Measurements for mitigating adverse health effects from atmospheric particulate pollutants
Atmospheric particulate pollution has been linked to a broad spectrum of adverse health effects including respiratory problems, cardiovascular diseases, cancer and dementia. These effects depend not only on physical, but also on chemical properties of airborne particulate matter (PM) though to date it has proven difficult to disentangle the relative contribution of PM constituents to the reported population-level health effects. We propose the use of “tailored” reference aerosols, combined with high-resolution optical imaging of exposed cells and state-of-the-art cell analysis methods to study the cytotoxic effects of airborne PM in vitro in a systematic way to help inform which PM metrics are associated with the induction of toxic mechanisms that can be linked to specific health effects. Need Airborne particles cause serious acute and chronic human health effects, associated with several hundred thousand premature deaths in the EU each year.
For historical reasons, atmospheric particulate pollutants have been regulated for human health purposes by the mass concentration of discrete size fractions: PM10and PM2.5 (particles with diameter below 10 μm and 2.5 μm, respectively). PM mass concentration, however, fails to capture the chemical heterogeneity of airborne particulates and is uninformative concerning the toxicologically important contributions of ultrafine particles (<100 nm), which are of negligible mass. We and others have therefore hypothesized that PM mass concentration, whilst useful, is not the most informative metric to characterise the potential of particles to cause the disparate detrimental health effects reported in the literature. The focus on mass also precludes the application of intelligent targeting of ‘health-relevant’ constituents.
There is therefore a need to generate new data on the contribution of PM constituents to discrete toxicological relevant pathways that can inform the causal link between the particles we breathe and the down-stream health effects. Such information is vital if new metrics, such as particle size, number concentration and chemistry, are to be integrated into the existing air quality guidelines.The current literature evaluating the associations between air pollution and adverse health outcomes has been dominated by epidemiological studies, investigating the overall healt effects of atmospheric air pollution, including particles, gases and mixtures.
These studies, however, are limited in their capacity to distinguish independent effects of isolated aerosol components or properties on health. To disentangle the effects of the different aerosol properties on health, there is a need for well-defined reference aerosols generated in the laboratory. These aerosols should simulate the properties of real ambient aerosols while being stable and reproducible, with properties that can be "tailored" according to the experimental needs and the specific research questions asked. In vitro studies are essential for understanding the cause-effect relationship between airborne particles and cell/tissue damage.
However, their value is fundamentally dependent on robust in vitro to in vivo correlation. To achieve this there is a need to go beyond the traditional cell-exposure techniques and simple biological models (e.g. 2D cultures). Novel methods for cell exposure that mimic the natural inhalation routes must be employed and new biological models, such as lung organoids and lung scaffolds (3D multicellular structures), must be developed to provide physiologically relevant models for measuring biological effects. Cellular responses to pollutant stressors can be investigated with a combination of optical imaging techniques and biomedical assays. In both cases, quantification and integration of data from across multiple analytical platforms is challenging statistically and subject to measurement error and/or interpretive biases. For a meaningful integration of multiple endpoints to establish adverse outcome pathways (AOPs) in relation to specific PM properties and components, a metrology framework must be established to derive quantitative and reproducible response metrics.
PI: Dr Ian Mudway