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

The Relationship Between Metal Exposure and HPV Infection: Evidence from Explainable Machine Learning Methods

HPV is a ubiquitous pathogen implicated in cervical and other cancers. Although vaccines are available, they do not encompass all subtypes. Meanwhile, metal exposure may elevate the risk of HPV infection and amplify its carcinogenic potential, but studies to further elucidate this relationship are insufficient. This study entailed a cross-sectional analysis utilizing data from the National Health and Nutrition Examination Survey (NHANES) 2007-2016. The study sample comprised 2765 women. Multivariate logistic regression was employed to examine the association between single metal exposure and HPV infection, weighted quantile sum (WQS) regression was utilized for assessing the mixed metal exposure effect, and the XGBoost + SHapley Additive exPlanations (SHAP) to evaluate the contribution of metal exposure in HPV infection. Multivariate logistic regression analysis indicated that elevated Co concentration was inversely associated with HPV infection (OR 0.891; 95% CI 0.814-0.975), while elevated Pb concentration correlated with an increased HPV infection (OR 1.176; 95% CI 1.074-1.287). Regression analysis of the WQS for mixed metal exposure suggested that the WQS index was potentially linked to an increased likelihood of HPV infection in the positive direction (OR 1.249; 95% CI 1.052-1.482), with no significant association observed in the negative direction (OR 0.852; 95% CI 0.713-1.017). SHAP analysis prioritized the importance of characteristics: number of sexual partners, marital status, poverty-to-income ratio (PIR), Co, Pb, and alcohol consumption. Exposure to Pb was associated with an increase in the incidence of HPV infection, whereas Co exposure demonstrated an inverse relationship. The composite exposure to multiple metals showed a positive association with the prevalence of HPV infection. These findings indicate that exposure to metals could potentially escalate the prevalence of HPV infection.

Accelerated Longitudinal Glycemic Changes in Relation to Urinary Toxic/Essential Metals and Metal Mixtures Among Mexican Americans Living in Starr County, Texas

OBJECTIVE

Metal and metalloid exposures (hereafter "metals") are associated with adverse health outcomes, including type 2 diabetes; however, previous studies were largely cross-sectional or underpowered. Furthermore, underserved racial and ethnic groups are underrepresented in environmental health research despite having higher rates of type 2 diabetes and a greater risk of metal exposures. Consequently, we evaluated continuous glycemic traits in relation to baseline urinary toxic metal, essential metal, and metal mixtures in a cohort of Mexican American adults.

RESEARCH DESIGN AND METHODS

A total of 510 participants were selected based upon self-reported diabetes status and followed over 3 years. Urinary metals were assessed at baseline. Linear mixed-effects models were used to estimate per-month changes in hemoglobin A1c, fasting plasma glucose, and postload glucose in relation to urinary metal levels. Multiple statistical approaches were used to assess the associations between glycemic traits and metal mixtures.

RESULTS

After adjustment, higher urinary levels of arsenic, selenium, copper, molybdenum, nickel, and tin were associated with faster increases in measures of glycemia. The toxic metal mixture composed of arsenic, lead, cadmium, nickel, and tin was associated with faster increases in postload glucose. Using postload glucose criteria, highest versus lowest arsenic was predicted to accelerate conversion of normoglycemia to prediabetes and diabetes by 23 and 65 months, respectively.

CONCLUSIONS

In this underrepresented, high-risk Mexican American population, exposure to toxic metals and alterations in essential metal homeostasis were associated with faster increases in glycemia over time that may accelerate type 2 diabetes development.

The Evaluation of Selected Trace Elements in Blood, Serum and Blood Cells of Type 2 Diabetes Patients with and without Renal Disorder

BACKGROUND

An appropriate diet is the basis for the treatment of type 2 diabetes (T2DM). However, there are no strict recommendations regarding the content of micronutrients and their modifications in the presence of chronic kidney disease (CKD). Therefore, we decided to investigate whether T2DM patients, including those with CKD, have different levels of chromium, nickel, cobalt, magnesium, and zinc in various blood elements compared to healthy individuals.

METHODS

We divided our subjects into three groups: the control group (individuals without T2DM and proper renal function), those with T2DM and proper renal function, and those with T2DM and GFR < 60 mL/min/1.73 m2.

RESULTS

We observed higher levels of chromium in all materials examined in patients with T2DM and impaired renal function. Both study groups found higher levels of nickel in samples of whole blood and red blood cells. Patients with T2DM and proper renal function had higher levels of serum manganese. Both study groups had lower levels of serum zinc. We observed higher levels of chromium in all materials examined in patients with T2DM and impaired renal function. Both study groups found higher levels of nickel in samples of whole blood and red blood cells. Patients with T2DM and proper renal function had higher levels of serum manganese. Both study groups had lower levels of serum zinc.

CONCLUSIONS

In order to ensure effective care for patients with T2DM, it is necessary to improve the standard diet, including the content of micronutrients and their modification in patients with concomitant CKD.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Association between serum trace element, mineral, and amino acid levels with non-alcoholic fatty liver disease (NAFLD) in adult women

The objective of the present study is assessment of serum trace element and amino acid levels in non-alcoholic fatty liver disease (NAFLD) patients with subsequent evaluation of its independent associations with markers of liver injury and metabolic risk.

MATERIALS AND METHODS

140 women aged 20-90 years old with diagnosed NAFLD and 140 healthy women with a respective age range were enrolled in the current study. Analysis of serum and hair levels of trace elements and minerals was performed with inductively-coupled plasma mass-spectrometry (ICP-MS). Serum amino acid concentrations were evaluated by high-pressure liquid chromatography (HPLC) with UV-detection. In addition, routine biochemical parameters including liver damage markers, alanine aminotransferase (ALT) and gamma-glutamyltransferase (GGT), were assessed spectrophotometrically.

RESULTS

The findings demonstrated that patients with NAFLD were characterized by higher ALT, GGT, lactate dehydrogenase (LDH) and cholinesterase (CE) activity, as well as increased levels of total cholesterol, low-density lipoprotein cholesterol, triglycerides, and uric acid. NAFLD patients were characterized by reduced serum and hair Co, Se, and Zn levels, as well as hair Cu content and serum Mn concentrations in comparison to controls. Circulating Ala, Cit, Glu, Gly, Ile, Leu, Phe, and Tyr levels in NAFLD patients exceeded those in the control group. Multiple linear regression demonstrated that serum and hair trace element levels were significantly associated with circulating amino acid levels after adjustment for age, BMI, and metabolic parameters including liver damage markers.

CONCLUSION

It is proposed that altered trace element handling may contribute to NAFLD pathogenesis through modulation of amino acid metabolism.

Associations Between Individual and Combined Metal Exposures in Whole Blood and Kidney Function in U.S. Adults Aged 40 Years and Older

The effects of metal exposure on kidney function have been reported in previous literature. There is limited and inconsistent information on the associations between individual and combined exposures to metals and kidney function among the middle-aged and older population. The aim of this study was to clarify the associations of exposure to individual metals with kidney function while accounting for potential coexposure to metal mixtures and to evaluate the joint and interactive associations of blood metals with kidney function. A total of 1669 adults aged 40 years and older were enrolled in the present cross-sectional study using the 2015-2016 National Health and Nutrition Examination Survey (NHANES). Single-metal and multimetal multivariable logistic regression models, quantile G-computation, and Bayesian kernel machine regression models (BKMR) were fitted to explore the individual and joint associations of whole blood metals [lead (Pb), cadmium (Cd), mercury (Hg), cobalt (Co), manganese (Mn), and selenium (Se)] with the odds of decreased estimated glomerular filtration rate (eGFR) and albuminuria. A decreased eGFR was defined as an eGFR ≤ 60 mL/min per 1.73 m2, and albuminuria was categorized as a urinary albumin-creatinine ratio (UACR) of ≥ 30.0 mg/g. The results from quantile G-computation and BKMR indicated positive associations between exposure to the metal mixture and the prevalence of decreased eGFR and albuminuria (all P values < 0.05). These positive associations were mainly driven by blood Co, Cd, and Pb. Furthermore, blood Mn was identified as an influential element contributing to an inverse correlation with kidney dysfunction within metal mixtures. Increasing blood Se levels were negatively associated with the prevalence of decreased eGFR and positively associated with albuminuria. In addition, a potential pairwise interaction between Mn-Co on decreased eGFR was identified by BKMR analysis. Findings from our study suggested a positive association between exposure to the whole blood metal mixture and decreased kidney function, with blood Co, Pb, and Cd being the main contributors to this association, while Mn demonstrated an inverse relationship with renal dysfunction. However, as our study was cross-sectional in nature, further prospective studies are warranted to better understand the individual and combined effects of metals on kidney function.

Identification of the regulatory network and potential markers for type 2 diabetes mellitus related to internal exposure to metals in Chinese adults

People intake metals from their environment. This study investigated type 2 diabetes mellitus (T2DM) related to internal exposure to metals and attempted to identify possible biomarkers. A total of 734 Chinese adults were enrolled, and urinary levels of ten metals were measured. Multinomial logistic regression model was used to assess the association between metals and impaired fasting glucose (IFG) and T2DM. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction were used to explore the pathogenesis of T2DM related to metals. After adjustment, lead (Pb) was positively associated with IFG (odds ratio [OR] 1.31, 95% confidence interval [CI] 1.06-1.61) and T2DM (OR 1.41, 95% CI 1.01-1.98), but cobalt was negatively associated with IFG (OR 0.57, 95% CI 0.34-0.95). Transcriptome analysis showed 69 target genes involved in the Pb-target network of T2DM. GO enrichment indicated that the target genes are enriched mainly in the biological process category. KEGG enrichment indicated that Pb exposure leads to non-alcoholic fatty liver disease, lipid and atherosclerosis, and insulin resistance. Moreover, there is alteration of four key pathways, and six algorithms were used to identify 12 possible genes in T2DM related to Pb. SOD2 and ICAM1 show strong similarity in expression, suggesting a functional correlation between these key genes. This study reveals that SOD2 and ICAM1 may be potential targets of Pb exposure-induced T2DM and provides novel insight into the biological effects and underlying mechanism of T2DM related to internal exposure to metals in the Chinese population.

Joint Effect of Multiple Metals on Hyperuricemia and Their Interaction with Obesity: A Community-Based Cross-Sectional Study in China

Metal exposures have been inconsistently related to the risk of hyperuricemia, and limited research has investigated the interaction between obesity and metals in hyperuricemia. To explore their associations and interaction effects, 3300 participants were enrolled from 11 districts within 1 province in China, and the blood concentrations of 13 metals were measured to assess internal exposure. Multivariable logistic regression, restricted cubic spline (RCS), Bayesian kernel machine regression (BKMR), and interaction analysis were applied in the single- and multi-metal models. In single-metal models, five metals (V, Cr, Mn, Co, and Zn) were positively associated with hyperuricemia in males, but V was negatively associated with hyperuricemia in females. Following the multi-metal logistic regression, the multivariate-adjusted odds ratios (95% confidence intervals) of hyperuricemia were 1.7 (1.18, 2.45) for Cr and 1.76 (1.26, 2.46) for Co in males, and 0.68 (0.47, 0.99) for V in females. For V and Co, RCS models revealed wavy and inverted V-shaped negative associations with female hyperuricemia risk. The BKMR models showed a significant joint effect of multiple metals on hyperuricemia when the concentrations of five metals were at or above their 55th percentile compared to their median values, and V, Cr, Mn, and Co were major contributors to the combined effect. A potential interaction between Cr and obesity and Zn and obesity in increasing the risk of hyperuricemia was observed. Our results suggest that higher levels of Cr and Co may increase male hyperuricemia risk, while higher levels of V may decrease female hyperuricemia risk. Therefore, the management of metal exposure in the environment and diet should be improved to prevent hyperuricemia.

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.

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

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

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

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

Sex differences in the link between blood cobalt concentrations and insulin resistance in adults without diabetes

Background

Little is known about the effects of environmental cobalt exposure on insulin resistance (IR) in the general adult population. We investigated the association between cobalt concentration and IR.

Methods

A total of 1281 subjects aged more than 20 years with complete blood cobalt data were identified from the National Health and Nutrition Examination Survey (NHANES) 2015–2016 cycle. Blood cobalt levels were analyzed for their association with IR among all populations and subgroups by sex. Regression coefficients and 95% confidence intervals (CIs) of blood cobalt concentrations in association with fasting glucose, insulin and homeostatic model assessment of insulin resistance (HOMA-IR) were estimated using multivariate linear regression after adjusting for age, sex, ethnicity, alcohol consumption, body mass index, education level, and household income. A multivariate generalized linear regression analysis was further carried out to explore the association between cobalt exposure and IR.

Results

A negative association between blood cobalt concentration (coefficient = − 0.125, 95% CI − 0.234, − 0.015; P = 0.026) and HOMA-IR in female adults in the age- and sex-adjusted model was observed. However, no associations with HOMA-IR, fasting glucose, or insulin were found in the overall population. In the generalized linear models, participants with the lowest cobalt levels had a 2.74% (95% CI 0.04%, 5.50%) increase in HOMA-IR (P for trend = 0.031) compared with subjects with the highest cobalt levels. Restricted cubic spline regression suggested that a non-linear relationship may exist between blood cobalt and HOMA-IR.

Conclusions

These results provide epidemiological evidence that low levels of blood cobalt are negatively associated with HOMA-IR in female adults.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12199-021-00966-w.