| Title: | Associations between blood glucose and early- and late-onset colorectal cancer: Evidence from two prospective cohorts and Mendelian randomization analyses |
| Journal: | Journal of the National Cancer Center |
| Published: | 1 Jun 2024 |
| DOI: | https://doi.org/10.1016/j.jncc.2024.04.006 |
Publication 11937
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Abstract
Background The incidence of early-onset colorectal cancer (EOCRC), which exhibits differential clinical, pathological, and molecular features compared to late-onset CRC (LOCRC), is rising globally. The potential differential effects of blood glucose on EOCRC compared to LOCRC have not been investigated. Methods This study analyzed 374,568 participants from UK Biobank cohort and 172,809 participants from Kailuan cohort. The linear associations between blood glucose and EOCRC/LOCRC were estimated using Cox regression models. Restricted cubic spline (RCS) analysis and non-linear Mendelian randomization (MR) analysis using a 70-SNPs genetic instrument for fasting glucose were used to explore the potential non-linear associations. Results Participants in the highest quintile of blood glucose had higher overall CRC risk compared to the lowest quintile (HR = 1.10 in the UK Biobank cohort, 95% CI: 1.01-1.21, P-trend = 0.012; HR = 1.23 in the Kailuan cohort, 95% CI: 1.01-1.51, P-trend = 0.036). Elevated glucose (>7.0 mmol/L) was more strongly associated with increased risk of EOCRC (HR = 1.61, 95% CI: 1.07-2.44) than with LOCRC (HR = 1.14, 95% CI: 1.02-1.27) in the UK Biobank cohort (P-heterogeneity = 0.014). Elevated glucose (>7.0 mmol/L) was associated with increased risk of LOCRC (HR = 1.25, 95% CI: 1.04-1.65) in the Kailuan cohort as well. There was no evidence for non-linear associations between blood glucose and risks of EOCRC/LOCRC. Conclusions This study showed a positive association between blood glucose and CRC risk in a dose-response manner, particularly for EOCRC, suggesting that tighter glucose control should be a priority for younger age groups.</p>
11 Authors
- Chenyu Luo
- Jiahui Luo
- Yuhan Zhang
- Bin Lu
- Na Li
- Yueyang Zhou
- Shuohua Chen
- Shouling Wu
- Qingsong Zhang
- Min Dai
- Hongda Chen
1 Application
| Application ID | Title |
|---|---|
| 90170 | Risk prediction models incorporating genetic, environmental and lifestyle factors for common and rare malignancies |
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