Multiple xenoestrogen air pollutants and breast cancer risk: Statistical approaches to investigate combined exposures effect.

Studies suggested that exposure to air pollutants, with endocrine disrupting (ED) properties, have a key role in breast cancer (BC) development. Although the population is exposed simultaneously to a mixture of multiple pollutants and ED pollutants may act via common biological mechanisms leading to synergic effects, epidemiological studies generally evaluate the effect of each pollutant separately. We aimed to assess the complex effect of exposure to a mixture of four xenoestrogen air pollutants (benzo-[a]-pyrene (BaP), cadmium, dioxin (2,3,7,8-Tétrachlorodibenzo-p-dioxin TCDD)), and polychlorinated biphenyl 153 (PCB153)) on the risk of BC, using three recent statistical methods, namely weighted quantile sum (WQS), quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR). The study was conducted on 5222 cases and 5222 matched controls nested within the French prospective E3N cohort initiated in 1990. Annual average exposure estimates to the pollutants were assessed using a chemistry transport model, at the participants' residence address between 1990 and 2011. We found a positive association between the WQS index of the joint effect and the risk of overall BC (adjusted odds ratio (OR) = 1.10, 95% confidence intervals (CI): 1.03-1.19). Similar results were found for QGC (OR = 1.11, 95%CI: 1.03-1.19). Despite the association did not reach statistical significance in the BKMR model, we observed an increasing trend between the joint effect of the four pollutants and the risk of BC, when fixing other chemicals at their median concentrations. BaP, cadmium and PCB153 also showed positive trends in the multi-pollutant mixture, while dioxin showed a modest inverse trend. Despite we found a clear evidence of a positive association between the joint exposure to pollutants and BC risk only from WQS and QGC regression, we observed a similar suggestive trend using BKMR. This study makes a major contribution to the understanding of the joint effects of air pollution.

Inhibiting Lysyl Oxidases prevents pathologic cartilage calcification.

Lysyl oxidases (LOX(L)) are enzymes that catalyze the formation of cross-links in collagen and elastin fibers during physiologic calcification of bone. However, it remains unknown whether they may promote pathologic calcification of articular cartilage, an important hallmark of debilitating arthropathies. Here, we have studied the possible roles of LOX(L) in cartilage calcification, related and not related to their cross-linking activity. We first demonstrated that inhibition of LOX(L) by ß-aminoproprionitrile (BAPN) significantly reduced calcification in murine and human chondrocytes, and in joint of meniscectomized mice. These BAPN's effects on calcification were accounted for by different LOX(L) roles. Firstly, reduced LOX(L)-mediated extracellular matrix cross-links downregulated Anx5, Pit1 and Pit2 calcification genes. Secondly, BAPN reduced collagen fibrotic markers Col1 and Col3. Additionally, LOX(L) inhibition blocked chondrocytes hypertrophic differentiation (Runx2 and COL10), pro-inflammatory IL-6 release and reactive oxygen species (ROS) production, all triggers of chondrocyte calcification. Through unbiased transcriptomic analysis we confirmed a positive correlation between LOX(L) genes and genes for calcification, hypertrophy and extracellular matrix catabolism. This association was conserved throughout species (mouse, human) and tissues that can undergo pathologic calcification (kidney, arteries, skin). Overall, LOX(L) play a critical role in the process of chondrocyte calcification and may be therapeutic targets to treat cartilage calcification in arthropathies.

A new ex vivo human model of osteoarthritis cartilage calcification.

OBJECTIVE: Cartilage pathologic calcification is a hallmark of osteoarthritis (OA). Here, we aimed to describe a new ex vivo human model to study the progression of cartilage calcification. METHOD: Cartilage explants (n = 11), as well as primary chondrocytes (n = 3), were obtained from OA patients undergoing knee replacement. Explants and chondrocytes were cultured in control (NT) or calcification (CM) medium (supplemented with ascorbic acid and ß-glycerophosphate). Calcification was evaluated by micro-CT scan at day 0 and 21 in explants, and by Alizarin red staining in chondrocyte monolayers. Raman spectrometry allowed characterization of the crystal type. Interleukin-6 (IL-6) secretion in explant and cell supernatants was measured by ELISA. Finally, matrix degradation was evaluated by Safranin-O staining of explant sections and by glycosaminoglycans (GAG) release in supernatants. RESULTS: Micro-CT scan showed calcifications in all explants at baseline (day 0), which in the CM group increased significantly in number and size after 21 days compared with the NT group. Raman spectrometry revealed that crystals were exclusively basic calcium phosphate crystals (carbonated hydroxyapatite) both in NT and CM. IL-6 secretion was significantly increased in calcifying conditions. Finally, CM significantly increased cartilage catabolism as assessed by decreased Safranin-O staining of tissue explants and increased GAG release in supernatants. CM effects (enhanced calcification, IL-6 secretion and proteoglycans turn-over) were recapitulated in vitro in OA chondrocytes. CONCLUSIONS: We have described a new ex vivo human model of cartilage calcification that can summurize the triad of events seen during osteoarthritis progression, i.e. calcification, inflammation, and cartilage degradation. This model will allow the identification of new anti-calcification compounds.

Loss of autism-candidate CHD8 perturbs neural crest development and intestinal homeostatic balance.

Individuals with mutations in CHD8 present with gastrointestinal complaints, yet the underlying mechanisms are understudied. Here, using a stable constitutive chd8 mutant zebrafish model, we found that the loss of chd8 leads to a reduced number of vagal neural crest cells (NCCs), enteric neural and glial progenitors, emigrating from the neural tube, and that their early migration capability was altered. At later stages, although the intestinal colonization by NCCs was complete, we found the decreased numbers of both serotonin-producing enterochromaffin cells and NCC-derived serotonergic neurons, suggesting an intestinal hyposerotonemia in the absence of chd8 Furthermore, transcriptomic analyses revealed an altered expression of key receptors and enzymes in serotonin and acetylcholine signaling pathways. The tissue examination of chd8 mutants revealed a thinner intestinal epithelium accompanied by an accumulation of neutrophils and the decreased numbers of goblet cells and eosinophils. Last, single-cell sequencing of whole intestines showed a global disruption of the immune balance with a perturbed expression of inflammatory interleukins and changes in immune cell clusters. Our findings propose a causal developmental link between chd8, NCC development, intestinal homeostasis, and autism-associated gastrointestinal complaints.

Long-term exposure to nitrogen dioxide air pollution and breast cancer risk: A nested case-control within the French E3N cohort study.

Nitrogen dioxide (NO2) is an important air pollutant due to its adverse effects on human health. Yet, current evidence on the association between NO2 and the risk of breast cancer lacks consistency. In this study, we investigated the association between long-term exposure to NO2 and breast cancer risk in the French E3N cohort study. Association of breast cancer risk with NO2 exposure was assessed in a nested case-control study within the French E3N cohort including 5222 breast cancer cases identified over the 1990-2011 follow-up period and 5222 matched controls. Annual mean concentrations of NO2 at participants' residential addresses for each year from recruitment 1990 through 2011, were estimated using a land use regression (LUR) model. Multivariable conditional logistic regression models were used to compute odds ratios (ORs) and their 95% confidence intervals (CIs). Additional analyses were performed using NO2 concentrations estimated by CHIMERE, a chemistry transport model. Overall, the mean NO2 exposure was associated with an increased risk of breast cancer. In all women, for each interquartile range (IQR) increase in NO2 levels (LUR: 17.8 µg/m3), the OR of the model adjusted for confounders was 1.09 (95% CI: 1.01-1.18). The corresponding OR in the fully adjusted model (additionally adjusted for established breast cancer risk factors) was 1.07 (95% CI: 0.98-1.15). By menopausal status, results for postmenopausal women were comparable to those for all women, while no association was observed among premenopausal women. By hormone receptor status, the OR of estrogen receptor positive breast cancer = 1.07 (95% CI: 0.97-1.19) in the fully adjusted model. Additional analyses using the CHIMERE model showed slight differences in ORs estimates. The results of this study indicate an increased risk of breast cancer associated with long-term exposure to NO2 air pollution. Observing comparable effects of NO2 exposure estimated by two different models, reinforces these findings.

Long-term air pollution exposure and Parkinson's disease mortality in a large pooled European cohort: An ELAPSE study.

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 (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (O3), as well as 8 PM2.5 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 PM2.5 (hazard ratio per 5 µg/m3: 1.25; 95% confidence interval: 1.01-1.55), NO2 (1.13; 0.95-1.34 per 10 µg/m3), and BC (1.12; 0.94-1.34 per 0.5 × 10-5m-1), and a negative association with O3 (0.74; 0.58-0.94 per 10 µg/m3). Associations of PM2.5, NO2, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM2.5 remained robust when adjusted for NO2 (1.24; 0.95-1.62) or BC (1.28; 0.96-1.71), whereas associations with NO2 or BC attenuated to null. O3 associations remained negative, but no longer statistically significant in models with PM2.5. We detected suggestive positive associations with the potassium component of PM2.5. CONCLUSION: Long-term exposure to PM2.5, at levels well below current EU air pollution limit values, may contribute to PD mortality.

Long-Term Exposure to Source-Specific Fine Particles and Mortality─A Pooled Analysis of 14 European Cohorts within the ELAPSE Project.

We assessed mortality risks associated with source-specific fine particles (PM2.5) in a pooled European cohort of 323,782 participants. Cox proportional hazard models were applied to estimate mortality hazard ratios (HRs) for source-specific PM2.5 identified through a source apportionment analysis. Exposure to 2010 annual average concentrations of source-specific PM2.5 components was assessed at baseline residential addresses. The source apportionment resulted in the identification of five sources: traffic, residual oil combustion, soil, biomass and agriculture, and industry. In single-source analysis, all identified sources were significantly positively associated with increased natural mortality risks. In multisource analysis, associations with all sources attenuated but remained statistically significant with traffic, oil, and biomass and agriculture. The highest association per interquartile increase was observed for the traffic component (HR: 1.06; 95% CI: 1.04 and 1.08 per 2.86 µg/m3 increase) across five identified sources. On a 1 µg/m3 basis, the residual oil-related PM2.5 had the strongest association (HR: 1.13; 95% CI: 1.05 and 1.22), which was substantially higher than that for generic PM2.5 mass, suggesting that past estimates using the generic PM2.5 exposure response function have underestimated the potential clean air health benefits of reducing fossil-fuel combustion. Source-specific associations with cause-specific mortality were in general consistent with findings of natural mortality.

Exposure to surrounding greenness and natural-cause and cause-specific mortality in the ELAPSE pooled cohort.

BACKGROUND: The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort. METHODS: Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants' baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise. RESULTS: The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found. CONCLUSIONS: We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise.

The impact of left truncation of exposure in environmental case-control studies: evidence from breast cancer risk associated with airborne dioxin.

In epidemiology, left-truncated data may bias exposure effect estimates. We analyzed the bias induced by left truncation in estimating breast cancer risk associated with exposure to airborne dioxins. Simulations were run with exposure estimates from a Geographic Information System (GIS)-based metric and considered two hypotheses for historical exposure, three scenarios for intra-individual correlation of annual exposures, and three exposure-effect models. For each correlation/model combination, 500 nested matched case-control studies were simulated and data fitted using a conditional logistic regression model. Bias magnitude was assessed by estimated odds-ratios (ORs) versus theoretical relative risks (TRRs) comparisons. With strong intra-individual correlation and continuous exposure, left truncation overestimated the Beta parameter associated with cumulative dioxin exposure. Versus a theoretical Beta of 4.17, the estimated mean Beta (5%; 95%) was 73.2 (67.7; 78.8) with left-truncated exposure and 4.37 (4.05; 4.66) with lifetime exposure. With exposure categorized in quintiles, the TRR was 2.0, the estimated ORQ5 vs. Q1 2.19 (2.04; 2.33) with truncated exposure versus 2.17 (2.02; 2.32) with lifetime exposure. However, the difference in exposure between Q5 and Q1 was 18× smaller with truncated data, indicating an important overestimation of the dose effect. No intra-individual correlation resulted in effect dilution and statistical power loss. Left truncation induced substantial bias in estimating breast cancer risk associated with exposure with continuous and categorical models. With strong intra-individual exposure correlation, both models detected associations, but categorical models provided better estimates of effect trends. This calls for careful consideration of left truncation-induced bias in interpreting environmental epidemiological data.

Exposure to airborne cadmium and breast cancer stage, grade and histology at diagnosis: findings from the E3N cohort study.

Molecular studies suggest that cadmium due to its estrogenic properties, might play a role in breast cancer (BC) progression. However epidemiological evidence is limited. This study explored the association between long-term exposure to airborne cadmium and risk of BC by stage, grade of differentiation, and histological types at diagnosis. A nested case-control study of 4401 cases and 4401 matched controls was conducted within the French E3N cohort. A Geographic Information System (GIS)-based metric demonstrated to reliably characterize long-term environmental exposures was employed to evaluate airborne exposure to cadmium. Multivariable adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression models. There was no relationship between cadmium exposure and stage of BC. Also, no association between cadmium exposure and grade of differentiation of BC was observed. However, further analyses by histological type suggested a positive association between cadmium and risk of invasive tubular carcinoma (ITC) BC [ORQ5 vs Q1 = 3.4 (95% CI 1.1-10.7)]. The restricted cubic spline assessment suggested a dose-response relationship between cadmium and ITC BC subtype. Our results do not support the hypothesis that airborne cadmium exposure may play a role in advanced BC risk, but suggest that cadmium may be associated with an increased risk of ITC.

Domestic use of pesticides during early periods of development and risk of testicular germ cell tumors in adulthood: a French nationwide case-control study.

BACKGROUND: Testicular germ cell tumours (TGCT) are the most frequent cancers in young men in developed countries and their incidence rate has doubled worldwide over the past 40 years. Early life exposures to pesticides are suspected to increase TGCT risk. Our research aimed at estimating adult TGCT risk associated with parental domestic use of pesticides during early periods of child development. METHODS: We conducted a case-control study of 304 TGCT cases, aged 18-45 years old, recruited in 20 French university hospitals, and 274 controls frequency-matched on hospital and birth year. Participants' mothers provided information on their domestic use of pesticides from 1 year before start of pregnancy to 1 year after their son's birth, for gardening activities, treatment of indoor plants, pets, wood and mold, and pest control. Odds ratios (OR) for TGCT (overall and by histological subtype) and 95% confidence intervals (CI) were estimated using conditional logistic regression. RESULTS: Prevalence of reported domestic use of pesticides was 77.3% for insecticides, 15.9% for fungicides and 12.1% for herbicides. While no association was found for any use of insecticides (OR = 1.27, CI = 0.80-2.01) or herbicides (OR = 1.15, CI = 0.67-2.00), elevated risks of TGCT overall (OR = 1.73, CI = 1.04-2.87) and non-seminoma subtype (OR = 2.44, CI = 1.26-4.74) were observed for any use of fungicides. When specific purposes were examined, using fungicides and/or insecticides for woodwork (OR = 2.35, CI = 1.06-5.20) and using insecticides on cats and dogs (OR = 1.95, CI = 1.12-3.40) were associated with increased risk of non-seminoma subtype. We found no association for seminoma subtype. CONCLUSIONS: Although recall bias may partially explain the elevated ORs, our study provides some evidence of a positive association between domestic use of pesticides during early periods of development, particularly fungicides and risk of adult TGCT and non-seminoma. Given the common domestic use of pesticides in France, further research on TGCT risk is warranted.

Long-term atmospheric exposure to PCB153 and breast cancer risk in a case-control study nested in the French E3N cohort from 1990 to 2011.

BACKGROUND: Although the genetic and hormonal risk factors of breast cancer are well identified, they cannot fully explain the occurrence of all cases. Epidemiological and experimental studies have suggested that exposure to environmental pollutants, especially those with potential estrogenic properties, as polychlorinated biphenyls (PCBs) may have a role in breast cancer development. Being the most abundantly detected in human tissues and in the environment, congener 153 (PCB153) is widely used in epidemiological studies as indicator for total PCBs exposure. OBJECTIVES: We aimed to estimate the association between cumulative atmospheric exposure to PCB153 and breast cancer risk. METHODS: We conducted a case-control study of 5222 cases and 5222 matched controls nested within the French E3N cohort from 1990 to 2011. Annual atmospheric PCB153 concentrations were simulated with the deterministic chemistry-transport model (CHIMERE) and were assigned to women using their geocoded residential history. Their cumulative PCB153 exposure was calculated for each woman from their cohort inclusion to their index date. Breast cancer odds ratios (ORs) associated with cumulative PCB153 exposure and their 95% confidence intervals (95% CIs) were estimated using multivariate conditional logistic regression models. RESULTS: Overall, our results showed a statistically significant linear increase in breast cancer risk related to cumulative atmospheric exposure to PCB153 as a continuous variable (adjusted OR = 1.19; 95% CI: 1.08-1.31, for an increment of one standard deviation among controls (55 pg/m3)). Among women who became postmenopausal during follow-up, the association remained statistically significant (adjusted OR = 1.23; 95% CI: 1.09-1.39). In analyses by hormone receptors status, the positive association remained significant only for ER-positive breast cancer (adjusted OR = 1.18; 95% CI: 1.05-1.33). DISCUSSION: This study is the first to have estimated the impact of atmospheric exposure to PCB153 on breast cancer risk. Our results showed a statistically significant increase in breast cancer risk, which may be limited to ER-positive breast cancer. These results warrant confirmation in further independent studies but raise the possibility that exposure to PCB153 increase breast cancer risk.

Risk of breast cancer associated with long-term exposure to benzo[a]pyrene (BaP) air pollution: Evidence from the French E3N cohort study.

BACKGROUND: Benzo[a]pyrene (BaP) is an endocrine-disrupting pollutant formed during incomplete combustion of organic materials. It has been recognized as a reproductive and developmental toxicant, however epidemiological evidence of the long-term effect of ambient air BaP on breast cancer (BC) is limited. Thus we evaluated associations between ambient air BaP exposure and risk of BC, overall and according to menopausal status and molecular subtypes (estrogen receptor negative/positive (ER-/ER+) and progesterone receptor negative/positive (PR-/PR+)), stage and grade of differentiation of BC in the French E3N cohort study. METHODS: Within a nested case-control study of 5222 incident BC cases and 5222 matched controls, annual BaP exposure was estimated using a chemistry-transport model (CHIMERE) and was assigned to the geocoded residential addresses of participants for each year during the 1990-2011 follow-up period. Multivariable conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: Overall, cumulative airborne BaP exposure was significantly associated with the overall risk of BC, for each 1 interquartile range (IQR) increase in the concentration levels of BaP (1.42 ng/m3), the OR = 1.15 (95% CI: 1.04-1.27). However, by menopausal status, the significant positive association remained only in women who underwent menopausal transition (i.e. premenopausal women at inclusion who became postmenopausal at diagnosis), OR per 1 IQR = 1.20 (95% CI: 1.03-1.40). By hormone receptor status, positive associations were observed for ER+, PR + and ER + PR + BC, with ORs = 1.17 (95% CI: 1.04-1.32), 1.16 (95% CI: 1.01-1.33), and 1.17 (95% CI: 1.01-1.36) per 1 IQR, respectively. There was also a borderline positive association between BaP and grade 3 BC (OR per 1 IQR = 1.15 (95% CI: 0.99-1.34). CONCLUSIONS: We provide evidence of increased risk of BC associated with cumulative BaP exposure, which varied according to menopausal status, hormone receptor status, and grade of differentiation of BC. Our results add further epidemiological evidence to the previous experimental studies suggesting the adverse effects of BaP.

Beyond the map: evidencing the spatial dimension of health inequalities.

BACKGROUND: Spatial inequalities in health result from different exposures to health risk factors according to the features of geographical contexts, in terms of physical environment, social deprivation, and health care accessibility. Using a common geographical referential, which combines indices measuring these contextual features, could improve the comparability of studies and the understanding of the spatial dimension of health inequalities. METHODS: We developed the Geographical Classification for Health studies (GeoClasH) to distinguish French municipalities according to their ability to influence health outcomes. Ten contextual scores measuring physical and social environment as well as spatial accessibility of health care have been computed and combined to classify French municipalities through a K-means clustering. Age-standardized mortality rates according to the clusters of this classification have been calculated to assess its effectiveness. RESULTS: Significant lower mortality rates compared to the mainland France population were found in the Wealthy Metropolitan Areas (SMR = 0.868, 95% CI 0.863-0.873) and in the Residential Outskirts (SMR = 0.971, 95% CI 0.964-0.978), while significant excess mortality were found for Precarious Population Districts (SMR = 1.037, 95% CI 1.035-1.039), Agricultural and Industrial Plains (SMR = 1.066, 95% CI 1.063-1.070) and Rural Margins (SMR = 1.042, 95% CI 1.037-1.047). CONCLUSIONS: Our results evidence the comprehensive contribution of the geographical context in the constitution of health inequalities. To our knowledge, GeoClasH is the first nationwide classification that combines social, environmental and health care access scores at the municipality scale. It can therefore be used as a proxy to assess the geographical context of the individuals in public health studies.

Chronic Low-Dose Exposure to Xenoestrogen Ambient Air Pollutants and Breast Cancer Risk: XENAIR Protocol for a Case-Control Study Nested Within the French E3N Cohort.

BACKGROUND: Breast cancer is the most frequent cancer in women in industrialized countries. Lifestyle and environmental factors, particularly endocrine-disrupting pollutants, have been suggested to play a role in breast cancer risk. Current epidemiological studies, although not fully consistent, suggest a positive association of breast cancer risk with exposure to several International Agency for Research on Cancer Group 1 air-pollutant carcinogens, such as particulate matter, polychlorinated biphenyls (PCB), dioxins, Benzo[a]pyrene (BaP), and cadmium. However, epidemiological studies remain scarce and inconsistent. It has been proposed that the menopausal status could modify the relationship between pollutants and breast cancer and that the association varies with hormone receptor status. OBJECTIVE: The XENAIR project will investigate the association of breast cancer risk (overall and by hormone receptor status) with chronic exposure to selected air pollutants, including particulate matter, nitrogen dioxide (NO2), ozone (O3), BaP, dioxins, PCB-153, and cadmium. METHODS: Our research is based on a case-control study nested within the French national E3N cohort of 5222 invasive breast cancer cases identified during follow-up from 1990 to 2011, and 5222 matched controls. A questionnaire was sent to all participants to collect their lifetime residential addresses and information on indoor pollution. We will assess these exposures using complementary models of land-use regression, atmospheric dispersion, and regional chemistry-transport (CHIMERE) models, via a Geographic Information System. Associations with breast cancer risk will be modeled using conditional logistic regression models. We will also study the impact of exposure on DNA methylation and interactions with genetic polymorphisms. Appropriate statistical methods, including Bayesian modeling, principal component analysis, and cluster analysis, will be used to assess the impact of multipollutant exposure. The fraction of breast cancer cases attributable to air pollution will be estimated. RESULTS: The XENAIR project will contribute to current knowledge on the health effects of air pollution and identify and understand environmental modifiable risk factors related to breast cancer risk. CONCLUSIONS: The results will provide relevant evidence to governments and policy-makers to improve effective public health prevention strategies on air pollution. The XENAIR dataset can be used in future efforts to study the effects of exposure to air pollution associated with other chronic conditions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15167.

Chronic long-term exposure to cadmium air pollution and breast cancer risk in the French E3N cohort.

Cadmium, due to its estrogen-like activity, has been suspected to increase the risk of breast cancer; however, epidemiological studies have reported inconsistent findings. We conducted a case-control study (4,059 cases and 4,059 matched controls) nested within the E3N French cohort study to estimate the risk of breast cancer associated with long-term exposure to airborne cadmium pollution, and its effect according to molecular subtype of breast cancer (estrogen receptor negative/positive [ER-/ER+] and progesterone receptor negative/positive [PR-/PR+]). Atmospheric exposure to cadmium was assessed using a Geographic Information System-based metric, which included subject's residence-to-cadmium source distance, wind direction, exposure duration and stack height. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression. Overall, there was no significant association between cumulative dose of airborne cadmium exposure and the risk of overall, premenopausal and postmenopausal breast cancer. However, by ER and PR status, inverse associations were observed for ER- (ORQ5 vs. Q1 = 0.63; 95% CI: 0.41-0.95, ptrend = 0.043) and for ER-/PR- breast tumors (ORQ4 vs. Q1 = 0.62; 95% CI: 0.40-0.95, ORQ5 vs. Q1 = 0.68; 95% CI: 0.42-1.07, ptrend = 0.088). Our study provides no evidence of an association between exposure to cadmium and risk of breast cancer overall but suggests that cadmium might be related to a decreased risk of ER- and ER-/PR- breast tumors. These observations and other possible effects linked to hormone receptor status warrant further investigations.

Automatic Land Cover Reconstruction From Historical Aerial Images: An Evaluation of Features Extraction and Classification Algorithms.

The land cover reconstruction from monochromatic historical aerial images is a challenging task that has recently attracted an increasing interest from the scientific community with the proliferation of large-scale epidemiological studies involving retrospective analysis of spatial patterns. However, the efforts made by the computer vision community in remote-sensing applications are mostly focused on prospective approaches through the analysis of high-resolution multi-spectral data acquired by the advanced spatial programs. Hence, four contributions are proposed in this paper. They aim at providing a comparison basis for the future development of computer vision algorithms applied to the automation of the land cover reconstruction from monochromatic historical aerial images. First, a new multi-scale multi-date dataset composed of 4.9 million non-overlapping annotated patches of the France territory between 1970 and 1990 has been created with the help of geography experts. This dataset has been named HistAerial. Second, an extensive comparison study of the state-of-the-art texture features extraction and classification algorithms, including deep convolutional neural networks (DCNNs), has been performed. It is presented in the form of an evaluation. Third, a novel low-dimensional local texture filter named rotated-corner local binary pattern (R-CRLBP) is presented as a simplification of the binary gradient contours filter through the use of an orthogonal combination representation. Finally, a novel combination of low-dimensional texture descriptors, including the R-CRLBP filter, is introduced as a light combination of local binary patterns (LCoLBPs). The LCoLBP filter achieved state-of-the-art results on the HistAerial dataset while conserving a relatively low-dimensional feature vector space compared with the DCNN approaches (17 times shorter).

Development and performance evaluation of a GIS-based metric to assess exposure to airborne pollutant emissions from industrial sources.

BACKGROUND: Dioxins are environmental and persistent organic carcinogens with endocrine disrupting properties. A positive association with several cancers, including risk of breast cancer has been suggested. OBJECTIVES: This study aimed to develop and assess performances of an exposure metric based on a Geographic Information System (GIS) through comparison with a validated dispersion model to estimate historical industrial dioxin exposure for its use in a case-control study nested within a prospective cohort. METHODS: Industrial dioxin sources were inventoried over the whole French territory (n > 2500) and annual average releases were estimated between 1990 and 2008. In three selected areas (rural, urban and urban-costal), dioxin dispersion was modelled using SIRANE, an urban Gaussian model and exposure of the French E3N cohort participants was estimated. The GIS-based metric was developed, calibrated and compared to SIRANE results using a set of parameters (local meteorological data, characteristics of industrial sources, e.g. emission intensity and stack height), by calculating weighted kappa statistics (wκ) and coefficient of determination (R2). Furthermore, as performance evaluation, the final GIS-based metric was tested to assess atmospheric exposure to cadmium. RESULTS: The concordance between the GIS-based metric and the dispersion model for dioxin exposure estimate was strong (wκ median = 0.78 (1st quintile = 0.72, 3rd quintile =0.82) and R2 median = 0.82 (1st quintile = 0.71, 3rd quintile = 0.87)). We observed similar performance for cadmium. CONCLUSIONS: Our study demonstrated the ability of the GIS-based metric to reliably characterize long-term environmental dioxin and cadmium exposures as well as the pertinence of using dispersion modelling to construct and calibrate the GIS-based metric.

Long-term airborne dioxin exposure and breast cancer risk in a case-control study nested within the French E3N prospective cohort.

BACKGROUND: Dioxins, Group 1 carcinogens, are emitted by industrial chlorinated combustion processes and suspected to increase breast cancer risk through receptor-mediated pathways. OBJECTIVES: We estimated breast cancer risk associated with airborne dioxin exposure, using geographic information system (GIS) methods and historical exposure data. METHODS: We designed a case-control study (429 breast cancer cases diagnosed between 1990 and 2008, matched to 716 controls) nested within the E3N (Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l'Education Nationale) cohort. Airborne dioxin exposure was assessed using a GIS-based metric including participants' residential history, technical characteristics of 222 dioxin sources, residential proximity to dioxin sources, exposure duration and wind direction. Odds ratios (OR) and 95% confidence intervals (CI) associated with quintiles of cumulative exposure were estimated using multivariate logistic regression models. RESULTS: We observed no increased risk of breast cancer for higher dioxin exposure levels overall and according to hormone-receptor status. We however observed a statistically significant OR for Q2 versus Q1 overall (1.612, 95% CI: 1.042-2.493) and for estrogen-receptor (ER) positive breast cancer (1.843, 95% CI: 1.033-3.292). CONCLUSIONS: Overall, as well as according to hormone-receptor status, no increased risk was observed for higher airborne dioxin exposure. The increased risk for low exposure levels might be compatible with non-monotonic dose-response relationship. Confirmation of our findings is required. Our GIS-based metric may provide an alternative in absence of ambient dioxin monitoring and may allow assessing exposure to other pollutants.