Association of urinary metals levels with type 2 diabetes risk in coke oven workers

Bisphenol mixtures, metal mixtures and type 2 diabetes mellitus: Insights from metabolite profiling

BACKGROUND

Little is known about the combined effect of bisphenol mixtures and metal mixtures on type 2 diabetes mellitus (T2DM) risk, and the mediating roles of metabolites.

METHODS

The study included 606 pairs of T2DM cases and controls matched by age and sex, and information of participants was collected through questionnaires and laboratory tests. Serum bisphenol and plasma metal concentrations were measured using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. Widely targeted metabolomics was employed to obtain the serum metabolomic profiles. Conditional logistic regression models were used to assess the single associations of bisphenols and metals with T2DM risk after multivariable adjustment. Additionally, the joint effects of bisphenol mixtures and metal mixtures were examined using quantile-based g-computation (QG-C) models. Furthermore, differential metabolites associated with T2DM were identified, and mediation analyses were performed to explore the role of metabolites in the associations of bisphenols and metals with T2DM risk.

RESULTS

The results showed bisphenol mixtures were associated with an increased T2DM risk, with bisphenol A (BPA) identified as the primary contributor. While the association between metal mixtures and T2DM remained inconclusive, cobalt (Co), iron (Fe), and zinc (Zn) showed the highest weight indices for T2DM risk. A total of 154 differential metabolites were screened between the T2DM cases and controls. Mediation analyses indicated that 9 metabolites mediated the association between BPA and T2DM, while L-valine mediated the association between Zn and T2DM risk.

CONCLUSIONS

The study indicated that BPA, Co, Fe, and Zn were the primary contributors to increased T2DM risk, and metabolites played a mediating role in the associations of BPA and Zn with the risk of T2DM. Our findings contribute to a better understanding of the mechanisms underlying the associations of bisphenols and metals with T2DM.

Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis

Background and objective

Heavy metals, ubiquitous in the environment, pose a global public health concern. The correlation between these and diabetic kidney disease (DKD) remains unclear. Our objective was to explore the correlation between heavy metal exposures and the incidence of DKD.

Methods

We analyzed data from the NHANES (2005-2020), using machine learning, and cross-sectional survey. Our study also involved a bidirectional two-sample Mendelian randomization (MR) analysis.

Results

Machine learning reveals correlation coefficients of -0.5059 and - 0.6510 for urinary Ba and urinary Tl with DKD, respectively. Multifactorial logistic regression implicates urinary Ba, urinary Pb, blood Cd, and blood Pb as potential associates of DKD. When adjusted for all covariates, the odds ratios and 95% confidence intervals are 0.87 (0.78, 0.98) (p = 0.023), 0.70 (0.53, 0.92) (p = 0.012), 0.53 (0.34, 0.82) (p = 0.005), and 0.76 (0.64, 0.90) (p = 0.002) in order. Furthermore, multiplicative interactions between urinary Ba and urinary Sb, urinary Cd and urinary Co, urinary Cd and urinary Pb, and blood Cd and blood Hg might be present. Among the diabetic population, the OR of urinary Tl with DKD is a mere 0.10, with a 95%CI of (0.01, 0.74), urinary Co 0.73 (0.54, 0.98) in Model 3, and urinary Pb 0.72 (0.55, 0.95) in Model 2. Restricted Cubic Splines (RCS) indicate a linear linkage between blood Cd in the general population and urinary Co, urinary Pb, and urinary Tl with DKD among diabetics. An observable trend effect is present between urinary Pb and urinary Tl with DKD. MR analysis reveals odds ratios and 95% confidence intervals of 1.16 (1.03, 1.32) (p = 0.018) and 1.17 (1.00, 1.36) (p = 0.044) for blood Cd and blood Mn, respectively.

Conclusion

In the general population, urinary Ba demonstrates a nonlinear inverse association with DKD, whereas in the diabetic population, urinary Tl displays a linear inverse relationship with DKD.

Association of serum metal levels with type 2 diabetes: A prospective cohort and mediating effects of metabolites analysis in Chinese population

Several studies have suggested an association between exposure to various metals and the onset of type 2 diabetes (T2D). However, the results vary across different studies. We aimed to investigate the associations between serum metal concentrations and the risk of developing T2D among 8734 participants using a prospective cohort study design. We utilized inductively coupled plasmamass spectrometry (ICP-MS) to assess the serum concentrations of 27 metals. Cox regression was applied to calculate the hazard ratios (HRs) for the associations between serum metal concentrations on the risk of developing T2D. Additionally, 196 incident T2D cases and 208 healthy control participants were randomly selected for serum metabolite measurement using an untargeted metabolomics approach to evaluate the mediating role of serum metabolite in the relationship between serum metal concentrations and the risk of developing T2D with a nested casecontrol study design. In the cohort study, after Bonferroni correction, the serum concentrations of zinc (Zn), mercury (Hg), and thallium (Tl) were positively associated with the risk of developing T2D, whereas the serum concentrations of manganese (Mn), molybdenum (Mo), barium (Ba), lutetium (Lu), and lead (Pb) were negatively associated with the risk of developing T2D. After adding these eight metals, the predictive ability increased significantly compared with that of the traditional clinical model (AUC: 0.791 vs. 0.772, P=8.85×10-5). In the nested casecontrol study, a machine learning analysis revealed that the serum concentrations of 14 out of 1579 detected metabolites were associated with the risk of developing T2D. According to generalized linear regression models, 7 of these metabolites were significantly associated with the serum concentrations of the identified metals. The mediation analysis showed that two metabolites (2-methyl-1,2-dihydrophthalazin-1-one and mestranol) mediated 46.81% and 58.70%, respectively, of the association between the serum Pb concentration and the risk of developing T2D. Our study suggested that serum Mn, Zn, Mo, Ba, Lu, Hg, Tl, and Pb were associated with T2D risk. Two metabolites mediated the associations between the serum Pb concentration and the risk of developing T2D.

Associations of metals and metal mixtures with glucose homeostasis: A combined bibliometric and epidemiological study

This study employs a combination of bibliometric and epidemiological methodologies to investigate the relationship between metal exposure and glucose homeostasis. The bibliometric analysis quantitatively assessed this field, focusing on study design, predominant metals, analytical techniques, and citation trends. Furthermore, we analyzed cross-sectional data from Beijing, examining the associations between 14 blood metals and 6 glucose homeostasis markers using generalized linear models (GLM). Key metals were identified using LASSO-PIPs criteria, and Bayesian kernel machine regression (BKMR) was applied to assess metal mixtures, introducing an "Overall Positive/Negative Effect" concept for deeper analysis. Our findings reveal an increasing research interest, particularly in selenium, zinc, cadmium, lead, and manganese. Urine (27.6%), serum (19.0%), and whole blood (19.0%) were the primary sample types, with cross-sectional studies (49.5%) as the dominant design. Epidemiologically, significant associations were found between 9 metals-cobalt, copper, lithium, manganese, nickel, lead, selenium, vanadium, zinc-and glucose homeostasis. Notably, positive-metal mixtures exhibited a significant overall positive effect on insulin levels, and notable interactions involving nickel were identified. These finding not only map the knowledge landscape of research in this domain but also introduces a novel perspective on the analysis strategies for metal mixtures.

Associations of essential metals with the risk of aortic arch calcification: a cross-sectional study in a mid-aged and older population of Shenzhen, China

Vascular calcification is a strong predictor of cardiovascular events. Essential metals play critical roles in maintaining human health. However, the association of essential metal levels with risk of aortic arch calcification (AoAC) remains unclear. We measured the plasma concentrations of nine essential metals in a cross-sectional population and evaluated their individual and combined effects on AoAC risk using multiple statistical methods. We also explored the mediating role of fasting glucose. In the logistic regression model, higher quartiles of magnesium and copper were associated with the decreased AoAC risk, while higher quartile of manganese was associated with higher AoAC risk. The least absolute shrinkage and selection operator penalized regression analysis identified magnesium, manganese, calcium, cobalt, and copper as key metals associated with AoAC risk. The weighted quantile sum regression suggested a combined effect of metal mixture. A linear and positive dose-response relationship was found between manganese and AoAC in males. Moreover, blood glucose might mediate a proportion of 9.38% of the association between manganese exposure and AoAC risk. In summary, five essential metal levels were associated with AoAC and showed combined effect. Fasting glucose might play a significant role in mediating manganese exposure-associated AoAC risk.

Chemical contaminants in blood and their implications in chronic diseases

Artificial chemical products are widely used and ubiquitous worldwide and pose a threat to the environment and human health. Accumulating epidemiological and toxicological evidence has elucidated the contributions of environmental chemical contaminants to the incidence and development of chronic diseases that have a negative impact on quality of life or may be life-threatening. However, the pathways of exposure to these chemicals and their involvements in chronic diseases remain unclear. We comprehensively reviewed the research progress on the exposure risks of humans to environmental contaminants, their body burden as indicated by blood monitoring, and the correlation of blood chemical contaminants with chronic diseases. After entering the human body through various routes of exposure, environmental contaminants are transported to target organs through blood circulation. The application of the modern analytical techniques based on human plasma or serum specimens is promising for determining the body burden of environmental contaminants, including legacy persistent organic pollutants, emerging pollutants, and inorganic elements. Furthermore, their body burden, as indicated by blood monitoring correlates with the incidence and development of metabolic syndromes, cancers, chronic nervous system diseases, cardiovascular diseases, and reproductive disorders. On this basis, we highlight the urgent need for further research on environmental pollution causing health problems in humans.

Effects of Various Heavy Metal Exposures on Insulin Resistance in Non-diabetic Populations: Interpretability Analysis from Machine Learning Modeling Perspective

Increasing and compelling evidence has been proved that heavy metal exposure is involved in the development of insulin resistance (IR). We trained an interpretable predictive machine learning (ML) model for IR in the non-diabetic populations based on levels of heavy metal exposure. A total of 4354 participants from the NHANES (2003-2020) with complete information were randomly divided into a training set and a test set. Twelve ML algorithms, including random forest (RF), XGBoost (XGB), logistic regression (LR), GaussianNB (GNB), ridge regression (RR), support vector machine (SVM), multilayer perceptron (MLP), decision tree (DT), AdaBoost (AB), Gradient Boosting Decision Tree (GBDT), Voting Classifier (VC), and K-Nearest Neighbour (KNN), were constructed for IR prediction using the training set. Among these models, the RF algorithm had the best predictive performance, showing an accuracy of 80.14%, an AUC of 0.856, and an F1 score of 0.74 in the test set. We embedded three interpretable methods, the permutation feature importance analysis, partial dependence plot (PDP), and Shapley additive explanations (SHAP) in RF model for model interpretation. Urinary Ba, urinary Mo, blood Pb, and blood Cd levels were identified as the main influencers of IR. Within a specific range, urinary Ba (0.56-3.56 µg/L) and urinary Mo (1.06-20.25 µg/L) levels exhibited the most pronounced upwards trend with the risk of IR, while blood Pb (0.05-2.81 µg/dL) and blood Cd (0.24-0.65 µg/L) levels showed a declining trend with IR. The findings on the synergistic effects demonstrated that controlling urinary Ba levels might be more crucial for the management of IR. The SHAP decision plot offered personalized care for IR based on heavy metal control. In conclusion, by utilizing interpretable ML approaches, we emphasize the predictive value of heavy metals for IR, especially Ba, Mo, Pb, and Cd.

Update of the risk assessment of inorganic arsenic in food

The European Commission asked EFSA to update its 2009 risk assessment on arsenic in food carrying out a hazard assessment of inorganic arsenic (iAs) and using the revised exposure assessment issued by EFSA in 2021. Epidemiological studies show that the chronic intake of iAs via diet and/or drinking water is associated with increased risk of several adverse outcomes including cancers of the skin, bladder and lung. The CONTAM Panel used the benchmark dose lower confidence limit based on a benchmark response (BMR) of 5% (relative increase of the background incidence after adjustment for confounders, BMDL05) of 0.06 μg iAs/kg bw per day obtained from a study on skin cancer as a Reference Point (RP). Inorganic As is a genotoxic carcinogen with additional epigenetic effects and the CONTAM Panel applied a margin of exposure (MOE) approach for the risk characterisation. In adults, the MOEs are low (range between 2 and 0.4 for mean consumers and between 0.9 and 0.2 at the 95th percentile exposure, respectively) and as such raise a health concern despite the uncertainties.

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.

Urinary metal profiles in mother-offspring pairs and their association with early dysglycemia in the International Hyperglycemia and Adverse Pregnancy Outcome Follow Up Study (HAPO-FUS)

BACKGROUND

Variations in dietary intake and environmental exposure patterns of essential and non-essential trace metals influence many aspects of human health throughout the life span.

OBJECTIVE

To examine the relationship between urine profiles of essential and non-essential metals in mother-offspring pairs and their association with early dysglycemia.

METHODS

Herein, we report findings from an ancillary study to the international Hyperglycemia and Adverse Pregnancy Outcome Follow-Up Study (HAPO-FUS) that examined urinary essential and non-essential metal profiles from mothers and offspring ages 10-14 years (1012 mothers, 1013 offspring, 968 matched pairs) from 10 international sites.

RESULTS

Our analysis demonstrated a diverse exposure pattern across participating sites. In multiple regression modelling, a positive association between markers of early dysglycemia and urinary zinc was found in both mothers and offspring after adjustment for common risk factors for diabetes. The analysis showed weaker, positive, and negative associations of the 2-h glucose value with urinary selenium and arsenic respectively. A positive association between 2-h glucose values and cadmium was found only in mothers in the fully adjusted model when participants with established diabetes were excluded. There was a high degree of concordance between mother and offspring urinary metal profiles. Mother-to-offspring urinary metal ratios were unique for each metal, providing insights into changes in their homeostasis across the lifespan.

SIGNIFICANCE

Urinary levels of essential and non-essential metals are closely correlated between mothers and their offspring in an international cohort. Urinary levels of zinc, selenium, arsenic, and cadmium showed varying degrees of association with early dysglycemia in a comparatively healthy cohort with a low rate of preexisting diabetes.

IMPACT STATEMENT

Our data provides novel evidence for a strong correlation between mother and offspring urinary metal patterns with a unique mother-to-offspring ratio for each metal. The study also provides new evidence for a strong positive association between early dysglycemia and urinary zinc, both in mothers and offspring. Weaker positive associations with urinary selenium and cadmium and negative associations with arsenic were also found. The low rate of preexisting diabetes in this population provides the unique advantage of minimizing the confounding effect of preexisting, diabetes related renal changes that would alter the relationship between dysglycemia and renal metal excretion.

Associations of nickel exposure with diabetes: evidence from observational studies

The results of environmental epidemiological studies regarding the relationship between human exposure to nickel and the risk of diabetes remain controversial. Therefore, we performed a meta-analysis to investigate the relationship between nickel exposure and diabetes. PubMed, Web of Science, and Embase electronic databases were thoroughly searched from their inception to May 2023 to obtain relevant studies. The random-effects model was employed to determine pooled odds ratios (ORs) and 95% confidence intervals (CIs). Stratified and sensitivity analyses were also performed. Cochran Q test and I2 statistic were employed to assess heterogeneity between studies. Begg's and Egger's tests were employed to evaluate publication bias. The indicated studies were evaluated using the ROBINS-E risk of bias tool. The dose-response relationship between nickel in urine and diabetes risk was estimated by restricted cubic spline. A total of 12 studies with 30,018 participants were included in this study. In this meta-analysis, comparing the highest vs. lowest levels of nickel exposure, the pooled ORs for diabetes were 1.42 (95% confidence interval 1.14-1.78) for urine and 1.03 (0.57-1.86) for blood, respectively. A linear relationship between urinary nickel and diabetes risk was discovered in the dose-response analysis (P nonlinearity = 0.6198). Each 1 µg/L increase of urinary nickel, the risk of diabetes increased by 7% (OR = 1.07, 95% CI 1.04-1.10). The risk of diabetes was positively correlated with urine nickel exposure, whereas the risk was not significantly correlated with blood nickel. In the future, more high-quality prospective studies are needed to validate this conclusion.

Toxicogenomic analysis of physiologically important metals: An integrated in silico approach

Biologically important metals regulate cellular homeostasis in living systems. Anthropogenic exposure to these metals can cause adverse effects, including an increased incidence of diseases in humans such as cancer, lung, and cardiovascular defects. However, the effects of metals and the common genes/signaling pathways involved in metal toxicity have not been elucidated. Hence, the present study used toxicogenomic data mining with the comparative toxicogenomics database to explore the impact of these metals. The metals were categorized into transition, alkali, and alkali earth. The common genes were identified and subjected to functional enrichment analysis. Further, gene-gene and protein-protein interactions were assessed. Also, the top ten transcription factors and miRNAs that regulate the genes were identified. The phenotypes and diseases that have increased incidence upon alterations of these genes were detected. Overall, we were able to identify IL1B and SOD2 as the common genes, along with the AGE-RAGE signaling pathway in diabetic complications as the common pathway altered. Enriched genes and pathways specific to each metal category were also found. Further, we identified heart failure as the major diseases that have increased the incidence of these metals' exposure. In conclusion, exposure to essential metals might cause adverse effects via inflammation and oxidative stress.

Exposure to multiple metals in adults and diabetes mellitus: a cross-sectional analysis

Diabetes mellitus (DM) is the most widely recognized metabolic illness with expanding morbidity among ongoing years. Its high incapacity rate and death rate badly affect individuals' quality of life. Increasing proofs backed the relationship between metal exposures with the risk of DM, but the methodological boundedness cannot clarify the complexity of the internal relationship of metal mixtures. We fitted the logistic regression model, weighted quantile sum regression model, and Bayesian kernel machine regression model to assess the relationship between the metal exposures with DM in adults who participated in the National Health and Nutrition Examination Survey 2013-2016. The metals (lead, cadmium, and copper) levels were significantly higher among diabetic compared to the healthy controls. In the logistic regression model established for each single metal, lead and manganese were associated with DM in both unadjusted and mutually adjusted models (highest vs. lowest concentration quartile). When considering all metal as a mixed exposure, we found a generally positive correlation between metal mixtures with DM (binary outcome) and glycohemoglobin (HbA1c) levels (continuous outcome). Exposure to metal mixtures was associated with an increased risk of DM and elevated levels of HbA1c.

Association of urinary metal levels with metabolic syndrome in coal workers

Studies have indicated that metal exposure is associated with an increased risk of metabolic syndrome (MetS). However, it is unclear whether overexposure to heavy metals occurs in miners and is associated with MetS risk remains unclear. In a cross-sectional study, analysis for metal exposure levels of 3428 participants from three types of workplaces was conducted. Relationships between metals in urine and MetS were characterized using a multivariate binary logistic regression model and restricted cubic spline analysis. The association between urinary metals and workplaces with respect to MetS was studied via mediation analysis and multiplicative interaction analysis. And a sensitivity analysis was performed to assess the robustness of the association between MetS and urinary metals in participants without obesity (n = 2811). Zn, Cu, Fe, Co, and Ni were found to be associated with MetS in the single-metal models, whereas only Zn and Cu showed considerable associations in the multimetal model. The odds ratios (95% CI) for MetS in the highest quartiles were 2.089 (1.611, 2.707) for urinary Zn and 1.394 (1.084, 1.794) for urinary Cu (both false discovery rate for both was < 0.05). Urinary Zn and Cu were positively associated with hypertriglyceridemia. In addition, higher Zn exposure was confirmed in underground workers than ground workers and office workers, and there was a significant association between urinary metal exposure and workplace, which together influenced the occurrence of MetS. These results provided scientific evidence for the relationship between Zn, Cu, workplaces, and MetS in coal workers and indicated that it is critical to reduce occupational metal exposure, especially in underground workers.

What adverse health effects will environmental heavy metal co-exposure bring us: based on a biological monitoring study of sanitation workers

To investigate the relationship between health effect profile and co-exposure to heavy metal, 254 sanitation workers from Guangzhou, China, were recruited. Ten urinary metals were determined by inductively coupled plasma mass spectrometry. Parameters of physical examination, including blood lipid metabolism, renal function, blood pressure, and lung function, were tested for each participant. The hazard quotients (HQs) of eight heavy metals were evaluated. Cobalt, copper (Cu), molybdenum (Mo), nickel (Ni), and tin (Sn) demonstrated the top five associations with human health with the ∑₁₉β as 2.220, 1.351, 1.234, 0.957, and 0.930, respectively. Most physical examination parameters of workers were under the normal ranges, except the levels of forced mid expiratory flow rate (MMEF_75/25), the maximum expiratory flow rate at 25% vital capacity (MEF₂₅) and apolipoprotein B in the first quartile, and the level of uric acid in the third quartile of sanitation works. Moreover, Cu was significantly associated with diastolic pressure, pulse, and high density lipid (p < 0.05). Each unit increase in Mo level was related to a 120% increase odd ratio (OR) of abnormal of systolic pressure, but was significantly and negatively correlated with high density lipoprotein and apolipoprotein A, suggesting that Mo exposure may be a risk factor of cardiovascular disease. Each unit increase in Ni and Sn levels was associated with an increased OR of abnormal rate of MMEF_75/25 and MEF₂₅ (p < 0.001), suggesting the increasing risks of respiratory diseases. Sanitation workers exposed to Ni and Pb alone had no carcinogenic risks (HQ < 1). However, 23.8%, 34.6%, and 87.3% of sanitation workers confronted non-carcinogenic risks when exposed to Cu, Mo alone (HQ > 1), or co-exposed to the four heavy metals (HI > 1). Our study preliminarily revealed the potential sensitive health indicators of heavy metal co-exposure, which will provide beneficial health protection suggestions for the occupational populations.

Association of blood cadmium and metabolic syndrome: a cross-sectional analysis of National Health and Nutrition Examination Survey 2017-2020

Previous findings have reported the role of different types of heavy metals in cardiometabolic diseases. In the present research, we aim to evaluate the association between blood cadmium levels and Metabolic Syndrome (MetS) based on the large-sample NHANES data. Public availably data from NHANES 2017-2020 cycle was obtained. Participants were divided into MetS and non-MetS groups according to waist circumference (WC), triglyceride (TG), high-density lipoprotein (HDL), blood pressure (BP) and fasting plasma glucose (FPG) levels based on the National Cholesterol Education Program (NCEP) criteria. Student's t test, Mann-Whitney U test, and Chi-square test were performed for univariate analysis. Multivariate logistic analysis was performed to explore the relationship between blood cadmium and MetS and research findings were presented in forest plot. We also investigated the association of blood cadmium and MetS in subgroups stratified by age, gender and race. Population with MetS had significantly higher levels of blood [0.30 (0.18-0.54) vs. 0.24 (0.15-0.46) ug/L, p < 0.001] and urinary cadmium levels [0.29 (0.17-0.52) vs. 0.20 (0.09-0.42) ug/L, p < 0.001] compared with those without MetS. Higher blood cadmium concentrations were also observed in participants with elevated WC (0.28 vs. 023 ug/L, p < 0.001], TG (0.28 vs. 0.26 ug/L, p = 0.029), BP (0.33 vs. 0.23 ug/L, p < 0.001) and FPG (0.29 vs. 0.24 ug/L, p < 0.001) compared with those with normal metabolic parameters. Multivariate logistic regression showed that one-unit increasement of blood cadmium was associated with 1.25 times higher prevalence ratios for MetS after adjusting potential confounders (95% CI: 1.06-1.48, p = 0.0083). The associations between serum cadmium concentrations and MetS components were then evaluated, and the results showed higher blood cadmium levels were associated with higher risk for elevated TG, low HDL and elevated BP when treated as continuous variable. When treated as categorical variable, only BP was found positively associated with blood cadmium. Stratified multiple logistic regression analysis indicated that the positive association between blood cadmium and MetS remained significant in subjects less than 60 years old and female subgroup. In conclusion, the cross-sectional survey suggested the positive association between blood cadmium levels and risk for MetS, prospective research need to be conducted for further evaluation of the causal relationship between blood cadmium and MetS.

Sex-specific and dose-response relationships of urinary cobalt and molybdenum levels with glucose levels and insulin resistance in U.S. adults

Growing studies have linked metal exposure to diabetes risk. However, these studies had inconsistent results. We used a multiple linear regression model to investigate the sex-specific and dose-response associations between urinary metals (cobalt (Co) and molybdenum (Mo)) and diabetes-related indicators (fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), homeostasis model assessment for insulin resistance (HOMA-IR), and insulin) in a cross-sectional study based on the United States National Health and Nutrition Examination Survey. The urinary metal concentrations of 1423 eligible individuals were stratified on the basis of the quartile distribution. Our results showed that the urinary Co level in males at the fourth quartile (Q4) was strongly correlated with increased FPG (β = 0.61, 95% CI: 0.17-1.04), HbA1c (β = 0.31, 95% CI: 0.09-0.54), insulin (β = 8.18, 95% CI: 2.84-13.52), and HOMA-IR (β = 3.42, 95% CI: 1.40-5.44) when compared with first quartile (Q1). High urinary Mo levels (Q4 vs. Q1) were associated with elevated FPG (β = 0.46, 95% CI: 0.17-0.75) and HbA1c (β = 0.27, 95% CI: 0.11-0.42) in the overall population. Positive linear dose-response associations were observed between urinary Co and insulin (P_nonlinear = 0.513) and HOMA-IR (P_nonlinear = 0.736) in males, as well as a positive linear dose-response relationship between urinary Mo and FPG (P_nonlinear = 0.826) and HbA1c (P_nonlinear = 0.376) in the overall population. Significant sex-specific and dose-response relationships were observed between urinary metals (Co and Mo) and diabetes-related indicators, and the potential mechanisms should be further investigated.

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

(1) Background: Trace elements play important roles in gestational diabetes mellitus (GDM), but the results from reported studies are inconsistent. This study aimed to examine the association between maternal exposure to V, Cr, Mn, Co, Ni, and Se in early pregnancy and GDM. (2) Methods: A nested case-control study with 403 GDM patients and 763 controls was conducted. Trace elements were measured using inductively coupled plasma-mass spectrometry in plasma collected from pregnant women in the first trimester of gestation. We used several statistical methods to explore the association between element exposure and GDM risk. (3) Results: Plasma V and Ni were associated with increased and decreased risk of GDM, respectively, in the single-element model. V and Mn were found to be positively, and Ni was found to be negatively associated with GDM risk in the multi-element model. Mn may be the main contributor to GDM risk and Ni the main protective factor against GDM risk in the quantile g computation (QGC). 6.89 μg/L~30.88 μg/L plasma Ni was identified as a safe window for decreased risk of GDM. (4) Conclusions: V was positively associated with GDM risk, while Ni was negatively associated. Ni has dual effects on GDM risk.

Cross-sectional and longitudinal associations of urinary zinc with glucose-insulin homeostasis traits and type 2 diabetes: Exploring the potential roles of systemic inflammation and oxidative damage in Chinese urban adults

The link between zinc exposure and glucose metabolism or the development of type 2 diabetes (T2D) is controversial, and underlying mechanisms are unclear. This study aimed to explore the associations of zinc exposure with glucose-insulin homeostasis traits and the long-term effects of zinc on the development of T2D, and further to estimate the potential roles of inflammation and oxidative damage in such relationships. We investigated 3890 urban adults from the Wuhan-Zhuhai cohort, and followed up every three years. Mixed linear model was applied to estimate dose-response associations between urinary zinc and glycemia traits [fasting plasma insulin (FPI), fasting plasma glucose (FPG), insulin resistance (homeostasis model assessment of insulin resistance, HOMA-IR), and β-cell dysfunction (homeostasis model assessment of β-cell function, HOMA-B)], as well as zinc and biomarkers for systemic inflammation (C-reactive protein) and oxidative damage (8-isoprostane and 8-hydroxy-2'-deoxyguanosine). Logistic regression model and Cox regression model were conducted to evaluate the relationships between urinary zinc and prevalence and incidence of T2D, respectively. We further performed mediation analysis to assess the roles of inflammation and oxidative damage biomarkers in above associations. At baseline, we observed significant dose-response relationships of elevated urinary zinc with increased FPI, FPG, HOMA-IR, and T2D prevalence and decreased HOMA-B, and such associations could be strengthened by increased C-reactive protein, 8-isoprostane, and 8-hydroxy-2'-deoxyguanosine. Elevated C-reactive protein significantly mediated 9.09% and 17.67% of the zinc-related FPG and HOMA-IR increments, respectively. In longitudinal analysis, a significantly positive association between urinary zinc and T2D incidence was observed among subjects with persistent high urinary zinc levels when compared with those with persistent low zinc levels. Our results suggested that high levels of zinc exposure adversely affected on glucose-insulin homeostasis and further contributed to increased risk of T2D cross-sectionally and longitudinally. Moreover, inflammatory response might play an important role in zinc-related glucose metabolic disorder.

Lead exposure and impaired glucose homeostasis in Chinese adults: A repeated measures study with 5 years of follow-up

Experimental studies suggest the diabetogenic effects of lead, but relevant data in humans are limited and have been primarily based on cross-sectional study design. We aimed to prospectively examine the association between lead exposure and glucose homeostasis in general population using repeated measurements. This cohort study included 5505 Chinese adults free of glucose-lowering medication use at baseline in 2014 and followed up 5 years later. Blood lead and glucose metabolic traits including fasting plasma glucose (FPG), fasting serum insulin, the homeostasis model assessment of insulin resistance (HOMA-IR), and HOMA of beta-cell function (HOMA-B) were measured at baseline and follow-up. Linear mixed models and linear regression models were performed to evaluate the associations between blood lead and markers of glucose homeostasis. After full adjustment for confounders including BMI, an interquartile range (IQR) increase in blood lead levels was associated with a 2.26 % increase in FPG (95 % CI: 0.16 %, 4.39 %) and an 11.3 % decrease in HOMA-B (95 % CI: - 19.1 %, - 2.71 %) in women. The odds ratios of hyperglycemia and beta-cell dysfunction corresponding to an IQR increase in blood lead levels were 1.39 (95 % CI: 0.99, 1.95) and 1.74 (95 % CI: 1.00, 3.03), respectively. Similar results were found for 5-year changes of glucose metabolic markers. Compared with the first quartile of baseline lead levels, the highest lead quartile was associated with an additional 3.03 % increase in FPG (95 % CI: 0.84 %, 5.26 %) and an additional 13.3 % decrease in HOMA-B (95 % CI: - 20.4 %, - 5.53 %) in women during follow-up. We observed no overall associations between blood lead levels and glucose metabolic markers in men. Our findings provide suggestive evidence that environmental exposure to lead might contribute to sex-dependent disruption of glucose homeostasis in general adult population.

Association between trace metals exposure and hearing loss

Background

Trace metals have side-effect on human health. The association between trace metals exposure and hearing loss remains unclear.

Methods

A total of 8,128 participants were exacted for analysis of association between trace metals and hearing loss from the database of the National Health and Nutrition Examination Survey (NHANES) (2013-2018). Multivariable logistic regression and restricted cubic spline models were used to examine the association between trace metals and hearing loss.

Results

Participants with hearing loss had a higher level of lead, cadmium, molybdenum, tin, thallium, and tungsten (all p < 0.05). After adjusting for confounders, compared with the reference of the lowest quartile, the ORs with 95%CIs for hearing loss across quartiles were 1.14 (0.86, 1.51), 1.49 (1.12, 1.98), 1.32 (0.97, 1.80) for cobalt, and 1.35 (0.98, 1.87), 1.58 (1.15, 2.16), 1.75 (1.28, 2.40) for tin. Individuals with the level of cobalt at third quartile had 49% higher risks of hearing loss than those at lowest quartile. And participants with highest quartile of tin had 1.75-folds risks of hearing loss than those with lowest quartile of tin. There were increasing trends in risks of hearing loss with a raised level of thallium (p for trend <0.05). Restricted cubic spline regression analysis indicated that there was a nonlinear association between hearing loss and the levels of tin (p for nonlinearity = 0.021). Subgroup analysis showed that individuals of female, without hypertension and diabetes, and with a higher level of low-density lipoprotein cholesterol had modified effects on the associations between hearing loss and exposure to tin.

Conclusions

Our study indicated that exposure to cobalt and tin were significantly associated with hearing loss.

Combined effects of bisphenol A and diabetes genetic risk score on incident type 2 diabetes: A nested case-control study

Observational studies reported inconsistent results on the association between bisphenol A (BPA) and type 2 diabetes (T2D) risk. Whether genetic factors modified the association remains unclear. The present nested case-control study prospectively investigated the association of BPA with T2D risk, and the interaction and combined effects of diabetes genetic risk score (GRS) and serum BPA on T2D risk. Based on the Dongfeng-Tongji cohort study, 995 incident diabetes cases and 1:1 age- and gender-matched controls were included. T2D was diagnosed based on the American Diabetes Association criteria. Serum BPA concentration was measured at baseline. Diabetes GRS was constructed by 88 diabetes-related SNPs selected from large-scale GWASs. A U-shaped association was observed between serum BPA levels and T2D risk, with the lowest odds of T2D at the serum BPA levels of 1.00 ng/mL (P = 0.001 for nonlinearity). Compared with the middle group, the multivariate-adjusted ORs of T2D in the lowest group and the highest group of serum BPA were 1.52 (95% CI: 1.04, 2.22) and 1.40 (95% CI: 1.08, 1.81), respectively. Both serum BPA levels (β = 0.107, P = 0.001) and weighted-GRS (w-GRS) (β = 0.072, P = 0.02) were significantly associated with baseline FPG levels. Participants with both highest w-GRS and serum BPA levels had highest risk of T2D (OR = 2.53, 95%CI: 1.49, 4.31, P = 0.001) and higher baseline FPG levels (β = 0.218, P = 0.01), compared with those with both lowest w-GRS and serum BPA levels. Non modified effects of serum BPA levels and w-GRS on T2D, baseline FPG levels, and 5-y changes of FPG levels were detected (All P_interaction > 0.05). Our results suggested a U-shaped association between serum BPA levels and T2D risk. Participants with higher serum BPA levels and diabetes genetic risk had higher FPG levels and higher risk of T2D.

Effects of multi-metal exposure on the risk of diabetes mellitus among people aged 40-75 years in rural areas in southwest China

AIMS/INTRODUCTION

Metals play an important role in diabetes mellitus. This cross-sectional study aimed to evaluate the overall, individual and interactive effects of multi-metal exposure on the prevalence of diabetes mellitus, impaired fasting glucose (IFG) rate and fasting blood glucose (FBG) levels.

MATERIALS AND METHODS

The FBG levels of a study population from a cadmium (Cd)-polluted area (n = 250) and an unpolluted area (n = 204), and the metal levels, including magnesium, calcium (Ca), iron (Fe), zinc (Zn), arsenic (As), Cd, copper and lead (Pb) in blood and urine were detected. The study population was divided into a normal fasting glucose group, an IFG group and a diabetes mellitus group on the basis of FBG levels.

RESULTS

The IFG rate and diabetes mellitus prevalence were negatively associated with blood Cd and urine Zn levels (IFG rate: odds ratio [OR] 0.780, 95% confidence interval [CI] 0.655-0.928; OR 0.622, 95% CI 0.465-0.831. Diabetes mellitus prevalence: OR 0.506, 95% CI 0.288-0.888; OR 0.609, 95% CI 0.395-0.939), the IFG rate was positively associated with urine Fe levels (OR 1.876, 95% CI 1.290-2.778), and diabetes mellitus prevalence was positively associated with urine Pb and blood Fe levels (OR 1.185, 95% CI 1.022-1.376; OR 1.008, 95% CI 1.001-1.014). A linear negative correlation was observed between FBG levels and blood Cd, and non-linear inverted U-shaped associations were found between FBG levels and Zn, Pb and copper in urine.

CONCLUSIONS

This research suggests that multi-metal exposure, especially Cd, Fe, Zn, copper and Pb, is linked to diabetes mellitus, and the interactive effects of multiple metals require further exploration.

The Association between Urinary Polycyclic Aromatic Hydrocarbons Metabolites and Type 2 Diabetes Mellitus

Polycyclic aromatic hydrocarbons (PAHs) are considered to be endocrine disruptors. In this study, the evidence on the association between PAHs and diabetes was systematically reviewed. PubMed, EMBASE, and ISI Web of Science were systematically searched for studies reporting the association between PAHs and diabetes. Of the 698 articles identified through the search, nine cross-sectional studies were included. Seven were conducted in the general population and two in coke oven workers. Fixed-effects and random-effects models were used to calculate the total effect. Subgroup analysis was further carried out according to the types of PAH metabolites. The results showed that the odds of diabetes were significantly higher for the highest category of urinary naphthalene (NAP), fluorine (FLU), phenanthrene (PHEN), and total mono-hydroxylated (OH-PAH) metabolites compared to the lowest category. The pooled odds ratios (OR) and 95% confidence intervals (CI) were 1.52 (95%CI: 1.19, 1.94), 1.53 (95%CI: 1.36, 1.71), 1.43 (95%CI: 1.28, 1.60), and 1.49 (95%CI: 1.07, 2.08), respectively. In coke oven workers, 4-hydroxyphenanthrene (4-OHPh) was significantly correlated with an increased risk of diabetes. Exposure measurements, outcome definitions, and adjustment for confounders were heterogeneous between studies. The results of the current study demonstrate a potentially adverse effect of PAHs on diabetes. Further mechanistic studies and longitudinal studies are needed to confirm whether PAH metabolite levels are causative, and hence associative, with increased diabetes incidences.

Cohort Profile Update: the China Metal-Exposed workers Cohort Study (Jinchang Cohort)

The Jinchang Cohort was an ongoing 20-year ambispective cohort with unique metal exposures to an occupational population. From January 2014 to December 2019, the Jinchang Cohort has completed three phases of follow-up. The baseline cohort was completed from June 2011 to December 2013, and a total of 48 001 people were included. Three phases of follow-ups included 46 713, 41 888, and 40 530 participants, respectively. The death data were collected from 2001 to 2020. The epidemiological, physical examination, physiological, and biochemical data of the cohort were collected at baseline and during follow-up. Biological specimens were collected on the baseline to establish a biological specimen bank. The concentrations of metals in urine and serum were detected by inductively coupled plasma mass spectrometry (ICP-MS). The new areas of research aim to study the all-cases mortality, the burden of diseases, heavy metals and diseases, and the course of the chain from disease to high-risk outcomes using a combination of macro and micro means, which provided a scientific basis to explore the pathogenesis of multi-etiology and multi-disease and to evaluate the effects of the intervention measures in the population.

Effect of Bis(maltolato)oxovanadium(IV) on Zinc, Copper, and Manganese Homeostasis and DMT1 mRNA Expression in Streptozotocin-Induced Hyperglycemic Rats

Our aim was to examine whether vanadium (IV) corrects alterations in zinc, copper and manganese homeostasis, observed in streptozotocin-induced hyperglycemic rats, and whether such changes are related to divalent metal transporter 1 (DMT1) mRNA expression, and antioxidant and proinflammatory parameters. Four groups of Wistar rats were examined: control; hyperglycemic (H); hyperglycemic treated with 1 mg V/day (HV); and hyperglycemic treated with 3 mg V/day (HVH). Vanadium was supplied in drinking water as bis(maltolato)oxovanadium(IV) for five weeks. Zinc, copper and manganese were measured in food, excreta, serum and tissues. DMT1 mRNA expression was quantified in the liver. Hyperglycemic rats showed increased Zn and Cu absorption and content in the liver, serum, kidneys and femurs; DMT1 expression also increased (p < 0.05 in all cases). HV rats showed no changes compared to H rats other than decreased DMT1 expression (p < 0.05). In the HVH group, decreased absorption and tissular content of studied elements (p < 0.05 in all cases) and DMT1 expression compared to H (p < 0.05) were observed. Liver zinc, copper and manganese content correlated positively with glutathione peroxidase activity and negatively with catalase activity (p < 0.05 in both cases). In conclusion, treatment with 3 mg V/d reverted the alterations in zinc and copper homeostasis caused by hyperglycemia, possibly facilitated by decreased DMT1 expression.

Association of urinary rubidium concentrations with hypertension risk and blood pressure levels: A cross-sectional study in China

BACHGROUND

Rubidium resembles potassium. We hypothesized that rubidium might play a role in blood pressure control.

METHODS

We measured urinary rubidium concentrations and blood pressure levels using validated techniques and methods in 2002 eligible participants. Multivariable logistic and linear regression models were applied to explore the associations. The restricted cubic spline model was utilized to investigate the dose-response relationship. Furthermore, we explored the associations of rubidium with risk factors (glomerular filtration rate, uric acid, and homocysteine) for hypertension and relevant biochemical indexes.

RESULTS

After adjustment for potential confounders and urinary potassium and sodium levels, doubling of urinary rubidium concentrations was significantly associated with decreased hypertension risk [odds ratio (OR), 0.76; 95% confidence interval (CI), 0.61, 0.93] and reduced systolic blood pressure (SBP) levels of 2.92 (95% CI: 1.56, 4.26) mm Hg. Each 1.00 mg/L increase in rubidium concentrations was associated with a 1.25 mm Hg decreased SBP levels, which was at least 200 times more effective than potassium. Furthermore, urinary rubidium concentrations were negatively associated with the risk factors for hypertension.

CONCLUSIONS

Rubidium might have more prominent effects on lowering blood pressure levels than potassium. Prospective studies and experimental research focusing on our findings are needed.

Identifying Effects of Urinary Metals on Type 2 Diabetes in U.S. Adults: Cross-Sectional Analysis of National Health and Nutrition Examination Survey 2011-2016

Growing evidence supports the associations of metal exposures with risk of type 2 diabetes (T2D), but the methodological limitations overlook the complexity of relationships within the metal mixtures. We identified and estimated the single and combined effects of urinary metals and their interactions with prevalence of T2D among 3078 participants in the NHANES 2011-2016. We analyzed 15 urinary metals and identified eight metals by elastic-net regression model for further analysis of the prevalence of T2D. Bayesian kernel machine regression and the weighted quantile sum (WQS) regression models identified four metals that had greater importance in T2D, namely cobalt (Co), tin (Sn), uranium (U) and strontium (Sr). The overall OR of T2D was 1.05 (95% CI: 1.01-1.08) for the positive effects and 1.00 (95% CI: 0.98-1.02) for the negative effect in the WQS models. We observed positive (Poverall = 0.008 and Pnon-linear = 0.100 for Co, Poverall = 0.011 and Pnon-linear = 0.138 for Sn) and inverse (Poverall = 0.001, Pnon-linear = 0.209 for Sr) linear dose-response relationships with T2D by restricted cubic spline analysis. Both additive and multiplicative interactions were found in urinary Sn and Sr. In conclusion, urinary Co, Sn, U and Sr played important roles in the development of T2D. The levels of Sn might modify the effect of Sr on T2D risk.

The association between urine elements and fasting glucose levels in a community-based elderly people in Beijing

Epidemiological studies have demonstrated that various kinds of urinary element concentrations were different between healthy, prediabetes, and diabetes patients. Meanwhile, many studies have explored the relationship between element concentration and fasting blood glucose (FBG), but the association between joint exposure to co-existing elements and FBG level has not been well understood. The study explored the associations of joint exposure to co-existing urinary elements with FBG level in a cross-sectional design. 275 retired elderly people were recruited from Beijing, China. The questionnaire survey was conducted, and biological samples were collected. The generalized linear model (GLM) and two-phase Bayesian kernel machine regression (BKMR) model were used to perform in-depth association analysis between urinary elements and FBG. The GLM analysis showed that Zn, Sr, and Cd were significantly correlated with the FBG level, under control potential confounding factors. The BKMR analysis demonstrated 8 elements (Zn, Se, Fe, Cr, Ni, Cd, Mn, and Al) had a higher influence on FBG (posterior inclusion probabilities > 0.1). Further intensive analyses result of the BKMR model indicated that the overall estimated exposure of 8 elements was positively correlated with the FBG level and was statistically significant when all creatinine-adjusted element concentrations were at their 65th percentile. Meanwhile, the BKMR analysis showed that Cd and Zn had a statistically significant association with FBG levels when other co-existing elements were controlled at different levels (25th, 50th, or 75th percentile), respectively. The results of the GLM and BKMR model were inconsistent. The BKMR model could flexibly calculate the joint exposure to co-existing elements, evaluate the possible interaction effects and nonlinear correlations. The meaningful conclusions were found that it was difficult to get by traditional methods. This study will provide methodological reference and experimental evidence for the association between joint exposure to co-existing elements and FBG in elderly people.

Tin speciation in the blood plasma of workers occupationally exposed in a cassiterite ore processing industry

ABSTRACT Mining is a high-risk activity due to its dangerous processes. Tin (Sn) is obtained from cassiterite ore and mining activities expose workers to the metal. Chronic exposure to Sn may cause pneumoconiosis, gastrointestinal and hematological effects, among others. This work aimed to assess the exposure of workers to tin in a cassiterite ore processing industry, using the speciation analysis in blood plasma. Twelve subjects donated the blood samples; six were occupationally exposed to Sn. Size exclusion chromatography separated proteins in blood plasma; a graphite furnace atomic absorption spectrometer determined total tin in the plasma and eluted fractions, while SDS-PAGE determined molecular masses of proteins. Tin levels in the workers’ plasma were four times higher than in the reference individuals. After fractionation, the metal only appeared in the total inclusion volume, not being possible to confirm the binding of tin to proteins, which certainly modifies their functions and impair workers’ health. Despite that, the work process needs to change since Sn levels in the workers’ plasma pointed to metal exposure. Further works are necessary to clarify whether the metal is free or bound to small proteins in blood plasma and understand the true impact of tin on workers’ health.

Clinical relevance of environmental manganese exposure with liver stiffness and steatosis detected by transient elastography in adults

Global manganese pollution to air and water is a significant threat to human health. The associations between manganese and liver stiffness and steatosis have not been reported in epidemiological studies. This study aimed to explore the clinical relevance of blood manganese with liver stiffness and steatosis in adults from the 2017-2018 National Health and Nutrition Examination Survey (N = 4,192). Subjects with excessive alcohol consumption and hepatitis B or C infection were excluded. Liver stiffness and steatosis were detected by transient elastography. Logistic regression and restricted cubic splines were adopted to explore the non-linear dose-response relationships. In multivariate analysis, while higher blood manganese concentrations were not associated with liver stiffness in the total sample and in males, an increased odds of significant liver fibrosis was found with higher blood manganese concentrations (tertile 3 vs. tertile 1) in females [odds ratios (95% confidence intervals): 2.34 (1.32-4.14), P trend < 0.01] and in other races [1.47 (1.05-2.05), P trend = 0.03]. Higher blood manganese concentrations were associated with liver steatosis in the total sample [1.33 (1.04-1.70), P trend = 0.03], in females [1.58 (1.02-2.44), P trend = 0.04], in other races [1.91 (1.50-2.43), P trend < 0.01], and in obese subjects [2.29 (1.13-4.65), P trend = 0.02]. Dose-response analysis showed that the departures from non-linear relationships between blood manganese concentrations and significant liver fibrosis (Pnon-linearity = 0.30) and steatosis (Pnon-linearity = 0.47) were not significant, suggesting that the observed associations were linear. In conclusion, higher blood manganese concentrations were positively associated with liver stiffness and steatosis, and the associations were mainly observed in females, in races other than Non-Hispanic White, and in obese subjects.

Environmental chemical exposure dynamics and machine learning-based prediction of diabetes mellitus

BACKGROUND

With dramatically increasing prevalence, diabetes mellitus has imposed a tremendous toll on individual well-being. Humans are exposed to various environmental chemicals, which have been postulated as underappreciated but potentially modifiable diabetes risk factors.

OBJECTIVES

To determine the utility of environmental chemical exposure in predicting diabetes mellitus.

METHODS

A total of 8501 eligible participants from NHANES 2005-2016 were randomly assigned to a discovery (N = 5953) set and a validation (N = 2548) set. We applied random forest (RF) and least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation in the discovery set to select features, and built an optimal model to predict diabetes mellitus, blood insulin, fasting plasma glucose (FPG) and 2-h plasma glucose after oral glucose tolerance test (2-h PG after OGTT).

RESULTS

The machine learning model using LASSO regression predicted diabetes with an area under the receiver operating characteristics (AUROC) of 0.80 and 0.78 in the discovery set and validation set, respectively. The linear model predicted blood insulin level with an R² of 0.42 and 0.40 in the discovery set and validation set, respectively. For FPG, the discovery set and validation set yielded an R² of 0.16 and 0.15, respectively. For 2-h PG after OGTT, the discovery set and validation set yielded an R² of 0.18 and 0.17, respectively.

CONCLUSION

We used environmental chemical exposure, constructed machine learning models and achieved relatively accurate prediction for diabetes, emphasizing the predictive value of widespread environmental chemicals for complicated diseases.

Cadmium exposure and risk of diabetes and prediabetes: A systematic review and dose-response meta-analysis

BACKGROUND

Cadmium exposure has been associated with increased diabetes risk in several studies, though there is still considerable debate about the magnitude and shape of the association.

OBJECTIVE

To perform a systematic review and meta-analysis of observational studies investigating the relation between cadmium exposure and risk of type 2 diabetes and prediabetes, and to summarize data on the magnitude and shape of the association.

DATA SOURCE

After conducting an online literature search through October 1, 2021, we identified 42 eligible studies investigating the association between cadmium exposure and risk of diabetes and prediabetes.

STUDY ELIGIBILITY CRITERIA

We included studies that assessed cadmium exposure through biomarker levels; examined type 2 diabetes or prediabetes among outcomes; and reported effect estimates for cadmium exposure for meta-analysis only.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies were evaluated using ROBINS-E risk of bias tool. We quantitively assessed the relation between exposure and study outcomes using one-stage dose-response meta-analysis with a random effects meta-analytical model.

RESULTS

In the meta-analysis, comparing highest-versus-lowest cadmium exposure levels, summary relative risks (RRs) for type 2 diabetes were 1.24 (95% confidence interval 0.96-1.59), 1.21 (1.00-1.45), and 1.47 (1.01-2.13) for blood, urinary, and toenail matrices, respectively. Similarly, there was an increased risk of prediabetes for cadmium concentrations in both urine (RR = 1.41, 95% CI: 1.15-1.73) and blood (RR = 1.38, 95% CI: 1.16-1.63). In the dose-response meta-analysis, we observed a consistent linear positive association between cadmium exposure and diabetes risk, with RRs of 1.25 (0.90-1.72) at 2.0 µg/g of creatinine. Conversely for blood cadmium, diabetes risk appeared to increase only above 1 µg/L. Prediabetes risk increased up to approximately 2 µg/g creatinine above which it reached a plateau with RR of 1.42 (1.12-1.76) at 2 µg/g creatinine.

LIMITATIONS AND CONCLUSIONS

This analysis provides moderate-certainty evidence for a positive association between cadmium exposure (measured in multiple matrices) and risk of both diabetes and prediabetes.

Plasma levels of trace element status in early pregnancy and the risk of gestational diabetes mellitus: A nested case-control study

PURPOSE

We investigated the impacts of plasma levels of magnesium (Mg), zinc (Zn), calcium (Ca), iron (Fe), copper (Cu), selenium (Se), and chromium (Cr) on GDM risk and the potential mediation effect of blood glucose levels on the relationship between trace elements and GDM risk.

METHODS

This nested case-control study was based on data from a birth cohort study conducted in Wuhan, China in 2013-2016. A total of 305 GDM cases and 305 individually-matched controls were included in the study. Conditional logistic regression models were used to estimate the associations between plasma trace element concentrations and GDM risk. A mediation analysis was conducted to explore whether blood glucose levels act as a mediator between trace element levels and GDM risk.

RESULTS

An IQR increment in plasma levels of Fe and Cu was associated with a significant increase in GDM risk [OR = 2.04 (95 % CI 1.62, 2.57) and OR = 1.52 (95 % CI 1.25, 1.82)], respectively. On the other hand, an IQR increment in plasma levels of Zn and Ca was associated with a significant decrease in GDM risk [OR = 0.55 (95 % CI 0.43, 0.71) and OR = 0.72 (95 % CI 0.56, 0.92)], respectively. The mediation analysis showed significant mediation of the association between Cu and GDM risk via the FBG (%mediated: 19.27 %), 1 h-PBG (12.64 %), 2h-PBG (28.44 %) pathways.

CONCLUSIONS

Plasma levels of Zn and Ca were negatively associated with GDM risk, while Fe and Cu were positively associated. Blood glucose levels act as a mediator between plasma trace element exposures and GDM risk.

Correlation between urinary contents of some metals and fasting plasma glucose levels: A cross-sectional study in China

Many metals are involved in the pathogenesis of diabetes, but most of existing studies focused on single metals. The study of mixtures represents real-life exposure scenarios and deserves attention. This study aimed to explore the potential relationship of urinary copper (Cu), zinc (Zn), arsenic (As), selenium (Se), and strontium (Sr) contents with fasting plasma glucose (FPG) levels in 2766 participants. The levels of metals in urine were determined by inductively coupled plasma-mass spectrometry. We used linear regression models and the Bayesian kernel machine regression (BKMR) to evaluate the association between metals and FPG levels. In the multiple metals linear regression, Zn (β = 0.434), Se (β = 0.172), and Sr (β = -0.143) showed significant association with FPG levels (all P < 0.05). The BKMR model analysis showed that the results of single metal association were consistent with the multiple metals linear regression. The mixture of five metals had a positive over-all effect on FPG levels, and Zn (PIP = 1.000) contributed the most to the FPG levels. Cu and As were negatively correlated with FPG levels in women. The potential interaction effect between Cu and Sr was observed in participants aged ≥ 60 years old (Pinteraction = 0.035). In summary, our results suggested that multiple metals in urine are associated with FPG levels. Further studies are needed to confirm these findings and clarify the underlying mechanisms.

The Associations between Blood and Urinary Concentrations of Metal Metabolites, Obesity, Hypertension, Type 2 Diabetes, and Dyslipidemia among US Adults: NHANES 1999-2016

Background

Heavy metals are well known to be associated with cancer outcomes, but its association with obesity and cardiometabolic risk outcomes requires further study.

Methods

Adult data from the National Health and Examination Survey (NHANES Continuous 1999-2016, n = 12,636 to 32,012) with data for blood or urinary metals concentrations and body mass index were used. The study aim was twofold: (1) to determine the association between heavy metals and obesity and (2) to examine the influence of heavy metals on the relationship between obesity and hypertension, type 2 diabetes, and dyslipidemia. Logistic regression was used to examine the main effects and interaction effects of metals and obesity for the odds of prevalent hypertension, type 2 diabetes, and dyslipidemia. Models were adjusted for age, gender, ethnicity, smoking status, physical active status, and poverty-income ratio, with additional adjustment for creatinine in models with the urinary measures of heavy metals. High-low concentration categories were defined by grouping metal quintiles with the most similar associations with obesity.

Results

Blood lead had a negative linear association with obesity (odds ratio (OR)  = 0.42, 95% confidence interval (CI) = 0.37-0.47). In those with obesity, high blood lead was associated with lower risk of prevalent dyslipidemia, while no association was found in those without obesity. The study observed a curvilinear relationship between urinary antimony and obesity with the moderate group having the highest odds of obesity (OR = 1.36, 1.16-1.59). However, the relationship between urinary antimony and prevalent hypertension and dyslipidemia risk was linear, positive, and independent of obesity. While not associated with prevalent obesity risk, high urinary uranium was associated with 30% (P=0.01) higher odds for prevalent type 2 diabetes.

Conclusions

The impact of environmental factors on obesity and health may be complex, and this study reinforces the heterogeneous relationship between various metals, obesity, and obesity-related metabolic diseases even at levels observed in the general population.

Protective Effects of Sodium Para-aminosalicylic Acid on Manganese-Induced Damage in Rat Pancreas

Sodium p-aminosalicylic acid (PAS-Na) has been previously shown to protect the brain from manganese (Mn)-induced toxicity. However, the efficacy of PAS-Na in protecting other organs from Mn toxicity and the mechanisms associated with this protection have yet to be addressed. Therefore, here, we assessed pancreatic damage in response to Mn treatment and the efficacy of PAS-Na in limiting this effect, along with specific mechanisms that mediate PAS-Na's protection. Mn exposure led to increased blood Mn content in dose- and time-dependent manner. Furthermore, subchronic Mn exposure (20 mg/kg for 8 weeks) led to pancreatic damage in a dose-dependent manner. In addition, the elevated Mn levels increased iron and decreased zinc and magnesium content in the pancreas. These effects were noted even 8 weeks after Mn exposure cessation. Mn exposure also affected the levels of amylase, lipase, and inflammatory factors such as tumor necrosis factor (TNF-α) and interleukin-1 β (IL-1β). PAS-Na significantly inhibited the increase in Mn concentration in both blood and pancreas, restored Mn-induced pancreatic damage, reversed the Mn-induced alterations in metal levels, and restored amylase and lipase concentrations. Taken together, we conclude that in rats, PAS-Na shows pharmacological efficacy in protecting the pancreas from Mn-induced damage.

Early pregnancy essential and non-essential metal mixtures and gestational glucose concentrations in the 2nd trimester: Results from project viva

Metals are involved in glucose metabolism, and some may alter glycemic regulation. However, joint effects of essential and non-essential metals on glucose concentrations during pregnancy are unclear. This study explored the joint associations of pregnancy exposures to essential (copper, magnesium, manganese, selenium, zinc) and non-essential (arsenic, barium, cadmium, cesium, lead, mercury) metals with gestational glucose concentrations using 1,311 women enrolled 1999-2002 in Project Viva, a Boston, MA-area pregnancy cohort. The study measured erythrocyte metal concentrations from 1st trimester blood samples and used glucose concentrations measured 1 h after non-fasting 50-gram glucose challenge tests (GCT) from clinical gestational diabetes screening at 26-28 weeks gestation. Bayesian Kernel Machine Regression (BKMR) and quantile-based g-computation were applied to model the associations of metal mixtures-including their interactions-with glucose concentrations post-GCT. We tested for reproducibility of BKMR results using generalized additive models. The BKMR model showed an inverse U-shaped association for barium and a linear inverse association for mercury. Specifically, estimated mean glucose concentrations were highest around 75th percentile of barium concentrations [2.1 (95% confidence interval: -0.2, 4.4) mg/dL higher comparing to the 25th percentile], and each interquartile range increase of erythrocyte mercury was associated with 1.9 mg/dL lower mean glucose concentrations (95% credible interval: -4.2, 0.4). Quantile g-computation showed joint associations of all metals, essential-metals, and non-essential metals on gestational glucose concentrations were all null, however, we observed evidences of interaction for barium and lead. Overall, we found early pregnancy barium and mercury erythrocytic concentrations were associated with altered post-load glucose concentrations in later pregnancy, with potential interactions between barium and lead.

Associations Between Serum Multiple Metals Exposures and Metabolic Syndrome: a Longitudinal Cohort Study

Although many studies have confirmed metabolic syndrome (MetS) is correlated with metal exposures, few studies have elucidated the associations of multiple metals with MetS risk. We aim to explore the relationship between serum 22 metals and MetS. We determined serum 22 metals using ICP-MS and used LASSO regression to select metals independently related with MetS to construct multiple-metals model. We further explored the dose-response relationship between positive metals and MetS by the restricted cubic spline regression. After screening by LASSO regression, serum 11 metals were selected to construct multiple-metals model in cross-sectional analysis, while 5 metals in longitudinal analysis. In the 11-metal model, only tin and zinc were associated with MetS in cross-sectional analysis (OR_tin = 2.22, 95% CI:1.43, 3.45; OR_zinc = 2.17, 95% CI: 1.42, 3.32; both P_trend < 0.05). Besides, the same results were found in the 5-metal model in longitudinal analysis (HR_tin = 1.66, 95% CI: 0.87, 3.17; HR_zinc = 1.83, 95% CI: 1.07, 3.14; both P_trend < 0.05). Moreover, there were positive linear relationships between serum tin and zinc concentrations and the increasing risk of MetS (both P_overall < 0.05, P_{non-linearity} > 0.05). Furthermore, the interaction between high tin and high zinc was also associated with increasing MetS risk (P_interaction < 0.05). We found that serum tin and zinc were independently and interactively associated with MetS in the southern Chinese men. Our results suggested that high tin and zinc may be the risk factors of MetS.

A systematic review and dose-response meta-analysis of exposure to environmental selenium and the risk of type 2 diabetes in nonexperimental studies

Accumulating evidence from both experimental and nonexperimental human studies in the last 15 years indicates that exposure to high levels of the trace element selenium increases the risk of type 2 diabetes. However, the relation of dose to effect is not well understood because randomized controlled trials used only one dose (200 μg/day) of selenium supplementation. While no new trial on this topic has been published since 2018, several nonexperimental studies have appeared. We therefore updated a previous meta-analysis to include recently published observational studies, and incorporated the recently developed one-stage random-effects model to display the dose-response relation between selenium and type 2 diabetes. We retrieved 34 potentially eligible nonexperimental studies on selenium and diabetes risk up to April 15, 2021. The bulk of the evidence indicates a direct relation between blood, dietary and urinary levels of selenium and risk of diabetes, but not with nail selenium, which may be considered a less reliable biomarker. The association was nonlinear, with risk increasing above 80 μg/day of dietary selenium. Whole blood/plasma/serum selenium concentrations of 160 μg/L corresponded to a risk ratio of 1.96 (95% CI 1.27-3.03) compared with a concentration of 90 μg/L (approximately 60 μg of daily selenium intake). The cohort studies, which are less susceptible to reverse causation bias, indicated increased risk for both blood and urine selenium levels and dietary selenium intake, whereas no such pattern emerged from studies relying on nail selenium content. Overall, the nonexperimental studies agree with findings from randomized controlled trials, indicating that moderate to high levels of selenium exposure are associated with increased risk for type 2 diabetes.

Sex-specific associations of plasma metals and metal mixtures with glucose metabolism: An occupational population-based study in China

Studies with multi-pollutant approach on the relationships between multiple metals and fasting plasma glucose (FPG) are limited. Few studies are available on the potential sex-specific associations between metal exposures and glucose metabolism. We explored the associations between 22 plasma metals and FPG level among the 769 participants from the manganese-exposed workers healthy cohort in China. We applied a sparse partial least squares (sPLS) regression followed by ordinary least-squares regression to evaluate multi-pollutant association. Bayesian kernel machine regression (BKMR) model was used to deal with metal mixtures and evaluate their joint effects on FPG level. In the sPLS model, negative associations on FPG levels were observed for plasma iron (belta = -0.066), cobalt (belta = -0.075), barium (belta = -0.109), and positive associations for strontium (belta = 0.082), and selenium (belta = 0.057) in men, which overlapped with the results among the overall participants. Among women, plasma copper (belta = 0.112) and antimony (belta = 0.137) were positively associated with elevated FPG level. Plasma magnesium was negatively associated with FPG level in both sexes (belta = -0.071 in men and belta = -0.144 in women). The results of overlapped for plasma magnesium was selected as the significant contributor to decreasing FPG level in the multi-pollutant, single-metal, and multi-metal models. BKMR model showed a significantly negative over-all effect of six metal mixtures (magnesium, iron, cobalt, selenium, strontium and barium) on FPG level among the overall participants from all the metals fixed at 50th percentile. In summary, our findings underline the probable role of metals in glucose homeostasis with potential sex-dependent heterogeneities, and suggest more researches are needed to explore the sex-specific associations of metal exposures with risk of diabetes.

U-shaped association between plasma cobalt levels and type 2 diabetes

AIMS

We aimed to investigate the association of plasma cobalt with newly diagnosed type 2 diabetes (T2D) and further explore the potential interaction effects between cobalt and several redox metals, such as manganese, copper and selenium.

DESIGN

A large case-control study including 4564 subjects was conducted. 2282 cases with newly diagnosed T2D and 2282 controls were matched by sex and age. The concentrations of cobalt and other metals in plasma were detected with inductively coupled plasma mass spectrometry (ICPMS).

RESULTS

The medians of the cobalt concentrations in plasma were 1.68 μg/dL for controls and T2D. There was a U-shaped relation between T2D and plasma cobalt, which was categorized into quartiles. After multivariable adjusted for the confounding factors, the odds ratios (ORs) of T2D across quartiles were 1.22 (95% CI: 1.01, 1.46), 1.12 (95% CI: 0.94, 1.35), 1.00 (reference) and 1.46 (95% CI: 1.22, 1.75), respectively. The association was almost consistent in subgroup analyses. According to the restricted cubic spline analysis, the lowest ORs of T2D was observed at the plasma cobalt of 2.00 μg/dL. There was a significant interaction between plasma cobalt and copper (P < 0.01). The ORs of T2D in those with medium concentration of plasma cobalt and copper was the lowest.

CONCLUSIONS

Higher or lower concentrations of plasma cobalt were related to higher ORs of T2D. The inter-relationship among redox metals in T2D should be further investigated.

Prospective association of metal levels with gestational diabetes mellitus and glucose: A retrospective cohort study from South China

OBJECTIVE

To explore the prospective correlation between serum metals before 24 weeks' gestation and gestational diabetes mellitus (GDM) or glucose in the late second trimester among southern Chinese pregnant women.

METHODS

A total of 8169 pregnant women were included in our retrospective cohort study. Logistic regression was used to investigate the relationships between metals (Manganese [Mn], copper [Cu], lead [Pb], calcium [Ca], zinc [Zn], magnesium [Mg]) and GDM. Quantile regression was performed to detect the shifts and associations with metals and three time-points glucose distribution of oral glucose tolerance test (OGTT) focused on the 10th, 50th, and 90th percentiles. Weighted quantile sum (WQS) regression was used to explore the relationship of metal mixtures and GDM as well as glucose.

RESULTS

Maternal serum concentrations of metals were assessed at mean 16.55 ± 2.92 weeks' gestation. Women with under weight might have 25% decreased risk of GDM for every 50% increase in Cu concentration within the safe limits. A 50% increase in Mn and Zn levels was related to a 0.051 μmol/L (95% CI: 0.033-0.070) and 0.059 μmol/L (95% CI: 0.040-0.079) increase in mean fasting plasma glucose of OGTT (OGTT0), respectively. The magnitude of association with Mn was smaller at the upper tail of OGTT0 distribution, while the magnitude of correlation with Zn was greater at the upper tail. However, there was a 0.012 mmol/L (95% CI: -0.017 to -0.008), 0.028 mmol/L (95% CI: -0.049 to -0.007), and 0.036 mmol/L (95% CI: -0.057 to -0.016) decrease in mean OGTT0 levels for every 50% increase in Pb, Ca, and Mg, respectively. The negative association of Pb, Ca, and Mg was greater at the lower tail of OGTT0 distribution. No significant relationship was observed in Cu and mean OGTT0 level (-0.010 mmol/L, 95% CI: -0.021 to 0.001), however, it showed a protective effect at the upper tail (-0.034 mmol/L, 95% CI: -0.049 to -0.017). No obvious correlation was found between metals and postprandial glucose levels (OGTT1 and OGTT2 from OGTT). The WQS index was significantly related to OGTT0 (P < 0.001). The contribution of Mn (80.19%) to metal mixture index was the highest related to OGTT0, followed by Cu (19.81%).

CONCLUSIONS

Higher Mn and Zn but lower Pb, Ca, and Mg concentrations within a certain range before 24 weeks' gestation might prospectively impair fasting plasma glucose during pregnancy; a greater focus is required on Mn. It could provide early markers of metal for predicting later glucose and suggest implement intervention for pregnant women.

Associations between metabolic syndrome and four heavy metals: A systematic review and meta-analysis

Four most concerned heavy metal pollutants, arsenic, cadmium, lead, and mercury may share common mechanisms to induce metabolic syndrome (MetS). However, recent studies exploring the relationships between MetS and metal exposure presented inconsistent findings. We aimed to clarify the relationship between heavy metal exposure biomarkers and MetS using a meta-analysis and systematic review approach. Literature search was conducted in international and the Chinese national databases up to June 2020. Of selected studies, we extracted the relevant data and evaluated the quality of each study's methodology. We then calculated the pooled effect sizes (ESs), standardized mean differences (SMDs), and their 95% confidence intervals (CIs) using a random-effect meta-analysis approach followed by stratification analyses for control of potential confounders. Involving 55,536 participants, the included 22 articles covered 52 observational studies reporting ESs and/or metal concentrations on specific metal and gender. Our results show that participants with MetS had significantly higher levels of heavy metal exposure [pooled ES = 1.16, 95% CI: 1.09, 1.23; n = 42, heterogeneity I2 = 75.6%; and SMD = 0.22, 95% CI: 0.15, 0.29; n = 32, I2 = 94.2%] than those without MetS. Pooled ESs in the subgroups stratified by arsenic, cadmium, lead, and mercury were 1.04 (95% CI: 0.97, 1.10; n = 8, I2 = 61.0%), 1.10 (0.95, 1.27; 11, 45.0%), 1.21 (1.00, 1.48; 12, 82.9%), and 1.26 (1.06, 1.48; 11, 67.7%), respectively. Pooled ESs in the subgroups stratified by blood, urine, and the other specimen were 1.22 (95% CI: 1.08, 1.38; n = 26, I2 = 75.8%), 1.06 (1.00, 1.13; 14, 58.1%), and 2.41 (1.30, 4.43; 2, 0.0%), respectively. In conclusion, heavy metal exposure was positively associated with MetS. Further studies are warranted to examine the effects of individual metals and their interaction on the relationship between MetS and heavy metals.

Plasma titanium level is positively associated with metabolic syndrome: A survey in China's heavy metal polluted regions

OBJECTIVE

Several heavy metals have been reported to be associated with metabolic syndrome(MetS) in general population, while effects of multiple metals exposure on MetS in residents living in heavy metal polluted regions have not been investigated. We aimed to assess the association of 23 metal levels and MetS among population living in China's heavy metal polluted regions.

METHODS

From August 2016 to July 2017, a total of 2109 eligible participants were consecutively enrolled in our study in Hunan province, China. The levels of plasma and urine metals were measured by inductively coupled plasma mass spectrometer (ICP-MS). MetS was defined by the criteria of the International Diabetes Federation. Multivariable regression models were applied to analysis the potential relationship.

RESULTS

In the overall population, crude model showed positive relationship of plasma titanium (Ti) with MetS and negative association of urine vanadium, iron, and selenium with MetS. After adjusted for potential confounders, only plasma Ti was positive associated with MetS (adjusted OR for Q4 versus Q1: 1.46; 95% CI: 1.06-1.99), and this positive correlation was explained by abdominal obesity (OR = 1.84, 95% CI: 1.41-2.39) and high triglycerides (OR = 2.23, 95% CI: 1.68-2.96). Further linear regression analysis revealed significant association of plasma Ti levels with waist circumference (β = 0.0056, 95% CI: 0.0004-0.0109, P = 0.036) and triglycerides (β = 0.0012, 95% CI: 0.0006-0.0019, P < 0.001), respectively.

CONCLUSION

High plasma Ti level was associated with increased risk of MetS via increasing waist circumference and triglycerides in people under high metal exposure.

Fasting Plasma Glucose Mediates the Prospective Effect of Maternal Metal Level on Birth Outcomes: A Retrospective and Longitudinal Population-Based Cohort Study

OBJECTIVE

Previously, we found that the presence of maternal serum metals before the 24th week of gestation prospectively increased fasting plasma glucose (FPG) at 24-28 weeks. We further explored the prospective association between levels of metals and neonatal outcomes and assessed the mediating effects of FPG on these relationships.

METHODS

A total of 7,644 pregnant women were included in a retrospective cohort study, and the relationships between metals [manganese (Mn), copper (Cu), lead (Pb), zinc (Zn), and magnesium (Mg)] and birth outcomes were explored. Quantile and linear regressions were performed to detect the shifts and associations between metals and neonatal size distribution focused on the 10th, 50th, and 90th percentiles. Mediation analysis was performed to assess the mediating effect of FPG on metals and birth outcomes.

RESULTS

After adjustment, a 50% increase in Mn and Zn levels was related to a 0.136-cm (95% CI: 0.067-0.205) and 0.120-cm (95% CI: 0.046-0.193) increase in head circumference, respectively. Based on head circumference distribution, the magnitude of the association with Mn was smaller at the upper tail, while the magnitude of correlation with Zn was greater at the upper tail. A 50% increase in Mn and Zn levels was related to a 0.135-cm (95% CI: 0.058-0.212) and 0.095-cm (95% CI: 0.013-0.178) increase in chest circumference, respectively. The magnitude of the association with Mn increased with increasing chest circumference, while the magnitude of correlation with Zn decreased with increasing chest circumference. FPG explained 10.00% and 17.65% of the associations of Mn with head and chest circumference. A positive indirect effect of Zn associated with head circumference (0.004, 95% CI: 0.002-0.006) and chest circumference (0.005, 95% CI: 0.003-0.008) through FPG was also observed, and the estimated proportion of the mediating effect was 13.79% and 26.32%, respectively.

CONCLUSION

Maternal serum Mn and Zn levels before the 24th week of gestation may prospectively increase the circumference of the neonatal head and chest. FPG at 24-28 weeks had positive mediating effects on these relationships. Further research is needed to identify a balance between maternal blood glucose and birth size.

Cadmium exposure, fasting blood glucose changes, and type 2 diabetes mellitus: A longitudinal prospective study in China

BACKGROUND

Cadmium is a recognized human carcinogen, raising global concern for its ubiquitously environmental exposure on public health. Diabetogenic effects of cadmium have been suggested in previous studies, but the longitudinal associations of chronic cadmium exposure with fasting blood glucose changes and type 2 diabetes mellitus have not been fully elucidated.

OBJECTIVE

To investigate the effects of long-term cadmium exposure on the fasting blood glucose changes and type 2 diabetes mellitus risk in a longitudinal prospective study of China.

METHODS

A total of 3521 urban adults were included as baseline study population from the Wuhan-Zhuhai cohort, and followed up three years later. Urinary cadmium concentrations were determined repeatedly during the follow-up of a three-year period. The within-person and between-person variability of urinary cadmium concentrations over three years was estimated using multilevel random-effects mixed models. Multivariate regression models were performed to evaluate the associations of cadmium exposure with fasting blood glucose changes and type 2 diabetes mellitus risk.

RESULTS

The geometric means of creatinine-corrected urinary cadmium concentration at baseline were 1.13 μg/g creatinine, which were close to the levels of follow-up (1.14 μg/g creatinine). The intra-class correlation coefficient of creatinine-corrected urinary cadmium concentrations was 0.71, achieving good reproducibility of cadmium over three years. With adjustment for potential confounders, each one-unit increase in log10-transformed cadmium was associated with a 0.11 (95%CI: 0.03 to 0.19) elevation in fasting blood glucose concentration, and was associated with a 42% (95%CI: 1.16 to 1.73) increase in risk of prevalent type 2 diabetes mellitus. Upward trends of fasting blood glucose changes and type 2 diabetes mellitus incidence were observed with increasing cadmium exposure. Individuals with the highest urinary cadmium exposure had a significant increase in fasting blood glucose change at follow-up [β (95% CI): 0.49 (0.31-0.67)]. Risk of incident type 2 diabetes mellitus were gradually elevated across increasing quartiles of cadmium exposure, though associations did not reach statistical significance (P = 0.15).

CONCLUSIONS

Our findings suggested that relatively high chronic cadmium exposure for general population adults might contribute to elevated changes of fasting blood glucose resulting in the development of type 2 diabetes mellitus.

Urinary copper, systemic inflammation, and blood lipid profiles: Wuhan-Zhuhai cohort study

Copper have been reported to be associated with metabolic diseases. However, results on copper exposure with blood lipid profiles are inconsistent, and the underlying mechanisms of this association remain unclear. This study focused on investigating associations between urinary copper and blood lipid profiles; and exploring the potential role of systemic inflammation in such relationships. Concentrations of urinary copper, plasma C-reactive protein (CRP), and four blood lipid parameters (e.g., Total cholesterol [TC], triglycerides [TG], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]) were measured in the adult participants from Wuhan-Zhuhai cohort. The associations between copper, CRP, and four blood lipids were assessed by the multivariable linear regression models, and the 3D mesh graphs was used to examine the joint effects of copper exposure and CRP on four blood lipid parameters. In addition, we used mediation analysis to investigate the mediated effects of CRP in the relationships between copper exposure and blood lipid profiles. Each 1% increase in urinary copper was statistically significantly associated with a 5.32% (95% CI: 2.48%, 8.24%) increase in TG after adjusting for the confounders (P < 0.05). No significant associations were observed between urinary copper and the other three blood lipid parameters (all P > 0.05). In addition, urinary copper increased monotonically with plasma CRP elevation, which in turn, was positively associated with TC, TG, and LDL-C and negatively related to HDL-C (all P < 0.05). Results from 3D mesh graphs demonstrated that increased levels of plasma CRP with higher urinary copper corresponded to higher TC, TG, LDL-C, and lower HDL-C concentrations. Mediation analysis observed that CRP mediated 6.27% in the relationships of urinary copper and TG. These findings suggest that systemic inflammation partly mediated the association between copper exposure and abnormal blood lipid, and may contribute to the development of dyslipidemias.

Gut microbiota: A target for heavy metal toxicity and a probiotic protective strategy

There is growing epidemiological evidence that heavy metals (HMs) may contribute to the progression of various metabolic diseases and that the etiology and progression of these diseases is partly due to HM-induced perturbations of the gut microbiota. Importantly, the gut microbiota are the first line of defense against the toxic effects of HMs, and there is a bidirectional relationship between the two. Thus, HM exposure alters the composition and metabolic profile of the gut microbiota at the functional level, and in turn, the gut microbiota alter the uptake and metabolism of HMs by acting as a physical barrier to HM absorption and by altering the pH, oxidative balance, and concentrations of detoxification enzymes or proteins involved in HM metabolism. Moreover, the gut microbiota can affect the integrity of the intestinal barrier, which may also in turn affect the absorption of HMs. Specifically, probiotic have been shown to reduce the absorption of HMs in the intestinal tract via the enhancement of intestinal HM sequestration, detoxification of HMs in the gut, changing the expression of metal transporter proteins, and maintaining the gut barrier function. This review is a summary of the bidirectional relationship between HMs and gut microbiota and of the probiotic-based protective strategies against HM-induced gut dysbiosis, with reference to strategies used in the food industry or for medically alleviating HM toxicity.

Associations between essential metals exposure and metabolic syndrome (MetS): Exploring the mediating role of systemic inflammation in a general Chinese population

BACKGROUND

Essential metals have been reported to be associated with metabolic diseases. However, the relationships between essential metals exposure and Metabolic Syndrome (MetS) is still uncertain, and the underlying mechanisms of the association remain unclear.

OBJECTIVES

To investigate the associations of urinary essential metals with MetS prevalence; and further to explore potential role of systemic inflammation biomarker, C-reactive protein (CRP), in relationships between essential metals exposure and MetS prevalence in a cross-sectional study.

METHODS

Concentrations of 8 urinary essential metals and plasma C-reactive protein (CRP) were quantified in 3272 adults from Wuhan-Zhuhai cohort. Urinary essential metals were adjusted by the corresponding urinary creatinine concentrations and reported as μg/mmol creatinine. Multivariable logistic regression and linear regression models were used to evaluate dose-response relationships between essential metals, plasma CRP, and MetS prevalence. Mediation analysis was performed to investigate the role of plasma CRP in the associations between urinary essential metals and MetS prevalence.

RESULTS

In the single-metal models, we observed positive dose-dependent relationships of urinary copper and zinc with MetS prevalence. Compared with the lowest quartiles of urinary metals, the ORs (95% CI) of MetS in the highest quartiles were 1.40 (1.03, 1.91) for urinary copper and 2.07 (1.51, 2.84) for zinc, respectively. The dose-dependent relationships of zinc and copper with MetS remained significant in the multiple-metal models and Bayesian kernel machine regression (BKMR) models. No significant associations were observed between others essential metals (e.g. manganese, iron, cobalt, selenium, chromium, molybdenum) and MetS in this general population (all P value > 0.05). In addition, urinary copper and zinc increased monotonically with plasma CRP elevation, and plasma CRP was positively associated with the MetS prevalence. Mediation analysis indicated that plasma CRP mediated 5.2% and 3.2% in the associations of urinary copper and zinc with MetS prevalence, respectively.

CONCLUSIONS

Elevated concentrations of urinary copper and zinc were associated with increased prevalence of MetS. Systemic inflammation may play an important role in the associations of copper and zinc exposure with MetS.