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 (L_DEN) and nighttime noise (L_NIGHT)—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.

Neurotoxicity is mediated by a variety of modes-of-actions leading to disturbance of neuronal function. In order to screen larger numbers of compounds for their neurotoxic potential, in vitro functional neuronal networks (NN) might be helpful tools. We established and characterized human NN (hNN) from hiPSC-derived neural progenitor cells by comparing hNN formation with two different differentiation media: in presence (CINDA) and absence (neural differentiation medium (NDM)) of maturation-supporting factors. As a NN control we included differentiating rat NN (rNN) in the study. Gene/protein expression and electrical activity from in vitro developing NN were assessed at multiple time points. Transcriptomes of 5, 14 and 28 days in vitro CINDA-grown hNN were compared to gene expression profiles of in vivo human developing brains. Molecular expression analyses as well as measures of electrical activity indicate that NN mature into neurons of different subtypes and astrocytes over time. In contrast to rNN, hNN are less electrically active within the same period of differentiation time, yet hNN grown in CINDA medium develop higher firing rates than hNN without supplements. Challenge of NN with neuronal receptor stimulators and inhibitors demonstrate presence of inhibitory, GABAergic neurons, whereas glutamatergic responses are limited. hiPSC-derived GABAergic hNN grown in CINDA medium might be a useful tool as part of an in vitro battery for assessing neurotoxicity.

Zusammenfassung: Hintergrund: Personen mit Migrationshintergrund (PmM) unterscheiden sich als Bevölkerungsgruppe hinsichtlich Morbidität, Mortalität und Inanspruchnahme des Gesundheitssystems meist von der autochthonen Bevölkerung, sie nehmen jedoch seltener an Gesundheitsstudien teil. Die Gruppe der PmM ist sehr heterogen, was in Studien bisher kaum berücksichtigt wird.Ziel der Arbeit: Es werden soziodemografische Charakteristika der PmM in der NAKO Gesundheitsstudie (Alter, Geschlecht, Zeit seit Migration, Bildung) dargestellt. Zudem wird exemplarisch untersucht, ob der Migrationshintergrund mit der Nutzung des Angebots zur Früherkennung von Darmkrebs (Hämoccult-Test) zusammenhängt.Methoden: Daten der ersten 101.816 Teilnehmenden der NAKO wurden deskriptiv und kartografisch ausgewertet. Die Zuweisung des Migrationshintergrunds erfolgte anhand der Definition des Statistischen Bundesamts und basiert auf Staatsangehörigkeit, Geburtsland, Einreisejahr und Geburtsland der Eltern.Ergebnisse: Der Anteil der PmM liegt bei 16,0 %. Die Verteilung über die 18 Studienzentren variiert zwischen 6 % (Neubrandenburg) und 33 % (Düsseldorf). Mit 153 Herkunftsländern sind in der NAKO die meisten Länder vertreten. Bei allen Variablen zeigen sich deutliche Unterschiede zwischen den verschiedenen Herkunftsregionen. Am Hämoccult-Test nehmen türkeistämmige Personen (OR = 0,67) und Aussiedler aus der ehemaligen Sowjetunion (OR = 0,60) seltener teil. PmM, die in Deutschland geboren sind, unterscheiden sich diesbezüglich nicht von der autochthonen Bevölkerung (OR = 0,99).Diskussion: PmM in der NAKO sind eine sehr heterogene Gruppe. Jedoch lassen sich aufgrund der Stichprobengröße einzelne Untergruppen der PmM hinsichtlich ihrer Herkunftsregion separat untersuchen.

Background: Air 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. Methods: We 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. Results: In 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 (PM_2.5), PM_{2.5absorbance} and respirable particles (PM₁₀). There were no significant associations with PM_coarse, NO₂, NO_x, 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. Conclusions: This study adds to the evidence to reduce ambient PM_2.5 concentrations as low as possible to protect the health of the general population.

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.