ArticlePLoS medicine2025
Polygenic risk scores for pan-cancer risk prediction in the Chinese population: A population-based cohort study based on the China Kadoorie Biobank.
Article in PLoS medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Genomic structural equation modelling of 12 cancers identifies a latent pan-cancer susceptibility factor and shared determinants of carcinogenesis.EBioMedicine · 2026Article
- Polygenic risk scores in cancer.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026Article
- Profiling the Onco-metabolic Nexus and Improving Cancer Risk Prediction Performance: A Large-scale Cohort and Genome-Wide Pleiotropic Analysis.Cancer research communications · 2026Article
- The Evolution of Gene Sequencing Technologies: Unveiling Genetic Architecture of Nonsyndromic Orofacial Clefts.Genetics research · 2026Review
- Dynamic screening initiation using 16 plasma protein biomarkers with polygenic risk and PLCOm2012: a precision prevention framework for lung cancer.Journal of translational medicine · 2025Article
- The Role of Genomic Scores in the Management of Prostate Cancer Patients: A Comprehensive Narrative Review.Cancers · 2025Review
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27 authors.
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Abstract
backgroundPolygenic risk scores (PRSs) have been extensively developed for cancer risk prediction in European populations, but their effectiveness in the Chinese population remains uncertain. METHODS AND
findingsWe constructed 80 PRSs for the 13 most common cancers using seven schemes and evaluated these PRSs in 100,219 participants from the China Kadoorie Biobank (CKB). The optimal PRSs with the highest discriminatory ability were used to define genetic risk, and their site-specific and cross-cancer associations were assessed. We modeled 10-year absolute risk trajectories for each cancer across risk strata defined by PRSs and modifiable risk scores and quantified the explained relative risk (ERR) of PRSs with modifiable risk factors for different cancers. More than 60% (50/80) of the PRSs demonstrated significant associations with the corresponding cancer outcomes. Optimal PRSs for nine common cancers were identified, with each standard deviation increase significantly associated with corresponding cancer risk (hazard ratios (HRs) ranging from 1.20 to 1.76). Compared with participants at low genetic risk and reduced modifiable risk scores, those with high genetic risk and elevated modifiable risk scores had the highest risk of incident cancer, with HRs ranging from 1.97 (95% confidence interval (CI): 1.11-3.48 for cervical cancer, P = 0.020) to 8.26 (95% CI: 1.92-35.46 for prostate cancer, P = 0.005). We observed nine significant cross-cancer associations for PRSs and found the integration of PRSs significantly increased the prediction accuracy for most cancers. The PRSs contributed 2.6%-20.3%, while modifiable risk factors explained 2.3%-16.7% of the ERR in the Chinese population.
conclusionsThe integration of existing evidence has facilitated the development of PRSs associated with nine common cancer risks in the Chinese population, potentially improving clinical risk assessment.
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