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The central goal of human genetics is to understand genetic differences both within and between populations and how these differences contribute to phenotypic variation. Recent advances in genotyping technologies and statistical methodology mean that we can now examine population differences at high genetic resolution, and attempt to find common variants that underlie variation in complex traits in the population. In this thesis, differences in maternal genetic ancestry in Australia were examined and a number of genetic association studies were undertaken in an attempt to map genetic variants that underlie complex traits. Abstract Before presenting the results from the five main genetic analyses, an overview is given of the history of gene-mapping in humans, the challenges this has presented, and the major discoveries from both empirical and theoretical studies that have advanced the field of human genetics to the point where hypothesis-free association testing of common variants with complex traits is now possible. The reasons why mitochondrial DNA has proved so useful in examining the history of populations, and the major findings from the field of mitochondrial population genetics are summarised. In addition, some of the major evidence of a role for mitochondrial variants in complex trait variation is presented. For the first main paper, data from 69 mitochondrial variants that tag the majority of common mitochondrial SNPs in European populations was used to test whether there is evidence for population stratification (i.e. the presence of more than one randomly mating population) in the maternal genetic line of modern Australians. By combining the genetic data with self-reported maternal ancestry data, it was shown that there are significant differences in the patterns of mitochondrial variation between groups of individuals whose maternal ancestors came from different areas of the world. Specifically, it was shown that there are significant differences between groups from different regions of Europe, with those from Eastern Europe showing large differences in SNP and haplogroup frequencies compared to the other groups. A test for assortative mating was performed by comparing whether mates in our sample shared more mitochondrial variants in common when compared to randomly drawn pairs from the population. No evidence of increased sharing was found. The second study involved testing whether common mitochondrial variants are associated with a number of physiological and biochemical traits, the majority of which are risk factors for the metabolic syndrome and type 2 diabetes. Phenotypic and genotypic data was available for just over 2,000 adolescent twins measured at three different timepoints. This is the first known mitochondrial association study to use family data, and a methodology based on a linear model was presented for performing such an association. In spite of having power to detect variants of modest effect, only viii one significant association was found between mt14365 and triacyglycerol levels in twins measured at age 12. This association was not replicated across the other age groups. The third study used the methodology developed for family-based mitochondrial association studies to test for association between mitochondrial variants and a battery of cognitive tests in twins aged 16. A previous study with a small sample size had shown an association between mitochondria and IQ, but this had never been replicated or followed-up. A total of 1,385 individuals from 665 families were included, but no statistically significant associations were found. The most strongly associated SNP was found in a gene in which variants have been shown to influence cognition in mice with a homogeneous nuclear genetic background. For the fourth study, a genome-wide association analysis was carried out of 6 self-reported traits related to the menstrual cycle. Sample sizes ranged from 468 for age at menopause to 5,743 for age at menarche. No SNPs were found to be associated at a genome-wide significant level, however, the results from previous association analyses of age at menarche and age at menopause were replicated. A number of regions for each trait that show modest evidence of association have been identified, and these should be targeted for replication in another sample. In addition, a number of genes that show strong evidence for association with each trait were identified and using a multivariate approach, a SNP in the RNA polymerase III subunit B gene was shown to potentially have a pleiotropic effect on age at menarche and duration of menses. In the final study, a genome-wide association study data for self-reported caffeine consumption and caffeine-related sleep disturbance was performed. A number of loci that potentially influence each trait were identified. The association data was combined with gene expression data from three cell types that had been treated with caffeine. A gene-based test was performed to test whether genes that were found to be consistently up- or down-regulated by caffeine treatment show increased evidence of association. There was no evidence of increased association signals in these genes. A number of the caffeine-regulated genes show strong evidence for overall association and represent good candidate genes for targeted replication in a larger sample. Finally, a synthesis of the main results of each study is presented including potential limitations of this research. This discussion includes a critical assessment of the current findings in both mitochondrial genetics and genome-wide association studies, and potential future directions in the field of gene-mapping in humans. |
