Polygenic risk scores for cervical HPV infection, neoplasia and cancer show potential for personalised screening: comparison of two methods

Abstract

The era of precision medicine requires the achievement of accurate risk assessment. Polygenic risk scores (PRSs) have strong potential for increasing the benefits of nationwide cancer screening programs. The current pool of evidence on the role of a PRS as a risk stratification model in actual practice and implementation is limited. To better understand the impact of possible method-induced variance, we constructed and validated two PRSs for cervical cancer (CC) using the Estonian Biobank female population (691 CC cases and 13,820 controls) and evaluated their utility in predicting incident cervical neoplasia (CIN), cancer, and human papillomavirus (HPV) infection using two methods (LDPred and BayesRR-RC). This study demonstrated that two genetic risk scores were significantly associated with CIN, CC, and HPV infection incidence. Independent of the method, we demonstrated that women with elevated PRS values reached the observed cumulative risk levels of CIN or CC much earlier. Our results indicated that the PRS-based discrimination rules could differ substantially when the PRSs contain similar predictive information. In summary, our analysis indicated that PRSs represent a personalized genetic component that could be an additional tool for cervical cancer risk stratification, and earlier detection of abnormalities provides invaluable information for those at high risk.

Keywords: Cervical cancer; Cervical intraepithelial neoplasia; HPV; Polygenic risk score; Screening.

Fig. 1

Flowchart of the study design and analysed groups

Fig. 2

Cumulative incidence of cervical cancer (accounting for competing risks) in a LDpred and b BayesRR-RC risk categories among women aged 30–75 years

Fig. 3

Cumulative incidence of cervical intraepithelial neoplasia (accounting for competing risks) in a LDpred and b BayesRR-RC risk categories among women aged 20–75 years

Fig. 4

The overlap among highest-risk women (top 5%) in the Estonian Biobank according to two genetic risk scores for cervical cancer. The graph shows women who were classified as being in the top 5% with at least one of the genetic risk scores (LDpred and BayesRR-RC)