Associations of total urinary arsenic with total cholesterol and high-density lipoprotein among 12-17-year-old participants from the 2009-2016 NHANES cycles: A cross-sectional study

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Assessing the impact of arsenic, lead, mercury, and cadmium exposure on glycemic and lipid profile markers: A systematic review and meta-analysis protocol

The toxicity of metals presents a significant threat to human health due to the metabolic changes they induce. Thus, it is crucial to understand the impact of exposure to toxic elements on glycemic and lipid profiles. To this end, we developed a systematic review protocol registered in PROSPERO (CRD42023393681), following PRISMA-P guidelines. This review aims to assess environmental exposure to arsenic, cadmium, mercury, and lead in individuals aged over ten years and elucidate their association with glycemic markers such as fasting plasma glucose, glycated hemoglobin, as well as lipid parameters including total cholesterol, triglycerides, high-density lipoprotein, and low-density lipoprotein cholesterol. Articles published in the MEDLINE (PubMed), EMBASE, Web of Science, LILACS, and Google Scholar databases until March 2024 will be included without language restrictions. The modified Newcastle-Ottawa scale will be employed to assess the quality of the included studies, and the results will be presented through narrative synthesis. If adequate data are available, a meta-analysis will be conducted. This review can help understand the metabolic responses to exposure to toxic elements and the associated health risks.

Functional metabolomics reveals arsenic-induced inhibition of linoleic acid metabolism in mice kidney in drinking water

Arsenic (As) is a heavy metal known for its detrimental effects on the kidneys, but the precise mechanisms underlying its toxicity remain unclear. In this study, we employed an integrated approach combining traditional toxicology methods with functional metabolomics to explore the nephrotoxicity induced by As in mice. Our findings demonstrated that after 28 days of exposure to sodium arsenite, blood urea nitrogen, serum creatinine levels were significantly increased, and pathological examination of the kidneys revealed dilation of renal tubules and glomerular injury. Additionally, uric acid, total cholesterol, and low-density lipoprotein cholesterol levels were significant increased while triglyceride level was decreased, resulting in renal insufficiency and lipid disorders. Subsequently, the kidney metabolomics analysis revealed that As exposure disrupted 24 differential metabolites, including 14 up-regulated and 10 down-regulated differential metabolites. Ten metabolic pathways including linoleic acid and glycerophospholipid metabolism were significantly enriched. Then, 80 metabolic targets and 168 predicted targets were identified using metabolite network pharmacology analysis. Of particular importance, potential toxicity targets, such as glycine amidinotransferase, mitochondrial (GATM), and nitric oxide synthase, and endothelial (NOS3), were prioritized through the "metabolite-target-pathway" network. Receiver operating characteristics curve and molecular docking analyses suggested that 1-palmitoyl-2-myristoyl-sn-glycero-3-PC, linoleic acid, and L-hydroxyarginine might be functional metabolites associated with GATM and NOS3. Moreover, targeted verification result showed that the level of linoleic acid in As group was 0.4951 μg/mL, which was significantly decreased compared with the control group. And in vivo and in vitro protein expression experiments confirmed that As exposure inhibited the expression of GATM and NOS3. In conclusion, these results suggest that As-induced renal injury may be associated with the inhibition of linoleic acid metabolism through the down-regulation of GATM and NOS3, resulting in decreased levels of linoleic acid, 1-palmitoyl-2-myristoyl-sn-glycero-3-PC, and L-hydroxyarginine metabolites.

Association of different obesity patterns with hypertension in US male adults: a cross-sectional study

Obesity is an important risk factor for hypertension. We aimed to investigate the association between different obesity patterns and hypertension risk in a large male population in the US. Male participants from the National Health and Nutrition Examination Survey (NHANES) (2007-2018) were enrolled in this cross-sectional study. Social demographic information, lifestyle factors, anthropometric measurements and biochemical measurements were collected. Three obesity patterns were classified according to the body mass index (BMI) and waist circumference (WC), including overweight and general obesity, abdominal obesity, and compound obesity. We adopted multivariate logistic regression to investigate the associations between hypertension and different obesity patterns after adjusting for cofounding factors. Subgroup analysis, stratified by age, smoking, drinking and estimated glomerular filtration rate (eGFR), was also conducted to explore the associations between obesity patterns and hypertension risk among different populations. Moreover, the association between WC and hypertension among male individuals was also explored using restricted cubic spline (RCS) analysis. Receiver operating characteristic (ROC) was used to evaluate the discriminatory power of WC for screening hypertension risk. 13,859 male participants from NHANES survey (2007-2018) were enrolled. Comparing with the normal-weight group, the odds ratios (ORs) [95% confidence interval (CI)] for hypertension in individuals with overweight and general obesity, abdominal obesity and compound obesity were 1.41 [1.17-1.70], 1.97 [1.53-2.54] and 3.28 [2.70-3.99], respectively. Subgroup analysis showed that the effect of different obesity patterns on hypertension risk was highly stable among individuals with different clinical conditions. In addition, WC had a positive correlation with the risk of hypertension (OR: 1.43; 95% CI 1.37-1.52; P < 0.001) in fully adjusted multivariate logistic regression model. RCS analysis showed that the association between WC and hypertension risk was in a nonlinear pattern, and WC had a good discriminatory power for hypertension in ROC analysis. Different patterns of obesity have a great impact on the risk of hypertension among male individuals. Increment of WC significantly increased the hypertension risk. More attention should be paid to the prevention of obesity, especially abdominal obesity and compound obesity in male individuals.

Metal mixtures with longitudinal changes in lipid profiles: findings from the manganese-exposed workers healthy cohort

The majority of epidemiological investigations on metal exposures and lipid metabolism employed cross-sectional designs and focused on individual metal. We explored the associations between metal mixture exposures and longitudinal changes in lipid profiles and potential sexual heterogeneity. We recruited 250 men and 73 women, aged 40 years at baseline (2012), and followed them up in 2020, from the manganese-exposed workers healthy cohort. We detected metal concentrations of blood cells at baseline with inductively coupled plasma mass spectrometry. Lipid profiles were repeatedly measured over 8 years of follow-up. We performed sparse partial least squares (sPLS) model to evaluate multi-pollutant associations. Bayesian kernel machine regression was utilized for metal mixtures as well as evaluating their joint impacts on lipid changes. In sPLS models, a positive association was found between manganese and change in total cholesterol (TC) (beta = 0.169), while a negative association was observed between cobalt (beta =  - 0.134) and change in low density lipoprotein cholesterol (LDL-C) (beta =  - 0.178) among overall participants, which were consistent in men. Interestingly, rubidium was positively associated with change in LDL-C (beta = 0.273) in women, while copper was negatively associated with change in TC (beta =  - 0.359) and LDL-C (beta =  - 0.267). Magnesium was negatively associated with change in TC (beta =  - 0.327). We did not observe the significantly cumulative effect of metal mixtures on lipid changes. In comparison to other metals, manganese had a more significant influence on lipid change [group PIP (0.579) and conditional PIP (0.556) for TC change in men]. Furthermore, male rats exposed to manganese (20 mg/kg) had higher levels of LDL-C in plasma and more apparent inflammatory infiltration, vacuolation of liver cells, nuclear pyknosis, and fatty change than the controls. These findings highlight the potential role of metal mixtures in lipid metabolism with sex-dependent heterogeneity. More researches are needed to explore the underlying mechanisms.

Linking the Low-Density Lipoprotein-Cholesterol (LDL) Level to Arsenic Acid, Dimethylarsinic, and Monomethylarsonic: Results from a National Population-Based Study from the NHANES, 2003–2020

Arsenic (As) contamination is a global public health problem. Elevated total cholesterol (TC) and low-density lipoprotein-cholesterol (LDL-C) are risk factors for cardiovascular diseases, but data on the association of urinary arsenic species’ level and LDL-C are limited. We performed an association analysis based on urinary arsenic species and blood TC and LDL-C in US adults. Methods: Urinary arsenic, arsenic acid (AA), dimethylarsinic (DMA), monomethylarsonic (MMA), TC, LDL-C, and other key covariates were obtained from the available National Health and Nutrition Examination Survey (NHANES) data from 2003 to 2020. Multiple linear regression analysis and generalized linear model are used to analyze linear and nonlinear relationships, respectively. Results: In total, 6633 adults aged 20 years were enrolled into the analysis. The median total urinary arsenic level was 7.86 µg/L. A positive association of urinary arsenic concentration quartiles was observed with TC (β: 2.42 95% CI 1.48, 3.36). The OR for TC of participants in the 80th versus 20th percentiles of urinary total arsenic was 1.34 (95% CI 1.13, 1.59). The OR for LDL-C of participants in the 80th versus 20th percentiles of urinary total arsenic was 1.36 (95% CI 1.15, 1.62). For speciated arsenics analysis, the OR for arsenic acid and TC was 1.35 (95% CI 1.02, 1.79), whereas the OR for DMA and LDL-L was 1.20 (95% CI 1.03, 1.41), and the OR for MMA and LDL-L was 1.30 (95% CI 1.11, 1.52). Conclusions: Urinary arsenic and arsenic species were positively associated with increased LDL-C concentration. Prevention of exposure to arsenic and arsenic species maybe helpful for the control of TC and LDL-C level in adults.