Yun-Hee Choi
Accurate estimates of disease risk (penetrance) associated with inherited gene mutations are critical for the clinical management of individuals at risk, but this estimation raises many statistical challenges especially when performed in a family-based design. In this paper, we propose a general frailty model-based approach to accommodate this design, where the frailty random effect accounts for shared risk among family members not due to the observed risk factors. It is of major interest when the goal is to discover other genetic variations besides the major gene and to get accurate estimates of penetrance (i.e. unbiased by unknown confounding factors). This approach is further extended to accommodate missing genotypes in family members and the non-random ascertainment of the families. Simulation results show that the proposed method performs well in realistic settings. Finally, a family-based breast cancer study of the BRCA1 and BRCA2 genes is used to illustrate the method.
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Journal of Biometrics & Biostatistics received 3496 citations as per Google Scholar report
