| Title: | Exposome approach for identifying modifiable factors for the prevention of colorectal cancer |
| Journal: | Scientific Reports |
| Published: | 14 Dec 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36517625/ |
| DOI: | https://doi.org/10.1038/s41598-022-25832-9 |
| URL: | https://www.nature.com/articles/s41598-022-25832-9.pdf |
Publication 10815
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Abstract
Previous studies have shown certain exposure factors (such as lifestyle and metabolism) are associated with colorectal cancer (CRC) events. However, the application of the exposome theoretical frame and the extent to which the exposome domain can modulate the risk of CRC remain unknown. Our study aimed to construct valid exposome measurements and examine the relationship between exposome counts and the risk of CRC. This study included 335,370 individuals in the UK Biobank. We used exploratory factor analysis to identify a valid construct of exposome factors. We then summed the exposome counts within each domain. Cox proportional hazard models were used to estimate the hazard ratios and 95% confidence intervals of CRC risk related to the exposome factors and counts. During an 8.69 year median follow-up, 10,702 CRC cases were identified. Five domains were extracted from 12 variables, including ecosystem, lifestyle, tobacco and alcohol use, social economics, and social support. The Cox model results showed that the ecosystem was positively related to the reduced CRC risk (HR = 0.970; 95% CI 0.952-0.989). Similar results were also found among the domains of healthy lifestyles (HR = 0. 889; 95% CI 0.871-0.907), and no tobacco and alcohol use (HR = 0.892; 95% CI 0.876-0.909). The disadvantageous social economic (HR = 1.081; 95% CI 1.058-1.105) and insufficient social support domains (HR = 1.036; 95% CI 1.017-1.056) were associated with an increased risk of CRC. Similar risk trends were also observed across the exposome count groups with CRC incidence. Our findings suggest that certain exposure domains are related to the incidence of CRC. Ecosystem, lifestyle, and social factors can be incorporated into prediction models to identify individuals at high risk of CRC.</p>
4 Authors
- Nanqian Chen
- Hailun Liang
- Tao Huang
- Ninghao Huang
1 Application
| Application ID | Title |
|---|---|
| 44430 | Genetic risk, environmental factors and chronic diseases and ageing outcomes |
Enabling scientific discoveries that improve human health