A patient-centric modeling framework captures recovery from SARS-CoV-2 infection.

The biology driving individual patient responses to severe acute respiratory syndrome coronavirus 2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year after disease onset, from 215 infected individuals with differing disease severities. Our analyses revealed distinct 'systemic recovery' profiles, with specific progression and resolution of the inflammatory, immune cell, metabolic and clinical responses. In particular, we found a strong inter-patient and intra-patient temporal covariation of innate immune cell numbers, kynurenine metabolites and lipid metabolites, which highlighted candidate immunologic and metabolic pathways influencing the restoration of homeostasis, the risk of death and that of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-19-systemic-recovery-prediction-app , designed to test our findings prospectively.

Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer's disease.

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer's disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10-5 to 1.3 × 10-44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049-1.4 × 10-5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD.

Stratification of Sepsis Patients on Admission into the Intensive Care Unit According to Differential Plasma Metabolic Phenotypes.

Delayed diagnosis of patients with sepsis or septic shock is associated with increased mortality and morbidity. UPLC-MS and NMR spectroscopy were used to measure panels of lipoproteins, lipids, biogenic amines, amino acids, and tryptophan pathway metabolites in blood plasma samples collected from 152 patients within 48 h of admission into the Intensive Care Unit (ICU) where 62 patients had no sepsis, 71 patients had sepsis, and 19 patients had septic shock. Patients with sepsis or septic shock had higher concentrations of neopterin and lower levels of HDL cholesterol and phospholipid particles in comparison to nonsepsis patients. Septic shock could be differentiated from sepsis patients based on different concentrations of 10 lipids, including significantly lower concentrations of five phosphatidylcholine species, three cholesterol esters, one dihydroceramide, and one phosphatidylethanolamine. The Supramolecular Phospholipid Composite (SPC) was reduced in all ICU patients, while the composite markers of acute phase glycoproteins were increased in the sepsis and septic shock patients within 48 h admission into ICU. We show that the plasma metabolic phenotype obtained within 48 h of ICU admission is diagnostic for the presence of sepsis and that septic shock can be differentiated from sepsis based on the lipid profile.

Cross-Validation of Metabolic Phenotypes in SARS-CoV-2 Infected Subpopulations Using Targeted Liquid Chromatography-Mass Spectrometry (LC-MS).

To ensure biological validity in metabolic phenotyping, findings must be replicated in independent sample sets. Targeted workflows have long been heralded as ideal platforms for such validation due to their robust quantitative capability. We evaluated the capability of liquid chromatography-mass spectrometry (LC-MS) assays targeting organic acids and bile acids to validate metabolic phenotypes of SARS-CoV-2 infection. Two independent sample sets were collected: (1) Australia: plasma, SARS-CoV-2 positive (n = 20), noninfected healthy controls (n = 22) and COVID-19 disease-like symptoms but negative for SARS-CoV-2 infection (n = 22). (2) Spain: serum, SARS-CoV-2 positive (n = 33) and noninfected healthy controls (n = 39). Multivariate modeling using orthogonal projections to latent structures discriminant analyses (OPLS-DA) classified healthy controls from SARS-CoV-2 positive (Australia; R2 = 0.17, ROC-AUC = 1; Spain R2 = 0.20, ROC-AUC = 1). Univariate analyses revealed 23 significantly different (p < 0.05) metabolites between healthy controls and SARS-CoV-2 positive individuals across both cohorts. Significant metabolites revealed consistent perturbations in cellular energy metabolism (pyruvic acid, and 2-oxoglutaric acid), oxidative stress (lactic acid, 2-hydroxybutyric acid), hypoxia (2-hydroxyglutaric acid, 5-aminolevulinic acid), liver activity (primary bile acids), and host-gut microbial cometabolism (hippuric acid, phenylpropionic acid, indole-3-propionic acid). These data support targeted LC-MS metabolic phenotyping workflows for biological validation in independent sample sets.

Exploring the Interactions between Obesity and Diabetes: Implications for Understanding Metabolic Dysregulation in a Saudi Arabian Adult Population.

The rising prevalence of obesity in Saudi Arabia is a major contributor to the nation's high levels of cardiometabolic diseases such as type 2 diabetes. To assess the impact of obesity on the diabetic metabolic phenotype presented in young Saudi Arabian adults, participants (n = 289, aged 18-40 years) were recruited and stratified into four groups: healthy weight (BMI 18.5-24.99 kg/m2) with (n = 57) and without diabetes (n = 58) or overweight/obese (BMI > 24.99 kg/m2) with (n = 102) and without diabetes (n = 72). Distinct plasma metabolic phenotypes associated with high BMI and diabetes were identified using nuclear magnetic resonance spectroscopy and ultraperformance liquid chromatography mass spectrometry. Increased plasma glucose and dysregulated lipoproteins were characteristics of obesity in individuals with and without diabetes, but the obesity-associated lipoprotein phenotype was partially masked in individuals with diabetes. Although there was little difference between diabetics and nondiabetics in the global plasma LDL cholesterol and phospholipid concentration, the distribution of lipoprotein particles was altered in diabetics with a shift toward denser and more atherogenic LDL5 and LDL6 particles, which was amplified in the presence of obesity. Further investigation is warranted in larger Middle Eastern populations to explore the dysregulation of metabolism driven by interactions between obesity and diabetes in young adults.

Integrative Molecular Structure Elucidation and Construction of an Extended Metabolic Pathway Associated with an Ancient Innate Immune Response in COVID-19 Patients.

We present compelling evidence for the existence of an extended innate viperin-dependent pathway, which provides crucial evidence for an adaptive response to viral agents, such as SARS-CoV-2. We show the in vivo biosynthesis of a family of novel endogenous cytosine metabolites with potential antiviral activities. Two-dimensional nuclear magnetic resonance (NMR) spectroscopy revealed a characteristic spin-system motif, indicating the presence of an extended panel of urinary metabolites during the acute viral replication phase. Mass spectrometry additionally enabled the characterization and quantification of the most abundant serum metabolites, showing the potential diagnostic value of the compounds for viral infections. In total, we unveiled ten nucleoside (cytosine- and uracil-based) analogue structures, eight of which were previously unknown in humans allowing us to propose a new extended viperin pathway for the innate production of antiviral compounds. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-α2, IFN-γ, and IL-10, suggest an association with the viperin enzyme contributing to an ancient endogenous innate immune defense mechanism against viral infection.

Rapid and Self-Administrable Capillary Blood Microsampling Demonstrates Statistical Equivalence with Standard Venous Collections in NMR-Based Lipoprotein Analysis.

We investigated plasma and serum blood derivatives from capillary blood microsamples (500 µL, MiniCollect tubes) and corresponding venous blood (10 mL vacutainers). Samples from 20 healthy participants were analyzed by 1H NMR, and 112 lipoprotein subfraction parameters; 3 supramolecular phospholipid composite (SPC) parameters from SPC1, SPC2, and SPC3 subfractions; 2 N-acetyl signals from α-1-acid glycoprotein (Glyc), GlycA, and GlycB; and 3 calculated parameters, SPC (total), SPC3/SPC2, and Glyc (total) were assessed. Using linear regression between capillary and venous collection sites, we explained that agreement (Adj. R2 ≥ 0.8, p < 0.001) was witnessed for 86% of plasma parameters (103/120) and 88% of serum parameters (106/120), indicating that capillary lipoprotein, SPC, and Glyc concentrations follow changes in venous concentrations. These results indicate that capillary blood microsamples are suitable for sampling in remote areas and for high-frequency longitudinal sampling of the majority of lipoproteins, SPCs, and Glycs.

Anti-Cholestatic Therapy with Obeticholic Acid Improves Short-Term Memory in Bile Duct-Ligated Mice.

Patients with cholestatic liver disease, including those with primary biliary cholangitis, can experience symptoms of impaired cognition or brain fog. This phenomenon remains unexplained and is currently untreatable. Bile duct ligation (BDL) is an established rodent model of cholestasis. In addition to liver changes, BDL animals develop cognitive symptoms early in the disease process (before development of cirrhosis and/or liver failure). The cellular mechanisms underpinning these cognitive symptoms are poorly understood. Herein, the study explored the neurocognitive symptom manifestations, and tested potential therapies, in BDL mice, and used human neuronal cell cultures to explore translatability to humans. BDL animals exhibited short-term memory loss and showed reduced astrocyte coverage of the blood-brain barrier, destabilized hippocampal network activity, and neuronal senescence. Ursodeoxycholic acid (first-line therapy for most human cholestatic diseases) did not reverse symptomatic or mechanistic aspects. In contrast, obeticholic acid (OCA), a farnesoid X receptor agonist and second-line anti-cholestatic agent, normalized memory function, suppressed blood-brain barrier changes, prevented hippocampal network deficits, and reversed neuronal senescence. Co-culture of human neuronal cells with either BDL or human cholestatic patient serum induced cellular senescence and increased mitochondrial respiration, changes that were limited again by OCA. These findings provide new insights into the mechanism of cognitive symptoms in BDL animals, suggesting that OCA therapy or farnesoid X receptor agonism could be used to limit cholestasis-induced neuronal senescence.

Implementation of pure shift 1 H NMR in metabolic phenotyping for structural information recovery of biofluid metabolites with complex spin systems.

NMR spectroscopy is a mainstay of metabolic profiling approaches to investigation of physiological and pathological processes. The one-dimensional proton pulse sequences typically used in phenotyping large numbers of samples generate spectra that are rich in information but where metabolite identification is often compromised by peak overlap. Recently developed pure shift (PS) NMR spectroscopy, where all J-coupling multiplicities are removed from the spectra, has the potential to simplify the complex proton NMR spectra that arise from biosamples and hence to aid metabolite identification. Here we have evaluated two complementary approaches to spectral simplification: the HOBS (band-selective with real-time acquisition) and the PSYCHE (broadband with pseudo-2D interferogram acquisition) pulse sequences. We compare their relative sensitivities and robustness for deconvolving both urine and serum matrices. Both methods improve resolution of resonances ranging from doublets, triplets and quartets to more complex signals such as doublets of doublets and multiplets in highly overcrowded spectral regions. HOBS is the more sensitive method and takes less time to acquire in comparison with PSYCHE, but can introduce unavoidable artefacts from metabolites with strong couplings, whereas PSYCHE is more adaptable to these types of spin system, although at the expense of sensitivity. Both methods are robust and easy to implement. We also demonstrate that strong coupling artefacts contain latent connectivity information that can be used to enhance metabolite identification. Metabolite identification is a bottleneck in metabolic profiling studies. In the case of NMR, PS experiments can be included in metabolite identification workflows, providing additional capability for biomarker discovery.

Maternal oxidative stress during pregnancy associated with emotional and behavioural problems in early childhood: implications for foetal programming.

Childhood mental disorders, including emotional and behavioural problems (EBP) are increasingly prevalent. Higher maternal oxidative stress (OS) during pregnancy (matOSpreg) is linked to offspring mental disorders. Environmental factors contribute to matOSpreg. However, the role of matOSpreg in childhood EBP is unclear. We investigated the associations between (i) matOSpreg and offspring EBP; (ii) social and prenatal environmental factors and matOSpreg; and (iii) social and prenatal factors and childhood EBP and evaluated whether matOSpreg mediated these associations. Maternal urinary OS biomarkers, 8-hydroxyguanosine (8-OHGua; an oxidative RNA damage marker) and 8-hydroxy-2'-deoxyguanosine (8-OHdG; an oxidative DNA damage marker), at 36 weeks of pregnancy were quantified by liquid chromatography-mass spectrometry in a population-derived birth cohort, Barwon Infant Study (n = 1074 mother-infant pairs). Social and prenatal environmental factors were collected by mother-reported questionnaires. Offspring total EBP was measured by Child Behavior Checklist Total Problems T-scores at age two (n = 675) and Strengths and Difficulties Questionnaire Total Difficulties score at age four (n = 791). Prospective associations were examined by multivariable regression analyses adjusted for covariates. Mediation effects were evaluated using counterfactual-based mediation analysis. Higher maternal urinary 8-OHGua at 36 weeks (mat8-OHGua36w) was associated with greater offspring total EBP at age four (ß = 0.38, 95% CI (0.07, 0.69), P = 0.02) and age two (ß = 0.62, 95% CI (-0.06, 1.30), P = 0.07). Weaker evidence of association was detected for 8-OHdG. Five early-life factors were associated with both mat8-OHGua36w and childhood EBP (P-range < 0.001-0.05), including lower maternal education, socioeconomic disadvantage and prenatal tobacco smoking. These risk factor-childhood EBP associations were partly mediated by higher mat8-OHGua36w (P-range = 0.01-0.05). Higher matOSpreg, particularly oxidant RNA damage, is associated with later offspring EBP. Effects of some social and prenatal lifestyle factors on childhood EBP were partly mediated by matOSpreg. Future studies are warranted to further elucidate the role of early-life oxidant damage in childhood EBP.

Meta-analysis of the Microbial Diversity Cultured in Bioreactors Simulating the Gut Microbiome.

Understanding the intricate ecological interactions within the gut microbiome and unravelling its impact on human health is a challenging task. Bioreactors are valuable tools that have contributed to our understanding of gut microbial ecology. However, there is a lack of studies describing and comparing the microbial diversity cultivated in these models. This knowledge is crucial for refining current models to reflect the gastrointestinal microbiome accurately. In this study, we analysed the microbial diversity of 1512 samples from 18 studies available in public repositories that employed cultures performed in batches and various bioreactor models to cultivate faecal microbiota. Community structure comparison between samples using t-distributed stochastic neighbour embedding and the Hellinger distance revealed a high variation between projects. The main driver of these differences was the inter-individual variation between the donor faecal inocula. Moreover, there was no overlap in the structure of the microbial communities between studies using the same bioreactor platform. In addition, α-diversity analysis using Hill numbers showed that highly complex bioreactors did not exhibit higher diversities than simpler designs. However, analyses of five projects in which the samples from the faecal inoculum were also provided revealed an amplicon sequence variants enrichment in bioreactors compared to the inoculum. Finally, a comparative analysis of the taxonomy of the families detected in the projects and the GMRepo database revealed bacterial families exclusively found in the bioreactor models. These findings highlight the potential of bioreactors to enrich low-abundance microorganisms from faecal samples, contributing to uncovering the gut microbial "dark matter".

Tryptophan-metabolizing gut microbes regulate adult neurogenesis via the aryl hydrocarbon receptor.

While modulatory effects of gut microbes on neurological phenotypes have been reported, the mechanisms remain largely unknown. Here, we demonstrate that indole, a tryptophan metabolite produced by tryptophanase-expressing gut microbes, elicits neurogenic effects in the adult mouse hippocampus. Neurogenesis is reduced in germ-free (GF) mice and in GF mice monocolonized with a single-gene tnaA knockout (KO) mutant Escherichia coli unable to produce indole. External administration of systemic indole increases adult neurogenesis in the dentate gyrus in these mouse models and in specific pathogen-free (SPF) control mice. Indole-treated mice display elevated synaptic markers postsynaptic density protein 95 and synaptophysin, suggesting synaptic maturation effects in vivo. By contrast, neurogenesis is not induced by indole in aryl hydrocarbon receptor KO (AhR-/-) mice or in ex vivo neurospheres derived from them. Neural progenitor cells exposed to indole exit the cell cycle, terminally differentiate, and mature into neurons that display longer and more branched neurites. These effects are not observed with kynurenine, another AhR ligand. The indole-AhR-mediated signaling pathway elevated the expression of ß-catenin, Neurog2, and VEGF-α genes, thus identifying a molecular pathway connecting gut microbiota composition and their metabolic function to neurogenesis in the adult hippocampus. Our data have implications for the understanding of mechanisms of brain aging and for potential next-generation therapeutic opportunities.

Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry.

Dysregulated lipid metabolism underpins many chronic diseases including cardiometabolic diseases. Mass spectrometry-based lipidomics is an important tool for understanding mechanisms of lipid dysfunction and is widely applied in epidemiology and clinical studies. With ever-increasing sample numbers, single batch acquisition is often unfeasible, requiring advanced methods that are accurate and robust to batch-to-batch and interday analytical variation. Herein, an optimized comprehensive targeted workflow for plasma and serum lipid quantification is presented, combining stable isotope internal standard dilution, automated sample preparation, and ultrahigh performance liquid chromatography-tandem mass spectrometry with rapid polarity switching to target 1163 lipid species spanning 20 subclasses. The resultant method is robust to common sources of analytical variation including blood collection tubes, hemolysis, freeze-thaw cycles, storage stability, analyte extraction technique, interinstrument variation, and batch-to-batch variation with 820 lipids reporting a relative standard deviation of <30% in 1048 replicate quality control plasma samples acquired across 16 independent batches (total injection count = 6142). However, sample hemolysis of ≥0.4% impacted lipid concentrations, specifically for phosphatidylethanolamines (PEs). Low interinstrument variability across two identical LC-MS systems indicated feasibility for intra/inter-lab parallelization of the assay. In summary, we have optimized a comprehensive lipidomic protocol to support rigorous analysis for large-scale, multibatch applications in precision medicine. The mass spectrometry lipidomics data have been deposited to massIVE: data set identifiers MSV000090952 and 10.25345/C5NP1WQ4S.

Nonsevere Burn Induces a Prolonged Systemic Metabolic Phenotype Indicative of a Persistent Inflammatory Response Postinjury.

Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic comorbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on the impact of nonsevere injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of a nonsevere burn injury, longitudinal plasma was collected from adults (n = 35) who presented at hospital with a nonsevere burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from nonburn control participants (n = 14). Samples underwent multiplatform metabolic phenotyping using 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoprotein signatures and 852 lipid species from across 20 subclasses. Multivariate data modeling (orthogonal projections to latent structures-discriminate analysis; OPLS-DA) revealed alterations in lipoprotein and lipid metabolism when comparing the baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value < 1.0e-4), low density lipoprotein-2 subfractions (variable importance in projection score; VIP > 6.83e-1) and monoacyglyceride (20:4) (p-value < 1.0e-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP > 7.75e-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols, and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of a nonsevere burn injury. The phenotype is indicative of an acute inflammatory profile that continues to be sustained postinjury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have an elevated incidence postburn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalize intervention strategies, and improve acute care, reducing the risk of chronic comorbidity.

Lysophosphatidylcholines modulate immunoregulatory checkpoints in peripheral monocytes and are associated with mortality in people with acute liver failure.

BACKGROUND & AIMS: Acute liver failure (ALF) is a life-threatening disease characterised by high-grade inflammation and immunoparesis, which is associated with a high incidence of death from sepsis. Herein, we aimed to describe the metabolic dysregulation in ALF and determine whether systemic immune responses are modulated via the lysophosphatidylcholine (LPC)-autotaxin (ATX)-lysophosphatidylcholinic acid (LPA) pathway. METHODS: Ninety-six individuals with ALF, 104 with cirrhosis, 31 with sepsis and 71 healthy controls (HCs) were recruited. Pathways of interest were identified by multivariate statistical analysis of proton nuclear magnetic resonance spectroscopy and untargeted ultraperformance liquid chromatography-mass spectrometry-based lipidomics. A targeted metabolomics panel was used for validation. Peripheral blood mononuclear cells were cultured with LPA 16:0, 18:0, 18:1, and their immune checkpoint surface expression was assessed by flow cytometry. Transcript-level expression of the LPA receptor (LPAR) in monocytes was investigated and the effect of LPAR antagonism was also examined in vitro. RESULTS: LPC 16:0 was highly discriminant between ALF and HC. There was an increase in ATX and LPA in individuals with ALF compared to HCs and those with sepsis. LPCs 16:0, 18:0 and 18:1 were reduced in individuals with ALF and were associated with a poor prognosis. Treatment of monocytes with LPA 16:0 increased their PD-L1 expression and reduced CD155, CD163, MerTK levels, without affecting immune checkpoints on T and NK/CD56+T cells. LPAR1 and 3 antagonism in culture reversed the effect of LPA on monocyte expression of MerTK and CD163. MerTK and CD163, but not LPAR genes, were differentially expressed and upregulated in monocytes from individuals with ALF compared to controls. CONCLUSION: Reduced LPC levels are biomarkers of poor prognosis in individuals with ALF. The LPC-ATX-LPA axis appears to modulate innate immune response in ALF via LPAR1 and LPAR3. Further investigations are required to identify novel therapeutic agents targeting these receptors. IMPACT AND IMPLICATIONS: We identified a metabolic signature of acute liver failure (ALF) and investigated the immunometabolic role of the lysophosphatidylcholine-autotaxin-lysophosphatidylcholinic acid pathway, with the aim of finding a mechanistic explanation for monocyte behaviour and identifying possible therapeutic targets (to modulate the systemic immune response in ALF). At present, no selective immune-based therapies exist. We were able to modulate the phenotype of monocytes in vitro and aim to extend these findings to murine models of ALF as a next step. Future therapies may be based on metabolic modulation; thus, the role of specific lipids in this pathway require elucidation and the relative merits of autotaxin inhibition, lysophosphatidylcholinic acid receptor blockade or lipid-based therapies need to be determined. Our findings begin to bridge this knowledge gap and the methods used herein could be useful in identifying therapeutic targets as part of an experimental medicine approach.

Metabolic Profiling Reveals Changes in Serum Predictive of Venous Ulcer Healing.

OBJECTIVE: The aim of this study was to identify potential biomarkers predictive of healing or failure to heal in a population with venous leg ulceration. SUMMARY BACKGROUND DATA: Venous leg ulceration presents important physical, psychological, social and financial burdens. Compression therapy is the main treatment, but it can be painful and time-consuming, with significant recurrence rates. The identification of a reliable biochemical signature with the ability to identify nonhealing ulcers has important translational applications for disease prognostication, personalized health care and the development of novel therapies. METHODS: Twenty-eight patients were assessed at baseline and at 20 weeks. Untargeted metabolic profiling was performed on urine, serum, and ulcer fluid, using mass spectrometry and nuclear magnetic resonance spectroscopy. RESULTS: A differential metabolic phenotype was identified in healing (n = 15) compared to nonhealing (n = 13) venous leg ulcer patients. Analysis of the assigned metabolites found ceramide and carnitine metabolism to be relevant pathways. In this pilot study, only serum biofluids could differentiate between healing and nonhealing patients. The ratio of carnitine to ceramide was able to differentiate between healing phenotypes with 100% sensitivity, 79% specificity, and 91% accuracy. CONCLUSIONS: This study reports a metabolic signature predictive of healing in venous leg ulceration and presents potential translational applications for disease prognostication and development of targeted therapies.

Metabolic phenotyping in health and disease.

Analyzing metabolites (small molecules <1 kDa) in body fluids such as urine and plasma using various spectroscopic methods provides information on the metabotype (metabolic phenotype) of individuals or populations, information that can be applied to personalized medicine or public healthcare.

Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction.

An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.

Balancing the Equation: A Natural History of Trimethylamine and Trimethylamine-N-oxide.

Trimethylamine (TMA) and its N-oxide (TMAO) are ubiquitous in prokaryote and eukaryote organisms as well as in the environment, reflecting their fundamental importance in evolutionary biology, and their diverse biochemical functions. Both metabolites have multiple biological roles including cell-signaling. Much attention has focused on the significance of serum and urinary TMAO in cardiovascular disease risk, yet this is only one of the many facets of a deeper TMA-TMAO partnership that reflects the significance of these metabolites in multiple biological processes spanning animals, plants, bacteria, and fungi. We report on analytical methods for measuring TMA and TMAO and attempt to critically synthesize and map the global functions of TMA and TMAO in a systems biology framework.

J-Edited DIffusional Proton Nuclear Magnetic Resonance Spectroscopic Measurement of Glycoprotein and Supramolecular Phospholipid Biomarkers of Inflammation in Human Serum.

Proton nuclear magnetic resonance (NMR) N-acetyl signals (Glyc) from glycoproteins and supramolecular phospholipids composite peak (SPC) from phospholipid quaternary nitrogen methyls in subcompartments of lipoprotein particles) can give important systemic metabolic information, but their absolute quantification is compromised by overlap with interfering resonances from lipoprotein lipids themselves. We present a J-Edited DIffusional (JEDI) proton NMR spectroscopic approach to selectively augment signals from the inflammatory marker peaks Glyc and SPCs in blood serum NMR spectra, which enables direct integration of peaks associated with molecules found in specific compartments. We explore a range of pulse sequences that allow editing based on peak J-modulation, translational diffusion, and T2 relaxation time and validate them for untreated blood serum samples from SARS-CoV-2 infected patients (n = 116) as well as samples from healthy controls and pregnant women with physiological inflammation and hyperlipidemia (n = 631). The data show that JEDI is an improved approach to selectively investigate inflammatory signals in serum and may have widespread diagnostic applicability to disease states associated with systemic inflammation.