MFSD7c functions as a transporter of choline at the blood-brain barrier.

Mutations in the orphan transporter MFSD7c (also known as Flvcr2), are linked to Fowler syndrome. Here, we used Mfsd7c knockout (Mfsd7c-/-) mice and cell-based assays to reveal that MFSD7c is a choline transporter at the blood-brain barrier (BBB). We performed comprehensive metabolomics analysis and detected differential changes of metabolites in the brains and livers of Mfsd7c-/-embryos. Particularly, we found that choline-related metabolites were altered in the brains but not in the livers of Mfsd7c-/- embryos. Thus, we hypothesized that MFSD7c regulates the level of choline in the brain. Indeed, expression of human MFSD7c in cells significantly increased choline uptake. Interestingly, we showed that choline uptake by MFSD7c is greatly increased by choline-metabolizing enzymes, leading us to demonstrate that MFSD7c is a facilitative transporter of choline. Furthermore, single-cell patch clamp analysis showed that the import of choline by MFSD7c is electrogenic. Choline transport function of MFSD7c was shown to be conserved in vertebrates, but not in yeasts. We demonstrated that human MFSD7c is a functional ortholog of HNM1, the yeast choline importer. We also showed that several missense mutations identified in patients exhibiting Fowler syndrome had abolished or reduced choline transport activity. Mice lacking Mfsd7c in endothelial cells of the central nervous system suppressed the import of exogenous choline from blood but unexpectedly had increased choline levels in the brain. Stable-isotope tracing study revealed that MFSD7c was required for exporting choline derived from lysophosphatidylcholine in the brain. Collectively, our work identifies MFSD7c as a choline exporter at the BBB and provides a foundation for future work to reveal the disease mechanisms of Fowler syndrome.

A reversible state of hypometabolism in a human cellular model of sporadic Parkinson's disease.

Sporadic Parkinson's Disease (sPD) is a progressive neurodegenerative disorder caused by multiple genetic and environmental factors. Mitochondrial dysfunction is one contributing factor, but its role at different stages of disease progression is not fully understood. Here, we showed that neural precursor cells and dopaminergic neurons derived from induced pluripotent stem cells (hiPSCs) from sPD patients exhibited a hypometabolism. Further analysis based on transcriptomics, proteomics, and metabolomics identified the citric acid cycle, specifically the α-ketoglutarate dehydrogenase complex (OGDHC), as bottleneck in sPD metabolism. A follow-up study of the patients approximately 10 years after initial biopsy demonstrated a correlation between OGDHC activity in our cellular model and the disease progression. In addition, the alterations in cellular metabolism observed in our cellular model were restored by interfering with the enhanced SHH signal transduction in sPD. Thus, inhibiting overactive SHH signaling may have potential as neuroprotective therapy during early stages of sPD.

Fecal Bile Acids and Neutral Sterols Are Associated with Latent Microbial Subgroups in the Human Gut.

Bile acids, neutral sterols, and the gut microbiome are intricately intertwined and each affects human health and metabolism. However, much is still unknown about this relationship. This analysis included 1280 participants of the KORA FF4 study. Fecal metabolites (primary and secondary bile acids, plant and animal sterols) were analyzed using a metabolomics approach. Dirichlet regression models were used to evaluate associations between the metabolites and twenty microbial subgroups that were previously identified using latent Dirichlet allocation. Significant associations were identified between 12 of 17 primary and secondary bile acids and several of the microbial subgroups. Three subgroups showed largely positive significant associations with bile acids, and six subgroups showed mostly inverse associations with fecal bile acids. We identified a trend where microbial subgroups that were previously associated with "healthy" factors were here inversely associated with fecal bile acid levels. Conversely, subgroups that were previously associated with "unhealthy" factors were positively associated with fecal bile acid levels. These results indicate that further research is necessary regarding bile acids and microbiota composition, particularly in relation to metabolic health.

Effects of Acute and Chronic Resistance Exercise on the Skeletal Muscle Metabolome.

Resistance training promotes metabolic health and stimulates muscle hypertrophy, but the precise routes by which resistance exercise (RE) conveys these health benefits are largely unknown. AIM: To investigate how acute RE affects human skeletal muscle metabolism. METHODS: We collected vastus lateralis biopsies from six healthy male untrained volunteers at rest, before the first of 13 RE training sessions, and 45 min after the first and last bouts of RE. Biopsies were analysed using untargeted mass spectrometry-based metabolomics. RESULTS: We measured 617 metabolites covering a broad range of metabolic pathways. In the untrained state RE altered 33 metabolites, including increased 3-methylhistidine and N-lactoylvaline, suggesting increased protein breakdown, as well as metabolites linked to ATP (xanthosine) and NAD (N1-methyl-2-pyridone-5-carboxamide) metabolism; the bile acid chenodeoxycholate also increased in response to RE in muscle opposing previous findings in blood. Resistance training led to muscle hypertrophy, with slow type I and fast/intermediate type II muscle fibre diameter increasing by 10.7% and 10.4%, respectively. Comparison of post-exercise metabolite levels between trained and untrained state revealed alterations of 46 metabolites, including decreased N-acetylated ketogenic amino acids and increased beta-citrylglutamate which might support growth. Only five of the metabolites that changed after acute exercise in the untrained state were altered after chronic training, indicating that training induces multiple metabolic changes not directly related to the acute exercise response. CONCLUSION: The human skeletal muscle metabolome is sensitive towards acute RE in the trained and untrained states and reflects a broad range of adaptive processes in response to repeated stimulation.

Untargeted and Targeted Circadian Metabolomics Using Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) and Flow Injection-Electrospray Ionization-Tandem Mass Spectrometry (FIA-ESI-MS/MS).

A diverse array of 24-h oscillating hormones and metabolites direct and reflect circadian clock function. Circadian metabolomics uses advanced high-throughput analytical chemistry techniques to comprehensively profile these small molecules (<1.5 kDa) across 24 h in cells, media, body fluids, breath, tissues, and subcellular compartments. The goals of circadian metabolomics experiments are often multifaceted. These include identifying and tracking rhythmic metabolic inputs and outputs of central and peripheral circadian clocks, quantifying endogenous free-running period, monitoring relative phase alignment between clocks, and mapping pathophysiological consequences of clock disruption or misalignment. Depending on the particular experimental question, samples are collected under free-running or entrained conditions. Here we describe both untargeted and targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) and flow injection-electrospray ionization-tandem mass spectrometry (FIA-ESI-MS/MS) based assays we have used for circadian metabolomics studies. We discuss tissue homogenization, chemical derivatization, measurement, and tips for data processing, normalization, scaling, how to handle outliers, and imputation of missing values.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired ß cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Non-targeted metabolomics identify polyamine metabolite acisoga as novel biomarker for reduced left ventricular function.

AIMS: Chronic heart failure with reduced ejection fraction remains a major health issue. To date, no reliable biomarker is available to predict reduced left ventricular ejection fraction (LV-EF). We aimed to identify novel circulating biomarkers for reduced left ventricular function using untargeted serum metabolomics in two independent patient cohorts. METHODS AND RESULTS: Echocardiography and non-targeted serum metabolomics were conducted in two patient cohorts with varying left ventricular function: (1) 25 patients with type 2 diabetes with established cardiovascular disease or high cardiovascular risk (LV-EF range 20-66%) (discovery cohort) and (2) 37 patients hospitalized for myocardial infarction (LV-EF range 25-60%) (validation cohort). In the discovery cohort, untargeted metabolomics revealed seven metabolites performing better than N-terminal pro-B-type natriuretic peptide in the prediction of impaired left ventricular function shown by LV-EF. For only one of the metabolites, acisoga, the predictive value for LV-EF could be confirmed in the validation cohort (r = -0.37, P = 0.02). In the discovery cohort, acisoga did not only correlate with LV-EF (r = -60, P = 0.0016), but also with global circumferential strain (r = 0.67, P = 0.0003) and global longitudinal strain (r = 0.68, P = 0.0002). Similar results could be detected in the discovery cohort in a 6 month follow-up proofing stability of these results over time. With an area under the curve of 0.86 in the receiver operating characteristic analysis, acisoga discriminated between patients with normal EF and LV-EF < 40%. Multivariate analysis exposed acisoga as independent marker for impairment of LV-EF (Beta = -0.71, P = 0.004). CONCLUSIONS: We found the polyamine metabolite acisoga to be elevated in patients with impaired LV-EF in two independent cohorts. Our analyses suggest that acisoga may be a valuable biomarker to detect patients with heart failure with reduced ejection fraction.

Common Muscle Metabolic Signatures Highlight Arginine and Lysine Metabolism as Potential Therapeutic Targets to Combat Unhealthy Aging.

Biological aging research is expected to reveal modifiable molecular mechanisms that can be harnessed to slow or possibly reverse unhealthy trajectories. However, there is first an urgent need to define consensus molecular markers of healthy and unhealthy aging. Established aging hallmarks are all linked to metabolism, and a 'rewired' metabolic circuitry has been shown to accelerate or delay biological aging. To identify metabolic signatures distinguishing healthy from unhealthy aging trajectories, we performed nontargeted metabolomics on skeletal muscles from 2-month-old and 21-month-old mice, and after dietary and lifestyle interventions known to impact biological aging. We hypothesized that common metabolic signatures would highlight specific pathways and processes promoting healthy aging, while revealing the molecular underpinnings of unhealthy aging. Here, we report 50 metabolites that commonly distinguished aging trajectories in all cohorts, including 18 commonly reduced under unhealthy aging and 32 increased. We stratified these metabolites according to known relationships with various aging hallmarks and found the greatest associations with oxidative stress and nutrient sensing. Collectively, our data suggest interventions aimed at maintaining skeletal muscle arginine and lysine may be useful therapeutic strategies to minimize biological aging and maintain skeletal muscle health, function, and regenerative capacity in old age.

Cancer-associated cells release citrate to support tumour metastatic progression.

Citrate is important for lipid synthesis and epigenetic regulation in addition to ATP production. We have previously reported that cancer cells import extracellular citrate via the pmCiC transporter to support their metabolism. Here, we show for the first time that citrate is supplied to cancer by cancer-associated stroma (CAS) and also that citrate synthesis and release is one of the latter's major metabolic tasks. Citrate release from CAS is controlled by cancer cells through cross-cellular communication. The availability of citrate from CAS regulated the cytokine profile, metabolism and features of cellular invasion. Moreover, citrate released by CAS is involved in inducing cancer progression especially enhancing invasiveness and organ colonisation. In line with the in vitro observations, we show that depriving cancer cells of citrate using gluconate, a specific inhibitor of pmCiC, significantly reduced the growth and metastatic spread of human pancreatic cancer cells in vivo and muted stromal activation and angiogenesis. We conclude that citrate is supplied to tumour cells by CAS and citrate uptake plays a significant role in cancer metastatic progression.

Combination therapies induce cancer cell death through the integrated stress response and disturbed pyrimidine metabolism.

By accentuating drug efficacy and impeding resistance mechanisms, combinatorial, multi-agent therapies have emerged as key approaches in the treatment of complex diseases, most notably cancer. Using high-throughput drug screens, we uncovered distinct metabolic vulnerabilities and thereby identified drug combinations synergistically causing a starvation-like lethal catabolic response in tumor cells from different cancer entities. Domperidone, a dopamine receptor antagonist, as well as several tricyclic antidepressants (TCAs), including imipramine, induced cancer cell death in combination with the mitochondrial uncoupler niclosamide ethanolamine (NEN) through activation of the integrated stress response pathway and the catabolic CLEAR network. Using transcriptome and metabolome analyses, we characterized a combinatorial response, mainly driven by the transcription factors CHOP and TFE3, which resulted in cell death through enhanced pyrimidine catabolism as well as reduced pyrimidine synthesis. Remarkably, the drug combinations sensitized human organoid cultures to the standard-of-care chemotherapy paclitaxel. Thus, our combinatorial approach could be clinically implemented into established treatment regimen, which would be further facilitated by the advantages of drug repurposing.

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

BACKGROUND: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. METHODS: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. RESULTS: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. CONCLUSIONS: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Blood Metabolomic Profiling Confirms and Identifies Biomarkers of Food Intake.

Metabolomics can be a tool to identify dietary biomarkers. However, reported food-metabolite associations have been inconsistent, and there is a need to explore further associations. Our aims were to confirm previously reported food-metabolite associations and to identify novel food-metabolite associations. We conducted a cross-sectional analysis of data from 849 participants (57% men) of the PopGen cohort. Dietary intake was obtained using FFQ and serum metabolites were profiled by an untargeted metabolomics approach. We conducted a systematic literature search to identify previously reported food-metabolite associations and analyzed these associations using linear regression. To identify potential novel food-metabolite associations, datasets were split into training and test datasets and linear regression models were fitted to the training datasets. Significant food-metabolite associations were evaluated in the test datasets. Models were adjusted for covariates. In the literature, we identified 82 food-metabolite associations. Of these, 44 associations were testable in our data and confirmed associations of coffee with 12 metabolites, of fish with five, of chocolate with two, of alcohol with four, and of butter, poultry and wine with one metabolite each. We did not identify novel food-metabolite associations; however, some associations were sex-specific. Potential use of some metabolites as biomarkers should consider sex differences in metabolism.

Circulating Metabolites Differentiate Acute Ischemic Stroke from Stroke Mimics.

OBJECTIVE: Early discrimination of patients with ischemic stroke (IS) from stroke mimics (SMs) poses a diagnostic challenge. The circulating metabolome might reflect pathophysiological events related to acute IS. Here, we investigated the utility of early metabolic changes for differentiating IS from SM. METHODS: We performed untargeted metabolomics on serum samples obtained from patients with IS (N = 508) and SM (N = 349; defined by absence of a diffusion weighted imaging [DWI] positive lesion on magnetic resonance imaging [MRI]) who presented to the hospital within 24 hours after symptom onset (median time from symptom onset to blood sampling = 3.3 hours; interquartile range [IQR] = 1.6-6.7 hours) and from neurologically normal controls (NCs; N = 112). We compared diagnostic groups in a discovery-validation approach by applying multivariable linear regression models, machine learning techniques, and propensity score matching. We further performed a targeted look-up of published metabolite sets. RESULTS: Levels of 41 metabolites were significantly associated with IS compared to NCs. The top metabolites showing the highest value in separating IS from SMs were asymmetrical and symmetrical dimethylarginine, pregnenolone sulfate, and adenosine. Together, these 4 metabolites differentiated patients with IS from SMs with an area under the curve (AUC) of 0.90 in the replication sample, which was superior to multimodal cranial computed tomography (CT; AUC = 0.80) obtained for routine diagnostics. They were further superior to previously published metabolite sets detected in our samples. All 4 metabolites returned to control levels by day 90. INTERPRETATION: A set of 4 metabolites with known biological effects relevant to stroke pathophysiology shows unprecedented utility to identify patients with IS upon hospital arrival, thus encouraging further investigation, including multicenter studies. ANN NEUROL 2020;88:736-746.

Empagliflozin improves left ventricular diastolic function of db/db mice.

OBJECTIVES: Investigation of the effect of SGLT2 inhibition by empagliflozin on left ventricular function in a model of diabetic cardiomyopathy. BACKGROUND: SGLT2 inhibition is a new strategy to treat diabetes. In the EMPA-REG Outcome trial empagliflozin treatment reduced cardiovascular and overall mortality in patients with diabetes presumably due to beneficial cardiac effects, leading to reduced heart failure hospitalization. The relevant mechanisms remain currently elusive but might be mediated by a shift in cardiac substrate utilization leading to improved energetic supply to the heart. METHODS: We used db/db mice on high-fat western diet with or without empagliflozin treatment as a model of severe diabetes. Left ventricular function was assessed by pressure catheter with or without dobutamine stress. RESULTS: Treatment with empagliflozin significantly increased glycosuria, improved glucose metabolism, ameliorated left ventricular diastolic function and reduced mortality of mice. This was associated with reduced cardiac glucose concentrations and decreased calcium/calmodulin-dependent protein kinase (CaMKII) activation with subsequent less phosphorylation of the ryanodine receptor (RyR). No change of cardiac ketone bodies or branched-chain amino acid (BCAA) metabolites in serum was detected nor was cardiac expression of relevant catabolic enzymes for these substrates affected. CONCLUSIONS: In a murine model of severe diabetes empagliflozin-dependent SGLT2 inhibition improved diastolic function and reduced mortality. Improvement of diastolic function was likely mediated by reduced spontaneous diastolic sarcoplasmic reticulum (SR) calcium release but independent of changes in cardiac ketone and BCAA metabolism.

Cross-omics analysis revealed gut microbiome-related metabolic pathways underlying atherosclerosis development after antibiotics treatment.

OBJECTIVE: The metabolic influence of gut microbiota plays a pivotal role in the pathogenesis of cardiometabolic diseases. Antibiotics affect intestinal bacterial diversity, and long-term usage has been identified as an independent risk factor for atherosclerosis-driven events. The aim of this study was to explore the interaction between gut dysbiosis by antibiotics and metabolic pathways with the impact on atherosclerosis development. METHODS: We combined oral antibiotics with different diets in an Apolipoprotein E-knockout mouse model linking gut microbiota to atherosclerotic lesion development via an integrative cross-omics approach including serum metabolomics and cecal 16S rRNA targeted metagenomic sequencing. We further investigated patients with carotid atherosclerosis compared to control subjects with comparable cardiovascular risk. RESULTS: Here, we show that increased atherosclerosis by antibiotics was connected to a loss of intestinal diversity and alterations of microbial metabolic functional capacity with a major impact on the host serum metabolome. Pathways that were modulated by antibiotics and connected to atherosclerosis included diminished tryptophan and disturbed lipid metabolism. These pathways were related to the reduction of certain members of Bacteroidetes and Clostridia by antibiotics in the gut. Patients with atherosclerosis presented a similar metabolic signature as those induced by antibiotics in our mouse model. CONCLUSION: Taken together, this work provides insights into the complex interaction between intestinal microbiota and host metabolism. Our data highlight that detrimental effects of antibiotics on the gut flora are connected to a pro-atherogenic metabolic phenotype beyond classical risk factors.

Trans-right ventricle and transpulmonary metabolite gradients in human pulmonary arterial hypertension.

OBJECTIVE: While metabolic dysfunction occurs in several pulmonary arterial hypertension (PAH) animal models, its role in the human hypertensive right ventricle (RV) and lung is not well characterised. We investigated whether circulating metabolite concentrations differ across the hypertensive RV and/or the pulmonary circulation, and correlate with invasive haemodynamic/echocardiographic variables in patients with PAH. METHODS: Prospective EDTA blood collection during cardiac catheterisation from the superior vena cava (SVC), pulmonary artery (PA) and ascending aorta (AAO) in children with PAH (no shunt) and non-PAH controls (Con), followed by unbiased screens of 427 metabolites and 836 lipid species and fatty acids (FAs) in blood plasma (Metabolon and Lipidyzer platforms). Metabolite concentrations were correlated with echocardiographic and invasive haemodynamic variables. RESULTS: Metabolomics/lipidomics analysis of differential concentrations (false discovery rate<0.15) revealed several metabolite gradients in the trans-RV (PA vs SVC) setting. Notably, dicarboxylic acids (eg, octadecanedioate: fold change (FC)_Control=0.77, FC_PAH=1.09, p value=0.044) and acylcarnitines (eg, stearoylcarnitine: FC_Control=0.74, FC_PAH=1.21, p value=0.058). Differentially regulated metabolites were also found in the transpulmonary (AAO vs PA) setting and between-group comparisons, that is, in the SVC (PAH-SVC vs Con-SVC), PA and AAO. Importantly, the differential PAH-metabolite concentrations correlated with numerous outcome-relevant variables (e.g., tricuspid annular plane systolic excursion, pulmonary vascular resistance). CONCLUSIONS: In PAH, trans-RV and transpulmonary metabolite gradients exist and correlate with haemodynamic determinants of clinical outcome. The most pronounced differential trans-RV gradients are known to be involved in lipid metabolism/lipotoxicity, that is, accumulation of long chain FAs. The identified accumulation of dicarboxylic acids and acylcarnitines likely indicates impaired ß-oxidation in the hypertensive RV and represents emerging biomarkers and therapeutic targets in PAH.

Associations between adipose tissue volume and small molecules in plasma and urine among asymptomatic subjects from the general population.

Obesity is one of the major risk factor for cardiovascular and metabolic diseases. A disproportional accumulation of fat at visceral (VAT) compared to subcutaneous sites (SAT) has been suspected as a key detrimental event. We used non-targeted metabolomics profiling to reveal metabolic pathways associated with higher VAT or SAT amount among subjects free of metabolic diseases to identify possible contributing metabolic pathways. The study population comprised 491 subjects [mean (standard deviation): age 44.6 yrs (13.0), body mass index 25.4 kg/m² (3.6), 60.1% females] without diabetes, hypertension, dyslipidemia, the metabolic syndrome or impaired renal function. We associated MRI-derived fat amounts with mass spectrometry-derived metabolites in plasma and urine using linear regression models adjusting for major confounders. We tested for sex-specific effects using interactions terms and performed sensitivity analyses for the influence of insulin resistance on the results. VAT and SAT were significantly associated with 155 (101 urine) and 49 (29 urine) metabolites, respectively, of which 45 (27 urine) were common to both. Major metabolic pathways were branched-chain amino acid metabolism (partially independent of insulin resistance), surrogate markers of oxidative stress and gut microbial diversity, and cortisol metabolism. We observed a novel positive association between VAT and plasma levels of the potential pharmacological agent piperine. Sex-specific effects were only a few, e.g. the female-specific association between VAT and O-methylascorbate. In brief, higher VAT was associated with an unfavorable metabolite profile in a sample of healthy, mostly non-obese individuals from the general population and only few sex-specific associations became apparent.

A Thyroid Hormone-Independent Molecular Fingerprint of 3,5-Diiodothyronine Suggests a Strong Relationship with Coffee Metabolism in Humans.

Background: In numerous studies based predominantly on rodent models, administration of 3,5-diiodo-L-thyronine (3,5-T2), a metabolite of the thyroid hormones (TH) thyroxine (T4) and triiodo-L-thyronine (T3), was reported to cause beneficial health effects, including reversal of steatohepatosis and prevention of insulin resistance, in most instances without adverse thyrotoxic side effects. However, the empirical evidence concerning the physiological relevance of endogenously produced 3,5-T2 in humans is comparatively poor. Therefore, to improve the understanding of 3,5-T2-related metabolic processes, we performed a comprehensive metabolomic study relating serum 3,5-T2 concentrations to plasma and urine metabolite levels within a large general population sample. Methods: Serum 3,5-T2 concentrations were determined for 856 participants of the population-based Study of Health in Pomerania-TREND (SHIP-TREND). Plasma and urine metabolome data were generated using mass spectrometry and nuclear magnetic resonance spectroscopy, allowing quantification of 613 and 578 metabolites in plasma and urine, respectively. To detect thyroid function-independent significant 3,5-T2-metabolite associations, linear regression analyses controlling for major confounders, including thyrotropin and free T4, were performed. The same analyses were carried out using a sample of 16 male healthy volunteers treated for 8 weeks with 250 µg/day levothyroxine to induce thyrotoxicosis. Results: The specific molecular fingerprint of 3,5-T2 comprised 15 and 73 significantly associated metabolites in plasma and urine, respectively. Serum 3,5-T2 concentrations were neither associated with classical thyroid function parameters nor altered during experimental thyrotoxicosis. Strikingly, many metabolites related to coffee metabolism, including caffeine and paraxanthine, formed the clearest positively associated molecular signature. Importantly, these associations were replicated in the experimental human thyrotoxicosis model. Conclusion: The molecular fingerprint of 3,5-T2 demonstrates a clear and strong positive association of the serum levels of this TH metabolite with plasma levels of compounds indicating coffee consumption, therefore pointing to the liver as an organ, the metabolism of which is strongly affected by coffee. Furthermore, 3,5-T2 serum concentrations were found not to be directly TH dependent. Considering the beneficial health effects of 3,5-T2 administration observed in animal models and those of coffee consumption demonstrated in large epidemiological studies, one might speculate that coffee-stimulated hepatic 3,5-T2 production or accumulation represents an important molecular link in this connection.

Plasma Metabolomics to Identify and Stratify Patients With Impaired Glucose Tolerance.

OBJECTIVE: Impaired glucose tolerance (IGT) is one of the presymptomatic states of type 2 diabetes mellitus and requires an oral glucose tolerance test (OGTT) for diagnosis. Our aims were twofold: (i) characterize signatures of small molecules predicting the OGTT response and (ii) identify metabolic subgroups of participants with IGT. METHODS: Plasma samples from 827 participants of the Study of Health in Pomerania free of diabetes were measured using mass spectrometry and proton-nuclear magnetic resonance spectroscopy. Linear regression analyses were used to screen for metabolites significantly associated with the OGTT response after 2 hours, adjusting for baseline glucose and insulin levels as well as important confounders. A signature predictive for IGT was established using regularized logistic regression. All cases with IGT (N = 159) were selected and subjected to unsupervised clustering using a k-means approach. RESULTS AND CONCLUSION: In total, 99 metabolites and 22 lipoprotein measures were significantly associated with either 2-hour glucose or 2-hour insulin levels. Those comprised variations in baseline concentrations of branched-chain amino ketoacids, acylcarnitines, lysophospholipids, or phosphatidylcholines, largely confirming previous studies. By the use of these metabolites, subjects with IGT segregated into two distinct groups. Our IGT prediction model combining both clinical and metabolomics traits achieved an area under the curve of 0.84, slightly improving the prediction based on established clinical measures. The present metabolomics approach revealed molecular signatures associated directly to the response of the OGTT and to IGT in line with previous studies. However, clustering of subjects with IGT revealed distinct metabolic signatures of otherwise similar individuals, pointing toward the possibility of metabolomics for patient stratification.