Bibliographic Details
| Title: |
High-Dimensional Mediation Analysis Based on Additive Hazards Model for Survival Data |
| Authors: |
Yidan Cui, Chengwen Luo, Linghao Luo, Zhangsheng Yu |
| Source: |
Frontiers in Genetics, Vol 12 (2021) |
| Publisher Information: |
Frontiers Media S.A., 2021. |
| Publication Year: |
2021 |
| Collection: |
LCC:Genetics |
| Subject Terms: |
high-dimensional mediators, additive hazards model, survival data, mediation analysis, SIS, Genetics, QH426-470 |
| More Details: |
Mediation analysis has been extensively used to identify potential pathways between exposure and outcome. However, the analytical methods of high-dimensional mediation analysis for survival data are still yet to be promoted, especially for non-Cox model approaches. We propose a procedure including “two-step” variable selection and indirect effect estimation for the additive hazards model with high-dimensional mediators. We first apply sure independence screening and smoothly clipped absolute deviation regularization to select mediators. Then we use the Sobel test and the BH method for indirect effect hypothesis testing. Simulation results demonstrate its good performance with a higher true-positive rate and accuracy, as well as a lower false-positive rate. We apply the proposed procedure to analyze DNA methylation markers mediating smoking and survival time of lung cancer patients in a TCGA (The Cancer Genome Atlas) cohort study. The real data application identifies four mediate CpGs, three of which are newly found. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1664-8021 |
| Relation: |
https://www.frontiersin.org/articles/10.3389/fgene.2021.771932/full; https://doaj.org/toc/1664-8021 |
| DOI: |
10.3389/fgene.2021.771932 |
| Access URL: |
https://doaj.org/article/a24b20e9416043b0b5d3d8d2327f744a |
| Accession Number: |
edsdoj.24b20e9416043b0b5d3d8d2327f744a |
| Database: |
Directory of Open Access Journals |
