Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

FAM49 - A novel regulator of the protrusive behaviour and motility of cells

Most eukaryotic cell motility relies on plasma membrane protrusions, which depend on the actin cytoskeleton and its tight regulation. The SCAR/WAVE complex, a pentameric assembly comprising SCAR/WAVE, Nap1, CYFIP/Pir121, Abi and HSPC300, is a key driver of actin-based protrusions such as pseudopods. SCAR/WAVE is thought to activate the Arp2/3 complex, a crucial actin nucleator, after being itself activated by upstream signals such as active Rac1. Despite recent progress on the study of the SCAR/WAVE complex, its regulation is still incompletely understood, with Nap1’s role being particularly enigmatic. Upon screening for potential Nap1 binding partners in the social amoeba Dictyostelium discoideum – a well established model organism in the study of the actin cytoskeleton and cell motility – we found FAM49, a ~36 kDa protein of unknown function which is highly conserved in Metazoa (animals) and evolutionarily closer species such as D. discoideum. Interestingly, D. discoideum’s FAM49 and its homologs contain a DUF1394 domain, which is also predicted in CYFIP/Pir121 proteins and most likely involved in their direct binding to active Rac1, which in turn contributes to SCAR/WAVE’s activation. FAM49’s unknown role, apparent high degree of conservation and potential connections to SCAR/WAVE and Rac1 persuaded us to start investigating its function and biological relevance in D. discoideum, leading to the work presented in this thesis. Several pieces of our data collectively support a function for FAM49 in modulating the protrusive behaviour, and ultimately motility, of D. discoideum cells, as well as a regulatory link between FAM49 and Rac1. FAM49’s involvement in protrusion regulation was first hinted at by our observation that GFP-tagged FAM49 is enriched in pseudopods. The possibility of a link with Rac1 was then strengthened by two additional observations: first, pseudopodial GFP-FAM49 is substantially co-enriched with active Rac, both showing fairly comparable spatio-temporal accumulation dynamics; second, when dominant-active (G12V) Rac1 is expressed in cells, it triggers the recruitment and persistent accumulation of GFP-FAM49 at the plasma membrane, where both become highly co-enriched. We subsequently determined that fam49 KO cells differ from wild-type cells in the way they protrude and move, as assessed in under-agarose chemotaxis assays. In particular, our data indicate that fam49 KO cells tend to display a lower degree of global protrusive activity, their protrusions extend more slowly and are less discrete, and the cells end up moving at lower speeds and with higher directional persistence. This phenotype was substantially rescued by FAM49 re-expression. While re-expressing FAM49 in fam49 KO cells we generated putative FAM49 overexpressor cells; compared to wild-type cells, they displayed atypically thin pseudopods and what seemed to be an excessively dynamic, and perhaps less coordinated, protrusive behaviour. Additional data in our study suggest that pseudopods made by fam49 KO cells are still driven by SCAR/WAVE, which is clearly not being replaced by WASP (as is now known to be the case in D. discoideum cells lacking a functional SCAR/WAVE complex). Nonetheless, the peculiar dynamics of those pseudopods imply that SCAR/WAVE’s activity is regulated differently when FAM49 is lost, though it remains to be determined how. This thesis is the first report of a dedicated study on FAM49 and lays the foundation for future research on it.