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Gene–environment interaction analysis under the Cox model

Author

Listed:
  • Kuangnan Fang

    (Xiamen University)

  • Jingmao Li

    (Xiamen University)

  • Yaqing Xu

    (Shanghai Jiao Tong University School of Medicine)

  • Shuangge Ma

    (Yale School of Public Health)

  • Qingzhao Zhang

    (Xiamen University
    Xiamen University)

Abstract

For the survival of cancer and many other complex diseases, gene–environment (G-E) interactions have been established as having essential importance. G-E interaction analysis can be roughly classified as marginal and joint, depending on the number of G variables analyzed at a time. In this study, we focus on joint analysis, which can better reflect disease biology and is statistically more challenging. Many approaches have been developed for joint G-E interaction analysis for survival outcomes and led to important findings. However, without rigorous statistical development, quite a few methods have a weak theoretical ground. To fill this knowledge gap, in this article, we consider joint G-E interaction analysis under the Cox model. Sparse group penalization is adopted for regularizing estimation and selecting important main effects and interactions. The “main effects, interactions” variable selection hierarchy, which has been strongly advocated in recent literature, is satisfied. Significantly advancing from some published studies, we rigorously establish the consistency properties under high dimensionality. An effective computational algorithm is developed, simulation demonstrates competitive performance of the proposed approach, and analysis of The Cancer Genome Atlas (TCGA) data on stomach adenocarcinoma (STAD) further demonstrates its practical utility.

Suggested Citation

  • Kuangnan Fang & Jingmao Li & Yaqing Xu & Shuangge Ma & Qingzhao Zhang, 2023. "Gene–environment interaction analysis under the Cox model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(6), pages 931-948, December.
    • Handle: RePEc:spr:aistmt:v:75:y:2023:i:6:d:10.1007_s10463-023-00871-9
    DOI: 10.1007/s10463-023-00871-9
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    References listed on IDEAS

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