La peau est un excellent modèle d’étude du vieillissement général. En plus de facteurs environnementaux, les facteurs génétiques jouent un rôle majeur dans le vieillissement cutané. Dans le cadre de ma thèse, j’ai eu accès à une cohorte exceptionnelle de 502 femmes caucasiennes très bien caractérisées sur le plan cutané, pour effectuer deux études d’association « génome-entier ». La première étude a montré le rôle joué par le système immunitaire, et en particulier le gène HLA‑C, dans la sévérité des lentigines du visage. La seconde a mis en évidence une association entre le gène H2AFY2 et la sévérité de l’affaissement de la paupière supérieure. La recherche de voies de signalisation biologiques associées à différents indicateurs du vieillissement cutané a souligné le rôle de la mélanogénèse et des mécanismes de réparation de l’ADN.Ces résultats ouvrent de nouvelles perspectives dans la compréhension des mécanismes inhérents au vieillissement cutané et général. / The skin is an excellent model to study general ageing. In addition to environmental factors, genetic factors play a key role in skin ageing mechanisms. During my PhD, I have had access to a unique cohort of 502 Caucasian women very-well characterized regarding their facial features to perform two genome-wide association studies. The first one pointed to the role of the immune system, and especially the HLA‑C gene, in the severity of facial lentigines. The second one identified an association between the H2AFY2 gene and the severity of superior eyelid drooping. I also looked for associations between biological pathways and several skin ageing indicators which underlined the role of the melanogenesis and several mechanisms of DNA repair.Overall, these results lead to new insights in the understanding of the molecular mechanisms underlying skin and global ageing.

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Despite some great success, many human diseases cannot be effectively treated, prevented or cured, yet. Moreover, prescribed drugs are often not very efficient and cause undesired side effects. Hence, there is a need to investigate the molecular basis of diseases and adverse drug reactions in more detail. For this purpose, relevant biomedical data needs to be gathered, integrated and analysed in a meaningful way. In this regard, we have developed novel integrative analysis approaches based on both perspectives, classical multivariate statistics and systems biology. A novel multilevel statistical method has been developed for exploiting molecular and pharmacological information for a set of drugs in order to investigate undesired side effects. Systems biology approaches have been used to study the genetic basis of human diseases at a global scale. For this purpose, we have developed an integrated gene-disease association database and tools for user-friendly access and analysis. We showed that modularity applies for mendelian, complex and environmental diseases and identified disease-related core biological processes. We have constructed a workflow to investigate adverse drug reactions using our gene-disease association database. A detailed study of currently available pathway data has been performed to evaluate its applicability to build network models. Finally, a strategy to integrate information about sequence variations with biological pathways has been implemented to study the effect of the sequence variations onto biological processes. In summary, the developed methods are of immense practical value for other biomedical researchers and can aid to improve the understanding of the molecular basis of diseases and adverse drug reactions.A pesar de que existen tratamientos eficaces para las enfermedades, no hay todavía una cura o un tratamiento efectivo para muchas de ellas. Asimismo los medicamentos pueden ser ineficaces o causar efectos secundarios indeseables. Por lo tanto, es necesario investigar en profundidad las bases moleculares de las enfermedades y de los efectos secundarios de los medicamentos. Para ello, es necesario identificar y analizar de forma integrada los datos biomédicos relevantes. En este sentido, hemos desarrollado nuevos métodos de análisis e integración de datos biomédicos que van desde el análisis estadístico multivariante a la biología de sistemas. En primer lugar, hemos desarrollado un nuevo método estadístico multinivel para la explotación de la información molecular y farmacológica de un conjunto de drogas a fin de investigar efectos secundarios no deseados. Luego, hemos usado métodos de biología de sistemas para estudiar las bases genéticas de enfermedades humanas a escala global. Para ello, hemos integrado en una base de datos asociaciones entre genes y enfermedades y hemos desarrollado herramientas para el fácil acceso y análisis de los datos. Mostramos que las enfermedades mendelianas, complejas y ambientales presentan modularidad e identificamos los procesos biológicos relacionados con dichas enfermedades. Hemos construido una herramienta para investigar las reacciones adversas a los medicamentos basada en nuestra base de datos de asociaciones entre genes y enfermedades. Realizamos un estudio detallado de los datos disponibles sobre los procesos biológicos para evaluar su aplicabilidad en la construcción de modelos dinámicos. Por último, desarrollamos una estrategia para integrar la información sobre las variaciones de secuencia de genes con los procesos biológicos para estudiar el efecto de dichas variaciones en los procesos biológicos. En resumen, los métodos presentados en esta tesis constituyen una herramienta valiosa para otros investigadores y pueden ayudar a mejorar la comprensión de las bases moleculares de las enfermedades y de las reacciones adversas a los medicamentos.

Indiana University-Purdue University Indianapolis (IUPUI) / Alzheimer's disease (AD) is a national priority, with nearly six million Americans affected at an annual cost of $200 billion and no available cure. A better understanding of the mechanisms underlying AD is crucial to combat its high and rising incidence and burdens. Most cases of AD are thought to have a complex etiology with numerous genetic and environmental factors influencing susceptibility. Recent genome-wide association studies (GWAS) have confirmed roles for several hypothesized genes and have discovered novel loci associated with disease risk. However, most GWAS-implicated genetic variants have displayed modest individual effects on disease risk and together leave substantial heritability and pathophysiology unexplained. As a result, new paradigms focusing on biological pathways have emerged, drawing on the hypothesis that complex diseases may be influenced by collective effects of multiple variants – of a variety of effect sizes, directions, and frequencies – within key biological pathways. A variety of tools have been developed for pathway-based statistical analysis of GWAS data, but consensus approaches have not been systematically determined. We critically review strategies for genetic pathway analysis, synthesizing extant concepts and methodologies to guide application and future development. We then apply pathway-based approaches to complement GWAS of key AD-related endophenotypes, focusing on two early, hallmark features of disease, episodic memory impairment and brain deposition of amyloid-β. Using GWAS and pathway analysis, we confirmed the association of APOE (apolipoprotein E) and discovered additional genetic modulators of memory functioning and amyloid-β deposition in AD, including pathways related to long-term potentiation, cell adhesion, inflammation, and NOTCH signaling. We also identified genetic associations to amyloid-β deposition that have classically been understood to mediate learning and memory, including the BCHE gene and signaling through the epidermal growth factor receptor. These findings validate the use of pathway analysis in complex diseases and illuminate novel genetic mechanisms of AD, including several pathways at the intersection of disease-related pathology and cognitive decline which represent targets for future studies. The complexity of the AD genetic architecture also suggests that biomarker and treatment strategies may require simultaneous targeting of multiple pathways to effectively combat disease onset and progression.