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

Authors :
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 Hein
Matthias 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
Source :
Cancer Medicine, Vol 7, Iss 5, Pp 1978-1987 (2018)
Publication Year :
2018
Publisher :
Wiley, 2018.

Abstract

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 (rg = 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.

Details

Language :
English
ISSN :
20457634
Volume :
7
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Cancer Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.463fb4a945b24c1c8ee3d74f75c3da32
Document Type :
article
Full Text :
https://doi.org/10.1002/cam4.1445