Genetic architecture of complex disease in humans :a cross-population exploration

• Main Author: Martínez Marigorta, Urko, 1983-
• Other Authors: Navarro i Cuartiellas, Arcadi, 1969-
• Format: Doctoral Thesis
• Language: English
• Published: Universitat Pompeu Fabra 2012
• Subjects: Complex disease; Genome-wide association studies; Human populations; Replicability; Genetic architecture of disease; Rare variants; Infinitesimal model; Genomic and personalized medicine; Enfermedades complejas; Estudio de asociación genómica; Poblaciones humanas; Replicabilidad; Arquitectura genética; Variantes raras; Modelo infinitesimal; Medicina personalizada y genómica; 575
• Online Access: http://hdl.handle.net/10803/96909

The aetiology of common diseases is shaped by the effects of genetic and environmental factors. Big efforts have been devoted to unravel the genetic basis of disease with the hope that it will help to develop new therapeutic treatments and to achieve personalized medicine. With the development of high-throughput genotyping technologies, hundreds of association studies have described many loci associated to disease. However, the depiction of disease architecture remains incomplete. The aim of this work is to perform exhaustive comparisons across human populations to evaluate pressing questions. Our results provide new insights in the allele frequency of risk variants, their sharing across populations and the likely architecture of disease === La etiología de las enfermedades comunes está formada por factores genéticos y ambientales. Se ha puesto mucho empeño en describir sus bases genéticas. Este conocimiento será útil para desarrollar nuevas terapias y la medicina personalizada. Gracias a las técnicas de genotipado masivo, centenares de estudios de asociación han descrito una infinidad de genes asociados a enfermedad. Pese a ello, la arquitectura genética de las enfermedades no ha sido totalmente descrita. Esta tesis pretende llevar a cabo exhaustivas comparaciones entre poblaciones para responder diversas preguntas candentes. Nuestros resultados dan pistas sobre la frecuencia de los alelos de riesgo, su presencia entre poblaciones y la probable arquitectura de las enfermedades.