Metabonomic study of biochemical changes in urinary of type 2 diabetes mellitus patients after the treatment of sulfonylurea antidiabetic drugs based on ultra-performance liquid chromatography/mass spectrometry: Metabonomic study of T2DM patient after the treatment of sulfonylurea

Pioglitazone-induced alterations of purine metabolism in healthy male subjects

Pioglitazone is class of thiazolidinediones that activates peroxisome proliferator-activated receptors (PPARs) in adipocytes to improve glucose metabolism and insulin sensitivity and has been used as a treatment for type 2 diabetes. However, the underlying mechanisms of associated pioglitazone-induced effects remain unclear. Our study aimed to investigate endogenous metabolite alterations associated with pioglitazone administration in healthy male subjects using an untargeted metabolomics approach. All subjects received 30 mg of pioglitazone once daily in the assigned sequence and period. Urine samples were collected before pioglitazone administration and for 24 h after 7 days of administration. A total of 1465 compounds were detected and filtered using a coefficient of variance below 30% and 108 metabolites were significantly altered upon pioglitazone administration via multivariate statistical analysis. Fourteen significant metabolites were identified using authentic standards and public libraries. Additionally, pathway analysis revealed that metabolites from purine and beta-alanine metabolisms were significantly altered after pioglitazone administration. Further analysis of quantification of metabolites from purine metabolism, revealed that the xanthine/hypoxanthine and uric acid/xanthine ratios were significantly decreased at post-dose. Pioglitazone-dependent endogenous metabolites and metabolic ratio indicated the potential effect of pioglitazone on the activation of PPAR and fatty acid synthesis. Additional studies involving patients are required to validate these findings.

Abnormal tryptophan catabolism in diabetes mellitus and its complications: Opportunities and challenges

In recent years, the incidence rate of diabetes mellitus (DM), including type 1 diabetes mellitus(T1DM), type 2 diabetes mellitus(T2DM), and gestational diabetes mellitus (GDM), has increased year by year and has become a major global health problem. DM can lead to serious complications of macrovascular and microvascular. Tryptophan (Trp) is an essential amino acid for the human body. Trp is metabolized in the body through the indole pathway, kynurenine (Kyn) pathway and serotonin (5-HT) pathway, and is regulated by intestinal microorganisms to varying degrees. These three metabolic pathways have extensive regulatory effects on the immune, endocrine, neural, and energy metabolism systems of the body, and are related to the physiological and pathological processes of various diseases. The key enzymes and metabolites in the Trp metabolic pathway are also deeply involved in the pathogenesis of DM, playing an important role in pancreatic function, insulin resistance (IR), intestinal barrier, and angiogenesis. In DM and its complications, there is a disruption of Trp metabolic balance. Several therapy approaches for DM and complications have been proven to modify tryptophan metabolism. The metabolism of Trp is becoming a new area of focus for DM prevention and care. This paper reviews the impact of the three metabolic pathways of Trp on the pathogenesis of DM and the alterations in Trp metabolism in these diseases, expecting to provide entry points for the treatment of DM and its complications.

Small molecule modulation of microbiota: a systems pharmacology perspective

BACKGROUND

Microbes are associated with many human diseases and influence drug efficacy. Small-molecule drugs may revolutionize biomedicine by fine-tuning the microbiota on the basis of individual patient microbiome signatures. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional "one-drug-one-target-one-disease" process. A systematic pharmacology approach that would suppress multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution.

RESULTS

We construct a disease-centric signed microbe-microbe interaction network using curated microbe metabolite information and their effects on host. We develop a Signed Random Walk with Restart algorithm for the accurate prediction of effect of microbes on human health and diseases. With a survey on the druggable and evolutionary space of microbe proteins, we find that 8-10% of them can be targeted by existing drugs or drug-like chemicals and that 25% of them have homologs to human proteins. We demonstrate that drugs for diabetes can be the lead compounds for development of microbiota-targeted therapeutics. We further show that the potential drug targets that specifically exist in pathogenic microbes are periplasmic and cellular outer membrane proteins.

CONCLUSION

The systematic studies of the polypharmacological landscape of the microbiome network may open a new avenue for the small-molecule drug discovery of the microbiome. We believe that the application of systematic method on the polypharmacological investigation could lead to the discovery of novel drug therapies.

Gut Microbiota and Antidiabetic Drugs: Perspectives of Personalized Treatment in Type 2 Diabetes Mellitus

Alterations in the composition and function of the gut microbiota have been reported in patients with type 2 diabetes mellitus (T2DM). Emerging studies show that prescribed antidiabetic drugs distort the gut microbiota signature associated with T2DM. Even more importantly, accumulated evidence provides support for the notion that gut microbiota, in turn, mediates the efficacy and safety of antidiabetic drugs. In this review, we highlight the current state-of-the-art knowledge on the crosstalk and interactions between gut microbiota and antidiabetic drugs, including metformin, α-glucosidase inhibitors, glucagon-like peptide-1 receptor agonists, dipeptidyl peptidase-4 inhibitors, sodium-glucose cotransporter 2 inhibitors, traditional Chinese medicines and other antidiabetic drugs, as well as address corresponding microbial-based therapeutics, aiming to provide novel preventative strategies and personalized therapeutic targets in T2DM.

Untargeted metabolomics analysis of the anti-diabetic effect of Red ginseng extract in Type 2 diabetes Mellitus rats based on UHPLC-MS/MS

Red ginseng is a traditional Chinese herbal medicine that has long been used to treat diabetes, and its blood sugar-lowering activity has been confirmed. However, the mechanism of action of red ginseng on type 2 diabetes mellitus (T2DM) at the metabolic level is still unclear. The purpose of this study is to investigate the effect of red ginseng extract in the treatment of T2DM rats based on untargeted metabolomics. The rat model of T2DM was induced by a high-fat diet (HFD) combined with streptozotocin (STZ), and serum samples were collected after four weeks of treatment. The ultra-high-performance liquid chromatography coupled with Q Exactive HF-X Mass Spectrometer was used to analyze the level of metabolites in serum to evaluate the differences in metabolic levels between different groups. The results of biochemical analysis showed that red ginseng extract intervention significantly improved the levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), serum glucose (GLU), and fasting insulin (FINS) after four weeks. Orthogonal partial least squares discriminant analysis was used to study the overall changes of rat metabolomics. After the intervention of red ginseng extract, 50 biomarkers showed a callback trend. Metabolic pathway enrichment analysis showed that the regulated pathways were D-arginine and D-ornithine metabolism, D-glutamine and D-glutamate metabolism, taurine and hypotaurine metabolism, arginine biosynthesis, and tryptophan metabolism. Generally, the results demonstrated that red ginseng extract had beneficial effects on T2DM, which could be mediated via ameliorating the metabolic disorders.

Metabolomics analysis of stool in rats with type 2 diabetes mellitus after single-anastomosis duodenal-ileal bypass with sleeve gastrectomy

BACKGROUND

Single-anastomosis duodenal-ileal bypass with sleeve gastrectomy (SADI-S) is one of the most effective bariatric procedures in the treatment of type 2 diabetes mellitus (T2DM). However, the mechanisms by which SADI-S improves T2DM are not well-known.

OBJECTIVE

To explore the effects of SADI-S on metabolites in the stool of rats with T2DM.

METHODS

Twenty rats were fed on high-fat diet and administered with a low-dose (30mg/kg) of streptozotocin to establish T2DM models. The rats were then randomly assigned to the SADI-S group (n=10) and sham operation group (n=9). Stool samples were collected from all rats at 8 weeks after surgery and stored at -80 °C. Metabolomics analysis was performed to identify differential metabolites through ultra- performance liquid chromatography-mass spectrometry.

RESULTS

At 8-week after surgery, rats of the SADI-S group showed significantly decreased fasting blood glucose, glucose tolerance test 2-hour, glycated haemoglobin, and body weight compared with those of the sham group. A total of 245 differential metabolites were identified between the two groups. Among them, 16 metabolites such as branched-chain amino acids (valine), aromatic amino acid (phenylalanine), bile acid (cholic acid, lithocholic acid, and β-muricholic acid), short-chain fatty acid (isobutyric acid), and phospholipid [lysoPE(17:0), lysoPE(20:3) and lysoPS(16:0)] were associated to the T2DM remission after SADI-S.

CONCLUSION

SADI-S improves T2DM in rats by regulating phenylalanine biosynthesis, valine, phenylalanine, alanine, glutamate, proline, bile acid, and phospholipid metabolism pathways.

Effects of Oral Glucose-Lowering Agents on Gut Microbiota and Microbial Metabolites

The current research and existing facts indicate that type 2 diabetes mellitus (T2DM) is characterized by gut microbiota dysbiosis and disturbed microbial metabolites. Oral glucose-lowering drugs are reported with pleiotropic beneficial effects, including not only a decrease in glucose level but also weight loss, antihypertension, anti-inflammation, and cardiovascular protection, but the underlying mechanisms are still not clear. Evidence can be found showing that oral glucose-lowering drugs might modify the gut microbiome and thereby alter gastrointestinal metabolites to improve host health. Although the connections among gut microbial communities, microbial metabolites, and T2DM are complex, figuring out how antidiabetic agents shape the gut microbiome is vital for optimizing the treatment, meaningful for the instruction for probiotic therapy and gut microbiota transplantation in T2DM. In this review, we focused on the literatures in gut microbiota and its metabolite profile alterations beneficial from oral antidiabetic drugs, trying to provide implications for future study in the developing field of these drugs, such as combination therapies, pre- and probiotics intervention in T2DM, and subjects with pregestational diabetes and gestational diabetes mellitus.

Changes in the gut microbiome influence the hypoglycemic effect of metformin through the altered metabolism of branched-chain and nonessential amino acids

AIMS

Although metformin has been reported to affect the gut microbiome, the mechanism has not been fully determined. We explained the potential underlying mechanisms of metformin through a multiomics approach.

METHODS

An open-label and single-arm clinical trial involving 20 healthy Korean was conducted. Serum glucose and insulin concentrations were measured, and stool samples were collected to analyze the microbiome. Untargeted metabolomic profiling of plasma, urine, and stool samples was performed by GC-TOF-MS. Network analysis was applied to infer the mechanism of the hypoglycemic effect of metformin.

RESULTS

The relative abundances of Escherichia, Romboutsia, Intestinibacter, and Clostridium were changed by metformin treatment. Additionally, the relative abundances of metabolites, including carbohydrates, amino acids, and fatty acids, were changed. These changes were correlated with energy metabolism, gluconeogenesis, and branched-chain amino acid metabolism, which are major metabolic pathways related to the hypoglycemic effect.

CONCLUSIONS

We observed that specific changes in metabolites may affect hypoglycemic effects through both pathways related to AMPK activation and microbial changes. Energy metabolism was mainly related to hypoglycemic effects. In particular, branched-chain amino acid metabolism and gluconeogenesis were related to microbial metabolites. Our results will help uncover the potential underlying mechanisms of metformin through AMPK and the microbiome.

Effect of Dapagliflozin on Urine Metabolome in Patients with Type 2 Diabetes

CONTEXT

Inhibitors of sodium-glucose cotransporters-2 have cardio- and renoprotective properties. However, the underlying mechanisms remain indeterminate.

OBJECTIVE

To evaluate the effect of dapagliflozin on renal metabolism assessed by urine metabolome analysis in patients with type 2 diabetes.

DESIGN

Prospective cohort study.

SETTING

Outpatient diabetes clinic of a tertiary academic center.

PATIENTS

Eighty patients with hemoglobin A1c > 7% on metformin monotherapy were prospectively enrolled.

INTERVENTION

Fifty patients were treated with dapagliflozin for 3 months. To exclude that the changes observed in urine metabolome were merely the result of the improvement in glycemia, 30 patients treated with insulin degludec were used for comparison.

MAIN OUTCOME MEASURE

Changes in urine metabolic profile before and after the administration of dapagliflozin and insulin degludec were assessed by proton-nuclear magnetic resonance spectroscopy.

RESULTS

In multivariate analysis urine metabolome was significantly altered by dapagliflozin (R2X = 0.819, R2Y = 0.627, Q2Y = 0.362, and coefficient of variation analysis of variance, P < 0.001) but not insulin. After dapagliflozin, the urine concentrations of ketone bodies, lactate, branched chain amino acids (P < 0.001), betaine, myo-inositol (P < 0001), and N-methylhydantoin (P < 0.005) were significantly increased. Additionally, the urine levels of alanine, creatine, sarcosine, and citrate were also increased (P < 0001, P <0.0001, and P <0.0005, respectively) whereas anserine decreased (P < 0005).

CONCLUSIONS

Dapagliflozin significantly affects urine metabolome in patients with type 2 diabetes in a glucose lowering-independent way. Most of the observed changes can be considered beneficial and may contribute to the renoprotective properties of dapagliflozin.

Applying metabolomics to veterinary pharmacology and therapeutics

Metabolomics is the large-scale study of low-molecular-weight substances in a biological system in a given physiological state at a given time point. Metabolomics can be applied to identify predictors of inter-individual variability in drug response, provide clinicians with data useful for decision-making processes in drug selection, and inform about the pharmacokinetics and pharmacodynamics of a drug. It is, therefore, an exceptional approach for gaining new understanding effects in the field of comparative veterinary pharmacology. However, the incorporation of metabolomics into veterinary pharmacology and toxicology is not yet widespread, and this is probably, at least in part, a result of its highly multidisciplinary nature. This article reviews the potential applications of metabolomics in veterinary pharmacology and therapeutics. It integrates key concepts for designing metabolomics studies and analyzing and interpreting metabolomics data, providing solid foundations for applying metabolomics to the study of drugs in all veterinary species.

Network pharmacology and metabolomics study on the intervention of traditional Chinese medicine Huanglian Decoction in rats with type 2 diabetes mellitus

ETHNOPHARMACOLOGICAL RELEVANCE

Type 2 diabetes mellitus (T2DM) is currently one of the most prominent and global chronic conditions. Huanglian Decoction (HLD) is a traditional Chinese medicine (TCM) preparation that has been used to treat T2DM for thousands of years in China. However, its mechanism of action at the metabolic level is still unclear. The purpose of this work is to study the mechanism of HLD in treating T2DM based on metabolomics and network pharmacology.

MATERIALS AND METHODS

In this study, metabolomics combined with network pharmacology was used to elucidate the therapeutic mechanism of HLD in T2DM. Serum samples were collected from rats with T2DM, induced by a high-sugar and high-fat diet combined with streptozotocin (STZ), to measure the levels of biochemical markers. Urinary metabolomics-based analysis using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) was conducted to evaluate the differential metabolites from multiple metabolic pathways.

RESULTS

After treatment with HLD for 4 weeks, biochemical indicators, including fasting blood glucose (FBG), blood lipid, fasting insulin (FINS), insulin sensitivity index (ISI), and homeostasis model assessment of insulin resistance (HOMA-IR), were significantly improved. Metabolomics results revealed that HLD regulated the biomarkers, such as cytosine, L-carnitine, betaine, phenylalanine, glucose, citrate, phenylpyruvate, and hippuric acid in glyoxylate and dicarboxylate metabolism, phenylalanine metabolism, and tricarboxylic acid (TCA) cycle. The combination of network pharmacology, metabolomics, western blot, and PCR showed that HLD can treat T2DM by enhancing the gene and protein expression levels of glucose transporter 4 (GLUT4), insulin receptor (INSR), and mitogen-activated protein kinase 1 (MAPK1) to interfere with glyoxylate and dicarboxylate metabolism.

CONCLUSIONS

The study based on metabolomics and network pharmacology indicated that HLD can improve T2DM through multiple targets and pathways, and it may be a useful alternative therapy for the treatment of T2DM.

Additional Effect of Dietary Fiber in Patients with Type 2 Diabetes Mellitus Using Metformin and Sulfonylurea: An Open-Label, Pilot Trial

BACKGROUND

Metformin, sulfonylurea, and dietary fiber are known to affect gut microbiota in patients with type 2 diabetes mellitus (T2DM). This open and single-arm pilot trial investigated the effects of the additional use of fiber on glycemic parameters, insulin, incretins, and microbiota in patients with T2DM who had been treated with metformin and sulfonylurea.

METHODS

Participants took fiber for 4 weeks and stopped for the next 4 weeks. Glycemic parameters, insulin, incretins during mixed-meal tolerance test (MMTT), lipopolysaccharide (LPS) level, and fecal microbiota were analyzed at weeks 0, 4, and 8. The first tertile of difference in glucose area under the curve during MMTT between weeks 0 and 4 was defined as 'responders' and the third as 'nonresponders,' respectively.

RESULTS

In all 10 participants, the peak incretin levels during MMTT were higher and LPS were lower at week 4 as compared with at baseline. While the insulin sensitivity of the 'responders' increased at week 4, that of the 'nonresponders' showed opposite results. However, the results were not statistically significant. In all participants, metabolically unfavorable microbiota decreased at week 4 and were restored at week 8. At baseline, metabolically hostile bacteria were more abundant in the 'nonresponders.' In 'responders,' Roseburia intestinalis increased at week 4.

CONCLUSION

While dietary fiber did not induce additional changes in glycemic parameters, it showed a trend of improvement in insulin sensitivity in 'responders.' Even if patients are already receiving diabetes treatment, the additional administration of fiber can lead to additional benefits in the treatment of diabetes.

Bi-directional drug-microbiome interactions of anti-diabetics

Type 2 diabetes (T2D) has become a global epidemic. Although several drugs are available to manage T2D, problems associated with person-to-person variability in drug efficacy and potential side-effects remain unresolved. Owing to the emerging role of the gut microbiome in obesity and T2D, the interaction between gut microbes and anti-diabetic drugs and its influence on drugs' functions remains of immediate research interest. On one hand, drugs can manipulate gut microbiome composition and metabolic capacity. Conversely, the metabolic activities of the microbiome and its metabolites can also influence drug metabolism and effects. Hence, understanding this bi-directional drug-microbiome interaction and how it influences the clinical outcomes of antidiabetic drugs can pave the way to develop next-generation strategies to ameliorate diabetes. This review presents evidences demonstrating the putative interactions between anti-diabetic drugs and the gut microbiome, and discusses the potential of microbiome modulators to manipulate drug-microbiome interactions and the drug metabolism.

A Pharmacometabolomic Approach to Predict Response to Metformin in Early-Phase Type 2 Diabetes Mellitus Patients

Metformin is a first-line medication for type 2 diabetes mellitus (T2DM). Based on its universal use, the consideration of inter-individual variability and development of predictive biomarkers are clinically significant. We aimed to identify endogenous markers of metformin responses using a pharmacometabolomic approach. Twenty-nine patients with early-phase T2DM were enrolled and orally administered metformin daily for 6 months. A total of 22 subjects were included in the final analysis. Patients were defined as responders or non-responders based on changes in their glycated haemoglobin A1c (HbA1c) from baseline, over 3 months. Urine metabolites at baseline, as well as at the 3 and 6 month follow-ups after the start of treatment were analysed using gas chromatography-mass spectrometry and evaluated with multivariate analyses. Metabolites distinguishable between the two response groups were obtained at baseline, as well as at the 3 and 6 month follow-ups, and significantly different metabolites were listed as markers of metformin response. Among the identified metabolites, citric acid, myoinositol, and hippuric acid levels showed particularly significant differences between the non-responder and responder groups. We thus identified different metabolite profiles in the two groups of T2DM patients after metformin administration, using pharmacometabolomics. These results might facilitate a better understanding and prediction of metformin response and its variability in individual patients.

Effects of Antidiabetic Drugs on Gut Microbiota Composition

Gut microbiota forms a catalog of about 1000 bacterial species; which mainly belong to the Firmicutes and Bacteroidetes phyla. Microbial genes are essential for key metabolic processes; such as the biosynthesis of short-chain fatty acids (SCFA); amino acids; bile acids or vitamins. It is becoming clear that gut microbiota is playing a prevalent role in pathologies such as metabolic syndrome; type 2 diabetes (T2D); inflammatory and bowel diseases. Obesity and related diseases; notably type 2 diabetes, induce gut dysbiosis. In this review; we aim to cover the current knowledge about the effects of antidiabetic drugs on gut microbiota diversity and composition as well as the potential beneficial effects mediated by specific taxa. Metformin is the first-line treatment against T2D. In addition to its glucose-lowering and insulin sensitizing effects, metformin promotes SCFA-producing and mucin-degrading bacteria. Other antidiabetic drugs discussed in this review show positive effects on dysbiosis; but without any consensus specifically regarding the Firmicutes to Bacteroidetes ratio. Thus, beneficial effects might be mediated by specific taxa.

Metabolomic analysis of healthy human urine following administration of glimepiride using a liquid chromatography-tandem mass spectrometry

Glimepiride, a third generation sulfonylurea, is an antihyperglycemic agent widely used to treat type 2 diabetes mellitus. In this study, an untargeted urinary metabolomic analysis was performed to identify endogenous metabolites affected by glimepiride administration. Urine samples of twelve healthy male volunteers were collected before and after administration of 2 mg glimepiride. These samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and then subjected to multivariate data analysis including principal component analysis and orthogonal partial least squares discriminant analysis. Through this metabolomic profiling, we identified several endogenous metabolites such as adenosine 3', 5'-cyclic monophosphate (cAMP), quercetin, tyramine, and urocanic acid, which exhibit significant metabolomic changes between pre- and posturine samples. Among these, cAMP, which is known to be related to insulin secretion, was the most significantly altered metabolite following glimepiride administration. In addition, the pathway analysis showed that purine, tyrosine, and histidine metabolism was affected by pharmacological responses to glimepiride. Together, the results suggest that the pharmacometabolomic approach, based on LC-MS/MS, is useful in understanding the alterations in biochemical pathways associated with glimepiride action.

Hypertensive patients exhibit an altered metabolism. A specific metabolite signature in urine is able to predict albuminuria progression

Hypertension (HTN) is increasing in prevalence, and albuminuria is a strong indicator of cardiovascular risk and renal damage progression. Despite blood pressure control with chronic treatment, a relevant subgroup of patients develop albuminuria. However, the biological factors responsible for albuminuria development and progression are underexplored. We aimed to identify key metabolic targets and biological pathways involved in the negative progression of cardiovascular and renal damage in hypertensives undergoing chronic treatment. A series of 1533 patients were followed for 5 years to investigate the evolution of albuminuria. Patients were classified as: (1) patients with persistent normoalbuminuria; (2) patients developing de novo albuminuria; and (3) patients with maintained albuminuria. At the end of follow-up, urine from 30 nonhypertensive subjects (control group) and a representative cohort of 118 patients was collected for metabolomic analysis. Metabolic patterns of interest were identified in a first discovery phase by nuclear magnetic resonance and further confirmed by liquid chromatography-mass spectrometry. Metabolites corresponding to HTN or albuminuria were measured in a prospective study carried out in 35 individuals still in normoalbuminuria, to evaluate their potential as predictors of albuminuria development. Nine metabolites were significantly altered, linking β-alanine metabolism, arginine and proline metabolism, and tricarboxylic acid cycle. The prospective study revealed a panel composed of guanidinoacetate, glutamate, and pantothenate, which was able to predict development of albuminuria. These metabolic signatures open new possibilities in hypertensive therapy and cardiovascular risk control, providing prompt and more efficient intervention, particularly in patients with worse cardiovascular prognosis.

Gut Microbiota and Nonalcoholic Fatty Liver Disease: Insights on Mechanism and Application of Metabolomics

Gut microbiota are intricately involved in the development of obesity-related metabolic diseases such as nonalcoholic fatty liver disease (NAFLD), type 2 diabetes, and insulin resistance. In the current review, we discuss the role of gut microbiota in the development of NAFLD by focusing on the mechanisms of gut microbiota-mediated host energy metabolism, insulin resistance, regulation of bile acids and choline metabolism, as well as gut microbiota-targeted therapy. We also discuss the application of a metabolomic approach to characterize gut microbial metabotypes in NAFLD.

Metabolomic insights into the intricate gut microbial-host interaction in the development of obesity and type 2 diabetes

Gut microbiota has recently been proposed as a crucial environmental factor in the development of metabolic diseases such as obesity and type 2 diabetes, mainly due to its contribution in the modulation of several processes including host energy metabolism, gut epithelial permeability, gut peptide hormone secretion, and host inflammatory state. Since the symbiotic interaction between the gut microbiota and the host is essentially reflected in specific metabolic signatures, much expectation is placed on the application of metabolomic approaches to unveil the key mechanisms linking the gut microbiota composition and activity with disease development. The present review aims to summarize the gut microbial-host co-metabolites identified so far by targeted and untargeted metabolomic studies in humans, in association with impaired glucose homeostasis and/or obesity. An alteration of the co-metabolism of bile acids, branched fatty acids, choline, vitamins (i.e., niacin), purines, and phenolic compounds has been associated so far with the obese or diabese phenotype, in respect to healthy controls. Furthermore, anti-diabetic treatments such as metformin and sulfonylurea have been observed to modulate the gut microbiota or at least their metabolic profiles, thereby potentially affecting insulin resistance through indirect mechanisms still unknown. Despite the scarcity of the metabolomic studies currently available on the microbial-host crosstalk, the data-driven results largely confirmed findings independently obtained from in vitro and animal model studies, putting forward the mechanisms underlying the implication of a dysfunctional gut microbiota in the development of metabolic disorders.