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Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set

Multiple studies have identified loci associated with the risk of developing prostate cancer but the associated genes are not well studied. Here we create a normal prostate tissue-specific eQTL data set and apply this data set to previously identified prostate cancer (PrCa)-risk SNPs in an effort to...

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Detalles Bibliográficos
Autores principales: Thibodeau, S. N., French, A. J., McDonnell, S. K., Cheville, J., Middha, S., Tillmans, L., Riska, S., Baheti, S., Larson, M. C., Fogarty, Z., Zhang, Y., Larson, N., Nair, A., O'Brien, D., Wang, L., Schaid, D J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Pub. Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4663677/
https://www.ncbi.nlm.nih.gov/pubmed/26611117
http://dx.doi.org/10.1038/ncomms9653
Descripción
Sumario:Multiple studies have identified loci associated with the risk of developing prostate cancer but the associated genes are not well studied. Here we create a normal prostate tissue-specific eQTL data set and apply this data set to previously identified prostate cancer (PrCa)-risk SNPs in an effort to identify candidate target genes. The eQTL data set is constructed by the genotyping and RNA sequencing of 471 samples. We focus on 146 PrCa-risk SNPs, including all SNPs in linkage disequilibrium with each risk SNP, resulting in 100 unique risk intervals. We analyse cis-acting associations where the transcript is located within 2 Mb (±1 Mb) of the risk SNP interval. Of all SNP–gene combinations tested, 41.7% of SNPs demonstrate a significant eQTL signal after adjustment for sample histology and 14 expression principal component covariates. Of the 100 PrCa-risk intervals, 51 have a significant eQTL signal and these are associated with 88 genes. This study provides a rich resource to study biological mechanisms underlying genetic risk to PrCa.