Metabolomics Reveals Gut Microbiota Contribute to PPARα Deficiency-Induced Alcoholic Liver Injury.

Incidence and mortality rates of alcoholic liver disease (ALD) is one of the highest in the world. In the present study, we found that the genetic knockout nuclear receptor the peroxisome proliferator-activated receptor α (PPARα) exacerbated ALD. Lipidomics of the liver revealed changed levels of lipid species encompassing phospholipids, ceramides (CM), and long-chain fatty acids in Ppara-null mice induced by ethanol. Moreover, 4-hydroxyphenylacetic acid (4-HPA) was changed as induced by ethanol in the metabolome of urine. Moreover, the phylum level analysis showed a decrease in the level of Bacteroidetes and an increase in the level of Firmicutes after alcohol feeding in Ppara-null mice, while there was no change in wild-type mice. In Ppara-null mice, the level of Clostridium_sensu_stricto_1 and Romboutsia were upregulated after alcohol feeding. These data revealed that PPARα deficiency potentiated alcohol-induced liver injury through promotion of lipid accumulation, changing the metabolome of urine, and increasing the level of Clostridium_sensu_stricto_1 and Romboutsia. 4-HPA could improve ALD in mice by regulating inflammation and lipid metabolism. Therefore, our findings suggest a novel approach to the treatment of ALD: focusing on the gut microbiota and its metabolites. Data are available via ProteomeXchange (PXD 041465).

Dissecting the relationship between plasma and tissue metabolome in a cohort of women with obesity: Analysis of subcutaneous and visceral adipose, muscle, and liver.

Untargeted metabolomics of blood samples has become widely applied to study metabolic alterations underpinning disease and to identify biomarkers. However, understanding the relevance of a blood metabolite marker can be challenging if it is unknown whether it reflects the concentration in relevant tissues. To explore this field, metabolomic and lipidomic profiles of plasma, four sites of adipose tissues (ATs) from peripheral or central depot, two sites of muscle tissue, and liver tissue from a group of nondiabetic women with obesity who were scheduled to undergo bariatric surgery (n = 21) or other upper GI surgery (n = 5), were measured by liquid chromatography coupled with mass spectrometry. Relationships between plasma and tissue profiles were examined using Pearson correlation analysis subject to Benjamini-Hochberg correction. Plasma metabolites and lipids showed the highest number of significantly positive correlations with their corresponding concentrations in liver tissue, including lipid species of ceramide, mono- and di-hexosylceramide, sphingomyelin, phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysophosphatidylethanolamine, dimethyl phosphatidylethanolamine, ether-linked PC, ether-linked PE, free fatty acid, cholesteryl ester, diacylglycerol and triacylglycerol, and polar metabolites linked to several metabolic functions and gut microbial metabolism. Plasma also showed significantly positive correlations with muscle for several phospholipid species and polar metabolites linked to metabolic functions and gut microbial metabolism, and with AT for several triacylglycerol species. In conclusion, plasma metabolomic and lipidomic profiles were reflective more of the liver profile than any of the muscle or AT sites examined in the present study. Our findings highlighted the importance of taking into consideration the metabolomic relationship of various tissues with plasma when postulating plasma metabolites marker to underlying mechanisms occurring in a specific tissue.

Comparative metabolism of THCA and THCV using UHPLC-Q-Exactive Orbitrap-MS.

Delta(9)-tetrahydrocannabinolic acid (THCA) and delta(9)-tetrahydrocannabivarin (THCV) are phytocannabinoids with a similar structure derived from Cannabis sativa and possess a variety of biological activities. However, the relationship between the metabolic characterisation and bioactivity of THCA and THCV remains elusive.To explore the relationship between the metabolism of THCA and THCV and their underlying mechanism of activity, human/mouse liver microsomes and mouse primary hepatocytes were used to compare the metabolic maps between THCA and THCV through comparative metabolomics. A total of 29 metabolites were identified containing 7 previously undescribed THCA metabolites and 10 previously undescribed THCV metabolites. Of these metabolites, THCA was transformed into an active metabolite of delta(9)-tetrahydrocannabinol (THC) in these three systems, while THCV was transformed into THC and CBD.Bioactivity assays indicated that all of these phytocannabinoids exhibited anti-inflammatory activity, but the effects of THCA and THCV were slightly different in macrophages RAW264.7. Prediction of ADMET lab demonstrated that THCV and its metabolites were endowed with the advantage of blood-brain barrier (BBB) penetration compared to THCA.In conclusion, this study highlighted that metabolism plays a critical role in the biological activity of phytocannabinoids.

Comparative Metabolomic Profiling of the Metabolic Differences of Δ9-Tetrahydrocannabinol and Cannabidiol.

More than one hundred cannabinoids have been found in cannabis. Δ9-Tetrahydrocannabinol (THC) is the recognized addictive constituent in cannabis; however, the mechanisms underlying THC-induced toxicity remain elusive. To better understand cannabis-induced toxicity, the present study compared the metabolic pathways of THC and its isomer cannabidiol (CBD) in human and mouse liver microsomes using the metabolomic approach. Thirty-two metabolites of THC were identified, including nine undescribed metabolites. Of note, two glutathione (GSH) and two cysteine (Cys) adducts were found in THC's metabolism. Molecular docking revealed that THC conjugates have a higher affinity with GSH and Cys than with the parent compound, THC. Human recombinant cytochrome P450 enzymes, and their corresponding chemical inhibitors, demonstrated that CYP3A4 and CYP1B1 were the primary enzymes responsible for the formation of THC-GSH and THC-Cys, thus enabling conjugation to occur. Collectively, this study systematically compared the metabolism of THC with the metabolism of CBD using the metabolomic approach, which thus highlights the critical role of metabolomics in identifying novel drug metabolites. Moreover, this study also facilitates mechanistic speculation in order to expand the knowledge of drug metabolism and safety.

Untargeted metabolomics reveals plasma metabolites predictive of ectopic fat in pancreas and liver as assessed by magnetic resonance imaging: the TOFI_Asia study.

BACKGROUND: Excess visceral obesity and ectopic organ fat is associated with increased risk of cardiometabolic disease. However, circulating markers for early detection of ectopic fat, particularly pancreas and liver, are lacking. METHODS: Lipid storage in pancreas, liver, abdominal subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) from 68 healthy or pre-diabetic Caucasian and Chinese women enroled in the TOFI_Asia study was assessed by magnetic resonance imaging/spectroscopy (MRI/S). Plasma metabolites were measured with untargeted liquid chromatography-mass spectroscopy (LC-MS). Multivariate partial least squares (PLS) regression identified metabolites predictive of VAT/SAT and ectopic fat; univariate linear regression adjusting for potential covariates identified individual metabolites associated with VAT/SAT and ectopic fat; linear regression adjusted for ethnicity identified clinical and anthropometric correlates for each fat depot. RESULTS: PLS identified 56, 64 and 31 metabolites which jointly predicted pancreatic fat (R2Y = 0.81, Q2 = 0.69), liver fat (RY2 = 0.8, Q2 = 0.66) and VAT/SAT ((R2Y = 0.7, Q2 = 0.62)) respectively. Among the PLS-identified metabolites, none of them remained significantly associated with pancreatic fat after adjusting for all covariates. Dihydrosphingomyelin (dhSM(d36:0)), 3 phosphatidylethanolamines, 5 diacylglycerols (DG) and 40 triacylglycerols (TG) were associated with liver fat independent of covariates. Three DGs and 12 TGs were associated with VAT/SAT independent of covariates. Notably, comparison with clinical correlates showed better predictivity of ectopic fat by these PLS-identified plasma metabolite markers. CONCLUSIONS: Untargeted metabolomics identified candidate markers of visceral and ectopic fat that improved fat level prediction over clinical markers. Several plasma metabolites were associated with level of liver fat and VAT/SAT ratio independent of age, total and visceral adiposity, whereas pancreatic fat deposition was only associated with increased sulfolithocholic acid independent of adiposity-related parameters, but not age.

Integrating network pharmacology and drug side-effect data to explore mechanism of liver injury-induced by tyrosine kinase inhibitors.

Tyrosine kinase inhibitors (TKIs) are highly efficient small-molecule anticancer drugs. Despite the specificity and efficacy of TKIs, they can produce off-target effects, leading to severe liver toxicity, and even some of them are labeled as black box hepatotoxicity. Thus, we focused on representative TKIs associated with severe hepatic adverse events, namely lapatinib, pazopanib, regorafenib, and sunitinib as objections of study, then integrated drug side-effect data from United State Food and Drug Administration (U.S. FDA) and network pharmacology to elucidate mechanism underlying TKI-induced liver injury. Based on network pharmacology, we constructed a specific comorbidity module of high risk of serious adverse effects and created drug-disease networks. Enrichment analysis of the networks revealed the depletion of all-trans-retinoic acid and the involvement of down-regulation of the HSP70 family-mediated endoplasmic reticulum (ER) stress as key factors in TKI-induced liver injury. These results were further verified by transcription data. Based on the target prediction results of drugs and reactive metabolites, we also shed light on the association between toxic metabolites and severe hepatic adverse reactions, and thinking HSPA8, HSPA1A, CYP1A1, CYP1A2 and CYP3A4 were potential therapeutic or preventive targets against TKI-induced liver injury. In conclusion, our research provides comprehensive insights into the mechanism underlying severe liver injury caused by TKIs, offering a better understanding of how to enhance patient safety and treatment efficacy.

Comprehensive biomarker analysis of metabolomics in different syndromes in traditional Chinese medical for prediabetes mellitus.

BACKGROUND: Prediabetes mellitus (PreDM) is a high-risk state for developing type 2 diabetes mellitus (T2DM) and often goes undiagnosed, which is closely associated with obesity and characterized by insulin resistance that urgently needs to be treated. PURPOSE: To obtain a better understanding of the biological processes associated with both "spleen-dampness" syndrome individuals and those with dysglycaemic control at its earliest stages, we performed a detailed metabolomic analysis of individuals with various early impairments in glycaemic control, the results can facilitate clinicians' decision making and benefit individuals at risk. METHODS: According to the diagnostic criteria of TCM patterns and PreDM, patients were divided into 4 groups with 20 cases, patients with syndrome of spleen deficiency with dampness encumbrance and PreDM (PDMPXSK group), patients with syndrome of dampness-heat in the spleen and PreDM (PDMSRYP group), patients with syndrome of spleen deficiency with dampness encumbrance and normal blood glucose (NDMPXSK group), and patients with syndrome of dampness-heat in the spleen and normal blood glucose (NDMSRYP group). Plasma samples from patients were collected for clinical index assessment and untargeted metabolomics using liquid chromatography-mass spectrometry. RESULTS: Among patients with the syndrome of spleen deficiency with dampness encumbrance (PXSK), those with PreDM (PDMPXSK group) had elevated levels of 2-hour post-load blood glucose (2-h PG), glycosylated hemoglobin (HbA1c), high-density lipoprotein cholesterol (HDL-C), and systolic blood pressure (SBP) than those in the normal blood glucose group (NDMPXSK group, P < 0.01). Among patients with the syndrome of dampness-heat in the spleen (SRYP), the levels of body mass index (BMI), fasting blood glucose (FBG), 2-h PG, HbA1c, and fasting insulin (FINS) were higher in the PreDM group (PDMSRYP group) than those in the normal blood glucose group (NDMSRYP group, P < 0.05). In both TCM syndromes, the plasma metabolomic profiles of PreDM patients were mainly discriminatory from the normal blood glucose controls of the same syndrome in the levels of lipid species, with the PXSK syndrome showing a more pronounced and broader spectrum of alterations than the SRYP syndrome. Changes associated with PreDM common to both syndromes included elevations in the levels of 27 metabolites which were mainly lipid species encompassing glycerophospholipids (GPs), diglycerides (DGs) and triglycerides (TGs), cholesterol and derivatives, and decreases in 5 metabolites consisting 1 DG, 1 TG, 2 N,N-dimethyl phosphatidylethanolamine (PE-NMe2) and iminoacetic acid. Correlation analysis identified significant positive correlations of 3α,7α,12α,25-Tetrahydroxy-5ß-cholestane-24-one with more than one glycaemia-related indicators, whereas DG (20:4/20:5) and PC (20:3/14:0) were positively and PC (18:1/14:0) was inversely correlated with more than one lipid profile-related indicators. Based on the value of correlation coefficient, the top three correlative pairs were TG with PC (18:1/14:0) (r = - 0.528), TG with TG (14:0/22:4/22:5) (r = 0.521) and FINS with PE-NMe (15:0/22:4) (r = 0.52). CONCLUSION: Our results revealed PreDM patients with different TCM syndromes were characterized by different clinical profiles. Common metabolite markers associated with PreDM shared by the two TCM syndromes were mainly lipid species encompassing GP, GL, cholesterol and derivatives. Our findings were in line with the current view that altered lipid metabolism is a conserved and early event of dysglycaemia. Our study also implied the possible involvement of perturbed bile acid homeostasis and dysregulated PE methylation during development of dysglycaemia.

Utilising a Clinical Metabolomics LC-MS Study to Determine the Integrity of Biological Samples for Statistical Modelling after Long Term -80 °C Storage: A TOFI_Asia Sub-Study.

Biological samples of lipids and metabolites degrade after extensive years in -80 °C storage. We aimed to determine if associated multivariate models are also impacted. Prior TOFI_Asia metabolomics studies from our laboratory established multivariate models of metabolic risks associated with ethnic diversity. Therefore, to compare multivariate modelling degradation after years of -80 °C storage, we selected a subset of aged (≥5-years) plasma samples from the TOFI_Asia study to re-analyze via untargeted LC-MS metabolomics. Samples from European Caucasian (n = 28) and Asian Chinese (n = 28) participants were evaluated for ethnic discrimination by partial least squares discriminative analysis (PLS-DA) of lipids and polar metabolites. Both showed a strong discernment between participants ethnicity by features, before (Initial) and after (Aged) 5-years of -80 °C storage. With receiver operator characteristic curves, sparse PLS-DA derived confusion matrix and prediction error rates, a considerable reduction in model integrity was apparent with the Aged polar metabolite model relative to Initial modelling. Ethnicity modelling with lipids maintained predictive integrity in Aged plasma samples, while equivalent polar metabolite models reduced in integrity. Our results indicate that researchers re-evaluating samples for multivariate modelling should consider time at -80 °C when producing predictive metrics from polar metabolites, more so than lipids.

Tripterygium wilfordii protects against an animal model of autoimmune hepatitis.

ETHNOPHARMACOLOGICAL RELEVANCE: Tripterygium wilfordii tablets (TWT) is widely used to treat autoimmune diseases such as rheumatoid arthritis. Celastrol, one main active ingredient in TWT, has been shown to produce a variety of beneficial effects, including anti-inflammatory, anti-obesity, anti-cancer, and immunomodulatory. However, whether TWT could protect against Concanavalin A (Con A)-induced hepatitis remains unclear. THE AIM OF THE STUDY: This study aims to investigate the protective effect of TWT against Con A-induced hepatitis and elucidate the underlying mechanism. MATERIALS AND METHODS: Metabolomic analysis, pathological analysis, biochemical analysis, qPCR and Western blot analysis and the Pxr-null mice were used in this study. RESULTS: The results indicated that TWT and its active ingredient celastrol could protect against Con A-induced acute hepatitis. Plasma metabolomics analysis revealed that metabolic perturbations related to bile acid and fatty acid metabolism induced by Con A were reversed by celastrol. The level of itaconate in the liver was increased by celastrol and speculated as an active endogenous compound mediating the protective effect of celastrol. Administration of 4-octanyl itaconate (4-OI) as a cell-permeable itaconate mimicker was found to attenuate Con A-induced liver injury through activation of the pregnane X receptor (PXR) and enhancement of the transcription factor EB (TFEB)-mediated autophagy. CONCLUSIONS: Celastrol increased itaconate and 4-OI promoted activation of TFEB-mediated lysosomal autophagy to protect against Con A-induced liver injury in a PXR-dependent manner. Our study reported a protective effect of celastrol against Con A-induced AIH via an increased production of itaconate and upregulation of TFEB. The results highlighted that PXR and TFEB-mediated lysosomal autophagic pathway may offer promising therapeutic target for the treatment of autoimmune hepatitis.

Metabolomics reveals that sulfotransferase 1 may regulate colchicine-induced liver injury.

Colchicine is widely used to treat gouty arthritis for years. Previous studies showed that colchicine overdose can cause liver damage, yet the mechanism underlying its hepatotoxicity remains unclear. In this study, hepatotoxicity of colchicine was investigated in vivo. Metabolomic analysis of colchicine metabolites and endogenous metabolites was performed using Ultra High Performance Liquid Chromatography (UHPLC) - mass spectrometry (MS). Seventeen metabolites of colchicine were identified, including 3 novel sulfated metabolites. Meanwhile, endogenous sulfated metabolites were found to be decreased by colchicine. Colchicine might regulate sulfotransferase 1 (SULT1) through perixisome proliferation-activated receptor ɑ (PPARα), and inhibition of SULT1 reduced the levels of sulfated metabolites of colchicine. Inhibition of SULT1 aggravated colchicine-induced liver injury, whereas activation of SULT1 attenuated its liver injury. The supplementation of endogenous sulfated metabolites indoxyl sulfate (IS) or p-cresol sulfate (PCS) alleviated colchicine-induced liver injury through modulation of the CASPASE-1-gasdermin D (GSDMD) pathway. These results indicated that colchicine might cause hepatotoxicity through inhibition of SULT1and decreased production of bioactive sulfated endogenous metabolites IS and PCS. Our results provided evidence for potential therapeutic targets and agents to prevent liver injury caused by colchicine. Targeting the SULT1 enzyme and administration of IS and PCS may be useful in alleviating colchicine hepatotoxicity.

Celastrol as an intestinal FXR inhibitor triggers tripolide-induced intestinal bleeding: Underlying mechanism of gastrointestinal injury induced by Tripterygium wilfordii.

BACKGROUND: Tripterygium wilfordii has been widely used for the treatment of rheumatoid arthritis, which is frequently accompanied by severe gastrointestinal damage. The molecular mechanism underlying the gastrointestinal injury of Tripterygium wilfordii are yet to be elucidated. METHODS: Transmission electron microscopy, and pathological and biochemical analyses were applied to assess intestinal bleeding. Metabolic changes in the serum and intestine were determined by metabolomics. In vivo (time-dependent effect and dose-response) and in vitro (double luciferase reporter gene system, DRATs, molecular docking, HepG2 cells and small intestinal organoids) studies were used to identify the inhibitory role of celastrol on intestinal farnesoid X receptor (FXR) signaling. Fxr-knockout mice and FXR inhibitors and agonists were used to evaluate the role of FXR in the intestinal bleeding induced by Tripterygium wilfordii. RESULTS: Co-treatment with triptolide + celastrol (from Tripterygium wilfordii) induced intestinal bleeding in mice. Metabolomic analysis indicated that celastrol suppressed intestinal FXR signaling, and further molecular studies revealed that celastrol was a novel intestinal FXR antagonist. In Fxr-knockout mice or the wild-type mice pre-treated with pharmacological inhibitors of FXR, triptolide alone could activate the duodenal JNK pathway and induce intestinal bleeding, which recapitulated the pathogenic features obtained by co-treatment with triptolide and celastrol. Lastly, intestinal bleeding induced by co-treatment with triptolide and celastrol could be effectively attenuated by the FXR or gut-restricted FXR agonist through downregulation of the duodenal JNK pathway. CONCLUSIONS: The synergistic effect between triptolide and celastrol contributed to the gastrointestinal injury induced by Tripterygium wilfordii via dysregulation of the FXR-JNK axis, suggesting that celastrol should be included in the quality standards system for evaluation of Tripterygium wilfordii preparations. Determining the mechanism of the FXR-JNK axis in intestinal bleeding could aid in the identification of additional therapeutic targets for the treatment of gastrointestinal hemorrhage diseases. This study also provides a new standard for the quality assessment of Tripterygium wilfordii used in the treatment of gastrointestinal disorders.

Engineered mesenchymal stem cell-derived extracellular vesicles constitute a versatile platform for targeted drug delivery.

Extracellular vesicles (EVs) are promising therapeutic carriers owing to their ideal size range and intrinsic biocompatibility. However, limited targeting ability has caused major setbacks in the clinical application of EV therapeutics. To overcome this, we genetically engineered natural free streptavidin (SA) on the cellular surface of bone marrow mesenchymal stem cells (BMSCs) and obtained typical EVs from these cells (BMSC-EVs). Biotin-coated gold nanoparticles confirmed the expression of SA on the membrane of EVs, which has a high affinity for biotinylated molecules. Using a squamous cell carcinoma model, we demonstrated that a pH-sensitive fusogenic peptide -modification of BMSC-EVs achieved targetability in the microenvironment of a hypoxic tumor to deliver anti-tumor drugs. Using EGFR+HER2- and EGFR-HER2+ breast cancer models, we demonstrated that anti-EGFR and anti-HER2 modifications of BMSC-EVs were able to specifically deliver drugs to EGFR+ and HER2+ tumors, respectively. Using a collagen-induced arthritis model, we confirmed that anti-IL12/IL23-modified BMSC-EVs specifically accumulated in the arthritic joint and alleviated inflammation. Administration of SA-overexpressing BMSC-EVs has limited immunogenicity and high safety in vivo, suggesting that BMSC-derived EVs are ideal drug delivery vehicle. These representative scenarios of targeting modification suggest that, using different biotinylated molecules, the SA-overexpressing BMSC-EVs could be endowed with different targetabilities, which allows BMSC-EVs to serve as a versatile platform for targeted drug delivery under various situations.

Recent advances in metabolism and toxicity of tyrosine kinase inhibitors.

Small molecule tyrosine kinase inhibitors (TKIs) are widely used as anticancer drugs approved by U.S. FDA. However, the toxicities of TKIs to multiple organs have greatly limited their clinical applications. The metabolism of TKIs generates several potentially toxic metabolites in vivo, that can disturb the endogenous metabolism as well as cellular function, leading to organ damage. Therefore, it is essential to identify the toxic metabolites and elucidate the underlying mechanism of TKI-induced toxicity. Metabolomics is a powerful tool for the identification of the xenobiotic metabolites and metabolic derangement associated with xenobiotic exposure, that is helpful to understand the toxicity of TKIs. The study using metabolomics approach has revealed that the reactive metabolites/intermediates (e.g., N-oxide metabolite, primary amine metabolite, 1,4-benzoquinone intermediate) and adducts with glutathione, cysteine and mercapturic acid can be derived from TKIs. Fourteen metabolic pathways could be affected following the TKI treatment, including lipid metabolism, bile acid metabolism, and gut microbiota-related pathway. Modulation of xenobiotic receptor signaling, inhibition of xenobiotic metabolism, and supplementation of endogenous metabolites are potential strategies to protect against TKI-induced toxicity. In this review, studies on the metabolism of TKIs and the alterations of endogenous metabolism are discussed, and the potential preventions against TKI-induced toxicity are summarized.

Metabolomic signatures for visceral adiposity and dysglycaemia in Asian Chinese and Caucasian European adults: the cross-sectional TOFI_Asia study.

BACKGROUND: Asian Chinese are more susceptible to deposition of visceral adipose tissue (VAT) and type 2 diabetes (T2D) development than European Caucasians when matched for gender, age and body mass index (BMI). Our aims were: (i) characterise the ethnicity-specific metabolomic signature of visceral adiposity measured by dual energy X-ray absorptiometry (DXA) and fasting plasma glucose (FPG), and (ii) identify individuals susceptible to worse metabolic health outcomes. METHODS: Fasting plasma samples from normoglycaemic (n = 274) and prediabetic (n = 83) participants were analysed with liquid chromatography-mass spectrometry using untargeted metabolomics. Multiple linear regression adjusting for age, gender and BMI was performed to identify metabolites associated with FPG and VAT calculated as percentage of total body fat (%VATTBF) in each ethnic group. Metabolic risk groups in each ethnicity were stratified based on the joint metabolomic signature for FPG and %VATTBF and clinically characterised using partial least squares-discriminant analysis (PLS-DA) and t-tests. RESULTS: FPG was correlated with 40 and 110 metabolites in Caucasians and Chinese respectively, with diglyceride DG(38:5) (adjusted ß = 0.29, p = 3.00E-05) in Caucasians and triglyceride TG(54:4) (adjusted ß = 0.28, p = 2.02E-07) in Chinese being the most significantly correlated metabolite based on the p-value. %VATTBF was correlated with 85 and 119 metabolites in Caucasians and Chinese respectively, with TG(56:2) (adjusted ß = 0.3, p = 8.25E-09) in Caucasians and TG(58:3) (adjusted ß = 0.25, p = 2.34E-08) in Chinese being the most significantly correlated. 24 metabolites associated with FPG were common to both ethnicities including glycerolipid species. 67 metabolites associated with %VATTBF were common to both ethnicities including positive correlations with dihydroceramide, sphingomyelin, glycerolipid, phosphatidylcholine, phosphatidylethnolamine, and inverse correlations with ether-linked phosphatidylcholine. Participant re-stratification found greater total and central adiposity, worse clinical lipid profiles, higher serum glucoregulatory peptides and liver enzymes in normal fasting glucose (NFG) individuals with a prediabetic metabolomic profile than NFG individuals with a normoglycaemic metabolomic profile in both ethnicities. CONCLUSIONS: Untargeted metabolomics identified common and disparate metabolites associated with FPG and %VATTBF, with an ethnic-dimorphic signature for these metabolic traits. These signatures could improve risk stratification and identify NFG individuals with an adverse cardiometabolic and T2D risk profile.

Tissue-Specific Sample Dilution: An Important Parameter to Optimise Prior to Untargeted LC-MS Metabolomics.

When developing a sample preparation protocol for LC-MS untargeted metabolomics of a new sample matrix unfamiliar to the laboratory, selection of a suitable injection concentration is rarely described. Here we developed a simple workflow to address this issue prior to untargeted LC-MS metabolomics using pig adipose tissue and liver tissue. Bi-phasic extraction was performed to enable simultaneous optimisation of parameters for analysis of both lipids and polar extracts. A series of diluted pooled samples were analysed by LC-MS and used to evaluate signal linearity. Suitable injected concentrations were determined based on both the number of reproducible features and linear features. With our laboratory settings, the optimum concentrations of tissue mass to reconstitution solvent of liver and adipose tissue lipid fractions were found to be 125 mg/mL and 7.81 mg/mL respectively, producing 2811 (ESI+) and 4326 (ESI-) linear features from liver, 698 (ESI+) and 498 (ESI-) linear features from adipose tissue. For analysis of the polar fraction of both tissues, 250 mg/mL was suitable, producing 403 (ESI+) and 235 (ESI-) linear features from liver, 114 (ESI+) and 108 (ESI-) linear features from adipose tissue. Incorrect reconstitution volumes resulted in either severe overloading or poor linearity in our lipid data, while too dilute polar fractions resulted in a low number of reproducible features (<50) compared to hundreds of reproducible features from the optimum concentration used. Our study highlights on multiple matrices and multiple extract and chromatography types, the critical importance of determining a suitable injected concentration prior to untargeted LC-MS metabolomics, with the described workflow applicable to any matrix and LC-MS system.