Polygenic risk modeling for prediction of epithelial ovarian cancer risk
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00209805%3A_____%2F22%3A00078949" target="_blank" >RIV/00209805:_____/22:00078949 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11110/22:10437378
Result on the web
<a href="https://www.nature.com/articles/s41431-021-00987-7" target="_blank" >https://www.nature.com/articles/s41431-021-00987-7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41431-021-00987-7" target="_blank" >10.1038/s41431-021-00987-7</a>
Alternative languages
Result language
angličtina
Original language name
Polygenic risk modeling for prediction of epithelial ovarian cancer risk
Original language description
Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30204 - Oncology
Result continuities
Project
<a href="/en/project/LO1413" target="_blank" >LO1413: RECAMO2020</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
European journal of human genetics
ISSN
1018-4813
e-ISSN
1476-5438
Volume of the periodical
30
Issue of the periodical within the volume
3
Country of publishing house
AT - AUSTRIA
Number of pages
14
Pages from-to
349-362
UT code for WoS article
000742272300002
EID of the result in the Scopus database
2-s2.0-85126235376