title: Genetic variants improve breast cancer risk prediction on mammograms.
abstract: Several recent genome-wide association studies have identified genetic variants associated with breast cancer. However, how much these genetic variants may help advance breast cancer risk prediction based on other clinical features, like mammographic findings, is unknown. We conducted a retrospective case-control study, collecting mammographic findings and high-frequency/low-penetrance genetic variants from an existing personalized medicine data repository. A Bayesian network was developed using Tree Augmented Naive Bayes (TAN) by training on the mammographic findings, with and without the 22 genetic variants collected. We analyzed the predictive performance using the area under the ROC curve, and found that the genetic variants significantly improved breast cancer risk prediction on mammograms. We also identified the interaction effect between the genetic variants and collected mammographic findings in an attempt to link genotype to mammographic phenotype to better understand disease patterns, mechanisms, and/or natural history.
authors.affiliation: University of Wisconsin, Madison, WI, USA.
authors.forename: Jie
authors.initials: J
authors.lastname: Liu
authors.affiliation: University of Wisconsin, Madison, WI, USA.
authors.forename: David
authors.initials: D
authors.lastname: Page
authors.affiliation: University of Wisconsin, Madison, WI, USA.
authors.forename: Houssam
authors.initials: H
authors.lastname: Nassif
authors.affiliation: University of Wisconsin, Madison, WI, USA.
authors.forename: Jude
authors.initials: J
authors.lastname: Shavlik
authors.affiliation: Marshfield Clinic Research Foundation, Marshfield, WI, USA.
authors.forename: Peggy
authors.initials: P
authors.lastname: Peissig
authors.affiliation: Essentia Institute of Rural Health, Duluth, MN, USA.
authors.forename: Catherine
authors.initials: C
authors.lastname: McCarty
authors.affiliation: Department of Hematology/Oncology, Marshfield Clinic Weston Center, Weston, WI, USA ; Marshfield Clinic Research Foundation, Marshfield, WI, USA ; School of Population Health, University of Queensland, Brisbane, Australia.
authors.forename: Adedayo A
authors.initials: AA
authors.lastname: Onitilo
authors.affiliation: University of Wisconsin, Madison, WI, USA.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Burnside
mesh_terms: D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000000981:diagnostic imaging / Q000235:genetics*; D016022:Case-Control Studies; D005260:Female; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D008327:Mammography; D016571:Neural Networks, Computer; D020641:Polymorphism, Single Nucleotide; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods*