medRxivGenetic & Genomic MedicinePreprint
Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk
Daniel R. BarnesiD, Jonathan P. TyreriD, Joe DennisiD, Goska LeslieiD, Manjeet K. BollaiD, Michael J. LushiD, Amber M. AeiltsiD, Kristiina AittomäkiiD, Nadine AndrieuiD, Irene Louise AndrulisiD, Hoda Anton‐CulveriD, Aðalgeir ArasoniD, Banu AruniD, Judith BalmañàiD, Elisa Victoria BanderaiD, Rosa Bjork BarkardottiriD, Lieke P. V. BergeriD, Amy Berrington de GonzáleziD, Pascaline Berthet, Katarzyna BiałkowskaiD, Line BjørgeiD, Amie M BlancoiD, Marinus J. BlokiD, Kristie A. Bobolis, Natalia Viktorovna BogdanovaiD, , Kirsten B. MoysichiD
Abstract
BackgroundNineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). MethodsWe analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan ResultsEight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that TP53 3-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76x10-9). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). ConclusionsThis study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 3
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Multi-Tissue Transcriptome-Wide Association Studies Identify 21 Novel Candidate Susceptibility Genes for High Grade Serous Epithelial Ovarian Cancer
Alexander Gusev, Kate Lawrenson, … Simon A. Gayther·bioRxiv·May 25, 2018
- The genomic landscape of early stage ovarian high grade serous carcinoma
Z. Cheng, H. Mirza, … I. McNeish·bioRxiv·May 5, 2021
- Population based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high grade serous ovarian cancer
Honglin Song, Ed Dicks, … Paul D.P. Pharoah·Journal of Medical GeneticsPeer-reviewed·Jun 16, 2020
- Structural variants at the BRCA1/2 loci are a common source of homologous repair deficiency in high grade serous ovarian carcinoma
A. Ewing, A. Meynert, … C. A. Semple·bioRxiv·May 11, 2020
- Ovarian Cancer Risk Variants are Enriched in Histotype-Specific Enhancers that Disrupt Transcription Factor Binding Sites
Michelle R. Jones, Pei-Chen Peng, … Simon A. Gayther·The American Journal of Human GeneticsPeer-reviewed·Sep 17, 2020
- Cross-ancestral GWAS identifies 29 novel variants across Head and Neck Cancer subsites
Elmira Ebrahimi, Apiwat Sangphukieo, … Paolo Garzino‐Demo·Nature CommunicationsPeer-reviewed·Oct 2, 2025