3 research outputs found

    Harmonization of human biomonitoring studies in Europe: characteristics of the HBM4EU-aligned studies participants

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    Human biomonitoring has become a pivotal tool for supporting chemicals' policies. It provides information on real-life human exposures and is increasingly used to prioritize chemicals of health concern and to evaluate the success of chemical policies. Europe has launched the ambitious REACH program in 2007 to improve the protection of human health and the environment. In October 2020 the EU commission published its new chemicals strategy for sustainability towards a toxic-free environment. The European Parliament called upon the commission to collect human biomonitoring data to support chemical's risk assessment and risk management. This manuscript describes the organization of the first HBM4EU-aligned studies that obtain comparable human biomonitoring (HBM) data of European citizens to monitor their internal exposure to environmental chemicals. The HBM4EU-aligned studies build on existing HBM capacity in Europe by aligning national or regional HBM studies. The HBM4EU-aligned studies focus on three age groups: children, teenagers, and adults. The participants are recruited between 2014 and 2021 in 11 to 12 primary sampling units that are geographically distributed across Europe. Urine samples are collected in all age groups, and blood samples are collected in children and teenagers. Auxiliary information on socio-demographics, lifestyle, health status, environment, and diet is collected using questionnaires. In total, biological samples from 3137 children aged 6-12 years are collected for the analysis of biomarkers for phthalates, HEXAMOLL((R)) DINCH, and flame retardants. Samples from 2950 teenagers aged 12-18 years are collected for the analysis of biomarkers for phthalates, Hexamoll((R)) DINCH, and per- and polyfluoroalkyl substances (PFASs), and samples from 3522 adults aged 20-39 years are collected for the analysis of cadmium, bisphenols, and metabolites of polyaromatic hydrocarbons (PAHs). The children's group consists of 50.4% boys and 49.5% girls, of which 44.1% live in cities, 29.0% live in towns/suburbs, and 26.8% live in rural areas. The teenagers' group includes 50.6% girls and 49.4% boys, with 37.7% of residents in cities, 31.2% in towns/suburbs, and 30.2% in rural areas. The adult group consists of 52.6% women and 47.4% men, 71.9% live in cities, 14.2% in towns/suburbs, and only 13.4% live in rural areas. The study population approaches the characteristics of the general European population based on age-matched EUROSTAT EU-28, 2017 data; however, individuals who obtained no to lower educational level (ISCED 0-2) are underrepresented. The data on internal human exposure to priority chemicals from this unique cohort will provide a baseline for Europe's strategy towards a non-toxic environment and challenges and recommendations to improve the sampling frame for future EU-wide HBM surveys are discussed

    Human Biomonitoring Data in Health Risk Assessments Published in Peer-Reviewed Journals between 2016 and 2021: Confronting Reality after a Preliminary Review

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    Human biomonitoring (HBM) is a rapidly developing field that is emphasized as an important approach for the assessment of health risks. However, its value for health risk assessment (HRA) remains to be clarified. We performed a review of publications concerned with applications of HBM in the assessment of health risks. The selection of publications for this review was limited by the search engines used (only PubMed and Scopus) and a timeframe of the last five years. The review focused on the clarity of 10 HRA elements, which influence the quality of HRA. We show that the usage of HBM data in HRA is limited and unclear. Primarily, the key HRA elements are not consistently applied or followed when using HBM in such assessments, and secondly, there are inconsistencies regarding the understanding of fundamental risk analysis principles and good practices in risk analysis. Our recommendations are as follows: (i) potential usage of HBM data in HRA should not be non-critically overestimated but rather limited and aligned to a specific value for exposure assessment or for the interpretation of health damage; (ii) improvements to HRA approaches, using HBM information or not, are needed and should strictly follow theoretical foundations of risk analysis

    NEUROSOME: a multidisciplinary training network to explore the neurodevelopmental and neurological exposome

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    On the basis of existing epidemiological data, the effect of neurotoxic metals (mercury, methylmercury, lead, manganese, cadmium), pesticides (organophosphates, pyrethroids) and flame retardants (brominated and organophosphate) on the neuropsychological development of exposed children appears to be variable among individuals. The extent to which the observed differences could be explained by genetic vulnerability or co-exposure to more environmental chemicals is still unclear. Although environmental health literature is rich with knowledge on the potential individual steps linking environmental contamination to disease, there is a lack of established causality for developing the respective Adverse Outcome Pathways (AOPs), especially taking into account cumulative exposure, where different mechanisms of toxicity are involved, interacting between them at different levels of biological organization. Furthermore, the brain, the target organ of neurotoxicants, it is not accessible if not using highly invasive or extremely costly (e.g. neuroimaging) methods. Research is needed to identify a set of peripheral accessible markers of susceptibility, vulnerability and effects, able to predict the neuropsychological/neurological outcome. NEUROSOME is an Innovative Training Networks funded in 2017 within H2020 Marie Sklodowska-Curie Actions. The main objective of the NEUROSOME project is the development of an integrated model based on real human biomonitoring data (HBM) to identify causal associations between early environmental exposures, the human genome, and the risk of neurodevelopmental disorders and neurodegenerative diseases. In particular, the project is based on the evaluation and re-analysis of biological samples collected in existing birth cohorts (PHIME, INMA, PROBE) and in the context of a cross-Mediterranean cohort study set up specifically within NEUROSOME. The project is focused on exposure to mixtures of heavy metals and organic compounds (phthalates, plasticizers, pyrethroids, organophosphate pesticides and brominated and organophosphate flame retardants), but will also consider the role of modulation and the synergistic or additive effects of other intrinsic (such as genetic susceptibility) and extrinsic (such as diet and socio-economic status) environmental stressors. This requires the synthesis among different scientific disciplines, including environmental and exposure modelling, recent advances in toxicology (including in vitro, in vivo and in silico aspects) with a special focus on omics technologies and bioinformatics, as well as environmental epidemiology, taking stock of gene- and exposome-wide associations. The NEUROSOME objectives are pursued through an interdisciplinary network aimed at developing new knowledge and training a new generation of young European researchers on the most current issues of the relationship between the environment and health. Fifteen selected Early Stage Researchers will move between participating institutions to integrate their transdisciplinary skills and learn the different research approaches, from in silico models to human biomonitoring. A preliminary set of results collected in the first year of the project will be presented: they include collection of HBM and outcome data from the relevant population studies, transcriptomics and metabolomic signatures linked to the neurodevelopmental phenotype in biosamples, the establishment of in vitro and in vivo models of exposure to environmentally relevant chemical mixtures and generic lifetime PBBK model incorporating mixtures interaction to integrate exposure data and modelling output with HBM data
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