Use of OMIC technologies to study arsenic exposure in human populations

Cortex metabolome and proteome analysis reveals chronic arsenic exposure via drinking water induces developmental neurotoxicity through hnRNP L mediated mitochondrial dysfunction in male rats

Lots of people are at the risk of arsenic-contaminated drinking water. Arsenic exposure was confirmed to be closely linked to neurocognitive deficits, particularly during childhood. The multi-omics approaches are known be well suitable for toxicological research. Thus, this study aimed to explore the molecular mechanisms of arsenic-induced learning and memory function impairments through the integrative proteome and metabolome analysis of cortex in rats. The weaned rats were exposed to arsenic-contaminated drinking water for six months to mimic the developmental exposure. 220 differential proteins and 19 differential metabolites were identified in the cortex, and nine potential biomarkers were found to be related to impaired Morris water maze (MWM) indicators. Chronic arsenic exposure affected the cognitive function by inducing the overproduction of amyloid-β (Aβ) peptides and the redox imbalance in the mitochondria. Glycolysis and tricarboxylic acid (TCA) cycle enhancement driven by the increased heterogeneous nuclear ribonucleoprotein L (hnRNP L) is a low-dose protective mechanism against arsenic-induced ATP deficiency and oxidative stress. Moreover, apoptosis is another important pathway of arsenic-induced neurotoxicity. This study provides new evidence about the alterations of proteins and metabolites in the cortex of the exposed rats under arsenic toxicity. These findings suggest hnRNP L could be a potential target for the treatment of arsenic-induced neurotoxicity.

Metabolomic Characterizations of Liver Injury Caused by Acute Arsenic Toxicity in Zebrafish

Arsenic is one of the most common metalloid contaminants in groundwater and it has both acute and chronic toxicity affecting multiple organs. Details of the mechanism of arsenic toxicity are still lacking and profile studies at metabolic level are very limited. Using gas chromatography coupled with mass spectroscopy (GC/MS), we first generated metabolomic profiles from the livers of arsenic-treated zebrafish and identified 34 significantly altered metabolite peaks as potential markers, including four prominent ones: cholic acid, glycylglycine, glycine and hypotaurine. Combined results from GC/MS, histological examination and pathway analyses suggested a series of alterations, including apoptosis, glycogenolysis, changes in amino acid metabolism and fatty acid composition, accumulation of bile acids and fats, and disturbance in glycolysis related energy metabolism. The alterations in glycolysis partially resemble Warburg effect commonly observed in many cancer cells. However, cellular damages were not reflected in two conventional liver function tests performed, Bilirubin assay and alanine aminotransferase (ALT) assay, probably because the short arsenate exposure was insufficient to induce detectable damage. This study demonstrated that metabolic changes could reflect mild liver impairments induced by arsenic exposure, which underscored their potential in reporting early liver injury.

Serum metabolomics reveals that arsenic exposure disrupted lipid and amino acid metabolism in rats: a step forward in understanding chronic arsenic toxicity

Chronic arsenic exposure through drinking water threatens public health worldwide. Although its multiorgan toxicity has been reported, the impact of chronic arsenic exposure on the metabolic network remains obscure. In this study, male Sprague Dawley rats were exposed to 0.5, 2 or 10 ppm sodium arsenite for three months. An ultra-high performance liquid chromatography/mass spectrometry based metabolomics approach was utilized to unveil the global metabolic response to chronic arsenic exposure in rats. Distinct serum metabolome profiles were found to be associated with the doses. Eighteen differential metabolites were identified, and most of them showed dose-dependent responses to arsenic exposure. Metabolic abnormalities mainly involved lipid metabolism and amino acid metabolism. The metabolic alterations were further confirmed by hepatic gene expression. Expressions of cpt2, lcat, cact, crot and mtr were significantly elevated in high dose groups. This study provides novel evidence to support the association between arsenic exposure and metabolic disruption, and it contributes to understanding the mechanism of chronic arsenic toxicity.

Urinary metabolomics revealed arsenic internal dose-related metabolic alterations: a proof-of-concept study in a Chinese male cohort

Urinary biomonitoring provides the most accurate arsenic exposure assessment; however, to improve the risk assessment, arsenic-related metabolic biomarkers are required to understand the internal processes that may be perturbed, which may, in turn, link the exposure to a specific health outcome. This study aimed to investigate arsenic-related urinary metabolome changes and identify dose-dependent metabolic biomarkers as a proof-of-concept of the information that could be obtained by combining metabolomics and targeted analyses. Urinary arsenic species such as inorganic arsenic, methylarsonic acid, dimethylarsinic acid and arsenobetaine were quantified using high performance liquid chromatography (HPLC)-inductively coupled plasma-mass spectrometry in a Chinese adult male cohort. Urinary metabolomics was conducted using HPLC-quadrupole time-of-flight mass spectrometry. Arsenic-related metabolic biomarkers were investigated by comparing the samples of the first and fifth quintiles of arsenic exposure classifications using a partial least-squares discriminant model. After the adjustments for age, body mass index, smoking, and alcohol consumption, five potential biomarkers related to arsenic exposure (i.e., testosterone, guanine, hippurate, acetyl-N-formyl-5-methoxykynurenamine, and serine) were identified from 61 candidate metabolites; these biomarkers suggested that endocrine disruption and oxidative stress were associated with urinary arsenic levels. Testosterone, guanine, and hippurate showed a high or moderate ability to discriminate the first and fifth quintiles of arsenic exposure with area-under-curve (AUC) values of 0.89, 0.87, and 0.83, respectively; their combination pattern showed an AUC value of 0.91 with a sensitivity of 88% and a specificity of 80%. Arsenic dose-dependent AUC value changes were also observed. This study demonstrated that metabolomics can be used to investigate arsenic-related biomarkers of metabolic changes; the dose-dependent trends of arsenic exposure to these biomarkers may translate into the potential use of metabolic biomarkers in arsenic risk assessment. Since this was a proof-of-concept study, more research is needed to confirm the relationships we observed between arsenic exposure and biochemical changes.

Assessing exposure and health consequences of chemicals in drinking water: current state of knowledge and research needs

BACKGROUND

Safe drinking water is essential for well-being. Although microbiological contamination remains the largest cause of water-related morbidity and mortality globally, chemicals in water supplies may also cause disease, and evidence of the human health consequences is limited or lacking for many of them.

OBJECTIVES

We aimed to summarize the state of knowledge, identify gaps in understanding, and provide recommendations for epidemiological research relating to chemicals occurring in drinking water.

DISCUSSION

Assessing exposure and the health consequences of chemicals in drinking water is challenging. Exposures are typically at low concentrations, measurements in water are frequently insufficient, chemicals are present in mixtures, exposure periods are usually long, multiple exposure routes may be involved, and valid biomarkers reflecting the relevant exposure period are scarce. In addition, the magnitude of the relative risks tends to be small.

CONCLUSIONS

Research should include well-designed epidemiological studies covering regions with contrasting contaminant levels and sufficient sample size; comprehensive evaluation of contaminant occurrence in combination with bioassays integrating the effect of complex mixtures; sufficient numbers of measurements in water to evaluate geographical and temporal variability; detailed information on personal habits resulting in exposure (e.g., ingestion, showering, swimming, diet); collection of biological samples to measure relevant biomarkers; and advanced statistical models to estimate exposure and relative risks, considering methods to address measurement error. Last, the incorporation of molecular markers of early biological effects and genetic susceptibility is essential to understand the mechanisms of action. There is a particular knowledge gap and need to evaluate human exposure and the risks of a wide range of emerging contaminants.

CITATION

Villanueva CM, Kogevinas M, Cordier S, Templeton MR, Vermeulen R, Nuckols JR, Nieuwenhuijsen MJ, Levallois P. 2014. Assessing exposure and health consequences of chemicals in drinking water: current state of knowledge and research needs. Environ Health Perspect 122:213–221; http://dx.doi.org/10.1289/ehp.1206229