Integrating genome-wide polygenic risk scores and non-genetic risk factors to develop and validate risk prediction models for colorectal cancer

ObjectiveWhile population screening programs for cancer colorectal (CRC) have proven benefit, risk-stratified approaches may improve screening outcomes further. To date, genome-wide polygenic risk scores (PRS) for CRC have not been integrated with non-genetic risk factors. We aimed to evaluate several genome-wide approaches, and the benefit of adding PRS to the QCancer-10 (colorectal cancer) non-genetic risk model, to identify those at highest risk of CRC. DesignUsing UK Biobank we developed and compared six different PRS for CRC. The top-performing genome-wide and GWAS-significant PRS were then combined with QCancer-10 and performance compared to QCancer-10 alone. ResultsPRS derived using LDpred2 software performed best, with an odds-ratio per standard deviation of 1.58, and top age- and sex-adjusted C-statistic of 0.733 in logistic regression and 0.724 in Cox regression models in the Geographic Validation Cohort. Integrated QCancer-10+PRS models out-performed QCancer-10, with C-statistics of 0.730 and 0.693, and explained variation of 28.1% and 21.0% from QCancer-10+LDpred2 and QCancer-10 respectively in men; performance improvements in women were similar. Men in the top 20% of risk accounted for 47.6% of cases, and women 42.5% using QCancer-10+LDpred2 models, with a 3.49-fold increase in risk in men and 2.75-fold increase in women in the top 5% of risk, compared to average risk. Decision curve analysis showed that adding PRS to QCancer-10 improved net-benefit and interventions avoided across most probability thresholds. ConclusionIntegrated QCancer-10+PRS models out-perform existing CRC risk prediction models. Evaluation of risk stratified screening using this approach in a bowel screening population could be warranted. SUMMARY BOXO_ST_ABSWhat is already known about this subjectC_ST_ABSO_LIRisk stratification based on genetic or environmental risk factors may improve cancer screening outcomes C_LIO_LIMany polygenic risk scores (PRS) based on a limited number of genome-wide significant SNPs have been assessed in colorectal cancer (CRC), but just two studies have examined the use of genome-wide PRS methodologies C_LIO_LINo previously published study has examined integrated models combining genome-wide PRS and non-genetic risk factors beyond age C_LIO_LIQCancer-10 (colorectal cancer) is the top-performing non-genetic risk prediction model for CRC C_LI What are the new findings?O_LIPRS derived using LDpred2 software outperform existing models, and other genome-wide and genome-wide significant models evaluated here C_LIO_LIAdding either LDpred2 PRS or genome-wide significant PRS improves the performance and clinical benefit of the QCancer-10 model, with greater gain from the LDpred2 model C_LI How might it impact on clinical practice in the foreseeable future?O_LIThe performance and clinical benefit of QCancer-10 is improved by adding PRS, to a level that suggests utility in stratifying CRC screening and prevention C_LI