Set‐based genetic association tests for panel count data based on weighted V statistics

Music City Center 

Almost all the existing multi-marker survival tests focus on time-to-event outcomes. However, panel count data are common in clinical and biomedical studies. Especially in the research of chronic and recurrence diseases, the exact event times of each subject are infeasible or very costly to measure. For example, in the study of early childhood caries, we can determine the increase in the number of teeth with carious lesions between two dental visits, but not the exact time when the lesions developed. In this work, we propose a new suite of set-based genetic association tests for panel count data. These tests can effectively account for genetic effect heterogeneity and adjust for covariates. In addition, we develop small-sample corrections to the tests to enhance the accuracy of the tests under small samples. The simulation study showed that the new tests perform well in terms of size and power under various scenarios and can outperform the existing tests for interval-censored outcomes in various scenarios. To show their practical application, a data set from a genetic study of early childhood caries (ECC) is analyzed with the developed tests to detect ECC-associated genes.

genetic heterogeneity

set‐based test

weighted V statistic

recurrent event 

Biometrics Section