Generalizability of PGS 313 for breast cancer risk in a Los Angeles biobank.

Autor: Shang H; Division of Internal Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA; Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA. Electronic address: hshang@mednet.ucla.edu., Ding Y; Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA., Venkateswaran V; Department of Oral Biology, UCLA School of Dentistry, Los Angeles, CA, USA., Boulier K; Division of Cardiology, Department of Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA., Kathuria-Prakash N; Division of Hematology-Oncology, Department of Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA., Malidarreh PB; Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA; Multi-Interprofessional Center for Health Informatics, University of Texas at Arlington, Arlington, TX, USA., Luber JM; Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA; Multi-Interprofessional Center for Health Informatics, University of Texas at Arlington, Arlington, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA., Pasaniuc B; Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA.
Jazyk: angličtina
Zdroj: HGG advances [HGG Adv] 2024 Jul 18; Vol. 5 (3), pp. 100302. Date of Electronic Publication: 2024 May 03.
DOI: 10.1016/j.xhgg.2024.100302
Abstrakt: Polygenic scores (PGSs) summarize the combined effect of common risk variants and are associated with breast cancer risk in patients without identifiable monogenic risk factors. One of the most well-validated PGSs in breast cancer to date is PGS 313 , which was developed from a Northern European biobank but has shown attenuated performance in non-European ancestries. We further investigate the generalizability of the PGS 313 for American women of European (EA), African (AFR), Asian (EAA), and Latinx (HL) ancestry within one institution with a singular electronic health record (EHR) system, genotyping platform, and quality control process. We found that the PGS 313 achieved overlapping areas under the receiver operator characteristic (ROC) curve (AUCs) in females of HL (AUC = 0.68, 95% confidence interval [CI] = 0.65-0.71) and EA ancestry (AUC = 0.70, 95% CI = 0.69-0.71) but lower AUCs for the AFR and EAA populations (AFR: AUC = 0.61, 95% CI = 0.56-0.65; EAA: AUC = 0.64, 95% CI = 0.60-0.680). While PGS 313 is associated with hormone-receptor-positive (HR+) disease in EA Americans (odds ratio [OR] = 1.42, 95% CI = 1.16-1.64), this association is lost in African, Latinx, and Asian Americans. In summary, we found that PGS 313 was significantly associated with breast cancer but with attenuated accuracy in women of AFR and EAA descent within a singular health system in Los Angeles. Our work further highlights the need for additional validation in diverse cohorts prior to the clinical implementation of PGSs.
Competing Interests: Declaration of interests The authors declare no competing interests.
(Published by Elsevier Inc.)
Databáze: MEDLINE
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