2008
DOI: 10.1007/s00439-008-0522-8
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Exploiting the proteome to improve the genome-wide genetic analysis of epistasis in common human diseases

Abstract: One of the central goals of human genetics is the identification of loci with alleles or genotypes that confer increased susceptibility. The availability of dense maps of single-nucleotide polymorphisms (SNPs) along with high-throughput genotyping technologies has set the stage for routine genomewide association studies that are expected to significantly improve our ability to identify susceptibility loci. Before this promise can be realized, there are some significant challenges that need to be addressed. We … Show more

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Cited by 80 publications
(52 citation statements)
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“…This approach detected the risk SNP modules using SNP networks, which provides a flexible strategy for the identification of the synergies of multiple SNPs by allowing for changes to the connection density of the SNP network. In our work, SNP-SNP interactions are identified solely based on the adjacency of SNPs on the chromosome; in addition to genomic location, other prior biological knowledge such as protein- protein interaction network information (Emily et al, 2009;Pattin and Moore, 2008) could also be used to construct the genomic-context SNP network. The results of simulations described herein demonstrate that this new method performs well with regard to its accuracy and false positive rates.…”
Section: Discussionmentioning
confidence: 99%
“…This approach detected the risk SNP modules using SNP networks, which provides a flexible strategy for the identification of the synergies of multiple SNPs by allowing for changes to the connection density of the SNP network. In our work, SNP-SNP interactions are identified solely based on the adjacency of SNPs on the chromosome; in addition to genomic location, other prior biological knowledge such as protein- protein interaction network information (Emily et al, 2009;Pattin and Moore, 2008) could also be used to construct the genomic-context SNP network. The results of simulations described herein demonstrate that this new method performs well with regard to its accuracy and false positive rates.…”
Section: Discussionmentioning
confidence: 99%
“…This problem is exaggerated when large-scale (e.g., genome-wide) explorations are conducted, since the number of false positive findings is greatly increased. However, by focusing on interactions between genes known to be involved in disease-related biological processes, one can maximize a priori biological plausibility and post-hoc interpretability while reducing the multiple testing correction threshold and computational burden (Pattin and Moore 2008). In this study, we investigated genes from the AD pathway of the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, which is a collection of manually curated pathways based on published literature for metabolism, genetic and environmental information processing, and human diseases, including AD (Kanehisa and Goto 2000; Kanehisa et al 2012).…”
Section: Introductionmentioning
confidence: 99%
“…Using biological expert knowledge from protein-protein interaction databases, the Gene Ontology, or known biochemical pathways we should be able to identify SNPs likely to be predictive of disease risk. For example, Pattin et al argue that once we successfully develop the methods to extract expert knowledge from protein-protein interaction databases, we will improve our ability to identify important epistatic interactions in genomewide studies [18]. By using biological knowledge to drive this search, the potential exists to enhance our comprehension of common human diseases.…”
Section: Editorial Discussionmentioning
confidence: 98%