| Title: | Impact of accelerated biological aging and genetic variation on esophageal adenocarcinoma: Joint and interaction effect in a prospective cohort |
| Journal: | International Journal of Cancer |
| Published: | 4 Sep 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39233364/ |
| DOI: | https://doi.org/10.1002/ijc.35161 |
Publication 13025
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Abstract
Accelerated biological aging may be associated with increased risk of esophageal adenocarcinoma (EAC). However, its relationship with genetic variation, and its effect on improving risk population stratification, remains unknown. We performed an exposome association study to determine potential associated factors associated with EAC. To quantify biological age and its difference from chronological age, we calculated the BioAge10 and Biological Age Acceleration (BioAgeAccel) based on chronological age and nine biomarkers. Multivariable Cox regression models for 362,310 participants from the UK Biobank with a median follow-up of 13.70 years were performed. We established a weighted polygenic risk score (wPRS) associated with EAC, to assess joint and interaction effects with BioAgeAccel. Four indicators were used to evaluate their interaction effects, and we fitted curves to evaluate the risk stratification ability of BioAgeAccel. Compared with biologically younger participants, those older had higher risk of EAC, with adjusted HR of 1.79 (95%CI: 1.52-2.10). Compared with low wPRS and biologically younger group, the high wPRS and biologically older group had a 4.30-fold increase in HR (95% CI: 2.78-6.66), at meanwhile, 1.15-fold relative excess risk was detected (95% CI: 0.30-2.75), and 22% of the overall EAC risk was attributable to the interactive effects (95% CI: 12%-31%). The 10-year absolute incidence risk indicates that biologically older individuals should begin screening procedures 4.18 years in advance, while youngers can postpone screening by 4.96 years, compared with general population. BioAgeAccel interacted positively with genetic variation and increased risk of EAC, it could serve as a novel indicator for predicting incidence.</p>
9 Authors
- Renjia Zhao
- Huangbo Yuan
- Shuaizhou Chen
- Kelin Xu
- Tiejun Zhang
- Zhenqiu Liu
- Yanfeng Jiang
- Chen Suo
- Xingdong Chen
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