellular vesicles and suggest it as a new mechanism of PLA2s involvement in ARDS. Thus, the elucidation of the spatiotemporal features of PLA2s expression may give new insights and provide valuable information about the risk of an individual to develop ARDS or advance to more severe stages, and potentially identify PLA2 isoforms as biomarkers and target for pharmacological intervention.

The lipid biology of sepsis

Sepsis, defined as the dysregulated immune response to an infection leading to organ dysfunction, is one of the leading causes of mortality around the globe. Despite the significant progress in delineating the underlying mechanisms of sepsis pathogenesis, there are currently no effective treatments or specific diagnostic biomarkers in the clinical setting. The perturbation of cell signaling mechanisms, inadequate inflammation resolution, and energy imbalance, all of which are altered during sepsis, are also known to lead to defective lipid metabolism. The use of lipids as biomarkers with high specificity and sensitivity may aid in early diagnosis and guide clinical decision making. In addition, identifying the link between specific lipid signatures and their role in sepsis pathology may lead to novel therapeutics. In this review, we discuss the recent evidence on dysregulated lipid metabolism both in experimental and human sepsis focused on bioactive lipids, fatty acids, and cholesterol as well as the enzymes regulating their levels during sepsis. We highlight not only their potential roles in sepsis pathogenesis but also the possibility of using these respective lipid compounds as diagnostic and prognostic biomarkers of sepsis.

Development and validation of a novel sepsis biomarker based on amino acid profiling

BACKGROUND & AIMS

Sepsis is a potentially fatal condition influenced by pathogens and host factors. Current sepsis biomarkers such as white blood cell count and C-reactive protein and procalcitonin levels show unsatisfactory performance in terms of diagnostic sensitivity and specificity in clinical practice. Thus, we developed and validated a new sepsis biomarker based on amino acid profiling.

METHODS

We used two independent groups. The training and validation groups included 161 and 22 healthy controls, 123 and 50 patients with systemic inflammatory response syndrome, and 115 and 45 patients with sepsis, respectively. Using mass spectrometry, we measured and analyzed serum amino acid levels to select candidate amino acids that could differentiate sepsis from other conditions. Then, several possible multivariate indexes were developed by generating formulae with different combinations of candidate amino acids. The formula showing the best performance was selected and validated further.

RESULTS

Kynurenine, tryptophan, phenylalanine, arginine, aspartic acid, glutamic acid, and glutamine were selected as candidate amino acids. Ten possible formulae were generated, and the formula with the highest diagnostic performance, which included kynurenine, tryptophan, phenylalanine, and arginine, was selected. In the validation group, the area under the receiving operating characteristic curve of the selected multivariate index (0.931) was similar to that of procalcitonin (0.945). Moreover, the generated multivariate index showed potential as a prognostic marker.

CONCLUSIONS

Serum amino acid composition in patients with sepsis differs significantly from that in healthy individuals and patients with inflammation only. The newly developed multivariate index is expected to be implementable as a sepsis biomarker in clinical practice in the near future.

A metabolomic endotype of bioenergetic dysfunction predicts mortality in critically ill patients with acute respiratory failure

Acute respiratory failure (ARF) requiring mechanical ventilation, a complicating factor in sepsis and other disorders, is associated with high morbidity and mortality. Despite its severity and prevalence, treatment options are limited. In light of accumulating evidence that mitochondrial abnormalities are common in ARF, here we applied broad spectrum quantitative and semiquantitative metabolomic analyses of serum from ARF patients to detect bioenergetic dysfunction and determine its association with survival. Plasma samples from surviving and non-surviving patients (N = 15/group) were taken at day 1 and day 3 after admission to the medical intensive care unit and, in survivors, at hospital discharge. Significant differences between survivors and non-survivors (ANOVA, 5% FDR) include bioenergetically relevant intermediates of redox cofactors nicotinamide adenine dinucleotide (NAD) and NAD phosphate (NADP), increased acyl-carnitines, bile acids, and decreased acyl-glycerophosphocholines. Many metabolites associated with poor outcomes are substrates of NAD(P)-dependent enzymatic processes, while alterations in NAD cofactors rely on bioavailability of dietary B-vitamins thiamine, riboflavin and pyridoxine. Changes in the efficiency of the nicotinamide-derived cofactors' biosynthetic pathways also associate with alterations in glutathione-dependent drug metabolism characterized by substantial differences observed in the acetaminophen metabolome. Based on these findings, a four-feature model developed with semi-quantitative and quantitative metabolomic results predicted patient outcomes with high accuracy (AUROC = 0.91). Collectively, this metabolomic endotype points to a close association between mitochondrial and bioenergetic dysfunction and mortality in human ARF, thus pointing to new pharmacologic targets to reduce mortality in this condition.

Effect of an intensified individual nutrition therapy on serum metabolites in critically ill patients - A targeted metabolomics analysis of the ONCA study

PURPOSE

The effect of medical nutrition on serum metabolomics has been poorly explored. The aim of the study was to investigate the relation between energy supply and metabolic profiles in critically ill patients.

MATERIALS AND METHODS

Twenty mechanically ventilated patients on enteral nutrition (EN) or enteral/parenteral nutrition (EN/PN) were randomized into two groups. One group received an individual energy supply based on indirect calorimetry (IC group, n = 9), the other group received a standard energy supply based on a formula, the standard care group (SC group, n = 11). Targeted metabolomics was performed in early-, late- and post-acute metabolic phase.

RESULTS

Individual versus standard care energy supply resulted in a metabolite class separation between the IC and the SC group (P < 0.001). In the SC group concentrations of four glucogenic amino acids and three biogenic amines increased between the early- and late-acute metabolic phase (P < 0.05). The metabolomics pattern differed between the routes of nutrition administration (P < 0.01).

CONCLUSIONS

The amount of energy supply by EN or PN, besides other factors, seems to modulate serum metabolites. Nutrition therapy based on individualized energy supply is associated with a reduction of metabolites reflecting catabolism. Therefore, metabolomics could be a new tool to determine metabolic phases in critically ill patients.