Limitations in next-generation sequencing-based genotyping of breast cancer polygenic risk score loci.
Alexandra BaumannChristian RuckertChristoph MeierTim HutschenreiterRobert RemyBenedikt SchnurMarvin DöbelRudel Christian Nkouamedjo FankepDariush SkowronekOliver KutzNorbert ArnoldAnna-Lena KatzkeMichael ForsterAnna-Lena KobielaKatharina ThiedigAndreas David ZimmerJulia RitterBernhard Heinrich Friedrich WeberEllen HonischKarl Hackmannnull nullGunnar SchmidtMarc SturmCorinna ErnstPublished in: European journal of human genetics : EJHG (2024)
Considering polygenic risk scores (PRSs) in individual risk prediction is increasingly implemented in genetic testing for hereditary breast cancer (BC) based on next-generation sequencing (NGS). To calculate individual BC risks, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) with the inclusion of the BCAC 313 or the BRIDGES 306 BC PRS is commonly used. The PRS calculation depends on accurately reproducing the variant allele frequencies (AFs) and, consequently, the distribution of PRS values anticipated by the algorithm. Here, the 324 loci of the BCAC 313 and the BRIDGES 306 BC PRS were examined in population-specific database gnomAD and in real-world data sets of five centers of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), to determine whether these expected AFs can be reproduced by NGS-based genotyping. Four PRS loci were non-existent in gnomAD v3.1.2 non-Finnish Europeans, further 24 loci showed noticeably deviating AFs. In real-world data, between 11 and 23 loci were reported with noticeably deviating AFs, and were shown to have effects on final risk prediction. Deviations depended on the sequencing approach, variant caller and calling mode (forced versus unforced) employed. Therefore, this study demonstrates the necessity to apply quality assurance not only in terms of sequencing coverage but also observed AFs in a sufficiently large cohort, when implementing PRSs in a routine diagnostic setting. Furthermore, future PRS design should be guided by the technical reproducibility of expected AFs across commonly used genotyping methods, especially NGS, in addition to the observed effect sizes.
Keyphrases
- genome wide
- copy number
- genome wide association study
- dna methylation
- genome wide association
- machine learning
- high throughput
- electronic health record
- single cell
- deep learning
- big data
- risk factors
- risk assessment
- emergency department
- healthcare
- current status
- clinical practice
- quality improvement
- young adults
- high resolution
- human health
- circulating tumor
- neural network