title: Leveraging Interaction between Genetic Variants and Mammographic Findings for Personalized Breast Cancer Diagnosis.
abstract: Recent large-scale genome-wide association studies (GWAS) have identified a number of genetic variants associated with breast cancer which showed great potential for clinical translation, especially in breast cancer diagnosis via mammograms. However, the amount of interaction between these genetic variants and mammographic features that can be leveraged for personalized diagnosis remains unknown. Our study utilizes germline genetic variants and mammographic features that we collected in a breast cancer case-control study. By computing the conditional mutual information between the genetic variants and mammographic features given the breast cancer status, we identified six interaction pairs which elevate breast cancer risk and five interaction pairs which reduce breast cancer risk.
authors: University of Wisconsin, Madison, WI, US.
authors: Jie
authors: J
authors: Liu
authors: University of Wisconsin, Madison, WI, US.
authors: Yirong
authors: Y
authors: Wu
authors: University of Wisconsin, Madison, WI, US.
authors: Irene
authors: I
authors: Ong
authors: University of Wisconsin, Madison, WI, US.
authors: David
authors: D
authors: Page
authors: Marshfield Clinic Research Foundation, Marshfield, WI, US.
authors: Peggy
authors: P
authors: Peissig
authors: Essentia Institute of Rural Health, Duluth, MN, US.
authors: Catherine
authors: C
authors: McCarty
authors: Marshfield Clinic Research Foundation, Marshfield, WI, US ; Department of Hematology/Oncology, Marshfield Clinic Weston Center, Weston, WI, US.
authors: Adedayo A
authors: AA
authors: Onitilo
authors: University of Wisconsin, Madison, WI, US.
authors: Elizabeth
authors: E
authors: Burnside