Higher blood glucose level associated with body mass index and gut microbiota in elderly people

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.

Food-related reward sensitivity across the spectrum of body weight and impulsive eating: Pilot findings from a multi-method approach

Overweight with and without comorbid binge-eating disorder (BED) has been associated with increased reward sensitivity, though evidence is heterogeneous. To disentangle this heterogeneity and gain insights into mechanisms of impaired reward processing, this study applied multi-method neuro-behavioural techniques. Reward sensitivity was investigated in N = 49 participants allocated to three subgroups: overweight individuals with BED (BED+, n = 17), overweight individuals without BED (BED-, n = 15), and normal-weight controls (NWC, n = 17). Applying a free exploration paradigm (food vs. non-food stimuli), eye tracking and electroencephalographic data were gathered. A valid cue before stimulus onset indicated the position of food, and the end points analysed after the cue and stimulus onset were attentional approach, attention allocation, and conflict processing (e.g., conflict between looking at the potentially rewarding food stimulus or not). The effect of negative mood was tested using mood induction. The study's main hypothesis was that individuals with overweight, particularly under negative mood, would have increased food-related reward sensitivity. All participants showed increased food-specific attentional approach (p < .001). BED + allocated more attention to food stimuli than non-food stimuli compared to the healthy control (p = .045). For individuals with overweight but without BED (BED-), results indicate that conflict processing might be prolonged after the stimulus onset (p = .011). No group-specific effect of negative mood was found. Preliminary results in overweight individuals with and without comorbid BED suggest that food stimuli are generally rewarding stimuli, but even more so for participants with binge eating psychopathology. Prolonged conflict processing during the confrontation with competing food and non-food stimuli was solely found in the BED- sample and might indicate a compensation mechanism. Replication is warranted. The multi-method approach seems to be promising to give indications for the development of psychotherapeutic treatment.

Alteration in Gut Microbiota Composition of Older Adults Is Associated with Obesity and Its Indices: A Systematic Review

BACKGROUND

Obesity in the older adults is a health concern that increases the risk of several life-threatening diseases. Previous research has been revealed that alterations in the gut microbiota composition is related to obesity. So, understanding the gut microbiota changes in older adults' obesity may help to provide promising strategies for their health management.

OBJECTIVES

Here we conducted a systematic review that investigate the alteration of gut microbiota composition in association with obesity and its indices in the older adults.

DESIGN

Systematic review.

SETTING

A comprehensive systematic search was performed through PubMed, Web of Science, Scopus and Embase databases for all relative studies up to 2023 with the main search concepts as Microbiota, Obesity and Elderly. The data about gut microbiota in association with obesity indices had been extracted.

PARTICIPANTS

Older adults (≥60 years).

INTERVENTION

None.

MEASUREMENTS

None.

RESULTS

Within 10741 recordes, 11 studies met the inclusion criteria and were included in this systematic review. Most of them indicated the gut microbiota alterations in obese compared with non-obese older adults. However, the gut microbiome composition in obese older adults is affected by other underlying diseases like diabetes and metabolic syndrome. The most important taxa that had abundance alteration in association with obesity in older adults were Christensenellaceae, Porphyromonadaceae and Rikenellaceae, Akkermansia, Blautia, Prevotella, Ruminococcus, Bacteroides and Faecalibacterium.

CONCLUSION

The gut microbiota composition is associated with obesity in older adults. Considering the other factors affecting the composition of gut microbiota, such as age, underlying diseases and lifestyle, a more accurate conclusion about this matter requires more future studies.

The correlation of the fecal microbiome with the biochemical profile during menopause: a Brazilian cohort study

BACKGROUND

Hormonal, biochemical, and metabolic changes after menopause may alter the quality of life of women, leading to vasomotor, psychological, and genitourinary symptoms, and changes in their gut microbiota, which regulates estrogen levels through the estroboloma. Fecal samples were used to investigate the changes in the gut microbiota during aging and hormonal changes in women. A balanced gut microbiota has been associated with health or disease conditions and remains poorly understood after menopause. This study identified the fecal microbiota, and their association with biochemical and hormonal parameters of a cohort of women in the climacteric in the city of Ouro Preto-MG, Brazil.

METHODS

A total of 102 women aged 40 to 65 years old were recruited and distributed into three groups according to the STRAW criteria for reproductive stage: reproductive (n = 18), premenopausal (n = 26), and postmenopausal (n = 58). Blood samples were collected to measure their serum biochemical and hormone levels, and the participants answered a questionnaire. The gut microbiota was analyzed from fecal samples by qPCR using the genera Bifidobacterium, Bacteroides, Lactobacillus, and Clostridium.

RESULTS

The following parameters showed differences among the groups: total cholesterol, triglycerides, VLDL, ApoB, urea, calcium, uric acid, and alkaline phosphatase (p < 0.05). qPCR revealed the genus Clostridium to be the most abundant in all three groups. In the reproductive age group, the significant correlations were: Bacteroides with glucose (r = -0.573 p = 0.0129), and SDHEA (r = -0.583 p = 0.0111). For the premenopausal group, they were: Bifidobacteria with total cholesterol (r = 0.396 p = 0.0451), LDL (r = 0.393 p = 0.0468), ApoB (r = 0.411 p = 0.0368); Lactobacillus and calcium (r = 0.443 p = 0.0232), ALP (r = 0.543 p = 0.0041), LPa (r =-0.442 p = 0.02336); and Bacteroides and urea (r =-0.461 p = 0.0176). In the postmenopausal group, they were Bifidobacterium and ALP (r =-0.315 p = 0.0159), Lactobacillus and urea (r =-0.276 p = 0.0356), and Clostridium and beta estradiol (r =-0.355 p = 0.0062).

CONCLUSION

In conclusion, the hormonal and metabolic changes during menopause in the population studied were accompanied by a significant change in the fecal microbiota, especially of the genus Clostridium.

Identification of Smartwatch-Collected Lifelog Variables Affecting Body Mass Index in Middle-Aged People Using Regression Machine Learning Algorithms and SHapley Additive Explanations

Body mass index (BMI) plays a vital role in determining the health of middle-aged people, and a high BMI is associated with various chronic diseases. This study aims to identify important lifelog factors related to BMI. The sleep, gait, and body data of 47 middle-aged women and 71 middle-aged men were collected using smartwatches. Variables were derived to examine the relationships between these factors and BMI. The data were divided into groups according to height based on the definition of BMI as the most influential variable. The data were analyzed using regression and tree-based models: Ridge Regression, eXtreme Gradient Boosting (XGBoost), and Category Boosting (CatBoost). Moreover, the importance of the BMI variables was visualized and examined using the SHapley Additive Explanations Technique (SHAP). The results showed that total sleep time, average morning gait speed, and sleep efficiency significantly affected BMI. However, the variables with the most substantial effects differed among the height groups. This indicates that the factors most profoundly affecting BMI differ according to body characteristics, suggesting the possibility of developing efficient methods for personalized healthcare.

Differences in Glycemic Abnormalities Between Primary Aldosteronism and Essential Hypertension: A Systematic Review and Meta-Analysis

Background

The relationship of glycemic abnormalities between primary aldosteronism (PA) patients and essential hypertension (EH) patients is still debatable. This meta-analysis aimed to explore differences in the prevalence of glycemic abnormalities and levels of abnormal glucose metabolism in PA and EH patients.

Methods

A search was performed using PubMed, Scopus, Cochrane and Web of Science databases from their inception through January 2022. Inclusion criteria for this study were 1) observational studies which contained specific data of interest, 2) studies including data which compared adult PA and EH patients and 3) studies which used appropriate methods to diagnose PA. Risk ratio (RR) or standardized mean difference (SMD) with a 95% confidence interval (95% CI) was calculated.

Results

Twenty-six studies involving 53,186 patients were included in the meta-analysis. Patients with PA demonstrated significantly higher overall incidence of glycemic abnormalities than patients with EH [RR 1.54; 95% CI (1.20,1.98)]. Risk of diabetes mellitus (DM) and impaired glucose tolerance (IGT) in PA patients were higher than in EH patients [RR 1.27; 95%CI (1.08, 1.49) and RR 2.99; 95%CI (1.74, 5.16), respectively]. There was no statistically significant difference of risk between these groups for impaired fasting glucose (IFG) [RR 1.70; 95%CI (0.55, 5.26)]. Moderate heterogeneity was observed in overall glycemic abnormalities outcomes. A high level of heterogeneity was observed for IFG, while the level was low for DM and IGT.

Conclusions

PA patients have a higher risk of glycemic abnormalities than in EH patients. Further study should be conducted to investigate underlying mechanisms of glycemic abnormalities in PA.

Systematic Review Registration

www.inplasy.com, INPLASY, identifier 202220004.

A Machine-Generated View of the Role of Blood Glucose Levels in the Severity of COVID-19

SARS-CoV-2 started spreading toward the end of 2019 causing COVID-19, a disease that reached pandemic proportions among the human population within months. The reasons for the spectrum of differences in the severity of the disease across the population, and in particular why the disease affects more severely the aging population and those with specific preconditions are unclear. We developed machine learning models to mine 240,000 scientific articles openly accessible in the CORD-19 database, and constructed knowledge graphs to synthesize the extracted information and navigate the collective knowledge in an attempt to search for a potential common underlying reason for disease severity. The machine-driven framework we developed repeatedly pointed to elevated blood glucose as a key facilitator in the progression of COVID-19. Indeed, when we systematically retraced the steps of the SARS-CoV-2 infection, we found evidence linking elevated glucose to each major step of the life-cycle of the virus, progression of the disease, and presentation of symptoms. Specifically, elevations of glucose provide ideal conditions for the virus to evade and weaken the first level of the immune defense system in the lungs, gain access to deep alveolar cells, bind to the ACE2 receptor and enter the pulmonary cells, accelerate replication of the virus within cells increasing cell death and inducing an pulmonary inflammatory response, which overwhelms an already weakened innate immune system to trigger an avalanche of systemic infections, inflammation and cell damage, a cytokine storm and thrombotic events. We tested the feasibility of the hypothesis by manually reviewing the literature referenced by the machine-generated synthesis, reconstructing atomistically the virus at the surface of the pulmonary airways, and performing quantitative computational modeling of the effects of glucose levels on the infection process. We conclude that elevation in glucose levels can facilitate the progression of the disease through multiple mechanisms and can explain much of the differences in disease severity seen across the population. The study provides diagnostic considerations, new areas of research and potential treatments, and cautions on treatment strategies and critical care conditions that induce elevations in blood glucose levels.

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.

Effects of Berberine on the Gastrointestinal Microbiota

The gastrointestinal microbiota is a multi-faceted system that is unraveling novel contributors to the development and progression of several diseases. Berberine has been used to treat obesity, diabetes mellitus, atherosclerosis, and metabolic diseases in China. There are also clinical trials regarding berberine use in cardiovascular, gastrointestinal, and endocrine diseases. Berberine elicits clinical benefits at standard doses and has low toxicity. The mechanism underlying the role of berberine in lipid‐lowering and insulin resistance is incompletely understood, but one of the possible mechanisms is related to its effect on the gastrointestinal microbiota. An extensive search in electronic databases (PubMed, Scopus, Embase, Web of Sciences, Science Direct) was used to identify the role of the gastrointestinal microbiota in the berberine treatment. The aim of this review was to summarize the pharmacologic effects of berberine on animals and humans by regulation of the gastrointestinal microbiota.

Does a rise in BMI cause an increased risk of diabetes?: Evidence from India

BACKGROUND

Overnutrition increases the risk of diabetes. Evidence on the causal impact of overnutrition on diabetes is scarce for India. Considering a representative sample from India, this study examines the causal effect of a rise in the Body Mass Index (BMI) of an individual on the likelihood of being diabetic while addressing the issue of unobserved endogeneity between overnutrition and diabetes.

METHODS

The study considers individual level data from Demographic and Health Surveys (DHS) of India, namely, National Family Health Survey (NFHS) for the year 2015-16. The NFHS is a large-scale, multi-round survey conducted in a representative sample of households throughout India. The survey covers females having age 15-49 years and males having age 15-54 years. The instrument variable approach is used to address the potential endogeneity in the relationship between BMI and diabetes. We instrument BMI of an individual by BMI of a non-biologically related household member. Ordered Probit, Probit and IV-Probit models are estimated using two alternative definitions for measuring diabetes-self-reported diabetes status and blood glucose levels (ordinal measure).

RESULTS

The coefficients obtained from the Ordered Probit and Probit models are much smaller than those estimated by an IV-Probit model. The latter estimates the causal impact of a rise in BMI on diabetes by taking into account the effect of the unobserved genetic and other related factors. The likelihood of being diabetic is twice or more among the overweight and obese individuals as compared to non-overweight individuals in all the specifications. With a unit increase in BMI the probability of being diabetic increases by about 1.5% among overweight and obese individuals and by 0.5% among the non-overweight individuals in the IV-Probit model. Similar results from the Ordered Probit model show that on average, the overweight and obese individuals experience about 0.2% increase in the probability of being diabetic and about 0.4% increase in the probability of being prediabetic.

CONCLUSION

Our study demonstrates that the likelihood of being both prediabetic and diabetic is higher among the overweight and obese individuals as compared to the non-overweight individuals. We also find that the level of risk of being prediabetic or diabetic differs across gender, wealth quintiles and regions and the effects are more severe among population in the urban areas, belonging to the richest wealth quintile and men. Our findings have significant implications for the policy formulation as diabetes has a substantial health and economic burden associated with it. Future studies may investigate the effect of abdominal obesity on diabetes.

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

In this work, we studied 217 Mexican subjects divided into six groups with different stages of glucose intolerance: 76 Controls (CO), 54 prediabetes (PRE), 14 T2D no medication (T2D−No−M), 14 T2D with Metformin (T2D−M), 22 T2D with polypharmacy (T2D−P), and 37 T2D with polypharmacy and insulin (T2D−P+I). We aimed to determine differences in the gut microbiota diversity for each condition. At the phylum level, we found that Firmicutes and Bacteroidetes outline major changes in the gut microbiota. The gut bacterial richness and diversity of individuals in the T2D−No−M group were lesser than other groups. Interestingly, we found a significant difference in the beta diversity of the gut microbiota among all groups. Higher abundance was found for Comamonadaceae in PRE, and Sutterella spp. in T2D−No−M. In addition, we found associations of specific microbial taxa with clinical parameters. Finally, we report predicted metabolic pathways of gut microbiota linked to T2D−M and PRE conditions. Collectively, these results indicate that each group has specific predicted metabolic characteristics and gut bacteria populations for each phenotype. The results of this study could be used to define strategies to modulate gut microbiota through noninvasive treatments, such as dietary intervention, probiotics or prebiotics, and to improve glucose tolerance of individuals with prediabetes or T2D.

Relationship Between Modified Body Adiposity Index and A Body Shape Index with Biochemical Parameters in Bariatric Surgery Candidates

BACKGROUND

Body mass index, an estimate of body fat percentage, has been previously shown to be associated with metabolic disorders. However, there is little data on the associations between a body shape index (ABSI) or modified body adiposity index (MBAI), which provide valuable definitions of body fat, with serum biochemical parameter levels. Therefore, this study was conducted to find either ABSI or MBAI associations with serum biochemical parameter levels in bariatric surgery candidates.

METHODS

This cross-sectional study was conducted on 776 bariatric surgery candidates (age range 18-69 years) between November 2010 and September 2017. Demographic data, anthropometric indices, biochemical parameters, and body composition analysis data were drawn from the National Obesity Surgery Database, Iran. ABSI and MBAI were calculated using related equations. A stepwise multivariate linear regression was used to evaluate whether ABSI or MBAI was associated with each serum biochemical parameter.

RESULTS

ABSI, age, and multivitamin/mineral supplementation (MVMS) were independently associated with serum vitamin D (β = 24.374, SE 10.756, P value 0.026; β = 0.022, SE 0.007, P value 0.002; β = 0.639, SE 0.235, P value 0.008). However, a negative association was observed between MBAI and vitamin D (β = - 0.037, SE 0.016, P value 0.025) in a model adjusted for age and MVMS. Additionally, MBAI and age showed a significant positive association with serum HDL-c (β = 0.185, SE 0.085, P value 0.028; β = 0.171, SE 0.033, P value < 0.001), although there was a negative association between male sex and HDL-c (β = - 4.004, SE 0.891, P value < 0.001).

CONCLUSION

ABSI and MBAI may be appropriate indices in predicting serum vitamin D and HDL-c levels.

Analysis of gut microbiota of obese individuals with type 2 diabetes and healthy individuals

Type 2 diabetes mellitus (T2DM) accounts for 90% of diabetes cases worldwide. The majority of T2DM patients are obese. Dysbiosis in the gut microflora is strongly associated with the pathogenesis of obesity and T2DM; however, the microbiome of obese-T2DM individuals in the Pakistani population remains unexplored. The gut microbiota signature of 60 Pakistani adults was studied using 16S rRNA sequencing targeting V₃–V₄ hypervariable regions. The sequence analysis revealed that bacteria from Firmicutes were predominant along with those from Clostridia and Negativicutes, whereas bacteria from Verrucomicrobia, Bacteroidetes, Proteobacteria, and Elusimicrobia were less abundant among the obese T2DM patients. These data distinctively vary from those in reports on the Indian population. The difference in gut microbiota could presumably be related to the distinct lifestyle and eastern dietary habits (high carbohydrate and fat intake, low fiber intake) and unregulated antibiotic consumption. This is the first study carried out to understand the gut microbiome and its correlation with individual life style of obese T2DM patients in the Pakistani population.

Age-stratified comparative analysis of the differences of gut microbiota associated with blood glucose level

Background

Gut bacteria are an important component of the microbiota ecosystem in humans and other animals, and they play important roles in human health. The aim of this study was to investigate the relationship between gut microbiota and multiple demographical-, behavioral-, or biochemical-related factors in subjects with chronic disease. Subjects with a very wide age range who participated in community-based chronic disease prevention and screening programs in China were enrolled. We analyzed the intestinal microbiota composition using 16S rRNA-based high-throughput sequencing of fecal samples, analyzed the association between gut microbiota structure and multiple demographical, behavioral, and biochemical factors, and compared the differences in microbiota composition in age-stratified groups with different blood glucose levels.

Results

Our results showed that both age and blood glucose levels had a significant impact on the gut microbiota structure. We also identified several taxa showed distinct abundance in groups with different glucose levels. Lactobacillus and Bifidobacterium at genus level and their related taxa were more abundant in the GLU high group comparing with GLU normal group and in NGR group comparing with DM group. Further analysis using the age-stratified data showed that blood glucose levels had a more significant impact on the gut microbiota in the ≥76 y age group than in the ≤75 y age group, which indicated that it is necessary to take age into account when conducting such studies. Moreover, we identified several taxa that were highly associated with blood glucose levels in the ≥76 y age group but not in the ≤75 y age group. Within the ≥76 y age group, Lachnospiraceae incertae sedis and Bacteroides were more abundant in the GLU normal group, whereas Lactobacillus and Bifidobacterium at genus level were more abundant in the GLU high group.

Conclusions

This result suggested that taxa that are capable of differentiating blood glucose levels might differ significantly in different age groups.

Hypoglycemic Mechanism of the Berberine Organic Acid Salt under the Synergistic Effect of Intestinal Flora and Oxidative Stress

Both alterations to the intestinal microflora and chronic systemic inflammation predispose towards type 2 diabetes (T2D). Changes in the composition of the intestinal microflora are associated with glucose metabolism changes in rats with T2D. Here, we demonstrate that a berberine fumarate (BF) has a hypoglycemic effect by regulating the intestinal microflora and metabolism of diabetic rats. The T2D rats had disorders of glucose and lipid metabolism, an abnormal intestinal microflora, fewer butyrate-producing and probiotic-type bacteria, larger numbers of potentially pathogenic and sulfate-reducing bacteria, and tissue inflammation. Administration of berberine fumarate significantly ameliorated the metabolic disorder; increased the populations of Bacteroidetes, Clostridia, Lactobacillales, Prevotellaceae, and Alloprevotella; and reduced those of Bacteroidales, Lachnospiraceae, Rikenellaceae, and Desulfovibrio. In addition, it reduced inflammation, inhibiting the overexpression of TLR4 and p-JNK and increasing the expression of PI3K, GLUT2, and other proteins, which are closely related to oxidative stress, thereby promoting the metabolism of glucose.

Effects of Baicalein on Cortical Proinflammatory Cytokines and the Intestinal Microbiome in Senescence Accelerated Mouse Prone 8

Baicalein, a flavonoid derived from the roots of Scutellariae baicalensis Georgi, has shown health benefits for an array of human diseases including dementia. The senescence-accelerated mouse prone 8 (SAMP8) strain is extensively used as a senile dementia model. To further investigate the effects of baicalein in SAMP8 mice, behavioral testing, biochemical detection, and gut microbiota analysis were performed. The results demonstrated that treatment with baicalein ameliorated the senescence status of the SAMP8 mice, as manifested by reducing the grading score of senescence. Additionally, baicalein improved the cognitive functions of the SAMP8 mice, including spatial learning and memory abilities, object recognition memory, and olfactory memory. Furthermore, baicalein significantly inhibited the release of proinflammatory cytokines such as interleukin-6 (IL-6), interleukin-1 beta (IL-1β), and tumor necrosis factor-α (TNF-α) in the brain cortex of SAMP8 mice. Gut microbiota analysis revealed that treatment with baicalein markedly altered the abundance of six genera in SAMP8 mice. Correlation analysis indicated that the abundances of Mucispirillum, Bacteroides, and Sutterella were negatively correlated with cognitive abilities and that Christensenellaceae was positively correlated with cognition. Furthermore, the abundance of Christensenellaceae was negatively correlated with the levels of IL-6 and TNF-α, while [ Prevotella] was positively correlated with the levels of IL-1β and IL-6. In addition, Mucispirillum and Bacteroides were positively correlated with the level of IL-6 in the brain cortex. These data indicated that baicalein ameliorates senescence status and improves cognitive function in SAMP8 mice and that this effect might be attributable to suppression of cortical proinflammatory cytokines and modulation of the intestinal microbiome.

Dissecting cause and effect in host-microbiome interactions using the combined worm-bug model system

High-throughput molecular studies are greatly advancing our knowledge of the human microbiome and its specific role in governing health and disease states. A myriad of ongoing studies aim at identifying links between microbial community disequilibria (dysbiosis) and human diseases. However, due to the inherent complexity and heterogeneity of the human microbiome we need robust experimental models that allow the systematic manipulation of variables to test the multitude of hypotheses arisen from large-scale ‘meta-omic’ projects. The nematode C. elegans combined with bacterial models offers an avenue to dissect cause and effect in host-microbiome interactions. This combined model allows the genetic manipulation of both host and microbial genetics and the use of a variety of tools, to identify pathways affecting host health. A number of recent high impact studies have used C. elegans to identify microbial pathways affecting ageing and longevity, demonstrating the power of the combined C. elegans-bacterial model. Here I will review the current state of the field, what we have learned from using C. elegans to study gut microbiome and host interactions, and the potential of using this model system in the future.

Evaluating the contribution of gut microbiome to the variance of porcine serum glucose and lipid concentration

Serum glucose and lipids are important indicators for host metabolic condition. Interaction of host and gut microbes regulates the metabolism process. However, how much the gut microbiome contributes to the variance of serum glucose and lipids is largely unknown. Here we carried out a 16S rRNA gene based association study between cecum microbiome and the concentration of serum glucose and lipids in 240 Chinese Erhualian pigs. We identified tens of bacterial taxa associated with serum glucose and lipids. The butyrate-producing bacteria were significantly associated with serum glucose level. The pathogenic bacteria belonging to Proteobacteria and Fusobacteria showed significant associations with increased serum lipid levels, while the bacteria Lactobacillus and Bacilli had negative correlations with serum lipids. Cross-validation analysis revealed that 23.8% variation of serum glucose and 1.6%~6.0% variations of serum lipids were explained by gut microbiome. Furthermore, predicted function capacities related to nutrition intake, transport and carbohydrate metabolism were significantly associated with serum glucose level, while the pathways related to antioxidant metabolism and bile synthesis tended to be associated with serum lipid level. The results provide meaningful information to get insight into the effect of gut microbiome on serum glucose and lipid levels in pigs.

Mulberry leaf alleviates streptozotocin-induced diabetic rats by attenuating NEFA signaling and modulating intestinal microflora

Improvement of hyperglycemia through dietotherapy/herbal remedy is an effective approach to treating diabetes. In this study, mulberry leaf, famous for silkworm’s special food and therapeutic value without any side effects, alleviated diabetes by attenuating NEFA signaling and modulating intestinal microflora. Mulberry leaf treatment significantly reduce fasting blood-glucose and HbA1c, ameliorate the blood lipid profile and improve insulin resistance in streptozotocin-induced diabetic rats. Mechanistically, we found that mulberry leaf inhibited NEFA signaling by reducing downstream signaling in the NEFA pathway, further verified by reduced PKC and improved cellular energy homeostasis based on restored expression of PGC-1α, AK2, OXPHOS and adiponectin. Mulberry leaf treatment also restored the phyla Bacteroidetes and Proteobacteria and class Clostridia, which were associated with insulin resistance and diabetes. Our findings reveal that mulberry leaf is an edible with therapeutic potential for diabetes and may provide a novel dietotherapy/herbal remedy to the treatment of diabetes.

The Role of Supplemental Complex Dietary Carbohydrates and Gut Microbiota in Promoting Cardiometabolic and Immunological Health in Obesity: Lessons from Healthy Non-Obese Individuals

Dietary supplementation with complex carbohydrates is known to alter the composition of gut microbiota, and optimal implementation of the use of these so called "prebiotics" could be of great potential in prevention and possibly treatment of obesity and associated cardiometabolic and inflammatory diseases via changes in the gut microbiota. An alternative to this "microbiocentric view" is the idea that health-promoting effects of certain complex carbohydrates reside in the host, and could secondarily affect the diversity and abundance of gut microbiota. To circumvent this potential interpretational problem, we aimed at providing an overview about whether and how dietary supplementation of different complex carbohydrates changes the gut microbiome in healthy non-obese individuals. We then reviewed whether the reported changes in gut bacterial members found to be established by complex carbohydrates would benefit or harm the cardiometabolic and immunological health of the host taking into account the alterations in the microbiome composition and abundance known to be associated with obesity and its associated disorders. By combining these research areas, we aimed to give a better insight into the potential of (foods containing) complex carbohydrates in the treatment and prevention of above-mentioned diseases. We conclude that supplemental complex carbohydrates that increase Bifidobacteria and Lactobacilli, without increasing the deleterious Bacteroides, are most likely promoting cardiometabolic and immunological health in obese subjects. Because certain complex carbohydrates also affect the host's immunity directly, it is likely that host-microbiome interactions in determination of health and disease characteristics are indeed bidirectional. Overall, this review article shows that whereas it is relatively clear in which direction supplemental fermentable carbohydrates can alter the gut microbiome, the relevance of these changes regarding health remains controversial. Future research should take into account the different causes of obesity and its adverse health conditions, which in turn have drastic effects on the microbiome balance.

Association between body mass index and Firmicutes/Bacteroidetes ratio in an adult Ukrainian population

Background

Metagenomic studies confirm that obesity is associated with a composition of gut microbiota. There are some controversies, however, about the composition of gut microbial communities in obese individuals in different populations. To examine the association between body mass index and microbiota composition in Ukrainian population, fecal concentrations of Bacteroidetes, Firmicutes, Actinobacteria and Firmicutes/Bacteroidetes (F/B) ratio were analyzed in 61 adult individuals.

Results

The relative abundance of Actinobacteria was small (5–7%) and comparable in different BMI categories. The content of Firmicutes was gradually increased while the content of Bacteroidetes was decreased with increasing body mass index (BMI). The F/B ratio also raised with increasing BMI. In an unadjusted logistic regression model, F/B ratio was significantly associated with BMI (OR = 1.23, 95% CI 1,09–1,38). This association continued to be significant after adjusting for confounders such as age, sex, tobacco smoking and physical activity (OR = 1.33, 95% CI 1,11–1,60).

Conclusions

The obtained data indicate that obese persons in Ukraine adult population have a significantly higher level of Firmicutes and lower level of Bacteroidetes compared to normal-weight and lean adults.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-017-1027-1) contains supplementary material, which is available to authorized users.

Gut Microbiome Associates With Lifetime Cardiovascular Disease Risk Profile Among Bogalusa Heart Study Participants

RATIONALE

Few studies have systematically assessed the influence of gut microbiota on cardiovascular disease (CVD) risk.

OBJECTIVE

To examine the association between gut microbiota and lifetime CVD risk profile among 55 Bogalusa Heart Study participants with the highest and 57 with the lowest lifetime burdens of CVD risk factors.

METHODS AND RESULTS

16S ribosomal RNA sequencing was conducted on microbial DNA extracted from stool samples of the Bogalusa Heart Study participants. α Diversity, including measures of richness and evenness, and individual genera were tested for associations with lifetime CVD risk profile. Multivariable regression techniques were used to adjust for age, sex, and race (model 1), along with body mass index (model 2) and both body mass index and diet (model 3). In model 1, odds ratios (95% confidence intervals) for each SD increase in richness, measured by the number of observed operational taxonomic units, Chao 1 index, and abundance-based coverage estimator, were 0.62 (0.39-0.99), 0.61 (0.38-0.98), and 0.63 (0.39-0.99), respectively. Associations were consistent in models 2 and 3. Four genera were enriched among those with high versus low CVD risk profile in all models. Model 1 P values were 2.12×10(-3), 7.95×10(-5), 4.39×10(-4), and 1.51×10(-4) for Prevotella 2, Prevotella 7, Tyzzerella, and Tyzzerella 4, respectively. Two genera were depleted among those with high versus low CVD risk profile in all models. Model 1 P values were 2.96×10(-6) and 1.82×10(-4) for Alloprevotella and Catenibacterium, respectively.

CONCLUSIONS

The current study identified associations of overall microbial richness and 6 microbial genera with lifetime CVD risk.

Impact of demographics on human gut microbial diversity in a US Midwest population

The clinical utility of microbiome biomarkers depends on the reliable and reproducible nature of comparative results. Underappreciation of the variation associated with common demographic, health, and behavioral factors may confound associations of interest and generate false positives. Here, we present the Midwestern Reference Panel (MWRP), a resource for comparative gut microbiome studies conducted in the Midwestern United States. We analyzed the relationships between demographic and health behavior-related factors and the microbiota in this cohort, and estimated their effect sizes. Most variables investigated were associated with the gut microbiota. Specifically, body mass index (BMI), race, sex, and alcohol use were significantly associated with microbial β-diversity (P < 0.05, unweighted UniFrac). BMI, race and alcohol use were also significantly associated with microbial α-diversity (P < 0.05, species richness). Tobacco use showed a trend toward association with the microbiota (P < 0.1, unweighted UniFrac). The effect sizes of the associations, as quantified by adjusted R² values based on unweighted UniFrac distances, were small (< 1% for all variables), indicating that these factors explain only a small percentage of overall microbiota variability. Nevertheless, the significant associations between these variables and the gut microbiota suggest that they could still be potential confounders in comparative studies and that controlling for these variables in study design, which is the main objective of the MWRP, is important for increasing reproducibility in comparative microbiome studies.

Early Shifts of Brain Metabolism by Caloric Restriction Preserve White Matter Integrity and Long-Term Memory in Aging Mice

Preservation of brain integrity with age is highly associated with lifespan determination. Caloric restriction (CR) has been shown to increase longevity and healthspan in various species; however, its effects on preserving living brain functions in aging remain largely unexplored. In the study, we used multimodal, non-invasive neuroimaging (PET/MRI/MRS) to determine in vivo brain glucose metabolism, energy metabolites, and white matter structural integrity in young and old mice fed with either control or 40% CR diet. In addition, we determined the animals' memory and learning ability with behavioral assessments. Blood glucose, blood ketone bodies, and body weight were also measured. We found distinct patterns between normal aging and CR aging on brain functions - normal aging showed reductions in brain glucose metabolism, white matter integrity, and long-term memory, resembling human brain aging. CR aging, in contrast, displayed an early shift from glucose to ketone bodies metabolism, which was associated with preservations of brain energy production, white matter integrity, and long-term memory in aging mice. Among all the mice, we found a positive correlation between blood glucose level and body weight, but an inverse association between blood glucose level and lifespan. Our findings suggest that CR could slow down brain aging, in part due to the early shift of energy metabolism caused by lower caloric intake, and we were able to identify the age-dependent effects of CR non-invasively using neuroimaging. These results provide a rationale for CR-induced sustenance of brain health with extended longevity.

Improving healthspan via changes in gut microbiota and fermentation

Dietary resistant starch impact on intestinal microbiome and improving healthspan is the topic of this review. In the elderly population, dietary fiber intake is lower than recommended. Dietary resistant starch as a source of fiber produces a profound change in gut microbiota and fermentation in animal models of aging. Dietary resistant starch has the potential for improving healthspan in the elderly through multiple mechanisms as follows: (1) enhancing gut microbiota profile and production of short-chain fatty acids, (2) improving gut barrier function, (3) increasing gut peptides that are important in glucose homeostasis and lipid metabolism, and (4) mimicking many of the effects of caloric restriction including upregulation of genes involved in xenobiotic metabolism.

Gut microorganisms as promising targets for the management of type 2 diabetes

Each human intestine harbours not only hundreds of trillions of bacteria but also bacteriophage particles, viruses, fungi and archaea, which constitute a complex and dynamic ecosystem referred to as the gut microbiota. An increasing number of data obtained during the last 10 years have indicated changes in gut bacterial composition or function in type 2 diabetic patients. Analysis of this 'dysbiosis' enables the detection of alterations in specific bacteria, clusters of bacteria or bacterial functions associated with the occurrence or evolution of type 2 diabetes; these bacteria are predominantly involved in the control of inflammation and energy homeostasis. Our review focuses on two key questions: does gut dysbiosis truly play a role in the occurrence of type 2 diabetes, and will recent discoveries linking the gut microbiota to host health be helpful for the development of novel therapeutic approaches for type 2 diabetes? Here we review how pharmacological, surgical and nutritional interventions for type 2 diabetic patients may impact the gut microbiota. Experimental studies in animals are identifying which bacterial metabolites and components act on host immune homeostasis and glucose metabolism, primarily by targeting intestinal cells involved in endocrine and gut barrier functions. We discuss novel approaches (e.g. probiotics, prebiotics and faecal transfer) and the need for research and adequate intervention studies to evaluate the feasibility and relevance of these new therapies for the management of type 2 diabetes.

Composition and temporal stability of the gut microbiota in older persons

The composition and function of the human gut microbiota has been linked to health and disease. We previously identified correlations between habitual diet, microbiota composition gradients and health gradients in an unstratified cohort of 178 elderly subjects. To refine our understanding of diet–microbiota associations and differential taxon abundance, we adapted an iterative bi-clustering algorithm (iterative binary bclustering of gene sets (iBBiG)) and applied it to microbiota composition data from 732 faecal samples from 371 ELDERMET cohort subjects, including longitudinal samples. We thus identified distinctive microbiota configurations associated with ageing in both community and long-stay residential care elderly subjects. Mixed-taxa populations were identified that had clinically distinct associations. Microbiota temporal instability was observed in both community-dwelling and long-term care subjects, particularly in those with low initial microbiota diversity. However, the stability of the microbiota of subjects had little impact on the directional change of the microbiota as observed for long-stay subjects who display a gradual shift away from their initial microbiota. This was not observed in community-dwelling subjects. This directional change was associated with duration in long-stay. Changes in these bacterial populations represent the loss of the health-associated and youth-associated microbiota components and gain of an elderly associated microbiota. Interestingly, community-associated microbiota configurations were impacted more by the use of antibiotics than the microbiota of individuals in long-term care, as the community-associated microbiota showed more loss but also more recovery following antibiotic treatment. This improved definition of gut microbiota composition patterns in the elderly will better inform the design of dietary or antibiotic interventions targeting the gut microbiota.