Polychlorinated biphenyls, polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, pesticides, and diabetes in the Anniston Community Health Survey follow-up (ACHS II): single exposure and mixture analysis approaches

Unraveling the pesticide-diabetes connection: A case-cohort study integrating Mendelian randomization analysis with a focus on physical activity's mitigating effect

BACKGROUND AND AIMS

There is no evidence on the longitudinal and causal associations between multiple pesticides and the incidence of type 2 diabetes mellitus (T2DM) in the Chinese rural population, and whether physical activity (PA) modified these associations remains unclear. Here, we aimed to investigate the longitudinal and causal associations between pesticides mixture and T2DM, and determine whether PA modified these associations.

METHODS

A total of 925 subjects with normal glucose and 925 subjects with impaired fasting glucose (IFG) were enrolled in this case-cohort study. A total of 51 targeted pesticides were quantified at baseline. Logistic regression, quantile g-computation, and Bayesian kernel machine regression (BKMR) were used to assess the individual and combined effects of pesticides on IFG and T2DM. Mendelian randomization (MR) analysis was employed to obtain the causal association between pesticides and T2DM.

RESULTS

After 3-year follow-up, one-unit increment in ln-isofenphos, ln-malathion, and ln-deltamethrin were associated with an increase conversion of IFG to T2DM (FDR-P<0.05). One quartile increment in organochlorine pesticides (OCPs), organophosphorus pesticides (OPs), herbicides and pyrethroids mixtures were related to a higher incidence of T2DM among IFG patients (P<0.05). The BKMR results showed a positive trend between exposure to pesticides mixture and T2DM. The MR analysis indicated a positive association between exposure to pesticides and T2DM risk (P<0.05). No any significant association was found between pesticides and IFG. In addition, compared to subjects with high levels of PA, those with low levels of PA were related to increased risk of T2DM with the increased levels of pesticides among IFG patients.

CONCLUSIONS

Individual and combined exposure to pesticides increased the incidence of T2DM among IFG patients. MR analysis further supported the causal association of pesticides exposure with T2DM risk. Our study furtherly indicated that high levels of PA attenuated the diabetogenic effect of pesticides exposure.

Diabetes mellitus and serum organochlorine pesticides mixtures in Mexican women

BACKGROUND

Very recently, it has been reported that exposure to different mixtures of organochlorine pesticides (OCP) is associated with the development of diabetes mellitus (DM). In Mexico, DM is a public health problem that might be related to the historical intense use of OCP. We aimed to evaluate, the association between DM and serum concentrations of OCP mixtures, and identify the main contributors within them.

METHODS

We conducted a secondary cross-sectional analysis on the control group from a breast cancer population-based case-control study conducted from 2007 to 2011 in Northern Mexico. We identified 214 self-reported diabetic women and 694 non-diabetics. We obtained direct information about sociodemographic, lifestyle and reproductive characteristics. We determined 24 OCP and metabolites in serum by gas chromatography using an electron capture micro detector. We used Weighted Quantile Sum regression to assess the association of DM and exposure to multiple OCP, and the contribution of each compound within the mixture.

RESULTS

We found a positive adjusted association between DM and an OCP mixture (OR: 2.63, 95%CI: 1.85, 3.74), whose primary contribution arose from p, p'-DDE (mean weight 23.3%), HCB (mean weight 17.3%), trans nonachlor (mean weight 15.4%), o, p'-DDE (mean weight 7.3%), heptachlor epoxide (mean weight 5.9%), oxychlordane (mean weight 4.7%), and heptachlor (mean weight 4.5%). In addition, these OCP along with p, p'-DDT and cis chlordane, were of concern and remained associated when excluding hypertensive women from the analysis (OR 2.55; 95% CI 1.56, 4.18).

CONCLUSIONS

Our results indicate, for the first time in a Latin-American population, that the concomitant exposure to multiple OCP is associated with DM. Further research is needed since the composition of OCP mixtures may vary according to regional pesticides use patterns.

Chronic Aroclor 1260 exposure alters the mouse liver proteome, selenoproteins, and metals in steatotic liver disease

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) continues to increase due in part to the obesity epidemic and to environmental exposures to metabolism disrupting chemicals. A single gavage exposure of male mice to Aroclor 1260 (Ar1260), an environmentally relevant mixture of non-dioxin-like polychlorinated biphenyls (PCBs), resulted in steatohepatitis and altered RNA modifications in selenocysteine tRNA 34 weeks post-exposure. Unbiased approaches identified the liver proteome, selenoproteins, and levels of 25 metals. Ar1260 altered the abundance of 128 proteins. Enrichment analysis of the liver Ar1260 proteome included glutathione metabolism and translation of selenoproteins. Hepatic glutathione peroxidase 4 (GPX4) and Selenoprotein O (SELENOO) were increased and Selenoprotein F (SELENOF), Selenoprotein S (SELENOS), Selenium binding protein 2 (SELENBP2) were decreased with Ar1260 exposure. Increased copper, selenium (Se), and zinc and reduced iron levels were detected. These data demonstrate that Ar1260 exposure alters the (seleno)proteome, Se, and metals in MASLD-associated pathways.

Associations of chronic exposure to a mixture of pesticides and type 2 diabetes mellitus in a Chinese elderly population

Epidemiological studies have related exposure to pesticides to increased risk of diabetes. However, few studies have evaluated the health effects of mixed pesticides exposure, especially in an elderly population. Here, we utilized gas chromatography-tandem mass spectrometry to quantify the levels of 39 pesticides in 4 categories in a Chinese elderly population. Then we used general linear models to explore the association between individual pesticide exposure and type 2 diabetes mellitus (T2DM). Restricted cubic spline (RCS) models were fitted to identify potential non-linearities between those associations. Furthermore, stratified analysis by gender was conducted to explore the gender-specific associations. Finally, we used weighted quantile sum (WQS) regression, quantile-based g computation (qgcomp), and Bayesian kernel machine regression (BKMR) to evaluate the effects of mixed exposure to 39 pesticides. The results showed that exposure to pesticides was associated with high risk of T2DM, with β-Hexachlorocyclohexane (β-BHC) and oxadiazon being the most significant independent contributors, which was pronounced among elderly women. Moreover, the association of β-BHC and oxadiazon with T2DM was linear. These indicated that it is an urgent need to take practical measures to control these harmful pesticides.

Combined effects of organochlorine pesticides on type 2 diabetes mellitus: Insights from endocrine disrupting effects of hormones

Association between organochlorine pesticides (OCPs) exposure and type 2 diabetes mellitus (T2DM) remains contradictory, and the evidence is mostly focused on a single exposure. Here, we assessed the associations between individual and combined OCPs exposure and T2DM, and explored the underlying mechanism of sex hormones and the methylation levels of sex hormone receptors in above associations. A case-control study with 1812 participants was performed. Gas chromatography mass spectrometry, liquid chromatography-tandem mass spectrometry, and pyrosequencing were used to measure plasma OCPs, serum sex hormones, and whole blood methylation levels of sex hormone receptors, respectively. Generalized linear models were used to analyze the relationships between OCPs, sex hormones, the methylation levels of sex hormone receptors, and T2DM. Quantile based g-computation (QGC) and Bayesian Kernel Machine Regression (BKMR) were employed to assess the combined OCPs exposure. The roles of sex hormones and the methylation levels of their receptors were evaluated by moderating mediation models. After adjusting for covariates, each unit (2.718 ng/ml) increase in p,p'-DDE was associated with a higher risk of T2DM in males (odds ratio (OR) and 95% confidence interval (CI): 1.066 (1.023, 1.112)). QGC and BKMR showed a positive combined effect in the associations of OCPs mixtures on T2DM among premenopausal females, and positive effects but not statistically significant among males and postmenopausal females. p,p'-DDE was the largest contributor for the positive associations. Furthermore, testosterone mediated 21.149% of the associations of p,p'-DDE with T2DM moderated by the androgen receptor methylation (ARm) located in CpG island 1. Individual and mixtures of OCPs exposure were positively linked to elevated risk of T2DM. Testosterone and ARm may participate in the related processes of OCPs with T2DM, providing new insights into the adverse endocrine effects caused by OCPs and specific pathways for the etiology and control of diabetes.

Associations between blood essential metal mixture and serum uric acid: a cross-sectional study

Introduction

Although several studies have explored the associations between single essential metals and serum uric acid (SUA), the study about the essential metal mixture and the interactions of metals for hyperuricemia remains unclear.

Methods

We performed a cross-sectional study to explore the association of the SUA levels with the blood essential metal mixture, including magnesium (Mg), calcium (Ca), iron (Fe), copper (Cu), zinc (Zn), manganese (Mn) in Chinese community-dwelling adults (n=1039). The multivariable linear regression, the weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were conducted to estimate the associations of blood essential metals with SUA levels and the BKMR model was also conducted to estimate the interactions of the essential metals on SUA.

Results

In the multivariable linear regression, the association of blood Mg, Mn, and Cu with SUA was statistically significant, both in considering multiple metals and a single metal. In WQS regression [β=13.59 (95%CI: 5.57, 21.60)] and BKMR models, a positive association was found between the mixture of essential metals in blood and SUA. Specifically, blood Mg and Cu showed a positive association with SUA, while blood Mn showed a negative association. Additionally, no interactions between individual metals on SUA were observed.

Discussion

In conclusion, further attention should be paid to the relationship between the mixture of essential metals in blood and SUA. However, more studies are needed to confirm these findings.