Association between Plasma Trace Element Concentrations in Early Pregnancy and Gestational Diabetes Mellitus in Shanghai, China

Are miR-26a and miR-26b microRNAs potent prognostic markers of gestational diabetes?

Background

Gestational diabetes mellitus is a common public health problem, accompanied by complications for the mother and fetus. So, introducing new biomarkers to identify early diabetes is essential. As serum miRNAs are potentially appropriate markers, we investigated miR-26a and miR-26b expression levels in pregnant women with and without gestational diabetes.

Method

Demographic and clinical characteristics of 40 gestational diabetic patients and 40 healthy controls were assessed. The expression level of miR-26a and miR-26b microRNAs was measured by real-time PCR. Statistical analysis was done with GraphPad Prism software (version 8.4.3).

Result

The findings of this study showed that the expression level of miR-26a and miR-26b increased in women with gestational diabetes compared with healthy pregnant women, but the increase in expression was only significant for miR-26a (p < 0.05).

Conclusion

According to the statistical and ROC curves, we suggest miR-26a as a potential biomarker for the early diagnosis of gestational diabetes mellitus.

Metalloestrogens exposure and risk of gestational diabetes mellitus: Evidence emerging from the systematic review and meta-analysis

BACKGROUND

Metalloestrogens are metals and metalloid elements with estrogenic activity found everywhere. Their impact on human health is becoming more apparent as human activities increase.

OBJECTIVE

Our aim is to conduct a comprehensive systematic review and meta-analysis of observational studies exploring the correlation between metalloestrogens (specifically As, Sb, Cr, Cd, Cu, Se, Hg) and Gestational Diabetes Mellitus (GDM).

METHODS

PubMed, Web of Science, and Embase were searched to examine the link between metalloestrogens (As, Sb, Cr, Cd, Cu, Se, and Hg) and GDM until December 2023. Risk estimates were derived using random effects models. Subgroup analyses were conducted based on study countries, exposure sample, exposure assessment method, and detection methods. Sensitivity analyses and adjustments for publication bias were carried out to assess the strength of the findings.

RESULTS

Out of the 389 articles identified initially, 350 met our criteria and 33 were included in the meta-analysis, involving 141,175 subjects (9450 cases, 131,725 controls). Arsenic, antimony, and copper exposure exhibited a potential increase in GDM risk to some extent (As: OR = 1.28, 95 % CI [1.08, 1.52]; Sb: OR = 1.73, 95 % CI [1.13, 2.65]; Cu: OR = 1.29, 95 % CI [1.02, 1.63]), although there is a high degree of heterogeneity (As: Q = 52.93, p < 0.05, I2 = 64.1 %; Sb: Q = 31.40, p < 0.05, I2 = 80.9 %; Cu: Q = 21.14, p < 0.05, I2 = 71.6 %). Conversely, selenium, cadmium, chromium, and mercury exposure did not exhibit any association with the risk of GDM in our study.

DISCUSSION

Our research indicates that the existence of harmful metalloestrogens in the surroundings has a notable effect on the likelihood of GDM. Hence, we stress the significance of environmental elements in the development of GDM and the pressing need for relevant policies and measures.

Mixture effects of trace element levels on cardiovascular diseases and type 2 diabetes risk in adults using G-computation analysis

There is an increasing concern about the health effects of exposure to a mixture of pollutants. This study aimed to evaluate the associations between serum levels of heavy/essential metals ([Arsenic (As), Cadmium (Cd), Mercury (Hg), Lead (Pb), Nickel (Ni), Chromium (Cr), Copper (Cu), Iron (Fe), and Zinc (Zn)]) and the risk of developing cardiovascular diseases (CVDs) and type 2 diabetes mellitus (T2D). Data were collected from 450 participants (150 with CVDs, 150 with T2D, and 150 healthy subjects) randomly selected from the Ravansar Non-Communicable Disease (RaNCD) cohort in Western Iran, covering the years 2018-2023. Trace element levels in the serum samples were assayed using ICP-MS. Logistic regression was performed to estimate the adjusted risk of exposure to single and multi-metals and CVD/T2D. Odds ratios were adjusted for age, sex, education, residential areas, hypertension, and BMI. The mixture effect of exposure to multi-metals and CVD/T2D was obtained using Quantile G-computation (QGC). In the logistic regression model, chromium, nickel, and zinc levels were associated with CVD, and significant trends were observed for these chemical quartiles (P < 0.001). Arsenic, chromium, and copper levels were also associated with T2D. The weight quartile sum (WQS) index was significantly associated with both CVD (OR 4.17, 95% CI 2.16-7.69) and T2D (OR 11.96, 95% CI 5.65-18.26). Cd, Pb, and Ni were the most heavily weighed chemicals in these models.The Cd had the highest weight among the metals in the CVD model (weighted at 0.78), followed by Hg weighted at 0.197. For T2D, the serum Pb (weighted at 0.32), Ni (weighted at 0.19), Cr (weighted at 0.17), and Cd (weighted at 0.14) were the most weighted in the G-computation model. The results showed the significant role of toxic and essential elements in CVDs and T2D risk. This association may be driven primarily by cadmium and mercury for CVDs and Pb, Ni, Cr, and Cd for T2D, respectively. Prospective studies with higher sample sizes are necessary to confirm or refute our preliminary results as well as to determine other important elements.

The relationship between plasma nickel concentrations and type 2 diabetes mellitus risk: A protective effect within a specific range

BACKGROUND

Nickel is considered an essential nutrient for certain microbial, plant, and animal species, but its role in human health remains controversial. Some studies have reported the relationship between nickel and type 2 diabetes mellitus (T2DM), but the results are not consistent and the mechanism is not clear, which needs further exploration.

AIM

To investigate the possible correlation between nickel and T2DM.

METHODS

We conducted a case-control study of 192 patients with T2DM and 189 healthy controls at a hospital in central China. Plasma concentrations of nickel and six other trace elements were measured with inductively coupled plasma mass spectrometry. Logistic regression models, restricted cubic spline models (RCS), and Bayesian kernel machine regression (BKMR) were used to evaluate the relationship between plasma nickel and T2DM and its metabolic risk factors, as well as the presence or absence of interactions between nickel and other elements.

RESULTS

The T2DM group exhibited considerably lower plasma nickel levels than the control group (P < 0.001). Whether using a crude or adjusted model, logistic regression analysis finds a negative correlation between nickel levels and the risk of T2DM (P trend < 0.001). According to the RCS, the risk of T2DM reduces with rising nickel levels when the value is below 6.1 μg/L; nickel has a negative linear correlation with fasting plasma glucose (FPG), an inverse U-shaped connection with superoxide dismutase (SOD), and a positive linear correlation with malondialdehyde (MDA) (all P overall < 0.05). The plasma nickel concentration was positively correlated with zinc, vanadium, and chromium (r = 0.23, 0.11, and 0.19, respectively; all P < 0.05) and negatively correlated with copper (r = - 0.11, P < 0.05). In the BKMR model, interactions of nickel with zinc on T2DM and SOD, nickel with chromium on T2DM and homeostasis model assessment of β cell (HOMA-β), and nickel with copper on FPG, homeostasis model assessment of insulin (HOMA-IR), and MDA were observed.

CONCLUSION

Nickel may have a dual effect on the risk of T2DM, with a protective range of less than 6.1 μg/L. Potential interactions between nickel, copper, zinc, and chromium existed in their associations with T2DM and its metabolic risk factors.

Role of placental barrier on trace element transfer in maternal fetal system and hypertensive disorders complicating pregnancy and gestational diabetes mellitus

BACKGROUND

Hypertensive disorders complicating pregnancy (HDCP) and gestational diabetes mellitus (GDM) can affect the placental barrier function to varying degrees. However, current studies show that the transfer and distribution characteristics of trace elements in the maternal-fetal system are still unclear. This study investigated the effect of the placental barrier on the transfer of trace elements from mother to fetus and its relationship with HDCP and GDM.

METHODS

A case-control method was used in this study. 140 pairs of samples were collected; 60 were from healthy pregnant women, and 80 were from patients with pregnancy complications. The contents of trace elements in paired samples were determined by inductively coupled plasma-mass spectrometry (ICP-MS). SPSS software was used to analyze the differences in trace element levels in matched samples of each group. The correlations were analyzed based on Pearson's correlation factor (r).

RESULTS

The distribution characteristics of Fe content in the pathological group (HDCP group and GDM group) were the same as those in the normal group (umbilical cord blood > maternal blood > placenta), but there was no significant difference in the iron content in maternal blood and cord blood of pathological group. The distribution characteristics of Mn content in the pathological group (placenta > umbilical cord blood > maternal blood) were changed compared with those in the normal group (placenta > maternal blood > umbilical cord blood). In addition, the placental Cr content and cord blood Cr and Ni content of the pathological group were higher than those of the normal group. HDCP placental Cr and GDM placental Fe levels were significantly correlated with the Apgar score.

CONCLUSIONS

The transfer of Fe and Mn and the placental barrier function of Cr and Ni in the maternal-fetal system of HDCP and GDM are significantly altered, which directly or indirectly increases the maternal and fetal health risk.

Blood manganese level and gestational diabetes mellitus: a systematic review and meta-analysis

BACKGROUND

Previous studies evaluating the relationship between blood manganese (Mn) level and gestational diabetes mellitus (GDM) in pregnant women showed inconsistent results. A systematic review and meta-analysis was therefore performed to investigate the above association.

METHODS

Relevant observational studies were obtained by search of electronic databases including Medline, Embase, Cochrane Library and Web of Science from database inception to 10 March 2023. Two authors independently performed database search, literature identification and data extraction. A randomised-effects model was selected to pool the data by incorporating the influence of potential heterogeneity. Subgroup analysis was performed to evaluate the influence of study characteristics on the results of the meta-analysis.

RESULTS

Six datasets from five observational studies, involving 91,249 pregnant women were included in the meta-analysis. Among the participants, 3597 (3.9%) were diagnosed as GDM. Overall, pooled results showed that a high blood level of Mn was associated with a higher risk of GDM (compared between women with highest versus lowest category blood Mn, odds ratio: 1.31, 95% confidence interval: 1.19-1.44, p < .001) with no significant heterogeneity (p for Cochrane Q-test = 0.93, I2 = 0%). Subgroup analyses according to study design, mean maternal age, matrix or methods for measuring blood Mn, and the incidence of GDM also showed consistent results (p for subgroup difference all >.05).

CONCLUSIONS

Results of the meta-analysis suggest that a high blood Mn level may be a risk factor of GDM in pregnant women. Studies are needed to determine the underlying mechanisms, and to investigate if the relationship between blood Mn level and GDM is dose-dependent.

Micronutrients in Maternal and Infant Health: Where We Are and Where We Should Go

The first 1000 days of life are defined by the World Health Organization as a "window of opportunity" for a person's growth and development, and nutrition is particularly important during this time window [...].