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Population‐specific validation and comparison of the performance of 77‐ and 313‐variant polygenic risk scores for breast cancer risk prediction

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3Pays d’affiliation déclarés

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Abstract Background The polygenic risk score (PRS) allows the quantification of the polygenic effect of many low‐penetrance alleles on the risk of breast cancer (BC). This study aimed to evaluate the performance of two sets comprising 77 or 313 low‐penetrance loci (PRS77 and PRS313) in patients with BC in the Czech population. Methods In a retrospective case‐control study, variants were genotyped from both the PRS77 and PRS313 sets in 1329 patients with BC and 1324 noncancer controls, all women without germline pathogenic variants in BC predisposition genes. Odds ratios (ORs) were calculated according to the categorical PRS in individual deciles. Weighted Cox regression analysis was used to estimate the hazard ratio (HR) per standard deviation (SD) increase in PRS. Results The distributions of standardized PRSs in patients and controls were significantly different (p < 2.2 × 10−16) with both sets. PRS313 outperformed PRS77 in categorical and continuous PRS analyses. For patients in the highest 2.5% of PRS313, the risk reached an OR of 3.05 (95% CI, 1.66–5.89; p = 1.76 × 10−4). The continuous risk was estimated as an HRper SD of 1.64 (95% CI, 1.49–1.81; p < 2.0 × 10−16), which resulted in an absolute risk of 21.03% at age 80 years for individuals in the 95th percentile of PRS313. Discordant categorization into PRS deciles was observed in 248 individuals (9.3%). Conclusions Both PRS77 and PRS313 are able to stratify individuals according to their BC risk in the Czech population. PRS313 shows better discriminatory ability. The results support the potential clinical utility of using PRS313 in individualized BC risk prediction.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Population‐specific validation and comparison of the performance of 77‐ and 313‐variant polygenic risk scores for breast cancer risk prediction
Date Crossref
08/05/2024
Éditeur
Wiley
Type
journal-article

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Institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Sujets associés

BRCA gene mutations in cancerGenetic Associations and EpidemiologyBreast Cancer Treatment Studies

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