A1 Refereed original research article in a scientific journal
Two-locus genome-wide linkage scan for prostate cancer susceptibility genes with an interaction effect
Authors: Chang BL, Lange EM, Dimitrov L, Valis CJ, Gillanders EM, Lange LA, Wiley KE, Isaacs SD, Wiklund F, Baffoe-Bonnie A, Langefeld CD, Zheng SL, Matikainen MP, Ikonen T, Fredriksson H, Tammela T, Walsh PC, Bailey-Wilson JE, Schleutker J, Gronberg H, Cooney KA, Isaacs WB, Suh E, Trent JM, Xu JF, Xu JF
Publisher: SPRINGER
Publication year: 2006
Journal: Human Genetics
Journal name in source: HUMAN GENETICS
Journal acronym: HUM GENET
Volume: 118
Issue: 6
First page : 716
Last page: 724
Number of pages: 9
ISSN: 0340-6717
DOI: https://doi.org/10.1007/s00439-005-0099-4
Abstract
Prostate cancer represents a significant worldwide public health burden. Epidemiological and genetic epidemiological studies have consistently provided data supporting the existence of inherited prostate cancer susceptibility genes. Segregation analyses of prostate cancer suggest that a multigene model may best explain familial clustering of this disease. Therefore, modeling gene-gene interactions in linkage analysis may improve the power to detect chromosomal regions harboring these disease susceptibility genes. In this study, we systematically screened for prostate cancer linkage by modeling two-locus gene-gene interactions for all possible pairs of loci across the genome in 426 prostate cancer families from Johns Hopkins Hospital, University of Michigan, University of Ume (a) over circle, and University of Tampere. We found suggestive evidence for an epistatic interaction for six sets of loci (target chromosome-wide/reference marker-specific P <= 0.0001). Evidence for these interactions was found in two independent subsets from within the 426 families. While the validity of these results requires confirmation from independent studies and the identification of the specific genes underlying this linkage evidence, our approach of systematically assessing gene-gene interactions across the entire genome represents a promising alternative approach for gene identification for prostate cancer.
Prostate cancer represents a significant worldwide public health burden. Epidemiological and genetic epidemiological studies have consistently provided data supporting the existence of inherited prostate cancer susceptibility genes. Segregation analyses of prostate cancer suggest that a multigene model may best explain familial clustering of this disease. Therefore, modeling gene-gene interactions in linkage analysis may improve the power to detect chromosomal regions harboring these disease susceptibility genes. In this study, we systematically screened for prostate cancer linkage by modeling two-locus gene-gene interactions for all possible pairs of loci across the genome in 426 prostate cancer families from Johns Hopkins Hospital, University of Michigan, University of Ume (a) over circle, and University of Tampere. We found suggestive evidence for an epistatic interaction for six sets of loci (target chromosome-wide/reference marker-specific P <= 0.0001). Evidence for these interactions was found in two independent subsets from within the 426 families. While the validity of these results requires confirmation from independent studies and the identification of the specific genes underlying this linkage evidence, our approach of systematically assessing gene-gene interactions across the entire genome represents a promising alternative approach for gene identification for prostate cancer.
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