Mineralocorticoids, glucose homeostasis and type 2 diabetes mellitus: The Henan Rural Cohort study

Risk Estimation of Gestational Diabetes Mellitus in the First Trimester

CONTEXT

There is no early, first-trimester risk estimation available to predict later (gestational week 24-28) gestational diabetes mellitus (GDM); however, it would be beneficial to start an early treatment to prevent the development of complications.

OBJECTIVE

We aimed to identify early, first-trimester prediction markers for GDM.

METHODS

The present case-control study is based on the study cohort of a Hungarian biobank containing biological samples and follow-up data from 2545 pregnant women. Oxidative-nitrative stress-related parameters, steroid hormone, and metabolite levels were measured in the serum/plasma samples collected at the end of the first trimester from 55 randomly selected control and 55 women who developed GDM later.

RESULTS

Pregnant women who developed GDM later during the pregnancy were older and had higher body mass index. The following parameters showed higher concentration in their serum/plasma samples: fructosamine, total antioxidant capacity, testosterone, cortisone, 21-deoxycortisol; soluble urokinase plasminogen activator receptor, dehydroepiandrosterone sulfate, dihydrotestosterone, cortisol, and 11-deoxycorticosterone levels were lower. Analyzing these variables using a forward stepwise multivariate logistic regression model, we established a GDM prediction model with a specificity of 96.6% and sensitivity of 97.5% (included variables: fructosamine, cortisol, cortisone, 11-deoxycorticosterone, SuPAR).

CONCLUSION

Based on these measurements, we accurately predict the development of later-onset GDM (24th-28th weeks of pregnancy). Early risk estimation provides the opportunity for targeted prevention and the timely treatment of GDM. Prevention and slowing the progression of GDM result in a lower lifelong metabolic risk for both mother and offspring.

Co-exposure of organophosphorus pesticides is associated with increased risk of type 2 diabetes mellitus in a Chinese population

OBJECTIVE

The epidemiological evidence of human exposure to organophosphorus pesticides (OPPs) with type 2 diabetes mellitus (T2DM) and prediabetes (PDM) is scarce. We aimed to examine the association of T2DM/PDM risk with single OPP exposure and multi-OPP co-exposure.

METHODS

Plasma levels of ten OPPs were measured using the gas chromatography-triple quadrupole mass spectrometry (GC-MS/MS) among 2734 subjects from the Henan Rural Cohort Study. We used generalized linear regression to estimate odds ratios (ORs) or β with 95% confidence intervals (CIs), and constructed quantile g-computation and Bayesian kernel machine regression (BKMR) models to investigate the association of OPPs mixture with the risk of T2DM and PDM.

RESULTS

High detection rates ranged from 76.35% (isazophos) to 99.17% (malathion and methidathion) for all OPPs. Several plasma OPPs concentrations were in positive correlation with T2DM and PDM. Additionally, positive associations of several OPPs with fasting plasma glucose (FPG) values and glycosylated hemoglobin (HbA1c) levels were observed. In the quantile g-computation, we identified significantly positive associations between OPPs mixtures and T2DM as well as PDM, and fenthion had the greatest contribution for T2DM, followed by fenitrothion and cadusafos. As for PDM, the increased risk was largely explained by cadusafos, fenthion, and malathion. Furthermore, BKMR models suggested that co-exposure to OPPs was linked to an increased risk of T2DM and PDM.

CONCLUSION

Our findings suggested that the individual and mixture of OPPs co-exposure were associated with an increased risk of T2DM and PDM, implying that OPPs might act an important role in the development of T2DM.

Negative associations of morning serum cortisol levels with obesity: the Henan rural cohort study

AIMS

To evaluate the associations of morning serum cortisol levels with obesity defined by different indices in Chinese rural populations.

MATERIALS AND METHODS

A cross-sectional study was performed including 6198 participants (2566 males and 3632 females). Serum cortisol was collected in morning and quantified by liquid chromatography-tandem mass spectrometry. Obesity was defined by body mass index (BMI), body fat percentage (BFP), waist-to-height ratio (WHtR), waist circumference (WC), visceral fat index (VFI) and waist-to-hip ratio (WHR). Both multivariable liner regression, logistic regression and restrictive cubic splines models were used to estimate the gender-specific relationships between cortisol levels and obesity defined by different indices, respectively.

RESULTS

After adjusting for potential confounders, serum cortisol was negatively associated with different obesity measures, except obese females defined by BFP (for instance, overall obesity defined by BMI, Quartile 4 vs. Quartile 1, odds ratio (OR) = 0.25, 95% confidence interval (CI):0.15, 0.41 in males, and OR = 0.58, 95% CI: 0.42,0.80 in females, central obesity defined by WC, OR = 0.52, 95% CI:0.39,0.69 in males and OR = 0.63, 95% CI:0.51,0.77 in females). Similarly, restrictive cubic splines showed the nonlinear relationship between high levels of cortisol and different obesity indices. Furthermore, ROC curve analysis indicated that cortisol could improve the discrimination of model with common biomarkers.

CONCLUSION

Morning serum cortisol were negatively related to obesity defined by different indices in Chinese rural populations. In addition, cortisol could be as a biomarker for prediction of obesity in males.