Impact of occupational pesticide exposure on the human gut microbiome

The rising use of pesticides in modern agriculture has led to a shift in disease burden in which exposure to these chemicals plays an increasingly important role. The human gut microbiome, which is partially responsible for the biotransformation of xenobiotics, is also known to promote biotransformation of environmental pollutants. Understanding the effects of occupational pesticide exposure on the gut microbiome can thus provide valuable insights into the mechanisms underlying the impact of pesticide exposure on health. Here we investigate the impact of occupational pesticide exposure on human gut microbiome composition in 7198 participants from the Dutch Microbiome Project of the Lifelines Study. We used job-exposure matrices in combination with occupational codes to retrieve categorical and cumulative estimates of occupational exposures to general pesticides, herbicides, insecticides and fungicides. Approximately 4% of our cohort was occupationally exposed to at least one class of pesticides, with predominant exposure to multiple pesticide classes. Most participants reported long-term employment, suggesting a cumulative profile of exposure. We demonstrate that contact with insecticides, fungicides and a general “all pesticides” class was consistently associated with changes in the gut microbiome, showing significant associations with decreased alpha diversity and a differing beta diversity. We also report changes in the abundance of 39 different bacterial taxa upon exposure to the different pesticide classes included in this study. Together, the extent of statistically relevant associations between gut microbial changes and pesticide exposure in our findings highlights the impact of these compounds on the human gut microbiome.</p

Impact of occupational pesticide exposure on the human gut microbiome

The rising use of pesticides in modern agriculture has led to a shift in disease burden in which exposure to these chemicals plays an increasingly important role. The human gut microbiome, which is partially responsible for the biotransformation of xenobiotics, is also known to promote biotransformation of environmental pollutants. Understanding the effects of occupational pesticide exposure on the gut microbiome can thus provide valuable insights into the mechanisms underlying the impact of pesticide exposure on health. Here we investigate the impact of occupational pesticide exposure on human gut microbiome composition in 7198 participants from the Dutch Microbiome Project of the Lifelines Study. We used job-exposure matrices in combination with occupational codes to retrieve categorical and cumulative estimates of occupational exposures to general pesticides, herbicides, insecticides and fungicides. Approximately 4% of our cohort was occupationally exposed to at least one class of pesticides, with predominant exposure to multiple pesticide classes. Most participants reported long-term employment, suggesting a cumulative profile of exposure. We demonstrate that contact with insecticides, fungicides and a general “all pesticides” class was consistently associated with changes in the gut microbiome, showing significant associations with decreased alpha diversity and a differing beta diversity. We also report changes in the abundance of 39 different bacterial taxa upon exposure to the different pesticide classes included in this study. Together, the extent of statistically relevant associations between gut microbial changes and pesticide exposure in our findings highlights the impact of these compounds on the human gut microbiome.</p

Tracking Mental Wellbeing of Dutch Adolescents During the First Year of the COVID-19 Lockdown: A Longitudinal Study

Purpose: Adolescents might be susceptible to the effects of the COVID-19 lockdown. We assessed changes in mental wellbeing throughout the first year of the pandemic and compared these with prepandemic levels. Methods: This five-wave prospective study among Dutch adolescents aged 12–17 years used data collected before the pandemic (n = 224) (T0), in May (T1), July (T2), and October 2020 (T3), and in February 2021 (T4). Generalized estimating equations were used to assess the association between stringency of the lockdown with mental wellbeing. Results: Adolescents had a lower life satisfaction during the first full lockdown (T1) [adjusted β: −0.36, 95% confidence interval (CI): −0.58 to −0.13], during the partial lockdown (T3) (adjusted β: −0.37, 95% CI: −0.63 to −0.12), and during the second full lockdown (T4) (adjusted β: −0.79, 95% CI: −1.07 to −0.52) compared to before the pandemic (T0). Adolescents reported more internalizing symptoms during only the second full lockdown (T4) (adjusted β: 2.58, 95% CI: 0.41–4.75). During the pandemic [at T1 (adjusted β: 0.29, 95% CI: 0.20–0.38), T2 (adjusted β: 0.36, 95% CI: 0.26–0.46), T3 (adjusted β: 0.33, 95% CI: 0.22–0.45), and T4 (adjusted β: 0.20, 95% CI: 0.07–0.34)], adolescents reported a better psychosomatic health, partly attributable to less trouble falling asleep (p < .01). Discussion: The COVID-19 lockdown measures have had both a negative and positive impact on mental wellbeing of Dutch adolescents. However, mental wellbeing was most impacted during the second full lockdown compared to before the pandemic

Defining and Measuring Resilience in Children with a Chronic Disease: a Scoping Review

UNLABELLED: More than 25% of all children grow up with a chronic disease. They are at higher risk for developmental and psychosocial problems. However, children who function resiliently manage to adapt positively to these challenges. We aim to systematically review how resilience is defined and measured in children with a chronic disease. A search of PubMed, Cochrane, Embase, and PsycINFO was performed on December 9, 2022, using resilience, disease, and child/adolescent as search terms. Two reviewers independently screened articles for inclusion according to predefined criteria. Extraction domains included study characteristics, definition, and instruments assessing resilience outcomes, and resilience factors. Fifty-five out of 8766 articles were identified as relevant. In general, resilience was characterized as positive adaptation to adversity. The included studies assessed resilience by the outcomes of positive adaptation, or by resilience factors, or both. We categorized the assessed resilience outcomes into three groups: personal traits, psychosocial functioning, and disease-related outcomes. Moreover, myriad of resilience factors were measured, which were grouped into internal resilience factors (cognitive, social, and emotional competence factors), disease-related factors, and external factors (caregiver factors, social factors, and contextual factors). Our scoping review provides insight into the definitions and instruments used to measure resilience in children with a chronic disease. More knowledge is needed on which resilience factors are related to positive adaptation in specific illness-related challenges, which underlying mechanisms are responsible for this positive adaptation, and how these underlying mechanisms interact with one another. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42844-023-00092-2

Impact of occupational pesticide exposure on the human gut microbiome

The rising use of pesticides in modern agriculture has led to a shift in disease burden in which exposure to these chemicals plays an increasingly important role. The human gut microbiome, which is partially responsible for the biotransformation of xenobiotics, is also known to promote biotransformation of environmental pollutants. Understanding the effects of occupational pesticide exposure on the gut microbiome can thus provide valuable insights into the mechanisms underlying the impact of pesticide exposure on health. Here we investigate the impact of occupational pesticide exposure on human gut microbiome composition in 7198 participants from the Dutch Microbiome Project of the Lifelines Study. We used job-exposure matrices in combination with occupational codes to retrieve categorical and cumulative estimates of occupational exposures to general pesticides, herbicides, insecticides and fungicides. Approximately 4% of our cohort was occupationally exposed to at least one class of pesticides, with predominant exposure to multiple pesticide classes. Most participants reported long-term employment, suggesting a cumulative profile of exposure. We demonstrate that contact with insecticides, fungicides and a general "all pesticides" class was consistently associated with changes in the gut microbiome, showing significant associations with decreased alpha diversity and a differing beta diversity. We also report changes in the abundance of 39 different bacterial taxa upon exposure to the different pesticide classes included in this study. Together, the extent of statistically relevant associations between gut microbial changes and pesticide exposure in our findings highlights the impact of these compounds on the human gut microbiome

Multi-source data approach for personalized outcome prediction in lung cancer screening: update from the NELSON trial

Trials show that low-dose computed tomography (CT) lung cancer screening in long-term (ex-)smokers reduces lung cancer mortality. However, many individuals were exposed to unnecessary diagnostic procedures. This project aims to improve the efficiency of lung cancer screening by identifying high-risk participants, and improving risk discrimination for nodules. This study is an extension of the Dutch-Belgian Randomized Lung Cancer Screening Trial, with a focus on personalized outcome prediction (NELSON-POP). New data will be added on genetics, air pollution, malignancy risk for lung nodules, and CT biomarkers beyond lung nodules (emphysema, coronary calcification, bone density, vertebral height and body composition). The roles of polygenic risk scores and air pollution in screen-detected lung cancer diagnosis and survival will be established. The association between the AI-based nodule malignancy score and lung cancer will be evaluated at baseline and incident screening rounds. The association of chest CT imaging biomarkers with outcomes will be established. Based on these results, multisource prediction models for pre-screening and post-baseline-screening participant selection and nodule management will be developed. The new models will be externally validated. We hypothesize that we can identify 15-20% participants with low-risk of lung cancer or short life expectancy and thus prevent ~140,000 Dutch individuals from being screened unnecessarily. We hypothesize that our models will improve the specificity of nodule management by 10% without loss of sensitivity as compared to assessment of nodule size/growth alone, and reduce unnecessary work-up by 40-50%