Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes
View Publication
Export 
BiBTeXStratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
DOI: 10.1016/j.ajhg.2018.11.002
Projects: GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer
Publication type: Journal article
Journal: American journal of human genetics
Human Diseases: Hereditary breast ovarian cancer syndrome
Citation: The American Journal of Human Genetics 104(1):21-34
Date Published: 2019
Registered Mode: imported from a bibtex file
Export PNG
Download
Submitter
Views: 1664
Created: 15th Jul 2020 at 13:29
Last updated: 7th Dec 2021 at 17:58
TagsThis item has not yet been tagged.
AttributionsNone
Related items
The German Consortium for Hereditary Breast and Ovarian Cancer HBOC has been founded in 1996 by the German Cancer Aid and has been funded by the German Cancer Aid until recently. GC-HBOC currently comprises 17 university centers providing genetic counseling, histopathological and molecular tissue analysis, genetic testing, and specific structured surveillance programs for early cancer detection at each clinical unit, all based on defined standard operating procedures.
Programme: LIFE Management Cluster
Public web page: http://www.konsortium-familiaerer-brustkrebs.de/
Start date: 1st Jan 1996
Projects: LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer
Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)
https://orcid.org/0000-0002-7247-282X
Projects: LHA - Leipzig Health Atlas, LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE HNC - Head and Neck Cancer Group, LIFE Heart, MMML - Molecular mechanisms in malignant lymphoma, GLA - German Lymphoma Alliance, MMML Demonstrators - Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine, HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles, e:Med, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer, MMML-MYC-SYS, NLP4CR - Natural Language Processing for Clinical Research, Genetical Statistics and Systems Biology, SepNet - German Competence Network Sepsis, LIFE Child, HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome, GGN - German Glioma Network, CAPSys - Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome, CapSys - Systems Medicine of Community Acquired Pneumonia, ProstataCA, HaematoSys - Systems biology of haematopoiesis and haematopoietic neoplasia, SMITH - Smart Medical Information Technology for Healthcare, Task Force COVID-19 Leipzig, NFDI4Health, POLAR - Polypharmacy, Drug Interactions, Risks, Management of health information systems, LivSys Transfer - Transfer of the LivSys in vitro system for hepatotoxicity into application, Project Test Demonstrator, Fundus photography as tool for analysis of eyes of subjects with diabetes, Clinical Trials Leipzig, NFDI4Health - TA3 Services, STOP-NUC, SCALE-TORT
Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)
https://orcid.org/0000-0001-8344-0658
Rui Zhang, M.Sc. Stephanstraße 1A 04103 Leipzig Germany
Projects: LIFE Heart, LIFE - Leipzig Research Center for Civilization Diseases, LIFE HNC - Head and Neck Cancer Group, SepNet - German Competence Network Sepsis, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer, LIFE Child, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, LIFE Adult
Web page: https://www.uniklinikum-leipzig.de/einrichtungen/life
Taxonomy URI: http://purl.obolibrary.org/obo/DOID_5683
Synonyms: BRCA1- and BRCA2-associated hereditary breast and ovarian cancer (HBOC)
Definitions: Xref MGI., An autosomal dominant disease characterized by the higher than normal tendency associated with BRCA1 and BRCA2 to develop breast and ovarian cancers in genetically related families.
