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dc.contributor.authorCiampa, Julia
dc.contributor.authorYeager, Meredith
dc.contributor.authorJacobs, Kevin
dc.contributor.authorThun, Michael J.
dc.contributor.authorGapstur, Susan
dc.contributor.authorAlbanes, Demetrius
dc.contributor.authorVirtamo, Jarmo
dc.contributor.authorWeinstein, Stephanie J.
dc.contributor.authorGiovannucci, Edward
dc.contributor.authorWillett, Walter C.::94559ea206eef8a8844fc5b80654fa5b::600
dc.contributor.authorCancel-Tassin, Geraldine
dc.contributor.authorCussenot, Olivier
dc.contributor.authorValeri, Antoine
dc.contributor.authorHunter, David
dc.contributor.authorHoover, Robert
dc.contributor.authorThomas, Gilles
dc.contributor.authorChanock, Stephen
dc.contributor.authorHolmes, Chris
dc.contributor.authorChatterjee, Nilanjan
dc.date.accessioned2019-09-23T15:35:26Z
dc.date.issued2011
dc.identifier.citationCiampa, Julia, Meredith Yeager, Kevin Jacobs, Michael J. Thun, Susan Gapstur, Demetrius Albanes, Jarmo Virtamo, et al. 2011. “Application of a Novel Score Test for Genetic Association Incorporating Gene-Gene Interaction Suggests Functionality for Prostate Cancer Susceptibility Regions.” Human Heredity 72 (3): 182–93. https://doi.org/10.1159/000331222.
dc.identifier.issn0001-5652
dc.identifier.issn1423-0062
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:41392189*
dc.description.abstractAims: We introduce an innovative multilocus test for disease association. It is an extension of an existing score test that gains power over alternative methods by incorporating a parsimonious one-degree-of-freedom model for interaction. We use our method in applications designed to detect interactions that generate hypotheses about the functionality of prostate cancer (PRCA) susceptibility regions. Methods: Our proposed score test is designed to gain additional power through the use of a retrospective likelihood that exploits an assumption of independence between unlinked loci in the underlying population. Its performance is validated through simulation. The method is used in conditional scans with data from stage II of the Cancer Genetic Markers of Susceptibility PRCA genome-wide association study. Results: Our proposed method increases power to detect susceptibility loci in diverse settings. It identified two high-ranking, biologically interesting interactions: (1) rs748120 of NR2C2 and subregions of 8q24 that contain independent susceptibility loci specific to PRCA and (2) rs4810671 of SULF2 and both JAZF1 and HNF1B that are associated with PRCA and type 2 diabetes. Conclusions: Our score test is a promising multilocus tool for genetic epidemiology. The results of our applications suggest functionality for poorly understood PRCA susceptibility regions. They motivate replication study.
dc.language.isoen_US
dc.publisherKarger Publishers
dash.licenseMETA_ONLY
dc.titleApplication of a Novel Score Test for Genetic Association Incorporating Gene-Gene Interaction Suggests Functionality for Prostate Cancer Susceptibility Regions
dc.typeJournal Article
dc.description.versionVersion of Record
dc.relation.journalHuman Heredity
dash.depositing.authorGiovannucci, Edward L.::fd8dcb59a5a5859f2a85fabae12a60cf::600
dc.date.available2019-09-23T15:35:26Z
dash.workflow.comments1Science Serial ID 40738
dc.identifier.doi10.1159/000331222
dash.source.volume72;3
dash.source.page182


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