Evidence of a genetic link between endometriosis and ovarian cancer

ORIGINAL ARTICLE: GENETICS

Evidence of a genetic link between endometriosis and ovarian cancer Alice W. Lee, M.P.H.,a Claire Templeman, M.D.,b Douglas A. Stram, B.S.,a Jonathan Beesley, Ph.D.,c Jonathan Tyrer, Ph.D.,d Andrew Berchuck, M.D.,e Paul P. Pharoah, Ph.D.,d,f Georgia Chenevix-Trench, Ph.D.,c and Celeste Leigh Pearce, Ph.D.,a,g on behalf of the Ovarian Cancer Association Consortium a Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California; b Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, California; c Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; d Department of Oncology and Strangeways Research Laboratory, University of Cambridge, Cambridge, United Kingdom; e Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina; f Department of Public Health and Primary Care and Strangeways Research Laboratory, University of Cambridge, Cambridge, United Kingdom; and g Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan

Objective: To evaluate whether endometriosis-associated genetic variation affects risk of ovarian cancer. Design: Pooled genetic analysis. Setting: University hospital. Patient(s): Genetic data from 46,176 participants (15,361 ovarian cancer cases and 30,815 controls) from 41 ovarian cancer studies. Intervention(s): None. Main Outcome Measure(s): Endometriosis-associated genetic variation and ovarian cancer. Result(s): There was significant evidence of an association between endometriosis-related genetic variation and ovarian cancer risk, especially for the high-grade serous and clear cell histotypes. Overall we observed 15 significant burden statistics, which was three times more than expected.

Received June 8, 2015; revised August 17, 2015; accepted September 16, 2015. P.P.P. reports grants from the National Institutes of Health and Cancer Research UK during the conduct of the study. A.W.L. has nothing to disclose. C.T. has nothing to disclose. D.A.S. has nothing to disclose. J.B. has nothing to disclose. J.T. has nothing to disclose. A.B. has nothing to disclose. G.C.-T. has nothing to disclose. C.L.P. has nothing to disclose. This work was supported by the National Cancer Institute (K07-CA095666, K07-CA80668, K07-CA143047, K22-CA138563, N01-CN55424, N01-PC67001, N01PC067010, N01-PC035137, P01-CA017054, P01-CA087696, P30-CA072720, P30-CA15083, P30-CA008748, P50-CA159981, P50-CA105009, P50-CA136393, R01-CA149429, R01-CA014089, R01-CA016056, R01-CA017054, R01-CA049449, R01-CA050385, R01-CA054419, R01-CA058598, R01-CA058860, R01CA061107, R01-CA061132, R01-CA063678, R01-CA063682, R01-CA067262, R01-CA071766, R01-CA074850, R01-CA076016, R01-CA080978, R01CA083918, R01-CA087538, R01-CA092044, R01-CA095023, R01-CA122443, R01-CA112523, R01-CA114343, R01-CA126841, R01-CA136924, R03CA113148, R03-CA115195, U01-CA069417, U01-CA071966, and Intramural research funds); the European Commission's Seventh Framework Programme (agreement number 223175 HEALTH F2 2009-223175); a National Cancer Institute, Cancer Post-GWAS Initiative (U19-CA148112); the Genetic Associations and Mechanisms in Oncology (GAME-ON); the Ovarian Cancer Research Fund (thanks to donations by the family and friends of Kathryn Sladek Smith) (PPD/RPCI.07); the National Institute of Environmental Health Sciences (T32ES013678 to A.W.L.); National Health and Medical Research Council (to G.-C.T.); American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN to B.K.); National Center for Advancing Translational Sciences (NCATS) (UL1TR000124 to B.K.); California Cancer Research Program (00-01389V-20170, N01-CN25403, 2II0200); the Canadian Institutes of Health Research (MOP-86727); Cancer Australia; Cancer Council Victoria; Cancer Council Queensland; Cancer Council New South Wales; Cancer Council South Australia; Cancer Council Tasmania; Cancer Foundation of Western Australia; the Cancer Institute of New Jersey; Cancer Research UK (C490/A6187, C490/A10119, C490/A10124); the Danish Cancer Society (94-222-52); the ELAN Program of the University of Erlangen-Nuremberg; the Eve Appeal; the Helsinki University Central Hospital Research Fund; Helse Vest; the Norwegian Cancer Society; the Norwegian Research Council; the Ovarian Cancer Research Fund; Nationaal Kankerplan of Belgium; the L & S Milken Foundation; the Polish Ministry of Science and Higher Education (4 PO5C 028 14, 2 PO5A 068 27); the Roswell Park Cancer Institute Alliance Foundation; the National Institutes of Health/National Center for Research Resources/General Clinical Research Center (MO1-RR000056); the US Army Medical Research and Material Command (DAMD17-01-1-0729, DAMD1702-1-0666, DAMD17-02-1-0669, W81XWH-07-0449, W81XWH-10-1-02802); the U.S. Public Health Service (PSA-042205); the National Health and Medical Research Council of Australia (199600, 400281); the German Federal Ministry of Education and Research of Germany Programme of Clinical Biomedical Research (01 GB 9401); the State of Baden-Wurttemberg through Medical Faculty of the University of Ulm (P.685); the German Cancer Research Center; the Minnesota Ovarian Cancer Alliance; the Mayo Foundation; the Fred C. and Katherine B. Andersen Foundation; the Lon V. Smith Foundation (LVS-39420); the Oak Foundation; the Oregon Health & Science University Foundation; the Mermaid I project; the Rudolf-Bartling Foundation; the UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge, Imperial College London, University College Hospital ‘‘Womens Health Theme’’ and the Royal Marsden Hospital; and WorkSafeBC 14. A.W.L., C.T., G.C.-T., and C.L.P. should be considered similar in author order. Reprint requests: Celeste Leigh Pearce, Ph.D., Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, SPH Tower, Office #4642, Ann Arbor, MI 48109-2029 (E-mail: [email protected]). Fertility and Sterility® Vol. -, No. -, - 2015 0015-0282/$36.00 Copyright ©2015 American Society for Reproductive Medicine, Published by Elsevier Inc. http://dx.doi.org/10.1016/j.fertnstert.2015.09.023 VOL. - NO. - / - 2015

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ORIGINAL ARTICLE: GENETICS Conclusion(s): By focusing on candidate regions from a phenotype associated with ovarian cancer, we have shown a clear genetic link between endometriosis and ovarian cancer that warrants further follow-up. The functional significance of the identified regions and SNPs is presently uncertain, though future fine mapping and histotype-specific functional analyses may shed light on the etiologies of both gynecologic conditions. (Fertil SterilÒ 2015;-: -–-. Ó2015 by American Society for Reproductive Medicine.) Key Words: Endometriosis, ovarian cancer, genetic variation, SNPs Discuss: You can discuss this article with its authors and with other ASRM members at http:// fertstertforum.com/leea-endometriosis-ovarian-cancer/

O

varian carcinoma (ovarian cancer) is the most fatal malignancy in the female reproductive system, accounting for more than 140,000 deaths annually worldwide (1). Endometriosis, the presence of ectopic endometrial glands and tissue in the peritoneum, is a common gynecologic condition, occurring in 6%–10% of the general female population (2). Studies that have controlled for parity have shown that endometriosis is a well-established ovarian cancer risk factor, especially for the endometrioid and clear cell histotypes (3). Although the etiology of endometriosis remains enigmatic, it is influenced by genetic factors, with an estimated heritability of 51% and an incidence that is approximately seven times higher in relatives of women with endometriosis than in women without such family history (4, 5). To date, seven variants reaching genome-wide significance have been identified in association with risk of endometriosis (6–8). In addition, the most recent meta-analysis by Nyholt et al. (9) has identified multiple additional variants associated with risk, albeit some at a sub-genome-wide significance level (P%1
105). Genetics also plays a role in the etiology of ovarian cancer: women with first-degree family histories of the disease have more than a twofold increased risk (10). High-penetrance susceptibility genes, such as BRCA1 and BRCA2, as well as 18 published common variants identified through genome-wide association studies (GWASs) account for a substantial portion of ovarian cancer's familial risk, but at least 60% remains unexplained (6–8,11–16). Lee et al. (17) have previously shown that the cumulative effect of many risk variants contributes to disease heritability, and hence it is likely that the germline genetic contributions to ovarian cancer are not limited to GWAS-identified variants. Given the important role genetics plays in the etiologies of both endometriosis and ovarian cancer and the consistent epidemiologic evidence of their association with one another, the two gynecologic conditions may also have a similar genetic profile. Hence, on the basis of the results presented by Nyholt et al. of their endometriosis GWAS meta-analysis, we present the first report that evaluates whether variation in the 18 regions harboring the top 38 endometriosis-associated singlenucleotide polymorphisms (SNPs) is associated with risk of ovarian cancer.

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MATERIALS AND METHODS All studies included in this report obtained institutional ethics committee approval, and all participating subjects provided written, informed consent.

Study Populations Our analysis included 41 studies participating in the Ovarian Cancer Association Consortium (OCAC), an international collaboration of ovarian cancer studies founded in 2005. In total, 20 studies were conducted in Europe, 19 in North America, and 2 in Australia. Only participants of European ancestry were included, as was determined from the program LAMP (Local Ancestry in Admixed Populations) (see ‘‘Statistical Analysis,’’ below). We used a combined total of 46,176 participants (15,361 ovarian cancer cases and 30,815 controls) in our analyses; borderline tumors were excluded. Details regarding sample quality control have been previously published (15). Supplemental Table 1 (available online) provides an overview of each study's characteristics and the numbers of subjects included.

Genotyping and Imputation Analyses The genetic data for our analyses came from three population-based ovarian cancer GWASs, which comprised 2,162 cases and 2,564 controls from a GWAS in North America (‘‘US GWAS’’) (18), 1,763 cases and 6,118 controls from a GWAS in the United Kingdom (‘‘UK GWAS’’) (11), and 443 cases and 441 controls from a second GWAS in North America. In addition, 11,030 cases and 21,693 controls were genotyped using the iCOGS array, which was a large-scale genotyping project by the Collaborative Oncological Geneenvironment Study (COGS) (15). The US and UK GWASs included several independent case–control studies, and samples from these studies were also genotyped using the iCOGS array. All duplicates were removed from the analyses, resulting in genetic data for 15,361 women diagnosed with ovarian cancer and 30,815 controls. Study sets were created on the basis of the scope of genotyping information (GWAS vs. COGS) available for imputation. These sets are indicated in Supplemental Table 1. Details regarding the genotyping platform for each dataset have been published previously (15). Imputation of the entire scope of genetic variation in the genome was carried out separately for iCOGS samples and VOL. - NO. - / - 2015

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Fertility and Sterility® each of the GWASs. We imputed variants by combining all available genotype data with information from the April 2012 release of the 1000 Genomes Project using the program IMPUTE2 (19). In addition, all data were pre-phased using the software SHAPEIT, to improve computation efficiency (20).

SNP Selection The SNPs evaluated here were based on the results of Nyholt et al.'s genome-wide association meta-analysis (9), which included two large endometriosis GWASs: one conducted in a Japanese sample obtained from BioBank Japan (21) and the other in a European sample from Australia and the UK by the International Endogene Consortium (22). Nyholt et al. found six SNPs (rs7521902, rs12700667, rs10859871, rs4141819, rs1537377, and rs7739264) that reached genomewide significance (P%5
108) in their analysis, as well as an additional SNP (rs13394619) that reached genome-wide significance when combined with the results from a previous meta-analysis of two Japanese case–control cohorts (23). These seven SNPs, as well as an additional 31 SNPs that showed suggestive evidence of an association with endometriosis (P%1
105), were included in our analyses for a total of 38 index SNPs. A list of these SNPs is provided in Table 1. In addition, we evaluated genetic variation in the surrounding regions of each of the 38 index SNPs. Initially these regions were defined as the areas 25 kb up- and downstream of each index SNP. All variants in these 50-kb regions were analyzed, and the SNP with the strongest ovarian cancer association in each region was identified. The final regions, which we have labeled as regions A to R, were defined as including all SNPs with an r2 R 0.2 with the most significantly associated ovarian cancer SNPs. On the basis of each SNP's linkage disequilibrium pattern, a total of 18 regions of varying sizes was identified because some of the 38 SNPs were strongly correlated with each other. Only SNPs with an imputation r2 R 0.5 and a minor allele frequency (MAF) R0.05 were considered. In total, 6,981 SNPs (including the original 38 SNPs) were assessed.

Statistical Analysis We used LAMP to assign intercontinental ancestry according to genotype frequencies in European populations according to HapMap (24). Subjects were classified as European if they had 90% or more European ancestry. Principal components analysis to control for population substructure was also performed using a set of 37,000 unlinked markers, as well as an in-house program written in Cþþ that used the Intel MKL library for eigenvectors (http://ccge.medschl.cam.ac.uk/software/pccalc). We carried out unconditional logistic regression analyses, adjusting for the first five eigenvalues from the principal components analysis for European ancestry, to determine the association between each SNP and risk of ovarian cancer. For all ovarian cancer cases combined and for high-grade serous cases, the analyses were carried out within each study set, and the set-specific results were summarized using a fixed-effects meta-analysis approach. For

the less-common histotypes (mucinous, endometrioid, clear cell), the cases and controls were pooled across all study sets, and study set was included as a term in the model. A logadditive mode of inheritance was used, with each SNP modeled as an ordinal variable. Hence, the effect estimates reflect per-allele odds ratios (ORs). All P values reported herein are two-sided. To evaluate whether overall genetic variation implicated in risk of endometriosis also plays a role in risk of ovarian cancer, we calculated burden statistics using the admixture likelihood (AML) method (25). We used the AMLcalc program to accomplish this using 1,000 simulations with the maximum proportion of associated SNPs set to 0.2 on the genotyped and imputed data and adjusting for the first five ancestry principal components. P values for the AML trend test are provided. We calculated burden statistics across the 38 SNPs identified by Nyholt et al., as well as across each of the 18 regions for ovarian cancer overall risk and for the four main histotypes. This allowed us to take a global approach to assess whether the combined variation that exists among the 38 endometriosis-associated SNPs or across the 18 regions plays a role in ovarian cancer risk after accounting for the correlation between SNPs. Manhattan plots were generated by plotting the -log P vs. the chromosomal position using GraphPad Prism 6 to provide a picture of the distribution of P values by histotype across each region. This plotting was done for all regions except region A because it was presented in a recent meta-analysis by OCAC and the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) (16). Linkage disequilibrium plots depicting pairwise correlation data from the 1000 Genomes CEU (Utah residents [CEPH] with Northern and Western European Ancestry) population were generated using HaploView. Epigenomic data made available from the ENCODE and Roadmap Epigenomics Consortia were obtained and visualized in the University of California, Santa Cruz Genome Browser.

RESULTS In total, 38 SNPs with a P%1
105 spanning 18 unique, uncorrelated regions were identified from the endometriosis GWAS meta-analysis carried out by Nyholt et al. (9) (Table 1). Table 1 presents the association between each of those 38 SNPs and risk of ovarian cancer. Eight SNPs (rs7515106, rs7521902, rs742356, rs4858692, rs1603995, rs4241991, rs6907340, and rs10777670) from five different regions (regions A, F, I, J, and R) showed statistically significant associations with ovarian cancer risk (P%.05), with the most significantly associated SNP being rs7515106 from region A on chromosome 1 (P¼4.9
106). When considering all 38 SNPs together, the calculated AML burden statistic showed significant evidence of an association with ovarian cancer risk (P¼ .001); it slightly attenuated when the SNPs from region A were excluded (P¼ .052). Given that each region was defined by the area containing SNPs with an r2 R 0.2 with the SNP most significantly associated with ovarian cancer risk, Table 2 presents the coordinates as well as the number of SNPs with genotyped or imputed data available for each region. Overall, a total of

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ORIGINAL ARTICLE: GENETICS

TABLE 1 Association between the top 38 SNPs identified through endometriosis genome-wide scans and ovarian cancer risk. Endometriosisc a

Region A A A B C C D E F F G H I J J J J J J J K L M N N N N O O P Q Q Q Q R R R R

Chromosome 1p36 1p36 1p36 1p31 2p25 2p25 2p14 3p24 3p24 3p24 3p14 3q13 4q12 6p22 6p22 6p22 6p22 6p22 6p22 6p22 6q21 6q25 6q25 7p15 7p15 7p15 7p15 7q33 7q33 9p21 10q26 10q26 10q26 10q26 12q22 12q22 12q22 12q22

b

Position

22473410 22490724 22501846 80278733 11725241 11727507 67864675 24927203 25075167 25075530 55216779 104575864 55931246 19706761 19708481 19729003 19761215 19785588 19790809 19803768 113111808 152638209 158144402 25860812 25871109 25873110 25901639 134607676 134618710 22169700 117325021 117393524 117396288 117398195 95574831 95631276 95702385 95711876

SNP

OR e

Ovarian cancerd

P value 6

2.1
10 4.6
108 3.1
106 9.6
106 8.1
106 6.1
108 4.0
107 9.6
106 1.3
106 1.6
106 7.4
106 8.6
106 4.6
106 6.3
106 4.3
106 3.1
107 3.4
106 1.3
107 7.3
107 5.9
107 8.2
106 8.1
106 4.4
106 2.1
106 5.6
107 7.4
107 9.3
1010 2.3
106 4.7
106 2.5
106 1.5
106 8.2
106 7.6
106 6.9
106 1.6
107 4.8
107 2.1
106 5.5
109 Burden statistic (all SNPs): Burden statistic (excluding Region A SNPs):

rs7515106 rs7521902e rs742356 rs12744944e rs12470971 rs13394619 rs4141819e rs10510551 rs4858692 rs1603995 rs9311552 rs12635480 rs4241991 rs1016251 rs9366312 rs9356708e rs6916251 rs7739264e rs2223361 rs6907340 rs9487982 rs1890100 rs16900375 rs7798431e rs1055144e rs10282436e rs12700667e rs7809057 rs6973420 rs1537377e rs1572396 rs2769422e rs2804250 rs2769417 rs10777670e rs10859856 rs11107973 rs10859871e

1.18 1.18 1.15 1.15 1.14 1.15 1.16 1.14 1.16 1.16 1.13 1.34 1.16 1.14 1.14 1.16 1.14 1.16 1.15 1.15 1.22 1.16 1.29 1.16 1.18 1.18 1.22 1.15 1.14 1.14 1.16 1.14 1.15 1.15 1.19 1.15 1.14 1.18

OR

P value

1.09 1.08 1.05 1.00 0.97 0.98 1.00 1.01 0.96 0.96 1.00 0.99 0.95 1.02 1.02 1.02 1.02 0.98 1.03 1.03 0.99 1.01 1.01 0.98 0.97 0.97 0.97 1.00 1.00 1.03 1.02 1.01 1.01 1.01 1.05 1.01 1.01 1.03

4.9
106* 7.3
106* .004* .80 .062 .23 .86 .54 .025* .017 .85 .78 .018* .154 .14 .132 .13 .13 .093 .045* .68 .70 .84 .28 .19 .18 .072 .81 .87 .071 .24 .55 .54 .55 .021* .39 .36 .088 .001* .052

a

The 38 SNPs represent 18 distinct regions of linkage disequilibrium (Regions A-R). Based on build 37. Odds ratios and P values reported in Nyholt et al. (9) for the association between the SNP and risk of endometriosis. d Odds ratios and P-values for the association between the SNP and risk of ovarian cancer. e SNP was genotyped. * Significant P values at P%.05 for ovarian cancer. b c

Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

6,981 SNPs across 18 regions were evaluated. Region O was the largest, spanning almost 500 kb, but region R included the largest number of SNPs with an MAF R0.05 and an imputation r2 R 0.8 (n ¼ 1,309). Table 2 also presents the burden statistics for each region for all ovarian cancers combined and for the four main histotypes. In total there were 15 significant burden statistics at a P%.05 level, covering eight different regions. Of these, the most significant burden statistic was for region A (P¼5.0
105 for overall). However, there was a total of six regions (A, C, D, I, P, and R) that showed a significant association with ovarian cancer overall, and among them, five regions also had significant histotype-specific burden statistics. High-grade serous and clear cell cancers had the greatest

number of significant burden statistics, each with four and both sharing region A. When burden statistics were calculated globally across all 18 regions, significant evidence of an association was found between overall genetic variation and risk of all ovarian cancers combined (P¼ .002), as well as risk of the high-grade serous and clear cell histotypes (P¼ .002 and P¼ .039, respectively). Odds ratios and 95% confidence intervals (CIs) for the most significant SNPs associated with ovarian cancer are presented in Table 3. Region A contained the most significant SNP, rs10917151 (OR 1.11, P¼4.0
107), but regions L, P, and R also had SNPs of notable significance (P¼3.3
104 for rs73007780, P¼2.5
104 for rs1333052, P¼1.2
105 for rs7397212, respectively). Supplemental Tables 2 VOL. - NO. - / - 2015

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TABLE 2 Burden statistics for the association between the 18 genomic regions, harboring SNPs associated with endometriosis, and risk of ovarian cancer by histotype. Burden statisticsc Region

Chr.

A 1p36 B 1p31 C 2p25 D 2p14 E 3p24 F 3p24 G 3p14 H 3q13 I 4q12 J 6p22 K 6q21 L 6q25 M 6q25 N 7p15 O 7q33 P 9p21 Q 10q26 R 12q22 Global –

Region coordinatesa 22347396–22531542 80152740–80338250 11661140–11712075 67983706–68019054 24940850–25060867 25035804–25075645 55181646–55221542 104584856–104828081 55988082–56027573 19567942–19632693 112966971–113226112 152544371–152677815 158184000–158192932 25888067–25897388 134455276–134936517 22140648–22201586 117345263–117407423 95304634–95709315 –

Region No. of SNPs size (kb) Coverage in regionb 184.146 185.510 50.935 35.348 120.017 39.841 39.896 243.225 39.491 64.751 259.141 133.444 8.932 9.321 481.241 60.938 62.160 404.681 –

0.99 0.99 0.98 0.97 0.96 0.96 0.94 0.99 0.96 0.97 0.97 1.00 0.94 0.95 0.98 0.96 0.99 0.98 –

Overall

High-grade serous

5.0
105* 1.0
104* .71 .057 .041* .70 .044* .21 .67 .85 .15 .32 .30 .32 .84 .95 .011* .010* .61 .54 .15 .63 .26 .39 .23 .50 .16 .38 .54 .96 .002* .026* .82 .56 .011* .025* .002* .002*

594 607 107 77 390 168 113 846 135 194 550 370 19 15 1,082 184 204 1,309 –

Mucinous Endometrioid Clear cell .78 .26 .11 .16 .28 .17 .79 .86 .23 .20 .19 .75 .075 .79 .70 .63 .13 .53 .61

.35 .93 .23 .43 .57 .036* .54 .34 .19 .23 .67 .26 .48 .22 .12 .17 .70 .15 .20

.007* .015* .014* .54 .65 .28 .68 .48 .018* .29 .82 .070 .61 .12 .94 .14 .27 .28 .039*

Note: ‘‘Global’’ refers to when all SNPs across all regions are considered. Chr. ¼ chromosome. a Defined as including all SNPs with an r2 R 0.2 with the most significant ovarian cancer-associated SNP (when considering the areas 25 kb up- and downstream of the index SNP as presented in Table 1). b Based on r2 R 0.5 and MAF R 0.05. c Took into account the first five ancestry principal components; P values for trend reported. * Significant P values at P%.05. Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

and 3 present the most significant SNPs for each region by histotype (high-grade serous and mucinous in Supplemental Table 2; endometrioid and clear cell in Supplemental Table 3). Similar to the results for ovarian cancer overall,

region A for high-grade serous cancer contained the most significant SNP, rs3754496 (P¼5.3
108), whereas region R for high-grade serous cancer harbored the largest number of significant SNPs (n ¼ 327) when looking across the four

TABLE 3 Odds ratios and 95% CIs for the most significant SNP in each of the 18 genomic regions for ovarian cancer overall. Region

No. of significant SNPs

Most significant SNP

ORa

95% CI

P value

192 2 53 14 5 22 10 6 87 1 59 24 2 1 0 68 2 256

rs10917151 rs28556754 rs142034631 rs17034382 rs62228500 rs1846555 rs17054879 rs114063826 rs12331507b rs9717730 rs4437516 rs73007780 rs7742463 rs73093677 N/A rs1333052 rs2804241 rs7397212

1.11 0.96 1.05 0.94 0.94 1.04 0.94 1.08 0.95 1.07 1.04 0.88 0.94 0.93 – 1.06 1.05 1.13

1.07–1.15 0.93–0.99 1.01–1.10 0.91–0.98 0.89–1.00 1.01–1.08 0.90–0.98 1.02–1.14 0.92–0.98 1.02–1.13 1.01–1.07 0.83–0.95 0.90–0.98 0.88–0.99 – 1.03–1.09 1.00–1.11 1.07–1.20

4.0
107 .017 .004 .004 .033 .015 .005 .007 1.0
103 .012 .018 3.3
104 .002 .023 – 2.5
104 .041 1.2
105

A B C D E F G H I J K L M N O P Q R

Note: ‘‘Significant’’ reflects a P%.05. N/A means there are no significant SNPs in that region. a OR ¼ per-allele odds ratio, adjusted for the first five principal components; based on study set-specific ORs that were meta-analyzed. b SNP was genotyped. Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

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print & web 4C=FPO

FIGURE 1

Manhattan and linkage disequilibrium plots for region P. These plots depict the results for all 184 SNPs in region P (chromosome 9p21, position 22140648–22201586). The Manhattan plot includes ovarian cancer overall (‘‘invasive’’) and its four histotypes, with the x axis corresponding to the chromosomal position (in Mb), the y axis to the -log P, and the line to P¼5.0
108. Rs1333052, the most significant SNP in the region (P¼2.5
104 for ovarian cancer overall), is indicated. The linkage disequilibrium plot depicts pairwise correlation data from the 1000 Genomes CEU (Utah residents [CEPH] with Northern and Western European Ancestry) population. Epigenomic data from the ENCODE and Roadmap Epigenomics Consortia were obtained and visualized in the University of California, Santa Cruz Genome Browser. Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

histotypes. Other SNPs of notable significance were found in region R for high-grade serous cancer (rs6538605, P¼1.2
104) and endometrioid cancer (rs11107893, P¼4.3
104) as well as in regions A (rs4654785, P¼1.3
104) and L (rs71575922, P¼1.4
104) for clear cell cancer. Figure 1 presents the Manhattan and linkage disequilibrium plots for region P, the region showing the most significant burden statistic across all 18 regions, excluding region A (P¼ .002 for ovarian cancer overall). A clear elevation of P values is present, especially when looking at ovarian cancer overall, with the most significant SNP rs1333052 (P¼2.5
104) indicated. In addition, Supplemental Figure 1 presents the Manhattan plots for the remaining regions with significant burden statistics, whereas Supplemental Figure 2 presents these plots for the regions that did not have significant burden statistics. With the exception of region L showing some elevation of P values for clear cell cancer, reasonable given its borderline significant burden statistic (P¼ .07), all plots in Supplemental Figure 2 look relatively flat.

DISCUSSION We took a novel approach toward evaluating endometriosisassociated SNPs with ovarian cancer risk and found appreciable support for a shared genetic etiology between these two gynecologic conditions. Across the 18 regions harboring

putative endometriosis SNPs, we calculated a total of 15 significant burden statistics for ovarian cancer risk, compared with approximately 5 expected by chance at the P%.05 level (i.e., 18 regions
5 types of ovarian cancer (overall, highgrade serous, mucinous, endometrioid, clear cell) ¼ 90 total), a conservative estimate owing to the strong correlation between overall and high-grade serous. Endometriosis and ovarian cancer were first linked because of their frequent co-occurrence in surgical specimens. Most recently a pooled analysis of 13 case–control studies by Pearce et al. (3) showed that after adjusting for oral contraceptive use and parity, women with a history of endometriosis were 46% more likely to develop ovarian cancer, with the association primarily restricted to the endometrioid and clear cell histotypes. Endometriosis may be a precursor lesion for endometrioid and clear cell ovarian cancer, but the process of its malignant transformation is not well understood (26, 27). The two gynecologic conditions are likely to have a shared pathophysiology, given evidence from pathology case series reporting endometrioid and clear cell ovarian cancers arising from endometriotic foci as well as epidemiologic studies that highlight their similar hormonerelated risk factors, such as nulliparity (27). In addition, both traits seem to thrive in similar hormonal and immune environments, highlighting a possible shared inflammatory etiology. VOL. - NO. - / - 2015

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Fertility and Sterility® Some of these results are contrary to what we expected. Consistent with our hypothesis, we calculated a significant global burden statistic for clear cell ovarian cancer when considering all endometriosis SNPs together. However, we did not see this association for the endometrioid histotype despite its well-established association with endometriosis. In addition, we observed a link with the high-grade serous histotype, which previous epidemiologic studies have not found to be associated with endometriosis; we did not observe any associations with the low-grade serous histotype (data not shown owing to small numbers). Our findings suggest that although endometriosis is not a precursor lesion for high-grade serous ovarian cancer, the genetic pathways related to risk of these two diseases are shared. This finding paves the way for interesting lines of inquiry related to shared pathways. Perhaps women with endometriosis are more likely to have endosalpingiosis, which is common but infrequently noted in pathology reports, and which may predispose to high-grade serous ovarian cancer. Our ovarian cancer susceptibility GWASs have identified thousands of nominally significant associations, but most are due to chance. Deciphering the noise from true signals is difficult despite our large sample size. In this analysis we took a novel, two-pronged approach, first selecting candidate regions from a phenotype linked to ovarian cancer and then assessing whether the burden of associations in these regions was significant. The burden statistics implicate some of these regions in risk of ovarian cancer, although the exact relevance of the regions remains unknown. Region A includes the most significantly associated SNP among all 6,981 considered, rs3754496 (P¼5.4
108 for high-grade serous), an imputed SNP located near WNT4, a gene involved in steroidogenesis and in the development of the ovarian follicle and the female reproductive tract, biological functions that make its role in the development of both endometriosis and ovarian cancer compelling (28). Our data from OCAC for region A have previously been combined with those of CIMBA, and a genome-wide significant association was observed (16). In addition, Table 1 shows that an association with the remaining regions may exist even after excluding region A (P¼ .052). Only 3 of the 15 significant burden statistics presented in Table 2 are found in region A, with the other 12 spanning seven other regions. Region P had the most significant burden statistic (P¼ .001 for ovarian cancer overall), with rs1333052 as its most significant SNP (P¼2.5
104). This SNP is located adjacent to CDKN2B, a tumor suppressor gene whose methylation has been commonly seen in ovarian carcinogenesis (29). In addition, rs1333052 lies within a binding site for GATA2, one of six factors that constitute the GATA family of transcriptional regulatory proteins, which has been shown to play a role in ovarian function; it was identified by genome-wide ChIP sequencing (30). Rs12331507 in region I, which, other than region A, had the greatest number of significant burden statistics, lies in an intergenic region approximately 20 kb upstream of KDR, a gene that encodes one of the two receptors for

vascular endothelial growth factor (VEGF); VEGF has been shown to be expressed by tumor cells in ovarian cancer (31). Interestingly, the most significant SNP in region C, rs142034631, is located in GREB1, an estrogen-responsive gene that modulates tumor progression in models of ovarian cancer (32). Although the specific relevance of these genes and regions as well as the functional significance of their most significantly associated SNPs cannot be determined at this time, these results suggest that additional real associations exist between ovarian cancer risk and variation in the endometriosis-related regions. More importantly, they highlight the presence of a genetic commonality that high-grade serous and clear cell ovarian cancers and endometriosis are likely to share. In conclusion, we have shown significant evidence of a genetic link between endometriosis and ovarian cancer that warrants further follow-up. Whether the association between these two gynecologic conditions is causal remains unknown. However, fine mapping studies of the regions we have identified will greatly contribute to our knowledge regarding the etiologies of both diseases, as well as shed some light on their likely shared pathophysiology. The clinical implications of these results remain to be established, but next steps would include fine mapping of the regions with significant burden statistics (regions A, B, C, D, F, I, P, and R) and functional analyses of the most likely causal SNP(s). Acknowledgments: Ovarian Cancer Association Consortium: Roberta B. Ness, Agnieszka DansonkaMieszkowska, Aleksandra Gentry-Maharaj, Alexander Hein, Alice S. Whittemore, Allan Jensen, Andreas du Bois, Angela Brooks-Wilson, Anja Rudolph, Anna Jakubowska, Anna H. Wu, Argyrios Ziogas, Arif B. Ekici, Arto Leminen, Australian Cancer Study (Ovarian Cancer), Australian Ovarian Cancer Study Group, Barry Rosen, Beata Spiewankiewicz, Beth Y. Karlan, Britton Trabert, Brooke L. Fridley, C. Blake Gilks, Camilla Krakstad, Catherine M. Phelan, Cezary Cybulski, Christine Walsh, Claus Hogdall, Daniel W. Cramer, David G. Huntsman, Diana Eccles, Diether Lambrechts, Dong Liang, Douglas A. Levine, Edwin S. Iversen, Elisa V. Bandera, Elizabeth M. Poole, Ellen L. Goode, Els Van Nieuwenhuysen, Estrid Hogdall, Fiona Bruinsma, Florian Heitz, Francesmary Modugno, Graham G. Giles, Harvey A. Risch, Helen Baker, Helga B. Salvesen, Heli Nevanlinna, Hoda Anton-Culver, Honglin Song, Iain McNeish, Ian G. Campbell, Ignace Vergote, Ingo B. Runnebaum, Ingvild L. Tangen, Ira Schwaab, Jacek Gronwald, James Paul, Jan Lubinski, Jennifer A. Doherty, Jenny Chang-Claude, Jenny Lester, Joellen M. Schildkraut, John R. McLaughlin, Jolanta Lissowska, Jolanta Kupryjanczyk, Jonathan Tyrer, Joseph L. Kelley, Joseph H. Rothstein, Julie M. Cunningham, Karen Lu, Karen Carty, Kathryn L. Terry, Katja K.H. Aben, Kirsten B. Moysich, Kristine G. Wicklund, Kunle Odunsi, Lambertus A. Kiemeney, Lara Sucheston-Campbell, Lene Lundvall, Leon F.A.G. Massuger, Liisa M. Pelttari, Linda E. Kelemen, Linda S. Cook, Line Bjorge, Lotte Nedergaard, Louise A. Brinton, Lynne R. Wilkens, Malcolm C. Pike, Marc T. Goodman, Maria Bisogna, Mary Anne Rossing, Matthias

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ORIGINAL ARTICLE: GENETICS W. Beckmann, Matthias D€ urst, Melissa C. Southey, Melissa Kellar, Michelle A.T. Hildebrandt, Nadeem Siddiqui, Natalia Antonenkova, Natalia Bogdanova, Nhu D. Le, Nicolas Wentzensen, Pamela J. Thompson, Patricia Harrington, Penelope M. Webb, Peter A. Fasching, Peter Hillemanns, Philipp Harter, Piotr Sobiczewski, Rachel Palmieri Weber, Ralf Butzow, Robert P. Edwards, Robert A. Vierkant, Rosalind Glasspool, Sandra Orsulic, Sandrina Lambrechts, Sara H. Olson, Shan Wang-Gohrke, Shashi Lele, Shelley S. Tworoger, Simon A. Gayther, Stacey A. Missmer, Steven A. Narod, Susan J. Ramus, Susanne K. Kjaer, Tanja Pejovic, Thilo D€ ork, Ursula Eilber, Usha Menon, Valerie McGuire, Weiva Sieh, Xifeng Wu, Yukie Bean, Yurii B Shvetsov. The authors thank all the individuals who took part in this study and all the researchers, clinicians, and technical and administrative staff who have made possible the many studies contributing to this work. In particular, the authors thank D. Bowtell, A. deFazio, D. Gertig, A. Green, P. Parsons, N. Hayward, and D. Whiteman (AUS) (see Supplemental Table 1 for site abbreviations); G. Peuteman, T. Van Brussel, and D. Smeets (BEL); the staff of the genotyping unit, S. LaBoissiere and F. Robidoux (Genome Quebec); L. Gacucova (HMO); P. Schurmann, F. Kramer, W. Zheng, T. W. Park, Simon, K. Beer-Grondke, and D. Schmidt (HJO); S. Windebank, C. Hilker, and J. Vollenweider (MAY); the state cancer registries of AL, AZ, AR, CA, CO, CT, DE, FL, GA, HI, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WYL (NHS); L. Paddock, M. King, L. Rodriguez-Rodriguez, A. Samoila, and Y. Bensman (NJO); M. Sherman, A. Hutchinson, N. SzeszeniaDabrowska, B. Peplonska, W. Zatonski, A. Soni, P. Chao, and M. Stagner (POL); C. Luccarini, P. Harrington the SEARCH team and ECRIC (SEA); I. Jacobs, M. Widschwendter, E. Wozniak, N. Balogun, A. Ryan, C. Karpinskyj, and J. Ford (UKO); Carole Pye (UKR); A. Amin Al Olama, J. Dennis, E. Dicks, K. Michilaidou, K. Kuchenbaker (COGS); and G. Montgomery.

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Adachi S, Tajima A, Quan J, Haino K, Yoshihara K, Masuzaki H, et al. Metaanalysis of genome-wide association scans for genetic susceptibility to endometriosis in Japanese population. J Hum Genet 2010;55:816–21. 9. Bojesen SE, Pooley KA, Johnatty SE, Beesley J, Michailidou K, Tyrer JP, et al. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer. Nat Genet 2013;45: 371–84. 384e1–2. 10. Bolton KL, Ganda C, Berchuck A, Pharaoh PD, Gayther SA. Role of common genetic variants in ovarian cancer susceptibility and outcome: progress to date from the Ovarian Cancer Association Consortium (OCAC). J Intern Med 2012;271:366–78. 11. Kuchenbaecker KB, Ramus SJ, Tyrer J, Lee A, Shen HC, Beesley J, et al. Identification of six new susceptibility loci for invasive epithelial ovarian cancer. Nat Genet 2015;47:164–71. 12. Nyholt DR, Low SK, Anderson CA, Painter JN, Uno S, Morris AP, et al. Genome-wide association meta-analysis identifies new endometriosis risk loci. Nat Genet 2012;44:1355–9. 13. Pearce CL, Rossing MA, Lee AW, Ness RB, Webb PM, for Australian Cancer Study (Ovarian Cancer), et al. Combined and interactive effects of environmental and GWAS-identified risk factors in ovarian cancer. Cancer Epidemiol Biomarkers Prev 2013;22:880–90. 14. Song H, Ramus SJ, Tyrer J, Bolton KL, Gentry-Maharaj A, Wozniak E, et al. A genome-wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2. Nat Genet 2009;41:996–1000. 15. Goode EL, Chenevix-Trench G, Song H, Ramus SJ, Notaridou M, Lawrenson K, et al. A genome-wide association study identifies susceptibility loci for ovarian cancer at 2q31 and 8q24. Nat Genet 2010;42:874–9. 16. Bolton KL, Tyrer J, Song H, Ramus SJ, Notaridou M, Jones C, et al. Common variants at 19p13 are associated with susceptibility to ovarian cancer. Nat Genet 2010;42:880–4. 17. Permuth-Wey J, Lawrenson K, Shen HC, Velkova A, Tyrer JP, Chen Z, et al. Identification and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31. Nat Commun 2013;4:1627. 18. Pharoah PD, Tsai YY, Ramus SJ, Phelan CM, Goode EL, Lawrenson K, et al. GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer. Nat Genet 2013;45:362–70. 370e1–2. 19. Shen H, Fridley BL, Song H, Lawrenson K, Cunningham JM, Ramus SJ, et al. Epigenetic analysis leads to identification of HNF1B as a subtype-specific susceptibility gene for ovarian cancer. Nat Commun 2013;4:1628. 20. Lee SH, Harold D, Nyholt DR, ANZGene Consortium, International Endogene Consortium, Genetic and Environmental Risk for Alzheimer's Disease Consortium, et al. Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis. Hum Mol Genet 2013;22:832–41. 21. Permuth-Wey J, Kim D, Tsai YY, Lin HY, Chen YA, Barnholtz-Sloan J, et al. LIN28B polymorphisms influence susceptibility to epithelial ovarian cancer. Cancer Res 2011;71:3896–903. 22. Howie B, Marchini J, Stephens M. Genotype imputation with thousands of genomes. G3 (Bethesda) 2011;1:457–70. 23. Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet 2012;44:955–9. 24. Sankararaman S, Sridhar S, Kimmel G, Halperin E. Estimating local ancestry in admixed populations. Am J Hum Genet 2008;82:290–303. 25. Tyrer J, Pharoah PD, Easton DF. The admixture maximum likelihood test: a novel experiment-wise test of association between disease and multiple SNPs. Genet Epidemiol 2006;30:636–43. 26. Nezhat F, Datta MS, Hanson V, Pejovic T, Nezhat C, Nezhat C. The relationship of endometriosis and ovarian malignancy: a review. Fertil Steril 2008; 90:1559–70. 27. Ness RB. Endometriosis and ovarian cancer: thoughts on shared pathophysiology. Am J Obstet Gynecol 2003;189:280–94. 28. Franco HL, Dai D, Lee KY, Rubel CA, Roop D, Boerboom D, et al. WNT4 is a key regulator of normal postnatal uterine development and progesterone signaling during embryo implantation and decidualization in the mouse. FASEB J 2011;25:1176–87.

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Ozdemir F, Altinisik J, Karateke A, Coksuer H, Buyru N. Methylation of tumor suppressor genes in ovarian cancer. Exp Ther Med 2012;4: 1092–6. Viger RS, Guittot SM, Anttonen M, Wilson DB, Heikinheimo M. Role of the GATA family of transcription factors in endocrine development, function, and disease. Mol Endocrinol 2008;22:781–98.

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ORIGINAL ARTICLE: GENETICS

SUPPLEMENTAL FIGURE 1

(A–F) Manhattan plots for the regions that resulted in a significant burden statistic at the P%.05 level. These plots include all SNPs in each region for ovarian cancer overall (‘‘invasive’’) and its four histotypes, with the x axis corresponding to the chromosomal position (in Mb), the y axis to the -log P, and the line to P¼5.0
108. Region A, which is presented in a previous publication (16), and region P, which is shown in the article, are not included. Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

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SUPPLEMENTAL FIGURE 1 Continued

Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

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SUPPLEMENTAL FIGURE 2

(A–J) Manhattan plots for the regions that did not result in a significant burden statistic at the P%.05 level. These plots include all SNPs in each region for ovarian cancer overall (‘‘invasive’’) and its four histotypes, with the x axis corresponding to the chromosomal position (in Mb), the y axis to the -log P, and the line to P¼5.0
108. Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

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SUPPLEMENTAL FIGURE 2 Continued

Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

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SUPPLEMENTAL FIGURE 2 Continued

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SUPPLEMENTAL TABLE 1 Description of OCAC study sites included in analyses. Study set abbreviation AUS

BAV FLA 5.4.0 DTD
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BEL BWH1 DAN DOV

GER HAW HJO HMO HOC HPE

LA2

MSK

Site abbreviation

Australian Ovarian Cancer Study/Australian Cancer Study (Ovarian Cancer) Melbourne Collaborative Cohort Study Bavarian Ovarian Cancer Cases and Controls Belgian Ovarian Cancer Study New England Case–Control Study Danish Malignant Ovarian Tumor Study Danish Pelvic Mass Study Diseases of the Ovary and their Evaluation Oregon Ovarian Cancer Registry German Ovarian Cancer Study Dr. Horst Schmidt Kliniken Hawaii Ovarian Cancer Case–Control Study Hannover-Jena Ovarian Cancer Study Hannover-Minsk Ovarian Cancer Study Helsinki Ovarian Cancer Study Gilda Radner Familial Ovarian Cancer Registry Hormones and Ovarian Cancer Prediction

AUS

Australia

Population-based/case– control

977

880

498

42

106

52

MCC

Melbourne, Australia

66

66

19

7

7

6

BAV

Southeast Germany

143

96

42

8

13

6

BEL

Belgium

1,349

276

183

23

22

23

NEC

142

104

103

0

0

0

MAL

USA: NH and Eastern MA Denmark

828

440

183

42

54

33

PVD DOV

Denmark USA: Western WA

0 1,487

169 904

119 435

10 26

14 148

8 65

ORE

USA: Portland, OR

Cohort/Nested case– control Population-based/case– control Hospital-based/case– control Population-based/case– control Population-based/case– control Case-only Population-based/case– control Case-only

0

55

37

2

5

2

GER

Southern Germany

413

189

68

21

21

6

HSK HAW

0 157

147 60

103 36

1 3

16 12

0 5

HJO

Germany USA: HI and Southern CA Germany

273

261

107

9

26

4

HMO

Belarus

Population-based/case– control Case-only Population-based/case– control Hospital-based/case– control Case-control

138

142

1

7

12

1

HOC

Helsinki, Finland

Case-control

447

210

0

39

26

11

GRR

USA

Familial cancer/case-only

0

134

0

5

18

11

HOP

USA: Western PA, Northeastern OH, Western NY USA: Southern CA

Population-based/case– control

1,464

568

275

29

83

42

Case-only

0

277

201

12

18

9

USC

USA: Southern CA (Los Angeles County)

Population-based/case– control

1,047

693

341

44

79

35

MDA

USA: TX

384

375

135

27

28

4

MSK

USA: NY

Hospital-based/case– control Case–control

593

467

343

0

20

18

Women's Cancer Research Institute - Cedars-Sinai Medical Center Los Angeles County Case– Control Studies of Ovarian Cancer MD Anderson Ovarian Cancer Study Memorial Sloan Kettering Cancer Center Gynecology Tissue Bank

9.e6

Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

LAX

Location

Site type

Controls Cases

Fertility and Sterility®

MDA

High-grade Clear serous Mucinous Endometrioid cell

Site namea

Continued. Study set abbreviation MYO1 NCO NEC NHS FLA 5.4.0 DTD
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NOR NTH OVA PLD

POL1 SEA

STA

UCI

Site namea

Site abbreviation

Mayo Clinic Ovarian Cancer Case–Control Study North Carolina Ovarian Cancer Study New England Case–Control Study Nurses' Health Study

MAY

NHS

USA: NH and Eastern MA USA

University of Bergen Norway Study Nijmegen Polygene Study & Nijmegen Biomedical Study Ovarian Cancer in Alberta and British Columbia Study Poland Ovarian Cancer Study

NOR

NCI Ovarian Case–Control Study in Poland Warsaw Ovarian Cancer Study NCI Ovarian Case–Control Study in Poland UK Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH) Ovarian Cancer Study Familial Registry for Ovarian Cancer and Genetic Epidemiology of Ovarian Cancer UC Irvine Ovarian Cancer Study

Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

Location

Controls Cases

High-grade Clear serous Mucinous Endometrioid cell

Clinic-based/case–control

441

443

343

11

34

20

172

266

133

16

35

24

980

618

331

41

140

33

455

138

0

7

14

6

Norway

Population-based/case– control Population-based/case– control Population-based/nested case–control Case-control

371

237

85

15

27

11

NTH

Eastern Netherlands

Case-control

323

295

64

33

64

20

OVA

Canada: Alberta and British Columbia

Case-control

748

640

0

26

103

57

POC

Poland: Szczecin, Poznan, Opole, Rzeszow Poland: Warsaw, Lodz

Case-control

417

422

0

33

39

9

Population-based/case– control Case-control

186

42

15

4

10

2

204

202

131

8

20

17

Population-based/case– control Population-based/case– control

555

212

57

13

28

9

6023

316

108

43

29

28

NCO NEC

POL WOC POL

USA: MN, SD, ND, IL, IA, WI USA: NC

Site type

Poland: Warsaw, Central Poland Poland, Warsaw, Lodz

SEA

UK: East Anglia and West Midlands

STA

USA: San Francisco Bay

Population-based/case– control

313

251

135

16

32

20

UCI

USA: Southern CA (Orange, San Diego, Imperial Counties)

Population-based/case– control

367

277

143

19

48

23

ORIGINAL ARTICLE: GENETICS

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SUPPLEMENTAL TABLE 1 Continued. Study set abbreviation UK

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UK2

US

USN

b

Site abbreviation

Royal Marsden Hospital Case Series UK Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH) Ovarian Cancer Study UK Ovarian Cancer Population Study UK Familial Ovarian Cancer Registry Welcome Trust Case– Control Consortium Royal Marsden Hospital Case Series Southampton Ovarian Cancer Study Scottish Randomised Trial in Ovarian Cancer UK Ovarian Cancer Population Study UK Familial Ovarian Cancer Registry Mayo Clinic Hospital

RMH

UK: London

Hospital-based/case-only

0

138

0

15

26

16

SEA

UK: East Anglia, West Midlands

Population-based/case– control

1

1,130

346

111

205

127

UKO

Population-based/case– control Case-only/familial register

1

494

186

53

82

42

UKR

UK: England, Wales, Northern Ireland UK: National

0

44

0

3

6

2

WTC

UK

6,116

0

0

0

0

0

RMH

UK: London

Blood donors, 1958 Birth Cohort Controls Hospital-based/case-only

0

10

0

1

1

1

SOC

UK: Wessex

Hospital-based/case-only

0

274

72

33

62

11

SRO

UK: Glasgow, patients recruited worldwide UK: England, Wales, Northern Ireland UK: National

Case-only from clinical trial

0

158

87

3

17

8

Population-based/case– control Case-only/familial register

1,103

238

93

24

32

25

0

3

0

0

0

0

Clinic-based/case–control

519

358

233

11

71

25

Population-based/case– control Population-based/case– control Population-based/case– control Clinic-based/case–control

654

487

249

18

78

56

169

227

129

13

28

12

524

729

0

56

154

46

10

10

9

0

1

0

Case-control

181

169

80

7

27

20

74

20

0

1

7

2

North Carolina Ovarian Cancer Study Tampa Bay Ovarian Cancer Study Toronto Ovarian Cancer Study Mayo Clinic Ovarian Cancer Case–Control Study New Jersey Ovarian Cancer Study Toronto Ovarian Cancer Study

UKO UKR MAY

Location

NCO

USA: MN, SD, ND, IL, IA, WI USA: NC

TBO

USA: FL

TOR

Canada: Ontario

MAY NJO

USA: MN, SD, ND, IL, IA, WI USA: NJ

TOR

Canada: Ontario

Some sites appear in more than one study set owing to differences in genotyping platform within each site. Sum of numbers do not equal total number of cases because some cases were not classified as one of the four histotypes.

Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

Site type

Population-based/case– control Total

Controls Cases

30,815 15,361

b

6,258

991

b

b

2,148

1,013b

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a

High-grade Clear serous Mucinous Endometrioid cell

Site namea

ORIGINAL ARTICLE: GENETICS

SUPPLEMENTAL TABLE 2 Odds ratios and 95% CIs for the most significant SNP in each of the 18 genomic regions for high-grade serous and mucinous ovarian cancers. High-grade serous (n [ 6,258) No. of significant Region SNPs A B C D E F G H I J K L M N O P Q R

221 50 0 0 0 3 6 1 101 0 1 13 0 0 1 52 0 327

Most significant SNP rs3754496 rs1524169 N/A N/A N/A rs1846555 rs73063613 chr3:104626317:I rs1547512 N/A chr6:113076251:D chr6:152616764:D N/A N/A rs13311403 rs10965263 N/A rs6538605

ORa 1.16 1.05 – – – 1.05 1.07 1.08 1.06 – 1.08 0.87 – – 1.07 1.07 – 0.92

95% CI

Mucinous (n [ 991)

P value 8

1.10–1.23 5.6
10 1.01–1.10 9.7
103 – – – – – – 1.00–1.10 .031 1.01–1.13 .015 1.01–1.15 .031 1.02–1.10 .006 – – 1.00–1.15 .037 0.80–0.96 .003 – – – – 1.01–1.14 .024 1.02–1.12 .005 – – 0.88–0.96 1.2
104

No. of significant SNPs

Most s ignificant SNP

ORb

4 2 27 3 14 23 0 5 2 1 23 6 3 0 15 1 35 14

rs2501276 chr1:80243322:I rs142034631 rs71413109 rs12487626 rs4858684 N/A rs116203658 rs62304730 chr6:19617536:I rs7751257 rs12206761 rs7742463 N/A rs6954307 rs1930591c rs2769419 rs7397485

0.80 0.90 1.15 0.74 0.89 0.85 – 0.76 1.14 1.11 1.21 1.18 0.81 – 0.79 0.91 1.13 0.86

95% CI

P value

0.67–0.95 .012 0.82–0.99 .028 1.02–1.29 .020 0.60–0.91 .005 0.80–0.98 .024 0.76–0.94 .003 – – 0.60–0.97 .028 1.02–1.28 .024 1.01–1.22 .034 1.08–1.34 5.8
104 1.04–1.34 .013 0.72–0.92 7.1
104 – – 0.67–0.93 .005 0.83–1.00 .040 1.03–1.24 .009 0.78–0.96 .006

Note: ‘‘Significant’’ reflects a P%.05. N/A means there are no significant SNPs in that region. a OR ¼ Per-allele odds ratio, adjusted for the first five principal components; based on study set–specific ORs that were meta-analyzed. b OR ¼ Per-allele odds ratio, adjusted for the first five principal components and study set. c SNP was genotyped. Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

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Fertility and Sterility®

SUPPLEMENTAL TABLE 3 Odds ratios and 95% CIs for the most significant SNP in each of the 18 genomic regions for endometrioid and clear cell ovarian cancers. Endometrioid (n [ 2,148)

Region A B C D E F G H I J K L M N O P Q R

No. of significant SNPs

Most significant SNP

ORa

95% CI

49 0 47 3 13 53 1 4 9 1 5 18 0 1 72 6 0 106

rs12024016 N/A rs1898003 rs17034338 rs7639387 rs1603996 rs17054879 rs75281964 rs2412627 rs10434838 rs34384052 rs9479288 N/A rs73093677 rs12530891b rs6475610b N/A rs11107893

1.17 – 1.09 0.86 0.87 1.15 0.91 1.14 0.86 1.08 1.14 0.82 – 0.84 1.10 1.09 – 1.18

1.02–1.33 – 1.01–1.17 0.75–0.99 0.77–0.99 1.06–1.24 0.84–1.00 1.01–1.28 0.79–0.94 1.01–1.16 1.03–1.25 0.72–0.94 – 0.73–0.95 1.03–1.18 1.02–1.16 – 1.08–1.30

Clear cell (n [ 1,013)

P value

No. of significant SNPs

Most significant SNP

ORa

95% CI

P value

.023 – .020 .038 .030 .001 .050 .033 .001 .029 .009 .004 – .008 .006 .008 – 4.3
104

176 210 51 0 0 3 1 25 52 40 1 57 0 2 5 27 0 93

rs4654785 chr1:80301656:D rs10929757 N/A N/A rs62228504 rs6767715 rs77484561 rs12331507b rs2743617 rs72942081 rs71575922 N/A rs73093677 rs3800729b rs10965256b N/A chr12:95380417:D

1.22 0.87 1.18 – – 0.83 1.13 1.22 0.85 1.24 1.26 1.25 – 0.80 0.87 0.73 – 0.86

1.10–1.35 0.79–0.95 1.07–1.31 – – 0.70–0.99 1.02–1.26 1.04–1.43 0.77–0.93 1.04–1.49 1.03–1.55 1.12–1.41 – 0.66–0.97 0.77–0.98 0.60–0.89 – 0.78–0.96

1.3
104 .003 .001 – – .033 .020 .013 8.3
104 .017 .028 1.4
104 – .023 .021 .002 – .005

Note: ‘‘Significant’’ reflects a P%.05. N/A means there are no significant SNPs in that region. a OR ¼ Per-allele odds ratio, adjusted for the first five principal components and study set. b SNP was genotyped. Lee. Endometriosis SNPs and ovarian cancer. Fertil Steril 2015.

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FLA 5.4.0 DTD
FNS29891_proof
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9:02 am
ce JS