Développement d’outils utilisant la surveillance biologique pour évaluer l’exposition et les risques pour la santé : application au méthylmercure et au sélénium

Dans une perspective d’analyse des risques pour la santé publique, l’estimation de l’exposition revêt une importance capitale. Parmi les approches existantes d’estimation de l’exposition, l’utilisation d’outils, tels que des questionnaires alimentaires, la modélisation toxicocinétique ou les reconstructions de doses, en complément de la surveillance biologique, permet de raffiner les estimations, et ainsi, de mieux caractériser les risques pour la santé. Ces différents outils et approches ont été développés et appliqués à deux substances d’intérêt, le méthylmercure et le sélénium en raison des effets toxiques bien connus du méthylmercure, de l’interaction entre le méthylmercure et le sélénium réduisant potentiellement ces effets toxiques, et de l’existence de sources communes via la consommation de poisson. Ainsi, l’objectif général de cette thèse consistait à produire des données cinétiques et comparatives manquantes pour la validation et l’interprétation d’approches et d’outils d’évaluation de l’exposition au méthylmercure et au sélénium. Pour ce faire, l’influence du choix de la méthode d’évaluation de l’exposition au méthylmercure a été déterminée en comparant les apports quotidiens et les risques pour la santé estimés par différentes approches (évaluation directe de l’exposition par la surveillance biologique combinée à la modélisation toxicocinétique ou évaluation indirecte par questionnaire alimentaire). D’importantes différences entre ces deux approches ont été observées : les apports quotidiens de méthylmercure estimés par questionnaires sont en moyenne six fois plus élevés que ceux estimés à l’aide de surveillance biologique et modélisation. Ces deux méthodes conduisent à une appréciation des risques pour la santé divergente puisqu’avec l’approche indirecte, les doses quotidiennes estimées de méthylmercure dépassent les normes de Santé Canada pour 21 des 23 volontaires, alors qu’avec l’approche directe, seulement 2 des 23 volontaires sont susceptibles de dépasser les normes. Ces différences pourraient être dues, entre autres, à des biais de mémoire et de désirabilité lors de la complétion des questionnaires. En outre, l’étude de la distribution du sélénium dans différentes matrices biologiques suite à une exposition non alimentaire (shampoing à forte teneur en sélénium) visait, d’une part, à étudier la cinétique du sélénium provenant de cette source d’exposition et, d’autre part, à évaluer la contribution de cette source à la charge corporelle totale. Un suivi des concentrations biologiques (sang, urine, cheveux et ongles) pendant une période de 18 mois chez des volontaires exposés à une source non alimentaire de sélénium a contribué à mieux expliciter les mécanismes de transfert du sélénium du site d’absorption vers le sang (concomitance des voies régulées et non régulées). Ceci a permis de montrer que, contrairement au méthylmercure, l’utilisation des cheveux comme biomarqueur peut mener à une surestimation importante de la charge corporelle réelle en sélénium en cas de non contrôle de facteurs confondants tels que l’utilisation de shampoing contenant du sélénium. Finalement, une analyse exhaustive des données de surveillance biologique du sélénium issues de 75 études publiées dans la littérature a permis de mieux comprendre la cinétique globale du sélénium dans l’organisme humain. En particulier, elle a permis le développement d’un outil reliant les apports quotidiens et les concentrations biologiques de sélénium dans les différentes matrices à l’aide d’algorithmes mathématiques. Conséquemment, à l’aide de ces données cinétiques exprimées par un système d’équations logarithmiques et de leur représentation graphique, il est possible d’estimer les apports quotidiens chez un individu à partir de divers prélèvements biologiques, et ainsi, de faciliter la comparaison d’études de surveillance biologique du sélénium utilisant des biomarqueurs différents. L’ensemble de ces résultats de recherche montre que la méthode choisie pour évaluer l’exposition a un impact important sur les estimations des risques associés. De plus, les recherches menées ont permis de mettre en évidence que le sélénium non alimentaire ne contribue pas de façon significative à la charge corporelle totale, mais constitue un facteur de confusion pour l’estimation de la charge corporelle réelle en sélénium. Finalement, la détermination des équations et des coefficients reliant les concentrations de sélénium entre différentes matrices biologiques, à l’aide d’une vaste base de données cinétiques, concourt à mieux interpréter les résultats de surveillance biologique.In the context of public health risk analysis, exposure assessments are of primary importance. Among the approaches used to assess exposure, tools such as food questionnaires, toxicokinetic modelling or reverse dosimetry, combined with biomonitoring allow to refine exposure estimates as well as toxicological health risk estimates. Such approaches and tools have been developed and applied to two contaminants of interest - methylmercury and selenium - due to the known toxic effect of methylmercury, the interaction between methylmercury and selenium which reduces its toxicity, and common sources of exposure through fish consumption. Hence, the main objective of this thesis consists in producing kinetic and comparative data for the validation and the interpretation of approaches and tools used for exposure assessment to methylmercury and selenium. These data are currently lacking. To achieve this goal, the influence of the method used to assess methylmercury exposure was determined by comparing daily intakes and health risk estimated with different approaches (direct exposure assessment using biomonitoring and toxicokinetic modelling or indirect exposure assessment using food questionnaires). Important discrepancies between these two methods have been observed: the questionnaire-based intakes are higher than modeled intakes higher by a six-fold factor. These two approaches lead to divergent health risk estimates considering that, with the direct exposure assessment, methylmercury daily intakes are above Health Canada guidelines in most cases (21 of 23 volunteers) while only 2 volunteers have intakes above guidelines when using the direct approach. Among possible reasons, discrepancies could be due to recall and desirability bias related to the completion of food questionnaire. Subsequently, the study of selenium distribution in different biological matrices following a non-dietary exposure (selenium-containing shampoo) aimed to study the kinetic of the selenium originating from this exposure as well as assess the contribution of this source to the total Se body burden. The time courses of selenium biological concentration in blood, urine, hair and nails over 18 months for volunteers exposed to a non-dietary source of selenium contributed to better elucidate the mechanisms of selenium transfer to blood (concurrency of regulated and non-regulated pathways). This study also confirms that, unlike methylmercury, the use of hair as a biomarker can lead to a significant overestimate of the actual selenium body burden if confounding factors such as the use of selenium-containing shampoo are not controlled. In addition, a detailed analysis of selenium biomonitoring data from 75 published studies in the literature was conducted in order to better understand the kinetic of selenium in the human body. In particular, this analysis led to the development of a tool that relates daily intakes and selenium concentrations in biological matrices using mathematical algorithms. Consequently, by using these kinetic data expressed as a system of logarithmic equations and graphical representations, it enables the assessment of daily intakes in an individual from various biological sampling. Moreover, it facilitates the comparison of selenium biomonitoring data from studies using different biomarkers. Overall, these results show that the approach used to assess exposure has a sound impact on health risk estimates. Research showed that selenium from a non-dietary source does not contribute significantly to total body burden, however it constitutes a confounding factor. Finally, the determination of equations and coefficients using an extensive kinetic database relating selenium concentrations from different biological matrices helps to better interpret biomonitoring data

Psychosocial factors, health behaviors and risk of cancer incidence:Testing interaction and effect modification in an individual participant data meta-analysis

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.</p

Psychosocial factors, health behaviors and risk of cancer incidence:Testing interaction and effect modification in an individual participant data meta-analysis

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.</p

Depression, anxiety, and the risk of cancer:An individual participant data meta-analysis

Background: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. Methods: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). Results: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06–1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04–1.23). Conclusions: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. Preregistration number: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.</p

Psychosocial factors and cancer incidence (PSY-CA):Protocol for individual participant data meta-analyses

OBJECTIVES: Psychosocial factors have been hypothesized to increase the risk of cancer. This study aims (1) to test whether psychosocial factors (depression, anxiety, recent loss events, subjective social support, relationship status, general distress, and neuroticism) are associated with the incidence of any cancer (any, breast, lung, prostate, colorectal, smoking-related, and alcohol-related); (2) to test the interaction between psychosocial factors and factors related to cancer risk (smoking, alcohol use, weight, physical activity, sedentary behavior, sleep, age, sex, education, hormone replacement therapy, and menopausal status) with regard to the incidence of cancer; and (3) to test the mediating role of health behaviors (smoking, alcohol use, weight, physical activity, sedentary behavior, and sleep) in the relationship between psychosocial factors and the incidence of cancer.METHODS: The psychosocial factors and cancer incidence (PSY-CA) consortium was established involving experts in the field of (psycho-)oncology, methodology, and epidemiology. Using data collected in 18 cohorts (N = 617,355), a preplanned two-stage individual participant data (IPD) meta-analysis is proposed. Standardized analyses will be conducted on harmonized datasets for each cohort (stage 1), and meta-analyses will be performed on the risk estimates (stage 2).CONCLUSION: PSY-CA aims to elucidate the relationship between psychosocial factors and cancer risk by addressing several shortcomings of prior meta-analyses.</p

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis

BACKGROUND: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. METHODS: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). RESULTS: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06-1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04-1.23). CONCLUSIONS: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. PREREGISTRATION NUMBER: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677

Chapitre 11. Toxicologie

International audiencePlan du chapitre : 11.1. Concepts fondamentaux de toxicologie : continuum exposition-effet ; 11.1.1. Quelques définitions ; 11.1.2. Intoxication aiguë et intoxication chronique ; 11.1.3. Toxicité locale et toxicité systémique ; 11.1.4. Toxicocinétique ; 11.1.5. Toxicodynamique ; 11.2. Facteurs modifiants la toxicité ; 11.2.1. Facteurs endogènes susceptibles d’influencer les paramètres toxicocinétiques : âge, sexe et habitudes de vie ; 11.2.2. Facteurs endogènes génétiques : les polymorphismes ; 11.2.3. Interactions 11.3. Méthodes et modèles de prédiction de la toxicité ; 11.3.1. Toxicologie clinique ; 11.3.2. Essais chez les volontaires humains ; 11.3.3. Toxicologie expérimentale ; 11.3.4. Les méthodes d’études ; 11.3.5. Interprétation et modélisation ; 11.4. Expérimentation et éthique ; 11.4.1. En expérimentation humaine ; 11.4.2. En expérimentation animal.e ; 11.5. Perspective

Biomonitoring equivalents for perfluorooctanoic acid (PFOA) for the interpretation of biomonitoring data

Background: Perfluorooctanoic acid (PFOA) is detected in the blood of virtually all biomonitoring study participants. Assessing health risks associated with blood PFOA levels is challenging because exposure guidance values (EGVs) are typically expressed in terms of external dose. Biomonitoring equivalents (BEs) consistent with EGVs could facilitate health-based interpretations. Objective: To i) derive BEs for serum/plasma PFOA corresponding to non-cancer EGVs of the U.S. Environmental Protection Agency (U.S. EPA), the Agency for Toxic Substances and Disease Registry (ATSDR) and Health Canada, and ii) compare with PFOA concentrations from national biomonitoring surveys. Methods: Starting from EGV points of departure, we employed pharmacokinetic data/models and uncertainty factors. Points of departure in pregnant rodents (U.S. EPA 2016, ATSDR) were converted into fetus and pup serum concentrations using an animal gestation/lactation pharmacokinetic model, and equivalent human fetus and child concentrations were converted into BEs in maternal serum using a human gestation/lactation model. The point of departure in adult rodents (Health Canada) was converted into a BE using experimental data. For epidemiology-based EGVs (U.S. EPA 2023, draft), BEs were directly based on epidemiological data or derived using a human gestation/lactation pharmacokinetic model. BEs were compared with Canadian/U.S. biomonitoring data. Results: Non-cancer BEs (ng/mL) were 684 (Health Canada, 2018) or ranged from 15 to 29 (U.S. EPA, 2016), 6–10 (ATSDR, 2021) and 0.2–0.8 (U.S. EPA, 2023, draft). Ninety-fifth percentiles of serum levels from the 2018–2019 Canadian Health Measures Survey (CHMS) and the 2017–2018 National Health and Nutrition Examination Survey (NHANES) were slightly below the BE for ATSDR, and geometric means were above the non-cancer BEs for the U.S. EPA (2023, draft). Conclusion: Non-cancer BEs spanned three orders of magnitude. The lowest BEs were for EGVs based on developmental endpoints in epidemiological studies. Concentrations in Canadian/U.S. national surveys were higher than or close to BEs for the most recent non-cancer EGVs

Chapitre 14. Évaluation des risques sanitaires

International audienceL’évaluation des risques décrite dans ce chapitre, au sens de Risk Assessment défini en 1983 par le National Research Council (NRC, 1983) est une analyse scientifique basée sur le recueil de données et la modélisation. Ses résultats sont des expressions qualitatives ou quantitatives de l’intensité et de la vraisemblance de dommages, causés par une exposition. L’évaluation s’effectue au niveau populationnel, car il ne s’agit pas de prédictions individuelles. Elle est la première composante de l’analyse des risques, qui comprend également la gestion et la communication des risques (OMS, 2021). Cet outil mobilise et organise les connaissances existantes pour aider à la décision publique, répondre à une question spécifique, guider la mise en œuvre de politiques publiques, ou la mise en place de réglementations protectrices de la santé.Si ce chapitre traite des composés chimiques, les concepts, principes et étapes de la démarche s’appliquent aussi aux risques physiques et biologiques. Après une présentation de ses objectifs, ce chapitre abordera les raisons d’être et les concepts de la démarche d’évaluation des risques sanitaires, puis en détaillera les étapes : formulation du problème, identification des dangers, établissement de la relation dose-réponse, évaluation des expositions et enfin caractérisation des risques et des incertitudes

Validation of breast cancer risk assessment tools on a French-Canadian population-based cohort

Objectives Evaluate the accuracy of the Breast Cancer Risk Assessment Tool (BCRAT), International Breast Cancer Intervention Study risk evaluation tool (IBIS), Polygenic Risk Scores (PRS) and combined scores (BCRAT+PRS and IBIS +PRS) to predict the occurrence of invasive breast cancers at 5 years in a French-Canadian population.Design Population-based cohort study.Setting We used the population-based cohort CARTaGENE, composed of 43 037 Quebec residents aged between 40 and 69 years and broadly representative of the population recorded on the Quebec administrative health insurance registries.Participants 10 200 women recruited in 2009–2010 were included for validating BCRAT and IBIS and 4555 with genetic information for validating the PRS and combined scores.Outcome measures We computed the absolute risks of breast cancer at 5 years using BCRAT, IBIS, four published PRS and combined models. We reported the overall calibration performance, goodness-of-fit test and discriminatory accuracy.Results 131 (1.28%) women developed a breast cancer at 5 years for validating BCRAT and IBIS and 58 (1.27%) for validating PRS and combined scores. Median follow-up was 5 years. BCRAT and IBIS had an overall expected-to-observed ratio of 1.01 (0.85–1.19) and 1.02 (0.86–1.21) but with significant differences when partitioning by risk groups (p&lt;0.05). IBIS’ c-index was significantly higher than BCRAT (63.42 (59.35–67.49) vs 58.63 (54.05–63.21), p=0.013). PRS scores had a global calibration around 0.82, with a CI including one, and non-significant goodness-of-fit tests. PRS’ c-indexes were non-significantly higher than BCRAT and IBIS, the highest being 64.43 (58.23–70.63). Combined models did not improve the results.Conclusions In this French-Canadian population-based cohort, BCRAT and IBIS have good mean calibration that could be improved for risk subgroups, and modest discriminatory accuracy. Despite this modest discriminatory power, these tools can be of interest for primary care physicians for delivering a personalised message to their high-risk patients, regarding screening and lifestyle counselling