| Title: | Developing an optimal stratification model for colorectal cancer screening and reducing racial disparities in multi-center population-based studies |
| Journal: | Genome Medicine |
| Published: | 13 Jun 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38872215/ |
| DOI: | https://doi.org/10.1186/s13073-024-01355-y |
| URL: | https://genomemedicine.biomedcentral.com/counter/pdf/10.1186/s13073-024-01355-y |
Publication 11862
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Abstract
BackgroundEarly detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages of the dynamic adenoma-carcinoma sequence in EAS population.MethodsTo develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS148); (2) SNPs selection from large-scale meta-analysis data by clumping and thresholding (PRS183); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRSGenomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with non-advanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants.ResultsThree trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS183 demonstrated the optimal discriminatory ability in both EAS and EUR validation datasets, particularly for individuals at risk of colorectal neoplasms. Using two large-scale and independent prospective cohorts, we further confirmed a significant dose-response effect of PRS183 on incident colorectal neoplasms. Incorporating PRS183 with lifestyle factors into a comprehensive strategy improves risk stratification and discriminatory accuracy compared to using PRS or lifestyle factors separately. This comprehensive risk-stratified model shows potential in addressing missed diagnoses in screening tests (best NPV = 0.93), while moderately reducing unnecessary screening (best PPV = 0.32).ConclusionsOur comprehensive risk-stratified model in population-based CRC screening trials represents a promising advancement in personalized risk assessment, facilitating tailored CRC screening in the EAS population. This approach enhances the transferability of PRSs across ancestries and thereby helps address health disparity.Graphical Abstract</p>
22 Authors
- Jianbo Tian
- Ming Zhang
- Fuwei Zhang
- Kai Gao
- Zequn Lu
- Yimin Cai
- Can Chen
- Caibo Ning
- Yanmin Li
- Sangni Qian
- Hao Bai
- Yizhuo Liu
- Heng Zhang
- Shuoni Chen
- Xiangpan Li
- Yongchang Wei
- Bin Li
- Ying Zhu
- Jinhua Yang
- Mingjuan Jin
- Xiaoping Miao
- Kun Chen
Enabling scientific discoveries that improve human health