Adverse associations of different obesity measures and the interactions with long-term exposure to air pollutants with prevalent type 2 diabetes mellitus: The Henan Rural Cohort study

Association of short-chain fatty acids and the gut microbiome with type 2 diabetes: Evidence from the Henan Rural Cohort

BACKGROUND AND AIMS

Human studies about short-chain fatty acids (SCFAs), the gut microbiome, and Type 2 diabetes (T2DM) are limited. Here we explored the association between SCFAs and T2DM and the effects of gut microbial diversity on glucose status in rural populations.

METHODS AND RESULTS

We performed a cross-sectional study from the Henan Rural Cohort and collected stool samples. Gut microbiota composition and faecal SCFA concentrations were measured by 16S rRNA and GC-MS. The population was divided based on the tertiles of SCFAs, and logistic regression models assessed the relationship between SCFAs and T2DM. Generalized linear models tested the interactions between SCFAs and gut microbial diversity on glucose indicators (glucose, HbAlc and insulin). Compared to the lowest tertile of total SCFA, acetate and butyrate, the highest tertile exhibited lower T2DM prevalence, with ORs and 95% CIs of 0.291 (0.085-0.991), 0.160 (0.044-0.574) and 0.171 (0.047-0.620), respectively. Restricted cubic spline demonstrated an approximately inverse S-shaped association. We also noted interactions of the ACE index with the highest tertile of valerate on glucose levels (P-interaction = 0.022) and the Shannon index with the middle tertile of butyrate on insulin levels (P-interaction = 0.034). Genus Prevotella_9 and Odoribacter were inversely correlated with T2DM, and the genus Blautia was positively associated with T2DM. These bacteria are common SCFA-producing members.

CONCLUSIONS

Inverse S-shaped associations between SCFAs (total SCFA, acetate, and butyrate) and T2DM were observed. Valerate and butyrate modify glucose status with increasing gut microbial diversity.

Investigation of the causal relationship between inflammatory bowel disease and type 2 diabetes mellitus: a Mendelian randomization study

Background: Type 2 diabetes mellitus (T2DM) and inflammatory bowel disease (IBD) have been associated, according to various epidemiological research. This study uses Mendelian randomization (MR) to investigate the causal link between T2DM and IBD. Methods: To investigate the causal relationship between IBD and T2DM risk using European population data from the genome-wide association study (GWAS) summary datasets, we constructed a two-sample MR study to evaluate the genetically predicted impacts of liability towards IBD outcomes on T2DM risk. As instrumental variables (IVs), we chose 26 single nucleotide polymorphisms (SNPs) associated with IBD exposure data. The European T2DM GWAS data was obtained from the IEU OpenGWAS Project database, which contains 298,957 cases as the outcome data. The causal relationship between T2DM and IBD using a reverse MR analysis was also performed. Results: The two-sample MR analysis, with the Bonferroni adjustment for multiple testing, revealed that T2DM risk in Europeans is unaffected by their IBD liability (odds ratio (OR): 0.950-1.066, 95% confidence interval (CI): 0.885-1.019, p = 0.152-0.926). The effects of liability to T2DM on IBD were not supported by the reverse MR analysis either (OR: 0.739-1.131, 95% confidence interval (CI): 0.651-1.100, p = 0.058-0.832). MR analysis of IBS on T2DM also have no significant causal relationship (OR: 0.003-1.007, 95% confidence interval (CI): 1.013-5.791, p = 0.069-0.790). FUMA precisely mapped 22 protein-coding genes utilizing significant SNPs of T2DM acquired from GWAS. Conclusion: The MR study showed that the existing evidence did not support the significant causal effect of IBD on T2DM, nor did it support the causal impact of T2DM on IBD.

Synergistic association of long-term ozone exposure and solid fuel use with biomarkers of advanced fibrosis

This study aims to explore the association of combined exposure to cooking fuel type and ambient ozone (O3) levels with hepatic fibrosis indices among rural adults. A total of 21,010 participants were derived from the Henan Rural Cohort. Information regarding cooking fuel type was collected through a questionnaire, and the concentration of ground-level O3 for each subject was obtained from the Tracking Air Pollution in China (TAP) dataset. A generalized linear model was used to examine the independent association of cooking fuel type or O3 exposure with hepatic fibrosis indices (FIB-4, APRI, and AST/ALT), and their possible interactions with advanced fibrosis were conducted. Compared to clean fuel users, solid fuel users had increased the risk of advanced fibrosis, the adjusted odds ratio (OR) of its assessment by FIB-4 1.240 (1.151, 1.336), by APRI 1.298 (1.185, 1.422), and by AST/ALT 1.135 (1.049, 1.227), respectively. Compared to low O3 exposure, the adjusted ORs of advanced fibrosis assessed by FIB-4, APRI, and AST/ALT in women with high O3 exposure were correspondingly 1.219 (1.138, 1.305), 1.110 (1.017, 1.212), and 0.883 (0.822, 0.949). The adjusted ORs of advanced fibrosis assessed by FIB-4, APRI, and AST/ALT for solid fuel users with high O3 exposure relative to clean fuel users with low O3 exposure in women were 1.557 (1.381, 1.755), 1.427 (1.237, 1.644), and 0.979 (0.863, 1.108), respectively. Significant additive effect of O3 exposure and solid fuel use on FIB-4-defined advanced fibrosis was observed in women, which was quantified by RERI (0.265, 95%CI: 0.052, 0.477), AP (0.170 95%CI: 0.045, 0.295), and SI (1.906, 95%CI: 1.058, 3.432). Solid fuel users with high O3 exposure were significantly associated with elevated hepatic fibrosis indices among rural women, suggesting that poor air quality may induce hepatocellular injury, and women might be more vulnerable to air pollution. The findings indicate that using cleaner fuels in cooking is an effective measure to maintain sustainable development of the environment and gain beneficial effect on human health. Clinical trial registration: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

Association of long-term exposure to PM2.5 constituents with glucose metabolism in Chinese rural population

BACKGROUND

Evidence on the associations of fine particulate matter (PM_2.5) constituents and glucose metabolism is limited in resource-limited areas. This study aimed to explore the associations of PM_2.5 constituents with glucose metabolism in rural areas, and to further specify the most responsible constituent.

METHODS

A total of 38,442 adults were recruited from the Henan Rural Cohort Study during 2015-2017. Three-year averaged concentrations of PM_2.5 mass and its constituents (black carbon (BC), ammonium (NH₄⁺), nitrate (NO₃^-), organic matter (OM), inorganic sulfate (SO₄^2-), soil particles (SOIL) and sea salt (SS)) were estimated by a hybrid satellite-based model. Generalized linear model was applied to explore the associations of PM_2.5 mass and its constituents with type 2 diabetes mellitus (T2DM), fasting blood glucose (FBG), insulin, and HOMA-β. Proportion and residual analyses were employed to specify the most responsible constituent.

RESULTS

The adjusted odds ratio (OR) for T2DM associated with 1 μg/m³ increase was 1.02 for PM_2.5 mass, 1.28 for BC, 1.15 for NH₄⁺, 1.08 for NO₃^-, 1.10 for OM, 1.11 for SO₄^2-, and 1.12 for SOIL. Significant associations of PM_2.5 mass and its constituents with elevated FBG, decreased insulin and HOMA-β were also observed. Proportion and residual analyses indicated that BC was the most responsible constituent, in which 1 percentage increment in the proportion of BC in PM_2.5 corresponded with 1.51-fold risk for T2DM, 0.17 mmol/L increase in FBG, 2.18 μU/mL decrease in insulin, and 38.26 % decrease in HOMA-β; and 1 μg/m³ increment in the PM_2.5-adjusted BC corresponded with 1.59-fold risk for T2DM, 0.53 mmol/L increase in FBG, 4.79 μU/mL decrease in insulin, and 91.32 % decrease in HOMA-β.

CONCLUSIONS

PM_2.5 mass and its constituents (BC, NH₄⁺, NO₃^-, OM, SO₄^2-, SOIL) were associated with T2DM, increased FBG, decreased insulin and HOMA-β, of which BC was most responsible for these associations.

TRIAL REGISTRATION

The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

Stroke prevention in rural residents: development of a simplified risk assessment tool with artificial intelligence

BACKGROUND

Limited studies have focused on the risk assessment of stroke in rural regions. Moreover, the application of artificial intelligence in stroke risk scoring system is still insufficient. This study aims to develop a simplified and visualized risk score with good performance and convenience for rural stroke risk assessment, which is combined with a machine learning (ML) algorithm.

METHODS

Participants of the Henan Rural Cohort were enrolled in this study. The total participants (n = 38,322) were randomly split into a train set and a test set in the ratio of 7:3. An ML algorithm was used to select variables and the logistic regression was then applied to construct the scoring system. The C-statistic and the Brier score (BS) were used to evaluate the discrimination and calibration. The Framingham stroke risk profile (FSRP) and the self-reported stroke risk function (SRSRF) were chosen to be compared.

RESULTS

The Rural Stroke Risk Score (RSRS) was produced in this study, including age, drinking status, triglyceride, type 2 diabetes mellitus, hypertension, waist circumference, and family history of stroke. On validation, the C-statistic was 0.757 (95% CI 0.749-0.765) and the BS was 0.058 in the test set. In addition, the discrimination of RSRS was 6.02% and 7.34% higher than that of the FSRP and SRSRF, respectively.

CONCLUSIONS

A well-performed scoring system for assessing stroke risk in rural residents was developed in this study. This risk score would facilitate stroke screening and the prevention of cardiovascular disease in economically underdeveloped areas.

The underlying mechanism of PM2.5-induced ischemic stroke

Under the background of global industrialization, PM_2.5 has become the fourth-leading risk factor for ischemic stroke worldwide, according to the 2019 GBD estimates. This highlights the hazards of PM_2.5 for ischemic stroke, but unfortunately, PM_2.5 has not received the attention that matches its harmfulness. This article is the first to systematically describe the molecular biological mechanism of PM_2.5-induced ischemic stroke, and also propose potential therapeutic and intervention strategies. We highlight the effect of PM_2.5 on traditional cerebrovascular risk factors (hypertension, hyperglycemia, dyslipidemia, atrial fibrillation), which were easily overlooked in previous studies. Additionally, the effects of PM_2.5 on platelet parameters, megakaryocytes activation, platelet methylation, and PM_2.5-induced oxidative stress, local RAS activation, and miRNA alterations in endothelial cells have also been described. Finally, PM_2.5-induced ischemic brain pathological injury and microglia-dominated neuroinflammation are discussed. Our ultimate goal is to raise the public awareness of the harm of PM_2.5 to ischemic stroke, and to provide a certain level of health guidance for stroke-susceptible populations, as well as point out some interesting ideas and directions for future clinical and basic research.

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.