Associations of multiple plasma metals with incident type 2 diabetes in Chinese adults: The Dongfeng-Tongji Cohort

Association of metals and bisphenols exposure with lipid profiles and dyslipidemia in Chinese adults: Independent, combined and interactive effects

BACKGROUND

Although studies have assessed the association of metals and bisphenols with lipid metabolism, the observed results have been controversial, and limited knowledge exists about the combined and interactive effects of metals and bisphenols exposure on lipid metabolism.

METHODS

Plasma metals and serum bisphenols concentrations were evaluated in 888 participants. Multiple linear regression and logistic regression models were conducted to assess individual associations of 18 metals and 3 bisphenols with 5 lipid profiles and dyslipidemia risk, respectively. The dose-response relationships of targeted contaminants with lipid profiles and dyslipidemia risk were captured by applying a restriction cubic spline (RCS) function. The bayesian kernel machine regression (BKMR) model was used to assess the overall effects of metals and bisphenols mixture on lipid profiles and dyslipidemia risk. The interactive effects of targeted contaminants on interested outcomes were explored by constructing an interaction model.

RESULTS

Single-contaminant analyses revealed that exposure to iron (Fe), nickel (Ni), copper (Cu), arsenic (As), selenium (Se), strontium (Sr), and tin (Sn) was associated with elevated lipid levels. Cobalt (Co) showed a negative association with high density lipoprotein cholesterol (HDL-C). Bisphenol A (BPA) and bisphenol AF (BPAF) were associated with decreased HDL-C levels, with nonlinear associations observed. Vanadium (V), lead (Pb), and silver (Ag) displayed U-shaped dose-response relationships with most lipid profiles. Multi-contaminant analyses indicated positive trends between contaminants mixture and total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C). The interaction analyses showed that Se-Fe exhibited synergistic effects on LDL-C and non-HDL-C, and Se-Sn showed a synergistic effect on HDL-C.

CONCLUSIONS

Our study suggested that exposure to metals and bisphenols was associated with changes in lipid levels, and demonstrated their combined and interactive effects.

A prospective cohort study of multimetal exposure and risk of gestational diabetes mellitus

The relationship between co-exposure to multiple metals and gestational diabetes mellitus (GDM) and the mechanisms involved are poorly understood. In this nested case-control study, 228 GDM cases and 456 matched controls were recruited, and biological samples were collected at 12-14 gestational weeks. The urinary concentrations of 10 metals and 8-hydroxydeoxyguanosine (8-OHdG) as well as the serum levels of malondialdehyde (MDA) and advanced glycation end products (AGEs) were determined to assess the association of metals with GDM risk and the mediating effects of oxidative stress. Urinary Ti concentration was significantly and positively associated with the risk of GDM (odds ratio [OR]:1.45, 95 % confidence interval [CI]: 1.12, 1.88), while Mn and Fe were negatively associated with GDM risk (OR: 0.67, 95 % CI: 0.50, 0.91 or OR: 0.61, 95 % CI: 0.47, 0.80, respectively). A significant negative association was observed between Mo and GDM risk, specifically in overweight and obese pregnant women. Bayesian kernel machine regression showed a significant negative joint effect of the mixture of 10 metals on GDM risk. The adjusted restricted cubic spline showed a protective role of Mn and Fe in GDM risk (P < 0.05). A significant negative association was observed between essential metals and GDM risk in quantile g-computation analysis (P < 0.05). Mediation analyses showed a mediating effect of MDA on the association between Ti and GDM risk, with a proportion of 8.7 % (P < 0.05), and significant direct and total effects on Ti, Mn, and Fe. This study identified Ti as a potential risk factor and Mn, Fe, and Mo as potential protective factors against GDM, as well as the mediating effect of lipid oxidation.

Effects of exposure to multiple metallic elements in the first trimester of pregnancy on the risk of preterm birth

Exposure to certain heavy metals has been demonstrated to be associated with a higher risk of preterm birth (PTB). However, studies focused on the effects of other metal mixtures were limited. A nested case‒control study enrolling 94 PTB cases and 282 controls was conducted. Metallic elements were detected in maternal plasma collected in the first trimester using inductively coupled plasma‒mass spectrometry. The effect of maternal exposure on the risk of PTB was investigated using logistic regression, least absolute shrinkage and selection operator, restricted cubic spline (RCS), quantile g computation (QGC) and Bayesian kernel machine regression (BKMR). Vanadium (V) and arsenic (As) were positively associated with PTB risk in the logistic model, and V remains positively associated in the multi-exposure logistic model. QGC analysis determined V (69.42%) and nickel (Ni) (70.30%) as the maximum positive and negative contributors to the PTB risk, respectively. BKMR models further demonstrated a positive relationship between the exposure levels of the mixtures and PTB risk, and V was identified as the most important independent variable among the elements. RCS analysis showed an inverted U-shape effect of V and gestational age, and plasma V more than 2.18 μg/L was considered a risk factor for shortened gestation length. Exposure to metallic elements mixtures consisting of V, As, cobalt, Ni, chromium and manganese in the first trimester was associated with an increased risk of PTB, and V was considered the most important factor in the mixtures in promoting the incidence of PTB.

Relationship of urinary glyphosate concentrations with glycosylated hemoglobin and diabetes in US adults: a cross-sectional study

BACKGROUND

Glyphosate is a commonly used herbicide worldwide and is purportedly associated with multiple health effects. Research assessing the association of glyphosate concentrations with glycosylated hemoglobin (HbA1c) levels and the prevalence of diabetes is scarce. We sought to evaluate the association between urinary glyphosate levels and HbA1c levels and the prevalence of diabetes.

METHODS

A total of 2,745 adults in the National Health and Nutrition Examination Survey from 2013 to 2016 were included in this study. Generalized linear models (GLM) were applied to evaluate the associations of glyphosate concentrations with HbA1c levels and the prevalence of diabetes. The dose-response relationship was examined using restricted cubic splines (RCS).

RESULTS

Significantly positive correlations of urinary glyphosate concentrations with HbA1c levels (percentage change: 1.45; 95% CI: 0.95, 1.96; P < 0.001) and the prevalence of diabetes (OR: 1.45; 95% CI: 1.24, 1.68; P < 0.001) were found after adjustment. Compared with the lowest quartile of glyphosate levels, the highest quartile was positively associated with HbA1c levels (percentage change: 4.19; 95% CI: 2.54, 5.85; P < 0.001) and the prevalence of diabetes (OR: 1.89; 95% CI: 1.37, 2.63; P < 0.001). The RCS curves demonstrated a monotonically increasing dose-response relationship between urinary glyphosate levels and the prevalence of diabetes and HbA1c levels.

CONCLUSIONS

Urinary glyphosate concentrations are positively associated with HBA1c levels and the prevalence of diabetes. To verify our findings, additional large-scale prospective investigations are required.

Human molybdenum exposure risk in industrial regions of China: New critical effect indicators and reference dose

Evidence increasingly suggests molybdenum exposure at environmental levels is still associated with adverse human health, emphasizing the necessity to establish a more protective reference dose (RfD). Herein, we conducted a study measuring 15 urinary metals and 30 clinical health indicators in 2267 participants residing near chemical enterprises across 11 Chinese provinces to investigate their relationships. The kidney and cystatin-C emerged as the most sensitive organ and critical effect indicator of molybdenum exposure, respectively. Odds of cystatin-C-defined chronic kidney disease (CKD) in the highest quantile of molybdenum exposure significantly increased by 133.5% (odds ratio [OR]: 2.34, 95% CI: 1.78, 3.11) and 75.8% (OR: 1.76, 95% CI: 1.24, 2.49) before and after adjusting for urinary 14 metals, respectively. Intriguingly, cystatin-C significantly mediated 15.9-89.5% of molybdenum's impacts on liver and lung function, suggesting nephrotoxicity from molybdenum exposure may trigger hepatotoxicity and pulmonary toxicity. We derived a new RfD for molybdenum exposure (0.87 μg/kg-day) based on cystatin-C-defined estimated glomerular filtration rate by employing Bayesian Benchmark Dose modeling analysis. This RfD is significantly lower than current exposure guidance values (5-30 μg/kg-day). Remarkably, >90% of participants exceeded the new RfD, underscoring the significant health impacts of environmental molybdenum exposure on populations in industrial regions of China.

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.

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

BACKGROUND

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

AIM

To investigate the possible correlation between nickel and T2DM.

METHODS

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

RESULTS

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

CONCLUSION

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

A nested case-control study of serum zinc and incident diabetes among Chinese adults: Effect modifications and mediation analysis

Although numerous evidences suggest that zinc may have a beneficial impact on preventing and treating diabetes, findings from the population studies are inconclusive. To address this gap, we conducted a nested case-control study, employing restricted cubic splines and a conditional logistic regression model to explore the association between serum zinc levels and the risk of diabetes. We also assessed potential effect modifications through stratified analyses and examined the mediating effects of metabolic indicators using a multiclass mediation effect model. We measured baseline serum zinc concentrations using Inductively Coupled Plasma Mass Spectrometry in a cohort of 2156 participants, including 1078 individuals with diabetes and 1078 matched controls. Our findings revealed a 51 % increased risk of diabetes when comparing the highest quartile (Q4) to the lowest quartile (Q1) of serum zinc levels (Odds Ratio [95 % Confidence Interval]: 1.51 [1.09, 2.09]). There was a positive linear dose-response relationship between serum zinc and diabetes risk (P overall ≤0.01, P nonlinear = 0.20). Effect modifications were evident between serum zinc and factors such as educational attainment, body mass index, alcohol index, family history of diabetes, history of hypertension, coronary heart disease, and stroke, all of which influenced the risk of diabetes (all P-interaction <0.05). Moreover, our study identified significant indirect effects of triglycerides levels on diabetes risk for participants in the third (Q3) and fourth (Q4) quartiles of serum zinc, with mediation proportions of 19.23 % and 19.28 %, respectively. A significant indirect effect of alanine aminotransferase on diabetes risk was found for those in the Q4 of serum zinc, with a mediation proportion of 12.05 %. Considering these findings, it is advisable to conduct testing for serum zinc level and exercise caution when considering zinc supplementation. Furthermore, our results emphasized the necessity for additional validation through large-sample prospective population studies and experimental research.

Associations between plasma metal/metalloid mixtures and the risk of central obesity: A prospective cohort study of Chinese adults

Central obesity has increased rapidly over the past decade and posed a substantial disease burden worldwide. Exposure to metals/metalloids has been acknowledged to be involved in the development of central obesity through regulation of cortisol, insulin resistance, and glucocorticoid receptor reduction. Despite the importance, it is lack of prospective study which comprehensively evaluate the relations between multiple metals exposure and central obesity. We explored the prospective associations of plasma metal concentrations with central obesity in a prospective study of the Dongfeng-Tongji cohort. The present study included 2127 participants with a 6.87-year mean follow-up duration. We measured 23 plasma metal/metalloid concentrations at baseline. The associations between metals and incident central obesity were examined utilizing the Cox proportional hazard regression in single and multiple metals models. Additionally, we applied elastic net (ENET), Bayesian kernel machine regression (BKMR), plasma metal score (PMS), and quantile-based g-computation (Qgcomp) models to explore the joint associations of metal mixtures with central obesity. After adjusting potential confounders, we found significant associations of plasma manganese (Mn) and thallium (Tl) concentrations with a higher risk of central obesity, whereas plasma rubidium (Rb) concentration was associated with a lower risk of central obesity both in single and multiple metals models (all FDR <0.05). The ENET and Qqcomp models verified similar metals (Mn, Rb, and Tl) as important predictors for central obesity. The results of both BKMR model and PMS suggested cumulative exposure to metal mixtures was associated with a higher risk of central obesity. Our findings suggested that co-exposure to metals was associated with a higher risk of central obesity. This study expands our knowledge that the management of metals/metalloids exposure may be beneficial for the prevention of new-onset central obesity, which may subsequently alleviate the disease burden of late-life health outcomes.

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.

Associations of multiple plasma metals with osteoporosis: findings from the Dongfeng-Tongji cohort

With the aging population, osteoporosis has become a more prevalent public health issue. Existing researches have indicated significant relations of single metal exposure with osteoporosis (e.g., lead, copper, and zinc), whereas the evidence regarding the joint association of metal mixtures with osteoporosis remain limited and inconclusive. A total of 4924 participants from the Dongfeng-Tongji cohort were included in the present study. Plasma levels of 23 metals were determined by inductively coupled plasma mass spectrometry, and the presence of osteoporosis was defined as a bone mineral density T-score ≤  - 2.5. We applied stepwise regression, plasma metal score, and quantile g-computation model to evaluate the association between plasma metal mixtures and osteoporosis risk. Of the 4924 participants, the prevalence of osteoporosis was 10.9% (N = 265) in males and 27.5% (N = 684) in females. In the multiple-metals model, arsenic was positively associated with osteoporosis in males, while zinc was positively associated with osteoporosis in females. Comparing extreme quartiles, the multivariate-adjusted ORs of osteoporosis were 2.20 (95% CI, 1.29, 3.79; P-trend = 0.006) for arsenic in males and 2.16 (95% CI, 1.44, 3.23; P-trend < 0.001) for zinc in females. The plasma metal score was significantly and positively associated with a higher risk of osteoporosis, with ORs (95% CI) comparing extreme quartiles were 5.00 (95% CI, 3.36, 7.65; P-trend < 0.001) in males and 1.76 (95% CI, 1.35, 2.29; P-trend < 0.001) in females. Furthermore, the results of quantile g-computation revealed a consistent positive trend of metal mixtures with risk of osteoporosis and suggested the dominant role of arsenic in males and zinc in females, respectively. Our findings highlighted the importance of controlling metal mixtures exposure for the prevention of osteoporosis in the middle-aged and elder population. Further prospective studies in larger populations are warranted to confirm our findings.

The association between plasma zinc concentrations and markers of glucose metabolism in adults in Cameroon

An abnormal Zn status has been suggested to play a role in the pathogenesis of type 2 diabetes. However, epidemiological studies of the relationship between plasma Zn concentrations and diabetes are sparse and inconclusive. We aimed to investigate the association between plasma Zn concentrations and glycaemic markers (fasting glucose, 2-h glucose and homeostatic model assessment of insulin resistance) in rural and urban Cameroon. We studied 596 healthy adults (63·3 % women) aged 25-55 years in a population-based cross-sectional study. The mean plasma Zn concentration was 13·7 ± 2·7 µmol/L overall, with higher levels in men (14·4 ± 2·9 µmol/l) than in women (13·2 ± 2·6 µmol/l), P-value < 0·0001. There was an inverse relationship between tertiles of plasma Zn and 2-h glucose concentrations (P-value for linear trend = 0·002). The difference in 2-h glucose between those in the highest tertile of plasma Zn compared to the lowest was -0·63 (95 % CI - 1·02, -0·23) mmol/l. This remained significant after adjusting for age, sex, smoking status, alcohol intake, education level, area of residence, adiposity and objectively measured physical activity -0·43(-0·82, -0·04). Similar inverse associations were observed between plasma Zn concentrations and fasting glucose and homeostatic model assessment of insulin resistance when adjusted for socio-demographic and health-related behavioural characteristics. The current findings of an inverse association between plasma Zn concentrations and several markers of glucose homeostasis, together with growing evidence from intervention studies, suggest a role for Zn in glucose metabolism. If supported by further evidence, strategies to improve Zn status in populations may provide a cheap public health prevention approach for diabetes.

Associations between multiple metals during early pregnancy and gestational diabetes mellitus under four statistical models

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy. Metal exposure is an emerging factor affecting the risk of GDM. However, the effects of metal mixture on GDM and key metals within the mixture remain unclear. This study was aimed at investigating the association between metal mixture during early pregnancy and the risk of GDM using four statistical methods and further at identifying the key metals within the mixture associated with GDM. A nested case-control study including 128 GDM cases and 318 controls was conducted in Beijing, China. Urine samples were collected before 13 gestational weeks and the concentrations of 13 metals were measured. Single-metal analysis (unconditional logistic regression) and mixture analyses (Bayesian kernel machine regression (BKMR), quantile g-computation, and elastic-net regression (ENET) models) were applied to estimate the associations between exposure to multiple metals and GDM. Single-metal analysis showed that Ni was associated with lower risk of GDM, while positive associations of Sr and Sb with GDM were observed. Compared with the lowest quartile of Ni, the ORs of GDM in the highest quartiles were 0.49 (95% CI 0.24, 0.98). In mixture analyses, Ni and Mg showed negative associations with GDM, while Co and Sb were positively associated with GDM in BKMR and quantile g-computation models. No significant joint effect of metal mixture on GDM was observed. However, interestingly, Ni was identified as a key metal within the mixture associated with decreased risk of GDM by all three mixture methods. Our study emphasized that metal exposure during early pregnancy was associated with GDM, and Ni might have important association with decreased GDM risk.

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.

Associations of circulating multiple metals with the risk of incident hyperuricemia and the average annual change in uric acid levels

BACKGROUND

Hyperuricemia has been linked to exposure to certain metals in cross-sectional studies. However, prospective studies evaluating the associations of multiple metal exposures with incident hyperuricemia are scarce.

OBJECTIVES

To prospectively investigate the associations of multiple metal/metalloid concentrations with incident hyperuricemia as well as average annual change in uric acid levels in a longitudinal cohort.

METHODS

A longitudinal cohort study included 3957 subjects who were free of cardiovascular disease with certain risk factors for cardiovascular disease at baseline. Incident hyperuricemia was ascertained if serum uric acid level was ≥ 420 μmol/L for men and ≥ 360 μmol/L for women during the follow-up visit in 2013. The relationships between 17 single plasma metals/metalloids and incident hyperuricemia were assessed using unconditional logistic regression models. For metals/metalloids significantly related to incident hyperuricemia, we further utilized generalized linear regression models to evaluate their associations with the average annual change in uric acid levels. Finally, we applied the weighted quantile sum (WQS) regression to investigate the joint effects of metals/metalloids on hyperuricemia risk and uric acid changes, and to identify the most significant metals.

RESULTS

After adjusting for potential confounders, plasma aluminum, arsenic, barium, lead, strontium, vanadium, and zinc concentrations were positively associated with incident hyperuricemia in both main analyses and sensitivity analyzes. Compared to the lowest quartiles, participants in the highest quartiles had 63 %-125 % higher risks of incident hyperuricemia (all FDR < 0.05). Furthermore, the positive associations of these seven metals with an average annual uric acid increase reinforced the findings. Finally, the WQS analyses showed that plasma metals mixtures were positively associated with the risk of incident hyperuricemia (OR: 1.47; 95 % CI: 1.23, 1.76) and the average annual change in uric acid levels (β: 3.17; 95 % CI: 2.42, 3.93), and strontium and vanadium were the most heavily weighted metals, respectively.

CONCLUSION

Our findings identify aluminum, arsenic, barium, lead, strontium, vanadium, and zinc exposures as independent risk factors for hyperuricemia and provide new insights into the prevention of hyperuricemia.

An updated systematic review and dose-response meta-analysis on the relation between exposure to arsenic and risk of type 2 diabetes

Arsenic is among the most critical environmental toxicants associated with many human disorders. However, its effect on type 2 diabetes mellitus (T2DM) is contradictory. This systematic review and dose-response meta-analysis aim to update information on the association between arsenic exposure and the risk of T2DM. The sample type (drinking water, urine, blood, and nails) conducted the subgroup analysis. Evaluation of the high vs. low arsenic concentrations showed a significant association between drinking water arsenic (OR: 1.58, 95% CI: 1.20-2.08) and urinary arsenic (OR: 1.37, 95% CI: 1.24-1.51) with the risk of T2DM. The linear dose-response meta-analysis showed that each 1 μg/L increase in levels of drinking water arsenic (OR: 1.01, 95% CI: 1.00-1.01) and urinary arsenic (OR: 1.01, 95% CI: 1.00-1.02) was associated with a 1% increased risk of T2DM. The non-linear dose-response analysis indicated that arsenic in urine was associated with the risk of T2DM (Pnon-linearity<0.001). However, this effect was not statistically significant for arsenic in drinking water (Pnon-linearity=0.941). Our findings suggest that blood arsenic was not significantly linked to the increased risk of T2DM in high vs. low (OR: 1.21, 95% CI: 0.85-1.71), linear (OR: 1.04, 95% CI: 0.99-1.09), and non-linear (Pnon-linearity=0.365) analysis. Also, nail arsenic was not associated with the risk of T2DM in this meta-analysis (OR: 1.33, 95% CI: 0.69-2.59). This updated dose-response meta-analysis indicated that arsenic exposure was significantly correlated with the risk of T2DM.

Association of Selenium Intake and Selenium Concentrations with Risk of Type 2 Diabetes in Adults: A Narrative Review

Several recent studies have suggested selenium (Se) as a potential risk factor for diabetes mellitus (DM); however, the relationship between high Se levels and type 2 diabetes mellitus (T2DM) risk remains unclear. This review article aimed to provide a comprehensive discussion to clarify the association between high dietary Se intake and blood Se concentrations and the risk of T2DM among adults. We conducted searches in the PubMed, Science Direct, and Google Scholar databases for the years 2016 to 2022 and evaluated 12 articles from systematic reviews, meta-analyses, cohort studies, and cross-sectional studies. This review found a controversial association between high blood Se concentrations and T2DM risk while demonstrating a positive correlation with DM risk. In contrast, there are conflicting results regarding the association between high dietary Se intake and T2DM risk. Thus, longitudinal studies and randomized controlled trials are needed to better elucidate the link.

Heavy metals in influent and effluent from 146 drinking water treatment plants across China: Occurrence, explanatory factors, probabilistic health risk, and removal efficiency

Heavy metals (HMs) in drinking water have drawn worldwide attention due to their risks to public health; however, a systematic assessment of the occurrence of HMs in drinking water treatment plants (DWTPs) at a large geographical scale across China and the removal efficiency, human health risks, and the correlation with environmental factors have yet to be established. Therefore, this study characterised the occurrence patterns of nine conventional dissolved HMs in the influent and effluent water samples from 146 typical DWTPs in seven major river basins across China (which consist of the Yangtze River, the Yellow River, the Songhua River, the Pearl River, the Huaihe River, the Liaohe River and the Haihe River) for the first time and removal efficiency, probabilistic health risks, and the correlation with water quality. According to the findings, a total of eight HMs (beryllium (Be), antimony (Sb), barium (Ba), molybdenum (Mo), nickel (Ni), vanadium (V), cobalt (Co) and titanium (Ti)) were detected, with detection frequencies in influent and effluent water ranging from 2.90 (Mo) to 99.30% (Ba) and 1.40 (Ti) to 97.90% (Ba), respectively. The average concentration range was 0.41 (Be)- 77.36 (Sb) μg/L. Among them, Sb (exceeding standard rate 8%), Ba (2.89%), Ni (21.43%), and V (1.33%) were exceeded the national standard (GB5749-2022). By combining Spearman's results and redundancy analysis, our results revealed a close correlation among pH, turbidity (TURB), potassium permanganate index (COD_Mn), and total nitrogen (TN) along with the concentration and composition of HMs. In addition, the concentration of HMs in finished water was strongly affected by the concentration of HMs in raw water, as evidenced by the fact that HMs in surface water poses a risk to the quality of finished water. Metal concentration was the primary factor in assessing the health risk of a single metal, and the carcinogenic risk of Ba, Mo, Ni, and Sb should be paid attention to. In DWTPs, the removal efficiencies of various HMs also vary greatly, with an average removal rate ranging from 16.30% to 95.64%. In summary, our findings provide insights into the water quality and health risks caused by HMs in drinking water.

Increased hypertension risk for the elderly with high blood levels of strontium and lead

Hypertension has long been recognized as the global health burden. Heavy metal pollution may be one of the environmental risk factors of hypertension. However, the association remains unclear. We studied the levels of aluminum (Al), vanadium (V), manganese (Mn), arsenic (As), selenium (Se), strontium (Sr), barium (Ba), titanium (Ti), lead (Pb) and cobalt (Co) in whole blood, and the relationship between trace element exposure and hypertension in the elderly community-based Chinese population. A total of 1013 participants from the west of Anhui Province in China were consecutively enrolled in this study in 2016. The general sociodemographic characteristics, lifestyles, disease history and physical examination information were collected by face-to-face survey and physical examination. The levels of ten trace elements were determined by inductively coupled plasma mass spectrometry (ICP-MS). Multivariable logistic regression model was used to assess the association of trace element exposure with the risk of hypertension. Results showed that the odds ratio of hypertension in the highest quartile was 1.811 (95% CI 1.175-2.790, P trend = 0.005) and 1.772 (95% CI 1.121-2.800, P trend = 0.022), respectively, after adjusting for potential confounders, as compared with the lowest quartile of blood Pb and Sr levels.

Association of urinary nickel levels with diabetes and fasting blood glucose levels: A nationwide Chinese population-based study

Some epidemiological studies support a relationship between nickel exposure and diabetes in the general population. To address this, we tested the association of nickel exposure with diabetes in 10,890 adults aged ≥ 18 years old from the China National Human Biomonitoring study conducted in 2017-2018. Urinary nickel concentrations and fasting blood glucose (FBG) were measured, and lifestyle and demographic data were collected. Weighted logistic and linear regressions were used to estimate the associations of urinary nickel levels with diabetes prevalence and FBG. Restricted cubic splines (RCS) were used to test for the dose-response relationship. The odd ratio (95% confidence interval [CI]) of diabetes for the highest versus lowest quartiles of urinary nickel concentrations was 1.74 (1.28, 2.36) in the multivariate model (p _trend =0.001). Each one-unit increase in log-transformed urinary nickel concentrations was associated with a 0.36 (0.17, 0.55) mmol/L elevation in FBG. The RCS curves showed a monotonically increasing dose-response relationship of urinary nickel with diabetes as well as FBG levels, and then tended to flatten after about 4.75 μg/L of nickel exposure. The nickel-diabetes association was stronger in individuals with lower than those with higher rice consumption (OR: 2.39 vs. 1.72). Our study supports a positive association between nickel exposure and diabetes prevalence in Chinese adults, especially in individuals with lower rice consumption. Further large-scale prospective studies are needed to validate our findings.

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.

Biogenic Selenium Nanoparticles in Biomedical Sciences: Properties, Current Trends, Novel Opportunities and Emerging Challenges in Theranostic Nanomedicine

Selenium is an important dietary supplement and an essential trace element incorporated into selenoproteins with growth-modulating properties and cytotoxic mechanisms of action. However, different compounds of selenium usually possess a narrow nutritional or therapeutic window with a low degree of absorption and delicate safety margins, depending on the dose and the chemical form in which they are provided to the organism. Hence, selenium nanoparticles (SeNPs) are emerging as a novel therapeutic and diagnostic platform with decreased toxicity and the capacity to enhance the biological properties of Se-based compounds. Consistent with the exciting possibilities offered by nanotechnology in the diagnosis, treatment, and prevention of diseases, SeNPs are useful tools in current biomedical research with exceptional benefits as potential therapeutics, with enhanced bioavailability, improved targeting, and effectiveness against oxidative stress and inflammation-mediated disorders. In view of the need for developing eco-friendly, inexpensive, simple, and high-throughput biomedical agents that can also ally with theranostic purposes and exhibit negligible side effects, biogenic SeNPs are receiving special attention. The present manuscript aims to be a reference in its kind by providing the readership with a thorough and comprehensive review that emphasizes the current, yet expanding, possibilities offered by biogenic SeNPs in the biomedical field and the promise they hold among selenium-derived products to, eventually, elicit future developments. First, the present review recalls the physiological importance of selenium as an oligo-element and introduces the unique biological, physicochemical, optoelectronic, and catalytic properties of Se nanomaterials. Then, it addresses the significance of nanosizing on pharmacological activity (pharmacokinetics and pharmacodynamics) and cellular interactions of SeNPs. Importantly, it discusses in detail the role of biosynthesized SeNPs as innovative theranostic agents for personalized nanomedicine-based therapies. Finally, this review explores the role of biogenic SeNPs in the ongoing context of the SARS-CoV-2 pandemic and presents key prospects in translational nanomedicine.

The effect and underlying mechanisms of titanium dioxide nanoparticles on glucose homeostasis: A literature review

Titanium dioxide (TiO₂ ) is used extensively as a white pigment in the food industry, personal care, and a variety of products of everyday use. Although TiO₂ has been categorized as a bioinert material, recent evidence has demonstrated different toxicity profiles of TiO₂ nanoparticles (NPs) and a potential health risk to humans. Studies indicated that titanium dioxide enters the systemic circulation and accumulates in the lungs, liver, kidneys, spleen, heart, and central nervous system and may cause oxidative stress and tissue damage in these vital organs. Recently, some studies have raised concerns about the possible detrimental effects of TiO₂ NPs on glucose homeostasis. However, the findings should be interpreted with caution due to the methodological issues. This article aims to evaluate current evidence regarding the effects of TiO₂ NPs on glucose homeostasis, including possible underlying mechanisms. Furthermore, the limitations of current studies are discussed, which may provide a comprehensive understanding and new perspectives for future studies in this field.

Scientific opinion on the tolerable upper intake level for selenium

Following a request from the European Commission, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was asked to deliver a scientific opinion on the tolerable upper intake level (UL) for selenium. Systematic reviews of the literature were conducted to identify evidence regarding excess selenium intake and clinical effects and potential biomarkers of effect, risk of chronic diseases and impaired neuropsychological development in humans. Alopecia, as an early observable feature and a well-established adverse effect of excess selenium exposure, is selected as the critical endpoint on which to base a UL for selenium. A lowest-observed-adverse-effect-level (LOAEL) of 330 μg/day is identified from a large randomised controlled trial in humans (the Selenium and Vitamin E Cancer Prevention Trial (SELECT)), to which an uncertainty factor of 1.3 is applied. A UL of 255 μg/day is established for adult men and women (including pregnant and lactating women). ULs for children are derived from the UL for adults using allometric scaling (body weight0.75). Based on available intake data, adult consumers are unlikely to exceed the UL, except for regular users of food supplements containing high daily doses of selenium or regular consumers of Brazil nuts. No risk has been reported with the current levels of selenium intake in European countries from food (excluding food supplements) in toddlers and children, and selenium intake arising from the natural content of foods does not raise reasons for concern. Selenium-containing supplements in toddlers and children should be used with caution, based on individual needs.

Association of Serum Antioxidant Minerals and Type 2 Diabetes Mellitus in Chinese Urban Residents

Antioxidant minerals including zinc, copper and selenium play critical roles in the maintenance of the redox balance in the body. However, their influences on type 2 diabetes mellitus (T2DM) are still inconclusive in Chinese populations. To elucidate the relationship between antioxidant minerals and T2DM, serum zinc, copper and selenium concentrations were measured in 1443 Chinese urban residents using a 1:2 matched case-control study. Conditional logistic regression models (CLR) were used to obtain the odds ratios (ORs) and 95% confidence intervals (CIs), and restricted cubic splines (RCS) were used to examine their dose−response associations. Serum zinc (OR = 0.52 [0.35, 0.77]) and copper concentrations (OR = 0.25 [0.17, 0.37]) were negatively associated with T2DM in a fully adjusted model. An L-shaped zinc-T2DM association (Poverall association = 0.003, and Pnonlinearity = 0.005) and a negative linear copper-T2DM association (Poverall association < 0.0001, and Pnonlinearity = 0.395) were observed. No association was found between serum selenium and T2DM in fully adjusted CLR or RCS models. In addition, joint associations with T2DM were identified between serum zinc and copper and between serum selenium and copper. In conclusion, our study emphasizes the importance of an adequate intake of antioxidant minerals for T2DM prevention in the Chinese population.

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.

Metabolome-Wide Association Study of Multiple Plasma Metals with Serum Metabolomic Profile among Middle-to-Older-Aged Chinese Adults

Metal exposure has been associated with risk of various cardio-metabolic disorders, and investigation on the association between exposure to multiple metals and metabolic responses may reveal novel clues to the underlying mechanisms. Based on a metabolome-wide association study of 17 plasma metals with untargeted metabolomic profiling of 189 serum metabolites among 1992 participants within the Dongfeng-Tongji cohort, we replicated two metal-associated pathways, linoleic acid metabolism and aminoacyl-tRNA biosynthesis, with novel metal associations (false discovery rate, FDR < 0.05), and we also identified two novel pathways, including biosynthesis of unsaturated fatty acids and alpha-linolenic acid metabolism, as associated with metal exposure (FDR < 0.05). Moreover, two-way orthogonal partial least-squares analysis showed that five metabolites, including aspartylphenylalanine, free fatty acid 14:1, uridine, carnitine C14:2, and LPC 18:2, contributed most to the joint covariation between the two data matrices (12.3%, 8.3%, 8.0%, 7.4%, and 7.3%, respectively). Further BKMR analysis showed significant positive joint associations of plasma Al, As, Ba, and Zn with aspartylphenylalanine and of plasma Ba, Co, Mn, and Pb with carnitine C14:2, when all the metals were at the 55th percentiles or above, compared with the median. We also found significant interactions between As and Ba in the association with aspartylphenylalanine (P for interaction = 0.048) and between Ba and Pb in the association with carnitine C14:2 (P for interaction < 0.001). Together, these findings may provide new insights into the mechanisms underlying the adverse health effects induced by metal exposure.

Associations of exposure to multiple metals with blood pressure and hypertension: A cross-sectional study in Chinese preschool children

Exposure to metals might be a risk factor for hypertension, which contributes largely to the global burden of disease and mortality. However, relevant epidemiological studies of associations between metals exposure with hypertension among preschoolers are limited. This study aimed to explore the associations of urine metals with blood pressure and hypertension among Chinese preschoolers. A total of 1220 eligible participants who had urine metals measurement, blood pressure measurements, and relevant covariates were included in this cross-sectional study. Urine concentrations of metals were measured by inductively coupled plasma mass spectrometer. The single and multiple metals regression models were used to investigate the associations of urine metal with blood pressure and the risk of hypertension after adjusting for potential confounders. We observed urine concentrations of chromium, iron, and barium were negatively associated with levels of systolic blood pressure, diastolic blood pressure and the risk of hypertension in the single metal model (all P-FDR adjustment <0.05). Significant associations of urine chromium concentrations with systolic blood pressure, diastolic blood pressure and the risk of hypertension were found in the multi-metal model (β or OR (95% confidence interval) was -3.07 (-5.12, -1.02), -2.25 (-4.29, -0.22), and 0.51 (0.26, 0.97) for 3rd quartile, compared with 1st quartile, respectively). The same association was found for barium concentrations in the multi-metal model, while none of the associations among iron quartiles was significant. In addition, urine chromium, iron and barium may have joint effects on systolic blood pressure, diastolic blood pressure and hypertension. Children's age and body mass index could modify the associations of chromium, iron, and barium concentrations with blood pressure. Our findings suggested that exposure to chromium, iron, and barium was inversely associated with blood pressure and hypertension among preschool children. These findings need further validation in prospective studies.

Individual and joint associations of co-exposure to multiple plasma metals with telomere length among middle-aged and older Chinese in the Dongfeng-Tongji cohort

Studies on associations of metals with leucocyte telomere length (LTL) were mainly limited to several most common toxic metals and single-metal effect, but the impact of other common metals and especially the overall joint associations and interactions of metal mixture with LTL are largely unknown. We included 15 plasma metals and LTL among 4906 participants from Dongfeng-Tongji cohort. Multivariable linear regression was used to estimate associations of individual metals with LTL. We also applied Bayesian kernel machine regression (BKMR) and quantile g-computation regression (Q-g) to evaluate the overall association and interactions, and identified the major contributors as well as the potential modifications by major characteristics. Multivariable linear regression found vanadium, copper, arsenic, aluminum and nickel were negatively associated with LTL, and a 2-fold change was related to 1.9%-5.1% shorter LTL; while manganese and zinc showed 3.7% and 4.0% longer LTL (all P < 0.05) in multiple-metal models. BKMR confirmed above metals and revealed a linearly inverse joint association between 15 metals and LTL. Q-g regression further indicated each quantile increase in mixture was associated with 5.2% shorter LTL (95% CI: -8.1%, -2.3%). Furthermore, manganese counteracted against aluminum and vanadium respectively (P_int<0.05). In addition, associations of vanadium, aluminum and metal mixture with LTL were more prominent in overweight participants. Our results are among the first to provide a new comprehensive view of metal mixture exposure on LTL attrition in the general population, including identifying the major components, metals interactions and the overall effects.

Associations of multiple plasma metals with chronic kidney disease in patients with diabetes

As common contaminants, metals are non-negligible risk factors for diabetes and chronic kidney disease. However, whether there is an association between multiple metals exposure and incident chronic kidney disease (CKD) risk in patients with diabetes is unclear. We conducted a prospective study to evaluate these associations. In total, 3071 diabetics with baseline estimated glomerular filtration rate (eGFR) ≥ 60 mL/min/1.73 m² from the Dongfeng-Tongji cohort were included. We measured baseline plasma concentrations of 23 metals and investigated the associations between plasma metal concentrations and CKD in diabetics using logistic regression, the least absolute shrinkage and selection operator (LASSO), and the Bayesian Kernel Machine Regression (BKMR) models. During average 4.6 years of follow-up, 457 diabetics developed CKD (14.9 %). The three models consistently found plasma levels of zinc, arsenic, and rubidium had a positive association with incident CKD risk in patients with diabetes, while titanium, cadmium, and lead had an inverse correlation. The results of BKMR showed a significant and positive overall effect of 23 metals on the risk of CKD, when all of the metals were above the 50th percentile as compared to the median value. In addition, potential interactions of zinc and arsenic, zinc and cadmium, zinc and lead, titanium and arsenic, and cadmium and lead on CKD risk were observed. In summary, we found significant associations of plasma titanium, zinc, arsenic, rubidium, cadmium, and lead with CKD in diabetes and interactions between these metals except for rubidium. Co-exposure to multiple metals was associated with increased CKD risk in diabetics.

Relationship between maternal exposure to heavy metal titanium and offspring congenital heart defects in Lanzhou, China: A nested case-control study

Background

Previous studies have found that exposure to heavy metals increased the incidence of congenital heart defects (CHDs). However, there is a paucity of information about the connection between exposure to titanium and CHDs. This study sought to examine the relationship between prenatal titanium exposure and the risk of CHDs in offspring.

Methods

We looked back on a birth cohort study that was carried out in our hospital between 2010 and 2012. The associations between titanium exposure and the risk of CHDs were analyzed by using logistic regression analysis to investigate titanium concentrations in maternal whole blood and fetal umbilical cord blood.

Results

A total of 97 case groups and 194 control groups were included for a nested case-control study. The [P₅₀ (P₂₅, P₇₅)] of titanium were 371.91 (188.85, 659.15) μg/L and 370.43 (264.86, 459.76) μg/L in serum titanium levels in pregnant women and in umbilical cord serum titanium content in the CHDs group, respectively. There was a moderate positive correlation between the concentration of titanium in pregnant women's blood and that in umbilical cord blood. A higher concentrations of maternal blood titanium level was associated with a greater risk of CHDs (OR 2.706, 95% CI 1.547–4.734), the multiple CHDs (OR 2.382, 95% CI 1.219–4.655), atrial septal defects (OR 2.367, 95% CI 1.215–4.609), and patent ductus arteriosus (OR 2.412, 95% CI 1.336–4.357). Dramatically higher concentrations of umbilical cord blood levels had an increased risk of CHDs and different heart defects.

Conclusion

Titanium can cross the placental barrier and the occurrence of CHDs may be related to titanium exposure.

Plasma metal concentrations and their interactions with genetic susceptibility on homocysteine levels

Limited studies have evaluated the associations of multiple metal exposures with homocysteine (Hcy) levels, which were independent risk factor for cardiovascular disease (CVD). Furthermore, the interactions between genetic variants and plasma metals in relation to Hcy levels were largely unknown. We aimed to explore the associations of multiple plasma metals (including metalloids arsenic [As] and selenium [Se]) with Hcy levels and whether their associations were modified by genetic susceptibility. We included 2989 participants from the baseline of the Dongfeng-Tongji cohort (DFTJ cohort) and conducted a cross-sectional study to explore the associations of 17 plasma metals with serum Hcy levels. Both multi-variable linear regression model (single-metal model) and LASSO penalized regression model (multiple-metal model) were used to identify the Hcy-associated metals. The weighted genetic risk score (GRS) was calculated based on 18 established Hcy-associated genetic variants. For metals that were associated with Hcy, we further assessed the gene-metal interactions on Hcy levels. Among 17 metals, plasma molybdenum (Mo), strontium (Sr), and Zinc (Zn) were positively associated with Hcy levels, whereas Se was inversely associated with Hcy levels in both single- and multiple-metal models. We also observed that the genetic predisposition to Hcy significantly modified the association between plasma Se and serum Hcy levels (P for interaction = 0.003), while no significant gene-metal interactions were found for Mo, Sr, and Zn (all P for interactions > 0.05). These findings provide novel insight into the associations of the plasma concentrations of Mo, Se, Sr and Zn with Hcy levels and address the importance of Se as a potential upstream modifiable factor for the personalized prevention of elevated Hcy levels and CVD.

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 (P_overall = 0.008 and P_non-linear = 0.100 for Co, P_overall = 0.011 and P_non-linear = 0.138 for Sn) and inverse (P_overall = 0.001, P_non-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.

Manganese Exposure and Metabolic Syndrome: A Systematic Review and Meta-Analysis

Manganese (Mn) is an essential element acting as a co-factor of superoxide dismutase, and it is potentially beneficial for cardiometabolic health by reducing oxidative stress. Although some studies have examined the relationship between Mn and metabolic syndrome (MetS), no systematic review and meta-analysis has been presented to summarize the evidence. Therefore, the present review examined the association between dietary and environmental Mn exposure, and MetS risk. A total of nine cross-sectional studies and three case-control studies were included, which assessed Mn from diet, serum, urine, and whole blood. The association of the highest Mn level from diet (three studies, odds ratio (OR): 0.83, 95% confidence interval (C.I.) = 0.57, 1.21), serum (two studies, OR: 0.87, 95% C.I. = 0.66, 1.14), urine (two studies, OR: 0.84, 95% C.I. = 0.59, 1.19), and whole blood (two studies, OR: 0.92, 95% C.I. = 0.53, 1.60) were insignificant, but some included studies have suggested a non-linear relationship of urinary and blood Mn with MetS, and higher dietary Mn may associate with a lower MetS risk in some of the included studies. While more evidence from prospective cohorts is needed, future studies should use novel statistical approaches to evaluate relative contribution of Mn on MetS risk along with other inter-related exposures.

Associations of plasma metal levels with type 2 diabetes and the mediating effects of microRNAs

The present study aims to determine the associations of multiple plasma metal levels and plasma microRNAs (miRNAs) with diabetes risk, and further explore the mediating effects of plasma miRNAs on the associations of plasma metal with diabetes risk. We detected plasma levels of 23 metals by inductively coupled plasma mass spectrometry (ICP-MS) among 94 newly diagnosed and untreated diabetic cases and 94 healthy controls. The plasma miRNAs were examined by microRNA Array screening and Taqman real-time PCR validation among the same study population. The multivariate logistic regression models were employed to explore the associations of plasma metal and miRNAs levels with diabetes risk. Generalized linear regression models were utilized to investigate the relationships between plasma metal and plasma miRNAs, and mediation analysis was used to assess the mediating effects of plasma miRNAs on the relationships between plasma metals and diabetes risk. Plasma aluminum (Al), titanium (Ti), copper (Cu), zinc (Zn), selenium (Se), rubidium (Rb), strontium (Sr), barium (Ba), and Thallium (Tl) levels were correlated with elevated diabetic risk while molybdenum (Mo) with decreased diabetic risk (P < 0.05 after FDR multiple correction). MiR-122-5p and miR-3141 were positively associated with diabetes risk (all P < 0.05). Ti, Cu, and Zn were positively correlated with miR-122-5p (P = 0.001, 0.028 and 0.004 respectively). Ti, Cu, and Se were positively correlated with miR-3141 (P = 0.003, 0.015, and 0.031 respectively). In addition, Zn was positively correlated with miR-193b-3p (P = 0.002). Ti was negatively correlated with miR-26b-3p (P = 0.016), while Mo and miR-26b-3p were positively correlated (P = 0.042). In the mediation analysis, miR-122-5p mediated 48.0% of the association between Ti and diabetes risk. The biological mechanisms of the association are needed to be explored in further studies.

Associations between multiple heavy metals exposure and glycated hemoglobin in a Chinese population

BACKGROUND

Heavy metals may play an important role as environmental risk factors in diabetes mellitus. This study aimed to explore the association of HbA1c with As, Cd, Cu, Ni, Pb, and Zn in single-metal exposure and multi-metal co-exposure models.

METHODS

A cross-sectional study involving 3472 participants was conducted. Plasma concentrations of heavy metals were determined by inductively coupled plasma mass spectrometry. We estimated the association of each metal with HbA1c by linear regression. Potential heterogeneities by sex, age, and smoking were investigated, and metal mixtures and interactions were assessed by the Bayesian kernel machine regression (BKMR).

RESULTS

In linear regression, Cu (β = 0.324, p < 0.05) and Ni (β = -0.19, p < 0.05) showed significant association with HbA1c in all participants. In BKMR analyses, all exposure-response relationships were approximately linear. Cu was significantly and positively associated with HbA1c levels in overall participants, women, participants aged 60 years old and above, and nonsmokers. Ni was significantly and negatively associated with HbA1c levels in overall participants. We did not observe the overall effect of plasma metal mixtures on HbA1c or the interaction effect of the metals on HbA1c.

CONCLUSION

Cu was positively correlated with HbA1c, whereas Ni was negatively correlated with HbA1c, when evaluated individually or in a metal mixture. Additional studies are necessary to confirm these correlations and to control for exposure to different metals in the general population.

Associations of plasma metal concentrations with the risks of all-cause and cardiovascular disease mortality in Chinese adults

BACKGROUND

Exposure to metals/metalloids from both the natural environment and anthropogenic sources have a complex influence on human health. However, relatively few studies have explored the relations of exposure to multiple metals/metalloids with mortality. Therefore, this prospective study aims to examine the relations of multiple metal/metalloids exposures with all-cause and cardiovascular disease (CVD) mortality.

METHODS

A total of 6155 participants within the Dongfeng-Tongji (DF-TJ) cohort were involved in this analysis, which were followed for mortality until December 31, 2018. We applied inductively coupled plasma mass spectrometry (ICP-MS) to measure baseline plasma concentrations of 23 metals. We utilized Cox regression models to calculate the hazard ratios (HRs) for all-cause and CVD mortality associated with metal concentrations. We proposed plasma metal score to assess the simultaneous exposure to multiple metals through summing each metal concentration weighted by the regression coefficients with all-cause mortality.

RESULTS

During the follow-up (mean duration, 9.8 years), we ascertained 876 deaths, including 416 deaths of CVD (157 deaths of coronary heart disease and 259 deaths of stroke). In the multiple-metals model, after adjusting for potential confounders, plasma copper, molybdenum, and vanadium were positively associated with all-cause mortality, whereas manganese, selenium, and thallium were negatively associated with the risk of all-cause mortality, with adjusted HRs (95% Confidence Interval, CI) of the fourth quartiles were 1.73 (1.42-2.11, P-trend < 0.001) for copper, 1.33 (1.09-1.63, P-trend = 0.005) for molybdenum, 1.43 (1.16-1.77, P-trend < 0.001) for vanadium, 0.74 (0.58-0.94, P-trend = 0.005) for manganese, 0.68 (0.56-0.83, P-trend < 0.001) for selenium, and 0.74 (0.59-0.92, P-trend = 0.002) for thallium, respectively. Positive associations were observed between plasma copper, molybdenum, vanadium concentrations and CVD mortality, whereas negative associations were found for plasma selenium and thallium concentrations with CVD mortality in the multiple-metals model. Compared with the first quartiles, the HRs of fourth quartiles were 1.94 (1.45-2.58, P-trend < 0.001) for copper, 1.72 (1.26-2.35, P-trend < 0.001) for molybdenum, 1.81 (1.32-2.47, P-trend < 0.001) for vanadium, 0.67 (0.50-0.89, P-trend = 0.003) for selenium, and 0.58 (0.41-0.81, P-trend < 0.001) for thallium, respectively. The plasma metal score was significantly associated with higher risks of all-cause and CVD death in dose-response fashions. When compared with the first quartiles of plasma metal score, the HRs of fourth quartiles were 2.16 (1.76-2.64; P-trend < 0.001) for all-cause mortality and 3.00 (2.24-4.02; P-trend < 0.001) for CVD mortality.

CONCLUSIONS

The study indicated that several plasma metals/metalloids were key determinants and predictors of all-cause and CVD death in the Chinese population. Our findings highlighted the importance to comprehensively assess and monitor multiple metals/metalloids exposures.

Environmental Nickel Exposure and Diabetes in a Nationally Representative Sample of US Adults

Laboratory studies have shown that nickel exposure may adversely affect glucose metabolism. However, studies about the effects of environmental nickel exposure on diabetes pathogenesis in humans are sparse. We aimed to evaluate the association of urinary nickel concentrations, as a biomarker of environmental nickel exposure, and diabetes in a nationally representative sample of US adults. The data from a nationally representative population (n = 1585) in the National Health and Nutrition Examination Survey 2017-18 were used. Diabetes (n = 330) was defined as self-reported physician's diagnosis, HbA1c ≥ 6.5%, fasting plasma glucose ≥ 126 mg/dL, or 2-h plasma glucose ≥ 200 mg/dL. Urinary nickel concentrations were determined by inductively coupled plasma mass spectrometry. Logistic regression with sample weights was used to estimate the odds ratios (ORs) of diabetes and 95% confidence intervals (CIs). Urinary nickel concentrations were higher in individuals with diabetes (weighted median 1.23 μg/L) than those without diabetes (1.01 μg/L). After adjustment for urinary creatinine and other risk factors for diabetes, the OR of diabetes comparing the highest with lowest quartile of urinary nickel concentrations was 2.70 (95% CI 1.39-5.24; P_trend = 0.03). Environmental nickel exposure is positively and significantly associated with diabetes in U.S. adults.

Associations of plasma metal concentrations with incident dyslipidemia: Prospective findings from the Dongfeng-Tongji cohort

Metal exposures are ubiquitous around the world, while it is lack of prospective studies to evaluate the associations of exposure to multiple metal/metalloids with incident dyslipidemia. A total of 2947 participants without dyslipidemia at baseline were included in the analyses. We utilized inductively coupled plasma mass spectrometry to measure the baseline plasma metal concentrations. Unconditional logistic regression models were applied to estimate the relations between plasma metals and risk of incident dyslipidemia, and principal component analysis was performed to extract principal components of metals. During 5.01 ± 0.31 years of follow-up, 521 subjects were diagnosed with incident dyslipidemia. After multivariable adjustment, the odds ratios (ORs) of dyslipidemia comparing the highest quartiles to the lowest were 1.58 (95% CI: 1.20, 2.08; P_trend = 0.001) for aluminum, 1.34 (95% CI: 1.03, 1.75; P_trend = 0.03) for arsenic, 1.44 (1.09, 1.91; P_trend = 0.03) for strontium, and 1.47 (95% CI: 1.09, 2.00; P_trend = 0.005) for vanadium. The four metals also showed significant associations with the subtypes of dyslipidemia, including low HDL-C and high LDL-C. The first principal component, which mainly represented aluminum, arsenic, barium, lead, vanadium, and zinc, was associated with increased risk of incident dyslipidemia, and the adjusted OR was 1.40 (95% CI: 1.07, 1.84; P_trend = 0.02) comparing extreme quartiles. The study indicated that elevated plasma aluminum, arsenic, strontium, and vanadium concentrations were associated with a higher incidence of dyslipidemia. These findings highlight the importance of controlling metal exposures for dyslipidemia prevention.

Trace elements concentration in adipose tissue and the risk of incident type 2 diabetes in a prospective adult cohort

The aim of this work was to study the associations of adipose tissue trace element concentrations with type 2 diabetes (T2DM) incidence over a 16-year follow-up period in an adult cohort from Southern Spain. 16-year T2DM incidence was gathered from hospital records. Chemical analyses of Cr, V, Zn, Fe, Cu and Se in adipose tissue were performed using inductively coupled plasma mass spectrometry. Multivariable Cox-regression models were used. Complementary cross-sectional analyses with markers of glucose homeostasis at recruitment were performed by multivariable linear regression. Out of 214 participants, 39 developed T2DM during the follow-up. Adipose tissue concentrations of Fe (HR = 1.97, 95% CI: 0.99 to 2.58, p = 0.057), Cr (HR = 1.58, 95% CI: 1.07-2.33, p = 0.022) and Cu (HR = 1.61, 95% CI: 1.01-2.58, p = 0.046) were individually associated with T2DM incidence. When Fe, Cr and Cu were simultaneously entered in a model, only Cr was significantly associated with T2DM incidence (HR = 1.68, 95% CI: 1.02-2.76, p = 0.041). Furthermore, adipose tissue V (β = 0.283, p = 0.004) and Zn (β = 0.217, p = 0.028) concentrations were positively associated with β-pancreatic cell function (HOMA-β), while Se showed an inverse association (β = -0.049, p = 0.027). Although further research is warranted on the potential mechanisms of action, our results suggest that adipose tissue concentrations of certain trace elements (particularly Fe, Cr and Cu) are associated with the risk of incident T2DM, while V and Zn might have a protective effect. These biomarkers might complement prediction algorithms and contribute to identify patients with an increased risk of T2DM.

Contribution of trace element exposure to gestational diabetes mellitus through disturbing the gut microbiome

BACKGROUND

A healthy gut microbiome is critical for glucose metabolism during pregnancy. In vivo studies indicate that trace element affects the composition and function of the gut microbiome and potentially leads to metabolic disorders but their relationships are largely unknown. We aimed to investigate whether the gut microbiome plays a role in the relationship between trace element exposure and gestational diabetes mellitus (GDM).

METHODS

In a prospective cohort study, serum levels of 22 trace elements and the fecal gut microbiome composition were assessed in 837 pregnant women in the second trimester between 22 and 24 weeks of pregnancy prior to GDM diagnosis. Regression and mediation analysis were used to explore the link between element exposure, the gut microbiome, and GDM.

RESULTS

128 pregnant women (15.3%) were diagnosed with GDM. No individual trace elements were found significantly associated with GDM. In contrast, the composition of the gut microbiome was dramatically altered in women later diagnosed with GDM and characterized by lower alpha diversity and lower abundance of co-abundance groups (CAGs) composed of genera belonging to Ruminococcaceae, Coriobacteriales, and Lachnospiraceae. Rubidium (Rb) was positively associated with alpha diversity indices while mercury (Hg) and vanadium (V) showed negative associations. Elements including rubidium (Rb), thallium (Tl), arsenic (As), and antimony (Sb) were significantly correlated with GDM-related CAGs and mediation analysis revealed that Rb and Sb were inversely related to GDM risk by altering abundance levels of CAGs enriched for Lachnospiraceae, Coriobacteriales, and Ruminococcaceae.

CONCLUSION

Our study indicates that trace element exposure is associated with specific gut microbiome features that may contribute to GDM development, which could provide a new avenue for intervening in environmental exposure-related GDM.

Association of whole blood copper, magnesium and zinc levels with metabolic syndrome components in 6-12-year-old rural Chinese children: 2010-2012 China National Nutrition and Health Survey

BACKGROUND

Metabolic syndrome (MetS) is significantly associated with the risk of cardiovascular disease and its prevalence is showing a trend of getting younger. Previous studies on the relationship between elements and MetS were mostly reported in adults with single element analysis, while reports in children with combined effects of multiple elements were very limited. The aim of this study is to investigate the association between whole blood Cu, Mg and Zn in both single and combined effects and MetS components in rural Chinese children aged 6-12 years based on the data from 2010-2012 China National Nutrition and Health Survey.

METHODS

A total of 911 children (51.2% male, 48.7% female) aged 6-12 years were included. Basic characteristics and MetS component parameters were collected and determined by trained stuffs. Elements were detected by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Multivariate logistic regression analysis was performed to examine the independent relationship between elements and MetS components.

RESULTS

In single metal analysis, copper was positively associated with elevated waist (OR = 2.00, 1.18-3.28) and all of the metals were associated with elevated TG. And the comprehensive analysis of multiple elements were mostly consistent with the results of single element analysis (low Cu + high Zn with elevated TG (OR = 2.21, 1.18-4.13), high Cu + low Mg with elevated TG (OR = 0.40, 0.16-0.95), high Cu + high Mg with elevated waist (OR = 2.03, 1.26-3.27)), except the combination of Zn and Mg (high Zn + low Mg with reduced HDL-C (OR = 0.47, 0.28-0.77)).

CONCLUSIONS

Our study suggested Cu, Zn and Mg in children are indeed associated with metabolic syndrome components, whether in single element or multi-element combined analysis. The results will be confirmed through additional cohort research.

Exposure to heavy metals from point pollution sources and risk of incident type 2 diabetes among women: a prospective cohort analysis

Heavy metal exposures may contribute to diabetes risk but prospective studies are uncommon. We analyzed the Australian Longitudinal Study on Women's Health (three cohorts aged 18-23, 45-50, or 70-75 at baseline in 1996, N = 34,191) merged with emissions data for 10 heavy metals (As, Be, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn) from the National Pollutant Inventory. Over 20-year follow-up, 2,584 women (7.6%) reported incident diabetes. Cox proportional hazards regression models showed that women aged 45-50 at baseline had higher diabetes risk in association with exposure to total air emissions, total water emissions, all individual metals air emissions, and six individual water emissions. After correction for false discovery rate, nine of 11 air emissions and five water emissions remained significant. Associations were not observed for land-based emissions, or for younger or older cohorts. Emissions were dominated by mining, electricity generation and other metals-related industrial processes.

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.

The Relationship Between Heavy Metal Exposure, Trace Element Level, and Monocyte to HDL Cholesterol Ratio with Gestational Diabetes Mellitus

The objective of this study is to assess the levels of heavy metals (cadmium, lead, antimony, mercury, and arsenic), which are also called endocrine-disrupting chemicals, and trace elements (chromium-III, chromium-VI, zinc, copper, and selenium) vs. monocyte to HDL ratio among pregnant women with gestational diabetes mellitus (GDM). A total of 112 pregnant women (60 with GDM and 52 healthy women) were included in this case-control study. Analysis of heavy metals and trace elements were performed in inductively coupled plasma mass spectrometer. Heavy metals (cadmium, lead, antimony, mercury, and arsenic), trace elements (chromium-III, chromium-VI, zinc, copper, and selenium), and metabolic parameters were assessed in both groups. It was determined that the levels of cadmium, lead, antimony, and copper were higher (p < 0.05) and levels of chromium-III, zinc, and selenium were lower (p < 0.05) among the GDM group compared to the control group, whereas there was a statistically insignificant difference between the two groups, regarding the levels of copper, mercury, and arsenic (p > 0.05). Moreover, the monocyte to HDL ratio was higher in the GDM group (p < 0.05), and the insulin resistance was significantly higher as well (p < 0.05). The results of our study demonstrated that environmental factors could be effective in the etiology of GDM. Toxic heavy metals, through inducing Cu, OS, and chronic inflammation, and other trace elements, either directly by impacting insulin secretion or through weakening the body's antioxidant defense system, could play a role in the occurrence of GDM.

Single-cell transcriptomics uncovers phenotypic alterations in the monocytes in a Chinese population with chronic cadmium exposure

BACKGROUND

Cadmium is the most prevalent form of heavy metal contaminant globally and its exposure rises serious health concern. Chronic exposure to cadmium causes immune disturbances. However, few studies have addressed how it affects circulating immune cells, one of the most essential elements for the host defense system, at both population and molecular level. Therefore, this is the first single-cell transcriptomic analysis of the response of the human circulating immune system to plasma cadmium level.

METHODS

We conducted a cross-sectional study in Hunan province, which has the highest level of cadmium land contamination in China. A total of 3283 individuals were eligible for analyzing the association between plasma cadmium levels and the monocyte counts and its subgroups. Another 780 individuals were assigned for validation. Thirty propensity-matched individuals without chronic disease from the lowest- and highest-quartile groups according to serum cadmium levels were selected for single-cell RNA sequencing (scRNA-seq) and flow cytometry analyses. Moreover, the monocyte phenotypic alterations in the heavy metal-exposed population were validated with a cecal ligation and puncture sepsis mouse model.

RESULTS

From August 2016 to July 2017, we conducted a cross-sectional study to identify phenotypic alterations in peripheral immune cells in cadmium polluted areas in China. Monocyte percentages were negatively associated with plasma cadmium levels in multivariable linear regression analysis. Peripheral blood mononuclear cell scRNA-seq revealed that the CD14⁺ monocyte subset was dramatically reduced in the highest-quartile cadmium-exposed group. Moreover, we assessed different hallmarks of immune cell dysfunction-such as host defense capability, apoptotic signaling, cellular diversity and malignant gene expression in monocytes. Importantly, cadmium induced phenotypic alterations in the immune system were validated in the cecal ligation and puncture sepsis mouse model, in which chronic exposure to cadmium not only increased the death rate but also decreased monocyte numbers and the ability to clear bacterial infections.

CONCLUSION

This transcriptomic analysis provides molecular information about how the most important hallmarks of immune cell dysfunction are affected by plasma cadmium level. The significant phenotypic alterations in monocytes serving as early indicators of increased susceptibility to infectious and malignant diseases.

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.