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Deaths caused by environmental pollution are agrowing public health issue. Most of the premature deaths related to pollution are caused by non communicable diseases such as chronic obstructive pulmonary disease, type-2 diabetes, cardiovascular disease and cancer. They are considered complex diseases because of their multicausality and the various mechanisms involved in their emergence and evolution.Knowledge of disease-causing mechanismsis increasing and the identification of disease-associated biomarkers improving thanks to technological progress, in particular that of the technologiesthat are applied to the measurement and interpretation of molecular components—the so-called “Omics” technologies. These technologies have allowed the cellular causes of some complex diseases to be identified: genetic variants of susceptibility or protection to pollutants (Genomics), as well as changes in the DNA (Epigenomics) and their effects on the process of transcription of specific genes for repair, on metabolism or on the non-coding RNA associated with diseases (Transcriptomics). In addition, Proteomics and Metabolomics do not cease to provide information on proteins and metabolites involved in disease processes. Bioinformatics has evolved parallel to the development of omics, which has allowed the results of the measurements of hundreds of molecules to be interpreted and organized into networks that show the relationships among them.Omics are mainly used to develop disease risk models based on population studies, but information on genomes, transcriptomes, epigenomes, microbiomes, proteomes and metabolomesis also used to decipher diseases in order to facilitate prognosis and guide patient treatment, thus contributing to personalized, precision medicine. However, their clinical application is still limited by their cost and their technical, regulatory and ethical implications. Las muertes provocadas por la contaminación ambiental son un problema de salud pública en incremento. La mayoría de las muertes prematuras provocadas por la contaminación son enfermedades no transmisibles, como enfermedad pulmonar obstructiva crónica, diabetes tipo 2, enfermedades cardiovasculares y cáncer. Estas son consideradas enfermedades complejas por su multicausalidad y los diversos mecanismos involucrados en su aparición y evolución. El conocimiento del mecanismo de producción de la enfermedad, y la identificación de biomarcadores asociados a enfermedad está avanzando gracias al avance de la tecnología, y específicamente de la tecnología aplicada a medición e interpretación de componentes moleculares: las tecnologías “ÓMICAS”. Estas han permitido identificar causas celulares de algunas enfermedades complejas: variantes genéticas de susceptibilidad o protección a agentes contaminantes (Genómica), así como cambios sobre el ADN (Epigenómica) y sus efectos en el proceso de transcripción de genes específicos de reparación, metabolismo o bien RNA no codificante asociado a enfermedades (Transcriptómica); además la Proteómica y la Metabolómica aportan constante información sobre las proteínas y metabolitos involucrados en los procesos de enfermedad. Paralelo al desarrollo de las tecnologías ómicas ha evolucionado la bioinformática, que ha permitido la interpretación de los resultados de mediciones de cientos de moléculas para organizarlos en redes que traducen las relaciones entre ellas. Las tecnologías ómicas se aplican principalmente para determinar modelos de riesgo de enfermedad en base a estudios poblacionales, pero también la información del genoma, transcriptoma, el epigenoma, el microbioma, el proteoma y el metaboloma se utilizarán para ayudar a descifrar la enfermedad a fin de facilitar el pronóstico y guiar el tratamiento de pacientes, ayudando a la medicina individualizada y medicina de precisión. Sin embargo, su aplicación clínica está aún limitada por el costo y las implicaciones técnicas, regulatorias y éticas. As mortes causadas pela poluição ambiental sãoum problema de saúde pública crescente. A maioria das mortes prematuras causadas por contaminação sãodoençasnãotransmissíveis, como doença pulmonar obstrutiva crónica, diabetes tipo 2, doenças cardiovasculares e cancro. Estas são consideradas doenças complexas pela sua multicausalidade e pelos vários mecanismos envolvidos no seu aparecimento e evolução. O conhecimento do mecanismo de produção da doença e a identificação de biomarcadores associados à doençaestá a avançar graçasao desenvolvimento da tecnologia e, especificamente, à tecnologia aplicada à medição e interpretação de componentes moleculares: as tecnologias “ÓMICAS”. Estas permitiram identificar as causas celulares de algumasdoenças complexas: variantes genéticas de suscetibilidade ouproteção a agentes contaminantes (Genómica), bem como alterações no DNA (Epigenética) e os seusefeitos no processo de transcrição de genes específicos de reparação, metabolismo ou RNAnão-codificanteassociado a doenças (Transcriptómica);acresce a Proteómica e a Metabolómica que fornecem informação sobre as proteínas e metabólitosenvolvidos nos processos de doença. Paralelamente ao desenvolvimento das novas técnicas biotecnológicas, geralmente denominadas por “Ómicas”, evoluiu a bioinformática, o que permitiu a interpretação dos resultados das análises de centenas de moléculas para organizá-las em redes que traduzem as relações entre elas. As tecnologias “Ómicas” aplicam-se principalmente para determinar modelos de risco de doença com base em estudos populacionais, mas igualmente a informação do genoma, do transcriptoma, do epigenoma, do microbioma, do proteoma e do metaboloma será usada para ajudar a decifrar a doença, a fim de facilitar o prognóstico e orientar o tratamento dos pacientes, auxiliado a medicina individualizada e a medicina de precisão. No entanto, a sua aplicação clínica ainda é limitada pelo custo e implicações técnicas, regulamentares e éticas.

Background: Exposure to inorganic arsenic (iAs) from drinking water is a global public health problem, yet much remains unknown about the extent of exposure in susceptible populations.

BackgroundThe concentration of arsenic in urine has been used as a marker of exposure to inorganic As (iAs). Relative proportions of urinary metabolites of iAs have been identified as potential biomarkers of susceptibility to iAs toxicity. However, the adverse effects of iAs exposure are ultimately determined by the concentrations of iAs metabolites in target tissues.ObjectiveIn this study we examined the feasibility of analyzing As species in cells that originate in the urinary bladder, a target organ for As-induced cancer in humans.MethodsExfoliated bladder epithelial cells (BECs) were collected from urine of 21 residents of Zimapan, Mexico, who were exposed to iAs in drinking water. We determined concentrations of iAs, methyl-As (MAs), and dimethyl-As (DMAs) in urine using conventional hydride generation-cryotrapping-atomic absorption spectrometry (HG-CT-AAS). We used an optimized HG-CT-AAS technique with detection limits of 12–17 pg As for analysis of As species in BECs.ResultsAll urine samples and 20 of 21 BEC samples contained detectable concentrations of iAs, MAs, and DMAs. Sums of concentrations of these As species in BECs ranged from 0.18 to 11.4 ng As/mg protein and in urine from 4.8 to 1,947 ng As/mL. We found no correlations between the concentrations or ratios of As species in BECs and in urine.ConclusionThese results suggest that urinary levels of iAs metabolites do not necessarily reflect levels of these metabolites in the bladder epithelium. Thus, analysis of As species in BECs may provide a more effective tool for risk assessment of bladder cancer and other urothelial diseases associated with exposures to iAs.

Background: A growing number of studies link chronic exposure to inorganic arsenic (iAs) with the risk of diabetes. Many of these studies assessed iAs exposure by measuring arsenic (As) species in urine. However, this approach has been criticized because of uncertainties associated with renal function and urine dilution in diabetic individuals.

BackgroundExposure to arsenic (As) concentrations in drinking water > 150 μg/L has been associated with risk of diabetes and cardiovascular disease, but little is known about the effects of lower exposures.ObjectiveThis study aimed to examine whether moderate As exposure, or indicators of individual As metabolism at these levels of exposure, are associated with cardiometabolic risk.MethodsWe analyzed cross-sectional associations between arsenic exposure and multiple markers of cardiometabolic risk using drinking-water As measurements and urinary As species data obtained from 1,160 adults in Chihuahua, Mexico, who were recruited in 2008–2013. Fasting blood glucose and lipid levels, the results of an oral glucose tolerance test, and blood pressure were used to characterize cardiometabolic risk. Multivariable logistic, multinomial, and linear regression were used to assess associations between cardiometabolic outcomes and water As or the sum of inorganic and methylated As species in urine.ResultsAfter multivariable adjustment, concentrations in the second quartile of water As (25.5 to < 47.9 μg/L) and concentrations of total speciated urinary As (< 55.8 μg/L) below the median were significantly associated with elevated triglycerides, high total cholesterol, and diabetes. However, moderate water and urinary As levels were also positively associated with HDL cholesterol. Associations between arsenic exposure and both dysglycemia and triglyceridemia were higher among individuals with higher proportions of dimethylarsenic in urine.ConclusionsModerate exposure to As may increase cardiometabolic risk, particularly in individuals with high proportions of urinary dimethylarsenic. In this cohort, As exposure was associated with several markers of increased cardiometabolic risk (diabetes, triglyceridemia, and cholesterolemia), but exposure was also associated with higher rather than lower HDL cholesterol.CitationMendez MA, González-Horta C, Sánchez-Ramírez B, Ballinas-Casarrubias L, Hernández Cerón R, Viniegra Morales D, Baeza Terrazas FA, Ishida MC, Gutiérrez-Torres DS, Saunders RJ, Drobná Z, Fry RC, Buse JB, Loomis D, García-Vargas GG, Del Razo LM, Stýblo M. 2016. Chronic exposure to arsenic and markers of cardiometabolic risk: a cross-sectional study in Chihuahua, Mexico. Environ Health Perspect 124:104–111; http://dx.doi.org/10.1289/ehp.1408742