Genetic overlap between endometriosis and endometrial cancer: evidence from cross-disease genetic correlation and GWAS meta-analyses

Jodie N. Painter, Tracy A. O'Mara, Andrew P. Morris, Timothy H.T. Cheng, Maggie Gorman, Lynn Martin, Shirley Hodson, Angela Jones, Nicholas G. Martin, Scott Gordon, Anjali K. Henders, John Attia, Mark McEvoy, Elizabeth G. Holliday, Rodney J. Scott, Penelope M. Webb, Peter A. Fasching, Matthias W. Beckmann, Arif B. Ekici, Alexander HeinMatthias Rübner, Per Hall, Kamila Czene, Thilo Dörk, Matthias Dürst, Peter Hillemanns, Ingo Runnebaum, Diether Lambrechts, Frederic Amant, Daniela Annibali, Jeroen Depreeuw, Adriaan Vanderstichele, Ellen L. Goode, Julie M. Cunningham, Sean C. Dowdy, Stacey J. Winham, Jone Trovik, Erling Hoivik, Henrica M.J. Werner, Camilla Krakstad, Katie Ashton, Geoffrey Otton, Tony Proietto, Emma Tham, Miriam Mints, Shahana Ahmed, Catherine S. Healey, Mitul Shah, Paul D.P. Pharoah, Alison M. Dunning, Joe Dennis, Manjeet K. Bolla, Kyriaki Michailidou, Qin Wang, Jonathan P. Tyrer, John L. Hopper, Julian Peto, Anthony J. Swerdlow, Barbara Burwinkel, Hermann Brenner, Alfons Meindl, Hiltrud Brauch, Annika Lindblom, Jenny Chang-Claude, Fergus J. Couch, Graham G. Giles, Vessela N. Kristensen, Angela Cox, Krina T. Zondervan, Dale R. Nyholt, Stuart MacGregor, Grant W. Montgomery, Ian Tomlinson, Douglas F. Easton, Deborah J. Thompson, Amanda B. Spurdle

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Epidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (r g = 0.23, P = 9.3 × 10 −3 ), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10 −3 ) and concordance in effect direction (P = 2.0 × 10 −3 ) between the two diseases. Cross-disease GWAS meta-analysis highlighted 13 distinct loci associated at P ≤ 10 −5 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10 −8 , OR = 1.11, 95% CI = 1.07–1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross-disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases.

Original languageEnglish (US)
Pages (from-to)1978-1987
Number of pages10
JournalCancer medicine
Volume7
Issue number5
DOIs
StatePublished - May 2018

Keywords

  • Cross-disease analysis
  • endometrial cancer
  • endometriosis
  • genetic correlation
  • genome-wide association study

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

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