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Particulate air pollution is widespread, yet we have little understanding of the long-term health implications associated with exposure. We investigated DNA damage, mutation, and methylation in gametes of male mice exposed to particulate air pollution in an industrial/ urban environment. C57BL/CBA mice were exposed in situ to ambient air near two integrated steel mills and a major highway, alongside control mice breathing high-efficiency air particulate (HEPA) filtered ambient air. PCR analysis of an expanded simple tandem repeat (ESTR) locus revealed a 1.6-fold increase in sperm mutation frequency in mice exposed to ambient air for 10 wks, followed by a 6-wk break, compared with HEPA-filtered air, indicating that mutations were induced in spermatogonial stem cells. DNA collected after 3 or 10 wks of exposure did not exhibit increased mutation frequency. Bulky DNA adducts were below the detection threshold in testes samples, suggesting that DNA reactive chemicals do not reach the germ line and cause ESTR mutation. In contrast, DNA strand breaks were elevated at 3 and 10 wks, possibly resulting from oxidative stress arising from exposure to particles and associated airborne pollutants. Sperm DNA was hypermethylated in mice breathing ambient relative to HEPAfiltered air and this change persisted following removal from the environmental exposure. Increased germ-line DNA mutation frequencies may cause population-level changes in genetic composition and disease. Changes in methylation can have widespread repercussions for chromatin structure, gene expression and genome stability. Potential health effects warrant extensive further investigation.DNA adducts ͉ DNA strand breaks ͉ tandem repeat mutation C ombustion of fossil fuels results in the production of complex mixtures of chemicals that are released into the environment and potentially affect millions of people globally. Previous work demonstrated that the offspring of wild birds breeding near integrated steel mills on the North American Great Lakes inherited increased numbers of tandem repeat DNA sequence mutations compared with those from areas without steel mills (1, 2). Subsequent studies investigated expanded simple tandem repeat (ESTR) mutation in outbred laboratory mice caged near two integrated steel mills and a major highway in Hamilton, Ontario, Canada, and at a rural reference site (3, 4). Using a pedigree approach (5), a significant increase in germ-line mutation rate was found in mice housed in the industrial environment compared with the reference site. The majority of mutations were transmitted through the paternal germ line. High-efficiency particulate-air (HEPA) filtration of the ambient air resulted in a significant reduction in mutation frequency, down to levels measured at the reference location (4). Therefore, the particulate fraction of air in this industrial location was largely responsible for the mutagenic hazard.These findings show that chemical pollutants may cause heritable mutation. Further research is required to confirm these results...

Exhaled breath contains thousands of volatile organic compounds (VOCs) of which the composition varies depending on health status. Various metabolic processes within the body produce volatile products that are released into the blood and will be passed on to the airway once the blood reaches the lungs. Moreover, the occurrence of chronic inflammation and/or oxidative stress can result in the excretion of volatile compounds that generate unique VOC patterns. Consequently, measuring the total amount of VOCs in exhaled air, a kind of metabolomics also referred to as breathomics, for clinical diagnosis and monitoring purposes gained increased interest over the last years. This paper describes the currently available methodologies regarding sampling, sample analysis and data processing as well as their advantages and potential drawbacks. Additionally, different application possibilities of VOC profiling are discussed. Until now, breathomics has merely been applied for diagnostic purposes. Exhaled air analysis can, however, also be applied as an analytical or monitoring tool. Within the analytic perspective, the use of VOCs as biomarkers of oxidative stress, inflammation or carcinogenesis is described. As monitoring tool, breathomics can be applied to elucidate the heterogeneity observed in chronic diseases, to study the pathogen(s) responsible for occurring infections and to monitor treatment efficacy.

The discriminant analyses demonstrated that asthma and healthy groups are distinct from one another. A total of eight components discriminated between asthmatic and healthy children with a 92% correct classification, achieving a sensitivity of 89% and a specificity of 95%. Conclusion The results show that a limited number of VOC in exhaled air can well be used to distinguish children with asthma from healthy children.

We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics.

SummaryLow-dose exposures to common environmental chemicals that are deemed safe individually may be combining to instigate carcinogenesis, thereby contributing to the incidence of cancer. This risk may be overlooked by current regulatory practices and needs to be vigorously investigated.

No abstract

Ventilator-associated pneumonia (VAP) is a nosocomial infection occurring in the intensive care unit (ICU). The diagnostic standard is based on clinical criteria and bronchoalveolar lavage (BAL). Exhaled breath analysis is a promising non-invasive method for rapid diagnosis of diseases and contains volatile organic compounds (VOCs) that can differentiate diseased from healthy individuals. The aim of this study was to determine whether analysis of VOCs in exhaled breath can be used as a non-invasive monitoring tool for VAP. One hundred critically ill patients with clinical suspicion of VAP underwent BAL. Before BAL, exhaled air samples were collected and analysed by gas chromatography time-of-flight mass spectrometry (GC-tof-MS). The clinical suspicion of VAP was confirmed by BAL diagnostic criteria in 32 patients [VAP(+)] and rejected in 68 patients [VAP(−)]. Multivariate statistical comparison of VOC profiles between VAP(+) and VAP(−) revealed a subset of 12 VOCs that correctly discriminated between those two patient groups with a sensitivity and specificity of 75.8% ± 13.5% and 73.0% ± 11.8%, respectively. These results suggest that detection of VAP in ICU patients is possible by examining exhaled breath, enabling a simple, safe and non-invasive approach that could diminish diagnostic burden of VAP.