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BACKGROUND: Many studies reported associations between long-term exposure to environmental factors and mortality; however, little is known on the combined effects of these factors and health. We aimed to evaluate the association between external exposome and all-cause mortality in large administrative and traditional adult cohorts in Europe.METHODS: Data from six administrative cohorts (Catalonia, Greece, Rome, Sweden, Switzerland and the Netherlands, totaling 27,913,545 subjects) and three traditional adult cohorts (CEANS-Sweden, EPIC-NL-the Netherlands, KORA-Germany, totaling 57,653 participants) were included. Multiple exposures were assigned at the residential addresses, and were divided into three a priori defined domains: (1) air pollution [fine particulate matter (PM 2.5), nitrogen dioxide (NO₂), black carbon (BC) and warm-season Ozone (warm-O 3)]; (2) land/built environment (Normalized Difference Vegetation Index-NDVI, impervious surfaces, and distance to water); (3) air temperature (cold- and warm-season mean and standard deviation). Each domain was synthesized through Principal Component Analysis (PCA), with the aim of explaining at least 80% of its variability. Cox proportional-hazards regression models were applied and the total risk of the external exposome was estimated through the Cumulative Risk Index (CRI). The estimates were adjusted for individual- and area-level covariates. RESULTS: More than 205 million person-years at risk and more than 3.2 million deaths were analyzed. In single-component models, IQR increases of the first principal component of the air pollution domain were associated with higher mortality [HRs ranging from 1.011 (95% CI: 1.005-1.018) for the Rome cohort to 1.076 (1.071-1.081) for the Swedish cohort]. In contrast, lower levels of the first principal component of the land/built environment domain, pointing to reduced vegetation and higher percentage of impervious surfaces, were associated with higher risks. Fi

The severity of COVID-19 is linked to an imbalanced immune response. The dysregulated metabolism of small molecules and bioactive lipids has also been associated with disease severity. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyze over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). This is the third publication in a series, and it reports the results of comprehensive lipidome profiling using targeted LC-MS/MS. We identified 1076 lipid features across 25 subclasses, including glycerophospholipids, sterols, glycerolipids, and sphingolipids, among which 531 lipid features were dramatically changed in the plasma of intensive care unit (ICU) patients compared to patients in the ward. Patients in the ICU showed 1.3-57-fold increases in ceramides, (lyso-)glycerophospholipids, diglycerides, triglycerides, and plasmagen phosphoethanolamines, and 1.3-2-fold lower levels of a cyclic lysophosphatidic acid, sphingosine-1-phosphates, sphingomyelins, arachidonic acid-containing phospholipids, lactosylceramide, and cholesterol esters compared to patients in the ward. Specifically, phosphatidylinositols (PIs) showed strong fatty acid saturation-dependent behavior, with saturated fatty acid (SFA)- and monosaturated fatty acid (MUFA)-derived PI decreasing and polystaturated (PUFA)-derived PI increasing. We also found ~4000 significant Spearman correlations between lipids and multiple clinical markers of immune response with |R| ≥ 0.35 and FDR corrected Q < 0.05. Except for lysophosphatidic acid, lysophospholipids were positively associated with the CD4 fraction of T cells, and the cytokines IL-8 and IL-18. In contrast, sphingosine-1-phosphates were negatively correlated with innate immune markers such as CRP and IL-6. Further indications of metabolic changes in moderate COVID-19 di

BACKGROUND: We evaluated the independent and joint effects of air pollution, land/built environment characteristics, and ambient temperature on all-cause mortality as part of the EXPANSE project.METHODS: We collected data from six administrative cohorts covering Catalonia, Greece, the Netherlands, Rome, Sweden, and Switzerland and three traditional cohorts in Sweden, the Netherlands, and Germany. Participants were linked to spatial exposure estimates derived from hybrid land use regression models and satellite data for: air pollution [fine particulate matter (PM 2.5), nitrogen dioxide (NO₂), black carbon (BC), warm season ozone (O 3)], land/built environment [normalized difference vegetation index (NDVI), distance to water, impervious surfaces], and ambient temperature (the mean and standard deviation of warm and cool season temperature). We applied Cox proportional hazard models accounting for several cohort-specific individual and area-level variables. We evaluated the associations through single and multiexposure models, and interactions between exposures. The joint effects were estimated using the cumulative risk index (CRI). Cohort-specific hazard ratios (HR) were combined using random-effects meta-analyses. RESULTS: We observed over 3.1 million deaths out of approximately 204 million person-years. In administrative cohorts, increased exposure to PM 2.5, NO 2, and BC was significantly associated with all-cause mortality (pooled HRs: 1.054, 1.033, and 1.032, respectively). We observed an adverse effect of increased impervious surface and mean season-specific temperature, and a protective effect of increased O 3, NDVI, distance to water, and temperature variation on all-cause mortality. The effects of PM 2.5 were higher in areas with lower (10th percentile) compared to higher (90th percentile) NDVI levels [pooled HRs: 1.054 (95% confidence interval (CI) 1.030-1.079) vs. 1.038 (95% CI 0.964-1.118)]. A similar pattern was observed for NO 2. The CRI

Glyphosate, a controversial herbicide, has been approved for use in the European Union for another 10 years despite uncertainty over whether it increases the risk of neurodegenerative disorders such as Parkinson disease. We call for new approaches to assessing the neurotoxicity of glyphosate and other pesticides and improving their regulation.

Correction to: Leukemia https://doi.org/10.1038/s41375-022-01711-0, published online 22 October 2022

Background: Although per- and polyfluoroalkyl substances (PFAS) exposure is a potential contributor to the increasing thyroid cancer trend, limited studies have investigated the association between PFAS exposure and thyroid cancer in human populations. We therefore investigated associations between plasma PFAS levels and thyroid cancer diagnosis using a nested case-control study of patients with thyroid cancer with plasma samples collected at/before cancer diagnosis. Methods: 88 patients with thyroid cancer using diagnosis codes and 88 healthy (non-cancer) controls pair-matched on sex, age (±5 years), race/ethnicity, body mass index, smoking status, and year of sample collection were identified in the BioMe population (a medical record-linked biobank at the Icahn School of Medicine at Mount Sinai in New York); 74 patients had papillary thyroid cancer. Eight plasma PFAS were measured using untargeted analysis with liquid chromatography-high resolution mass spectrometry and suspect screening. Associations between individual PFAS levels and thyroid cancer were evaluated using unconditional logistic regression models to estimate adjusted odds ratios (ORadj) and 95% confidence intervals (CI). Findings: There was a 56% increased rate of thyroid cancer diagnosis per doubling of linear perfluorooctanesulfonic acid (n-PFOS) intensity (ORadj, 1.56, 95% CI: 1.17–2.15, P = 0.004); results were similar when including patients with papillary thyroid cancer only (ORadj, 1.56, 95% CI: 1.13–2.21, P = 0.009). This positive association remained in subset analysis investigating exposure timing including 31 thyroid cancer cases diagnosed ≥1 year after plasma sample collection (ORadj, 2.67, 95% CI: 1.59–4.88, P < 0.001). Interpretation: This study reports associations between exposure to PFAS and increased rate of (papillary) thyroid cancer. Thyroid cancer risk from PFAS exposure is a global concern given the prevalence of PFAS exposure.

BACKGROUND: Work circumstances can substantially negatively impact health. To explore this, large occupational cohorts of free-text job descriptions are manually coded and linked to exposure. Although several automatic coding tools have been developed, accurate exposure assessment is only feasible with human intervention.METHODS: We developed OPERAS, a customizable decision support system for epidemiological job coding. Using 812,522 entries, we developed and tested classification models for the Professions et Catégories Socioprofessionnelles (PCS)2003, Nomenclature d'Activités Française (NAF)2008, International Standard Classifications of Occupation (ISCO)-88, and ISCO-68. Each code comes with an estimated correctness measure to identify instances potentially requiring expert review. Here, OPERAS' decision support enables an increase in efficiency and accuracy of the coding process through code suggestions. Using the Formaldehyde, Silica, ALOHA, and DOM job-exposure matrices, we assessed the classification models' exposure assessment accuracy.RESULTS: We show that, using expert-coded job descriptions as gold standard, OPERAS realized a 0.66-0.84, 0.62-0.81, 0.60-0.79, and 0.57-0.78 inter-coder reliability (in Cohen's Kappa) on the first, second, third, and fourth coding levels, respectively. These exceed the respective inter-coder reliability of expert coders ranging 0.59-0.76, 0.56-0.71, 0.46-0.63, 0.40-0.56 on the same levels, enabling a 75.0-98.4% exposure assessment accuracy and an estimated 19.7-55.7% minimum workload reduction.CONCLUSIONS: OPERAS secures a high degree of accuracy in occupational classification and exposure assessment of free-text job descriptions, substantially reducing workload. As such, OPERAS significantly outperforms both expert coders and other current coding tools. This enables large-scale, efficient, and effective exposure assessment securing healthy work conditions.

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.

Chronic lymphocytic leukemia (CLL) is preceded by monoclonal B-cell lymphocytosis (MBL), a potential CLL precursor state which can be detected in up to 17% in aged individuals. Recently, we described significant B-cell receptor immunoglobulin heavy chain (BCR IGH) gene repertoire skewing and clonotypic evolution up to 22 years before CLL diagnosis. However, pathobiological drivers during the earliest stages of MBL development remain incompletely characterized. In this study, we utilized the EuroClonality-NDC panel to sequence recurrently mutated genes in CLL in 39 peripheral blood samples from 16 CLL patients sampled up to 16 years prior to diagnosis. CLL diagnosis ranged from 5 months to 16 years after first blood sampling. Of 16 CLL patients, 8 (50%) presented with variants of interest in genes recurrently mutated in CLL such as NOTCH1, ATM, and SF3B1 . ATM variants and the IGLV3-21R110 mutation were present from the early stages of (pre)MBL development, while NOTCH1, SF3B1, and XPO1 variants arose closer to diagnosis. We additionally detected variants in FAT1 and PLCG2 as early as 10 years prior to CLL diagnosis. Overall, our data shows specific genetic drivers of CLL are associated with early and late stages of CLL development.

INTRODUCTION: Only a small number of risk factors for pancreatic ductal adenocarcinoma (PDAC) has been established. Several studies identified a role of epigenetics and of deregulation of DNA methylation. DNA methylation is variable across a lifetime and in different tissues; nevertheless, its levels can be regulated by genetic variants like methylation quantitative trait loci (mQTLs), which can be used as a surrogate.MATERIALS AND METHODS: We scanned the whole genome for mQTLs and performed an association study in 14 705 PDAC cases and 246 921 controls. The methylation data were obtained from whole blood and pancreatic cancer tissue through online databases. We used the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium genome-wide association study (GWAS) data as discovery phase and the Pancreatic Disease Research consortium, the FinnGen project and the Japan Pancreatic Cancer Research consortium GWAS as replication phase.RESULTS: The C allele of 15q26.1-rs12905855 showed an association with a decreased risk of PDAC (OR=0.90, 95% CI 0.87 to 0.94, p=4.93×10 -8 in the overall meta-analysis), reaching genome-level statistical significance. 15q26.1-rs12905855 decreases the methylation of a 'C-phosphate-G' (CpG) site located in the promoter region of the RCCD1 antisense ( RCCD1-AS1) gene which, when expressed, decreases the expression of the RCC1 domain-containing ( RCCD1) gene (part of a histone demethylase complex). Thus, it is possible that the rs12905855 C-allele has a protective role in PDAC development through an increase of RCCD1 gene expression, made possible by the inactivity of RCCD1-AS1. CONCLUSION: We identified a novel PDAC risk locus which modulates cancer risk by controlling gene expression through DNA methylation.

Nightshift work disturbs the circadian rhythm, which might contribute to the development of cardio-metabolic disorders. In this cross-sectional study, we aimed to gain insight into perturbations of disease relevant metabolic pathways due to nightshift work. We characterized the metabolic profiles of 237 female nurses and paramedic staff participating in the Klokwerk study using the Nightingale Health platform. We performed analyses on plasma levels of 225 metabolites, including cholesterol, triglycerides, fatty acids, and amino acids. Using both principal component- and univariate-regression, we compared metabolic profiles of nightshift workers to metabolic profiles from workers that did not work night shifts (defined as day workers). We also assessed whether differential effects were observed between recently started versus more experienced workers. Within the group of nightshift workers, we compared metabolic profiles measured right after a nightshift with metabolic profiles measured on a day when no nightshift work was conducted. We observed evidence for an impact of nightshift work on the presence of unfavorable fatty acid profiles in blood. Amongst the fatty acids, effects were most prominent for PUFA/FA ratios (consistently decreased) and SFA/FA ratios (consistently elevated). This pattern of less favorable fatty acid profiles was also observed in samples collected directly after a night shift. Amino acid levels (histidine, glutamine, isoleucine, and leucine) and lipoproteins (especially HDL-cholesterol, VLDL-cholesterol, and triglycerides) were elevated when comparing nightshift workers with day workers. Amino acid levels were decreased in the samples that were collected directly after working a nightshift (compared to levels in samples that were collected during a non-nightshift period). The observed effects were generally more pronounced in samples collected directly after the nightshift and among recently started compared to more experienced nightshift

BACKGROUND: COPD and adult-onset asthma (AOA) are the most common noncommunicable respiratory diseases. To improve early identification and prevention, an overview of risk factors is needed. We therefore aimed to systematically summarise the nongenetic (exposome) risk factors for AOA and COPD. Additionally, we aimed to compare the risk factors for COPD and AOA.METHODS: In this umbrella review, we searched PubMed for articles from inception until 1 February 2023 and screened the references of relevant articles. We included systematic reviews and meta-analyses of observational epidemiological studies in humans that assessed a minimum of one lifestyle or environmental risk factor for AOA or COPD.RESULTS: In total, 75 reviews were included, of which 45 focused on risk factors for COPD, 28 on AOA and two examined both. For asthma, 43 different risk factors were identified while 45 were identified for COPD. For AOA, smoking, a high body mass index (BMI), wood dust exposure and residential chemical exposures, such as formaldehyde exposure or exposure to volatile organic compounds, were amongst the risk factors found. For COPD, smoking, ambient air pollution including nitrogen dioxide, a low BMI, indoor biomass burning, childhood asthma, occupational dust exposure and diet were amongst the risk factors found.CONCLUSIONS: Many different factors for COPD and asthma have been found, highlighting the differences and similarities. The results of this systematic review can be used to target and identify people at high risk for COPD or AOA.

BACKGROUND: The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson's Disease (PD) remains limited.OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts.METHODS: Within the project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (PM 2.5), nitrogen dioxide (NO 2), black carbon (BC), and ozone (O 3), as well as 8 PM 2.5 components (copper, iron, potassium, nickel, sulphur, silicon, vanadium, zinc), for 2010 were estimated using Europe-wide hybrid land use regression models. PD mortality was defined as underlying cause of death being either PD, secondary Parkinsonism, or dementia in PD. We applied Cox proportional hazard models to investigate the associations between air pollution and PD mortality, adjusting for potential confounders. RESULTS: Of 271,720 cohort participants, 381 died from PD during 19.7 years of follow-up. In single-pollutant analyses, we observed positive associations between PD mortality and PM 2.5 (hazard ratio per 5 µg/m 3: 1.25; 95% confidence interval: 1.01-1.55), NO 2 (1.13; 0.95-1.34 per 10 µg/m 3), and BC (1.12; 0.94-1.34 per 0.5 × 10 -5m -1), and a negative association with O 3 (0.74; 0.58-0.94 per 10 µg/m 3). Associations of PM 2.5, NO 2, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM 2.5 remained robust when adjusted for NO 2 (1.24; 0.95-1.62) or BC (1.28; 0.96-1.71), whereas associations with NO 2 or BC attenuated to null. O 3 associations remained negative, but no longer statistically significant in models with PM 2.5. We detected suggestive positive associations with the potassium component of P