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Studies have shown how air pollution and temperature affect blood pressure. We investigated the combined effect of air pollution and temperature on blood pressure in a cohort of older German women. We conducted a cross-sectional analysis of systolic (SBP) and diastolic blood pressure (DBP) data from follow-up 3 (2012–2013) of the Study on the influence of Air pollution on lung function inflammation and ageing (SALIA) cohort. Short-term data on daily air pollutants and temperature were obtained from the German Weather Bureau and the German Environment Agency. A generalized additive model was used to capture their combined effect. Stratified analyses were performed to quantify the variation in the estimated effects. The core model was adjusted for potential covariates. We observed a combined association of temperature and air pollution with blood pressure. We found that lower temperatures and higher levels of air pollutants such as PM 2.5 and NO 2 were associated with higher SBP and DBP. However, higher O 3 exposure was generally associated with lower SBP and DBP. Stratified analyses showed that the associations between temperature, air pollution, and blood pressure were stronger among women living in urban areas and those with lower socio-economic status. The combined effect of low ambient temperature and high air pollution substantially increased BP among older German women.

Background Genetic risk scores (GRS) summarize genetic features such as single nucleotide polymorphisms (SNPs) in a single statistic with respect to a given trait. So far, GRS are typically built using generalized linear models or regularized extensions. However, these linear methods are usually not able to incorporate gene-gene interactions or non-linear SNP-response relationships. Tree-based statistical learning methods such as random forests and logic regression may be an alternative to such regularized-regression-based methods and are investigated in this article. Moreover, we consider modifications of random forests and logic regression for the construction of GRS. Results In an extensive simulation study and an application to a real data set from a German cohort study, we show that both tree-based approaches can outperform elastic net when constructing GRS for binary traits. Especially a modification of logic regression called logic bagging could induce comparatively high predictive power as measured by the area under the curve and the statistical power. Even when considering no epistatic interaction effects but only marginal genetic effects, the regularized regression method lead in most cases to inferior results. Conclusions When constructing GRS, we recommend taking random forests and logic bagging into account, in particular, if it can be assumed that possibly unknown epistasis between SNPs is present. To develop the best possible prediction models, extensive joint hyperparameter optimizations should be conducted.

Allergies have been linked to immune dysfunction, genetics, and environmental factors. However, environmental exposures are often highly correlated similar to genetic predictors making the cumulative assessment of exposures difficult. Here, we aim to investigate the relative contribution of genetic variants as well as different individual and environmental factors on the presence or absence of allergies in 450 elderly German women enrolled in the SALIA cohort study living in the Ruhr area by using genetic risk score (GRS) and exposomal risk scores (ERS). We used the novel cross leverage scores (CLS) to select genetic variants to be included in the GRS. The weights of the risk scores were obtained through bootstrapped and cross-validated ridge regression. We characterized the relative contributions of the risk scores to presence of allergies such as atopic dermatitis, asthma, or allergic rhinitis using McFadden’s Pseudo R-squared. Overall, our model was able to explain 11.13% of the variance of allergy diagnosis. The modest variance explained is consistent with prior work on complex polygenic and environmentally influenced traits, reflecting that no single exposure or domain is likely to fully capture individual risk. The GRS had the highest relative contribution at 3.80%, followed by the meteorological risk score with 1.13%. This method can easily be adapted to other diseases and can facilitate health risk assessments of exposomal factors. In addition, the results may aid policy-making, for example, by regulating specific sources of exposure.

ObjectiveTo investigate the interplay between the genetic predisposition to successful ageing and air pollution on lung disease in healthy aged German women under the hypothesis that ageing and lung diseases share mechanisms of oxidative stress and inflammation that can be regulated by genetic predisposition and environmental factors.DesignGerman Study on the influence of Air pollution on Lung function, Inflammation and Aging prospective cohort between baseline (1985–1994) and follow-up (2007–2010).SettingUrban Ruhr area and the adjacent rural Münsterland in Germany.ParticipantsAt baseline, 4874 women aged 55 years living between 1985 and 1994 in the setting and at follow-up examination, 834 of them participated.Main outcome measuresChronic lung disease was defined as any of asthma, chronic bronchitis, cough (with sputum) or chronic obstructive pulmonary disease. Chronic individual exposures to nitrogen dioxide (NO2), nitrogen oxides, particulate matter with median aerodynamic diameters <2.5 (PM2.5), PM10, PMcoarse and PM2.5 absorbance based on European Study of Cohorts for Air Pollution Effects land-use regression models were used. Main and interaction effects between the genetic risk score (77 single-nucleotide polymorphisms (SNPs) related to successful ageing) and air pollutant exposures were investigated using adjusted logistic regression models.ResultsIn 560 women (67–80 years), chronic lung disease was present in 156. Higher exposure to air pollution was associated with increased odds by up to 43% per IQR-increase in NO2 (IQR=11.6 µg/m³, 95% CI 1.15 to 1.77). The genetic make-up reduced the negative impact of air pollution (gene–environment interaction with NO2: OR=0.66, 95% CI 0.45 to 0.96), while a healthy lifestyle further strengthens this association.ConclusionsIn elderly women, genetic predisposition based on successful ageing SNPs likely reduces the negative impact of air pollution on chronic lung disease, while a healthy lifestyle further strengthens this association.

Background Air pollutants can activate low-grade subclinical inflammation which further impairs respiratory health. We aimed to investigate the role of polygenic susceptibility to chronic air pollution-induced subclinical airway inflammation. Methods We used data from 296 women (69–79 years) enrolled in the population-based SALIA cohort (Study on the influence of Air pollution on Lung function, Inflammation and Aging). Biomarkers of airway inflammation were measured in induced-sputum samples at follow-up investigation in 2007–2010. Chronic air pollution exposures at residential addresses within 15 years prior to the biomarker assessments were used to estimate main environmental effects on subclinical airway inflammation. Furthermore, we calculated internally weighted polygenic risk scores based on genome-wide derived single nucleotide polymorphisms. Polygenic main and gene-environment interaction (GxE) effects were investigated by adjusted linear regression models. Results Higher exposures to nitrogen dioxide (NO 2 ), nitrogen oxides (NO x ), particulate matter with aerodynamic diameters of ≤ 2.5 μm, ≤ 10 μm, and 2.5–10 µm significantly increased the levels of leukotriene (LT)B 4 by 19.7% (p-value = 0.005), 20.9% (p = 0.002), 22.1% (p = 0.004), 17.4% (p = 0.004), and 23.4% (p = 0.001), respectively. We found significant effects of NO 2 (25.9%, p = 0.008) and NO x (25.9%, p-value = 0.004) on the total number of cells. No significant GxE effects were observed. The trends were mostly robust in sensitivity analyses. Conclusions While this study confirms that higher chronic exposures to air pollution increase the risk of subclinical airway inflammation in elderly women, we could not demonstrate a significant role of polygenic susceptibility on this pathway. Further studies are required to investigate the role of polygenic susceptibility. Graphical Abstract

BackgroundAir pollution is a risk factor for chronic obstructive pulmonary disease (COPD). Fraction of exhaled nitric oxide (FeNO) could be a useful biomarker for health effects of air pollutants. However, there were limited data from older populations with higher prevalence of COPD and other inflammatory conditions.MethodsWe obtained data from the German Study on the influence of Air pollution on Lung function, Inflammation and Ageing. Spirometry and FeNO were measured by standard techniques. Air pollutant exposures were estimated following the European Study of Cohorts for Air Pollution Effects protocols, and ozone (O3) measured at the closest ground level monitoring station. Multiple linear regression models were fitted to FeNO with each pollutant separately and adjusted for potential confounders.ResultsIn 236 women (mean age 74.6 years), geometric mean FeNO was 15.2ppb. Almost a third (n=71, 30.1%) of the women had some chronic inflammatory respiratory condition. A higher FeNO concentration was associated with exposures to fine particles (PM2.5), PM2.5absorbance and respirable particles (PM10). There were no significant associations with PMcoarse, NO2, NOx, O3 or length of major roads within a 1 km buffer. Restricting the analysis to participants with a chronic inflammatory respiratory condition, with or without impaired lung function produced similar findings. Adjusting for diabetes did not materially alter the findings. There were no significant interactions between individual pollutants and asthma or current smoking.ConclusionsThis study adds to the evidence to reduce ambient PM2.5 concentrations as low as possible to protect the health of the general population.

Polygenic susceptibility likely influences individual responses to air pollutants and the risk of asthma. We compared the role of polygenic susceptibility on air pollution-associated asthma between German and Japanese women. We investigated women that were enrolled in the German SALIA cohort (n = 771, mean age = 73 years) and the Japanese Shika cohort (n = 847, mean age = 67 years) with known asthma status. Adjusted logistic regression models were used to assess the associations between (1) particulate matter with a median aerodynamic diameter ≤ 2.5μm (PM2.5) and nitrogen dioxide (NO2), (2) polygenic risk scores (PRS), and (3) gene-environment interactions (G × E) with asthma. We found an increased risk of asthma in Japanese women after exposure to low pollutant levels (PM2.5: median = 12.7µg/m3, p-value < 0.001, NO2: median = 8.5µg/m3, p-value < 0.001) and in German women protective polygenic effects (p-value = 0.008). While we found no significant G × E effects, the direction in both groups was that the PRS increased the effect of PM2.5 and decreased the effect of NO2 on asthma. Our study confirms that exposure to low air pollution levels increases the risk of asthma in Japanese women and indicates polygenic effects in German women; however, there was no evidence of G × E effects. Future genome-wide G × E studies should further explore the role of ethnic-specific polygenic susceptibility to asthma.

Understanding intramammary estrogen homeostasis constitutes the basis of understanding the role of lifestyle factors in breast cancer etiology. Thus, the aim of the present study was to identify variables influencing levels of the estrogens present in normal breast glandular and adipose tissues (GLT and ADT, i.e., 17β-estradiol, estrone, estrone-3-sulfate, and 2-methoxy-estrone) by multiple linear regression models. Explanatory variables (exVARs) considered were (a) levels of metabolic precursors as well as levels of transcripts encoding proteins involved in estrogen (biotrans)formation, (b) data on breast cancer risk factors (i.e., body mass index, BMI, intake of estrogen-active drugs, and smoking) collected by questionnaire, and (c) tissue characteristics (i.e., mass percentage of oil, oil%, and lobule type of the GLT). Levels of estrogens in GLT and ADT were influenced by both extramammary production (menopausal status, intake of estrogen-active drugs, and BMI) thus showing that variables known to affect levels of circulating estrogens influence estrogen levels in breast tissues as well for the first time. Moreover, intratissue (biotrans)formation (by aromatase, hydroxysteroid-17beta-dehydrogenase 2, and beta-glucuronidase) influenced intratissue estrogen levels, as well. Distinct differences were observed between the exVARs exhibiting significant influence on (a) levels of specific estrogens and (b) the same dependent variables in GLT and ADT. Since oil% and lobule type of GLT influenced levels of some estrogens, these variables may be included in tissue characterization to prevent sample bias. In conclusion, evidence for the intracrine activity of the human breast supports biotransformation-based strategies for breast cancer prevention. The susceptibility of estrogen homeostasis to systemic and tissue-specific modulation renders both beneficial and adverse effects of further variables associated with lifestyle and the environment possible.

Genetic and exposomal factors contribute to the development of human aging. For example, genetic polymorphisms and exposure to environmental factors (air pollution, tobacco smoke, etc.) influence lung and skin aging traits. For prevention purposes it is highly desirable to know the extent to which each category of the exposome and genetic factors contribute to their development. Estimating such extents, however, is methodologically challenging, mainly because the predictors are often highly correlated. Tackling this challenge, this article proposes to use weighted risk scores to assess combined effects of categories of such predictors, and a measure of relative importance to quantify their relative contribution. The risk score weights are determined via regularized regression and the relative contributions are estimated by the proportion of explained variance in linear regression. This approach is applied to data from a cohort of elderly Caucasian women investigated in 2007–2010 by estimating the relative contribution of genetic and exposomal factors to skin and lung aging. Overall, the models explain 17% (95% CI: [9%, 28%]) of the outcome’s variance for skin aging and 23% ([11%, 34%]) for lung function parameters. For both aging traits, genetic factors make up the largest contribution. The proposed approach enables us to quantify and rank contributions of categories of exposomal and genetic factors to human aging traits and facilitates risk assessment related to common human diseases in general. Obtained rankings can aid political decision making, for example, by prioritizing protective measures such as limit values for certain exposures.

The detrimental effects of traffic noise on cognition in children are well documented. Not much is known about the health effects in adults. We investigated the association of residential exposure to road traffic noise and annoyance due to road traffic noise with cognitive function in a cohort of 288 elderly women from the longitudinal Study on the influence of Air pollution on Lung function, Inflammation and Aging (SALIA) in Germany. Residential noise levels—weighted 24-h mean (LDEN) and nighttime noise (LNIGHT)—were modeled for the most exposed facade of dwellings and dichotomized at ≥50 dB(A). Traffic noise annoyance (day and night) was estimated by questionnaire. Cognitive function was assessed using the Consortium to Establish a Registry on Alzheimer’s Disease (CERAD-Plus) Neuropsychological Assessment Battery. The modeled noise levels were associated with impaired total cognition and the constructional praxis domain, independently of air pollution. Self-reported noise annoyance was associated with better performance in semantic memory and constructional praxis domains. This finding should be interpreted with caution since we could not control for potential confounding by hearing loss. Noise levels and annoyance were associated, but their health effects seemed mutually independent.