Characterization of the Gut Microbiota of Individuals at Different T2D Stages Reveals a Complex Relationship with the Host

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.

Integration of polygenic and gut metagenomic risk prediction for common diseases

Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.

Evaluation of gut microbiota predictive potential associated with phenotypic characteristics to identify multifactorial diseases

Gut microbiota has been implicated in various clinical conditions, yet the substantial heterogeneity in gut microbiota research results necessitates a more sophisticated approach than merely identifying statistically different microbial taxa between healthy and unhealthy individuals. Our study seeks to not only select microbial taxa but also explore their synergy with phenotypic host variables to develop novel predictive models for specific clinical conditions.

DESIGN

We assessed 50 healthy and 152 unhealthy individuals for phenotypic variables (PV) and gut microbiota (GM) composition by 16S rRNA gene sequencing. The entire modeling process was conducted in the R environment using the Random Forest algorithm. Model performance was assessed through ROC curve construction.

RESULTS

We evaluated 52 bacterial taxa and pre-selected PV (p < 0.05) for their contribution to the final models. Across all diseases, the models achieved their best performance when GM and PV data were integrated. Notably, the integrated predictive models demonstrated exceptional performance for rheumatoid arthritis (AUC = 88.03%), type 2 diabetes (AUC = 96.96%), systemic lupus erythematosus (AUC = 98.4%), and type 1 diabetes (AUC = 86.19%).

CONCLUSION

Our findings underscore that the selection of bacterial taxa based solely on differences in relative abundance between groups is insufficient to serve as clinical markers. Machine learning techniques are essential for mitigating the considerable variability observed within gut microbiota. In our study, the use of microbial taxa alone exhibited limited predictive power for health outcomes, while the integration of phenotypic variables into predictive models substantially enhanced their predictive capabilities.

Functional alterations and predictive capacity of gut microbiome in type 2 diabetes

The gut microbiome plays a significant role in the development of Type 2 Diabetes Mellitus (T2DM), but the functional mechanisms behind this association merit deeper investigation. Here, we used the nanopore sequencing technology for metagenomic analyses to compare the gut microbiome of individuals with T2DM from the United Arab Emirates (n = 40) with that of control (n = 44). DMM enterotyping of the cohort resulted concordantly with previous results, in three dominant groups Bacteroides (K1), Firmicutes (K2), and Prevotella (K3) lineages. The diversity analysis revealed a high level of diversity in the Firmicutes group (K2) both in terms of species richness and evenness (Wilcoxon rank-sum test, p value < 0.05 vs. K1 and K3 groups), consistent with the Ruminococcus enterotype described in Western populations. Additionally, functional enrichment analyses of KEGG modules showed significant differences in abundance between individuals with T2DM and controls (FDR < 0.05). These differences include modules associated with the degradation of amino acids, such as arginine, the degradation of urea as well as those associated with homoacetogenesis. Prediction analysis with the Predomics approach suggested potential biomarkers for T2DM, including a balance between a depletion of Enterococcus faecium and Blautia lineages with an enrichment of Absiella spp or Eubacterium limosum in T2DM individuals, highlighting the potential of metagenomic analysis in predicting predisposition to diabetic cardiomyopathy in T2DM patients.

Parabacteroides distasonis ameliorates insulin resistance via activation of intestinal GPR109a

Gut microbiota plays a key role in insulin resistance (IR). Here we perform a case-control study of Chinese adults (ChiCTR2200065715) and identify that Parabacteroides distasonis is inversely correlated with IR. Treatment with P. distasonis improves IR, strengthens intestinal integrity, and reduces systemic inflammation in mice. We further demonstrate that P. distasonis-derived nicotinic acid (NA) is a vital bioactive molecule that fortifies intestinal barrier function via activating intestinal G-protein-coupled receptor 109a (GPR109a), leading to ameliorating IR. We also conduct a bioactive dietary fiber screening to induce P. distasonis growth. Dendrobium officinale polysaccharide (DOP) shows favorable growth-promoting effects on P. distasonis and protects against IR in mice simultaneously. Finally, the reduced P. distasonis and NA levels were also validated in another human type 2 diabetes mellitus cohort. These findings reveal the unique mechanisms of P. distasonis on IR and provide viable strategies for the treatment and prevention of IR by bioactive dietary fiber.

Unveiling the potential pleiotropic effects of metformin in treating COVID-19: a comprehensive review

This review article explores the potential of metformin, a medication commonly used for type 2 diabetes, as an antiviral and anti-inflammatory agent in the context of coronavirus disease 2019 (COVID-19). Metformin has demonstrated inhibitory effects on the growth of SARS-CoV-2 in cell culture models and has shown promising results in reducing viral load and achieving undetectable viral levels in clinical trials. Additionally, metformin exhibits anti-inflammatory properties by reducing the production of pro-inflammatory cytokines and modulating immune cell function, which may help prevent cytokine storms associated with severe COVID-19. The drug's ability to regulate the balance between pro-inflammatory Th17 cells and anti-inflammatory Treg cells suggests its potential in mitigating inflammation and restoring T cell functionality. Furthermore, metformin's modulation of the gut microbiota, particularly changes in bacterial taxa and the production of short-chain fatty acids, may contribute to its therapeutic effects. The interplay between metformin, bile acids, the gut microbiome, glucagon-like peptide-1 secretion, and glycemic control has implications for the management of diabetes and potential interventions in COVID-19. By refreshing the current evidence, this review highlights the potential of metformin as a therapeutic option in the management of COVID-19, while also exploring its effects on the gut microbiome and immunometabolism.

Associations between Metabolomic Biomarkers of Avocado Intake and Glycemia in the Multi-Ethnic Study of Atherosclerosis

BACKGROUND

Avocado consumption is linked to better glucose homeostasis, but small associations suggest potential population heterogeneity. Metabolomic data capture the effects of food intake after digestion and metabolism, thus accounting for individual differences in these processes.

OBJECTIVES

To identify metabolomic biomarkers of avocado intake and to examine their associations with glycemia.

METHODS

Baseline data from 6224 multi-ethnic older adults (62% female) included self-reported avocado intake, fasting glucose and insulin, and untargeted plasma proton nuclear magnetic resonance metabolomic features (metabolomic data were available for a randomly selected subset; N = 3438). Subsequently, incident type 2 diabetes (T2D) was assessed over an ∼18 y follow-up period. A metabolome-wide association study of avocado consumption status (consumer compared with nonconsumer) was conducted, and the relationship of these features with glycemia via cross-sectional associations with fasting insulin and glucose and longitudinal associations with incident T2D was examined.

RESULTS

Three highly-correlated spectral features were associated with avocado intake at metabolome-wide significance levels (P < 5.3 ∗ 10-7) and combined into a single biomarker. We did not find evidence that these features were additionally associated with overall dietary quality, nor with any of 47 other food groups (all P > 0.001), supporting their suitability as a biomarker of avocado intake. Avocado intake showed a modest association only with lower fasting insulin (β = -0.07 +/- 0.03, P = 0.03), an association that was attenuated to nonsignificance when additionally controlling for body mass index (kg/m2). However, our biomarker of avocado intake was strongly associated with lower fasting glucose (β = -0.22 +/- 0.02, P < 2.0 ∗ 10-16), lower fasting insulin (β = -0.17 +/- 0.02, P < 2.0 ∗ 10-16), and a lower incidence of T2D (hazard ratio: 0.68; 0.63-074, P < 2.0 ∗ 10-16), even when adjusting for BMI.

CONCLUSIONS

Highly significant associations between glycemia and avocado-related metabolomic features, which serve as biomarkers of the physiological impact of dietary intake after digestion and absorption, compared to modest relationships between glycemia and avocado consumption, highlights the importance of considering individual differences in metabolism when considering diet-health relationships.

Outer membrane vesicles derived from gut microbiota mediate tubulointerstitial inflammation: a potential new mechanism for diabetic kidney disease

Rationale: Chronic tubulointerstitial inflammation is a common pathological process in diabetic kidney disease (DKD). However, its underlying mechanism is largely unknown. This study aims at investigating the role of gut microbiota-derived outer membrane vesicles (OMVs) in tubulointerstitial inflammation in DKD. Methods: Gut microbiota in diabetes mellitus rats was manipulated by microbiota depletion and fecal microbiota transplantation to explore its role in tubulointerstitial inflammation. To check the direct effects of OMVs, fecal bacterial extracellular vesicles (fBEVs) were administrated to mice orally and HK-2 cells in vitro. For mechanistic investigations, HK-2 cells were treated with small interfering RNA against caspase-4 and fBEVs pre-neutralized by polymyxin B. Results: By performing gut microbiota manipulation, it was confirmed that gut microbiota mediated tubulointerstitial inflammation in DKD. In diabetic rats, gut microbiota-derived OMVs were increased and were clearly detected in distant renal tubulointerstitium. Diabetic fBEVs directly administered by gavage translocated into tubular epithelial cells and induced tubulointerstitial inflammation and kidney injury. In vitro, OMVs were internalized through various endocytic pathways and triggered cellular inflammatory response. Mechanistically, it was revealed that OMVs-derived lipopolysaccharide induced tubular inflammation, which was mediated by the activation of the caspase-11 pathway. Conclusions: Increased OMVs due to dysbiosis translocated through leaky gut barrier into distant tubulointerstitium and induced cellular inflammation and renal tubulointerstitial injury in DKD. These findings enrich the mechanism understanding of how gut microbiota and its releasing OMVs influence the development and progression of kidney disease.

The F/B ratio as a biomarker for inflammation in COVID-19 and T2D: Impact of metformin

The pandemic of COVID-19 has highlighted the intricate relationship between gut microbiome and overall health. Recent studies have shown that the Firmicutes/Bacteroidetes ratio in the gut microbiome may be linked to various diseases including COVID-19 and type 2 diabetes (T2D). Understanding the link between gut microbiome and these diseases is essential for developing strategies for prevention and treatment. In this study, 115 participants were recruited and divided into three groups: 1st group: T2D patients and healthy controls, 2nd group: COVID-19 patients with and without T2D, 3rd group: T2D patients with COVID-19 treated with or without metformin. Gut microbial composition at the phylum level was assessed using qRT-PCR with universal primers targeting the bacterial 16 S rRNA gene and specific primers for Firmicutes and Bacteroidetes. Data was analyzed using one-way ANOVA, logistic regression, and Spearman's rank correlation coefficient. The study found that the ratio of Firmicutes to Bacteroidetes (F/B) was higher in patients with both T2D and COVID-19 compared to those with only T2D or COVID-19. Additionally, the F/B ratio was positively correlated with C-reactive protein (CRP) in T2D and COVID-19 patients. The study also suggests that metformin treatment may affect this correlation. Logistic regression analysis showed that the F/B ratio was significantly associated with CRP. These findings suggest that the F/B ratio may be a potential biomarker for inflammation in T2D and COVID-19 patients and metformin treatment may have an effect on the correlation between F/B and CRP levels.

Sleep and probiotics in diabetes management

In this manuscript, we call attention to the importance of investigating affordable strategies to improve the management of diabetes. Studies indicate that imbalances in the gut microbiota may lead to the development and progression of this disease. At the same time, poor sleep and sleep disorders, which are very prevalent in individuals with diabetes, can be related to a worse prognosis for the disease and can be impacted by changes in the intestinal microbiome. A suggested treatment that may be effective in controlling diabetes and improving sleep quality through increased metabolic regulation is probiotic supplementation. Scientific evidence has shown a relationship between the use of probiotics and improvements in sleep, in glucose concentrations, and in the levels of high density lipoprotein cholesterol. We suggest that probiotic supplementation can play an important role in the management of diabetes and sleep disorders in diabetic patients. Further randomized clinical studies should be undertaken to better understand the impact and effectiveness of the use of probiotics in improving sleep and controlling diabetes.

Role of the Gut Microbiome in the Development of Atherosclerotic Cardiovascular Disease

Atherosclerotic cardiovascular disease (ASCVD) is the primary cause of death globally, with nine million deaths directly attributable to ischemic heart diseases in 2020. Since the last few decades, great effort has been put toward primary and secondary prevention strategies through identification and treatment of major cardiovascular risk factors, including hypertension, diabetes, dyslipidemia, smoking, and a sedentary lifestyle. Once labelled “the forgotten organ”, the gut microbiota has recently been rediscovered and has been found to play key functions in the incidence of ASCVD both directly by contributing to the development of atherosclerosis and indirectly by playing a part in the occurrence of fundamental cardiovascular risk factors. Essential gut metabolites, such as trimethylamine N-oxide (TMAO), secondary bile acids, lipopolysaccharides (LPS), and short-chain fatty acids (SCFAs), have been associated with the extent of ischemic heart diseases. This paper reviews the latest data on the impact of the gut microbiome in the incidence of ASCVD.

The predicted mechanisms and evidence of probiotics on type 2 diabetes mellitus (T2DM)

Type 2 diabetes mellitus (T2DM) is a serious endocrine and metabolic disease that is highly prevalent and causes high mortality and morbidity rates worldwide. This review aims to focus on the potential of probiotics in the management of T2DM and its complications and to summarise the various mechanisms of action of probiotics with respect to T2DM. In this review, experimental studies conducted between 2016 and 2022 were explored. The possible mechanisms of action are based on their ability to modulate the gut microbiota, boost the production of short-chain fatty acids (SCFAs) and glucagon-like peptides, inhibit α-glucosidase, elevate sirtuin 1 (SIRT1) levels while reducing fetuin-A levels, and regulate the level of inflammatory cytokines. This review recommends carrying out further studies, especially human trials, to provide robust evidence-based knowledge on the use of probiotics for the treatment of T2DM.IMPACT STATEMENTT2DM is prevalent worldwide causing high rates of morbidity and mortality.Gut microbiota play a significant role in the pathogenesis of T2DM.Probiotics can be used as possible therapeutic tools for the management of T2DM.The possible mechanisms of action of probiotics include modulation of the gut microbiota, production of SCFAs and glucagon-like peptides, inhibition of α-glucosidase, raising SIRT1, reducing fetuin-A levels, and regulating the level of inflammatory cytokines.

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.

Alterations of the gut microbiota in type 2 diabetics with or without subclinical hypothyroidism

Background

Diabetes and thyroid dysfunction are two closely related endocrine diseases. Increasing evidences show that gut microbiota plays an important role in both glucose metabolism and thyroid homeostasis. Meanwhile, copy number variation (CNV) of host salivary α-amylase gene (AMY1) has been shown to correlate with glucose homeostasis. Hence, we aim to characterize the gut microbiota and CNV of AMY1 in type 2 diabetes (T2D) patients with or without subclinical hypothyroidism (SCH).

Methods

High-throughput sequencing was used to analyze the gut microbiota of euthyroid T2D patients, T2D patients with SCH and healthy controls. Highly sensitive droplet digital PCR was used to measure AMY1 CN.

Results

Our results revealed that T2D patients have lower gut microbial diversity, no matter with or without SCH. The characteristic taxa of T2D patients were Coriobacteriales, Coriobacteriaceae, Peptostreptococcaceae, Pseudomonadaceae, Collinsella, Pseudomonas and Romboutsia. Meanwhile, Escherichia/Shigella, Lactobacillus_Oris, Parabacteroides Distasonis_ATCC_8503, Acetanaerobacterium, Lactonifactor, uncultured bacterium of Acetanaerobacterium were enriched in T2D patients with SCH. Moreover, serum levels of free triiodothyronine (FT3) and free thyroxine (FT4) in T2D patients were both negatively correlated with richness of gut microbiota. A number of specific taxa were also associated with clinical parameters at the phylum and genus level. In contrast, no correlation was found between AMY1 CN and T2D or T2D_SCH.

Conclusion

This study identified characteristic bacterial taxa in gut microbiota of T2D patients with or without SCH, as well as the taxa associated with clinical indices in T2D patients. These results might be exploited in the prevention, diagnosis and treatment of endocrine disorders in the future.

Gut Microbiota Associated with Gestational Health Conditions in a Sample of Mexican Women

Gestational diabetes (GD), pre-gestational diabetes (PD), and pre-eclampsia (PE) are morbidities affecting gestational health which have been associated with dysbiosis of the mother's gut microbiota. This study aimed to assess the extent of change in the gut microbiota diversity, short-chain fatty acids (SCFA) production, and fecal metabolites profile in a sample of Mexican women affected by these disorders. Fecal samples were collected from women with GD, PD, or PE in the third trimester of pregnancy, along with clinical and biochemical data. Gut microbiota was characterized by high-throughput DNA sequencing of V3-16S rRNA gene libraries; SCFA and metabolites were measured by High-Pressure Liquid Chromatography (HPLC) and (Fourier Transform Ion Cyclotron Mass Spectrometry (FT-ICR MS), respectively, in extracts prepared from feces. Although the results for fecal microbiota did not show statistically significant differences in alfa diversity for GD, PD, and PE concerning controls, there was a difference in beta diversity for GD versus CO, and a high abundance of Proteobacteria, followed by Firmicutes and Bacteroidota among gestational health conditions. DESeq2 analysis revealed bacterial genera associated with each health condition; the Spearman's correlation analyses showed selected anthropometric, biochemical, dietary, and SCFA metadata associated with specific bacterial abundances, and although the HPLC did not show relevant differences in SCFA content among the studied groups, FT-ICR MS disclosed the presence of interesting metabolites of complex phenolic, valeric, arachidic, and caprylic acid nature. The major conclusion of our work is that GD, PD, and PE are associated with fecal bacterial microbiota profiles, with distinct predictive metagenomes.

Fufang Fanshiliu Decoction Revealed the Antidiabetic Effect through Modulating Inflammatory Response and Gut Microbiota Composition

Background

Diabetes mellitus brings serious threats and financial burdens to human beings worldwide. Fufang Fanshiliu decoction (FFSLD), a traditional Chinese medicine formula showing great antidiabetic effects, has been used in clinics for many years.

Objective

This study aims to explore the underlying therapeutic mechanisms of FFSLD in Type II diabetes mellitus (T2DM).

Methods

Sprague–Dawley rats induced by high-fat diet feeding combined with streptozotocin injection were used to establish the T2DM model. All rats were randomly divided into 6 groups: control, model, metformin, high dosage, middle dosage, and low dosage of FFSLD. After 4 weeks of treatment, serum, intestinal mucosa, and fecal samples were collected for further analysis. ELISA was used to detect the diabetic-related serum indicators and proinflammation cytokines. Gene or protein expressions of mitogen-activated protein kinase (MAPK), interleukin 1 beta (IL-1β), transforming growth factor-beta (TGF-β), and tumor necrosis factor-alpha (TNF-α) in intestinal mucosa were analyzed by quantitative real-time polymerase chain reaction (RT-PCR) or western blot. 16s rRNA gene sequencing was used to detect the changes of gut microbiome in these groups. Intestinal gut microbiota (GM) composition was further analyzed according to the sequencing libraries.

Results

FFSLD effectively recovered the diabetic-related biochemical indexes by reducing fasting blood glucose (FBG), total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), insulin, and increasing high-density lipoprotein cholesterol (HDL-C). Furthermore, FFSLD significantly ameliorated the abnormal levels of proinflammation cytokines including IL-1β, IL-6, TNF-α, and TGF-β. In addition, the GM compositions of rats in control, model, and FFSLD treated groups were different. FFSLD significantly increased the relative abundance of Lactobacillus, Akkermansia, and Proteus, and reduced the relative abundance of Alistipes, Desulfovibrio, and Helicobacter. Moreover, these changed bacteria were closely related to the diabetic-related serum indicators and proinflammatory cytokines.

Conclusion

These results suggest that FFSLD alleviates diabetic symptoms in T2DM rats through regulating GM composition and inhibiting inflammatory response, which clarify the therapeutic mechanism of FFSLD on T2DM and provide a theoretical basis for its further clinical application.

Gut Microbiota Composition in Prediabetes and Newly Diagnosed Type 2 Diabetes: A Systematic Review of Observational Studies

Evidence of gut microbiota involvement in regulating glucose metabolism and type 2 diabetes mellitus (T2DM) progression is accumulating. The understanding of microbial dysbiosis and specific alterations of gut microbiota composition that occur during the early stages of glucose intolerance, unperturbed by anti-diabetic medications, is especially essential. Hence, this systematic review was conducted to summarise the existing evidence related to microbiota composition and diversity in individuals with prediabetes (preDM) and individuals newly diagnosed with T2DM (newDM) in comparison to individuals with normal glucose tolerance (nonDM). A systematic search of the PubMed, MEDLINE and CINAHL databases were conducted from inception to February 2021 supplemented with manual searches of the list of references. The primary keywords of “type 2 diabetes”, “prediabetes”, “newly-diagnosed” and “gut microbiota” were used. Observational studies that conducted analysis of the gut microbiota of respondents with preDM and newDM were included. The quality of the studies was assessed using the modified Newcastle-Ottawa scale by independent reviewers. A total of 18 studies (5,489 participants) were included. Low gut microbial diversity was generally observed in preDM and newDM when compared to nonDM. Differences in gut microbiota composition between the disease groups and nonDM were inconsistent across the included studies. Four out of the 18 studies found increased abundance of phylum Firmicutes along with decreased abundance of Bacteroidetes in newDM. At the genus/species levels, decreased abundance of Faecalibacterium prausnitzii, Roseburia, Dialister, Flavonifractor, Alistipes, Haemophilus and Akkermansia muciniphila and increased abundance of Lactobacillus, Streptococcus, Escherichia, Veillonella and Collinsella were observed in the disease groups in at least two studies. Lactobacillus was also found to positively correlate with fasting plasma glucose (FPG), HbA1c and/or homeostatic assessment of insulin resistance (HOMA-IR) in four studies. This renders a need for further investigations on the species/strain-specific role of endogenously present Lactobacillus in glucose regulation mechanism and T2DM disease progression. Differences in dietary intake caused significant variation in specific bacterial abundances. More studies are needed to establish more consistent associations, between clinical biomarkers or dietary intake and specific gut bacterial composition in prediabetes and early T2DM.

Impact of Geographical Location on the Gut Microbiota Profile in Egyptian Children with Type 1 Diabetes Mellitus: A Pilot Study

Purpose

To investigate the compositional and functional characteristics of T1DM-associated gut microbiota in two Egyptian cities and to study the geographical locality effects.

Patients and Methods

This case-control study included 32 children with controlled T1DM and 16 controls, selected from two different regions of Egypt. The gut microbiota of both diabetic and control children was analyzed through 16S rRNA gene sequencing; this was done using the Illumina MiSeq platform.

Results

Consistent findings among the diabetic children included significantly lower alpha diversity than the control children, as well as a lower mean Firmicutes/Bacteroidetes (F/B) ratio, and reduced proportions of Firmicutes and the genera Prevotella and Ruminococcus. In the diabetic children, there were also significantly enriched representations of Actinobacteria, Bacteroidetes, and Proteobacteria and the genera Lactobacilli, Bacteroides, and Faecalibacterium. When comparing the two diabetic groups, the Ismailia group (IsDM) was found to have a significantly higher F/B ratio and diversity indices, with resultant differences at the functional level.

Conclusion

There are a number of consistent changes in the microbiota profile characterizing the diabetic groups irrespective of the geographical location including significantly lower alpha diversity, mean Firmicutes/ Bacteroidetes (F/B) ratio, and reduced proportions of Firmicutes and genera Prevotella and Ruminococcus. There are also significantly enriched representations of Actinobacteria, Bacteroidetes, and Proteobacteria and genera Lactobacilli, Bacteroides, and Faecalibacterium pointing to the greater driving power of the disease.

Microbiome risk profiles as biomarkers for inflammatory and metabolic disorders

The intestine harbours a complex array of microorganisms collectively known as the gut microbiota. The past two decades have witnessed increasing interest in studying the gut microbiota in health and disease, largely driven by rapid innovation in high-throughput multi-omics technologies. As a result, microbial dysbiosis has been linked to many human pathologies, including type 2 diabetes mellitus and inflammatory bowel disease. Integrated analyses of multi-omics data, including metagenomics and metabolomics along with measurements of host response and cataloguing of bacterial isolates, have identified many bacteria and bacterial products that are correlated with disease. Nevertheless, insight into the mechanisms through which microbes affect intestinal health requires going beyond correlation to causation. Current understanding of the contribution of the gut microbiota to disease causality remains limited, largely owing to the heterogeneity of microbial community structures, interindividual differences in disease evolution and incomplete understanding of the mechanisms that integrate microbiota-derived signals into host signalling pathways. In this Review, we provide a broad insight into the microbiome signatures linked to inflammatory and metabolic disorders, discuss outstanding challenges in this field and propose applications of multi-omics technologies that could lead to an improved mechanistic understanding of microorganism-host interactions.

Reconstruction of intestinal microecology of type 2 diabetes by fecal microbiota transplantation: Why and how

Type 2 diabetes (T2D) is a chronic metabolic disease characterized by hyperglycemia due to insulin resistance. Mounting evidence has correlated T2D to alterations in the composition of gut microbiota. Accordingly, targeting the gut microbiota has become an emerging strategy for T2D management. The aim of this article is to get a better insight into the rationale for targeting gut microbiota in T2D treatment. Thus, we herein reviewed the change of gut microbiota composition in T2D, factors shaping gut microbiota, and potential mechanisms behind the contribution of gut microbiota to T2D pathogenesis. At present, it has become possible to use intestinal microorganism capsules, bacteria liquid, and other preparations to carry out fecal microbiota transplantation for the treatment and intervention of T2D with insulin resistance and immune-mediated type 1 diabetes (T1D).

Immunoregulatory Intestinal Microbiota and COVID-19 in Patients with Type Two Diabetes: A Double-Edged Sword

Coronavirus disease 2019, or COVID-19, is a major challenge facing scientists worldwide. Alongside the lungs, the system of organs comprising the GI tract is commonly targeted by COVID-19. The dysbiotic modulations in the intestine influence the disease severity, potentially due to the ability of the intestinal microbiota to modulate T lymphocyte functions, i.e., to suppress or activate T cell subpopulations. The interplay between the lungs and intestinal microbiota is named the gut-lung axis. One of the most usual comorbidities in COVID-19 patients is type 2 diabetes, which induces changes in intestinal microbiota, resulting in a pro-inflammatory immune response, and consequently, a more severe course of COVID-19. However, changes in the microbiota in this comorbid pathology remain unclear. Metformin is used as a medication to treat type 2 diabetes. The use of the type 2 diabetes drug metformin is a promising treatment for this comorbidity because, in addition to its hypoglycemic action, it can increase amount of intestinal bacteria that induce regulatory T cell response. This dual activity of metformin can reduce lung damage and improve the course of the COVID-19 disease.

Metformin: Expanding the Scope of Application-Starting Earlier than Yesterday, Canceling Later

Today the area of application of metformin is expanding, and a wealth of data point to its benefits in people without carbohydrate metabolism disorders. Already in the population of people leading an unhealthy lifestyle, before the formation of obesity and prediabetes metformin smooths out the adverse effects of a high-fat diet. Being prescribed at this stage, metformin will probably be able to, if not prevent, then significantly reduce the progression of all subsequent metabolic changes. To a large extent, this review will discuss the proofs of the evidence for this. Another recent important change is a removal of a number of restrictions on its use in patients with heart failure, acute coronary syndrome and chronic kidney disease. We will discuss the reasons for these changes and present a new perspective on the role of increasing lactate in metformin therapy.

Gut Microbiota: An Important Player in Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is one of the common metabolic diseases in the world. Due to the rise in morbidity and mortality, it has become a global health problem. To date, T2DM still cannot be cured, and its intervention measures mainly focus on glucose control as well as the prevention and treatment of related complications. Interestingly, the gut microbiota plays an important role in the development of metabolic diseases, especially T2DM. In this review, we introduce the characteristics of the gut microbiota in T2DM population, T2DM animal models, and diabetic complications. In addition, we describe the molecular mechanisms linking host and the gut microbiota in T2DM, including the host molecules that induce gut microbiota dysbiosis, immune and inflammatory responses, and gut microbial metabolites involved in pathogenesis. These findings suggest that we can treat T2DM and its complications by remodeling the gut microbiota through interventions such as drugs, probiotics, prebiotics, fecal microbiota transplantation (FMT) and diets.

Antidiabetic Effects of Pediococcus acidilactici pA1c on HFD-Induced Mice

Prediabetes (PreD), which is associated with impaired glucose tolerance and fasting blood glucose, is a potential risk factor for type 2 diabetes mellitus (T2D). Growing evidence suggests the role of the gastrointestinal microbiota in both PreD and T2D, which opens the possibility for a novel nutritional approach, based on probiotics, for improving glucose regulation and delaying disease progression of PreD to T2D. In this light, the present study aimed to assess the antidiabetic properties of Pediococcus acidilactici (pA1c) in a murine model of high-fat diet (HFD)-induced T2D. For that purpose, C57BL/6 mice were given HFD enriched with either probiotic (1 × 10¹⁰ CFU/day) or placebo for 12 weeks. We determined body weight, fasting blood glucose, glucose tolerance, HOMA-IR and HOMA-β index, C-peptide, GLP-1, leptin, and lipid profile. We also measured hepatic gene expression (G6P, PEPCK, GCK, IL-1β, and IL-6) and examined pancreatic and intestinal histology (% of GLP-1⁺ cells, % of goblet cells and villus length). We found that pA1c supplementation significantly attenuated body weight gain, mitigated glucose dysregulation by reducing fasting blood glucose levels, glucose tolerance test, leptin levels, and insulin resistance, increased C-peptide and GLP-1 levels, enhanced pancreatic function, and improved intestinal histology. These findings indicate that pA1c improved HFD-induced T2D derived insulin resistance and intestinal histology, as well as protected from body weight increase. Together, our study proposes that pA1c may be a promising new dietary management strategy to improve metabolic disorders in PreD and T2D.

A Combined Supplement of Probiotic Strains AP-32, bv-77, and CP-9 Increased Akkermansia mucinphila and Reduced Non-Esterified Fatty Acids and Energy Metabolism in HFD-Induced Obese Rats

Obesity is referred to as a condition in which excess body fat has accumulated to an extent that it causes negative impacts on health. The formation of body fat is regulated by complicated networks in relation to energy metabolism, and gut microbiota have been regarded as a key player. Studies have shown that supplements of probiotics provide benefits to health, including an improvement in metabolic syndrome and the control of body weight. In the present study, three probiotic strains, AP-32, bv-77, and CP-9, stood out from nine candidates using a lipid consumption assay, and were subsequently introduced to further animal tests. A rodent model of obesity was induced by a high-fat diet (HFD) in Sprague-Dawley (SD) rats, and three probiotic strains were administered either separately or in a mixture. A low dose (5 × 10⁹ CFU/kg/day) and a high dose (2.5 × 10¹⁰ CFU/kg/day) of probiotics were orally provided to obese rats. The bioeffects of the probiotic supplements were evaluated based on five aspects: (1) the body weight and growth rate; (2) ketone bodies, non-esterified fatty acids (NEFAs), and feed efficiency; (3) blood biochemistry; (4) fat content; and (5) gut microbiota composition. Our results demonstrated that the supplement of AP-32, CP-9, and bv-77 alleviated the increasing rate of body weight and prevented the elevation of NEFAs and ketone bodies in obese rats. Although the effect on fat content showed a minor improvement, the supplement of probiotics displayed significant improvements in HFD-induced poor blood biochemical characteristics, such as alanine aminotransferase (ALT), aspartate Transaminase (AST), and uric acid, within 4 weeks. Furthermore, the combined supplement of three strains significantly increased Akkermansia mucinphila as compared with three individual strains, while its enrichment was negatively correlated with NEFAs and energy metabolism. In general, a mixture of three probiotic strains delivered a better outcome than a single strain, and the high dose of supplements provided a more profound benefit than the low dose. In conclusion, three probiotic strains, AP-32, bv-77, and CP-9, can alleviate body fat formation in obese rats. Furthermore, a combined supplement of these three probiotic strains may have potential in treating or controlling metabolic disorders.

Tang-Ping-San Decoction Remodel Intestinal Flora and Barrier to Ameliorate Type 2 Diabetes Mellitus in Rodent Model

PURPOSE

Type 2 diabetes mellitus (T2DM) is a complex genetic disease associated with genetic and environmental factors. Previous studies have shown that changes in the gut microbiota may affect the development of host metabolic diseases and promote the progression of T2DM. Tang-ping-san (TPS) decoction can effectively treat T2DM. However, its specific mechanisms must be evaluated.

PATIENTS AND METHODS

In the present study, we established an animal model of T2DM using a high‑fat diet (HFD) with intraperitoneal injection streptozotocin injection.

RESULTS

The therapeutic effect of TPS decoction on T2DM in mice was initially evaluated. TPS decoction was found to improve hyperglycemia, hyperlipidemia, insulin resistance, and pathological liver, pancreatic, and colon changes. Moreover, it reduced the pro-inflammatory cytokine levels. Based on 16SrRNA sequencing, TPS decoction reduced the Firmicutes/Bacteroidetes ratio at the phylum level. At the genus level, it increased the relative abundances of Akkermansia, Muribaculaceae, and the Eubacterium coprostanoligenes group and decreased the relative abundance of Fusobacterium, Escherichia coli, Dubosiella, and Helicobacter.

CONCLUSION

TPS decoction improves T2DM and liver function and reduces the risk of hyperglycemia, hyperlipidemia, insulin resistance, pathological organ changes, and inflammatory reactions. The mechanism of TPS decoction in T2DM can be correlated with the reversal of gut microbiota dysfunction and repair of the intestinal mucosal barrier.

Are There Differences in Gut Microbiome in Patients with Type 2 Diabetes Treated by Metformin or Metformin and Insulin?

INTRODUCTION

Recently, gut microbiota has been described as being involved in the health and diseases of the host, and together with diet and drugs may influence metabolic health. Yet, there is still no answer which type of treatment plays the most important role in the interplay of gut microbiota and type of treatment for type 2 diabetes (T2DM). An attempt was made to answer the question of which factors have the most significant impact on the intestinal microbiome in the context of metformin or metformin+insulin use in treatment of the patients with T2DM. Thus the aim of the study was to compare the gut microbiome profiles of patients with T2DM and two of the most traditional treatment methods.

METHODS

T2DM patients treated by metformin (Met) and metformin+insulin (Met+Ins), with the treatment duration of 5-10 years were enrolled. Biochemically blood glucose and glycated hemoglobin (HbA1c), lipids and kidney function were investigated and the quantitative and qualitative examination of the fecal intestinal flora were performed through the next-generation sequencing.

RESULTS

There were no significant differences in the study of the gut microbiome: the dominant bacterial phyla were Firmicutes and Verrucomicrobia, while Bacteroidetes and Proteobacteria shared smaller proportions in both groups. However, the group Met+Ins had worse metabolic control in terms of blood glucose and HbA1c in comparison with the Met group.

CONCLUSION

As there are no differences in gut microbiome in T2DM patients treated with metformin only or metformin plus insulin, adding insulin in the treatment of T2DM may delay late diabetic complications development.

Pi-Dan-Jian-Qing Decoction Ameliorates Type 2 Diabetes Mellitus Through Regulating the Gut Microbiota and Serum Metabolism

Pi-Dan-Jian-Qing decoction (PDJQ) can been used in the treatment of type 2 diabetes mellitus (T2DM) in clinic. However, the protective mechanisms of PDJQ on T2DM remain unknown. Recent studies have shown that the changes in gut microbiota could affect the host metabolism and contribute to progression of T2DM. In this study, we first investigated the therapeutic effects of PDJQ on T2DM rats. 16S rRNA sequencing and untargeted metabolomics analyses were used to investigate the mechanisms of action of PDJQ in the treatment of T2DM. Our results showed that PDJQ treatment could improve the hyperglycemia, hyperlipidemia, insulin resistance (IR) and pathological changes of liver, pancreas, kidney, and colon in T2DM rats. PDJQ could also decrease the levels of pro-inflammatory cytokines and inhibit the oxidative stress. 16S rRNA sequencing showed that PDJQ could decrease the Firmicutes/Bacteroidetes (F to B) ratio at the phylum level. At the genus level, PDJQ could increase the relative abundances of Lactobacillus, Blautia, Bacteroides, Desulfovibrio and Akkermansia and decrease the relative abundance of Prevotella. Serum untargeted metabolomics analysis showed that PDJQ could regulate tryptophan metabolism, histidine metabolism, tricarboxylic acid (TCA) cycle, phenylalanine, tyrosine and tryptophan biosynthesis and tyrosine metabolism pathways. Correlation analysis indicated that the modulatory effects of PDJQ on the tryptophan metabolism, histidine metabolism and TCA cycle pathways were related to alterations in the abundance of Lactobacillus, Bacteroides and Akkermansia. In conclusion, our study revealed the various ameliorative effects of PDJQ on T2DM, including improving the liver and kidney functions and alleviating the hyperglycemia, hyperlipidemia, IR, pathological changes, oxidative stress and inflammatory response. The mechanisms of PDJQ on T2DM are likely linked to an improvement in the dysbiosis of gut microbiota and modulation of tryptophan metabolism, histamine metabolism, and the TCA cycle.

Gut microbiota in a population highly affected by obesity and type 2 diabetes and susceptibility to COVID-19

Coronavirus disease 2019 (COVID-19) is a disease produced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and it is currently causing a catastrophic pandemic affecting humans worldwide. This disease has been lethal for approximately 3.12 million people around the world since January 2020. Globally, among the most affected countries, Mexico ranks third in deaths after the United States of America and Brazil. Although the high number of deceased people might also be explained by social aspects and lifestyle customs in Mexico, there is a relationship between this high proportion of deaths and comorbidities such as high blood pressure (HBP), type 2 diabetes, obesity, and metabolic syndrome. The official epidemiological figures reported by the Mexican government have indicated that 18.4% of the population suffers from HBP, close to 10.3% of adults suffer from type 2 diabetes, and approximately 36.1% of the population suffers from obesity. Disbalances in the gut microbiota (GM) have been associated with these diseases and with COVID-19 severity, presumably due to inflammatory dysfunction. Recent data about the association between GM dysbiosis and metabolic diseases could suggest that the high levels of susceptibility to SARS-CoV-2 infection and COVID-19 morbidity in the Mexican population are primarily due to the prevalence of type 2 diabetes, obesity, and metabolic syndrome.

Gut Bacterial Characteristics of Patients With Type 2 Diabetes Mellitus and the Application Potential

Type 2 diabetes mellitus (T2DM) is a complex disorder comprehensively influenced by genetic and environmental risk, and research increasingly has indicated the role of microbial dysbiosis in T2DM pathogenesis. However, studies comparing the microbiome characteristics between T2DM and healthy controls have reported inconsistent results. To further identify and describe the characteristics of the intestinal flora of T2DM patients, we performed a systematic review and meta-analysis of stool microbial profiles to discern and describe microbial dysbiosis in T2DM and to explore heterogeneity among 7 studies (600 T2DM cases, 543 controls, 1143 samples in total). Using a random effects model and a fixed effects model, we observed significant differences in beta diversity, but not alpha diversity, between individuals with T2DM and controls. We identified various operational taxonomic unit (OTUs) and bacterial genera with significant odds ratios for T2DM. The T2DM signatures derived from a single study by stepwise feature selection could be applied in other studies. By training on multiple studies, we improved the detection accuracy and disease specificity for T2DM. We also discuss the relationship between T2DM-enriched or T2DM-depleted genera and probiotics and provide new ideas for diabetes prevention and improvement.

The Role of the Gut Microbiome in Diabetes and Obesity-Related Kidney Disease

Diabetic kidney disease (DKD) is a progressive disorder, which is increasing globally in prevalence due to the increased incidence of obesity and diabetes mellitus. Despite optimal clinical management, a significant number of patients with diabetes develop DKD. Hence, hitherto unrecognized factors are likely to be involved in the initiation and progression of DKD. An extensive number of studies have demonstrated the role of microbiota in health and disease. Dysregulation in the microbiota resulting in a deficiency of short chain fatty acids (SCFAs) such as propionate, acetate, and butyrate, by-products of healthy gut microbiota metabolism, have been demonstrated in obesity, type 1 and type 2 diabetes. However, it is not clear to date whether such changes in the microbiota are causative or merely associated with the diseases. It is also not clear which microbiota have protective effects on humans. Few studies have investigated the centrality of reduced SCFA in DKD development and progression or the potential therapeutic effects of supplemental SCFAs on insulin resistance, inflammation, and metabolic changes. SCFA receptors are expressed in the kidneys, and emerging data have demonstrated that intestinal dysbiosis activates the renal renin-angiotensin system, which contributes to the development of DKD. In this review, we will summarize the complex relationship between the gut microbiota and the kidney, examine the evidence for the role of gut dysbiosis in diabetes and obesity-related kidney disease, and explore the mechanisms involved. In addition, we will describe the role of potential therapies that modulate the gut microbiota to prevent or reduce kidney disease progression.

Gut Microbiota in Bone Health and Diabetes

PURPOSE OF REVIEW

Patients with diabetes mellitus (DM) are at increased risk of developing osteopathogenesis and skeletal fragility. The role of the gut microbiota in both DM and osteopathy is not fully explored and may be involved in the pathology of both diseases.

RECENT FINDINGS

Gut microbiota alterations have been observed in DM and osteopathogenic disorders as compared with healthy controls, such as significantly lower abundance of Prevotella and higher abundance of Lactobacillus, with a diminished bacterial diversity. Other overlapping gastro-intestinal features include the loss of intestinal barrier function with translocation of bacterial metabolites to the blood stream, induction of immunological deficits and changes in hormonal and endocrinal signalling, which may lead to the development of diabetic osteopathy. Signalling pathways involved in both DM and osteopathy are affected by gut bacteria and their metabolites. Future studies should focus on gut microbiota involvement in both diseases.

Multi-strain probiotic supplement attenuates streptozotocin-induced type-2 diabetes by reducing inflammation and β-cell death in rats

Probiotics are health beneficial bacterial populations colonizing the human gut and skin. Probiotics are believed to be involved in immune system regulation, gut microbiota stabilization, prevention of infectious diseases, and adjustments of host metabolic activities. Probiotics such as Lactobacillus and Bifidobacterium affect glycemic levels, blood lipids, and protein metabolism. However, the interactions between probiotics and metabolic diseases as well as the underlying mechanisms remain unclear. We used streptozotocin (STZ)-induced diabetic animal models to study the effect of Probioglu^TM, a multi-strain probiotic supplement including Lactobaccilus salivarius subsp. salicinius AP-32, L. johnsonii MH-68, L. reuteri GL-104, and Bifidobacterium animalis subsp. lactis CP-9, on the regulation of physiochemical parameters related to type-2 diabetes. Experimental rats were randomly assigned into five groups, control group, streptozotocin (STZ)-treated rats (STZ group), STZ + 1× Probioglu^TM group, STZ + 5× Probioglu^TM group, and STZ + 10× Probioglu^TM group, and physiological data were measured at weeks 0, 2, 4, 6, and 8. Our results indicate that supplementation with Probioglu^TM significantly improved glucose tolerance, glycemic levels, insulin levels, and insulin resistance (HOMA-IR). Furthermore, we observed reduction in urea and blood lipid levels, including low-density lipoprotein (LDL), triglycerides (TG), and total cholesterol (TC). Probioglu^TM administration increased the β-cell mass in STZ-induced diabetic animal models, whereas it reduced the levels of proinflammatory cytokines TNF-α, IL-6, and IL-1β. In addition, the enhancement of oxidative stress biomarkers and superoxide dismutase (SOD) activities was associated with a decrease in malondialdehyde (MDA) levels. We conclude that Probioglu^TM attenuates STZ-induced type-2 diabetes by protecting β-cells, stabilizing glycemic levels, and reducing inflammation. Among all probiotic treating groups, the 10×Probioglu^TM treatment revealed the best results. However, these experimental results still need to be validated by different animal models of type-2 diabetes and human clinical trials in the future.

The gut microbiome and type 2 diabetes status in the Multiethnic Cohort

BACKGROUND

The gut microbiome may play a role in inflammation associated with type 2 diabetes (T2D) development. This cross-sectional study examined its relation with glycemic status within a subset of the Multiethnic Cohort (MEC) and estimated the association of circulating bacterial endotoxin (measured as plasma lipopolysaccharide-binding protein (LBP)) with T2D, which may be mediated by C-reactive protein (CRP).

METHODS

In 2013-16, cohort members from five ethnic groups completed clinic visits, questionnaires, and stool and blood collections. Participants with self-reported T2D and/or taking medication were considered T2D cases. Those with fasting glucose >125 and 100-125 mg/dL were classified as undiagnosed (UT2D) and pre-diabetes (PT2D) cases, respectively. We characterized the gut microbiome through 16S rRNA gene sequencing and measured plasma LBP and CRP by standard assays. Linear regression was applied to estimate associations of the gut microbiome community structure and LBP with T2D status adjusting for relevant confounders.

RESULTS

Among 1,702 participants (59.9-77.4 years), 735 (43%) were normoglycemic (NG), 506 (30%) PT2D, 154 (9%) UT2D, and 307 (18%) T2D. The Shannon diversity index decreased (ptrend = 0.05), while endotoxin, measured as LBP, increased (ptrend = 0.0003) from NG to T2D. Of 10 phyla, Actinobacteria (ptrend = 0.007), Firmicutes (ptrend = 0.003), and Synergistetes (ptrend = 0.02) were inversely associated and Lentisphaerae (ptrend = 0.01) was positively associated with T2D status. Clostridium sensu stricto 1, Lachnospira, and Peptostreptococcaceae were less, while Escherichia-Shigella and Lachnospiraceae were more abundant among T2D patients, but the associations with Actinobacteria, Clostridium sensu stricto 1, and Escherichia-Shigella may be due metformin use. PT2D/UT2D values were closer to NG than T2D. No indication was detected that CRP mediated the association of LBP with T2D.

CONCLUSIONS

T2D but not PT2D/UT2D status was associated with lower abundance of SCFA-producing genera and a higher abundance of gram-negative endotoxin-producing bacteria suggesting that the gut microbiome may contribute to chronic systemic inflammation and T2D through bacterial translocation.

Gut Microbiota Alterations and Cognitive Impairment Are Sexually Dissociated in a Transgenic Mice Model of Alzheimer's Disease

BACKGROUND

Normal aging is accompanied by cognitive deficiencies, affecting women and men equally. Aging is the main risk factor for Alzheimer's disease (AD), with women having a higher risk. The higher prevalence of AD in women is associated with the abrupt hormonal decline seen after menopause. However, other factors may be involved in this sex-related cognitive decline. Alterations in gut microbiota (GM) and its bioproducts have been reported in AD subjects and transgenic (Tg) mice, having a direct impact on brain amyloid-β pathology in male (M), but not in female (F) mice.

OBJECTIVE

The aim of this work was to determine GM composition and cognitive dysfunction in M and F wildtype (WT) and Tg mice, in a sex/genotype segregation design.

METHODS

Anxiety, short term working-memory, spatial learning, and long-term spatial memory were evaluated in 6-month-old WT and Tg male mice. Fecal short chain fatty acids were determined by chromatography, and DNA sequencing and bioinformatic analyses were used to determine GM differences.

RESULTS

We observed sex-dependent differences in cognitive skills in WT mice, favoring F mice. However, the cognitive advantage of females was lost in Tg mice. GM composition showed few sex-related differences in WT mice. Contrary, Tg-M mice presented a more severe dysbiosis than Tg-F mice. A decreased abundance of Ruminococcaceae was associated with cognitive deficits in Tg-F mice, while butyrate levels were positively associated with better working- and object recognition-memory in WT-F mice.

CONCLUSION

This report describes a sex-dependent association between GM alterations and cognitive impairment in a mice model of AD.

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.

Impact drugs targeting cardiometabolic risk on the gut microbiota

PURPOSE OF REVIEW

Alterations in the gut microbiome composition or function are associated with risk factors for cardiometabolic diseases, including hypertension, hyperlipidemia and hyperglycemia. Based on recent evidence that also oral medications used to treat these conditions could alter the gut microbiome composition and function and, vice versa, that the gut microbiome could affect the efficacy of these treatments, we reviewed the literature on these observed interactions.

RECENT FINDINGS

While the interaction of metformin with the gut microbiome has been studied most, other drugs that target cardiometabolic risk are gaining attention and often showed associations with alterations in microbiome-related features, including alterations in specific microbial taxa or pathways, microbiome composition or microbiome-derived metabolites, while the gut microbiome was also involved in drug metabolism and drug efficacy. As for metformin, for some of them even a potential therapeutic effect via the gut microbiome is postulated. However, exact mechanisms remain to be elucidated.

SUMMARY

There is growing interest in clarifying the interactions between the gut microbiome and drugs to treat hypertension, hyperlipidemia and hyperglycemia as well as the first pass effect of microbiome on drug efficacy. While mostly analysed in animal models, also human studies are gaining more and more traction. Improving the understanding of the gut microbiome drug interaction can provide clinical directions for therapy by optimizing drug efficacy or providing new targets for drug development.

A P4 Medicine Perspective of Gut Microbiota and Prediabetes: Systems Analysis and Personalized Intervention

Type 2 diabetes (T2D) accounts for approximately 90% of diabetes worldwide and has become a global public health problem. Generally, individuals go to hospitals and get healthcare only when they have obvious T2D symptoms. While the underlying cause and mechanism of the disease are usually not well understood, treatment is for the symptoms, but not for the disease cause, and patients often continue to progress with more symptoms. Prediabetes is the early stage of diabetes and provides a good time window for intervention and prevention. However, with few symptoms, prediabetes is usually ignored without any treatment. Obviously, it is far from ideal to rely on the traditional medical system for diabetes healthcare. As a result, the medical system must be transformed from a reactive approach to a proactive approach. Root cause analysis and personalized intervention should be conducted for patients with prediabetes. Based on systems medicine, also known as P4 medicine, with a predictive, preventive, personalized, and participatory approach, new medical system is expected to significantly promote the prevention and treatment of chronic diseases such as prediabetes and diabetes. Many studies have shown that the occurrence and development of diabetes is closely related to gut microbiota. However, the relationship between diabetes and gut microbiota has not been fully elucidated. This review describes the research on the relationship between gut microbiota and diabetes and some exploratory trials on the interventions of prediabetes based on P4 medicine model. Furthermore, we also discussed how these findings might influence the diagnosis, prevention and treatment of diabetes in the future, thereby to improve the wellness of human beings.

Effects of Maresin 1 (MaR1) on Colonic Inflammation and Gut Dysbiosis in Diet-Induced Obese Mice

The aim of this study was to characterize the effects of Maresin 1 (MaR1), a DHA-derived pro-resolving lipid mediator, on obesity-related colonic inflammation and gut dysbiosis in diet-induced obese (DIO) mice. In colonic mucosa of DIO mice, the MaR1 treatment decreased the expression of inflammatory genes, such as Tnf-α and Il-1β. As expected, the DIO mice exhibited significant changes in gut microbiota composition at the phylum, genus, and species levels, with a trend to a higher Firmicutes/Bacteroidetes ratio. Deferribacteres and Synergistetes also increased in the DIO animals. In contrast, these animals exhibited a significant decrease in the content of Cyanobacteria and Actinobacteria. Treatment with MaR1 was not able to reverse the dysbiosis caused by obesity on the most abundant phyla. However, the MaR1 treatment increased the content of P. xylanivorans, which have been considered to be a promising probiotic with healthy effects on gut inflammation. Finally, a positive association was found between the Deferribacteres and Il-1β expression, suggesting that the increase in Deferribacteres observed in obesity could contribute to the overexpression of inflammatory cytokines in the colonic mucosa. In conclusion, MaR1 administration ameliorates the inflammatory state in the colonic mucosa and partially compensates changes on gut microbiota caused by obesity.

A Double-Blind Randomized Placebo-Controlled Study Assessing the Safety, Tolerability and Efficacy of a Herbal Medicine Containing Pycnogenol Combined with Papain and Aloe vera in the Prevention and Management of Pre-Diabetes

Background: Herbal medicines present attractive options to patients with chronic diseases. Undertaking clinical studies with patients presenting with symptomless pre-T2D can lead to significant limitations. Methods: A 12-week randomized double-blind placebo-controlled clinical study was conducted that investigated the safety and efficacy of an herbal formulation administered orally for the treatment of pre-type 2 diabetes (pre-T2D). Results: A numerically greater proportion of subjects in the interventional arm had impaired fasting glucose (IFG) at week 12 compared to the control arm (71.0% vs. 69.0%, p = 0.75). Fewer participants had impaired glucose tolerance (IGT) at 12 weeks in the intervention arm compared to the control arm (unadjusted 58.3% vs. 66.7%, p = 0.65; adjusting for baseline IGT, p = 0.266). In a subgroup analysis, subjects with a baseline fasting plasma glucose (FPG) level in the range of 6.1-6.9 mmol/L demonstrated a non-significant lower proportion of IFG at week 12 in the intervention arm compared to the control arm (60.0% vs. 41.7% p = 0.343). Total blood cholesterol and triglyceride levels remained unchanged from baseline to week 12 in both treatment groups. Conclusions: This study suggests that a polyherbal medicine was not effective for reducing the metabolic markers associated with pre-T2D over a 12-week period. Therefore, larger studies with well-defined endpoints and of longer duration are warranted.

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.