Predictive Value of Genetic Risk Scores in the Development of Colorectal Adenomas

• Published in: Digestive diseases and sciences Vol. 67; no. 8; pp. 4049 - 4058
• Main Authors: Gargallo-Puyuelo, Carla J., Aznar-Gimeno, Rocío, Carrera-Lasfuentes, Patricia, Lanas, Ángel, Ferrández, Ángel, Quintero, Enrique, Carrillo, Marta, Alonso-Abreu, Inmaculada, Esteban, Luis M., de la Vega Rodrigálvarez-Chamarro, María, del Hoyo-Alonso, Rafael, García-González, María Asunción
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-08-2022; Springer Nature B.V
• Subjects: Age; Biochemistry; Colonoscopy; Colorectal cancer; Family medical history; Gastroenterology; Health risk assessment; Hepatology; Hospitals; Medicine; Medicine & Public Health; Nonsteroidal anti-inflammatory drugs; Oncology; Original Article; Transplant Surgery; Tumors; White people; Genetic risk scores; Predictive value; Colorectal adenomas; Colorectal screening; Single-nucleotide polymorphism
• ISSN: 0163-2116; 1573-2568
• DOI: 10.1007/s10620-021-07218-5

Introduction
Unlike colorectal cancer (CRC), few studies have explored the predictive value of genetic risk scores (GRS) in the development of colorectal adenomas (CRA), either alone or in combination with other demographic and clinical factors.
Methods
In this study, genomic DNA from 613 Spanish Caucasian patients with CRA and 829 polyp-free individuals was genotyped for 88 single-nucleotide polymorphisms (SNPs) associated with CRC risk using the MassArray™ (Sequenom) platform. After applying a multivariate logistic regression model, five SNPs were selected to calculate the GRS. Regression models adjusted by sex, age, family history of CRC, chronic use of NSAIDs, low-dose ASA, and consumption of tobacco were built in order to study the association between GRS and CRA risk. We evaluated the discriminatory capacity using the area under the receiver operating characteristic curve (AUC). The interactions between demographic information and GRS were also analyzed.
Results
Significant associations between high GRS values and risk of CRA for analyzed models were observed. In particular, patients with higher GRS values had 2.3–2.6-fold increase in risk of CRA compared to patients with middle values. Combining sex and age with the GRS significantly increased the discriminatory accuracy of the univariate model with GRS alone. The best model achieved an AUC value of 0.665 (95% CI: 0.63–0.69). The GRS showed a different behavior depending on sex and age.
Conclusion
Our findings showed that, besides sex and age, GRS is an important risk factor for development of CRA and may be useful for CRC risk stratification and adaptation of screening programs.