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Gene-based analysis of bi-variate survival traits via functional regressions with applications to eye diseases.

Authors:
Bingsong Zhang Chi-Yang Chiu Fang Yuan Tian Sang Richard J Cook Alexander F Wilson Joan E Bailey-Wilson Emily Y Chew Momiao Xiong Ruzong Fan

Genet Epidemiol 2021 Mar 1. Epub 2021 Mar 1.

Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, District of Columbia, USA.

Genetic studies of two related survival outcomes of a pleiotropic gene are commonly encountered but statistical models to analyze them are rarely developed. To analyze sequencing data, we propose mixed effect Cox proportional hazard models by functional regressions to perform gene-based joint association analysis of two survival traits motivated by our ongoing real studies. These models extend fixed effect Cox models of univariate survival traits by incorporating variations and correlation of multivariate survival traits into the models. The associations between genetic variants and two survival traits are tested by likelihood ratio test statistics. Extensive simulation studies suggest that type I error rates are well controlled and power performances are stable. The proposed models are applied to analyze bivariate survival traits of left and right eyes in the age-related macular degeneration progression.

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http://dx.doi.org/10.1002/gepi.22381DOI Listing
March 2021

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