TY - JOUR
T1 - Genome-wide association study of 398,238 women unveils seven loci associated with high-grade serous ovarian cancer
AU - Barnes, Daniel
AU - Tyrer, Jonathan P
AU - Antoniou, Antonis C.
AU - Pharoah, Paul D P
AU - Richenberg, George F
AU - al , et
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/11/20
Y1 - 2025/11/20
N2 - Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We meta-analyzed >22 million variants for 398,238 women from the Ovarian Cancer Association Consortium (OCAC), UK Biobank (UKBB) and Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA) to identify novel HGSOC susceptibility loci. Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was TP53 3’-UTR SNP rs78378222-T’s association with HGSOC (per-T-allele relative risk (RR) = 1.44, 95% CI:1.28–1.62, P = 1.76 × 10−9). Polygenic scores (PGS) were developed using OCAC and CIMBA data and trained on FinnGen data. 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 when validated in the UKBB. This study represents the largest HGSOC GWAS to date – demonstrating that improvements in imputation reference panels and increased sample sizes help to identify HGSOC associated variants that previously went undetected, ultimately improving PGS which can improve personalized HGSOC risk prediction.
AB - Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We meta-analyzed >22 million variants for 398,238 women from the Ovarian Cancer Association Consortium (OCAC), UK Biobank (UKBB) and Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA) to identify novel HGSOC susceptibility loci. Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was TP53 3’-UTR SNP rs78378222-T’s association with HGSOC (per-T-allele relative risk (RR) = 1.44, 95% CI:1.28–1.62, P = 1.76 × 10−9). Polygenic scores (PGS) were developed using OCAC and CIMBA data and trained on FinnGen data. 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 when validated in the UKBB. This study represents the largest HGSOC GWAS to date – demonstrating that improvements in imputation reference panels and increased sample sizes help to identify HGSOC associated variants that previously went undetected, ultimately improving PGS which can improve personalized HGSOC risk prediction.
U2 - 10.1038/s41525-025-00529-w
DO - 10.1038/s41525-025-00529-w
M3 - Article (Academic Journal)
C2 - 41266372
SN - 2056-7944
VL - 10
JO - NPJ Genomic Medicine
JF - NPJ Genomic Medicine
IS - 1
M1 - 73
ER -
