Publications
37 results found
Vineis P, Handakas E, Alfano R, et al., 2023, The contribution to policies of an exposome-based approach to childhood obesity, Exposome, Vol: https://academic.oup.com/exposome/advance-article/doi/10.1093/exposome/osad006/7180277, ISSN: 2635-2265
Childhood obesity is an increasingly severe public health problem, with a prospective impact on health. We propose an exposome approach to identifying actionable risk factors for this condition. Our assumption is that relationships between external exposures and outcomes such as rapid growth, overweight or obesity in children can be better understood through a “meet-in-the-middle” model. This is based on a combination of external and internal exposome-based approaches, i.e. the study of multiple exposures (in our case dietary patterns) and molecular pathways (metabolomics and epigenetics). This may strengthen causal reasoning by identifying intermediate markers that are associated with both exposures and outcomes. Our biomarker-based studies in the STOP consortium suggest (in several ways, including mediation analysis) that Branched-Chain Amino Acids (BCAAs) could be mediators of the effect of dietary risk factors on childhood overweight/obesity. This is consistent with intervention and animal studies showing that higher intake of BCAAs has a positive impact on body composition, glycemia and satiety. Concerning food, of particular concern is the trend of increasing intake of ultra-processed food (UPF), including among children. Several mechanisms have been proposed to explain the impact of UPF on obesity and overweight, including nutrient intake (particularly proteins), changes in appetite or the role of additives. Research from the ALSPAC cohort has shown a relationship between UPF intake and trajectories in childhood adiposity, while UPF was related to lower blood levels of BCAAs. We suggest that an exposome-based approach can help strengthening causal reasoning and support policies. Intake of UPF in children should be restricted to prevent obesity.
Robinson O, 2023, The exposome approach to study children's health, Current Opinion in Environmental Science & Health, Vol: 32, Pages: 1-7, ISSN: 2468-5844
The exposome represents an interdisciplinary science and promising field of research that can identify how multiple facets of the environment influences health across the lifespan. A particular sensitive and critical window for environmental exposures and exposure-associated health is during early life, especially childhood. Previous studies of the exposome during childhood are highlighted, including the external and internal exposome. Challenges, and potential ways to overcome them, of the childhood exposome are presented with the aims to improve exposome studies during early life.
Miranda Araujo AN, Nogueira Leroux I, Sousa Furtado DZ, et al., 2023, Integration of proteomic and metabolomic analyses: New insights for mapping informal workers exposed to potentially toxic elements, FRONTIERS IN PUBLIC HEALTH, Vol: 10
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Handakas E, Chang K, Khandpur N, et al., 2022, Metabolic profiles of ultra-processed food consumption and their role in obesity risk in British children, Clinical Nutrition, Vol: 41, Pages: 2537-2548, ISSN: 0261-5614
Background & aimsHigher consumption of ultra-processed foods (UPF) has been associated with childhood obesity, but underlying mechanisms remain unclear. We investigated plasma nuclear magnetic resonance metabolic profiles of higher UPF consumption and their role in obesity risk in the British ALSPAC cohort.MethodsWe performed cross-sectional and prospective metabolome wide association analyses of UPF, calculated from food diaries using the NOVA classification. In cross-sectional analysis, we tested the association between UPF consumption and metabolic profile at 7 years (N = 4528), and in the prospective analysis we tested the association between UPF consumption at 13 years and metabolic profile at 17 years (N = 3086). Effects of UPF-associated metabolites at 7 years on subsequent fat mass accumulation were assessed using growth curve models.ResultsAt 7 years, UPF was associated with 115 metabolic traits including lower levels of branched-chain and aromatic amino acids and higher levels of citrate, glutamine, and monounsaturated fatty acids, which were also associated with greater fat mass accumulation. Reported intake of nutrients mediated associations with most metabolites, except for citrate.ConclusionsUPF consumption among British children is associated with perturbation of multiple metabolic traits, many of which contribute to child obesity risk.
Handakas E, Xu Y, Blair Segal A, et al., 2022, Molecular mediators of the association between child obesity and mental health, Frontiers in Genetics, Vol: 13, Pages: 1-18, ISSN: 1664-8021
Biological mechanisms underlying the association between obesity and depression remain unclear. We investigated the role of metabolites and DNA methylation as mediators of the relationship between childhood obesity and subsequent poor mental health in the English Avon Longitudinal Study of Parents and Children. Obesity was defined according to United Kingdom Growth charts at age 7 years and mental health through the Short Mood and Feelings Questionnaire (SMFQ) completed at age 11 years. Metabolites and DNA methylation were measured by nuclear magnetic resonance spectroscopy and Illumina array in blood at the age of 7 years. The associations between obesity and SMFQ score, as continuous count data or using cut-offs to define depressive symptoms (SMFQ >7) or depression (SMFQ >11), were tested using adjusted Poisson and logistic regression. Candidate metabolite mediators were identified through metabolome-wide association scans for obesity and SMFQ score, correcting for false-discovery rate. Candidate DNA methylation mediators were identified through testing the association of putative BMI-associated CpG sites with SMFQ scores, correcting for look-up false-discovery rate. Mediation by candidate molecular markers was tested. Two-sample Mendelian randomization (MR) analyses were additionally applied to test causal associations of metabolites with depression in independent adult samples. 4,018 and 768 children were included for metabolomics and epigenetics analyses, respectively. Obesity at 7 years was associated with a 14% increase in SMFQ score (95% CI: 1.04, 1.25) and greater odds of depression (OR: 1.46 (95% CI: 0.78, 2.38) at 11 years. Natural indirect effects (mediating pathways) between obesity and depression for tyrosine, leucine and conjugated linoleic acid were 1.06 (95% CI: 1.00, 1.13, proportion mediated (PM): 15%), 1.04 (95% CI: 0.99, 1.10, PM: 9.6%) and 1.06 (95% CI: 1.00, 1.12, PM: 13.9%) respectively. In MR analysis, one unit increase in tyrosine was
Robinson O, 2022, Cord blood metabolites and rapid postnatal growth as multiple mediators in the prenatal propensity to childhood overweight, International Journal of Obesity, Vol: 46, Pages: 1384-1393, ISSN: 0307-0565
BACKGROUND: The mechanisms underlying childhood overweight and obesity are poorly known. Here, we investigated the direct and indirect effects of different prenatal exposures on offspring rapid postnatal growth and overweight in childhood, mediated through cord blood metabolites. Additionally, rapid postnatal growth was considered a potential mediator on childhood overweight, alone and sequentially to each metabolite.METHODS: Within four European birth-cohorts (N=375 mother-child dyads), information on seven prenatal exposures (maternal education, pre-pregnancy BMI, weight gain and tobacco smoke during pregnancy, age at delivery, parity, and child gestational age), selected as obesogenic according to a-priori knowledge, was collected. Cord blood levels of 31 metabolites, associated with rapid postnatal growth and/or childhood overweight in a previous study, were measured via liquid-chromatography-quadrupole-time-of-flight-mass-spectrometry. Rapid growth at 12 months and childhood overweight (including obesity) between four and eight years were defined with reference to WHO growth charts. Single mediation analysis was performed using the imputation approach and multiple mediation analysis using the extended-imputation approach.RESULTS: Single mediation suggested that the effect of maternal education, pregnancy weight gain, parity, and gestational age on rapid postnatal growth but not on childhood overweight was partly mediated by seven metabolites, including cholestenone, decenoylcarnitine(C10:1), phosphatidylcholine(C34:3), progesterone and three unidentified metabolites; and the effect of gestational age on childhood overweight was mainly mediated by rapid postnatal growth. Multiple mediation suggested that the effect of gestational age on childhood overweight was mainly mediated by rapid postnatal growth and that the mediating role of the metabolites was marginal. CONCLUSION: Our findings provide evidence of the involvement of in utero metabolism in the propensity
Malacarne D, Chandakas E, Robinson O, et al., 2022, The built environment as determinant of childhood obesity: a systematic literature review, Obesity Reviews, Vol: 23, Pages: 1-11, ISSN: 1467-7881
We evaluated the epidemiological evidence on the built environment and its link to childhood obesity, focusing on environmental factors such as traffic noise and air pollution, as well as physical factors potentially driving obesity-related behaviours, such as neighbourhood walkability and availability and accessibility of parks and playgrounds. Eligible studies were i) conducted on human children below the age of 18 years, ii) focused on body size measurements in childhood, iii) examined at least one built environment characteristic, iv) reported effect sizes and associated confidence intervals, and v) were published in English language. A z-Test, as alternative to the meta-analysis, was used to quantify associations due to heterogeneity in exposure and outcome definition. We found strong evidence for an association of traffic-related air pollution (nitrogen dioxide and nitrogen oxides exposure; p<0.001) and built environment characteristics supportive of walking (street intersection density; p<0.01 and access to parks; p<0.001) with childhood obesity. We identified a lack of studies which account for interactions between different built environment exposures or verify the role and mechanism of important effect modifiers such as age.
Handakas E, Lau CH, Alfano R, et al., 2022, A systematic review of metabolomic studies of childhood obesity: State of the evidence for metabolic determinants and consequences, Obesity Reviews, Vol: 23, Pages: 1-13, ISSN: 1467-7881
Childhood obesity has become a global epidemic and carries significant long-term consequences to physical and mental health. Metabolomics, the global profiling of small molecules or metabolites, may reveal the mechanisms of development of childhood obesity and clarify links between obesity and metabolic disease. A systematic review of metabolomic studies of childhood obesity was conducted, following Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, searching across Scopus, Ovid, Web of Science and PubMed databases for articles published from January 1, 2005 to July 8, 2020, retrieving 1271 different records and retaining 41 articles for qualitative synthesis. Study quality was assessed using a modified Newcastle–Ottawa Scale. Thirty-three studies were conducted on blood, six on urine, three on umbilical cord blood, and one on saliva. Thirty studies were primarily cross-sectional, five studies were primarily longitudinal, and seven studies examined effects of weight-loss following a life-style intervention. A consistent metabolic profile of childhood obesity was observed including amino acids (particularly branched chain and aromatic), carnitines, lipids, and steroids. Although the use of metabolomics in childhood obesity research is still developing, the identified metabolites have provided additional insight into the pathogenesis of many obesity-related diseases. Further longitudinal research is needed into the role of metabolic profiles and child obesity risk.
Alfano R, Robinson O, Handakas E, et al., 2022, Perspectives and challenges of epigenetic determinants of childhood obesity: A systematic review, Obesity Reviews, Vol: 23, Pages: 1-13, ISSN: 1467-7881
The tremendous increase in childhood obesity prevalence over the last few decades cannot merely be explained by genetics and evolutionary changes in the genome, implying that gene–environment interactions, such as epigenetic modifications, likely play a major role. This systematic review aims to summarize the evidence of the association between epigenetics and childhood obesity. A literature search was performed via PubMed and Scopus engines using a combination of terms related to epigenetics and pediatric obesity. Articles studying the association between epigenetic mechanisms (including DNA methylation and hydroxymethylation, non-coding RNAs, and chromatin and histones modification) and obesity and/or overweight (or any related anthropometric parameters) in children (0–18 years) were included. The risk of bias was assessed with a modified Newcastle–Ottawa scale for non-randomized studies. One hundred twenty-one studies explored epigenetic changes related to childhood obesity. DNA methylation was the most widely investigated mechanism (N = 101 studies), followed by non-coding RNAs (N = 19 studies) with evidence suggestive of an association with childhood obesity for DNA methylation of specific genes and microRNAs (miRNAs). One study, focusing on histones modification, was identified. Heterogeneity of findings may have hindered more insights into the epigenetic changes related to childhood obesity. Gaps and challenges that future research should face are herein described.
Salles FJ, Braga Tavares DJ, Freire BM, et al., 2021, Home-based informal jewelry production increases exposure of working families to cadmium, SCIENCE OF THE TOTAL ENVIRONMENT, Vol: 785, ISSN: 0048-9697
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- Citations: 10
Handakas E, Keski-Rahkonen P, Chatzi L, et al., 2021, Cord blood metabolic signatures predictive of childhood overweight and rapid growth, International Journal of Obesity, Vol: 45, Pages: 2252-2260, ISSN: 0307-0565
INTRODUCTION:Metabolomics may identify biological pathways predisposing children to risk of overweight and obesity. In this study, we have investigated the cord blood metabolic signatures of rapid growth in infancy and overweight in early childhood in four European birth cohorts.METHODS:Untargeted liquid chromatography-mass spectrometry metabolomic profiles were measured in cord blood from 399 newborns from four European cohorts (ENVIRONAGE, Rhea, INMA and Piccolipiu). Rapid growth in the first year of life and overweight in childhood were defined with reference to WHO growth charts. Metabolome-wide association scans for rapid growth and overweight on over 4500 metabolic features were performed using multiple adjusted logistic mixed effect models and controlling the false discovery rate (FDR) at 5%. Additionally, we performed a look-up analysis of 43 pre-annotated metabolites, previously associated with birthweight or rapid growth. RESULTS:In the MWAS analysis, we identified three and eight metabolites associated with rapid growth and overweight respectively, after FDR correction. Higher levels of cholestenone, a cholesterol derivative produced by microbial catabolism, was predictive of rapid growth (p=1.6x10-3). Lower levels of the branched chain amino acid (BCAA) valine (p=8.6x10-6) was predictive of overweight in childhood. The area under the receiver operator curve for multivariate prediction models including these metabolites and traditional risk factors was 0.77 for rapid growth and 0.82 for overweight, compared to 0.69 and 0.69 respectively for models using traditional risk factors alone. Among the 43 pre-annotated metabolites, seven and five metabolites were nominally associated (P<0.05) with rapid growth and overweight respectively. The BCAA leucine, remained associated (1.6x 0-3) with overweight after FDR correction.CONCLUSION:The metabolites identified here may assist in the identification of children at risk of developing obesity and improve understa
Sarigiannis DA, Papaioannou N, Handakas E, et al., 2021, Neurodevelopmental exposome: The effect of in utero co-exposure to heavy metals and phthalates on child neurodevelopment, ENVIRONMENTAL RESEARCH, Vol: 197, ISSN: 0013-9351
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- Citations: 12
Sarigiannis DA, Handakas EJ, Karakitsios SP, et al., 2021, Life cycle assessment of municipal waste management options, ENVIRONMENTAL RESEARCH, Vol: 193, ISSN: 0013-9351
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- Citations: 9
Ronaldson A, Chandakas E, Kang Q, et al., 2020, Cohort profile: he East London Health and Care Partnership Data Repository: using novel integrated data to support commissioning and research, BMJ Open, Vol: 10, Pages: 1-10, ISSN: 2044-6055
Purpose The East London Health and Care Partnership (ELHCP) Data Repository was established to support commissioning decisions in London. This dataset comprises routine clinical data for the general practitioner (GP)-registered populations of two London boroughs, Tower Hamlets and City and Hackney, and provides a rich source of demographic, clinical and health service use data of relevance to clinicians, commissioners, researchers and policy makers. This paper describes the dataset in its current form, its representativeness and data completeness.Participants There were 351 749 and 344 511 members of the GP-registered population in the two boroughs, respectively, for the financial year 2017/2018. Demographic information and prevalence data were available for 9 mental health and 15 physical health conditions. Prevalence rates from the cohort were compared with local and national data. In order to illustrate the health service use data available in the dataset, emergency department use across mental health conditions was described. Information about data completeness was provided.Findings to date The ELHCP Data Repository provides a rich source of information about a relatively young, urban, ethnically diverse, population within areas of socioeconomic deprivation. Prevalence data were in line with local and national statistics with some exceptions. Physical health conditions were more common in those with mental health conditions, reflecting that comorbidities are the norm rather than the exception. This has implications for integrated care. Data completeness for risk factors (eg, blood pressure, cholesterol) was high in patients with long-term conditions.Future plans The data are being further cleaned and evaluated using imputation, Bayesian and economic methods, principally focusing on specific cohorts, including type II diabetes, depression and personality disorder. Data continue to be collected for the foreseeable future to support commissioning deci
Robinson O, Chadeau Hyam M, Karaman I, et al., 2020, Determinants of accelerated metabolomic and epigenetic ageing in a UK cohort, Aging Cell, Vol: 19, Pages: 1-13, ISSN: 1474-9718
Markers of biological aging have potential utility in primary care and public health. We developed a model of age based on untargeted metabolic profiling across multiple platforms, including nuclear magnetic resonance spectroscopy and liquid chromatography–mass spectrometry in urine and serum, within a large sample (N = 2,239) from the UK Airwave cohort. We validated a subset of model predictors in a Finnish cohort including repeat measurements from 2,144 individuals. We investigated the determinants of accelerated aging, including lifestyle and psychological risk factors for premature mortality. The metabolomic age model was well correlated with chronological age (mean r = .86 across independent test sets). Increased metabolomic age acceleration (mAA) was associated after false discovery rate (FDR) correction with overweight/obesity, diabetes, heavy alcohol use and depression. DNA methylation age acceleration measures were uncorrelated with mAA. Increased DNA methylation phenotypic age acceleration (N = 1,110) was associated after FDR correction with heavy alcohol use, hypertension and low income. In conclusion, metabolomics is a promising approach for the assessment of biological age and appears complementary to established epigenetic clocks.
Sarigiannis DA, Karakitsios SP, Handakas E, et al., 2020, Development of a generic lifelong physiologically based biokinetic model for exposome studies, ENVIRONMENTAL RESEARCH, Vol: 185, ISSN: 0013-9351
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- Citations: 1
Sacone da Silva Ferrreira AP, Pereira EC, Salles FJ, et al., 2019, Home-based and informal work exposes the families to high levels of potentially toxic elements, CHEMOSPHERE, Vol: 218, Pages: 319-327, ISSN: 0045-6535
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- Citations: 12
Peters K, Bradbury J, Bergmann S, et al., 2019, PhenoMeNal: Processing and analysis of metabolomics data in the cloud, GigaScience, Vol: 8, ISSN: 2047-217X
Background: Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data formats, data repositories and data analysis tools. However, the rapid progress has resulted in a mosaic of independent-and sometimes incompatible-analysis methods that are difficult to connect into a useful and complete data analysis solution. Findings: PhenoMeNal (Phenome and Metabolome aNalysis) is an advanced and complete solution to set up Infrastructure-as-a-Service (IaaS) that brings workflow-oriented, interoperable metabolomics data analysis platforms into the cloud. PhenoMeNal seamlessly integrates a wide array of existing open source tools which are tested and packaged as Docker containers through the project's continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi and Pachyderm. Conclusions: PhenoMeNal constitutes a keystone solution in cloud e-infrastructures available for metabolomics. PhenoMeNal is a unique and complete solution for setting up cloud e-infrastructures through easy-to-use web interfaces that can be scaled to any custom public and private cloud environment. By harmonizing and automating software installation and configuration and through ready-to-use scientific workflow user interfaces, PhenoMeNal has succeeded in providing scientists with workflow-driven, reproducible and shareable metabolomics data analysis platforms which are interfaced through standard data formats, representative datasets, versioned, and have been tested for reproducibility and interoperability. The elastic implementation of PhenoMeNal further allows easy adap
Sarigiannis DA, Handakas EJ, Kermenidou M, et al., 2017, Monitoring of air pollution levels related to Charilaos Trikoupis Bridge, SCIENCE OF THE TOTAL ENVIRONMENT, Vol: 609, Pages: 1451-1463, ISSN: 0048-9697
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- Citations: 16
Pino A, Chiarotti F, Calamandrei G, et al., 2017, Human biomonitoring data analysis for metals in an Italian adolescents cohort: An exposome approach, ENVIRONMENTAL RESEARCH, Vol: 159, Pages: 344-354, ISSN: 0013-9351
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- Citations: 26
Sarigiannis DA, Polanska K, Hanke W, et al., 2017, Pathway analysis of neurodevelopment toxicity due to prenatal combined exposure to heavy metals and phthalates, 53rd Congress of the European-Societies-of-Toxicology (EUROTOX), Publisher: ELSEVIER IRELAND LTD, Pages: S65-S65, ISSN: 0378-4274
Sarigiannis DA, Gotti A, Handakas E, et al., 2017, Informatics and data analytics to support exposome-based discovery: Part 2 - computational exposure biology, Applying Big Data Analytics in Bioinformatics and Medicine, Pages: 145-187, ISBN: 9781522526070
This chapter aims at outlining the current state of science in the field of computational exposure biology and in particular at demonstrating how the bioinformatics techniques and algorithms can be used to support the association between environmental exposures and human health and the deciphering of the molecular and metabolic pathways of induced toxicity related to environmental chemical stressors. Examples of the integrated bioinformatics analyses outlined herein are given concerning exposure to airborne chemical mixtures, to organic compounds frequently found in consumer goods, and to mixtures of organic chemicals and metals through multiple exposure pathways. Advanced bioinformatics are coupled with big data analytics to perform studies of exposome-wide associations with putative adverse health outcomes. In conclusion, the chapter gives the reader an outline of the available computational tools and paves the way towards the development of future comprehensive applications that are expected to support efficiently exposome research in the 21st century.
Sarigiannis DA, Karakitsios SP, Handakas E, et al., 2017, Informatics and data analytics to support exposome-based discovery: Part 1 - assessment of external and internal exposure, Applying Big Data Analytics in Bioinformatics and Medicine, Pages: 115-144, ISBN: 9781522526070
This chapter provides a comprehensive overview of the state of the art and beyond regarding modelling and data analytics towards refined external and internal exposure assessment, for elucidating the human exposome. This includes methods for more accurate measurement of personal exposure (using wearable sensors) and for extrapolation to larger population groups (agent-based modelling). A key component in the modern risk and health impact assessment is the translation of external exposure into internal exposure metrics, accounting for age, gender, genetic and route of exposure dependent differences. The applicability of biokinetics covering a large chemical space is enhanced using quantitative structure activity relationships, especially when the latter are estimated using machine learning tools. Finally, comprehensive biomonitoring data interpretation and assimilation are supported by exposure reconstruction algorithms coupled with biokinetics
Handakas E, Chapizanis D, Sarigiannis DA, et al., 2017, STUDY OF IN-VEHICLE PARTICULATE MATTER EXPOSURE IN THESSALONIKI, GREECE, 18th International Symposium on Environmental Pollution and its Impact on Life in the Mediterranean Region (MESAEP), Publisher: PARLAR SCIENTIFIC PUBLICATIONS (P S P), Pages: 327-331, ISSN: 1018-4619
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Handakas E, Manariotis I, Yannopoulos P, et al., 2017, DECISION SUPPORT TOOL FOR URBAN SOLID WASTE MANAGEMENT, 18th International Symposium on Environmental Pollution and its Impact on Life in the Mediterranean Region (MESAEP), Publisher: PARLAR SCIENTIFIC PUBLICATIONS (P S P), Pages: 413-420, ISSN: 1018-4619
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Sarigiannis DA, Karakitsios SP, Handakas E, et al., 2016, Integrated exposure and risk characterization of bisphenol-A in Europe, FOOD AND CHEMICAL TOXICOLOGY, Vol: 98, Pages: 134-147, ISSN: 0278-6915
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- Citations: 36
Sarigiannis DA, Karakitsios SP, Gotti A, et al., 2016, The exposome and Health Impact Assessment, Publisher: OXFORD UNIV PRESS, ISSN: 1101-1262
Sarigiannis D, Karakitsios S, Handakas E, et al., 2016, Exposome analysis of polyaromatic hydrocarbons, 52nd Congress of the European-Societies-of-Toxicology (EUROTOX), Publisher: ELSEVIER IRELAND LTD, Pages: S57-S57, ISSN: 0378-4274
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Sarigiannis D, Karakitsios S, Handakas E, et al., 2016, Exposome analysis of polyaromatic hydrocarbons, Pages: 385-387
This study demonstrates the use of the INTEGRA platform (coupling multi-source multi-route external exposure modeling with a generic PBTK for internal exposure modeling) for estimating exposure to PAHs under a variety of scenarios of key relevance to REACH and the petroleum industry. The objective of the INTEGRA project is to bring together all information necessary for assessing the source-to-dose continuum over the entire life cycle of substances covering an extensive chemical space through the use of QSARs. The major outcome of INTEGRA is a comprehensive computational platform that integrates multimedia environmental and micro-environmental fate, exposure and internal dose within a dynamic framework in time. The platform allows multimedia interactions across different spatial scales, taking into account environmental releases and related processes at global, regional and local scale, up to the level of personal microenvironment. Coupling seamlessly exposure models with refined computational tools for internal dosimetry transforms risk assessment of environmental chemicals since it allows risk characterization to be based on internal dosimetry metrics. In this way high throughput system data such as the ones generated by Tox21 in vitro testing can be used. This opens the way towards a higher level of assessment that incorporates refined exposure (tissue dosimetry) and toxicity testing (Biological Pathway Altering Dose â€" BPAD) associated to environmental contamination at different scales.
Sarigiannis D, Karakitsios S, Gotti A, et al., 2015, INTEGRA: Advancing risk assessment using internal dosimetry metrics, 51st Congress of the European-Societies-of-Toxicology (EUROTOX), Publisher: ELSEVIER IRELAND LTD, Pages: S110-S111, ISSN: 0378-4274
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- Citations: 4
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