Gastric Cancer Risk Prediction Using an Epidemiological Risk Assessment Model and Polygenic Risk Score

• Published in: Cancers 2021-02, Vol.13 (4), p.876
• Main Authors: Park, Boyoung, Yang, Sarah, Lee, Jeonghee, Choi, Il Ju, Kim, Young-Il, Kim, Jeongseon
• Format: Article
• Language: English
• Subjects: Epidemiology; Family medical history; Gastric cancer; Genome-wide association studies; Genomes; Helicobacter pylori; Infections; Mortality; Population; Population studies; Risk assessment; Risk factors; Risk groups; Single-nucleotide polymorphism
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers13040876

We investigated the performance of a gastric cancer (GC) risk assessment model in combination with single-nucleotide polymorphisms (SNPs) as a polygenic risk score (PRS) in consideration of ( infection status. Six SNPs identified from genome-wide association studies and a marginal association with GC in the study population were included in the PRS. Discrimination of the GC risk assessment model, PRS, and the combination of the two (PRS-GCS) were examined regarding incremental risk and the area under the receiver operating characteristic curve (AUC), with grouping according to infection status. The GC risk assessment model score showed an association with GC, irrespective of infection. Conversely, the PRS exhibited an association only for those with infection. The PRS did not discriminate GC in those without infection, whereas the GC risk assessment model showed a modest discrimination. Among individuals with infection, discrimination by the GC risk assessment model and the PRS were comparable, with the PRS-GCS combination resulting in an increase in the AUC of 3%. In addition, the PRS-GCS classified more patients and fewer controls at the highest score quintile in those with infection. Overall, the PRS-GCS improved the identification of a GC-susceptible population of people with infection. In those without infection, the GC risk assessment model was better at identifying the high-risk group.