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

Publication ,  Journal Article
Dareng, EO; Coetzee, SG; Tyrer, JP; Peng, P-C; Rosenow, W; Chen, S; Davis, BD; Dezem, FS; Seo, J-H; Nameki, R; Reyes, AL; Aben, KKH; Black, A ...
Published in: Am J Hum Genet
June 6, 2024

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.

Duke Scholars

Published In

Am J Hum Genet

DOI

EISSN

1537-6605

Publication Date

June 6, 2024

Volume

111

Issue

6

Start / End Page

1061 / 1083

Location

United States

Related Subject Headings

  • Transcriptome
  • Risk Factors
  • Polymorphism, Single Nucleotide
  • Ovarian Neoplasms
  • Multiomics
  • Humans
  • Genomics
  • Genome-Wide Association Study
  • Genetics & Heredity
  • Genetic Predisposition to Disease
 

Citation

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Dareng, E. O., Coetzee, S. G., Tyrer, J. P., Peng, P.-C., Rosenow, W., Chen, S., … Gayther, S. A. (2024). Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions. Am J Hum Genet, 111(6), 1061–1083. https://doi.org/10.1016/j.ajhg.2024.04.011
Dareng, Eileen O., Simon G. Coetzee, Jonathan P. Tyrer, Pei-Chen Peng, Will Rosenow, Stephanie Chen, Brian D. Davis, et al. “Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.Am J Hum Genet 111, no. 6 (June 6, 2024): 1061–83. https://doi.org/10.1016/j.ajhg.2024.04.011.
Dareng EO, Coetzee SG, Tyrer JP, Peng P-C, Rosenow W, Chen S, et al. Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions. Am J Hum Genet. 2024 Jun 6;111(6):1061–83.
Dareng, Eileen O., et al. “Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.Am J Hum Genet, vol. 111, no. 6, June 2024, pp. 1061–83. Pubmed, doi:10.1016/j.ajhg.2024.04.011.
Dareng EO, Coetzee SG, Tyrer JP, Peng P-C, Rosenow W, Chen S, Davis BD, Dezem FS, Seo J-H, Nameki R, Reyes AL, Aben KKH, Anton-Culver H, Antonenkova NN, Aravantinos G, Bandera EV, Beane Freeman LE, Beckmann MW, Beeghly-Fadiel A, Benitez J, Bernardini MQ, Bjorge L, Black A, Bogdanova NV, Bolton KL, Brenton JD, Budzilowska A, Butzow R, Cai H, Campbell I, Cannioto R, Chang-Claude J, Chanock SJ, Chen K, Chenevix-Trench G, AOCS Group, Chiew Y-E, Cook LS, DeFazio A, Dennis J, Doherty JA, Dörk T, du Bois A, Dürst M, Eccles DM, Ene G, Fasching PA, Flanagan JM, Fortner RT, Fostira F, Gentry-Maharaj A, Giles GG, Goodman MT, Gronwald J, Haiman CA, Håkansson N, Heitz F, Hildebrandt MAT, Høgdall E, Høgdall CK, Huang R-Y, Jensen A, Jones ME, Kang D, Karlan BY, Karnezis AN, Kelemen LE, Kennedy CJ, Khusnutdinova EK, Kiemeney LA, Kjaer SK, Kupryjanczyk J, Labrie M, Lambrechts D, Larson MC, Le ND, Lester J, Li L, Lubiński J, Lush M, Marks JR, Matsuo K, May T, McLaughlin JR, McNeish IA, Menon U, Missmer S, Modugno F, Moffitt M, Monteiro AN, Moysich KB, Narod SA, Nguyen-Dumont T, Odunsi K, Olsson H, Onland-Moret NC, Park SK, Pejovic T, Permuth JB, Piskorz A, Prokofyeva D, Riggan MJ, Risch HA, Rodríguez-Antona C, Rossing MA, Sandler DP, Setiawan VW, Shan K, Song H, Southey MC, Steed H, Sutphen R, Swerdlow AJ, Teo SH, Terry KL, Thompson PJ, Vestrheim Thomsen LC, Titus L, Trabert B, Travis R, Tworoger SS, Valen E, Van Nieuwenhuysen E, Edwards DV, Vierkant RA, Webb PM, OPAL Study Group, Weinberg CR, Weise RM, Wentzensen N, White E, Winham SJ, Wolk A, Woo Y-L, Wu AH, Yan L, Yannoukakos D, Zeinomar N, Zheng W, Ziogas A, Berchuck A, Goode EL, Huntsman DG, Pearce CL, Ramus SJ, Sellers TA, Ovarian Cancer Association Consortium (OCAC), Freedman ML, Lawrenson K, Schildkraut JM, Hazelett D, Plummer JT, Kar S, Jones MR, Pharoah PDP, Gayther SA. Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions. Am J Hum Genet. 2024 Jun 6;111(6):1061–1083.
Journal cover image

Published In

Am J Hum Genet

DOI

EISSN

1537-6605

Publication Date

June 6, 2024

Volume

111

Issue

6

Start / End Page

1061 / 1083

Location

United States

Related Subject Headings

  • Transcriptome
  • Risk Factors
  • Polymorphism, Single Nucleotide
  • Ovarian Neoplasms
  • Multiomics
  • Humans
  • Genomics
  • Genome-Wide Association Study
  • Genetics & Heredity
  • Genetic Predisposition to Disease