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Significant overlap between human genome-wide association-study nominated breast cancer risk alleles and rat mammary cancer susceptibility loci
INTRODUCTION: Human population-based genome-wide association (GWA) studies identify low penetrance breast cancer risk alleles; however, GWA studies alone do not definitively determine causative genes or mechanisms. Stringent genome- wide statistical significance level requirements, set to avoid fals...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4054882/ https://www.ncbi.nlm.nih.gov/pubmed/24467842 http://dx.doi.org/10.1186/bcr3607 |
Sumario: | INTRODUCTION: Human population-based genome-wide association (GWA) studies identify low penetrance breast cancer risk alleles; however, GWA studies alone do not definitively determine causative genes or mechanisms. Stringent genome- wide statistical significance level requirements, set to avoid false-positive associations, yield many false-negative associations. Laboratory rats (Rattus norvegicus) are useful to study many aspects of breast cancer, including genetic susceptibility. Several rat mammary cancer associated loci have been identified using genetic linkage and congenic strain based-approaches. Here, we sought to determine the amount of overlap between GWA study nominated human breast and rat mammary cancer susceptibility loci. METHODS: We queried published GWA studies to identify two groups of SNPs, one that reached genome-wide significance and one comprised of SNPs failing a validation step and not reaching genome- wide significance. Human genome locations of these SNPs were compared to known rat mammary carcinoma susceptibility loci to determine if risk alleles existed in both species. Rat genome regions not known to associate with mammary cancer risk were randomly selected as control regions. RESULTS: Significantly more human breast cancer risk GWA study nominated SNPs mapped at orthologs of rat mammary cancer loci than to regions not known to contain rat mammary cancer loci. The rat genome was useful to predict associations that had met human genome-wide significance criteria and weaker associations that had not. CONCLUSIONS: Integration of human and rat comparative genomics may be useful to parse out false-negative associations in GWA studies of breast cancer risk. |
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