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

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.

SUBMITTER: Painter JN

PROVIDER: S-EPMC5943470 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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

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

Cancer medicine 20180402 5

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 r ...[more]

PMID: 29608257

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Project description:BackgroundClinical and epidemiological studies have suggested systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are comorbidities and common genetic etiologies can partly explain such coexistence. However, shared genetic determinations underlying the two diseases remain largely unknown.MethodsOur analysis relied on summary statistics available from genome-wide association studies of SLE (N = 23,210) and RA (N = 58,284). We first evaluated the genetic correlation between RA and SLE through the linkage disequilibrium score regression (LDSC). Then, we performed a multiple-tissue eQTL (expression quantitative trait loci) weighted integrative analysis for each of the two diseases and aggregated association evidence across these tissues via the recently proposed harmonic mean P-value (HMP) combination strategy, which can produce a single well-calibrated P-value for correlated test statistics. Afterwards, we conducted the pleiotropy-informed association using conjunction conditional FDR (ccFDR) to identify potential pleiotropic genes associated with both RA and SLE.ResultsWe found there existed a significant positive genetic correlation (r g = 0.404, P = 6.01E-10) via LDSC between RA and SLE. Based on the multiple-tissue eQTL weighted integrative analysis and the HMP combination across various tissues, we discovered 14 potential pleiotropic genes by ccFDR, among which four were likely newly novel genes (i.e., INPP5B, OR5K2, RP11-2C24.5, and CTD-3105H18.4). The SNP effect sizes of these pleiotropic genes were typically positively dependent, with an average correlation of 0.579. Functionally, these genes were implicated in multiple auto-immune relevant pathways such as inositol phosphate metabolic process, membrane and glucagon signaling pathway.ConclusionThis study reveals common genetic components between RA and SLE and provides candidate associated loci for understanding of molecular mechanism underlying the comorbidity of the two diseases.

Dataset Information

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

Publications

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

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