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Statistical Epistasis and Functional Brain Imaging Support a Role of Voltage-Gated Potassium Channels in Human Memory

Despite the current progress in high-throughput, dense genome scans, a major portion of complex traits' heritability still remains unexplained, a phenomenon commonly termed “missing heritability.” The negligence of analytical approaches accounting for gene-gene interaction effects, such as stat...

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Detalles Bibliográficos
Autores principales: Heck, Angela, Vogler, Christian, Gschwind, Leo, Ackermann, Sandra, Auschra, Bianca, Spalek, Klara, Rasch, Björn, de Quervain, Dominique, Papassotiropoulos, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3244442/
https://www.ncbi.nlm.nih.gov/pubmed/22216252
http://dx.doi.org/10.1371/journal.pone.0029337
Descripción
Sumario:Despite the current progress in high-throughput, dense genome scans, a major portion of complex traits' heritability still remains unexplained, a phenomenon commonly termed “missing heritability.” The negligence of analytical approaches accounting for gene-gene interaction effects, such as statistical epistasis, is probably central to this phenomenon. Here we performed a comprehensive two-way SNP interaction analysis of human episodic memory, which is a heritable complex trait, and focused on 120 genes known to show differential, memory-related expression patterns in rat hippocampus. Functional magnetic resonance imaging was also used to capture genotype-dependent differences in memory-related brain activity. A significant, episodic memory-related interaction between two markers located in potassium channel genes (KCNB2 and KCNH5) was observed (P (nominal combined) = 0.000001). The epistatic interaction was robust, as it was significant in a screening (P (nominal) = 0.0000012) and in a replication sample (P (nominal) = 0.01). Finally, we found genotype-dependent activity differences in the parahippocampal gyrus (P (nominal) = 0.001) supporting the behavioral genetics finding. Our results demonstrate the importance of analytical approaches that go beyond single marker statistics of complex traits.