Bidirectional modulation of TCA cycle metabolites and anaplerosis by metformin and its combination with SGLT2i.

BACKGROUND: Metformin and sodium-glucose-cotransporter-2 inhibitors (SGLT2i) are cornerstone therapies for managing hyperglycemia in diabetes. However, their detailed impacts on metabolic processes, particularly within the citric acid (TCA) cycle and its anaplerotic pathways, remain unclear. This study investigates the tissue-specific metabolic effects of metformin, both as a monotherapy and in combination with SGLT2i, on the TCA cycle and associated anaplerotic reactions in both mice and humans. METHODS: Metformin-specific metabolic changes were initially identified by comparing metformin-treated diabetic mice (MET) with vehicle-treated db/db mice (VG). These findings were then assessed in two human cohorts (KORA and QBB) and a longitudinal KORA study of metformin-naïve patients with Type 2 Diabetes (T2D). We also compared MET with db/db mice on combination therapy (SGLT2i + MET). Metabolic profiling analyzed 716 metabolites from plasma, liver, and kidney tissues post-treatment, using linear regression and Bonferroni correction for statistical analysis, complemented by pathway analyses to explore the pathophysiological implications. RESULTS: Metformin monotherapy significantly upregulated TCA cycle intermediates such as malate, fumarate, and α-ketoglutarate (α-KG) in plasma, and anaplerotic substrates including hepatic glutamate and renal 2-hydroxyglutarate (2-HG) in diabetic mice. Downregulated hepatic taurine was also observed. The addition of SGLT2i, however, reversed these effects, such as downregulating circulating malate and α-KG, and hepatic glutamate and renal 2-HG, but upregulated hepatic taurine. In human T2D patients on metformin therapy, significant systemic alterations in metabolites were observed, including increased malate but decreased citrulline. The bidirectional modulation of TCA cycle intermediates in mice influenced key anaplerotic pathways linked to glutaminolysis, tumorigenesis, immune regulation, and antioxidative responses. CONCLUSION: This study elucidates the specific metabolic consequences of metformin and SGLT2i on the TCA cycle, reflecting potential impacts on the immune system. Metformin shows promise for its anti-inflammatory properties, while the addition of SGLT2i may provide liver protection in conditions like metabolic dysfunction-associated steatotic liver disease (MASLD). These observations underscore the importance of personalized treatment strategies.

Long-Chain Acylcholines Link Butyrylcholinesterase to Regulation of Non-neuronal Cholinergic Signaling.

Acylcholines are comprised of an acyl chain esterified to a choline moiety; acetylcholine is the best-characterized member of this class, functioning as a neurotransmitter in the central and peripheral nervous systems as well as an inhibitor of cytokine production by macrophages and other innate immune cells. Acylcholines are metabolized by a class of cholinesterases, including acetylcholinesterase (a specific regulator of acetylcholine levels) and butyrylcholinesterase (BChE, an enigmatic enzyme whose function has not been resolved by genetic knockout models). BChE provides reserve capacity to hydrolyze acetylcholine, but its importance is arguable given acetylcholinesterase is the most catalytically efficient enzyme characterized to date. While known to be substrates of BChE in vitro, endogenous production of long-chain acylcholines is a recent discovery enabled by untargeted metabolomics. Compared to acetylcholine, long-chain acylcholines show greater stability in circulation with homeostatic levels-dictated by synthesis and clearance-suggested to impact cholinergic receptor sensitivity of acetylcholine with varying levels of antagonism. Acylcholines then provide a link between BChE and non-neuronal acetylcholine signaling, filling a gap in understanding around how imbalances between acylcholines and BChE could modulate inflammatory disease, such as the "cytokine storm" identified in severe COVID-19. Areas for further research, development, and clinical testing are outlined.

Genome-wide scan identifies novel genetic loci regulating salivary metabolite levels.

Saliva, as a biofluid, is inexpensive and non-invasive to obtain, and provides a vital tool to investigate oral health and its interaction with systemic health conditions. There is growing interest in salivary biomarkers for systemic diseases, notably cardiovascular disease. Whereas hundreds of genetic loci have been shown to be involved in the regulation of blood metabolites, leading to significant insights into the pathogenesis of complex human diseases, little is known about the impact of host genetics on salivary metabolites. Here we report the first genome-wide association study exploring 476 salivary metabolites in 1419 subjects from the TwinsUK cohort (discovery phase), followed by replication in the Study of Health in Pomerania (SHIP-2) cohort. A total of 14 distinct locus-metabolite associations were identified in the discovery phase, most of which were replicated in SHIP-2. While only a limited number of the loci that are known to regulate blood metabolites were also associated with salivary metabolites in our study, we identified several novel saliva-specific locus-metabolite associations, including associations for the AGMAT (with the metabolites 4-guanidinobutanoate and beta-guanidinopropanoate), ATP13A5 (with the metabolite creatinine) and DPYS (with the metabolites 3-ureidopropionate and 3-ureidoisobutyrate) loci. Our study suggests that there may be regulatory pathways of particular relevance to the salivary metabolome. In addition, some of our findings may have clinical significance, such as the utility of the pyrimidine (uracil) degradation metabolites in predicting 5-fluorouracil toxicity and the role of the agmatine pathway metabolites as biomarkers of oral health.

The potential of metabolic profiling for vaccine development.

Recent technological advances have provided deeper insights into the role of small molecules in biological processes. Metabolic profiling has thus entered the arena of -omics studies and rapidly proven its value both as stand-alone and as complement to other more advanced approaches, notably transcriptomics. Here we describe the potential of metabolic profiling for vaccinology embedded in the context of infection and immunity. This discussion is preceded by a description of the relevant technical and analytical tools for biological interpretation of metabolic data. Although not as widely applied as other -omics technologies, we believe that metabolic profiling can make important contributions to the better understanding of mechanisms underlying vaccine-induced responses and their effects on the prevention of infection or disease.

Self-Reported Medication Use and Urinary Drug Metabolites in the German Chronic Kidney Disease (GCKD) Study.

BACKGROUND: Polypharmacy is common among patients with CKD, but little is known about the urinary excretion of many drugs and their metabolites among patients with CKD. METHODS: To evaluate self-reported medication use in relation to urine drug metabolite levels in a large cohort of patients with CKD, the German Chronic Kidney Disease study, we ascertained self-reported use of 158 substances and 41 medication groups, and coded active ingredients according to the Anatomical Therapeutic Chemical Classification System. We used a nontargeted mass spectrometry-based approach to quantify metabolites in urine; calculated specificity, sensitivity, and accuracy of medication use and corresponding metabolite measurements; and used multivariable regression models to evaluate associations and prescription patterns. RESULTS: Among 4885 participants, there were 108 medication-drug metabolite pairs on the basis of reported medication use and 78 drug metabolites. Accuracy was excellent for measurements of 36 individual substances in which the unchanged drug was measured in urine (median, 98.5%; range, 61.1%-100%). For 66 pairs of substances and their related drug metabolites, median measurement-based specificity and sensitivity were 99.2% (range, 84.0%-100%) and 71.7% (range, 1.2%-100%), respectively. Commonly prescribed medications for hypertension and cardiovascular risk reduction-including angiotensin II receptor blockers, calcium channel blockers, and metoprolol-showed high sensitivity and specificity. Although self-reported use of prescribed analgesics (acetaminophen, ibuprofen) was <3% each, drug metabolite levels indicated higher usage (acetaminophen, 10%-26%; ibuprofen, 10%-18%). CONCLUSIONS: This comprehensive screen of associations between urine drug metabolite levels and self-reported medication use supports the use of pharmacometabolomics to assess medication adherence and prescription patterns in persons with CKD, and indicates under-reported use of medications available over the counter, such as analgesics.

Urine Metabolite Levels, Adverse Kidney Outcomes, and Mortality in CKD Patients: A Metabolome-wide Association Study.

RATIONALE & OBJECTIVE: Mechanisms underlying the variable course of disease progression in patients with chronic kidney disease (CKD) are incompletely understood. The aim of this study was to identify novel biomarkers of adverse kidney outcomes and overall mortality, which may offer insights into pathophysiologic mechanisms. STUDY DESIGN: Metabolome-wide association study. SETTING & PARTICIPANTS: 5,087 patients with CKD enrolled in the observational German Chronic Kidney Disease Study. EXPOSURES: Measurements of 1,487 metabolites in urine. OUTCOMES: End points of interest were time to kidney failure (KF), a combined end point of KF and acute kidney injury (KF+AKI), and overall mortality. ANALYTICAL APPROACH: Statistical analysis was based on a discovery-replication design (ratio 2:1) and multivariable-adjusted Cox regression models. RESULTS: After a median follow-up of 4 years, 362 patients died, 241 experienced KF, and 382 experienced KF+AKI. Overall, we identified 55 urine metabolites whose levels were significantly associated with adverse kidney outcomes and/or mortality. Higher levels of C-glycosyltryptophan were consistently associated with all 3 main end points (hazard ratios of 1.43 [95% CI, 1.27-1.61] for KF, 1.40 [95% CI, 1.27-1.55] for KF+AKI, and 1.47 [95% CI, 1.33-1.63] for death). Metabolites belonging to the phosphatidylcholine pathway showed significant enrichment. Members of this pathway contributed to the improvement of the prediction performance for KF observed when multiple metabolites were added to the well-established Kidney Failure Risk Equation. LIMITATIONS: Findings among patients of European ancestry with CKD may not be generalizable to the general population. CONCLUSIONS: Our comprehensive screen of the association between urine metabolite levels and adverse kidney outcomes and mortality identifies metabolites that predict KF and represents a valuable resource for future studies of biomarkers of CKD progression.

Amino acid metabolites that regulate G protein signaling during osmotic stress.

All cells respond to osmotic stress by implementing molecular signaling events to protect the organism. Failure to properly adapt can lead to pathologies such as hypertension and ischemia-reperfusion injury. Mitogen-activated protein kinases (MAPKs) are activated in response to osmotic stress, as well as by signals acting through G protein-coupled receptors (GPCRs). For proper adaptation, the action of these kinases must be coordinated. To identify second messengers of stress adaptation, we conducted a mass spectrometry-based global metabolomics profiling analysis, quantifying nearly 300 metabolites in the yeast S. cerevisiae. We show that three branched-chain amino acid (BCAA) metabolites increase in response to osmotic stress and require the MAPK Hog1. Ectopic addition of these BCAA derivatives promotes phosphorylation of the G protein α subunit and dampens G protein-dependent transcription, similar to that seen in response to osmotic stress. Conversely, genetic ablation of Hog1 activity or the BCAA-regulatory enzymes leads to diminished phosphorylation of Gα and increased transcription. Taken together, our results define a new class of candidate second messengers that mediate cross talk between osmotic stress and GPCR signaling pathways.

The Mycobacterium tuberculosis regulatory network and hypoxia.

We have taken the first steps towards a complete reconstruction of the Mycobacterium tuberculosis regulatory network based on ChIP-Seq and combined this reconstruction with system-wide profiling of messenger RNAs, proteins, metabolites and lipids during hypoxia and re-aeration. Adaptations to hypoxia are thought to have a prominent role in M. tuberculosis pathogenesis. Using ChIP-Seq combined with expression data from the induction of the same factors, we have reconstructed a draft regulatory network based on 50 transcription factors. This network model revealed a direct interconnection between the hypoxic response, lipid catabolism, lipid anabolism and the production of cell wall lipids. As a validation of this model, in response to oxygen availability we observe substantial alterations in lipid content and changes in gene expression and metabolites in corresponding metabolic pathways. The regulatory network reveals transcription factors underlying these changes, allows us to computationally predict expression changes, and indicates that Rv0081 is a regulatory hub.

Gut microbial diversity is associated with lower arterial stiffness in women.

Aims: The gut microbiome influences metabolic syndrome (MetS) and inflammation and is therapeutically modifiable. Arterial stiffness is poorly correlated with most traditional risk factors. Our aim was to examine whether gut microbial composition is associated with arterial stiffness. Methods and results: We assessed the correlation between carotid-femoral pulse wave velocity (PWV), a measure of arterial stiffness, and gut microbiome composition in 617 middle-aged women from the TwinsUK cohort with concurrent serum metabolomics data. Pulse wave velocity was negatively correlated with gut microbiome alpha diversity (Shannon index, Beta(SE)= -0.25(0.07), P = 1 × 10-4) after adjustment for covariates. We identified seven operational taxonomic units associated with PWV after adjusting for covariates and multiple testing-two belonging to the Ruminococcaceae family. Associations between microbe abundances, microbe diversity, and PWV remained significant after adjustment for levels of gut-derived metabolites (indolepropionate, trimethylamine oxide, and phenylacetylglutamine). We linearly combined the PWV-associated gut microbiome-derived variables and found that microbiome factors explained 8.3% (95% confidence interval 4.3-12.4%) of the variance in PWV. A formal mediation analysis revealed that only a small proportion (5.51%) of the total effect of the gut microbiome on PWV was mediated by insulin resistance and visceral fat, c-reactive protein, and cardiovascular risk factors after adjusting for age, body mass index, and mean arterial pressure. Conclusions: Gut microbiome diversity is inversely associated with arterial stiffness in women. The effect of gut microbiome composition on PWV is only minimally mediated by MetS. This first human observation linking the gut microbiome to arterial stiffness suggests that targeting the microbiome may be a way to treat arterial ageing.

Near-Complete Correction of Profound Metabolomic Impairments Corresponding to Functional Benefit in MPS IIIB Mice after IV rAAV9-hNAGLU Gene Delivery.

Mucopolysaccharidosis (MPS) IIIB is a lysosomal storage disease with complex CNS and somatic pathology due to a deficiency in α-N-acetylglucosaminidase (NAGLU). Using global metabolic profiling by mass spectrometry targeting 361 metabolites, this study detected significant decreases in 225 and increases in six metabolites in serum samples from 7-month-old MPS IIIB mice, compared to wild-type (WT) mice. The metabolic disturbances involve virtually all major pathways of amino acid, peptide (58/102), carbohydrate (18/28), lipid (111/139), nucleotide (12/24), energy (2/9), vitamin and cofactor (11/16), and xenobiotic (11/28) metabolism. Notably, the reduced metabolites included eight essential amino acids, vitamins (C, E, B2, and B6), and neurotransmitters (serotonin, glutamate, aspartate, tryptophan, and N-acetyltyrosine). The metabolic impairments appear to emerge early during disease progression before the age of 2 months. Importantly, the restoration of NAGLU activity with an intravenous (i.v.) injection of rAAV9-hNAGLU vector led to near-complete correction of all serum metabolite abnormalities, with 201 (87%) metabolites normalized and 30 (13%) over-corrected. While the mechanisms are unclear, our data demonstrate that the lack of NAGLU activity triggers profound functional metabolic disturbances in MPS IIIB. These metabolic impairments respond well to a systemic rAAV9-hNAGLU gene delivery, supporting the surrogate biomarker potential of serum metabolomic profiles for MPS IIIB therapies.

Metabolites of milk intake: a metabolomic approach in UK twins with findings replicated in two European cohorts.

PURPOSE: Milk provides a significant source of calcium, protein, vitamins and other minerals to Western populations throughout life. Due to its widespread use, the metabolic and health impact of milk consumption warrants further investigation and biomarkers would aid epidemiological studies. METHODS: Milk intake assessed by a validated food frequency questionnaire was analyzed against fasting blood metabolomic profiles from two metabolomic platforms in females from the TwinsUK cohort (n = 3559). The top metabolites were then replicated in two independent populations (EGCUT, n = 1109 and KORA, n = 1593), and the results from all cohorts were meta-analyzed. RESULTS: Four metabolites were significantly associated with milk intake in the TwinsUK cohort after adjustment for multiple testing (P < 8.08 × 10-5) and covariates (BMI, age, batch effects, family relatedness and dietary covariates) and replicated in the independent cohorts. Among the metabolites identified, the carnitine metabolite trimethyl-N-aminovalerate (ß = 0.012, SE = 0.002, P = 2.98 × 10-12) and the nucleotide uridine (ß = 0.004, SE = 0.001, P = 9.86 × 10-6) were the strongest novel predictive biomarkers from the non-targeted platform. Notably, the association between trimethyl-N-aminovalerate and milk intake was significant in a group of MZ twins discordant for milk intake (ß = 0.050, SE = 0.015, P = 7.53 × 10-4) and validated in the urine of 236 UK twins (ß = 0.091, SE = 0.032, P = 0.004). Two metabolites from the targeted platform, hydroxysphingomyelin C14:1 (ß = 0.034, SE = 0.005, P = 9.75 × 10-14) and diacylphosphatidylcholine C28:1 (ß = 0.034, SE = 0.004, P = 4.53 × 10-16), were also replicated. CONCLUSIONS: We identified and replicated in independent populations four novel biomarkers of milk intake: trimethyl-N-aminovalerate, uridine, hydroxysphingomyelin C14:1 and diacylphosphatidylcholine C28:1. Together, these metabolites have potential to objectively examine and refine milk-disease associations.

Human metabolic individuality in biomedical and pharmaceutical research.

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

Serum global metabolomics profiling reveals profound metabolic impairments in patients with MPS IIIA and MPS IIIB.

The monogenic defects in specific lysosomal enzymes in mucopolysaccharidosis (MPS) III lead to lysosomal storage of glycosaminoglycans and complex CNS and somatic pathology, for which the detailed mechanisms remain unclear. In this study, serum samples from patients with MPS IIIA (age 2-9 yr) and MPS IIIB (2-13 yr) and healthy controls (age 2-9 yr) were assayed by global metabolomics profiling of 658 metabolites using mass spectrometry. Significant alterations were detected in 423 metabolites in all MPS III patients, of which 366 (86.5%) decreased and 57 (13.5%) increased. Similar profiles were observed when analyzing data from MPS IIIA and MPS IIIB samples separately, with only limited age variations in 36 metabolites. The observed metabolic disturbances in MPS III patients involve virtually all major pathways of amino acid (101/150), peptide (17/21), carbohydrate (19/23), lipid (221/325), nucleotide (15/25), energy (8/9), vitamins and co-factors (8/21), and xenobiotics (34/84) metabolism. Notably, detected serum metabolite decreases involved all key amino acids, all major neurotransmitter pathways, and broad neuroprotective compounds. The elevated metabolites are predominantly lipid derivatives, and also include cysteine metabolites and a fibrinogen peptide fragment, consistent with the status of oxidative stress and inflammation in MPS III. This study demonstrates that the lysosomal glycosaminoglycans storage triggers profound metabolic disturbances in patients with MPS III disorders, leading to severe functional depression of virtually all metabolic pathways, which emerge early during the disease progression. Serum global metabolomics profiling may provide an important and minimally invasive tool for better understanding the disease mechanisms and identification of potential biomarkers for MPS III.

A Metabolome-Wide Association Study of Kidney Function and Disease in the General Population.

Small molecules are extensively metabolized and cleared by the kidney. Changes in serum metabolite concentrations may result from impaired kidney function and can be used to estimate filtration (e.g., the established marker creatinine) or may precede and potentially contribute to CKD development. Here, we applied a nontargeted metabolomics approach using gas and liquid chromatography coupled to mass spectrometry to quantify 493 small molecules in human serum. The associations of these molecules with GFR estimated on the basis of creatinine (eGFRcr) and cystatin C levels were assessed in ≤1735 participants in the KORA F4 study, followed by replication in 1164 individuals in the TwinsUK registry. After correction for multiple testing, 54 replicated metabolites significantly associated with eGFRcr, and six of these showed pairwise correlation (r≥0.50) with established kidney function measures: C-mannosyltryptophan, pseudouridine, N-acetylalanine, erythronate, myo-inositol, and N-acetylcarnosine. Higher C-mannosyltryptophan, pseudouridine, and O-sulfo-L-tyrosine concentrations associated with incident CKD (eGFRcr <60 ml/min per 1.73 m(2)) in the KORA F4 study. In contrast with serum creatinine, C-mannosyltryptophan and pseudouridine concentrations showed little dependence on sex. Furthermore, correlation with measured GFR in 200 participants in the AASK study was 0.78 for both C-mannosyltryptophan and pseudouridine concentration, and highly significant associations of both metabolites with incident ESRD disappeared upon adjustment for measured GFR. Thus, these molecules may be alternative or complementary markers of kidney function. In conclusion, our study provides a comprehensive list of kidney function-associated metabolites and highlights potential novel filtration markers that may help to improve the estimation of GFR.

Urine Metabolite Profiles Predictive of Human Kidney Allograft Status.

Noninvasive diagnosis and prognostication of acute cellular rejection in the kidney allograft may help realize the full benefits of kidney transplantation. To investigate whether urine metabolites predict kidney allograft status, we determined levels of 749 metabolites in 1516 urine samples from 241 kidney graft recipients enrolled in the prospective multicenter Clinical Trials in Organ Transplantation-04 study. A metabolite signature of the ratio of 3-sialyllactose to xanthosine in biopsy specimen-matched urine supernatants best discriminated acute cellular rejection biopsy specimens from specimens without rejection. For clinical application, we developed a high-throughput mass spectrometry-based assay that enabled absolute and rapid quantification of the 3-sialyllactose-to-xanthosine ratio in urine samples. A composite signature of ratios of 3-sialyllactose to xanthosine and quinolinate to X-16397 and our previously reported urinary cell mRNA signature of 18S ribosomal RNA, CD3ε mRNA, and interferon-inducible protein-10 mRNA outperformed the metabolite signatures and the mRNA signature. The area under the receiver operating characteristics curve for the composite metabolite-mRNA signature was 0.93, and the signature was diagnostic of acute cellular rejection with a specificity of 84% and a sensitivity of 90%. The composite signature, developed using solely biopsy specimen-matched urine samples, predicted future acute cellular rejection when applied to pristine samples taken days to weeks before biopsy. We conclude that metabolite profiling of urine offers a noninvasive means of diagnosing and prognosticating acute cellular rejection in the human kidney allograft, and that the combined metabolite and mRNA signature is diagnostic and prognostic of acute cellular rejection with very high accuracy.

Diagnostic and Prognostic Metabolites Identified for Joint Symptoms in the KORA Population.

This study aims at identifying metabolites that significantly associate with self-reported joint symptoms (diagnostic) and metabolites that can predict the change from a symptom-free status to the development of self-reported joint symptoms after a 7 years period (prognostic). More than 300 metabolites were analyzed for 2246 subjects from the longitudinal study of the KORA (Cooperative Health Research in the Region of Augsburg, Germany), specifically the fourth survey S4 and its 7-year follow-up study F4. Two types of self-reported symptoms, chronic joint inflammation and worn out joints, were used for the analyses. Diagnostic analysis identified dysregulated metabolites in cases with symptoms compared with controls. Prognostic analysis identified metabolites that differentiate subjects in S4 who remained symptom-free after 7 years (F4) from those who developed any combination of symptoms. 48 metabolites were identified as nominally significantly (p < 0.05) associated with the self-reported symptoms in the diagnostic analysis, among which steroids show Bonferroni significance. 45 metabolites were identified as nominally significantly associated with developing symptoms after 7 years, among which hippurate showed Bonferroni significance. We show that metabolic profiles of self-reported joint symptoms are in line with metabolites known to associate with various forms of arthritis and suggest that future studies may benefit from that by investigating the possible use of self-reporting/questionnaire along with metabolic markers for the early referral of patients for further diagnostic workup and treatment of arthritis.

Untargeted Plasma Metabolomics Identifies Endogenous Metabolite with Drug-like Properties in Chronic Animal Model of Multiple Sclerosis.

We performed untargeted metabolomics in plasma of B6 mice with experimental autoimmune encephalitis (EAE) at the chronic phase of the disease in search of an altered metabolic pathway(s). Of 324 metabolites measured, 100 metabolites that mapped to various pathways (mainly lipids) linked to mitochondrial function, inflammation, and membrane stability were observed to be significantly altered between EAE and control (p < 0.05, false discovery rate <0.10). Bioinformatics analysis revealed six metabolic pathways being impacted and altered in EAE, including α-linolenic acid and linoleic acid metabolism (PUFA). The metabolites of PUFAs, including ω-3 and ω-6 fatty acids, are commonly decreased in mouse models of multiple sclerosis (MS) and in patients with MS. Daily oral administration of resolvin D1, a downstream metabolite of ω-3, decreased disease progression by suppressing autoreactive T cells and inducing an M2 phenotype of monocytes/macrophages and resident brain microglial cells. This study provides a proof of principle for the application of metabolomics to identify an endogenous metabolite(s) possessing drug-like properties, which is assessed for therapy in preclinical mouse models of MS.

Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits.

Previously, we reported strong influences of genetic variants on metabolic phenotypes, some of them with clinical relevance. Here, we hypothesize that DNA methylation may have an important and potentially independent effect on human metabolism. To test this hypothesis, we conducted what is to the best of our knowledge the first epigenome-wide association study (EWAS) between DNA methylation and metabolic traits (metabotypes) in human blood. We assess 649 blood metabolic traits from 1814 participants of the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) population study for association with methylation of 457 004 CpG sites, determined on the Infinium HumanMethylation450 BeadChip platform. Using the EWAS approach, we identified two types of methylome-metabotype associations. One type is driven by an underlying genetic effect; the other type is independent of genetic variation and potentially driven by common environmental and life-style-dependent factors. We report eight CpG loci at genome-wide significance that have a genetic variant as confounder (P = 3.9 × 10(-20) to 2.0 × 10(-108), r(2) = 0.036 to 0.221). Seven loci display CpG site-specific associations to metabotypes, but do not exhibit any underlying genetic signals (P = 9.2 × 10(-14) to 2.7 × 10(-27), r(2) = 0.008 to 0.107). We further identify several groups of CpG loci that associate with a same metabotype, such as 4-vinylphenol sulfate and 4-androsten-3-beta,17-beta-diol disulfate. In these cases, the association between CpG-methylation and metabotype is likely the result of a common external environmental factor, including smoking. Our study shows that analysis of EWAS with large numbers of metabolic traits in large population cohorts are, in principle, feasible. Taken together, our data suggest that DNA methylation plays an important role in regulating human metabolism.

Identification of novel biomarkers for Parkinson's disease by metabolomic technologies.

OBJECTIVE: The pathogenesis of Parkinson's disease (PD) involves complex interactions between environmental and genetic factors. Metabolomics can shed light on alterations in metabolic pathways in many diseases, including neurodegenerative diseases. In the present study, we attempted to elucidate the candidate metabolic pathway(s) associated with PD. METHODS: Serum samples were collected from 35 individuals with idiopathic PD without dementia and 15 healthy age-matched control participants without PD. This analysis used a combination of three independent platforms: ultrahigh-performance liquid chromatography/tandem mass spectrometry (UPLC/MS/MS) optimised for basic species, UPLC/MS/MS optimised for acidic species and gas chromatography/MS (GC/MS). RESULTS: The metabolomic profiles of PD were clearly different from normal controls. PD profiles had significantly lower levels of tryptophan, caffeine and its metabolites, bilirubin and ergothioneine, and significantly higher levels of levodopa metabolites and biliverdin than those of normal controls. Alterations in the bilirubin/biliverdin ratio and ergothioneine can indicate oxidative stress intensity and may suggest elevated oxidative stress and/or insufficient ability for scavenging free radicals, which could contribute to PD pathogenesis. Decreased serum tryptophan level is associated with psychiatric problems in PD. A decrease in serum caffeine levels is consistent with an inverse association of caffeine consumption with development of PD based on past epidemiological studies. CONCLUSIONS: Metabolomic analysis detected biomarkers associated with PD pathogenesis and disease progression. Since critical metabolic biomarkers need to be identified in PD, future studies should include assay validation and replication in independent cohorts.

Molecular chaperone TRAP1 regulates a metabolic switch between mitochondrial respiration and aerobic glycolysis.

TRAP1 (TNF receptor-associated protein), a member of the HSP90 chaperone family, is found predominantly in mitochondria. TRAP1 is broadly considered to be an anticancer molecular target. However, current inhibitors cannot distinguish between HSP90 and TRAP1, making their utility as probes of TRAP1-specific function questionable. Some cancers express less TRAP1 than do their normal tissue counterparts, suggesting that TRAP1 function in mitochondria of normal and transformed cells is more complex than previously appreciated. We have used TRAP1-null cells and transient TRAP1 silencing/overexpression to show that TRAP1 regulates a metabolic switch between oxidative phosphorylation and aerobic glycolysis in immortalized mouse fibroblasts and in human tumor cells. TRAP1-deficiency promotes an increase in mitochondrial respiration and fatty acid oxidation, and in cellular accumulation of tricarboxylic acid cycle intermediates, ATP and reactive oxygen species. At the same time, glucose metabolism is suppressed. TRAP1-deficient cells also display strikingly enhanced invasiveness. TRAP1 interaction with and regulation of mitochondrial c-Src provide a mechanistic basis for these phenotypes. Taken together with the observation that TRAP1 expression is inversely correlated with tumor grade in several cancers, these data suggest that, in some settings, this mitochondrial molecular chaperone may act as a tumor suppressor.