| Title: | Variable selection-combined causal mediation analysis for continuous treatments with application to large-dimensional biomedical data |
| Journal: | PLOS Computational Biology |
| Published: | 24 Jun 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42341064/ |
| DOI: | https://doi.org/10.1371/journal.pcbi.1014436 |
| URL: | https://www.ukbiobank.ac.uk/wp-content/uploads/2025/01/Ethics-approval-renewal-2021.pdf |
Publication 20543
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Abstract
Substantial progress has been made in the area of causal inference utilizing large-scale data, among which the estimation of causal mediation effects has attracted a lot of attention. However, existing large-dimensional causal inference primarily focuses on total effects or typical causal mediation effects under binary variable settings, placing less emphasis on large-scale covariate selection with continuous treatment and mediator. To address this, we propose a weighted semiparametric estimation framework that integrates the generalized outcome-adaptive LASSO method into generalized propensity score modeling to achieve estimation of causal mediation effects under continuous variable settings. Simulation results show that our proposed method outperforms other regularization-based methods in selection accuracy and estimation efficiency, which is achieved by incorporating outcome-related key variables and excluding noise covariates. From the perspective of achieving a stable balance between efficiency and bias, as well as high-dimensional information filtering, our method may serve as a compelling alternative that balances estimation efficiency with model interpretability and inferential robustness. We further conduct a real-world application based on the UK Biobank database, quantifying the causal mediation effects of apolipoprotein B levels within the association between potential diabetes risk and cancer incidence using large-scale healthcare and medical data.</p>
11 Keywords
- Algorithms
- Causality
- Computational Biology
- Computer Simulation
- Databases, Factual
- Diabetes Mellitus
- Humans
- Mediation Analysis
- Models, Statistical
- Neoplasms
- Propensity Score
7 Authors
- Yajing Zhou
- Kecheng Wei
- Yahang Liu
- Zhaoyang Li
- Chen Huang
- Guoyou Qin
- Yongfu Yu
1 Application
| Application ID | Title |
|---|---|
| 96511 | Investigating the genome-wide association and risk factors for multi-organ ageing |
Enabling scientific discoveries that improve human health