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The probability of an event occurring or the proportion of patients experiencing an event, such as death or disease, is often of interest in medical research. It is a measure that is intuitively appealing to many consumers of statistics and yet the estimation is not always clearly understood or straightforward. Many researchers will take the complement of the survival function, obtained using the Kaplan-Meier estimator. However, in situations where patients are also at risk of competing events, the interpretation of such estimates may not be meaningful. Competing risks are present in almost all areas of medical research. They occur when patients are at risk of more than one mutually exclusive event, such as death from different causes. Although methods for the analysis of survival data in the presence of competing risks have been around since the 1760s there is increasing evidence that these methods are being underused. The primary aim of this thesis is to develop and apply new and accessible methods for analysing competing risks in order to enable better communication of the estimates obtained from such analyses. These developments will primarily involve the use of the recently established exible parametric survival model. Several applications of the methods will be considered in various areas of medical research to demonstrate the necessity of competing risks theory. As there is still a great amount of misunderstanding amongst clinical researchers about when these methods should be applied, considerations are made as to how to best present results. Finally, key concepts and assumptions of the methods will be assessed through sensitivity analyses and implications of data quality will be investigated through the use of a simulation study.

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Genome-wide association studies (GWAS) exploit the correlation in ge- netic diversity along chromosomes in order to detect effects on disease risk without having to type causal loci directly. The inevitable downside of this approach is that, when the correlation between the marker and the causal variant is imperfect, the risk associated with carrying the predisposing allele is diluted and its effect is underestimated. This thesis explores four different facets of this risk dilution: (1) estimating true effect sizes from those observed in GWAS; (2) asking how the context of a GWAS, including the population studied, the genotyping chip employed, and the use of im- putation, affects risk estimates; (3) assessing how often the best-associated SNP in a GWAS coincides with the causal variant; and (4) quantifying how departures from the simplest disease risk model at a causal variant distort the observed disease risk model. Using simulations, where we have information about the true risk at the causal locus, we show that the correlation between the marker and the causal variant is the primary driver of effect size underestimation. The extent of the underestimation depends on a number of factors, including the population in which the study is conducted, the genotyping chip employed, whether imputation is used, and the strength, frequency, and disease model of the risk allele. Suppose that a GWAS study is conducted in a European population, with an Affymetrix 6.0 genotyping chip, without imputation, and that the causal loci have a modest effect on disease risk, are common in the population, and follow an additive disease risk model. In such a study, we show that the risk estimated from the most associated SNP is very close to the truth approximately two-thirds of the time (although we predict that fine mapping of GWAS loci will infrequently identify causal variants with considerably higher risk), and that the best-associated variant is very often perfectly or nearly-perfectly correlated with, and almost always within 0.1cM of, the causal variant. However, the strong correlations among nearby loci mean that the causal and best-associated variants coincide infrequently, less than one-fifth of the time, even if the causal variant is genotyped. We explore ways in which these results change quantitatively depending on the parameters of the GWAS study. Additionally, we demonstrate that we expect to identify substantial deviations from the additive disease risk model among loci where association is detected, even though power to detect departures from the model drops off very quickly as the correlation between the marker and causal loci decreases. Finally, we discuss the implications of our results for the design and interpretation of future GWAS studies.

Les donneurs de méthyles (B12 et folates) régulent le cycle des monocarbones qui joue un rôle primordial dans les régulations épigénétiques/épigénomiques par méthylation. Une carence en donneurs de méthyles produit un retard de croissance intra-utérine et favorise les anomalies du développement, principalement du système nerveux central. De plus, des taux élevés d'homocystéine associés à une telle carence constituent un facteur de risque pour diverses pathologies neurodégénératives. Nous avons étudié les conséquences d'une carence péri-conceptionnelle et gestationnelle sur le développement cérébral embryonnaire de rats Wistar. L'étude morphométrique a montré un retard de croissance des embryons carencés qui affectait également le cerveau, avec une atrophie de structures telles que l'hippocampe, le cortex et la zone subventriculaire. En raison de la forte sensibilité de l'hippocampe, les effets de la carence ont par ailleurs été étudiés sur un modèle cellulaire de progéniteurs neuronaux hippocampiques. L'utilisation de ces deux modèles a permis de montrer in vivo et in vitro la régulation négative par la carence de la voie Stat3, qui influence prolifération et survie, via une régulation épigénomique post-transcriptionnelle impliquant miR-124. La dérégulation du programme neurogénique impliquant les histones désacétylases affecte la différenciation cellulaire. Par ailleurs, nous avons démontré que la carence en donneurs de méthyles était associée à une modification post-traductionnelle correspondant à une N-homocystéinylation irreversible de protéines neuronales, en particulier associées au cytosquelette. Cette modification induit l'agrégation des protéines, phénomène impliqué dans de nombreuses maladies neurodégénératives. La combinaison de ces différents mécanismes apporte un éclairage nouveau sur les défauts de développement et les troubles cognitifs associés à une carence précoce en donneurs de méthyles, soulignant l'importance de la « programmation foetale » dans la survenue de certaines pathologies neurologiques / Methyl donors (B12 and folate) regulate the one-carbon cycle that plays an important role in the epigenetic/epigenomic regulations by methylation. Methyl donor deficiency (MDD) leads to intrauterine growth retardation and promotes neurodevelopmental abnormalities. Also, high levels of homocysteine associated with such a deficiency are a risk factor for various neurodegenerative diseases. We have studied the consequences of a periconceptional and gestational deficiency on the development of the embryonic brain of Wistar rats. Morphometric studies showed retardation in the development of deficient embryos which also affected the brain, with an atrophy of some structures including hippocampus, cortex and subventricular zone. Given the high sensitivity of the hippocampus, the effects of MDD have been additionally studied in a cellular model of hippocampal neuronal progenitors. Using these two models, we showed both in vivo and in vitro the downregulation of Stat3 pathway regulating cell proliferation and survival, through an epigenomic post-transcriptional process involving miR-124. Disruption of the neurogenic program implying histone deacetylases was shown to alter cell differentiation. Furthermore, we showed that methyl donor deficiency was associated with a post-translational modification corresponding to an irreversible N- homocysteinylation of neuronal proteins, especially those associated with the cytoskeleton. Such a process leads to protein aggregation, a phenomenon involved in many neurodegenerative diseases. The combination of these different mechanisms provides new insights into developmental defects and cognitive impairment associated with an early MDD, highlighting the importance of "fetal programming" in the occurrence of some neurological diseases