Polygenic Risk Score Predicts Modified Risk in BRCA1 Pathogenic Variant c.4035del and c.5266dup Carriers in Breast Cancer Patients

Simple item page
dc.contributor.authorBerga-Švītiņa, Egija
dc.contributor.authorMaksimenko, Jeļena
dc.contributor.authorMiklaševičs, Edvīns
dc.contributor.authorFischer, Krista
dc.contributor.authorVilne, Baiba
dc.contributor.authorMägi, Reedik
dc.contributor.institutionBioinformatics Group
dc.contributor.institutionOnkoloģijas institūts
dc.contributor.institutionDepartment of Biology and Microbiology
dc.date.accessioned2023-10-30T12:50:01Z
dc.date.available2023-10-30T12:50:01Z
dc.date.issued2023-01
dc.descriptionFunding Information: This research has been developed with financing from the European Social Fund and Latvian state budget within the project no. 8.2.2.0/20/I/004 “Support for involving doctoral students in scientific research and studies” at Rīga Stradiņš University. Publisher Copyright: © 2023 by the authors.
dc.description.abstractThe aim of this study was to assess the power of the polygenic risk score (PRS) in estimating the overall genetic risk of women carrying germline BRCA1 pathogenic variants (PVs) c.4035del or c.5266dup to develop breast (BC) or ovarian cancer (OC) due to additional genetic variations. In this study, PRSs previously developed from two joint models using summary statistics of age-at-onset (BayesW model) and case–control data (BayesRR-RC model) from a genome-wide association analysis (GWAS) were applied to 406 germline BRCA1 PV (c.4035del or c.5266dup) carriers affected by BC or OC, compared with unaffected individuals. A binomial logistic regression model was used to assess the association of PRS with BC or OC development risk. We observed that the best-fitting BayesW PRS model effectively predicted the individual’s BC risk (OR = 1.37; 95% CI = 1.03–1.81, p = 0.02905 with AUC = 0.759). However, none of the applied PRS models was a good predictor of OC risk. The best-fitted PRS model (BayesW) contributed to assessing the risk of developing BC for germline BRCA1 PV (c.4035del or c.5266dup) carriers and may facilitate more precise and timely patient stratification and decision-making to improve the current BC treatment or even prevention strategies.en
dc.description.statusPeer reviewed
dc.format.extent928529
dc.identifier.citationBerga-Švītiņa, E, Maksimenko, J, Miklaševičs, E, Fischer, K, Vilne, B & Mägi, R 2023, 'Polygenic Risk Score Predicts Modified Risk in BRCA1 Pathogenic Variant c.4035del and c.5266dup Carriers in Breast Cancer Patients', Cancers, vol. 15, no. 11, 2957. https://doi.org/10.3390/cancers15112957
dc.identifier.doi10.3390/cancers15112957
dc.identifier.issn2072-6694
dc.identifier.otherMendeley: 3b60abbf-ba22-3d72-8f3b-4be060e102b9
dc.identifier.urihttps://dspace.rsu.lv/jspui/handle/123456789/14929
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85161944821&partnerID=8YFLogxK
dc.identifier.urlhttps://www.mendeley.com/catalogue/3b60abbf-ba22-3d72-8f3b-4be060e102b9/
dc.language.isoeng
dc.relation.ispartofCancers
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBRCA1 pathogenic variant carriers
dc.subjectbreast cancer
dc.subjectovarian cancer
dc.subjectpolygenic risk score (PRS)
dc.subject3.2 Clinical medicine
dc.subject1.1. Scientific article indexed in Web of Science and/or Scopus database
dc.subjectOncology
dc.subjectCancer Research
dc.subjectSDG 3 - Good Health and Well-being
dc.titlePolygenic Risk Score Predicts Modified Risk in BRCA1 Pathogenic Variant c.4035del and c.5266dup Carriers in Breast Cancer Patientsen
dc.type/dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Polygenic_Risk_Score_Predicts_Modified_Risk_in_BRCA1_Pathogenic_Variant_c.4035del_and_c.5266dup_Carriers_in_Breast_Cancer_Patients.pdf
Size:
906.77 KB
Format:
Adobe Portable Document Format
Download

Collections

Research outputs from Pure / Zinātniskās darbības rezultāti no ZDIS Pure