Gene-level pharmacogenetic analysis on survival outcomes using gene-trait similarity regression

Jung Ying Tzeng, Wenbin Lu, Fang Chi Hsu

研究成果: Article同行評審

8 引文 斯高帕斯(Scopus)

摘要

Gene/pathway-based methods are drawing significant attention due to their usefulness in detecting rare and common variants that affect disease susceptibility. The biological mechanism of drug responses indicates that a genebased analysis has even greater potential in pharmacogenetics. Motivated by a study from the Vitamin Intervention for Stroke Prevention (VISP) trial, we develop a gene-trait similarity regression for survival analysis to assess the effect of a gene or pathway on time-to-event outcomes. The similarity regression has a general framework that covers a range of survival models, such as the proportional hazards model and the proportional odds model. The inference procedure developed under the proportional hazards model is robust against model misspecification. We derive the equivalence between the similarity survival regression and a random effects model, which further unifies the current variance component-based methods. We demonstrate the effectiveness of the proposed method through simulation studies. In addition, we apply the method to the VISP trial data to identify the genes that exhibit an association with the risk of a recurrent stroke. The TCN2 gene was found to be associated with the recurrent stroke risk in the low-dose arm. This gene may impact recurrent stroke risk in response to cofactor therapy.

原文English
頁(從 - 到)1232-1255
頁數24
期刊Annals of Applied Statistics
8
發行號2
DOIs
出版狀態Published - 2014 6月

All Science Journal Classification (ASJC) codes

  • 統計與概率
  • 建模與模擬
  • 統計、概率和不確定性

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