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Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions

Eileen O Dareng, Simon G Coetzee, Jonathan P Tyrer, Pei-Chen Peng, Will Rosenow, Stephanie Chen, Brian D Davis, Felipe Segato Dezem, Ji-Heui Seo, Robbin Nameki, Alberto L Reyes, Katja K H Aben, Hoda Anton-Culver, Natalia N Antonenkova, Gerasimos Aravantinos, Elisa V Bandera, Laura E Beane Freeman, Matthias W Beckmann, Alicia Beeghly-Fadiel, Javier BenitezMarcus Q Bernardini, Line Bjorge, Amanda Black, Natalia V Bogdanova, Kelly L Bolton, James D Brenton, Agnieszka Budzilowska, Ralf Butzow, Hui Cai, Ian Campbell, Rikki Cannioto, Jenny Chang-Claude, Stephen J Chanock, Kexin Chen, Georgia Chenevix-Trench, Yoke-Eng Chiew, Linda S Cook, Anna DeFazio, Joe Dennis, Jennifer A Doherty, Thilo Dörk, Andreas du Bois, Matthias Dürst, Diana M Eccles, Gabrielle Ene, Peter A Fasching, Estrid Høgdall, Claus K Høgdall, Allan Jensen, Susanne K Kjaer, AOCS group

14 Citations (Scopus)

Abstract

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

Original languageEnglish
JournalAmerican Journal of Human Genetics
Volume111
Issue number6
Pages (from-to)1061-1083
Number of pages23
ISSN0002-9297
DOIs
Publication statusPublished - 6 Jun 2024

Keywords

  • Carcinoma, Ovarian Epithelial/genetics
  • Case-Control Studies
  • Female
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study
  • Genomics/methods
  • Humans
  • Multiomics
  • Ovarian Neoplasms/genetics
  • Polymorphism, Single Nucleotide
  • Risk Factors
  • Transcriptome
  • GWAS
  • epithelial ovarian cancer risk
  • functional mechanisms
  • fine mapping

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