Investigating the causal effect of potential therapeutic agents for colorectal cancer prevention: a Mendelian randomization analysis.
Abstract
Conventional observational studies have identified several potential therapeutic agents that may lower risk of colorectal cancer development. However, these studies are susceptible to unmeasured and residual confounding and reverse causation, undermining robust causal inference.
We used Mendelian randomization (MR), a genetic epidemiological method that can strengthen causal inference, to evaluate the effect of previously reported therapeutic agents on colorectal cancer risk, including medications, dietary micronutrients, and exogenous hormones. Genetic instruments were constructed using genome-wide association studies (GWASs) of molecular traits (e.g. circulating levels of protein drug targets, blood-based biomarkers of micronutrients, circulating levels of endogenous hormones). Using summary statistics from these GWASs and a colorectal cancer risk GWAS (cases=78,473, controls=107,143), we employed Wald ratios and inverse-variance weighted models to estimate causal effects.
We found evidence for associations of genetically-proxied elevated omega-3 fatty acids (OR 1.10; 95% CI 1.03, 1.18; p=6.20x10-3) and reduced plasma ACE levels (OR 1.08; 95% CI 1.03, 1.13; p=9.36x10-4) with colorectal cancer risk. Findings for ACE inhibition were consistent across sensitivity analyses.
Reduced plasma ACE levels were robustly linked to increased colorectal cancer risk. Further work is required to better understand the mechanism behind this finding and whether this translates to adverse effects via medication use (i.e. ACE inhibitors).
These findings provide updated evidence on the role of previously reported therapeutic agents in colorectal cancer risk, helping to prioritise further evaluation of those agents with potential aetiological roles in cancer development.
EDRN PI Authors
- (None specified)
Medline Author List
- Bishop DT
- Campbell PT
- Chan AT
- Fryer E
- Grant RC
- Gunter MJ
- Haycock P
- Le Marchand L
- Li CI
- Martin RM
- Moreno V
- Phipps AI
- Schmit SL
- Yarmolinsky J