UNLABELLED: Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. SIGNIFICANCE: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.
- MeSH
- celogenomová asociační studie MeSH
- genetická predispozice k nemoci MeSH
- genetické lokusy MeSH
- index tělesné hmotnosti MeSH
- jednonukleotidový polymorfismus MeSH
- kolorektální nádory * genetika MeSH
- lidé MeSH
- mezibuněčné signální peptidy a proteiny genetika MeSH
- obezita * komplikace genetika MeSH
- rizikové faktory MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
BACKGROUND: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. METHODS: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). RESULTS: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value3-d.f.: 5.46 × 10-11) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value2-d.f.: 7.84 × 10-09). DISCUSSION: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.
- MeSH
- celogenomová asociační studie metody MeSH
- diabetes mellitus * genetika MeSH
- genetická predispozice k nemoci MeSH
- interakce genů a prostředí MeSH
- jednonukleotidový polymorfismus MeSH
- kolorektální nádory * genetika MeSH
- lidé MeSH
- mikrofilamentové proteiny genetika MeSH
- rizikové faktory MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, P.H.S. MeSH
BACKGROUND: Polygenic risk scores (PRS) which summarize individuals' genetic risk profile may enhance targeted colorectal cancer screening. A critical step towards clinical implementation is rigorous external validations in large community-based cohorts. This study externally validated a PRS-enhanced colorectal cancer risk model comprising 140 known colorectal cancer loci to provide a comprehensive assessment on prediction performance. METHODS: The model was developed using 20,338 individuals and externally validated in a community-based cohort (n = 85,221). We validated predicted 5-year absolute colorectal cancer risk, including calibration using expected-to-observed case ratios (E/O) and calibration plots, and discriminatory accuracy using time-dependent AUC. The PRS-related improvement in AUC, sensitivity and specificity were assessed in individuals of age 45 to 74 years (screening-eligible age group) and 40 to 49 years with no endoscopy history (younger-age group). RESULTS: In European-ancestral individuals, the predicted 5-year risk calibrated well [E/O = 1.01; 95% confidence interval (CI), 0.91-1.13] and had high discriminatory accuracy (AUC = 0.73; 95% CI, 0.71-0.76). Adding the PRS to a model with age, sex, family and endoscopy history improved the 5-year AUC by 0.06 (P < 0.001) and 0.14 (P = 0.05) in the screening-eligible age and younger-age groups, respectively. Using a risk-threshold of 5-year SEER colorectal cancer incidence rate at age 50 years, adding the PRS had a similar sensitivity but improved the specificity by 11% (P < 0.001) in the screening-eligible age group. In the younger-age group it improved the sensitivity by 27% (P = 0.04) with similar specificity. CONCLUSIONS: The proposed PRS-enhanced model provides a well-calibrated 5-year colorectal cancer risk prediction and improves discriminatory accuracy in the external cohort. IMPACT: The proposed model has potential utility in risk-stratified colorectal cancer prevention.
