Effects of arsenic exposure on lipid metabolism: a systematic review and meta-analysis

Arsenic exposure at environmentally relevant levels induced metabolic toxicity in development mice: Mechanistic insights from integrated transcriptome and metabolome

Emerging evidence has linked arsenic exposure and metabolic homeostasis, but the mechanism is incompletely understood, especially at relatively low concentrations. In this study, we used a mouse model to evaluate the health impacts and metabolic toxicity of arsenic exposure in drinking water at environmentally relevant levels (0.25 and 1.0 ppm). Our results indicated that arsenic damaged intestinal barrier and induced arsenic accumulation, oxidative stress, and pathological changes in the liver and illum. Interestingly, arsenic increased the hepatic triglyceride (TG) and total cholesterol (TC), while reduced serum TG and TC levels. The liver transcriptome found that arsenic exposure caused transcriptome perturbation and promoted hepatic lipid accumulation by regulating the exogenous fatty acids degradation and apolipoproteins related genes. The serum metabolomics identified 74 and 88 differential metabolites in 0.25 and 1.0 ppm, respectively. The KEGG disease and subcellular location analysis indicated that arsenic induced liver and intestinal diseases, and the mitochondrion might be the target organelle for arsenic-induced toxicity. Co-enrichment of transcriptome and metabolome identified 24 metabolites and 9 genes as metabolic toxicity biomarkers. Moreover, 40 male (20 nonalcoholic fatty liver disease (NAFLD) cases and 20 healthy controls) was further selected to validate our findings. Importantly, the significantly changed L-palmitoylcarnitine, 3-hydroxybutyric acid, 2-hydroxycaproic acid and 6 genes of Hadha, Acadl, Aldh3a2, Cpt1a, Cpt2, and Acox1 were found in the NAFLD cases. The results from integrated multi-omics and chemical-protein network analysis indicated that L-palmitoylcarnitine played a critical role in metabolic toxicity by regulating mitochondrial fatty acids β-oxidation genes (Cpt1a, Cpt2). In conclusion, these findings provided new clues for the metabolic toxicity of arsenic exposure at environmentally relevant levels, which involved in the late-life NAFLD development. Our results also contribute to understanding the human responses and phenotypic changes to this hazardous material exposure in the environment.

Metabolic Derangement by Arsenic: a Review of the Mechanisms

Studies have implicated arsenic exposure in various pathological conditions, including metabolic disorders, which have become a global phenomenon, affecting developed, developing, and under-developed nations. Despite the huge risks associated with arsenic exposure, humans remain constantly exposed to it, especially through the consumption of contaminated water and food. This present study provides an in-depth insight into the mechanistic pathways involved in the metabolic derangement by arsenic. Compelling pieces of evidence demonstrate that arsenic induces metabolic disorders via multiple pathways. Apart from the initiation of oxidative stress and inflammation, arsenic prevents the phosphorylation of Akt at Ser473 and Thr308, leading to the inhibition of PDK-1/Akt insulin signaling, thereby reducing GLUT4 translocation through the activation of Nrf2. Also, arsenic downregulates mitochondrial deacetylase Sirt3, decreasing the ability of its associated transcription factor, FOXO3a, to bind to the agents that support the genes for manganese superoxide dismutase and PPARg co-activator (PGC)-1a. In addition, arsenic activates MAPKs, modulates p53/ Bcl-2 signaling, suppresses Mdm-2 and PARP, activates NLRP3 inflammasome and caspase-mediated apoptosis, and induces ER stress, and ox-mtDNA-dependent mitophagy and autophagy. More so, arsenic alters lipid metabolism by decreasing the presence of 3-hydroxy-e-methylglutaryl-CoA synthase 1 and carnitine O-octanoyl transferase (Crot) and increasing the presence of fatty acid-binding protein-3 mRNA. Furthermore, arsenic promotes atherosclerosis by inducing endothelial damage. This cascade of pathophysiological events promotes metabolic derangement. Although the pieces of evidence provided by this study are convincing, future studies evaluating the involvement of other likely mechanisms are important. Also, epidemiological studies might be necessary for the translation of most of the findings in animal models to humans.

Heavy Metal Exposure and Cardiovascular Disease

Heavy metals are harmful environmental pollutants that have attracted widespread attention due to their health hazards to human cardiovascular disease. Heavy metals, including lead, cadmium, mercury, arsenic, and chromium, are found in various sources such as air, water, soil, food, and industrial products. Recent research strongly suggests a connection between cardiovascular disease and exposure to toxic heavy metals. Epidemiological, basic, and clinical studies have revealed that heavy metals can promote the production of reactive oxygen species, which can then exacerbate reactive oxygen species generation and induce inflammation, resulting in endothelial dysfunction, lipid metabolism distribution, disruption of ion homeostasis, and epigenetic changes. Over time, heavy metal exposure eventually results in an increased risk of hypertension, arrhythmia, and atherosclerosis. Strengthening public health prevention and the application of chelation or antioxidants, such as vitamins and beta-carotene, along with minerals, such as selenium and zinc, can diminish the burden of cardiovascular disease attributable to metal exposure.

Atherogenic Index as a Cardiovascular Biomarker in Mexican Workers from Marginalized Urban Areas Occupationally Exposed to Metals

BACKGROUND

Cardiovascular disease (CVD) is one of the main causes of death and disability worldwide. The etiology of CVD is often associated with multiple risk factors, with environmental factors receiving considerable attention. Individuals with precarious jobs are among the groups most affected by chronic exposure to environmental pollutants.

AIM

This study aimed to evaluate occupational exposure to heavy metals among individuals in precarious job settings and investigate atherogenic indices as biomarkers of cardiovascular risk.

METHODS

A total of 137 workers participated in this cross-sectional study conducted in three work environments in San Luis Potosi, Mexico. Urine and blood samples were collected to assess metal exposure and biochemical profiles, including atherogenic indices.

RESULTS

The results showed that workers in the brick sector exhibited the highest levels of metal exposure, particularly arsenic (44.06 µg/L), followed by stonecutters and garbage collectors (24.7 and 16.9 µg/L, respectively). Similarly, Castelli risk index (CRI) and the atherogenic index of plasma (AIP) were higher in brickmakers (3.883 and 0.499) compared to stonecutters (3.285 and 0.386) and garbage collectors (3.329 and 0.367).

CONCLUSIONS

Evidence of exposure to heavy metals was observed in the three populations, in addition to the fact that individuals with greater exposure to arsenic also exhibited higher CRI and AIP.

Density Functional Theory Calculation May Confirm Arsenic-Thiol Adhesion as the Primary Mechanism of Arsenical Toxicity

Previously, it was believed that methylation was the body's primary method to detoxify inorganic arsenic. However, recent research has shown that the metabolized intermediate known as MMAIII is more toxic than arsenite and arsenate, contradicting a previous understanding. Another important question arises: is arsenical toxicity truly caused by arsenic binding to proteins through arsenic thiol adhesion? Based on the toxicity order of the experiment, with MMAIII being the most toxic, followed by arsenite, arsenate, DMAV, and MMAV, density functional theory (DFT) calculations can provide a straightforward assessment of this issue. Our practice captures all the transition states associated with a specific imaginary-frequency vibration mode, including proton transfer and simultaneous departure of leaving group. We have obtained the energy barriers for five arsenicals reacting with thiol, alcohol, and amine separately. In addition to energetic favorability, the following are the energy barriers for arsenic's reaction with thiol ranked from low to high: MMAIII (25.4 kcal/mol), arsenite (27.7 kcal/mol), arsenate (32.8 kcal/mol), DMAV (36.2 kcal/mol), and MMAV (38.3 kcal/mol). Results show that the toxicity of arsenicals is mainly caused by their reaction with thiol rather than with alcohol or amine, as supported by the trend of decreasing toxicity and increasing energy barriers. Thus, this DFT calculation may confirm the paradigm that arsenic-thiol adhesion is the primary cause of arsenic toxicity in the body.

Update of the risk assessment of inorganic arsenic in food

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

Do blood metals influence lipid profiles? Findings of a cross-sectional population-based survey

Dyslipidemia, an imbalance of lipids and a major risk factor for cardiovascular disease, has been associated with elevated blood and urine levels of several heavy metals. Using data from a Canadian Health Measures Survey (CHMS), we tested associations between blood levels of cadmium, copper, mercury, lead, manganese, molybdenum, nickel, selenium, and zinc, and the lipids triglycerides (TG), total cholesterol (TC), low density lipoproteins (LDL), high density lipoproteins (HDL) and apolipoproteins A1 (APO A1), and B (APO B). All adjusted associations between single metals and lipids were positive and significant, except for APO A1 and HDL. The joint effect of an interquartile range increase in heavy metals was positively associated with percentage increases of TC, LDL and APO B of 8.82% (95%CI: 7.06, 10.57), 7.01% (95%CI: 2.51, 11.51) and 7.15% (95%CI: 0.51, 13.78), respectively. Future studies are warranted to determine if reducing environmental exposure to heavy metals favorably influences lipid profiles and the risk of cardiovascular disease.

Association between Heavy Metals, Metalloids and Metabolic Syndrome: New Insights and Approaches

Metabolic syndrome (MetS) is an important public health issue that affects millions of people around the world and is growing to pandemic-like proportions. This syndrome is defined by the World Health Organization (WHO) as a pathologic condition characterized by abdominal obesity, insulin resistance, hypertension, and hyperlipidemia. Moreover, the etiology of MetS is multifactorial, involving many environmental factors, including toxicant exposures. Several studies have associated MetS with heavy metals exposure, which is the focus of this review. Environmental and/or occupational exposure to heavy metals are a major risk, contributing to the development of chronic diseases. Of particular note, toxic metals such as mercury, lead, and cadmium may contribute to the development of MetS by altering oxidative stress, IL-6 signaling, apoptosis, altered lipoprotein metabolism, fluid shear stress and atherosclerosis, and other mechanisms. In this review, we discuss the known and potential roles of heavy metals in MetS etiology as well as potential targeted pathways that are associated with MetS. Furthermore, we describe how new approaches involving proteomic and transcriptome analysis, as well as bioinformatic tools, may help bring about an understanding of the involvement of heavy metals and metalloids in MetS.

Urinary microbiota and metabolic signatures associated with inorganic arsenic-induced early bladder lesions

Inorganic arsenic (iAs) contamination in drinking water is a global public health problem, and exposure to iAs is a known risk factor for bladder cancer. Perturbation of urinary microbiome and metabolome induced by iAs exposure may have a more direct effect on the development of bladder cancer. The aim of this study was to determine the impact of iAs exposure on urinary microbiome and metabolome, and to identify microbiota and metabolic signatures that are associated with iAs-induced bladder lesions. We evaluated and quantified the pathological changes of bladder, and performed 16S rDNA sequencing and mass spectrometry-based metabolomics profiling on urine samples from rats exposed to low (30 mg/L NaAsO₂) or high (100 mg/L NaAsO₂) iAs from early life (in utero and childhood) to puberty. Our results showed that iAs induced pathological bladder lesions, and more severe effects were noticed in the high-iAs group and male rats. Furthermore, six and seven featured urinary bacteria genera were identified in female and male offspring rats, respectively. Several characteristic urinary metabolites, including Menadione, Pilocarpine, N-Acetylornithine, Prostaglandin B1, Deoxyinosine, Biopterin, and 1-Methyluric acid, were identified significantly higher in the high-iAs groups. In addition, the correlation analysis demonstrated that the differential bacteria genera were highly correlated with the featured urinary metabolites. Collectively, these results suggest that exposure to iAs in early life not only causes bladder lesions, but also perturbs urinary microbiome composition and associated metabolic profiles, which shows a strong correlation. Those differential urinary genera and metabolites may contribute to bladder lesions, suggesting a potential for development of urinary biomarkers for iAs-induced bladder cancer.

Association between combined exposure to plasma heavy metals and dyslipidemia in a chinese population

BACKGROUND

Exposure to heavy metals in the environment is widespread, while the relationship between combined exposure to heavy metals and dyslipidemia is unclear.

METHODS

A cross-sectional study was performed, and 3544 participants aged 30 years or older were included in the analyses. Heavy metal concentrations in plasma were based on inductively coupled plasma‒mass spectrometry. The relationship between heavy metals and dyslipidemia was estimated by logistic regression. BKMR was used to evaluate metal mixtures and their potential interactions.

RESULTS

In logistic regression analysis, participants in the fourth quartile of Fe and Zn (Fe > 1352.38 µg/L; Zn > 4401.42 µg/L) had a relatively higher risk of dyslipidemia (Fe, OR = 1.13, 95% CI: 0.92,1.38; Zn, OR = 1.30, 95% CI: 1.03,1.64). After sex stratification, females in the third quartile of plasma Zn (1062.05-4401.42 µg/L) had a higher relative risk of dyslipidemia (OR = 1.75, 95% CI: 1.28, 2.38). In BKMR analysis, metal mixtures were negatively associated with dyslipidemia in females when all metal concentrations were above the 50th percentile. In the total population (estimated from 0.030 to 0.031), As was positively associated with dyslipidemia when other metals were controlled at the 25th, 50th, or 75th percentile, respectively, and As was below the 75th percentile. In females (estimated from - 0.037 to -0.031), Zn was negatively associated with dyslipidemia when it was above the 50th percentile.

CONCLUSION

This study indicated that As was positively associated with dyslipidemia and that Zn may be negatively associated with dyslipidemia in females. Combined metal exposure was negatively associated with dyslipidemia in females. Females with low plasma Zn levels are more likely to develop dyslipidemia and should receive more clinical attention in this population.

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.

Co-cultivation as a Strategy to Reduce Food Chain-Mediated Arsenic Contamination in Human Beings

Arsenic (As) is a highly toxic metalloid present naturally in the earth's crust. In developing countries apart from drinking water, one major reason for arsenic toxicity among human beings is through contaminated crops and vegetables. The nutritional quality of the crops and vegetables grown in the arsenic-infested area gets compromised. A major challenge is to protect the vegetables and crops from arsenic contamination. Attempts have been made through different remediation technologies. The present research is designed to reduce the arsenic load in arsenic-sensitive (non-hyperaccumulator) plants by co-cultivation with hyperaccumulator plants, thus saving food chain contamination to humans. In the present study, done in potted plants, it has been found that co-cultivated B. oleracea has 1.5 times decreased arsenic translocation compared to the control plant; on the contrary, hyperaccumulator B. juncea showed higher translocation. Plant health biomarkers like total chlorophyll and protein contents were two times higher in co-cultivated B. oleracea compared to the As-treated control which actually seconds the fact of less translocation in the co-cultivated plants. The stress marker like proline content, super oxide dimutase, and malondialdehyde content showed a decrease in co-cultivated B. oleracea compared to the control plant grown in arsenic-infested soil which again reflected less stress in co-cultivated plants. From these findings of the research, we can hypothesize that hyperaccumulator B. juncea might save B. oleracea from arsenic-induced toxicity when co-cultivated and thus can save food chain-mediated contamination to human beings.

Gene-environment interaction analysis of redox-related metals and genetic variants with plasma metabolic patterns in a general population from Spain: The Hortega Study

Background

Limited studies have evaluated the joint influence of redox-related metals and genetic variation on metabolic pathways. We analyzed the association of 11 metals with metabolic patterns, and the interacting role of candidate genetic variants, in 1145 participants from the Hortega Study, a population-based sample from Spain.

Methods

Urine antimony (Sb), arsenic, barium (Ba), cadmium (Cd), chromium (Cr), cobalt (Co), molybdenum (Mo) and vanadium (V), and plasma copper (Cu), selenium (Se) and zinc (Zn) were measured by ICP-MS and AAS, respectively. We summarized 54 plasma metabolites, measured with targeted NMR, by estimating metabolic principal components (mPC). Redox-related SNPs (N = 291) were measured by oligo-ligation assay.

Results

In our study, the association with metabolic principal component (mPC) 1 (reflecting non-essential and essential amino acids, including branched chain, and bacterial co-metabolism versus fatty acids and VLDL subclasses) was positive for Se and Zn, but inverse for Cu, arsenobetaine-corrected arsenic (As) and Sb. The association with mPC2 (reflecting essential amino acids, including aromatic, and bacterial co-metabolism) was inverse for Se, Zn and Cd. The association with mPC3 (reflecting LDL subclasses) was positive for Cu, Se and Zn, but inverse for Co. The association for mPC4 (reflecting HDL subclasses) was positive for Sb, but inverse for plasma Zn. These associations were mainly driven by Cu and Sb for mPC1; Se, Zn and Cd for mPC2; Co, Se and Zn for mPC3; and Zn for mPC4. The most SNP-metal interacting genes were NOX1, GSR, GCLC, AGT and REN. Co and Zn showed the highest number of interactions with genetic variants associated to enriched endocrine, cardiovascular and neurological pathways.

Conclusions

Exposures to Co, Cu, Se, Zn, As, Cd and Sb were associated with several metabolic patterns involved in chronic disease. Carriers of redox-related variants may have differential susceptibility to metabolic alterations associated to excessive exposure to metals.

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In a population-based sample, cobalt, copper, selenium, zinc, arsenic, cadmium and antimony exposures were related to some metabolic patterns.

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Carriers of redox-related variants displayed differential susceptibility to metabolic alterations associated to excessive metal exposures.

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Cobalt and zinc showed a number of statistical interactions with variants from genes sharing biological pathways with a role in chronic diseases.

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The metabolic impact of metals combined with variation in redox-related genes might be large in the population, given metals widespread exposure.

Arsenic-fluoride co-exposure induced endoplasmic reticulum stress resulting in apoptosis in rat heart and H9c2 cells

Exposure to arsenic (As) or fluoride (F) has been shown to cause cardiovascular disease (CVDs). However, evidence about the effects of co-exposure to As and F on myocardium and their mechanisms remain scarce. Our aim was to fill the gap by establishing rat and H9c2 cell exposure models. We determined the effects of As and/or F exposure on the survival rate, apoptosis rate, morphology and ultrastructure of H9c2 cells; in addition, we tested the related genes and proteins of endoplasmic reticulum stress (ERS) and apoptosis in H9c2 cells and rat heart tissues. The results showed that As and/or F exposure induced early apoptosis of H9c2 cells and caused endoplasmic reticulum expansion. Additionally, the mRNA and protein expression levels of GRP78, PERK and CHOP in H9c2 cells were higher in the exposure groups than in the control group, and could be inhibited by 4-PBA. Furthermore, we found that As and/or F exposure increased the expression level of GRP78 in rat heart tissues, but interestingly, the expression level of CHOP protein was increased in the F and As groups, while significantly decreased in the co-exposure group. Overall, our results suggested that ERS-induced apoptosis was involved in the damage of myocardium by As and/or F exposure. In addition, factorial analysis results showed that As and F mainly play antagonistic roles in inducing myocardial injury, initiating ERS and apoptosis after exposure.

Is Arsenic Exposure a Risk Factor for Metabolic Syndrome? A Review of the Potential Mechanisms

Exposure to arsenic in drinking water is a worldwide health problem. This pollutant is associated with increased risk of developing chronic diseases, including metabolic diseases. Metabolic syndrome (MS) is a complex pathology that results from the interaction between environmental and genetic factors. This condition increases the risk of developing type 2 diabetes, cardiovascular diseases, and cancer. The MS includes at least three of the following signs, central obesity, impaired fasting glucose, insulin resistance, dyslipidemias, and hypertension. Here, we summarize the existing evidence of the multiple mechanisms triggered by arsenic to developing the cardinal signs of MS, showing that this pollutant could contribute to the multifactorial origin of this pathology.

Metabolic Syndrome and Endocrine Disrupting Chemicals: An Overview of Exposure and Health Effects

Increasing prevalence of metabolic syndrome (MetS) is causing a significant health burden among the European population. Current knowledge supports the notion that endocrine-disrupting chemicals (EDCs) interfere with human metabolism and hormonal balance, contributing to the conventionally recognized lifestyle-related MetS risk factors. This review aims to identify epidemiological studies focusing on the association between MetS or its individual components (e.g., obesity, insulin resistance, diabetes, dyslipidemia and hypertension) and eight HBM4EU priority substances (bisphenol A (BPA), per- and polyfluoroalkyl substances (PFASs), phthalates, polycyclic aromatic hydrocarbons (PAHs), pesticides and heavy metals (cadmium, arsenic and mercury)). Thus far, human biomonitoring (HBM) studies have presented evidence supporting the role of EDC exposures on the development of individual MetS components. The strength of the association varies between the components and EDCs. Current evidence on metabolic disturbances and EDCs is still limited and heterogeneous, and mainly represent studies from North America and Asia, highlighting the need for well-conducted and harmonized HBM programmes among the European population. Rigorous and ongoing HBM in combination with health monitoring can help to identify the most concerning EDC exposures, to guide future risk assessment and policy actions.