Lifestyle Factors Affecting the Gut Microbiota's Relationship with Type 1 Diabetes

Long-term drench of exopolysaccharide from Leuconostoc pseudomesenteroides XG5 protects against type 1 diabetes of NOD mice via stimulating GLP-1 secretion

BACKGROUND

Type 1 diabetes is an autoimmune disease that results in the specific destruction of insulin-producing beta cells in the pancreas. The aim of this study was to investigate the mechanism of exopolysaccharide from Leuconostoc pseudomesenteroides XG5 (XG5 EPS) against type 1 diabetes.

RESULTS

Long-term drench of XG5 EPS delayed the onset of autoimmune diabetes and had fewer islets with high-grade infiltration (an insulitis score of 3 or 4) than untreated NOD mice. Oral administration of 50 mg kg^-1  d^-1 XG5 EPS increased the insulin and glucagon-like peptide-1 (GLP-1) levels of serum, stimulated GLP-1 secretion and upregulated gcg mRNA expression of colon in NOD mice. Moreover, oral administration of 50 mg kg^-1  d^-1 XG5 EPS significantly increased total short-chain fatty acids levels in the colon contents, especially those of acetic acid and butyric acid. In NCI-H716 cells, 500 and 1000 μmol L^-1 sodium butyrate promoted the secretion of GLP-1 and upregulated the mRNA expression of gcg and PC3, while XG5 EPS and sodium acetate did not stimulate the GLP-1 secretion. Therefore, long-term drench of XG5 EPS delayed the onset of autoimmune diabetes, which may be directly correlated with the increase of butyrate in the colon of NOD mice.

CONCLUSION

Long-term drench of 50 mg kg^-1  d^-1 XG5 EPS promoted the expression and secretion of GLP-1 by increasing the production of butyric acid, thereby delaying T1D onset in NOD mice. © 2021 Society of Chemical Industry.

Is Population Density Associated with Non-Communicable Disease in Western Developed Countries? A Systematic Review

Over the last three decades, researchers have investigated population density and health outcomes at differing scale. There has not been a systematic review conducted in order to synthesise this evidence. Following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, we systematically reviewed quantitative evidence published since 1990 on population density and non-communicable disease (NCD) within Westernised countries. Fifty-four studies met the inclusion criteria and were evaluated utilising a quality assessment tool for ecological studies. High population density appears to be associated with higher mortality rates of a range of cancers, cardiovascular disease and COPD, and a higher incidence of a range of cancers, asthma and club foot. In contrast, diabetes incidence was found to be associated with low population density. High and low population density are therefore risk markers for a range of NCDs, indicating that there are unidentified factors and mechanisms underlying aetiology. On closer examination, our synthesis revealed important and complex relationships between population density, the built environment, the nature of greenspace and man-made exposures. In light of increasing rates of morbidity and mortality, future research is required to investigate these associations in order to establish causative agents for each NCD.

Can the Salivary Microbiome Predict Cardiovascular Diseases? Lessons Learned From the Qatari Population

Background: Many studies have linked dysbiosis of the gut microbiome to the development of cardiovascular diseases (CVD). However, studies assessing the association between the salivary microbiome and CVD risk on a large cohort remain sparse. This study aims to identify whether a predictive salivary microbiome signature is associated with a high risk of developing CVD in the Qatari population. Methods: Saliva samples from 2,974 Qatar Genome Project (QGP) participants were collected from Qatar Biobank (QBB). Based on the CVD score, subjects were classified into low-risk (LR < 10) (n = 2491), moderate-risk (MR = 10-20) (n = 320) and high-risk (HR > 30) (n = 163). To assess the salivary microbiome (SM) composition, 16S-rDNA libraries were sequenced and analyzed using QIIME-pipeline. Machine Learning (ML) strategies were used to identify SM-based predictors of CVD risk. Results: Firmicutes and Bacteroidetes were the predominant phyla among all the subjects included. Linear Discriminant Analysis Effect Size (LEfSe) analysis revealed that Clostridiaceae and Capnocytophaga were the most significantly abundant genera in the LR group, while Lactobacillus and Rothia were significantly abundant in the HR group. ML based prediction models revealed that Desulfobulbus, Prevotella, and Tissierellaceae were the common predictors of increased risk to CVD. Conclusion: This study identified significant differences in the SM composition in HR and LR CVD subjects. This is the first study to apply ML-based prediction modeling using the SM to predict CVD in an Arab population. More studies are required to better understand the mechanisms of how those microbes contribute to CVD.

Modulating the Microbiota as a Therapeutic Intervention for Type 2 Diabetes

Mounting evidence suggested that the gut microbiota has a significant role in the metabolism and disease status of the host. In particular, Type 2 Diabetes (T2D), which has a complex etiology that includes obesity and chronic low-grade inflammation, is modulated by the gut microbiota and microbial metabolites. Current literature supports that unbalanced gut microbial composition (dysbiosis) is a risk factor for T2D. In this review, we critically summarize the recent findings regarding the role of gut microbiota in T2D. Beyond these associative studies, we focus on the causal relationship between microbiota and T2D established using fecal microbiota transplantation (FMT) or probiotic supplementation, and the potential underlying mechanisms such as byproducts of microbial metabolism. These microbial metabolites are small molecules that establish communication between microbiota and host cells. We critically summarize the associations between T2D and microbial metabolites such as short-chain fatty acids (SCFAs) and trimethylamine N-Oxide (TMAO). Additionally, we comment on how host genetic architecture and the epigenome influence the microbial composition and thus how the gut microbiota may explain part of the missing heritability of T2D found by GWAS analysis. We also discuss future directions in this field and how approaches such as FMT, prebiotics, and probiotics supplementation are being considered as potential therapeutics for T2D.

Gut Microbiome Signatures Are Biomarkers for Cognitive Impairment in Patients With Ischemic Stroke

Post-stroke cognitive impairment (PSCI) is a common neuropsychiatric complication of stroke. Mounting evidence has demonstrated a connection between gut microbiota (GM) and neuropsychiatric disease. Our previous study revealed the changes in the GM in a mouse model of vascular dementia. However, the characteristic GM of PSCI remains unclear. This study aimed to characterize the GM of PSCI and explored the potential of GM as PSCI biomarkers. A total of 93 patients with ischemic stroke were enrolled in this study. The patients were divided into two groups according to their MoCA scores 3 months after stroke onset. Clinical data and biological variables were recorded. GM composition was analyzed using 16S ribosomal RNA sequencing, and the characteristic GM was identified by linear discriminant analysis Effect Size (Lefse). Our results showed that Proteobacteria was highly increased in the PSCI group compared with the post-stroke non-cognitive impairment (PSNCI) group, the similar alterations were also observed at the class, order, family, and genus levels of Proteobacteria. After age adjustments, the abundance of Firmicutes, and its members, including Clostridia, Clostridiales, Lachnospiraceae, and Lachnospiraceae_other, were significantly decreased in the age-matched PSCI group compared with the PSNCI group. Besides, the GM was closely associated with MoCA scores and the risk factors for PSCI, including higher baseline National Institute of Health Stroke Scale score, higher homocysteine (Hcy) level, higher prevalence of stroke recurrence, leukoaraiosis, and brain atrophy. The KEGG results showed the enriched module for folding, sorting and degradation (chaperones and folding catalysts) and the decreased modules related to metabolisms of cofactors and vitamins, amino acid, and lipid in PSCI patients. A significant correlation was observed between PSCI and the abundance of Enterobacteriaceae after adjustments (P = 0.035). Moreover, the receiver operating characteristic (ROC) models based on the characteristic GM and Enterobacteriaceae could distinguish PSCI patients from PSNCI patients [area under the curve (AUC) = 0.840, 0.629, respectively]. Our findings demonstrated that the characteristic GM, especially Enterobacteriaceae, might have the ability to predict PSCI in post-stroke patients, which are expected to be used as clinical biomarkers of PSCI.

Early Childhood Antibiotic Treatment for Otitis Media and Other Respiratory Tract Infections Is Associated With Risk of Type 1 Diabetes: A Nationwide Register-Based Study With Sibling Analysis

OBJECTIVE

The effect of early-life antibiotic treatment on the risk of type 1 diabetes is debated. This study assessed this question, applying a register-based design in children up to age 10 years including a large sibling-control analysis.

RESEARCH DESIGN AND METHODS

All singleton children (n = 797,318) born in Sweden between 1 July 2005 and 30 September 2013 were included and monitored to 31 December 2014. Cox proportional hazards models, adjusted for parental and perinatal characteristics, were applied, and stratified models were used to account for unmeasured confounders shared by siblings.

RESULTS

Type 1 diabetes developed in 1,297 children during the follow-up (median 4.0 years [range 0-8.3]). Prescribed antibiotics in the 1st year of life (23.8%) were associated with an increased risk of type 1 diabetes (adjusted hazard ratio [HR] 1.19 [95% CI 1.05-1.36]), with larger effect estimates among children delivered by cesarean section (P for interaction = 0.016). The association was driven by exposure to antibiotics primarily used for acute otitis media and respiratory tract infections. Further, we found an association of antibiotic prescriptions in pregnancy (22.5%) with type 1 diabetes (adjusted HR 1.15 [95% CI 1.00-1.32]). In general, sibling analysis supported these results, albeit often with statistically nonsignificant associations.

CONCLUSIONS

Dispensed prescription of antibiotics, mainly for acute otitis media and respiratory tract infections, in the 1st year of life is associated with an increased risk of type 1 diabetes before age 10 years, most prominently in children delivered by cesarean section.