Understanding the transmission dynamics of infectious diseases is important to well-informed public health policy, responsive infection control and individual patient management. The on-going revolution in whole-genome sequencing provides unprecedented resolution for detecting evidence of recent transmission and characterising population-level transmission dynamics. In this thesis, I develop and apply evolutionary approaches to investigating transmission, focusing on three globally important pathogens. Hepatitis C virus (HCV) is a major cause of liver disease affecting 150 million people and killing 350,000 annually. I conducted a meta-analysis of twentieth-century HCV epidemics, finding that the age of the epidemic can be predicted by genetic diversity. Using the coalescent, I fitted classic susceptible-infected (SI), susceptible-infected-susceptible (SIS) and susceptible-infected-recovered (SIR) epidemiological models. Most epidemics showed signatures of SI dynamics, but three, from Argentina, Hong Kong and Thailand, revealed complex SIR dynamics. Norovirus is the leading viral cause of diarrhoea, estimated to cost the NHS around £115 million annually. I analysed whole norovirus genomes via a stochastic transmission model, finding that up to 86% of hospital infection was attributable to transmission from another patient in the hospital. In contrast, the rate of new introductions to hospital by infected patients was extremely low (<0.0001%), underlining the importance of ward management during outbreaks. Campylobacter is the most commonly identified cause of bacterial gastroenteritis worldwide. I developed a zoonotic transmission model based on phylogeography approaches to test whether three strains previously associated with multiple host species were in fact aggregates of strongly host-restricted sub-strains, or genuine generalists. Members of the same strain isolated from different host species were often more closely related than those isolated from the same host species. I estimated 419, 389 and 31 zoonotic transmissions in ST-21, ST-45 and ST-828 respectively, strongly supporting the hypothesis that these strains are adapted to a generalist lifestyle.

Human ageing is accompanied by characteristic metabolic and endocrine changes, including altered hormone profiles, insulin resistance and deterioration of skeletal muscle. Obesity and diabetes may themselves drive an accelerated ageing phenotype. Untangling the causal web between ageing, obesity and diabetes is a priority in order to understand their aetiology and improve prevention and management. The role of biological ageing in determining the risk of obesity and associated conditions has often been examined using mean leukocyte telomere length (LTL), a marker of replicative fatigue and senescence. However, considering phenotypes which represent different domains of biological and functional ageing as exposures for obesity and related traits could allow the elucidation of new understudied phenotypes relevant to cardio-metabolic risk in the wider population. This PhD considers the causal role of (1) hand grip strength (HGS), a marker of overall strength and physical functioning, and (2) resting energy expenditure, an indicator of overall energy metabolism and the major component of daily energy expenditure, in cardio-metabolic risk. I also characterise a new and readily-quantifiable marker of age-related genomic instability, mosaic loss of the Y chromosome (mLOY). Observational evidence implicates each of these phenotypes in cardio-metabolic conditions and intermediate phenotypes. However, it is not possible to infer causality from these observational associations due to confounding and reverse-causality. Mendelian randomisation offers a solution to these limitations and can allow the causal nature of these relationships to be investigated. Using population-based data including UK Biobank, this thesis presents the first large-scale genetic discovery effort for each trait and provides new biological insight into their shared and separate aetiology. I used identified variants to investigate the bidirectional causal associations of each trait with cardio-metabolic outcomes, intermediate phenotypes and other related traits such as frailty and mortality. In total I identified 16 loci for hand grip strength, 19 for mLOY, and one signal for REE. I have shown that HGS is likely to be causally linked to fracture risk, and I have identified the important shared genetic architecture between mLOY, glycaemic traits and cancer. I have also demonstrated that at least one known genetic variant contributing to obesity risk acts partially via reduced REE. Overall the findings of my PhD contribute to our wider understanding of the aetiological role of ageing processes in metabolic dysfunction, and have implications for both basic science and translational applications.

Investigation of the relationship between iron deficiency, iron supplementation and susceptibility to infection, was suggested by the author's initial observations of an association of anaemia with serious bacterial infections in infancy in Papua New Guinea. The bulk of previous longitudinal clinical intervention studies in infancy showed beneficial effects of iron supplementation. However, defects of control and design and recording in these studies and contradictory anecdotal reports left the question unresolved. A prospective, placebo-controlled, randomised, double-blind trial of iron prophylaxis (3ml intramuscular iron dextran = 150mg Fe) to two month old infants was carried out on the North Coast of Papua New Guinea where there is high transmission of malaria. A literature review, pilot studies, protocol, demography, geography and laboratory methods developed are described. Findings indicate that the placebo control group became relatively iron deficient over the first year of life and that the iron dextran group had adequate, although not excessive iron stores and a higher mean haemoglobin; however, the prevalence and effects of malaria recorded in the field were higher in the iron dextran group. Analysis of field and hospital infectious morbidity in the trial indicated a deleterious association with iron dextran for all causes including respiratory infections (the main single reason for admission). Total duration of hospitalisation was significantly increased in the iron dextran group. Analysis of other factors showed (1) a higher admission rate associated with low weight-for-height recorded at the start of the trial; (2) a significant positive correlation between birth haemoglobin and hospital morbidity rates; (3) increased malaria rates in primiparous mothers of the cohort infants who received iron infusion during pregnancy; (4) lower relative risk of malaria associated with iron prophylaxis in individuals with alpha thalassaemia, which was found to be highly prevalent in this region. In conclusion, it is suggested that policies of iron supplementation, total dose iron injection and routine presumptive iron therapy for anaemia which are widely in practice in malaria endemic areas should be closely reviewed.

During human immunodeficiency virus 1 (HIV-1) infection, the viral population is in constant battle with the host immune system. The cytotoxic T-lymphocyte (CTL) response, a branch of the adaptive immune response, is implicated in viral control and can drive viral evolution in the infected host population. Endogenous viral peptides, or ‘epitopes’, are presented to CTLs by human leukocyte antigen (HLA) class I molecules on the surface of infected cells where they may be identified as non-self. Mutations in or proximal to a viral epitope can result in ‘escape’ from CTLs targeting that epitope. The repertoire of epitopes which may be presented is dependent upon host class I HLA types. As such, reversion may occur after transmission due to changes in viral fitness and selection in the context of a new HLA background. Thus, parameters describing the dynamics of CTL escape and reversion are key to understanding how CTL responses within individuals relate to HIV-1 sequence evolution in the infected host population. Escape and reversion can be studied directly using biological assays and longitudinal viral sequence data, or indirectly by considering viral sequences across multiple hosts. Indirect approaches include tree based methods which detect associations between host HLA and viral sequence but do not estimate rates of escape and reversion, and ordinary differential equation (ODE) models which estimate these rates but do not consider the dependency structure inherent in viral sequence data. We introduce two models which estimate escape and reversion rates whilst accounting for the shared ancestry of viral sequence data. For our first model, we lay out an integrated Bayesian approach which combines genealogical inference and an existing epidemiological model to inform escape and reversion rate estimates. Using this model, we find evidence for correlation between escape rate estimates across widely separated geographical regions. We also observe a non-linear negative correlation between in vitro replicative capacity and escape rate. Both findings suggest that epistasis does not play a strong role in the escape process. Although our first model worked well, it had some key limitations which we address in our second method. Notably, by making a series of approximations, we are able account for recombination and analyse very large datasets which would be computationally infeasible under the first model. We verify our second approach through extensive simulations, and use the method to estimate both drug and HLA associated selection along portions of the HIV-1 genome. We test the results of the model using existing knowledge, and determine a collection of putative selected sites which warrant further investigation. Finally, we find evidence to support the notion that the CTL response played a role in HIV-1 subtype diversification.

Ankylosing spondylitis (AS) is a common inflammatory arthritis of the spine and other affected joints, which is highly heritable, being strongly influenced by the HLA-B27 status, as well as hundreds of mostly unknown genetic variants of smaller effect. The aim of my research was to confirm some of the previously observed genetic associations and to identify new associations, many of which are in biological pathways relevant to AS pathogenesis, most notably the IL-23/T_H17 axis (IL23R) and antigen presentation (ERAP1 and ERAP2). Studies presented in this thesis include replication and refinement of several potential associations initially identified by earlier GWAS (WTCCC-TASC, 2007 and TASC, 2010). I conducted an extended study of IL23R association with AS and undertook a meta-analysis, confirming the association between AS and IL23R (non-synonymous SNP rs11209026, p=1.5 x 10-9, OR=0.61). An extensive re-sequencing and fine mapping project, including a meta-analysis, to replicate and refine the association of TNFRSF1A with AS was also undertaken; a novel variant in intron 6 was identified and a weak association with a low frequency variant, rs4149584 (p=0.01, OR=1.58), was detected. Somewhat stronger associations were seen with rs4149577 (p=0.002, OR=0.91) and rs4149578 (p=0.015, OR=1.14) in the meta-analysis. Associations at several additional loci had been identified by a more recent GWAS (WTCCC2-TASC, 2011). I used in silico techniques, including imputation using a denser panel of variants from the 1000 Genomes Project, conditional analysis and rare/low frequency variant analysis, to refine these associations. Imputation analysis (1782 cases/5167 controls) revealed novel associations with ERAP2 (rs4869313, p=7.3 x 10-8, OR=0.79) and several additional candidate loci including IL6R, UBE2L3 and 2p16.3. Ten SNPs were then directly typed in an independent sample (1804 cases/1848 controls) to replicate selected associations and to determine the imputation accuracy. I established that imputation using the 1000 Genomes Project pilot data was largely reliable, specifically for common variants (genotype concordence~97%). However, more accurate imputation of low frequency variants may require larger reference populations, like the most recent 1000 Genomes reference panels. The results of my research provide a better understanding of the complex genetics of AS, and help identify future targets for genetic and functional studies.