Genetic overlap between endometriosis and endometrial cancer: evidence from cross-disease genetic correlation and GWAS meta-analyses
AuthorPainter, JN; O'Mara, TA; Morris, AP; Cheng, THT; Gorman, M; Martin, L; Hodson, S; Jones, A; Martin, NG; Gordon, S; ...
Source TitleCancer Medicine
AffiliationMelbourne School of Population and Global Health
Document TypeJournal Article
CitationsPainter, J. N., O'Mara, T. A., Morris, A. P., Cheng, T. H. T., Gorman, M., Martin, L., Hodson, S., Jones, A., Martin, N. G., Gordon, S., Henders, A. K., Attia, J., McEvoy, M., Holliday, E. G., Scott, R. J., Webb, P. M., Fasching, P. A., Beckmann, M. W., Ekici, A. B. ,... Spurdle, A. B. (2018). Genetic overlap between endometriosis and endometrial cancer: evidence from cross-disease genetic correlation and GWAS meta-analyses. CANCER MEDICINE, 7 (5), pp.1978-1987. https://doi.org/10.1002/cam4.1445.
Access StatusOpen Access
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.
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