Nickel exposure is associated with the prevalence of type 2 diabetes in Chinese adults

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.

The association between e-cigarette use or dual use of e-cigarette and combustible cigarette and prediabetes, diabetes, or insulin resistance: Findings from the National Health and Nutrition Examination Survey (NHANES)

BACKGROUND

Studies have established associations between combustible cigarette use and diabetes. However, there is limited evidence on the association between e-cigarette use or dual use of e-cigarettes and combustible cigarettes and diabetes.

METHOD

With cross-sectional data of 5101 U.S. adults from the National Health and Nutrition Examination Survey, this study examined how e-cigarette use or dual use was related to diabetes, prediabetes, or insulin resistance. The presence of diabetes or prediabetes was determined by fasting glucose level, hemoglobin A1C (HbA1c), or the use of prescribed medications. Insulin resistance was assessed by the homeostatic model (HOMA-IR). The independent association between e-cigarette use or dual use and outcomes was examined using weighted multivariable logistic regression models controlling for potential confounders.

RESULTS

Of all participants, 6.3% were current e-cigarette users and 17.1% were former e-cigarette users. In the fully adjusted model, e-cigarette use was not associated with prediabetes or diabetes (P>0.05). However, former e-cigarette users were 22% (95% CI: 1.00, 1.84) more likely to report higher HOMA-IR (Q3 vs Q1) than never e-cigarette users. Among ever combustible cigarette users, current e-cigarette users and former e-cigarette users were 63% (95% CI: 1.00, 2.91) and 64% (95% CI: 1.04, 2.59) more likely to report higher HOMA-IR than never e-cigarette users, respectively. There was no significant association between dual use and diabetes, prediabetes, or insulin resistance (P>0.05).

CONCLUSIONS

E-cigarette use may be associated with insulin resistance. Our findings may inform future tobacco control policies and longitudinal studies assessing insulin resistance associated with e-cigarette use.

Nickel as a potential disruptor of thyroid function: benchmark modelling of human data

Introduction

Nickel (Ni) is one of the well-known toxic metals found in the environment. However, its influence on thyroid function is not explored enough. Hence, the aim of this study was to analyse the potential of Ni to disrupt thyroid function by exploring the relationship between blood Ni concentration and serum hormone levels (TSH, T4, T3, fT4 and fT3), as well as the parameters of thyroid homeostasis (SPINA-GT and SPINA-GD) by using correlation analysis and Benchmark (BMD) concept.

Methods

Ni concentration was measured by ICP-MS method, while CLIA was used for serum hormone determination. SPINA Thyr software was used to calculate SPINA-GT and SPINA-GD parameters. BMD analysis was performed by PROAST software (70.1). The limitations of this study are the small sample size and the uneven distribution of healthy and unhealthy subjects, limited confounding factors, as well as the age of the subjects that could have influenced the obtained results.

Results and discussion

The highest median value for blood Ni concentration was observed for the male population and amounted 8,278 µg/L. Accordingly, the statistically significant correlation was observed only in the male population, for Ni-fT4 and Ni-SPINA-GT pairs. The existence of a dose-response relationship was established between Ni and all the measured parameters of thyroid functions in entire population and in both sexes. However, the narrowest BMD intervals were obtained only in men, for Ni - SPINA-GT pair (1.36-60.9 µg/L) and Ni - fT3 pair (0.397-66.8 µg/L), indicating that even 78.68 and 83.25% of men in our study might be in 10% higher risk of Ni-induced SPINA-GT and fT3 alterations, respectively. Due to the relationship established between Ni and the SPINA-GT parameter, it can be concluded that Ni has an influence on the secretory function of the thyroid gland in men. Although the further research is required, these findings suggest possible role of Ni in thyroid function disturbances.

Metal Exposure during Early Pregnancy and Risk of Gestational Diabetes Mellitus: Mixture Effect and Mediation by Phospholipid Fatty Acids

Despite existing studies exploring the association between metal exposure and gestational diabetes mellitus (GDM), most of them have focused on a single metal or a small mixture of metals. Our prospective work investigated the joint and independent effects of early gestational exposure to 17 essential and nonessential metals on the GDM risk and potential mediation by plasma phospholipid fatty acids (PLFAs) based on a nested case-control study established with 335 GDM cases and 670 randomly matched healthy controls. The Bayesian kernel machine regression (BKMR) and quantile g-computation analyses demonstrated a joint effect from metal co-exposure on GDM risk. BKMR with hierarchical variable selection indicated that the group of essential metals was more strongly associated with GDM than the group of nonessential metals with group posterior inclusion probabilities (PIPs) of 0.979 and 0.672, respectively. Cu (0.988) and Ga (0.570) had the largest conditional PIPs within each group. We also observed significant mediation effects of selected unsaturated PLFAs on Cu-GDM and Ga-GDM associations. KEGG enrichment analysis further revealed significant enrichment in the biosynthesis of unsaturated PLFAs. C18:1 n-7 exhibited the largest proportion of mediation in both associations (23.8 and 22.9%). Collectively, our work demonstrated the joint effect of early gestational metal exposure on GDM risk and identified Cu and Ga as the key species to the joint effect. The findings lay a solid ground for further validation through multicenter investigations and mechanism exploration via laboratory studies.

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.

Adults

Background

Laboratory studies have linked nickel with the pathogenesis of cardiovascular disease (CVD); however, few observational studies in humans have confirmed this association.

Objective

This study aimed to use urinary nickel concentrations, as a biomarker of environmental nickel exposure, to evaluate the cross-sectional association between nickel exposure and CVD in a nationally representative sample of U.S. adults.

Methods

Data from a nationally representative sample (n = 2702) in the National Health and Nutrition Examination Survey 2017-20 were used. CVD (n = 326) was defined as self-reported physicians' diagnoses of coronary heart disease, angina, heart attack, or stroke. Urinary nickel concentrations were determined by inductively coupled plasma mass spectrometry. Logistic regression with sample weights was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of CVD.

Results

Urinary nickel concentrations were higher in individuals with CVD (weighted median 1.34 μg/L) compared to those without CVD (1.08 μg/L). After adjustment for demographic, socioeconomic, lifestyle, and other risk factors for CVD, the ORs (95% CIs) for CVD compared with the lowest quartile of urinary nickel were 3.57 (1.73-7.36) for the second quartile, 3.61 (1.83-7.13) for the third quartile, and 2.40 (1.03-5.59) for the fourth quartile. Cubic spline regression revealed a non-monotonic, inverse U-shaped, association between urinary nickel and CVD (Pnonlinearity < 0.001).

Conclusions

Nickel exposure is associated with CVD in a non-monotonic manner among U.S. adults independent of well-known CVD risk factors.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12403-023-00579-4.

Disease-associated metabolic pathways affected by heavy metals and metalloid

Increased exposure to environmental heavy metals and metalloids and their associated toxicities has become a major threat to human health. Hence, the association of these metals and metalloids with chronic, age-related metabolic disorders has gained much interest. The underlying molecular mechanisms that mediate these effects are often complex and incompletely understood. In this review, we summarize the currently known disease-associated metabolic and signaling pathways that are altered following different heavy metals and metalloids exposure, alongside a brief summary of the mechanisms of their impacts. The main focus of this study is to explore how these affected pathways are associated with chronic multifactorial diseases including diabetes, cardiovascular diseases, cancer, neurodegeneration, inflammation, and allergic responses upon exposure to arsenic (As), cadmium (Cd), chromium (Cr), iron (Fe), mercury (Hg), nickel (Ni), and vanadium (V). Although there is considerable overlap among the different heavy metals and metalloids-affected cellular pathways, these affect distinct metabolic pathways as well. The common pathways may be explored further to find common targets for treatment of the associated pathologic conditions.

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.

Mixtures of environmental contaminants and diabetes

BACKGROUND

Many studies have been published on the relationships between different environmental contaminants and diabetes. In these studies, the environmental contaminants have most often been evaluated one by one, but in real life we are exposed to a mixture of contaminants that interact with each other.

OBJECTIVE

The major aim of this study was to see if a mixture of contaminants could improve the prediction of incident diabetes, using machine learning.

METHODS

In the Prospective Investigation of the Vasculature in Uppsala (PIVUS) study (988 men and women aged 70 years), circulating levels of 42 contaminants from several chemical classes were measured at baseline. Incident diabetes was followed for 15 years. Six different machine-learning models were used to predict prevalent diabetes (n = 115). The variables with top importance were thereafter used to predict incident diabetes (n = 83).

RESULTS

Boosted regression trees performed best regarding prediction of prevalent diabetes (area under the ROC-curve = 0.70). Following removal of correlated contaminants, the addition of nine selected contaminants (Cd, Pb, Trans-nonachlor the phthalate MiBP, Hg, Ni, PCB126, PCB169 and PFOS) resulted in a significant improvement of 6.0 % of the ROC curve (from 0.66 to 0.72, p = 0.018) regarding incident diabetes (n = 51) compared with a baseline model including sex and BMI when the first 5 years of the follow-up was used. No such improvement in prediction was seen over 15 years follow-up. The single contaminant being most closely related to incident diabetes over 5 years was Nickel (odds ratio 1.44 for a SD change, 95 % CI 1.05-1.95, p = 0.022).

CONCLUSION

This study supports the view that machine learning was useful in finding a mixture of important contaminants that improved prediction of incident diabetes. This improvement in prediction was seen only during the first 5 years of follow-up.

Urinary Nickel Was Associated with the Prevalence of Diabetes: Results from NHANES

The study aimed to investigate the association between nickel exposure and the presence of diabetes (DM). The participants were analyzed from the National Health and Nutrition Examination Surveys (NHANES) 2017-2018. Urinary nickel exposure was measured using inductively coupled-plasma mass spectrometry. DM was diagnosed based on the WHO standards. The association between nickel and DM or fasting glucose was examined using multivariable linear regression models and logistic regression models. A total of 1899 participants (933 men and 966 women) were included in our study, of whom 342 (18.0%) were diagnosed with DM. There was a significant positive association between nickel level and DM (OR: 1.27, 95%CI: 1.04-1.56) after adjusting for potential confounding factors. Comparing with the lowest quartile, the highest quartile independently increased a 0.66-fold higher risk of DM (OR: 1.66, 95%CI: 1.13-2.44]). In addition, nickel exposure was independently related to the level of fasting glucose. The exposure to nickel was associated with a higher risk of DM in general population.

Recent advances in the application of ionomics in metabolic diseases

Trace elements and minerals play a significant role in human health and diseases. In recent years, ionomics has been rapidly and widely applied to explore the distribution, regulation, and crosstalk of different elements in various physiological and pathological processes. On the basis of multi-elemental analytical techniques and bioinformatics methods, it is possible to elucidate the relationship between the metabolism and homeostasis of diverse elements and common diseases. The current review aims to provide an overview of recent advances in the application of ionomics in metabolic disease research. We mainly focuses on the studies about ionomic or multi-elemental profiling of different biological samples for several major types of metabolic diseases, such as diabetes mellitus, obesity, and metabolic syndrome, which reveal distinct and dynamic patterns of ion contents and their potential benefits in the detection and prognosis of these illnesses. Accumulation of copper, selenium, and environmental toxic metals as well as deficiency of zinc and magnesium appear to be the most significant risk factors for the majority of metabolic diseases, suggesting that imbalance of these elements may be involved in the pathogenesis of these diseases. Moreover, each type of metabolic diseases has shown a relatively unique distribution of ions in biofluids and hair/nails from patients, which might serve as potential indicators for the respective disease. Overall, ionomics not only improves our understanding of the association between elemental dyshomeostasis and the development of metabolic disease but also assists in the identification of new potential diagnostic and prognostic markers in translational medicine.

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.

Metal Exposures in Residents Living Near an Urban Oil Drilling Site in Los Angeles, California

Urban environmental justice communities are potentially exposed to multiple toxic metals, through contaminated air, soil, water, and food. However, information on metals and their sources is lacking. This study uses non-negative matrix factorization (NMF) in a community-based participatory research study to identify potential sources and to understand how these metals cluster in a population near an urban oil drilling site. We recruited 203 Latinx, Black, and Asian residents who lived within 1 km of an oil drilling site in south Los Angeles and collected toenail clippings to assess exposure to arsenic (As), cadmium (Cd), mercury (Hg), manganese (Mn), nickel (Ni), lead (Pb), and antimony (Sb). Using NMF, we identified three clusters based on concentrations in the participants' toenails. As, Cd, Pb, and Sb grouped together, indicative of an industrial source. A second grouping was composed of Ni and Mn, which may be related to oil drilling. We also identified a third source factor predominantly driven by Hg and As, which may arise from dietary sources. Utilizing NMF, a dimension reduction method, we identified a source factor high in Ni and Mn in residents living in a neighborhood near an active oil drilling site.

Alleviating Effect of Methionine on Intestinal Development and Intercellular Junction Induced by Nickel

The aim of this study was to investigate the alleviating effect of methionine (Met) on intestinal injury induced by nickel. The mice were divided into six groups: Met-deficient + nickel group (MDN), Met-deficient group (MD), Met + nickel group (MN), high-dose Met + nickel group (HMN), high-dose Met group (HM), and blank control group (BC). Histopathological techniques, Alcian blue-periodic acid Schiff (AB-PAS) staining, enzyme-linked immunosorbent assay (ELISA), and real-time PCR were used to study the changes of intestinal development, the number of goblet cells, and the intercellular junction. The results showed that Met can inhibit the intestinal villus length and crypt depth decreases induced by nickel and increase the index villus length and crypt depth (V/C), the number of goblet cells, and the content of diamine oxidase (DAO) and decrease the content of fatty acid binding protein2 (FABP2) and endotoxin (ET) of the intestinal mucosa damage parameters, and the mRNA expression of intercellular junction (occludin, ZO-1, claudin-1) was damaged. It is suggested that Met could help inhibit the toxic effect of nickel on the intestinal development and intercellular connection.

Association between the nickel exposure and lipid profiles in general population from NHANES

This study is to investigate the association between nickel exposure and serum lipid profiles. We analyzed the population from the National Health and Nutrition Examination Surveys (NHANES) 2017-2018. Urinary nickel exposure was measured using inductively coupled-plasma mass spectrometry. Serum lipid profiles, including triglyceride (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), and low-density lipoprotein-cholesterol (LDL-C), were measured using the standard biochemistry assays. The association between urinary nickel and lipid profiles was examined using multivariable linear regression models and restricted cubic spine plots. There was a significant negative relationship between nickel level and TC (β, - 9.67; 95% CI, - 13.58 to - 5.76), HDL-C (β, - 1.57; 95% CI, - 2.98 to - 0.16), and LDL-C (β, - 5.88; 95% CI, - 11.04 to - 0.71) after adjusting for potential confounding factors. Furthermore, restricted cubic spines showed that only HDL-C was nonlinearly associated with nickel (p for nonlinearity 0.004). However, nickel exposure was not related to the level of triglyceride. The exposure to nickel was linearly associated with serum total cholesterol and LDL-C while nonlinearly associated with HDL-C in general population.

Metals and risk of incident metabolic syndrome in a prospective cohort of midlife women in the United States

Exposure to metals may contribute to the development of metabolic syndrome (MetS); however, evidence from midlife women who are at greater risk of cardiometabolic disease is limited. We assessed the associations of 15 urinary metal concentrations with incident MetS in a prospective cohort of midlife women in the United States. The study population included 947 White, Black, Chinese and Japanese women, aged 45-56 years, free of MetS at baseline (1999-2000), who participated in the Study of Women's Health Across the Nation Multi-Pollutant Study. Fifteen metals were detected in almost all participants urine samples using inductively coupled plasma mass spectrometry at the baseline. Incident MetS was identified annually through 2017 as having at least three of the following five components: high blood pressure, impaired fasting glucose, abdominal obesity, high triglycerides, and poor high-density lipoprotein cholesterol. We used the Cox proportional hazards models to investigate the associations between individual metals and MetS incidence. The adjusted hazard ratios (HR) (95% CI) for MetS in associations with each doubling of urinary metal concentration were 1.14 (1.08, 1.23) for arsenic, 1.14 (1.01, 1.29) for cobalt, and 1.20 (1.06, 1.37) for zinc. We further evaluated the associations between metal mixtures and MetS using the elastic net penalized Cox model and summarized the results into the environmental risk score (ERS). Arsenic, barium, cobalt, copper, nickel, antimony, thallium, and zinc had positive weights, and cadmium, cesium, mercury, molybdenum, lead, and tin had negative weights in the construction of the ERS. The adjusted HR of MetS comparing 75th vs. 25th percentiles of the ERS was 1.45 (1.13, 1.87). These findings support the view that arsenic, cobalt, zinc, as well as metal mixtures, might influence the risks of incident MetS in midlife women.

Urinary element profiles and associations with cardiometabolic diseases: A cross-sectional study across ten areas in China

BACKGROUND

Existing evidence on the associations of urinary element profiles with related food intake and cardiometabolic diseases has been limited in China.

OBJECTIVES

To examine the associations of urinary toxic metals and other elements with food intakes and with the prevalence of cardiometabolic diseases.

METHODS

Inductively coupled plasma mass spectrometry was used to measure the concentrations of cadmium (Cd), arsenic (As), nickel (Ni), aluminum (Al), copper (Cu), and 16 other elements in spot urine samples collected from 19,380 adults in 10 geographically diverse areas of China during 2013-2014. The levels of creatinine-corrected elements were used to analyze their correlations with self-reported dietary intake and associations with prevalent diabetes (n = 1862), stroke (n = 1322) and ischemic heart disease (IHD) (n = 1690).

RESULTS

Overall, the mean (SD) age was 59.2 (10.1) years with a mean BMI of 24.2 (3.5) kg/m². Of the 21 elements, the median (IQR) concentrations varied from 0.49 (0.31-0.82) μg/g creatinine for vanadium (V) to 1666 (1189-2321) mg/g creatinine for potassium (K). Nine urinary elements [Cd, As, Ni, lead (Pb), boron (B), magnesium (Mg), rubidium (Rb), strontium (Sr), and cesium (Cs); all rs > 0.20, p < 0.001] were positively correlated with staple food intake, five [Cd, As, selenium (Se), Rb, and Cs; all rs > 0.20, p < 0.001] with animal-sourced food group, and one (Cd; r = 0.21, p < 0.05) with pickled vegetable intake. For diabetes, adjusted prevalence ratios (PRs) per SD of specific element levels were 1.10 [95% confidence interval (CI): 1.03-1.18] for Cd, 1.24 (1.18-1.31) for As, 1.33 (1.27-1.39) for Ni, 1.14 (1.09-1.20) for Al, and 1.24 (1.18-1.30) for Cu. Cd was positively associated with stroke (PR per SD = 1.13, 1.04-1.23), while none of the elements were significantly associated with IHD.

CONCLUSION

In China, the urinary levels of several toxic metals were significantly associated with the consumption of specific food groups and the risk of cardiometabolic diseases including diabetes and stroke.

Individual and joint effects of metal exposure on metabolic syndrome among Chinese adults

Growing evidence suggests that metal exposure contributes to metabolic syndrome (MetS), but little is known about the effects of combined exposure to metal mixtures. This cross-sectional study included 3748 adults who were recruited from the Medical Physical Examination Center of Tongji Hospital, Wuhan, China. The levels of 21 metal(loid)s in urine were measured by inductively coupled plasma mass spectrometry. MetS was diagnosed according to National Cholesterol Education Program's Adult Treatment Panel III recommendations. Multivariate logistic regression model was uesd to explore the effects of single-metal and multi-metal exposures. The elastic net (ENET) regularization with an environmental risk score (ERS) was performed to estimate the joint effects of exposure to metal mixtures. A total of 636 participants (17%) were diagnosed with MetS. In single metal models, MetS was positively associated with zinc (Zn) and negatively associated with nickel (Ni). In multiple metal models, the associations remained significant after adjusting for the other metals. In the joint association analysis, the ENET models selected Zn as the strongest predictor of MetS. Compared to the lowest quartile, the highest quartile of ERS was associated with an elevated risk of MetS (OR = 3.72; 95% CI: 2.77, 5.91; P-trend < 0.001). Overall, we identified that the combined effect of multiple metals was related to an increased MetS risk, with Zn being the major contributor. These findings need further validation in prospective 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 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.

Mitochondria damage and ferroptosis involved in Ni-induced hepatotoxicity in mice

Nickel (Ni) is an environmental toxicant that can cause toxic damage to humans and animals. Although the hepatotoxicity of Ni has been confirmed, its precise mechanism is still unclear. In this study, the results showed that nickel chloride (NiCl₂)-treatment could induce mice hepatotoxicity including hepatic histopathological alterations and up-regulation of serum AST and ALT. According to the results, NiCl₂ increased malondialdehyde (MDA) production while reducing total antioxidant capacity (T-AOC) activity and glutathione (GSH) content. Additionally, NiCl₂ induced mitochondrial damage which was featured by increase in mitochondrial ROS (mt-ROS) and mitochondrial membrane potential (MMP) depolarization. The mitochondrial respiratory chain complexes I-IV and ATP content were decreased in the liver of NiCl₂-treated mice. Meanwhile, NiCl₂ caused hepatic ferroptosis accompanied by increased iron content in the liver and up-regulation of cyclooxygenase 2 (COX-2) protein and mRNA expression levels, down-regulation of glutathione eroxidase 4 (GPX4), ferritin heavy chain 1 (FTH1) and nuclear receptor coactivator 4 (NCOA4) protein and mRNA expression levels. Altogether, the above mentioned results indicate that NiCl₂ treatment may induce hepatic damage through mitochondrial damage and ferroptosis.

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.

Environmental pollution and diabetes mellitus

Diabetes mellitus (DM) is a chromic metabolic disease that affects a large segment of the population worldwide. Physical inactivity, poor nutrition, and genetic predisposition are main risk factors for disease development. In the last decade, it was clear to the scientific community that DM development is linked to a novel disease inducer that was later defined as diabetogenic factors of pollution and endocrine disrupting agents. Environmental pollution is exponentially increasing in uncontrolled manner in several countries. Environmental pollutants are of diverse nature and toxicities, including polyaromatic hydrocarbons (PAHs), pesticides, and heavy metals. In the current review, we shed light on the impact of each class of these pollutants and the underlined molecular mechanism of diabetes induction and biological toxicities. Finally, a brief overview about the connection between coronavirus disease 2019 and diabetes pandemics is presented.

Research progress on the effects of nickel on hormone secretion in the endocrine axis and on target organs

BACKGROUND

Nickel, as one of the most abundant elements in the earth's crust, plays many roles in human reproduction and life. It is an essential trace element for the human body, but can be harmful in excess amounts. Nickel has a significant impact on endocrine hormones in humans and animals, potentially causing abnormal secretions and changing the structure and function of endocrine organs. This article systematically reviews the effects of nickel on hormone secretion and target organs in the endocrine system and identifies areas of insufficient research.

METHODS

All data in this article were extracted from peer-reviewed articles. The PubMed, SciFinder, Google Scholar, Web of Science, and China National Knowledge Infrastructure databases were searched for relevant articles. Data on nickel's effect on endocrine system hormones and target organs were retrieved, and manually sorted prior to inclusion in this review.

RESULTS

Nickel acts on the endocrine system and affects the release and regulation of endocrine hormones. Disorders of endocrine hormones may lead to retardation of human growth and mental development, disturbance of water and salt regulation, and even a decline in reproductive ability. Nickel affects the hypothalamus and pituitary gland by regulating organs upstream of the endocrine axis; it can cause abnormal secretion of pituitary hormones, which affects target organs of the endocrine axis, resulting in dysfunction therein and abnormal secretion of related hormones. Nickel also damages target organs, mainly by inducing apoptosis, which triggers oxidative stress, cell autophagy, free radical release, and DNA damage. However, there are few studies on the endocrine axis, and some of the data are contradictory. Nevertheless, it is clear that nickel affects the endocrine system.

CONCLUSIONS

Nickel can damage organs in the endocrine system, such as the hypothalamus and pituitary. It also affects the secretion of hormones and damages the target organs of these hormones; this can result in endocrine system dysfunction. However, the results have been equivocal and further research is needed.

Potential Health Risks of Macro- and Microelements in Commercial Medicinal Plants Used to Treatment of Diabetes

Information on the content of medicinal plants used in the treatment of diabetes is scarce in the literature. The objectives of this study were to determine the levels of macroelements and microelements in three different medicinal plant species including the dry samples and teas from Bauhinia forficata, Eleusine Indica, and Orthosiphon stamineus and assess the human health risks of ingestion of the tea. The content of the dry samples and teas was obtained using the technique of inductively coupled plasma optical emission spectrometry (ICP OES) after microwave digestion procedure. The hazard quotient (HQ) method was used to access the human health risks posed by heavy metal through tea consumption. The results revealed the presence of K, Mg, Na, P, Al, Fe, Zn, Mn, Cu, Ni, and Se in dry samples and plant teas. The dry plants have high concentration of K and P. All dry plants contain Mg, Na, Al, Fe, Mn, Ni, Zn, and Cu above the limit permissible level set by the World Health Organization (WHO). All the hazard index (HI) values in plant teas were found to be within safe limits for human consumption (HI < 1). The plants may have possible action benefits when used in popular medicine. However, the ingestion through capsules prepared by enclosing a plant powder or teas can be harmful to the health of diabetics. The prescription of this plant for the treatment of diabetes should be treated with caution.

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.

A Positive Relationship between Exposure to Heavy Metals and Development of Chronic Diseases: A Case Study from Chile

Chile is a mining country, where waste mining is frequently found in the vicinity of inhabited areas. To explore the association between metal exposure and alterations in glucose metabolism, inflammatory status, and oxidative stress in individuals with chronic exposure to metals, a cross-sectional study was performed with 25 volunteers, between 45–65 years old. Inductive coupled plasma mass spectrometry (ICP-MS) was used to measure urinary levels of total arsenic (As) and its metabolites, cooper, nickel, chromium, and lead. Lipid profile, glucose, and insulin were measured in blood, as well as inflammation (interleukin-6, IL-6) and oxidative stress (8-hydroxy-2′deoxyguanosine, 8-OHdG) markers. Increased levels of Low-density lipoprotein, high-density lipoproteins, cholesterol and 8-OHdG, and the index for homeostasis model assessment—insulin resistance (HOMA-IR) were observed in 72%, 60%, and 56% of the volunteers, respectively. Blood-glucose levels were correlated with dimethylarsinic acid (DMA) (R² = 0.47, p = 0.019), inorganic As (As_i) (R² = 0.40, p = 0.012), and Ni (R² = 0.56; p = 0.044). The models with these compounds explained 72% of the glycemia variability (β_DMA = −6.47; β_Asi = 6.68; β_Ni = 6.87). Ni showed a significantly influence on IL-6 variability (β = 0.85: R² = 0.36). Changes in glycemia could be related to exposure to low levels of As_i and Ni, representing risk factors for metabolic diseases. Body mass index would confuse the relation between IL-6 and Ni levels, probably due to known chronic inflammation present in obese people.

Elemental Metabolomics for Prediction of Term Gestational Outcomes Utilising 18-Week Maternal Plasma and Urine Samples

A normal pregnancy is essential to establishing a healthy start to life. Complications during have been associated with adverse perinatal outcomes and lifelong health problems. The ability to identify risk factors associated with pregnancy complications early in gestation is vitally important for preventing negative foetal outcomes. Maternal nutrition has been long considered vital to a healthy pregnancy, with micronutrients and trace elements heavily implicated in maternofoetal metabolism. This study proposed the use of elemental metabolomics to study multiple elements at 18 weeks gestation from blood plasma and urine to construct models that could predict outcomes such as small for gestational age (SGA) (n = 10), low placental weight (n = 18), and preterm birth (n = 13) from control samples (n = 87). Samples collected from the Lyell McEwin Hospital in Adelaide, South Australia, were measured for 27 plasma elements and 37 urine elements by inductively coupled plasma mass spectrometry. Exploratory analysis indicated an average selenium concentration 20 μg/L lower than established reference ranges across all groups, low zinc in preterm (0.64 μg/L, reference range 0.66-1.10 μg/L), and higher iodine in preterm and SGA gestations (preterm 102 μg/L, SGA 111 μg/L, reference range 40-92 μg/L). Using random forest algorithms with receiver operating characteristic curves, low placental weight was predicted with 86.7% accuracy using plasma, 78.6% prediction for SGA with urine, and 73.5% determination of preterm pregnancies. This study indicates that elemental metabolomic modelling could provide a means of early detection of at-risk pregnancies allowing for more targeted monitoring of mothers, with potential for early intervention strategies to be developed.

Disease Ionomics: Understanding the Role of Ions in Complex Disease

Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases.

Update of the risk assessment of nickel in food and drinking water

The European Commission asked EFSA to update its previous Opinion on nickel in food and drinking water, taking into account new occurrence data, the updated benchmark dose (BMD) Guidance and newly available scientific information. More than 47,000 analytical results on the occurrence of nickel were used for calculating chronic and acute dietary exposure. An increased incidence of post-implantation loss in rats was identified as the critical effect for the risk characterisation of chronic oral exposure and a BMDL 10 of 1.3 mg Ni/kg body weight (bw) per day was selected as the reference point for the establishment of a tolerable daily intake (TDI) of 13 μg/kg bw. Eczematous flare-up reactions in the skin elicited in nickel-sensitised humans, a condition known as systemic contact dermatitis, was identified as the critical effect for the risk characterisation of acute oral exposure. A BMDL could not be derived, and therefore, the lowest-observed-adverse-effect-level of 4.3 μg Ni/kg bw was selected as the reference point. The margin of exposure (MOE) approach was applied and an MOE of 30 or higher was considered as being indicative of a low health concern. The mean lower bound (LB)/upper bound (UB) chronic dietary exposure was below or at the level of the TDI. The 95th percentile LB/UB chronic dietary exposure was below the TDI in adolescents and in all adult age groups, but generally exceeded the TDI in toddlers and in other children, as well as in infants in some surveys. This may raise a health concern in these young age groups. The MOE values for the mean UB acute dietary exposure and for the 95th percentile UB raises a health concern for nickel-sensitised individuals. The MOE values for an acute scenario regarding consumption of a glass of water on an empty stomach do not raise a health concern.

Ethanol extract of Nigella sativa has antioxidant and ameliorative effect against nickel chloride-induced hepato-renal injury in rats

Background

Nickel exposure causes hepato-renal toxicity via oxidative stress. Medicinal plants with antioxidants properties are being explored as treatment options. In this study, the effect of ethanol extract of Nigella sativa (ENS) on nickel chloride (NiCl2)-induced hepato-renal damage was evaluated by monitoring biochemical and oxidative stress markers. Additionally, the antioxidant capacity and phytochemical constituents of ENS were quantified using HPLC and GC-MS.

Result

NiCl2 significantly increased (p < 0.05) aspartate aminotransferase, creatinine, sodium ion, chloride ion and malondialdehyde levels, while antioxidant enzymes were decreased in the organs except for kidney glutathione-S-transferase when compared to the control. However, ENS exerted inhibitory effect against NiCl2 toxicity in both organs by reversing the biomarkers towards control levels. ENS has a high antioxidant capacity and is rich in antioxidants including gallic acid, quercetin, eucalyptol and levomenthol that may have accounted for the improvement of hepato-renal health in co-exposed rats.

Conclusion

Our result suggests that amelioration of nickel chloride-induced hepato-renal pathology by ethanol extract of Nigella sativa was related to its antioxidant properties. Therefore, Nigella sativa could be valuable in the management of nickel-induced toxicity.

Urinary metals and incident diabetes in midlife women: Study of Women's Health Across the Nation (SWAN)

INTRODUCTION

Environmental exposure to metals may play a role in the pathogenesis of diabetes; however, evidence from human studies is limited. We prospectively evaluated the associations of 20 urinary metal concentrations and their mixtures with incident diabetes in the Study of Women's Health Across the Nation, a multisite, multiethnic cohort study of midlife women.

RESEARCH DESIGN AND METHODS

The sample included 1237 white, black, Chinese and Japanese-American women, aged 45-56 years, free of diabetes at baseline (1999-2000) who were followed through 2016. Concentrations of 20 metals (arsenic, barium, beryllium, cadmium, cobalt, chromium, cesium, copper, mercury, manganese, molybdenum, nickel, lead, antimony, tin, thallium, uranium, vanadium, tungsten and zinc) were measured in urine specimens at baseline. Incident diabetes was identified annually by fasting glucose ≥126 mg/dL, self-reported doctor-diagnosed diabetes, or self-reported use of antidiabetic medications. A non-parametric clustering method, k-means clustering, was used to identify subgroups with different exposure patterns to metal mixtures.

RESULTS

After multivariable adjustment, the HR (95% CI) for diabetes associated with each doubling increase in urinary metal concentrations was 1.19 (1.10 to 1.30) for arsenic and 1.20 (1.05 to 1.37) for lead, in Cox proportional hazards models after controlling for multiple comparisons. A doubling in urinary excretion of zinc was associated with higher risk of diabetes (adjusted HR 1.31, 95% CI 1.11 to 1.53). Two distinct exposure patterns to metal mixtures-'high' versus 'low'-were identified. Participants assigned to the 'high' pattern had higher overall concentrations of all metals compared with those classified into the 'low' pattern. Adjusted HR for diabetes associated with 'high' pattern compared with 'low' was 1.42 (1.08 to 1.87).

CONCLUSIONS

Higher urinary concentrations of arsenic and lead, increased urinary excretion of zinc, as well as higher overall exposure to metal mixtures were associated with elevated risk of diabetes. Future studies should further investigate the underlying mechanisms.

Elemental metabolomics in human cord blood: Method validation and trace element quantification

BACKGROUND

Trace elements are an essential requirement for human health and development and changes in trace element status have been associated with pregnancy complications such as gestational diabetes mellitus (GDM), pre-eclampsia (PE), fetal growth restriction (FGR), and preterm birth. Elemental metabolomics, which involves the simultaneous quantification and characterisation of multiple elements, could provide important insights into these gestational disorders.

METHODS

This study used an Agilent 7900 inductively coupled plasma mass spectrometer (ICP-MS) to simultaneously measure 68 elements, in 166 placental cord blood samples collected from women with various pregnancy complications (control, hypertensive, PE, GDM, FGR, pre-term, and post-term birth).

RESULTS

There were single element differences across gestational outcomes for elements Mg, P, Cr, Ni, Sr, Mo, I, Au, Pb, and U. Hypertensive and post-term pregnancies were significantly higher in Ni concentrations when compared to controls (control = 2.74 μg/L, hypertensive = 6.72 μg/L, post-term = 7.93 μg/L, p < 0.05), iodine concentration was significantly higher in post-term pregnancies (p < 0.05), and Pb concentrations were the lowest in pre-term pregnancies (pre-term = 2.79 μg/L, control = 4.68 μg/L, PE = 5.32 μg/L, GDM = 8.27 μg/L, p < 0.01). Further analysis was conducted using receiver operating characteristic (ROC) curves for differentiating pregnancy groups. The ratio of Sn/Pb showed the best diagnostic power in discriminating between control and pre-term birth with area under the curve (AUC) 0.86. When comparing control and post-term birth, Mg/Cr (AUC = 0.84), and Cr (AUC = 0.83) had the best diagnostic powers. In pre-term and post-term comparisons Ba was the best single element (81.5%), and P/Cu provided the best ratio (91.7%).

CONCLUSIONS

This study has shown that analysis of multiple elements can enable differentiation between fetal cord blood samples from control, hypertensive, PE, GDM, FGR, pre and post-term pregnancies. This data highlights the power of elemental metabolomics and provides a basis for future gestational studies.

Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study

BACKGROUND

A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.

OBJECTIVES

This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.

METHODS

The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24-28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).

RESULTS

A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.

CONCLUSIONS

To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture.

Association between exposure to arsenic, nickel, cadmium, selenium, and zinc and fasting blood glucose levels

Associations between single metal and fasting blood glucose (FBG) levels have been reported in previous studies. However, the association between multi-metals exposure and FBG level are little known. To assess the joints of arsenic (As), nickel (Ni), cadmium (Cd), selenium (Se), and zinc (Zn) co-exposure on FBG levels, Bayesian kernel machine regression (BKMR) statistical method was used to estimate the potential joint associations between As, Ni, Cd, Se, and Zn co-exposure and FBG levels among 1478 community-based Chinese adults from two counties, Shimen (n = 696) and Huayuan (n = 782), with different exposure profiles in Hunan province of China. The metals levels were measured in spot urine (As, Ni, and Cd) and plasma (Se and Zn) using inductively coupled plasma-mass spectrometry, respectively. The exposure levels of all the five metals were significantly higher in Shimen area (median: As = 57.76 μg/L, Cd = 2.75 μg/L, Ni = 2.73 μg/L, Se = 112.67 μg/L, Zn = 905.68 μg/L) than those in Huayuan area (As = 41.14 μg/L, Cd = 2.22 μg/L, Ni = 1.88 μg/L, Se = 65.59 μg/L, Zn = 819.18 μg/L). The BKMR analyses showed a significantly positive over-all effect of the five metals on FBG levels when metals concentrations were all above the 50th percentile while a statistically negative over-all effect when metals concentrations were all under the 50th percentile in Shimen area. However, a totally opposite over-all effect of the mixture of the five metals on FBG levels was found in Huayuan area. BKMR also revealed a non-linear exposure-effect of Zn on FBG levels in Huayuan area. In addition, interaction effects of As and Se on FBG level were observed. The relationship between single or combined metals exposure and FBG was different against different exposure profiles. Potential interaction effects of As and Se on FBG levels may exist.

Multiple metal concentrations and gestational diabetes mellitus in Taiyuan, China

BACKGROUND

The association between multiple metal concentrations and gestational diabetes mellitus (GDM) is poorly understood.

METHODS

A total of 776 women with GDM and an equal number of controls were included in the study. Concentrations of metals in participants' blood (nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), thallium (Tl), mercury (Hg), lead (Pb)) were measured using inductively coupled plasma-mass. We used unconditional logistical regression models to estimate the associations between metals and GDM. We also employed weighted quantile sum (WQS) regression and principal components analysis (PCA) to examine metal mixtures in relation to GDM.

RESULTS

An increased risk of GDM was associated with As (OR = 1.49, 95% CI: 1.11, 2.01 for the 2nd tertile vs. the 1st tertile) and Hg (OR = 1.43, 95% CI: 1.09, 1.88 for the 3rd tertile vs. the 1st tertile). In WQS analysis, the WQS index was significantly associated with GDM (OR = 1.20, 95% CI: 1.02, 1.41). The major contributor to the metal mixture index was Hg (69.2%), followed by Pb (12.8%), and As (11.3%). Based on PCA, the second principal component, which was characterized by Hg, Ni, and Pb, was associated with an increased risk of GDM (OR = 1.46, 95% CI: 1.02, 2.08 for the highest quartile vs. the lowest quartile).

CONCLUSIONS

Our study results suggest that high metal levels are associated with an increased risk of GDM, and this increased risk is mainly driven by Hg and, to a lesser extent, by Ni, Pb, and As.

Occupational exposure to heavy metals, alcohol intake, and risk of type 2 diabetes and prediabetes among Chinese male workers

OBJECTIVE

Both exposure to heavy metals and alcohol intake have been related to the risk of type 2 diabetes (T2D). In this study, we aimed to assess the potential interactions between metal exposure and alcohol intake on the risk of T2D and prediabetes in a cohort of Chinese male workers.

METHODS

We conducted a cross-sectional analysis of 26,008 Chinese male workers in an occupational cohort study from 2011 to 2013. We assessed metal exposure and alcohol consumption at baseline in these workers who were aged ≥20 years. Based on occupations which were categorized according to measured urine metal levels, multiple logistic regression analyses were used to evaluate the independent and joint effects of metal and alcohol exposure on the risk of T2D and prediabetes.

RESULTS

Risks of T2D (P trend = 0.001) and prediabetes (P trend = 0.001) were significantly elevated with increasing number of standard drinks per week, years of drinking, and lifetime alcohol consumption. An adjusted odds ratio (OR) of 6.1 (95% confidence interval [CI]: 4.8-7.8) was observed for the smelting/refining workers (highest metal exposure levels) who had the highest lifetime alcohol consumption (>873 kg) (P interaction = 0.018), whereas no statistically significant joint effect was found for prediabetes (P interaction = 0.515).

CONCLUSIONS

Both exposures to metal and heavy alcohol intake were associated with the risk of diabetes in this large cohort of male workers. There was a strong interaction between these two exposures in affecting diabetes risk that needs to be confirmed in future studies.

Urinary ionomic analysis reveals new relationship between minerals and longevity in a Han Chinese population

Human longevity involves genetic, nutritional, environmental and many other factors playing a key role in healthy aging. Previous studies have shown that mineral metabolism and homeostasis are associated with lifespan extension. However, the majority of them have focused on a limited number of elements and ignored the complex relationship between them. In this study, we carried out a network-based approach to investigate the urinary ionome of nonagenarians and centenarians (longevity group) when compared with their biologically unrelated and younger family members (control group) from a Han Chinese population. Several differentially changed elements were identified, almost all of which showed an elevated level in the longevity group. Correlation analysis of the ionome revealed significant element-element interactions in each group. We then divided each group into distinct subgroups according to age ranges, and built the elemental correlation network for each of them. Significant elemental correlations and correlation changes involving all examined elements were identified within or between different subgroups, implying a highly dynamic and complex crosstalk among the elements during human life. Finally, more similar elemental patterns were observed between extremely old and middle-aged people. Overall, our data reveal new relationship between urinary minerals and human longevity, which may extend our understanding of the mechanism of healthy aging.

Elemental Metabolomics and Pregnancy Outcomes

Trace elements are important for human health and development. The body requires specific micronutrients to function, with aberrant changes associated with a variety of negative health outcomes. Despite this evidence, the status and function of micronutrients during pregnancy are relatively unknown and more information is required to ensure that women receive optimal intakes for foetal development. Changes in trace element status have been associated with pregnancy complications such as gestational diabetes mellitus (GDM), pre-eclampsia (PE), intrauterine growth restriction (IUGR), and preterm birth. Measuring micronutrients with methodologies such as elemental metabolomics, which involves the simultaneous quantification and characterisation of multiple elements, could provide insight into gestational disorders. Identifying unique and subtle micronutrient changes may highlight associated proteins that are affected underpinning the pathophysiology of these complications, leading to new means of disease diagnosis. This review will provide a comprehensive summary of micronutrient status during pregnancy, and their associations with gestational disorders. Furthermore, it will also comment on the potential use of elemental metabolomics as a technique for disease characterisation and prediction.

Association between prenatal nickel exposure and preterm low birth weight: possible effect of selenium

There is a proposed link between prenatal nickel (Ni) exposure and preterm low birth weight (PLBW); however, this association remains unclear. Selenium (Se) may modify this relationship by protecting against Ni toxicity. Concentrations of Ni and Se were measured in urine samples collected from 408 pregnant women (102 PLBW cases and 306 matched controls) in China. Conditional logistic regression was utilized to explore the association between Ni levels and PLBW, as well as the effect modification by Se on this association. A significant association was observed between higher maternal urinary Ni levels and risk of PLBW [adjusted odds ratio (OR) = 2.80 (95% confidence interval (CI): 1.44, 5.44) for the highest tertile], and this association was more apparent among female infants than that among male infants. Further analyses showed that mothers with high urinary Ni and low urinary Se levels had a significantly increased risk for PLBW [adjusted OR = 2.87 (95% CI: 1.09, 7.56)] compared with the mothers with low urinary Ni and high urinary Se levels. Our study indicates that prenatal exposure to Ni was a risk factor for PLBW. Se might provide protection against the toxicity of Ni.

Oxidative DNA damage mediates the association between urinary metals and prevalence of type 2 diabetes mellitus in Chinese adults

Previous publications have indicated that some metals are associated with an increased prevalence of type 2 diabetes mellitus (T2DM); however, the mechanisms remain largely unknown. This study aimed to quantify the associations of oxidative DNA damage with urinary metals and prevalence of T2DM among the general population, and further to assess the role of oxidative DNA damage in mediating the association of urinary metals with prevalence of T2DM. Diagnoses of T2DM were performed clinically or by measuring fasting levels of plasma glucose ≥7.0mmol/L. Concentrations of urinary metals and 8-hydroxy-2'-deoxyguanosine (8-OHdG) in 2127 participants were measured using inductively coupled plasma-mass spectrometry and high-performance liquid chromatography. Relationships among urinary metals, 8-OHdG (a biomarker for oxidative DNA damage), and prevalence of T2DM were analyzed using mediation analysis. After adjusting for covariates, we found that the log-transformed levels of urinary copper, arsenic, selenium, molybdenum, and antimony were positively associated with prevalence of T2DM. Urinary 8-OHdG was not only positively correlated with copper, arsenic, selenium, and antimony in an upwardly trending, dose-responsive manner but was also positively associated with prevalence of T2DM (odds ratio (OR): 1.95; 95% CI: 1.17-3.24). Mediation analysis estimated that urinary 8-OHdG mediated 13.22% and 8.84% of associations between prevalence of T2DM and concentrations of urinary arsenic and antimony, respectively (all P value<0.05). Our findings suggested that urinary arsenic and antimony concentrations were associated with an increased prevalence of T2DM by a mechanism partly involving oxidative DNA damage.

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

The long-term associations between multiple metals and incident diabetes are uncertain. We aimed to examine the relationship between plasma concentrations of 23 metals and the incidence of type 2 diabetes among Chinese senior adults. We quantified fasting plasma concentrations of 23 metals by inductively coupled plasma mass spectrometry among 1039 incident diabetes cases and 1039 controls (age and sex matched) nested in a prospective study, the Dongfeng-Tongji cohort. Both cases and controls were free of diabetes at baseline (2008-2010), incident diabetes were identified using the following criteria: fasting glucose ≥ 7.0 mmoL/l; or hemoglobin A1c (HbA1c) ≥ 6.5%; or self-reported physician diagnosis of diabetes or use of anti-diabetic medication during the follow-up visits in 2013. In the conditional logistic regression models, the multivariable adjusted ORs (95% CIs) of diabetes across quartiles (Q1-Q4) of metal concentrations were as follows: titanium, 1.00, 0.92, 1.31, 1.38 (1.00-1.91, P_trend = 0.011); selenium, 1.00, 1.08, 1.45, 1.27 (0.93-1.74, P_trend = 0.05); and antimony, 1.00, 0.79, 0.77, 0.60 (0.44-0.83, P_trend = 0.002). Arsenic was significantly associated with diabetes in the crude model (ORs comparing extreme quartiles 1.30; 1.02-1.65; P_trend = 0.006), but was not significant after adjustment for socio-demographic factors. No significant associations were found for other metals. In conclusion, titanium and selenium were positively while antimony was negatively associated with incident diabetes.

The role of pollutants in type 2 diabetes mellitus (T2DM) and their prospective impact on phytomedicinal treatment strategies

Type 2 diabetes mellitus (T2DM) is the most common form of diabetes and it is characterized by high blood sugar and abnormal sera lipid levels. Although the specific reasons for the development of these abnormalities are still not well understood, traditionally, genetic and lifestyle behavior have been reported as the leading causes of this disease. In the last three decades, the number of diabetic patients has drastically increased worldwide, with current statistics suggesting the number is to double in the next two decades. To combat this incurable ailment, orthodox medicines, to which economically disadvantaged patients have minimal access to, have been used. Thus, a considerable amalgamation of medicinal plants has recently been proven to possess therapeutic capabilities to manage T2DM, and this has prompted studies primarily focusing on the healing aspect of these plants, and ultimately, their commercialization. Hence, this review aims to highlight the potential threat of pollutants, i.e., polyfluoroalkyl compounds (PFCs), endocrine disrupting chemicals (EDCs) and heavy metals, to medicinal plants, and their prospective impact on the phytomedicinal therapy strategies for T2DM. It is further suggested that auxiliary research be undertaken to better comprehend the factors that influence the uptake of these compounds by these plants. This should include a comprehensive risk assessment of phytomedicinal products destined for the treatment of T2DM. Regulations that control the use of PFC-precursors in certain developing countries are also long overdue.

Trace Elements and Healthcare: A Bioinformatics Perspective

Biological trace elements are essential for human health. Imbalance in trace element metabolism and homeostasis may play an important role in a variety of diseases and disorders. While the majority of previous researches focused on experimental verification of genes involved in trace element metabolism and those encoding trace element-dependent proteins, bioinformatics study on trace elements is relatively rare and still at the starting stage. This chapter offers an overview of recent progress in bioinformatics analyses of trace element utilization, metabolism, and function, especially comparative genomics of several important metals. The relationship between individual elements and several diseases based on recent large-scale systematic studies such as genome-wide association studies and case-control studies is discussed. Lastly, developments of ionomics and its recent application in human health are also introduced.

Exposure to perchlorate, nitrate and thiocyanate, and prevalence of diabetes mellitus

Background

It is known that perchlorate, nitrate and thiocyanate have the property of inhibiting sodium iodide symporter. Animal studies have suggested that these compounds, especially perchlorate, might also interfere with insulin secretion. However, the association between their exposure and diabetes risk is largely unknown in humans.

Methods

Among 11 443 participants (mean age 42.3 years) from the National Health and Nutritional Examination Survey 2001-14, urinary perchlorate, nitrate and thiocyanate were measured by using ion chromatography coupled with electrospray tandem mass spectrometry. Diabetes was defined as self-reported doctor diagnosis, use of oral hypoglycaemic medication or insulin, fasting plasma glucose ≥ 126 mg/dl or glycated haemoglobin A1c (HbA1c) ≥ 6.5%.

Results

The median (interquartile range) levels of urinary perchlorate, nitrate and thiocyanate were 3.32 (1.84, 5.70) μg/l, 46.4 (27.9, 72.0) mg/l and 1.23 (0.59, 2.78) mg/l, respectively. Higher levels of urinary perchlorate were associated with elevated levels of fasting glucose, HbA1c, insulin and homeostatic model assessment of insulin resistance (all Ptrend < 0.001). After multivariate adjustment including urinary creatinine, smoking status and body mass index (BMI), higher urinary perchlorate, but not nitrate or thiocyanate, was associated with an increased prevalence of diabetes mellitus. Comparing extreme quintiles, the odds ratio (95% confidence interval) of diabetes was 1.53 (1.21, 1.93; Ptrend < 0.001) for perchlorate, 1.01 (0.77, 1.32; Ptrend = 0.44) for nitrate and 0.98 (0.73, 1.31; Ptrend = 0.64) for thiocyanate. When urinary perchlorate, nitrate and thiocyanate were further mutually adjusted, the results did not materially change. Similar results were observed when analyses were stratified by smoking status, as well as by age, gender, kidney function and BMI.

Conclusions

Higher urinary perchlorate levels are associated with an increased prevalence of diabetes mellitus, independent of traditional risk factors. Future prospective studies are needed to confirm these findings.

Dose-response analysis of environmental exposure to multiple metals and their joint effects with fasting plasma glucose among occupational workers

OBJECTIVES

Environmental exposure to metals may adversely affect cardiometabolic health. However, little data are available directly evaluating the roles of metal exposure in blood glucose of which dysfunction has been linked to diabetes. We aimed to evaluate the dose-response associations between fasting plasma glucose (FPG) and multiple urinary metals including nickel, cobalt, copper, zinc, and arsenic, as well as to examine their joint effects among occupational workers.

METHODS

We performed a population-based study of 464 workers in an ongoing occupational cohort study in China. Both spline and categorical analyses were used to evaluate the dose-response relationship between urinary metals levels and FPG.

RESULTS

We observed the J-shaped non-linear relationships between urinary nickel (P non-linearity = 0.03) and zinc (P non-linearity < 0.01) with FPG by spline analyses. A negative linear relationship between urinary cobalt and FPG (P for nonlinearity = 0.06) was found, but no statistically significant associations between urinary copper and arsenic with FPG. In linear regression analyses, the regression coefficient for log-transferred FPG was 0.017 (95% confidence intervals [CI]: -0.003, 0.038) in the 4th quartile concentration of urinary nickel, compared with 1st quartile. The joint effects between urinary nickel and cobalt with FPG were also detected (P for interaction = 0.04).

CONCLUSIONS

Multiple urinary metals, particularly nickel, zinc and cobalt, were associated with blood glucose among Chinese metal exposed workers, supporting the notion that metal exposure may play a critical role in diabetes development.

Hair biomonitoring and health status of a general population exposed to Nickel

An epidemiological cross-sectional study was conducted in a Greek population, being orally exposed to Ni via food consumption, in order to investigate possible health effects and to evaluate hair Ni concentration as a biomarker of exposure. The study population consisted of 139 men and 155 women, aged 25-69. Socio-demographics, lifestyle, dietary habits, occupational and medical history data were recorded through a personal interview. Hematological and biochemical examinations were conducted in blood specimens. Metals - Ni, Cr, Cd, Pb, Hg, Cu and Zn - were determined in hair samples. Women were characterized by higher Ni and Cu hair concentrations, while men by higher Cr and Hg. Factors affecting hair metal concentrations were identified to be dietary habits, consumption of local crops, occupation and smoking. Hair element content in the study population was comparable to the "reference ranges" reported in Europe, except for Ni, found higher in a fraction of our population. Men in the upper quartile of hair Ni distribution are at higher risk for abnormal high cholesterol, LDL, albumin and calcium, with odds ratios (OR) varying between 3.5 and 6.2. Accordingly, high hair Ni content in women is associated with abnormal glucose (OR=3.9), triglycerides (OR=3.1) and low abnormal sodium (OR=4.3). The study provides evidence of the suitability of hair analysis in assessing environmental exposure to Ni and supports the use of hair Ni content as a valuable and relatively inexpensive tool of biomonitoring, to identify people at risk for certain biochemical alterations.

Survey of urinary nickel in peritoneal dialysis patients

This study surveyed urinary nickel concentrations in peritoneal dialysis (PD) patients, and analyzed the association of urinary nickel concentrations with clinical outcomes and inflammatory biomarkers. In total, 50 PD patients and 50 healthy controls were recruited for this study. All participants were examined for the presence of toxic trace elements (antimony, arsenic, bismuth, cadmium, copper, manganese, mercury, nickel, lead, tellurium, thallium and zinc) in their urine by using inductively coupled plasma mass spectrometry (ICP-MS). It was found that PD patients demonstrated higher urinary nickel concentrations than healthy controls (6.1±3.5 versus 2.8±1.4 μg/L, P<0.001). There were 24 (48.0%) PD patients with normal urinary nickel concentrations, and 26 (52.0%) PD patients with high urinary nickel concentrations. The PD patients with high urinary nickel concentrations demonstrated higher log serum levels of high sensitivity C-reactive protein (0.4±0.5 versus 0.1±0.5 mg/L, P=0.046) than patients with normal urinary nickel concentrations. Furthermore, patients with high urinary nickel concentrations exhibited higher levels of cadmium (1.3±0.9 versus 0.6±0.5 μg/L, P<0.001), copper (7.7±5.7 versus 3.3±1.4 μg/L, P<0.001) and manganese (0.9±1.1 versus 0.4±0.4 μg/L, P=0.023) than patients with normal urinary nickel concentrations. Nevertheless, there were no significant differences in the clinical outcomes between PD patients with high and normal urinary nickel concentrations (P>0.05). Thus, it is concluded that approximately half of the patients undergoing PD had elevated urinary nickel levels, and these patients also had elevated serum levels of high sensitivity C-reactive protein. Nevertheless, no other real correlations were discovered including no impact on patient outcome. Further studies are warranted.

Occupational metal exposures, smoking and risk of diabetes and prediabetes

BACKGROUND

Metal exposure and tobacco smoking have been independently associated with diabetes, but no study has been conducted to investigate the interaction between them on the risk of diabetes.

AIMS

To investigate the effect of occupational exposure to metals, and potential effect modification by smoking, on the risk of diabetes and prediabetes in a cohort of Chinese male workers.

METHODS

We assessed metal exposure and tobacco smoking at baseline in the Jinchang Cohort of male workers. We used Poisson regression analyses to estimate the interaction between smoking and metal exposures based on occupations, which we grouped according to the measured urinary metal levels.

RESULTS

Among the 26008 study subjects, compared with non-smokers, the adjusted prevalence ratio (PR) for diabetes was 1.8 [95% confidence interval (CI) 1.3-2.4] for smokers of >40 pack-years. The adjusted PRs were 1.2 (95% CI 1.1-1.4) among mining/production workers and 2.7 (95% CI 2.4-3.0) among smelting/refining workers, both compared with office workers. There was significant effect modification under the additive model between smoking and metal exposure on the prevalence of diabetes (Pinteraction = 0.001), with an adjusted PR of 3.6 (95% CI 2.4-5.4) for those with >40 pack-years of smoking who had the highest metal exposures, whereas no significant interaction was observed for prediabetes.

CONCLUSIONS

Both exposure to metals and heavy smoking were associated with an increased prevalence of diabetes in this large cohort of male workers. There was also strong interaction between these two exposures in affecting diabetes risk that should be confirmed in future studies.