Exploring the Role of Low-Frequency and Structural Genetic Variation in Human Complex Traits

Quantitative traits and disease risk in humans are affected by both genetic and environmental factors. Using genome-wide association studies (GWAS) over the past decade, researchers have been successful in finding common genetic polymorphisms that explain a proportion of the variation in many common phenotypes. Despite these significant leaps forward in our understanding, the heritable components of many traits remain largely unaccounted for. A number of explanations as to the “missing heritability” of complex traits and disease risk have been postulated. This thesis addresses some of the unexplained potential sources of heritable trait variation and explores two of its potential causes: low frequency and structural genetic variation. Chapter 1 provides a background to GWAS, what we have learned from them, discusses the different mechanisms of heritability and reviews the potential explanations for “missing heritability” in complex traits. The chapter then describes low frequency and structural genetic variation and how they fit into the spectrum of genetic variation. Chapter 2 describes a study that tests the extent to which low frequency association signals can be discovered through low pass whole genome sequencing when using well-powered gene expression and biomarker phenotypes as model traits. The study then compares these association signals to 1000 Genomes based imputation in the same individuals. Chapter 3 uses methods to detect the structural forms of the human amylase locus with whole-genome sequencing data. The study detects and validates multi-allelic copy number within this region and finds a lack of evidence of a previous association between structural variation of the amylase locus and obesity and body mass index. Chapter 4 scans for rare copy-number variation (CNV) using SNP microarray data from over 120 thousand individuals at 69 sites that were previously identified as being associated with developmental delay. The chapter aims to refine their prevalence in the general population and attempts to understand their relationship with developmental delay and complex traits. Chapter 5 aims to detect large deletions and duplications genome-wide using SNP microarray data in a sample of over 120 thousand individuals where we have power to detect rare copy number events. I used novel approaches to test their association with 204 clinically relevant complex traits to determine their role in the heritability of complex traits. Chapter 6 discusses the findings from the previous chapters within this thesis. I then continue by describing some limitations of this work and explore the potential further directions for future work in this area of study

Japan’s foreign policy towards India : a neoclassical realist analysis of the policymaking process

This thesis analyses the formation of Japanese foreign policy through the case study of relations with India. The study concentrates on three streams of Japanese diplomacy; namely economic relations, nuclear policy and security issues through the theoretical framework of neoclassical realism (NCR). This approach, considered the ‘third generation’ of the mainstream paradigm, utilises neo-realism’s focus on structural factors and ultimately places primacy on systemic forces. Yet NCR seeks a more nuanced appraisal of foreign policy and incorporates internal structures into analysis. The dissertation argues that structural factors including India’s economic growth, the rise of China and facilitation provided by the US, initiated interest in India and continues to shape the development of policy. ‘China-hedging’ does not provide the only rationale. Furthermore, whilst structure is vital, with differing influential weight dependent on policy, it is unable alone to explain the exact nature and timing of policy decisions. In order to achieve this, the domestic ‘black box’ needs to be explored through analysis of unit-level variables such as policymakers’ perceptions, business interests, public opinion and norms. Elites in Japan have been particularly slow to appreciate India’s strategic worth despite favourable environmental conditions. The business community is noted as an important influence but whilst public opinion plays a minimal role overall, the prevalence of norms is able to dictate how policy is framed. The scope of the research project is confined to approximately the past two decades, though attention is given to historical relations to place contemporary analysis in context. Empirical data was sourced from academic, government and media outlets in addition to extensive interview fieldwork in Tokyo, Delhi, London and Washington DC. This thesis contributes to a nascent literature on an increasingly important area of not only Japan’s diplomacy but the regional dynamics of region no scholar of international relations can ignore

An Induced Natural Selection Heuristic for Finding Optimal Bayesian Experimental Designs

Bayesian optimal experimental design has immense potential to inform the collection of data so as to subsequently enhance our understanding of a variety of processes. However, a major impediment is the difficulty in evaluating optimal designs for problems with large, or high-dimensional, design spaces. We propose an efficient search heuristic suitable for general optimisation problems, with a particular focus on optimal Bayesian experimental design problems. The heuristic evaluates the objective (utility) function at an initial, randomly generated set of input values. At each generation of the algorithm, input values are "accepted" if their corresponding objective (utility) function satisfies some acceptance criteria, and new inputs are sampled about these accepted points. We demonstrate the new algorithm by evaluating the optimal Bayesian experimental designs for the previously considered death, pharmacokinetic and logistic regression models. Comparisons to the current "gold-standard" method are given to demonstrate the proposed algorithm as a computationally-efficient alternative for moderately-large design problems (i.e., up to approximately 40-dimensions)