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Air pollution has been shown to significantly impact human health including cancer. Gastric and upper aerodigestive tract (UADT) cancers are common and increased risk has been associated with smoking and occupational exposures. However, the association with air pollution remains unclear. We pooled European subcohorts (N = 287,576 participants for gastric and N = 297,406 for UADT analyses) and investigated the association between residential exposure to fine particles (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone in the warm season (O3w) with gastric and UADT cancer. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. During 5,305,133 and 5,434,843 person-years, 872 gastric and 1139 UADT incident cancer cases were observed, respectively. For gastric cancer, we found no association with PM2.5, NO2 and BC while for UADT the hazard ratios (95% confidence interval) were 1.15 (95% CI: 1.00-1.33) per 5 µg/m3 increase in PM2.5, 1.19 (1.08-1.30) per 10 µg/m3 increase in NO2, 1.14 (1.04-1.26) per 0.5 × 10-5 m-1 increase in BC and 0.81 (0.72-0.92) per 10 µg/m3 increase in O3w. We found no association between long-term ambient air pollution exposure and incidence of gastric cancer, while for long-term exposure to PM2.5, NO2 and BC increased incidence of UADT cancer was observed.
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Poluentes Atmosféricos , Poluição do Ar , Neoplasias Gástricas , Humanos , Material Particulado/efeitos adversos , Material Particulado/análise , Dióxido de Nitrogênio/efeitos adversos , Neoplasias Gástricas/epidemiologia , Neoplasias Gástricas/etiologia , Incidência , Exposição Ambiental/efeitos adversos , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análiseRESUMO
Advanced glycation end-products (AGEs), formed endogenously or obtained exogenously from diet, may contribute to chronic inflammation, intracellular signaling alterations, and pathogenesis of several chronic diseases including colorectal cancer (CRC). However, the role of AGEs in CRC survival is less known. The associations of pre-diagnostic circulating AGEs and their soluble receptor (sRAGE) with CRC-specific and overall mortality were estimated using multivariable-adjusted Cox proportional hazards regression among 1369 CRC cases in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Concentrations of major plasma AGEs, Nε-[carboxy-methyl]lysine (CML), Nε-[carboxy-ethyl]lysine (CEL) and Nδ-[5-hydro-5-methyl-4-imidazolon-2-yl]-ornithine (MG-H1), were measured using ultra-performance liquid chromatography mass-spectrometry. sRAGE was assessed by enzyme-linked immunosorbent assay. Over a mean follow-up period of 96 months, 693 deaths occurred of which 541 were due to CRC. Individual and combined AGEs were not statistically significantly associated with CRC-specific or overall mortality. However, there was a possible interaction by sex for CEL (Pinteraction = .05). Participants with higher sRAGE had a higher risk of dying from CRC (HRQ5vs.Q1 = 1.67, 95% CI: 1.21-2.30, Ptrend = .02) or any cause (HRQ5vs.Q1 = 1.38, 95% CI: 1.05-1.83, Ptrend = .09). These associations tended to be stronger among cases with diabetes (Pinteraction = .03) and pre-diabetes (Pinteraction <.01) before CRC diagnosis. Pre-diagnostic AGEs were not associated with CRC-specific and overall mortality in individuals with CRC. However, a positive association was observed for sRAGE. Our findings may stimulate further research on the role of AGEs and sRAGE in survival among cancer patients with special emphasis on potential effect modifications by sex and diabetes.
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Chronotype may affect tolerance for circadian disruption induced by shift work. This study examines the association between chronotype, self-reported sleep timing, shift type preference, and sleep problems among nurses, and studies chronotype stability over time. The study included 37,731 Dutch female nurses who completed a baseline (2011) and follow-up questionnaire (2017), with information on shift work (e.g., job history, shift type preference [collected in 2017 only]), and sleep characteristics (e.g., chronotype, preferred sleep-wake time in a work-free period [collected in 2017 only], and sleep problems between working days according to Medical Outcomes Study-Sleep Problem Index II [MOS-SPI-II]). The association between chronotype and sleep timing was examined using (age-adjusted) linear regression. Associations between chronotype and shift type preference and sleep problems (MOS-SPI-II >30) were examined using ordered logistic and Poisson regression, respectively. With later chronotype, midsleep time increased (definite evening vs. intermediate types [reference]: ß = 55 min, 95% confidence interval [95% CI]: 54-55), the odds ratio (OR) for 1-point increase in preference for night (2.68; 95% CI: 2.48-2.90) and evening shifts increased (OR 2.20; 95% CI: 2.03-2.38), while the odds for day (OR 0.17; 95% CI: 0.16-0.18) and morning shifts (OR 0.22; 95% CI: 0.21-0.24) decreased. Intermediate chronotype was associated with fewer sleep problems (median MOS-SPI-II = 27.2, p < 0.01), compared with definite morning (28.9) and evening types (31.7). This study shows that chronotype is associated with sleep-wake times in a work-free period, shift type preference, and sleep problems in nurses. Future studies on the association of shift work-induced circadian disruption and health outcomes should therefore consider chronotype as effect-modifier.
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Air pollution exposure is typically assessed at the front door where people live in large-scale epidemiological studies, overlooking individuals' daily mobility out-of-home. However, there is limited evidence that incorporating mobility data into personal air pollution assessment improves exposure assessment compared to home-based assessments. This study aimed to compare the agreement between mobility-based and home-based assessments with personal exposure measurements. We measured repeatedly particulate matter (PM2.5) and black carbon (BC) using a sample of 41 older adults in the Netherlands. In total, 104 valid 24 h average personal measurements were collected. Home-based exposures were estimated by combining participants' home locations and temporal-adjusted air pollution maps. Mobility-based estimates of air pollution were computed based on smartphone-based tracking data, temporal-adjusted air pollution maps, indoor-outdoor penetration, and travel mode adjustment. Intraclass correlation coefficients (ICC) revealed that mobility-based estimates significantly improved agreement with personal measurements compared to home-based assessments. For PM2.5, agreement increased by 64% (ICC: 0.39-0.64), and for BC, it increased by 21% (ICC: 0.43-0.52). Our findings suggest that adjusting for indoor-outdoor pollutant ratios in mobility-based assessments can provide more valid estimates of air pollution than the commonly used home-based assessments, with no added value observed from travel mode adjustments.
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Poluentes Atmosféricos , Poluição do Ar , Exposição Ambiental , Material Particulado , Humanos , Material Particulado/análise , Poluentes Atmosféricos/análise , Países Baixos , Monitoramento Ambiental/métodos , Masculino , Feminino , IdosoRESUMO
This randomized crossover study investigated the metabolic and mRNA alterations associated with exposure to high and low traffic-related air pollution (TRAP) in 50 participants who were either healthy or were diagnosed with chronic pulmonary obstructive disease (COPD) or ischemic heart disease (IHD). For the first time, this study combined transcriptomics and serum metabolomics measured in the same participants over multiple time points (2 h before, and 2 and 24 h after exposure) and over two contrasted exposure regimes to identify potential multiomic modifications linked to TRAP exposure. With a multivariate normal model, we identified 78 metabolic features and 53 mRNA features associated with at least one TRAP exposure. Nitrogen dioxide (NO2) emerged as the dominant pollutant, with 67 unique associated metabolomic features. Pathway analysis and annotation of metabolic features consistently indicated perturbations in the tryptophan metabolism associated with NO2 exposure, particularly in the gut-microbiome-associated indole pathway. Conditional multiomics networks revealed complex and intricate mechanisms associated with TRAP exposure, with some effects persisting 24 h after exposure. Our findings indicate that exposure to TRAP can alter important physiological mechanisms even after a short-term exposure of a 2 h walk. We describe for the first time a potential link between NO2 exposure and perturbation of the microbiome-related pathways.
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Poluentes Atmosféricos , Poluição do Ar , Microbioma Gastrointestinal , Humanos , Masculino , Londres , Feminino , Pessoa de Meia-Idade , Estudos Cross-Over , Poluição Relacionada com o Tráfego , Dióxido de NitrogênioRESUMO
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 disease were demonstrated in recovering ward patients compared to those at the start of hospitalization, where 99 lipid species were altered (6 increased by 30-62%; 93 decreased by 1.3-2.8-fold). Overall, these findings support and expand on early reports that dysregulated lipid metabolism is involved in COVID-19.
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COVID-19 , Esfingosina/análogos & derivados , Humanos , Lipidômica , Cromatografia Líquida , Espectrometria de Massas em Tandem , Ácidos Graxos/metabolismo , Glicerofosfolipídeos , Lisofosfolipídeos , Biomarcadores , Gravidade do Paciente , FosfatosRESUMO
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 (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and warm-season Ozone (warm-O3)]; (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. Finally, the CRI of external exposome increased mortality for almost all cohorts. The associations found in the traditional adult cohorts were generally consistent with the results from the administrative ones, albeit without reaching statistical significance. Discussion: Various components of the external exposome, analyzed individually or in combination, were associated with increased mortality across European cohorts. This sets the stage for future research on the connections between various exposure patterns and human health, aiding in the planning of healthier cities.
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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 (PM2.5), nitrogen dioxide (NO2), black carbon (BC), warm season ozone (O3)], 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 PM2.5, NO2, 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 O3, NDVI, distance to water, and temperature variation on all-cause mortality. The effects of PM2.5 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 NO2. The CRI of air pollutants (PM2.5 or NO2) plus NDVI and mean warm season temperature resulted in a stronger effect compared to single-exposure HRs: [PM2.5 pooled HR: 1.061 (95% CI 1.021-1.102); NO2 pooled HR: 1.041 (95% CI 1.025-1.057)]. Non-significant effects of similar patterns were observed in traditional cohorts. Discussion: The findings of our study not only support the independent effects of long-term exposure to air pollution and greenness, but also highlight the increased effect when interplaying with other environmental exposures.