Ryan PM, Patterson E, Carafa I, Mandal R, Wishart DS, Dinan TG, Cryan JF, Tuohy KM, Stanton C, Ross RP. Metformin and Dipeptidyl Peptidase-4 Inhibitor Differentially Modulate the Intestinal Microbiota and Plasma Metabolome of Metabolically Dysfunctional Mice. Can J Diabetes 2020; 44: 146-155. e2. [PMID: 31445961 DOI: 10.1016/j.jcjd.2019.05.008]

Anti-diabetic agents and the risks of dementia in patients with type 2 diabetes: a systematic review and network meta-analysis of observational studies and randomized controlled trials

OBJECTIVE

To evaluate the association between anti-diabetic agents and the risks of dementia in patients with type 2 diabetes (T2D).

METHODS

Literature retrieval was conducted in PubMed, Embase, the Cochrane Central Register of Controlled Trials and Clinicaltrial.gov between January 1995 and October 2024. Observational studies and randomized controlled trials (RCTs) in patients with T2D, which intercompared anti-diabetic agents or compared them with placebo, and reported the incidence of dementia were included. Conventional and network meta-analyses of these studies were implemented. Results were exhibited as the odds ratio (OR) or risk ratio (RR) with 95% confidence interval (CI).

RESULTS

A total of 41 observational studies (3,307,483 participants) and 23 RCTs (155,443 participants) were included. In the network meta-analysis of observational studies, compared with non-users, sodium glucose cotransporter-2 inhibitor (SGLT-2i) (OR = 0.56, 95%CI, 0.45 to 0.69), glucagon-like peptide-1 receptor agonist (GLP-1RA) (OR = 0.58, 95%CI, 0.46 to 0.73), thiazolidinedione (TZD) (OR = 0.68, 95%CI, 0.57 to 0.81) and metformin (OR = 0.89, 95%CI, 0.80 to 0.99) treatments were all associated with reduced risk of dementia in patients with T2D. The surface under the cumulative ranking curve (SUCRA) evaluation conferred a rank order as SGLT-2i > GLP-1RA > TZD > dipeptidyl peptidase-4 inhibitor (DPP-4i) > metformin > α-glucosidase inhibitor (AGI) > glucokinase activator (GKA) > sulfonylureas > glinides > insulin in terms of the cognitive benefits. Meanwhile, compared with non-users, SGLT-2i (OR = 0.43, 95%CI, 0.30 to 0.62), GLP-1RA (OR = 0.54, 95%CI, 0.30 to 0.96) and DPP-4i (OR = 0.73, 95%CI, 0.57 to 0.93) were associated with a reduced risk of Alzheimer's disease while a lower risk of vascular dementia was observed in patients receiving SGLT-2i (OR = 0.42, 95%CI, 0.22 to 0.80) and TZD (OR = 0.52, 95%CI, 0.36 to 0.75) treatment. In the network meta-analysis of RCTs, the risks of dementia were comparable among anti-diabetic agents and placebo.

CONCLUSION

Compared with non-users, SGLT-2i, GLP-1RA, TZD and metformin were associated with the reduced risk of dementia in patients with T2D. SGLT-2i, and GLP-1RA may serve as the optimal choice to improve the cognitive prognosis in patients with T2D.

Investigation of the relationship between inflammation and microbiota in the intestinal tissue of female and male rats fed with fructose: Modulatory role of metformin

BACKGROUND

It has been reported that High-Fructose (HF) consumption, considered one of the etiological factors of Metabolic Syndrome (MetS), causes changes in the gut microbiota and metabolic disorders. There is limited knowledge on the effects of metformin in HF-induced intestinal irregularities in male and female rats with MetS.

OBJECTIVES

In this study, we investigated the sex-dependent effects of metformin treatment on the gut microbiota, intestinal Tight Junction (TJ) proteins, and inflammation parameters in HF-induced MetS.

METHODS

Fructose was given to the male and female rats as a 20% solution in drinking water for 15 weeks. Metformin (200 mg/kg) was administered by gastric tube once a day during the final seven weeks. Biochemical, histopathological, immunohistochemical, and bioinformatics analyses were performed. Differences were considered statistically significant at p < 0.05.

RESULTS

The metformin treatment in fructose-fed rats promoted glucose, insulin, Homeostasis Model Assessment of Insulin Resistance Index (HOMA-IR), and Triglyceride (TG) values in both sexes. The inflammation score was significantly decreased with metformin treatment in fructose-fed male and female rats (p < 0.05). Moreover, metformin treatment significantly decreased Interleukin-1 Beta (IL-1β) and Tumor Necrosis Factor-Alpha (TNF-α) in ileum tissue from fructose-fed males (p < 0.05). Intestinal immunoreactivity of Occludin and Claudin-1 was increased with metformin treatment in fructose-fed female rats. HF and metformin treatment changed the gut microbial composition. Firmicutes/Bacteroidetes (F/B) ratio increased with HF in females. In the disease group, Bifidobacterium pseudolongum; in the treatment group, Lactobacillus helveticus and Lactobacillus reuteri are the prominent species in both sexes. When the male and female groups were compared, Akkermansia muciniphila was prominent in the male treatment group.

CONCLUSION

In conclusion, metformin treatment promoted biochemical parameters in both sexes of fructose-fed rats. Metformin showed a sex-dependent effect on inflammation parameters, permeability factors, and gut microbiota. Metformin has partly modulatory effects on fructose-induced intestinal changes.

Global and regional genetic association analysis of ulcerative colitis and type 2 diabetes mellitus and causal validation analysis of two-sample two-way Mendelian randomization

Background

Clinical co-occurrence of UC (Ulcerative Colitis) and T2DM (Type 2 Diabetes Mellitus) is observed. The aim of this study is to investigate the potential causal relationship between Ulcerative Colitis (UC) and Type 2 Diabetes Mellitus (T2DM) using LDSC and LAVA analysis, followed by genetic verification through TSMR, providing insights for clinical prevention and treatment.

Methods

Genetic loci closely related to T2DM were extracted as instrumental variables from the GWAS database, with UC as the outcome variable, involving European populations. The UC data included 27,432 samples and 8,050,003 SNPs, while the T2DM data comprised 406,831 samples and 11,914,699 SNPs. LDSC and LAVA were used for quantifying genetic correlation at both global (genome-wide) and local (genomic regions) levels. MR analysis was conducted using IVW, MR-Egger regression, Weighted median, and Weighted mode, assessing the causal relationship between UC and diabetes with OR values and 95% CI. Heterogeneity and pleiotropy were tested using Egger-intercept, MR-PRESSO, and sensitivity analysis through the "leave-one-out" method and Cochran Q test. Subsequently, a reverse MR operation was conducted using UC as the exposure data and T2DM as the outcome data for validation.

Results

Univariable and bivariable LDSC calculated the genetic correlation and potential sample overlap between T2DM and UC, resulting in rg = -0.0518, se = 0.0562, P = 0.3569 with no significant genetic association found for paired traits. LAVA analysis identified 9 regions with local genetic correlation, with 6negative and 3 positive associations, indicating a negative correlation between T2DM and UC. MR analysis, with T2DM as the exposure and UC as the outcome, involved 34 SNPs as instrumental variables. The OR values and 95% CI from IVW, MR-Egger, Weighted median, and Weighted mode were 0.917 (0.848~0.992), 0.949 (0.800~1.125), 0.881 (0.779~0.996), 0.834(0.723~0.962) respectively, with IVW P-value < 0.05, suggesting a negative causal relationship between T2DM and UC. MR-Egger regression showed an intercept of -0.004 with a standard error of 0.009, P = 0.666, and MR-PRESSO Global Test P-value > 0.05, indicating no pleiotropy and no outliers detected. Heterogeneity tests showed no heterogeneity, and the "leave-one-out" sensitivity analysis results were stable. With UC as the exposure and T2DM as the outcome, 32 SNPs were detected, but no clear causal association was found.

Conclusion

There is a causal relationship between T2DM and UC, where T2DM reduces the risk of UC, while no significant causal relationship was observed from UC to T2DM.

The interplay between diet and the gut microbiome: implications for health and disease

Diet has a pivotal role in shaping the composition, function and diversity of the gut microbiome, with various diets having a profound impact on the stability, functionality and diversity of the microbial community within our gut. Understanding the profound impact of varied diets on the microbiome is crucial, as it will enable us not only to make well-informed dietary decisions for better metabolic and intestinal health, but also to prevent and slow the onset of specific diet-related diseases that stem from suboptimal diets. In this Review, we explore how geographical location affects the gut microbiome and how different diets shape its composition and function. We examine the mechanisms by which whole dietary regimes, such as the Mediterranean diet, high-fibre diet, plant-based diet, high-protein diet, ketogenic diet and Western diet, influence the gut microbiome. Furthermore, we underscore the need for exhaustive studies to better understand the causal relationship between diet, host and microorganisms for the development of precision nutrition and microbiome-based therapies.

The interplay of gut microbiota, obesity, and depression: insights and interventions

The gut microbiome, body weight, and related comorbidities are intricately linked through a complex interaction of microbial, genetic, environmental, and psychological factors. Alterations in gut microbiota can contribute to the development of weight disorders and depressive symptoms, with the potential for these relationships to be bidirectional. Effective management of these interconnected conditions often involves a combination of lifestyle modifications and psychological support. Medical interventions, including treatments for obesity, antidiabetic drugs, antidepressants, antibiotics, and probiotics, can have beneficial and detrimental effects on gut microbiota and mental health. Further research is needed to better understand their impact on gut microbiome and mental health in the context of obesity.

Metformin-induced changes of the gut microbiota in patients with type 2 diabetes mellitus: results from a prospective cohort study

BACKGROUND

The influence of the microbiota on hypoglycemic agents is becoming more apparent. The effects of metformin, a primary anti-diabetes drug, on gut microbiota are still not fully understood.

RESEARCH DESIGN AND METHODS

This prospective cohort study aims to investigate the longitudinal effects of metformin on the gut microbiota of 25 treatment-naïve diabetes patients, each receiving a daily dose of 1500 mg. Microbiota compositions were analyzed at baseline, and at 1, 3, and 6 months of medication using 16S rRNA gene sequencing.

RESULTS

Prior to the 3-month period of metformin treatment, significant improvements were noted in body mass index (BMI) and glycemic-related parameters, such as fasting blood glucose (FPG) and hemoglobin A1c (HbA1c), alongside homeostasis model assessment indices of insulin resistance (HOMA-IR). At the 3-month mark of medication, a significant reduction in the α-diversity of the gut microbiota was noted, while β-diversity exhibited no marked variances throughout the treatment duration. The Firmicutes to Bacteroidetes ratio. markedly decreased. Metformin treatment consistently increased Escherichia-Shigella and decreased Romboutsia, while Pseudomonas decreased at 3 months. Fuzzy c-means clustering identified three longitudinal trajectory clusters for microbial fluctuations: (i) genera temporarily changing, (ii) genera continuing to decrease (Bacteroides), and (iii) genera continuing to increase(Lachnospiraceae ND3007 group, [Eubacterium] xylanophilum group, Romboutsia, Faecalibacterium and Ruminococcaceae UCG-014). The correlation matrix revealed associations between specific fecal taxa and metformin-related clinical parameters HbA1c, FPG, Uric Acid (UA), high-density lipoproteincholesterol (HDL-C), alanine aminotransferase (ALT), hypersensitive C-reactive protein (hs-CRP), triglyceride (TG) (P < 0.05). Metacyc database showed that metformin significantly altered 17 functional pathways. Amino acid metabolism pathways such as isoleucine biosynthesis predominated in the post-treatment group.

CONCLUSIONS

Metformin's role in glucose metabolism regulation may primarily involve specific alterations in certain gut microbial species rather than an overall increase in microbial species diversity. This may suggest gut microbiota targets in future studies on metabolic abnormalities caused by metformin.

Advances in the mechanism of metformin with wide-ranging effects on regulation of the intestinal microbiota

Metformin is of great focus because of its high safety, low side effects, and various effects other than lowering blood sugar, such as anti-inflammation, anti-tumor, and anti-aging. Studies have shown that metformin has a modulating effect on the composition and function of the intestinal microbiota other than acting on the liver. However, the composition of microbiota is complex and varies to some extent between species and individuals, and the experimental design of each study is also different. Multiple factors present a major obstacle to better comprehending the effects of metformin on the gut microbiota. This paper reviews the regulatory effects of metformin on the gut microbiota, such as increasing the abundance of genus Akkermansia, enriching short-chain fatty acids (SCFAs)-producing bacterial genus, and regulating gene expression of certain genera. The intestinal microbiota is a large and vital ecosystem in the human body and is considered to be the equivalent of an "organ" of the human body, which is highly relevant to human health and disease status. There are a lot of evidences that the gut microbiota is responsible for metformin's widespread effects. However, there are only a few systematic studies on this mechanism, and the specific mechanism is still unclear. This paper aims to summarize the possible mechanism of metformin in relation to gut microbiota.

Understanding the action mechanisms of metformin in the gastrointestinal tract

Metformin is the initial medication recommended for the treatment of type 2 diabetes mellitus (T2DM). In addition to diabetes treatment, the function of metformin also can be anti-aging, antiviral, and anti-inflammatory. Nevertheless, further exploration is required to fully understand its mode of operation. Historically, the liver has been acknowledged as the main location where metformin reduces glucose levels, however, there is increasing evidence suggesting that the gastrointestinal tract also plays a significant role in its action. In the gastrointestinal tract, metformin effects glucose uptake and absorption, increases glucagon-like peptide-1 (GLP-1) secretion, alters the composition and structure of the gut microbiota, and modulates the immune response. However, the side effects of it cannot be ignored such as gastrointestinal distress in patients. This review outlines the impact of metformin on the digestive system and explores potential explanations for variations in metformin effectiveness and adverse effects like gastrointestinal discomfort.

Crosstalk between glucagon-like peptide 1 and gut microbiota in metabolic diseases

Gut microbiota exert influence on gastrointestinal mucosal permeability, bile acid metabolism, short-chain fatty acid synthesis, dietary fiber fermentation, and farnesoid X receptor/Takeda G protein-coupled receptor 5 (TGR5) signal transduction. The incretin glucagon-like peptide 1 (GLP-1) is mainly produced by L cells in the gut and regulates postprandial blood glucose. Changes in gut microbiota composition and function have been observed in obesity and type 2 diabetes (T2D). Meanwhile, the function and rhythm of GLP-1 have also been affected in subjects with obesity or T2D. Therefore, it is necessary to discuss the link between the gut microbiome and GLP-1. In this review, we describe the interaction between GLP-1 and the gut microbiota in metabolic diseases. On the one hand, gut microbiota metabolites stimulate GLP-1 secretion, and gut microbiota affect GLP-1 function and rhythm. On the other hand, the mechanism of action of GLP-1 on gut microbiota involves the inflammatory response. Additionally, we discuss the effects and mechanism of various interventions, such as prebiotics, probiotics, antidiabetic drugs, and bariatric surgery, on the crosstalk between gut microbiota and GLP-1. Finally, we stress that gut microbiota can be used as a target for metabolic diseases, and the clinical application of GLP-1 receptor agonists should be individualized.

Pharmacological and Nutritional Modulation of Metabolome and Metagenome in Cardiometabolic Disorders

Cardiometabolic disorders are major causes of morbidity and mortality worldwide. A growing body of research indicates that the gut microbiota, whether it interacts favorably or not, plays an important role in host metabolism. Elucidating metabolic pathways may be crucial in preventing and treating cardiometabolic diseases, and omics methods are key to studying the interaction between the fecal microbiota and host metabolism. This review summarizes available studies that combine metabolomic and metagenomic approaches to describe the effects of drugs, diet, nutrients, and specific foods on cardiometabolic health and to identify potential targets for future research.

Inflammatory Bowel Sugar Disease: A Pause From New Pharmacological Agents and an Embrace of Natural Therapy

Inflammatory bowel diseases (IBDs), including Crohn's disease and ulcerative colitis, are immune-mediated chronic inflammatory diseases that target the gastrointestinal tract and other distant organs. The incidence of IBDs has been rising and is more prevailing in Western communities. The etiology has been vague, but different theories include environmental factors that elicit an uncontrolled immune response, which damages internal organs. Treatment of either Crohn's disease or ulcerative colitis has witnessed significant advances; however, pharmacological drugs' side effects limit their use. Research about microbiota and its influence on IBDs has gained fame, and multiple studies correlate microbiota diversity positively with IBD treatment. Many factors contribute to the microbiota's health, including different diets, antibiotics, prebiotics, probiotics, synbiotics, and postbiotics. Specific immune responses lie behind the pathogenesis of IBDs and microbiota dysbiosis, and different studies have postulated new ways to control this abnormal response. Physical activity, sun exposure, efficient sleep, intermittent fasting, and supplementation of probiotics and vitamins are natural ways that help modulate this immune response, do not cost money as IBD pharmacological drugs, and do not come with deleterious side effects that are sometimes more harmful than IBDs. Our article proposes a comprehensive natural approach that can benefit IBD patients enormously. This approach does not replace the medications currently used in treating IBDs. The suggested approach can be used in combination with medications and might aid in reducing the doses of those medications.

Effects of Shenling Baizhu powder on intestinal microflora metabolites and liver mitochondrial energy metabolism in nonalcoholic fatty liver mice

Background & purpose

Non-alcoholic fatty liver disease (NAFLD) is characterised by the excessive accumulation of triglycerides in the liver. Shenling Baizhu powder (SLBZP) is formulated from various natural medicinal plants that protect the liver and are used to treat intestinal diseases. SLBZP improves the symptoms of NAFLD. However, its mechanism of action remains unclear. Herein, we investigated the ameliorative effect of SLBZP on model mice with high-fat-diet (HFD)-induced NAFLD. Additionally, we evaluated the impact of SLBZP on the intestinal flora and its metabolites and mitochondrial energy metabolism in NAFLD.

Methods

We used HFD to establish a mouse model of NAFLD. Different drug interventions were administered. We measured serum biochemical indices. Liver sections were visualised with hematoxylin-eosin and oil red O staining. 16S rDNA amplicon sequencing technology was used to analyse the diversity and abundance of the intestinal flora. Short-chain fatty acids (SCFAs) in the intestinal contents were detected using GC-MS. Liver tissue was sampled to detect mitochondrial membrane functional indices. Western blotting was used to determine the levels of mitochondrial pathway-related proteins, namely, uncoupling protein 2 (UCP2), adenosine monophosphate-activated protein kinase (AMPK) and inhibitory factor 1 (IF1) of F1Fo ATP synthesis/hydrolase, in the liver.

Results

The spleen-invigorating classic recipe of SLBZP reduced liver lipid deposition in mice with HFD-induced NAFLD. Additionally, SCFAs produced by intestinal flora metabolism regulated the UCP2/AMPK/IF1 signalling pathway involved in liver mitochondrial energy metabolism to improve the liver mitochondrial membrane permeability, respiratory state and oxidative phosphorylation efficiency of mice with NAFLD. Finally, SLBZP increased the liver ATP level.

Conclusion

Our results suggest that the therapeutic effect of SLBZP on NAFLD is related to the regulation of hepatic mitochondrial energy metabolism by intestinal flora and its metabolites and is possibly associated with the UCP2/AMPK/IF1 signalling pathway.

Gut Microbiome and Microbiome-Derived Metabolites in Patients with End-Stage Kidney Disease

The composition of the gut microbiome is altered in patients with chronic kidney disease (CKD). Dysbiosis leads to decreased levels of stool organic acids (OAs) and systemic inflammation, followed by accumulation of uremic toxins (UTs) and the development of end-stage kidney disease (ESKD). We assessed the relationship between the microbiome and UT levels or the development of ESKD by comparing patients undergoing hemodialysis (HD) and those with normal renal function (NRF). This cross-sectional study recruited 41 patients undergoing HD and 38 sex- and age-matched patients with NRF, and gut microbiome, levels of plasma UTs, inflammatory markers, and stool OAs were compared. The indices of beta-diversity differed significantly between patients with NRF and those undergoing HD, and between patients undergoing HD with and without type 2 diabetes. The levels of stool total OA, inflammatory markers, and UTs differed significantly between the patients with NRF and those undergoing HD. The combined main effects of type 2 diabetes and kidney function status were accumulation of indoxyl sulfate and p-cresyl sulfate. The relative abundances of Negativicutes and Megamonas were associated with development of ESKD and with the levels of UTs, even after adjustment for factors associated with the progression of ESKD. The present study indicates that the gut environment differs between patients with NRF and those undergoing HD and between patients undergoing HD with and without type 2 diabetes. Moreover, ESKD patients with diabetes accumulate more UTs derived from the gut microbiome, which might be associated with cardio-renal diseases and poor prognosis.

Microbiota: A potential orchestrator of antidiabetic therapy

The gut microbiota, as a 'new organ' of humans, has been identified to affect many biological processes, including immunity, inflammatory response, gut-brain neural circuits, and energy metabolism. Profound dysbiosis of the gut microbiome could change the metabolic pattern, aggravate systemic inflammation and insulin resistance, and exacerbate metabolic disturbance and the progression of type 2 diabetes (T2D). The aim of this review is to focus on the potential roles and functional mechanisms of gut microbiota in the antidiabetic therapy. In general, antidiabetic drugs (α-glucosidase inhibitor, biguanides, incretin-based agents, and traditional Chinese medicine) induce the alteration of microbial diversity and composition, and the levels of bacterial component and derived metabolites, such as lipopolysaccharide (LPS), short chain fatty acids (SCFAs), bile acids and indoles. The altered microbial metabolites are involved in the regulation of gut barrier, inflammation response, insulin resistance and glucose homeostasis. Furthermore, we summarize the new strategies for antidiabetic treatment based on microbial regulation, such as pro/prebiotics administration and fecal microbiota transplantation, and discuss the need for more basic and clinical researches to evaluate the feasibility and efficacy of the new therapies for diabetes.

Pharmacomicrobiomics and type 2 diabetes mellitus: A novel perspective towards possible treatment

Type 2 diabetes mellitus (T2DM), a major driver of mortality worldwide, is more likely to develop other cardiometabolic risk factors, ultimately leading to diabetes-related mortality. Although a set of measures including lifestyle intervention and antidiabetic drugs have been proposed to manage T2DM, problems associated with potential side-effects and drug resistance are still unresolved. Pharmacomicrobiomics is an emerging field that investigates the interactions between the gut microbiome and drug response variability or drug toxicity. In recent years, increasing evidence supports that the gut microbiome, as the second genome, can serve as an attractive target for improving drug efficacy and safety by manipulating its composition. In this review, we outline the different composition of gut microbiome in T2DM and highlight how these microbiomes actually play a vital role in its development. Furthermore, we also investigate current state-of-the-art knowledge on pharmacomicrobiomics and microbiome's role in modulating the response to antidiabetic drugs, as well as provide innovative potential personalized treatments, including approaches for predicting response to treatment and for modulating the microbiome to improve drug efficacy or reduce drug toxicity.

Gut microbiome in PCOS associates to serum metabolomics: a cross-sectional study

The association between gut microbiome and chronic metabolic disease including polycystic ovary syndrome (PCOS), is well documented, however, the relationship between the gut microbiota and serum metabolites remains unknown. In this study, untargeted metabolomics together with a 16S rRNA gene sequencing tool was used to detect small molecule serum metabolites and the gut microbiome. We identified 15 differential metabolites between PCOS patients and the healthy control. Lysophosphatidylcholine (LPC) (18:2, 20:3, 18:1, P-16:0, 17:0, 15:0, 18:3, 20:4), phosphatidylcholine(PC), ganglioside GA2 (d18:1/16:0) and 1-linoleoylglycerophosphocholine were increased in the PCOS group, and the concentrations of phosphoniodidous acid, bilirubin, nicotinate beta-D-ribonucleotide and citric acid were decreased in the PCOS group, suggesting a lipid metabolism and energy metabolism disorder in the PCOS patients. The diversity of gut microbiota in PCOS group was lower than that in healthy controls. Escherichia/Shigella, Alistipes and an unnamed strain 0319_6G20 belonging to Proteobacteria were important distinguishing genera (LDA > 3.5) in PCOS. Prevotella_9 was positively correlated with phosphoniodidous acid, nicotinate beta-D-ribonucleotide and citric acid concentrations, and negatively correlated with the concentration of LPC (20:3) and 1-linoleoylglycerophosphocholine; Roseburia was negatively correlated with LPC concentration (20:4), while the characteristic genus 0319_6G20 of PCOS was positively correlated with LPC concentration (20:3) (COR > 0.45). SF-36 in the PCOS group was significantly lower than that in the healthy control (HC) group, which was associated with the presence of Escherichia-Shigella and Alistipes. Our finding demonstrated the correlation between the gut microbiota and serum metabolites in PCOS, and therefore characteristic gut microbiota and metabolites may play an important role in the insulin resistance and the mood changes of PCOS patients.

Glucagon-like peptide-1 analog liraglutide leads to multiple metabolic alterations in diet-induced obese mice

Liraglutide, a glucagon-like peptide-1 analog, has beneficial metabolic effects in patients with type 2 diabetes and obesity. Although the high efficacy of liraglutide as an anti-diabetic and anti-obesity drug is well known, liraglutide-induced metabolic alterations in diverse tissues remain largely unexplored. Here, we report the changes in metabolic profiles induced by a 2-week subcutaneous injection of liraglutide in diet-induced obese mice fed a high-fat diet for 8 weeks. Our comprehensive metabolomic analyses of the hypothalamus, plasma, liver, and skeletal muscle showed that liraglutide intervention led to various metabolic alterations in comparison with diet-induced obese or nonobese mice. We found that liraglutide remarkably coordinated not only fatty acid metabolism in the hypothalamus and skeletal muscle but also amino acid and carbohydrate metabolism in plasma and liver. Comparative analyses of metabolite dynamics revealed that liraglutide rewired intertissue metabolic correlations. Our study points to a previously unappreciated metabolic alteration by liraglutide in several tissues, which may underlie its therapeutic effects within and across the tissues.

Simiao Wan modulates the gut microbiota and bile acid metabolism during improving type 2 diabetes mellitus in mice

BACKGROUND

Gut microbiota coupled with their metabolites (bile acids, BAs) get involved in diabetic pathogenesis. Simiao Wan is a famous traditional Chinese formula consisting on Phellodendron chinense C.K.Schneid. (Rutaceae), Atractylodes lancea (Thunb.) DC. (Asteraceae), Achyranthes bidentata Blume (Amaranthaceae) and Coix lacryma-jobi var. ma-yuen (Rom.Caill.) Stapf (Poaceae), and used to treat gouty arthritis and hyperuricemia for thousands of years. However, the mechanisms underlying its beneficial efficacy on diabetes still needs to be explored.

PURPOSE

Our study was performed to reveal the effects of the 75% ethanol extraction of Simiao Wan (SMW) on diabetes, gut microbiota and bile acids (BAs) in diabetic mice.

METHODS

The effects of SMW on diabetes were evaluated in mice treated by high-fat diet (HFD)/streptozotocin (STZ). The 16S rDNA sequencing and BAs metabolomics were performed to assess the changes of BAs profiles and gut microbiota induced by SMW. Western blot and real-time quantitative PCR were conducted to evaluate the possible mechanism of SMW.

RESULTS

SMW significantly improved insulin resistance and hepatic lipid accumulation in HFD/STZ mice. It remarkably enriched in the bacteria Allobaculum, Clostridium, Akkermansia, Lactobacilus and Bilophila whereas decreased Coprococcus and Halomonas in diabetic mice. Furthermore, the profiles of BAs were also modulated by SMW, indicated by the reduction of conjugated BAs and 12α-OH/non-12α-OH BAs ratio in liver as well as the increase of primary BAs in feces. SMW also activated farnesoid X receptor and inhibited sterol regulatory element-binding protein-1 expression, contributing to its beneficial actions on lipid accumulation in liver.

CONCLUSION

Our results showed that SMW exerted its beneficial effects on insulin resistance and hepatic lipid accumulation indirectly through regulating profiles of gut microbe and BAs.

Association of gut microbiota with glycaemic traits and incident type 2 diabetes, and modulation by habitual diet: a population-based longitudinal cohort study in Chinese adults

AIMS/HYPOTHESIS

The gut microbiome is mainly shaped by diet, and varies across geographical regions. Little is known about the longitudinal association of gut microbiota with glycaemic control. We aimed to identify gut microbiota prospectively associated with glycaemic traits and type 2 diabetes in a geographically diverse population, and examined the cross-sectional association of dietary or lifestyle factors with the identified gut microbiota.

METHODS

The China Health and Nutrition Survey is a population-based longitudinal cohort covering 15 provinces/megacities across China. Of the participants in that study, 2772 diabetes-free participants with a gut microbiota profile based on 16S rRNA analysis were included in the present study (age 50.8 ± 12.7 years, mean ± SD). Using a multivariable-adjusted linear mixed-effects model, we examined the prospective association of gut microbiota with glycaemic traits (fasting glucose, fasting insulin, HbA1c and HOMA-IR). We constructed a healthy microbiome index (HMI), and used Poisson regression to examine the relationship between the HMI and incident type 2 diabetes. We evaluated the association of dietary or lifestyle factors with the glycaemic trait-related gut microbiota using a multivariable-adjusted linear regression model.

RESULTS

After follow-up for 3 years, 123 incident type 2 diabetes cases were identified. We identified 25 gut microbial genera positively or inversely associated with glycaemic traits. The newly created HMI (per SD unit) was inversely associated with incident type 2 diabetes (risk ratio 0.69, 95% CI 0.58, 0.84). Furthermore, we found that several microbial genera that were favourable for the glycaemic trait were consistently associated with healthy dietary habits (higher consumption of vegetable, fruit, fish and nuts).

CONCLUSIONS/INTERPRETATION

Our results revealed multiple gut microbiota prospectively associated with glycaemic traits and type 2 diabetes in a geographically diverse population, and highlighted the potential of gut microbiota-based diagnosis or therapy for type 2 diabetes.

DATA AVAILABILITY

The code for data analysis associated with the current study is available at https://github.com/wenutrition/Microbiota-T2D-CHNS.

Metformin in prediabetes: key mechanisms for the prevention of diabetes and cardiometabolic risks

Today, prediabetes is regarded by the world medical community as early diabetes mellitus. The accumulated research evidence shows that prediabetes is characterized by a spectrum of complications that are similar to those of diabetes mellitus, which means that the deterioration of cardiovascular prognosis starts already at the stage of prediabetes. In the current timeframe, metformin is actually the only drug that is widely prescribed for the treatment of prediabetes to prevent type 2 diabetes mellitus and cardiovascular diseases associated with insulin resistance and hyperinsulinemia. Meanwhile, metabolically unhealthy obesity characterized by hyperinsulinemia and insulin resistance is associated with a significantly unfavourable course of prediabetes, as well as the highest risk of developing both type 2 diabetes mellitus and cardiovascular diseases, development/ progression of chronic kidney disease. The theme of this review is the priority of metformin for the management of the most prognostically unfavourable phenotypes of prediabetes. The review is also devoted to the description of the most significant mechanisms that provide effects of metformin underlying the management of key disorders that determine the unfavourable prognosis of prediabetes. In particular, it sets forth the role of unhealthy nutrition, its effects on the development of imbalance of the composition of gut microbiota, which, in turn, entails a cascade of metabolic disorders underlying the development of metabolic ill health. The review sets forth the key role of metformin as a drug that protects against the development of these disorders. The information presented in this review will be useful to personalize the choice of both the scope and nature of interventions in patients with different phenotypic characteristics.

Metagenomic Analyses Reveal Distinct Gut Microbiota Signature for Predicting the Neoadjuvant Chemotherapy Responsiveness in Breast Cancer Patients

Background

Growing evidence supports the modulatory role of human gut microbiome on neoadjuvant chemotherapy (NAC) efficacy. However, the relationships among the gut microbiome, tumor-infiltrating lymphocytes (TILs), and NAC response for breast cancer (BC) patients remain unclear. We thus proposed this preliminary study to investigate the relationship between gut microbiome and BC patients’ responses to NAC treatment as well as underlying mechanisms.

Methods

Prior to receiving NAC, the fecal metagenome collected from 23 patients with invasive BC was analyzed. Patients were subsequently assigned to the NAC non-effectual group and the NAC effectual group based on their response to NAC. The peripheral T lymphocyte subset counts were examined by flow cytometry methods. CellMinor analysis was employed to explore the relationship between CD4 mRNA expression and the reaction of tumor cells to NAC drugs.

Results

The gut microbiomes of the NAC non-effectual group showed characteristics of low diversity with low abundances, distinct metagenomic composition with decreased butyrate-producing and indolepropionic acid-producing bacteria, and increased potential pathobionts compared with the NAC effectual group. The combination of Coprococcus, Dorea, and uncultured Ruminococcus sp. serves as signature bacteria for distinguishing NAC non-effectual group patients from the NAC effectual group. The absolute numbers of CD4⁺ and CD8⁺ TIL infiltration in tumors in the NAC non-effectual group were significantly lower than those in the effectual group. Similar findings were reported for the CD4⁺ T lymphocytes in the peripheral blood (p’s < 0.05). NAC effectual-related signature bacteria were proportional to these patients’ CD4⁺ T lymphocyte counts in peripheral blood and tumors (p’s < 0.05). CellMinor analysis showed that the CD4 mRNA expression level dramatically climbed with increased sensitivity of tumor cells to NAC drugs such as cyclophosphamide, cisplatin, and carboplatin (p’s < 0.05).

Conclusions

The composition of the gut microbial community differs between BC patients for whom NAC is effective to those that are treatment resistant. The modulation of the gut microbiota on host CD4⁺ T lymphocytes may be one critical mechanism underlying chemosensitivity and NAC pathologic response. Taken together, gut microbiota may serve as a potential biomarker for NAC response, which sheds light on novel intervention targets in the treatment of NAC non-effectual BC patients.

Intestinal AMPK modulation of microbiota mediates crosstalk with brown fat to control thermogenesis

The energy-dissipating capacity of brown adipose tissue through thermogenesis can be targeted to improve energy balance. Mammalian 5'-AMP-activated protein kinase, a key nutrient sensor for maintaining cellular energy status, is a known therapeutic target in Type II diabetes. Despite its well-established roles in regulating glucose metabolism in various tissues, the functions of AMPK in the intestine remain largely unexplored. Here we show that AMPKα1 deficiency in the intestine results in weight gain and impaired glucose tolerance under high fat diet feeding, while metformin administration fails to ameliorate these metabolic disorders in intestinal AMPKα1 knockout mice. Further, AMPKα1 in the intestine communicates with brown adipose tissue to promote thermogenesis. Mechanistically, we uncover a link between intestinal AMPKα1 activation and BAT thermogenic regulation through modulating anti-microbial peptide-controlled gut microbiota and the metabolites. Our findings identify AMPKα1-mediated mechanisms of intestine-BAT communication that may partially underlie the therapeutic effects of metformin.

Comparative Evaluation of the Effect of Metformin and Insulin on Gut Microbiota and Metabolome Profiles of Type 2 Diabetic Rats Induced by the Combination of Streptozotocin and High-Fat Diet

Lately, an increasing number of studies have investigated the relationship between metformin and gut microbiota, suggesting that metformin exerts part of its hypoglycemic effect through the microbes. However, its underlying mechanism remains largely undetermined. In the present study, we investigated the effects of metformin on gut microbiota and metabolome profiles in serum and compared it with insulin treatment in rats with type 2 diabetes mellitus (T2DM). Diabetic rats (DM group) were induced by a combination of streptozotocin and high-fat diet (HFD). After 7 days, DM rats were treated with metformin (MET group) or insulin (INS group) for 3 weeks. The 16S rRNA sequencing of the gut microbiota and non-targeted metabolomics analysis of serum were conducted. A total of 13 bile acids (BAs) in serum were further determined and compared among different groups. The rat model of T2DM was well established with the typical diabetic symptoms, showing significantly increased blood glucose, AUC of OGTT, HOMA-IR, TC, TG, LDL-C and TBA. Metformin or insulin treatment could ameliorate symptoms of diabetes and partly recover the abnormal biochemical indicators. Compared with DM rats, the relative abundances of 13 genera were significantly changed after metformin treatment, while only three genera were changed after insulin treatment. The metformin and insulin treatments also exhibited different serum metabolome profiles in T2DM rats. Moreover, 64 differential metabolites were identified between MET and DM groups, whereas 206 were identified between INS and DM groups. Insulin treatment showed greater influence on amino acids, glycerophospholipids/glycerolipids, and acylcarnitine compared with the metformin treatment, while metformin had an important impact on BAs. Furthermore, metformin could significantly decrease the serum levels of CA, GCA, UDCA, and GUDCA, but increase the level of TLCA in DM rats. Insulin treatment significantly decreased the levels of CA, UDCA, and CDCA. Besides, several metabolites in serum or microbiota were positively or negatively correlated with some bacteria. Collectively, our findings indicated that metformin had a stronger effect on gut microbiota than insulin, while insulin treatment showed greater influence on serum metabolites, which provided novel insights into the therapeutic effects of metformin on diabetes.

Pharmacomicrobiomics in Western Medicine and Traditional Chinese Medicine in Type 2 Diabetes

Pharmacomicrobiomics refers to the interactions between foreign compounds and the gut microbiome resulting in heterogeneous efficacy, side effects, and toxicity of the compound concerned. Glucose lowering drugs reduce blood glucose by modulating insulin secretion and its actions as well as redistributing energy disposal. Apart from genetic, ecological, and lifestyle factors, maintaining an equilibrium of the whole gut microbiome has been shown to improve human health. Microbial fingerprinting using faecal samples indicated an 'invisible phenotype' due to different compositions of microbiota which might orchestrate the interactions between patients' phenotypes and their responses to glucose-lowering drugs. In this article, we summarize the current evidence on differences in composition of gut microbiota between individuals with type 2 diabetes (T2D) and healthy individuals, the disruption of the balance of beneficial and pathogenic microbiota was shown in patients with T2D and how Western Medicine (WM) and Traditional Chinese Medicine (TCM) might re-shape the gut microbiota with benefits to the host immunity and metabolic health. We particularly highlighted the effects of both WM and TCM increase the relative abundance of health promoting bacteria, such as, Akkermansia muciniphila, Blautia, and Bifidobacterium adolescentis, and which have been implicated in type 2 diabetes (T2D). Several lines of evidence suggested that TCM might complement the efficacy of WM through alteration of microbiota which warrants further investigation in our pursuit of prevention and control of T2D.

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.

Metformin Reduces the Risk of Diverticula of Intestine in Taiwanese Patients with Type 2 Diabetes Mellitus

Aim: To investigate the risk of diverticula of intestine associated with metformin use. Methods: This retrospective cohort study used the Taiwan's National Health Insurance database to enroll 307,548 ever users and 18,839 never users of metformin. The patients were followed up starting on January 1, 2006 and ending on a date up to December 31, 2011. To address confounding by indication, hazard ratios were derived from Cox regression based on the inverse probability of treatment weighting using propensity score. Results: During follow-up, newly diagnosed cases of diverticula were identified in 1,828 ever users (incidence rate: 125.59 per 100,000 person-years) and 223 never users (incidence rate: 268.17 per 100,000 person-years). Ever users had an approximately 54% lower risk, as shown by the overall hazard ratio of 0.464 (95% confidence interval 0.404-0.534). While patients categorized in each tertile of cumulative duration of metformin therapy were compared to never users, a dose-response pattern was observed with hazard ratios of 0.847 (0.730-0.983), 0.455 (0.391-0.531) and 0.216 (0.183-0.255) for the first (<27.37 months), second (27.37-59.70 months) and third (>59.70 months) tertiles, respectively. The findings were similar when the diagnosis of diverticula was restricted to the small intestine or to the colon. Subgroup analyses suggested that the lower risk of diverticula of intestine associated with metformin use was significant in all age groups of <50, 50-64 and ≥65 years, but the magnitude of risk reduction attenuated with increasing age. Conclusion: Metformin treatment is associated with a significantly reduced risk of diverticula of intestine.

A Metabolic Pattern in Healthy Subjects Given a Single Dose of Metformin: A Metabolomics Approach

Metformin is a widely prescribed medication for the treatment of type 2 diabetes mellitus (T2DM). It possesses effective roles in various disorders, including cancer, dyslipidemia, and obesity. However, the underlying mechanisms of metformin's multiple benefits are not fully understood. Herein, a mass spectrometry-based untargeted metabolomics approach was used to investigate the metabolic changes associated with the administration of a single dose of metformin in the plasma of 26 healthy subjects at five-time points; pre-dose, before the maximum concentration of metformin (C_max), C_max, after C_max, and 36 h post-dose. A total of 111 metabolites involved in various biochemical processes were perturbed, with branched-chain amino acid (BCAA) being the most significantly altered pathway. Additionally, the Pearson similarity test revealed that 63 metabolites showed a change in their levels dependent on metformin level. Out of these 63, the level of 36 metabolites was significantly altered by metformin. Significantly altered metformin-dependent metabolites, including hydroxymethyl uracil, propionic acid, glycerophospholipids, and eicosanoids, pointed to fundamental biochemical processes such as lipid network signaling, energy homeostasis, DNA lesion repair mechanisms, and gut microbiota functions that could be linked to the multiple beneficial roles of metformin. Thus, the distinctive metabolic pattern linked to metformin administration can be used as a metabolic signature to predict the potential effect and mechanism of actions of new chemical entities during drug development.

The Role of Dipeptidyl Peptidase 4 as a Therapeutic Target and Serum Biomarker in Inflammatory Bowel Disease: A Systematic Review

BACKGROUND

The roles dipeptidyl peptidase 4 (DPP4), aminopeptidase N (APN), and their substrates in autoimmune diseases are being increasingly recognized. However, their significance in inflammatory bowel diseases (IBD) is not entirely understood. This systematic review aims to discuss the pathophysiological processes related to these ectopeptidases while comparing findings from preclinical and clinical settings.

METHODS

This review was conducted according to the PRISMA guidelines. We performed a literature search in PubMed, SCOPUS, and Web of Science to identify all reports from inception until February 2020. The search included validated animal models of intestinal inflammation and studies in IBD patients. Quality assessment was performed using SYRCLE's risk of bias tool and CASP qualitative and cohort checklists.

RESULTS

From the 45 included studies, 36 were performed in animal models and 12 in humans (3 reports included both). Overall, the methodological quality of preclinical studies was acceptable. In animal models, DPP4 and APN inhibition significantly improved intestinal inflammation.Glucagon-like peptide (GLP)-1 and GLP-2 analogs and GLP-2-relase-inducing drugs also showed significant benefits in recovery from inflammatory damage. A nonsignificant trend toward disease remission with the GLP-2 analog teduglutide was observed in the sole interventional human study. All human studies reported an inverse correlation between soluble DPP4/CD26 levels and disease severity, in accordance with the proposal of DPP4 as a biomarker for IBD.

CONCLUSIONS

The use of DPP4 inhibitors and analogs of its substrates has clear benefits in the treatment of experimentally induced intestinal inflammation. Further research is warranted to validate their potential diagnostic and therapeutic applications in IBD patients.

Metformin use is associated with a reduced risk of acute appendicitis in Taiwanese patients with type 2 diabetes mellitus

This retrospective cohort study used the nationwide database of Taiwan’s National Health Insurance to investigate whether metformin would reduce the risk of acute appendicitis in patients with type 2 diabetes mellitus. We first identified 423,949 patients newly diagnosed of diabetes from 1999 to 2005. After excluding patients having type 1 diabetes mellitus, missing data, previous history of acute appendicitis, aged < 15 years, aged > 80 years and followed up for < 6 months, 338,172 ever users and 21,861 never users of metformin were followed up from January 1, 2006 until December 31, 2011. Incidence of acute appendicitis was estimated for never users, ever users and subgroups (divided by median, tertiles and quartiles, respectively) of dose–response indicators including cumulative duration (months), cumulative dose (mg) and average daily dose (mg/day) of metformin therapy. We used Cox regression incorporated with the inverse probability of treatment weighting using propensity score to estimate the overall hazard ratio for ever versus never users, and the hazard ratios for subgroups of dose–response indicators versus never users. Results showed that new-onset acute appendicitis was diagnosed in 1558 ever users and 179 never users during follow-up. The incidence was 98.15 per 100,000 person-years in ever users and was 189.48 per 100,000 person-years in never users. The overall hazard ratio (95% confidence interval) of 0.514 (0.441–0.600) suggested a lower risk of acute appendicitis associated with metformin use. A dose–response pattern was consistently observed in the analyses of different subgroups of dose–response indicators and the reduced risk associated with metformin use was consistently observed in various sensitivity analyses. An average daily dose of 1000–1500 mg/day can significantly reduce the risk by > 50%. The benefit did not differ between different formulations of metformin, and the estimated hazard ratio for conventional/immediate-release metformin versus never users was 0.516 (0.441–0.603) and was 0.509 (0.421–0.615) for prolonged/slow-release metformin versus never users. It is concluded that metformin use is associated with a reduced risk of acute appendicitis in patients with type 2 diabetes mellitus.

Effects of vancomycin-induced gut microbiome alteration on the pharmacodynamics of metformin in healthy male subjects

Metformin is a major treatment for type 2 diabetes. This study was conducted to investigate the impact of gut microbiome dysbiosis on the pharmacokinetics and antihyperglycemic effects of metformin. Healthy adult males aged 19-45 years with no defecation abnormalities were recruited for this 4-period clinical study: baseline; post-metformin (i.e., multiple oral doses of 1000 mg metformin on days 1-4); post-vancomycin (i.e., multiple oral doses of 500 mg vancomycin on days 11-17 inducing gut microbiome changes); and post-metformin + vancomycin (i.e., multiple oral doses of 1000 mg metformin on days 16-19). In each period, serum glucose and insulin concentrations following an oral glucose tolerance test, fecal samples for gut microbiome composition, and safety data were obtained. Following metformin dosing, plasma and urine samples for pharmacokinetics were collected. Nine subjects completed the study. The pharmacokinetics of metformin remained unchanged, and the antihyperglycemic effect was significantly decreased after vancomycin administration (p value = 0.039), demonstrating the weak relationship between the pharmacokinetics and pharmacodynamics of metformin. Relative abundances of some genus were changed after vancomycin administration, and tended to correlate with the antihyperglycemic effects of metformin (p value = 0.062 for Erysipelatoclostridium; p value = 0.039 for Enterobacter; and p value = 0.086 for Faecalibacterium). Adverse events occurred in all subjects and were resolved without sequelae. In conclusion, a decrease in the antihyperglycemic effect of metformin was observed after concomitant administration with vancomycin, without changes in metformin pharmacokinetics. The antihyperglycemic effect was tended to correlate with the relative abundance of several genus, suggesting that the effect of metformin is partly attributable to the gut microbiome (ClinicalTrials.gov, NCT03809260).

The Relationship between the Gut Microbiome and Metformin as a Key for Treating Type 2 Diabetes Mellitus

Metformin is the first-line pharmacotherapy for treating type 2 diabetes mellitus (T2DM); however, its mechanism of modulating glucose metabolism is elusive. Recent advances have identified the gut as a potential target of metformin. As patients with metabolic disorders exhibit dysbiosis, the gut microbiome has garnered interest as a potential target for metabolic disease. Henceforth, studies have focused on unraveling the relationship of metabolic disorders with the human gut microbiome. According to various metagenome studies, gut dysbiosis is evident in T2DM patients. Besides this, alterations in the gut microbiome were also observed in the metformin-treated T2DM patients compared to the non-treated T2DM patients. Thus, several studies on rodents have suggested potential mechanisms interacting with the gut microbiome, including regulation of glucose metabolism, an increase in short-chain fatty acids, strengthening intestinal permeability against lipopolysaccharides, modulating the immune response, and interaction with bile acids. Furthermore, human studies have demonstrated evidence substantiating the hypotheses based on rodent studies. This review discusses the current knowledge of how metformin modulates T2DM with respect to the gut microbiome and discusses the prospect of harnessing this mechanism in treating T2DM.

Metabolomic analysis of a selective ABCA1 inducer in obesogenic challenge provides a rationale for therapeutic development

BACKGROUND

Therapeutic agents with novel mechanisms of action are needed to combat the growing epidemic of type 2 diabetes (T2D) and related metabolic syndromes. Liver X receptor (LXR) agonists possess preclinical efficacy yet produce side effects due to excessive lipogenesis. Anticipating that many beneficial and detrimental effects of LXR agonists are mediated by ABCA1 and SREPB1c expression, respectively, we hypothesized that a phenotypic optimization strategy prioritizing selective ABCA1 induction would identify an efficacious lead compound with an improved side effect profile over existing LXRβ agonists.

METHODS

We synthesized and characterized a novel small molecule for selective induction of ABCA1 vs. SREBP1c in vitro. This compound was evaluated in both wild-type mice and a high-fat diet (HFD) mouse model of obesity-driven diabetes through functional, biochemical, and metabolomic analysis.

FINDINGS

Six weeks of oral administration of our lead compound attenuated weight gain, glucose intolerance, insulin signaling deficits, and adiposity. Global metabolomics revealed suppression of gluconeogenesis, free fatty acids, and pro-inflammatory metabolites. Target identification linked these beneficial effects to selective LXRβ agonism and PPAR/RXR antagonism.

INTERPRETATION

Our observations in the HFD model, combined with the absence of lipogenesis and neutropenia in WT mice, support this novel approach to therapeutic development for T2D and related conditions.

Circulating metabolites and lipids are associated with glycaemic measures in South Asians

BACKGROUND

South Asians are at higher risk for diabetes (DM) than many other racial/ethnic groups. Circulating metabolites are measurable products of metabolic processes that may explain the aetiology of elevated risk. We characterized metabolites associated with prevalent DM and glycaemic measures in South Asians.

METHODS

We included 717 participants from the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study, aged 40-84 years. We used baseline fasting serum for metabolomics and demographic, behavioural, glycaemic data from baseline and at 5 years. We performed LC-MS untargeted metabolomic and lipidomic analysis with targeted integration of known signals. Individual linear and ordinal logistic regression models were adjusted for age, sex, BMI, diet, exercise, alcohol, smoking and family history of DM followed by elastic net regression to identify metabolites most associated with the outcome.

RESULTS

There were 258 metabolites with detectable signal in >98% of samples. Thirty-four metabolites were associated with prevalent DM in an elastic net model. Predominant metabolites associated with DM were sphingomyelins, proline (OR 15.86; 95% CI 4.72, 53.31) and betaine (OR 0.03; 0.004, 0.14). Baseline tri- and di-acylglycerols [DG (18:0/16:0) (18.36; 11.79, 24.92)] were positively associated with fasting glucose and long-chain acylcarnitines [CAR 26:1 (-0.40; -0.54, -0.27)] were inversely associated with prevalent DM and HbA_1c at follow-up.

DISCUSSION

A metabolomic signature in South Asians may help determine the unique aetiology of diabetes in this high-risk ethnic group. Future work will externally validate our findings and determine the effects of modifiable risk factors for DM.

Metformin Use Is Associated with a Lower Risk of Inflammatory Bowel Disease in Patients with Type 2 Diabetes Mellitus

AIM

Our aim was to compare the risk of developing inflammatory bowel disease [IBD] between ever users and never users of metformin.

METHODS

Patients with newly diagnosed type 2 diabetes mellitus from 1999 to 2005 were enrolled from Taiwan's National Health Insurance. A total of 340 211 ever users and 24 478 never users who were free from IBD on January 1, 2006 were followed up until December 31, 2011. Hazard ratios were estimated by Cox regression incorporating the inverse probability of treatment weighting using a propensity score.

RESULTS

New-onset IBD was diagnosed in 6466 ever users and 750 never users. The respective incidence rates were 412.0 and 741.3 per 100 000 person-years and the hazard ratio for ever vs never users was 0.55 [95% confidence interval: 0.51-0.60]. A dose-response pattern was observed while comparing the tertiles of cumulative duration of metformin therapy to never users. The respective hazard ratios for the first [<26.0 months], second [26.0-58.3 months] and third [>58.3 months] tertiles were 1.00 [0.93-1.09], 0.57 [0.52-0.62] and 0.24 [0.22-0.26]. While patients treated with oral antidiabetic drugs [OADs] without metformin were treated as a reference group, the hazard ratios for patients treated with OADs with metformin, with insulin without metformin [with/without other OADs] and with insulin and metformin [with/without other OADs] were 0.52 [0.42-0.66], 0.95 [0.76-1.20] and 0.50 [0.40-0.62], respectively.

CONCLUSION

A reduced risk of IBD is consistently observed in patients with type 2 diabetes mellitus who have been treated with metformin.

Role of gut microbiome in regulating the effectiveness of metformin in reducing colorectal cancer in type 2 diabetes

The prevalence of colorectal cancer (CRC) and type 2 diabetes mellitus (T2DM) is increasing globally. It is rarely noticed that the incidence of CRC is higher in patients with T2DM. What needs to be mentioned is that metformin, a commonly used clinical drug for T2DM, attracts scholars’ attention because of its benefits in lowering the risk of developing CRC. Hence, we try to find the common grounds of initiation of T2DM and CRC and the reason why metformin reduces the risk of CRC in patients with T2DM. We noticed consistent changes of gut microbiota, such as elevated Bacteroides, Prevotella and Bifidobacterium and depressed Firmicutes and Lactobacillus. Furthermore, many studies in recent years have proved that the efficacy of metformin, such as improving blood glucose, depends on the gut microbiota. Coincidentally, the progression of CRC is inseparable from the contributions of gut microbiota. Therefore, we first proposed the concept of the metformin-gut microbiota–CRC (in T2DM) axis to explain the effect of metformin in reducing CRC in patients with T2DM. In this review, we elaborated the new concept and its potential clinical application value.

Teneligliptin Promotes Bile Acid Synthesis and Attenuates Lipid Accumulation in Obese Mice by Targeting the KLF15-Fgf15 Pathway

Bile acids (BAs) play essential physiological roles not only by facilitating the absorption and transport of nutrients but also by acting as a complex molecular signaling system. Reduced levels of BAs have been observed in obesity and other metabolic disorders. In the present study, we explored the effect of the dipeptidyl peptidase-4 (DPP-4) inhibitor teneligliptin on BA synthesis, both in vitro and in vivo. In our in vivo experiments, we found that teneligliptin increased the liver, ileal, and serum BA concentrations in mice undergoing teneligliptin treatment for 10 weeks. We further found that in mice fed a high-fat diet, teneligliptin prevented an increase in markers of obesity (body weight, total cholesterol, total triglyceride, adipocyte size) while increasing the total serum and ileal levels of BA. Mechanistically, teneligliptin increased BA synthesis through the alternative synthesis pathway, as the levels of both 7α-hydroxylase (CYP7A1) and sterol 27-hydroxylase (CYP27A1) along with downstream oxysterol 7α-hydroxylase (CYP7B1) but not sterol 12α-hydroxylase (CYP8B1) were increased. Importantly, teneligliptin suppressed the expression of the BA synthesis inhibitory factor Fgf15, which was mediated through phosphatidylinositol 3-kinase (PI3K)/AKT/Krüppel-like factor 15 (KLF15) signaling. Inhibition of KLF15 abolished this effect. Together, our results provide evidence of the potential benefit of teneligliptin in the treatment of metabolic disorders via increased BA production.

Metformin and Probiotics in the Crosstalk between Colitis-Associated Colorectal Cancer and Diabetes in Mice

The co-occurrence of colorectal cancer (CRC) and diabetes mellitus along with inflammation and dismicrobism has been frequently reported. Several studies shed light on the antioncogenic potential of metformin on colorectal carcinogenesis. This study aimed to demonstrate that metformin in association with probiotics acts in a synergic effect in breaking the crosstalk, thus inhibiting CRC progression, improving diabetes, and reducing inflammation. Ninety-six male Balb/c mice, 6–8 weeks old, were divided into 16 control and experimental groups to assess the effect of the different treatments and combinations at the clinical, histological, and molecular levels. Metformin and probiotics showed beneficial outcomes on CRC and diabetes, alone and most importantly in combination. Their effects were exerted by inhibiting the inflammatory process whereby a downregulation of IL-6 and TNF-α as well as oxidative stress were depicted. The characterization of the effects of probiotics and metformin on CRC and diabetes sheds light on the role of inflammation and microbiota in this crosstalk. Deciphering the downstream signaling pathways elicited by these compounds will help in developing new effective targeted treatment modalities.

Effects of Metformin on the Gut Microbiota in Obesity and Type 2 Diabetes Mellitus

Metformin is a first-line treatment for type 2 diabetes mellitus (T2DM); however, its underlying mechanism is not fully understood. Gut microbiota affect the development and progression of T2DM. In recent years, an increasing number of studies has focused on the relationship between metformin and gut microbiota, suggesting that metformin might exert part of its hypoglycemic effect through these microbes. However, most of these results were not consistent due to the complex composition of the microbiota, the differences between species, the large variation between individuals, and the differences in experimental design, bringing great obstacle for our better understanding of the effects of metformin on the gut microbiota. Here, we reviewed the published papers concerning about the impacts of metformin on the gut microbiota of mice, rats, and humans with obesity or T2DM, and summarized the changes of gut microbiota composition caused by metformin and the possible underlying hypoglycemic mechanism which is related to gut microbiota. It was found that the proportions of some microbiota, such as phyla Bacteroidetes and Verrucomicrobia and genera Akkermansia, Bacteroides and Escherichia, were significantly affected by metformin in several studies. Metformin may exert part of hypoglycemic effects by altering the gut microbiota in ways that maintain the integrity of the intestinal barrier, promote the production of short-chain fatty acids (SCFAs), regulate bile acid metabolism, and improve glucose homeostasis.

Effects of Non-insulin Anti-hyperglycemic Agents on Gut Microbiota: A Systematic Review on Human and Animal Studies

Background: As growing evidence links gut microbiota with the therapeutic efficacy and side effects of anti-hyperglycemic drugs, this article aims to provide a systematic review of the reciprocal interactions between anti-hyperglycemic drugs and gut microbiota taxa, which underlie the effect of the gut microbiome on diabetic control via bug-host interactions. Method: We followed the PRISMA requirements to perform a systematic review on human vs. animal gut microbiota data in PubMed, SCOPUS, and EMBASE databases, and used Cochrane, ROBIN-I, and SYRCLE tools to assess potential bias risks. The outcomes of assessment were trends on gut microbiota taxa, diversity, and associations with metabolic control (e.g., glucose, lipid) following anti-hyperglycemic treatment. Results: Of 2,804 citations, 64 studies (17/humans; 47/mice) were included. In human studies, seven were randomized trials using metformin or acarbose in obese, pre-diabetes, and type 2 diabetes (T2D) patients. Treatment of pre-diabetes and newly diagnosed T2D patients with metformin or acarbose was associated with decreases in genus of Bacteroides, accompanied by increases in both Bifidobacterium and Lactobacillus. Additionally, T2D patients receiving metformin showed increases in various taxa of the order Enterobacteriales and the species Akkermansia muciniphila. Of seven studies with significant differences in beta-diversity, the incremental specific taxa were associated with the improvement of glucose and lipid profiles. In mice, the effects of metformin on A. muciniphila were similar, but an inverse association with Bacteroides was reported. Animal studies on other anti-hyperglycemic drugs, however, showed substantial variations in results. Conclusions: The changes in specific taxa and β-diversity of gut microbiota were associated with metformin and acarbose in humans while pertinent information for other anti-hyperglycemic drugs could only be obtained in rodent studies. Further human studies on anti-hyperglycemic drugs other than metformin and acarbose are needed to explore gut microbiota's role in their therapeutic efficacies and side effects.