{"paper_id":"6e353e69-99aa-4afc-a5b7-ef0fad2d4123","body_text":"The Open Reproductive Science Journal,  2008, 1, 35-40 35  \n \n 1874-2556/08 2008 Bentham Open \nOpen Access \nCommon Variation in the CYP17A1 and IFIT1 Genes on Chromosome 10 \nDoes Not Contribute to the Risk of Endometriosis \nZhen Zhen Zhao*,1, Dale R. Nyholt2, Lien Le1, Susan A. Treloar1 and Grant W. Montgomery1 \n1Molecular Epidemiology and 2Genetic Epidemiology  Laboratories, Queensland Ins titute of Medical Research, Bris-\nbane, Queensland, Australia \nAbstract: Endometriosis is a complex disease involving multiple susceptibility genes and environmental factors. Our pre-\nvious studies on endometriosis identified a region of significant linkage on chromosome 10q. Two biological candidate \ngenes (CYP17A1 and IFIT1) located on chromosome 10q, have previously been implicated in endometriosis and/or uter-\nine function. We hypothesized that variation in CYP17A1 and/or IFIT1 could contribute to the risk of endometriosis and \nmay account for some of the linkage signal on chromosome 10q. We genotyped 17 single nucleotide polymorphisms \n(SNPs) in the CYP17A1 and IFIT1 genes including SNP rs743572 previously associated with endometriosis in 768 endo-\nmetriosis cases and 768 unrelated controls. We found no evidence for association between endometriosis and individual \nSNPs or SNP haplotypes  in CYP17A1  and IFIT1. Common variation in these genes does not appear to be a major con-\ntributor to endometriosis susceptibility in our Australian sample. \nINTRODUCTION \n Endometriosis is a complex disease involving multiple \nsusceptibility genes and environmental factors [1-4]. Esti-\nmates of the population prevalence indicate that endometri-\nosis affects 8–10% of women of reproductive age [2, 5], but \nthe reasons for establishment and progression of endometri-\nosis remain uncertain. \n Our previous studies on endometriosis identified a region \nof significant linkage on chromosome 10q26 [6]. The peak \nlinkage signal is located at 148.75 cM between markers \nD10S587 and D10S1656 and the 95% confidence interval \n(CI) spans a region of 8.5 megabase pairs (Mbp). Gene map-\nping of plausible candidates may help to define the mecha-\nnisms contributing to the genetic susceptibility of endome-\ntriosis. Two candidate genes on chromosome 10q, which \nhave previously been implicated in endometriosis and uter-\nine function, are cytochrome P450,  family 17, subfamily A, \npolypeptide 1 ( CYP17A1, MIM #609300) and interferon-\ninduced protein with tetratricopeptide repeats 1 ( IFIT1, MIM \n#147690) [7-9]. \n Human endometrium is highly responsive to hormonal \nstimuli during the menstrual cycle with estrogen and proges-\nterone influencing maturational and functional changes in \nthe endometrium. The CYP17A1 gene lies at 104.5 Mbp, on \nthe shoulder of our linkage peak on chromosome 10 and en-\ncodes the cytochrome P450c17 \u0001 enzyme that is involved in \nestrogen biosynthesis and metabolism [10]. The gene is ex-\npressed in human follicles, corpora lutea and endometrial \ncarcinoma cells [11-13]. A number of studies on CYP17A1 \nvariation suggest it could be a genetic biomarker for hor-\nmone related diseases [7, 14, 15]. One single nucleotide \npolymorphism (SNP, rs743572) at the -34 bp position rela-\ntive to the start codon in the 5’UTR promoter region of  \n \n \n*Address correspondence to this author at the Queensland Institute of Medi-\ncal, Research, Brisbane, Queensland 4029, Australia;  \nE-mail: Zhen.Zhao@qimr.edu.au \nCYP17A1 has been commonly studied. The SNP was \nthought to be associated with a Sp-1 binding site that would \nlead to higher gene expression in male baldness [16]. In pa-\ntients with endometrial cancer, a marked decrease in the A2 \nallele of CYP17A1 was seen when compared with normal \ncontrols [7]. A subsequent study on 119 endometriosis cases \nand 108 normal controls demonstrated that the CYP17A1 \nallele was associated with an increased risk of endometriosis \nin a Chinese population [8], but lack of association between \nendometriosis and the CYP17A1 polymorphism was ob-\nserved in UK and Japanese populations [17]. \n The IFIT1 gene is located at 91.1 Mbp, close to the \nCYP17A1 locus just outside the 95% confidence region for \nour linkage peak. However the linkage peak is broad and \nthere is evidence for linkage and association with endometri-\nosis in Puerto Rican families at marker D10S677 [18], which \nis located at 113.34 cM (95.95 Mb) close to the IFIT1 locus. \nDuring early pregnancy, IFIT1 is highly expressed upon \nstimulation with interferon tau ( IFNT), a type I interferon \nproduced by the conceptus trophectoderm [9, 19]. As an en-\ndometrial gene,  IFIT1  is believed to respond to hormonal \nstimulation and may have a functional role for uterine sup-\nport of peri-implantation conceptus survival, growth, and \nimplantation [9]. Although IFIT1 has been studied in the \nsheep model, it is unknown if variants in IFIT1 contribute to \nrisk of human endometriosis. \n We previously excluded association between endometri-\nosis and candidate genes under the linkage peak including \nempty spiracles homeobox 2 ( EMX2), phosphatase and \ntensin homolog (PTEN) and fibroblast growth factor receptor \n2 (FGFR2) in our Australian sample [20, 21]. To continue to \nsearch for the gene or genes contributing to the linkage peak, \nwe examined variation in IFIT1 and/or CYP17A1 to deter-\nmine whether those genes contribute to the risk of endome-\ntriosis and may account for some of the linkage signal on \nchromosome 10q. \n \n\n36    The Open Reproductive Science Journal, 2008, Volume 1 Zhao et al. \nMATERIALS AND METHODS \nParticipants and Sample Collection \n The project was approved by the Human Research Ethics \nCommittee of the Queensland Institute of Medical Research \nand the Australian Twin Registry. Women with surgically \nconfirmed endometriosis were selected from each of 768 Aus-\ntralian affected sister pair families as previously described \n[20]. The sister with the most severe stage of disease was cho-\nsen for genotyping. Disease severity was assessed retro-\nspectively from medical records using the revised American \nFertility Society (rAFS) classification system [22]. Sixty one \npercent of cases were classified with minimal to mild endome-\ntriosis (rAFS stages I/II). The remaining 39% of cases with \nmoderate to severe (rAFS stages III/IV) endometriosis were \nmore likely to have ovarian endometriosis. A total of 645 \ncases (84%) were diagnosed at laparoscopy; the remaining \ncases were mostly diagnosed at hysterectomy, or in a small \nnumber of cases at laparotomy or during another procedure. \n The controls were 768 unrelated women who had volun-\nteered for a twin study of gyn aecological health [2]. Controls \nwere selected after consideration of the competing issues of \nascertainment bias from clinic controls and presence of undi-\nagnosed cases. They were selected from women who self-\nreported they had never been diagnosed with endometriosis \nand were therefore considered to be at low risk of having \nendometriosis. Twins had been asked simply ‘have you had \nendometriosis?’[2]. Additional information from medical \nrecords was used where available. Women were also asked \nwhether they had ever had a laparoscopy and/or a hysterec-\ntomy and the reasons for each. About 14% of control women \nreported having a hysterectomy and/or laparoscopy. No evi-\ndence of endometriosis was reported at any of these proce-\ndures in our control sample [20]. The mean ages (± SD) of \nthe cases and controls at the time of data collection were \n35.6 ± 9.1 years (range = 17-65) and 45.7 ± 12.2 (range = \n29-90) years respectively. Genomic DNAs were extracted \n[23], and diluted to a working concentration of 2.5 ng/ μl. \nThe case and control DNAs were randomly placed in 384-\nwell PCR plates. \nSNP Selection \n We selected 7 SNPs in the CYP17A1 gene based upon \nthe allelic association results in endometriosis [8] and allele \nfrequency information from the National Center for Biotech-\nnology Information (NCBI, http://www.ncbi.nlm.nih.gov/). \nTen SNPs were selected in the IFIT1 gene on the basis of \nthe allelic frequency information and SNP distribution across \nthe gene. The chosen CYP17A1 SNP list comprised two \npromoter, two intronic, two coding exonic and one 3’UTR \nSNPs. One 5’UTR promoter, seven intronic and two coding \nexonic SNPs were chosen in the IFIT1 gene. All SNP se-\nquences were downloaded from the Chip Bioinformatics \ndatabase (http://snpper.chip.org/) and the sequences were \ncross checked in NCBI and Sequenom RealSNP databases \n(https://www.realsnp.com/) before assay design. \nGenotyping \n Multiplex assays were designed using the Sequenom \nMassARRAY Assay Design software (version 3.0). SNPs \nwere typed using Sequenom iPLEX™ chemistry on a \nMALDI-TOF Mass Spectrometer. The 2.5 μL PCR reactions \nwere performed in standard 384-well plates using 10 ng ge-\nnomic DNA, 0.5 unit of Taq polymerase (Qiagen, Valencia, \nCA), 500 μmol of each dNTP, and 100 nmol of each PCR \nprimers. Standard PCR thermal cycling conditions and post-\nPCR extension reactions were carried out as described previ-\nously [24]. The iPLEX reaction products were desalted by \ndiluting samples with 15 \u0001l of water and adding 3 \u0001l of resin. \nThe products were spotted on a SpectroChip (Sequenom), \nand data were processed and analysed in a Compact Mass \nSpectrometer by MassARRAY Workstation (version 3.4) \nsoftware (Sequenom). \nStatistical Analysis \n The genotypes were inspected and results were tested for \ndepartures from Hardy-Weinberg equilibrium (HWE) sepa-\nrately for cases and controls using Haploview version 3.32 \n(Whitehead Institute for Biomedical Research, USA). The \nPLINK program (http://pngu.mgh.harvard.edu/purcell/ \nplink/) was used to test association between endometriosis \nand individual SNPs. Global p-values were obtained for each \nmarker or each haplotype by performing 10,000 permutation \ntests. Haplotype frequencies, linkage disequilibrium (LD) \nestimates and analysis were determined by Haploview [25] \nusing the default method of Gabriel [26]. A global p-value \n<0.05 was considered to be statistically significant. \n We performed power calculations for our case-control \nstudy assuming a disease (endometriosis) prevalence of 10% \nusing the Genetic Power Calculator [27]. Power calculations \nwere based on 768 unrelated cases and 768 unrelated con-\ntrols using a significance threshold ( \u0002) of P = 0.01. \nRESULTS \n Seven SNPs in the CYP17A1 gene and ten SNPs in the \nIFIT1 gene were typed in 768 endometriosis cases and 768 \nunrelated controls. All SNPs were in Hardy–Weinberg equi-\nlibrium. The minor allele frequencies of the CYP17A1 SNPs \nranged from 0.230 to 0.414 in cases and from 0.200 to 0.443 \nin controls. The minor allele frequencies of the IFIT1 SNPs \nranged from 0.058 to 0.484 in cases and from 0.072 to 0.498 \nin controls (Table 1). The minor allele frequency for the key \nSNP (rs743572) in the CYP17A1 gene was 0.386 and 0.397 \nin cases and controls, respectively. There was no significant \ndifference in allele frequency between cases and controls for \nthis key SNP (Table 1). SNP rs2486758, at the -362 bp posi-\ntion relative to the start codon in the 5’UTR promoter region \nof CYP17A1 gene showed nominal evidence of association \n(P < 0.05). However, the difference in allele frequency be-\ntween cases and controls was small and the effects were not \nsignificant after correcting for multiple testing of all SNPs. \n The positions of the SNPs genotyped in the IFIT1 gene \nand the CYP17A1 gene are shown in Fig. ( 1a). A linkage \ndisequilibrium plot of SNPs and common haplotype blocks \nfor the both genes are also shown in Fig. ( 1b,c). We found \nno evidence for association between endometriosis and indi-\nvidual SNPs in either IFIT1 or CYP17A1 for either the allelic \nor the genotypic association tests (Table 1). \n Stratification of cases according to stage of disease (469 \nStage A cases and 768 controls) gave a best point-wise P-\nvalue of 0.02 for SNP rs619824 in the CYP17A1 gene, but \nthe global result correcting for multiple tests was non-\nsignificant (P = 0.58). Analysis of 296 cases diagnosed with \n\nVariation in CYP17A1 and IFIT1 and Risk of Endometriosis The Open Reproductive Science Journal, 2008, Volume 1    37 \nstage B and 768 controls, showed no significant differences \nbetween cases and controls for any SNPs typed in the study. \nDISCUSSION \n Our results do not support an association between endo-\nmetriosis and common variation in either CYP17A1 or \nIFIT1. Although both genes are biological candidates for \nendometriosis and are located near the peak of our linkage \nsignal on chromosome 10, there was no evidence that vari-\nants in either gene were associated with endometriosis or \ncontribute to the linkage signal on chromosome 10q. \n Genetic studies of CYP17A1 variants to date have fol-\nlowed a defined biological hypothesis suggesting the 5’UTR \npromoter region SNP (rs743572) is associated with gene \nexpression [16]. While the T allele (rs743572) was found to \nbe associated with increased risk of endometriosis in a study \nof Chinese women [14], there was no association between \nCYP17A1 variants and endometriosis in studies in Brazilian, \nUK or Japanese populations [17, 28, 29]. Endometriosis is a \nsex steroid-dependent disease [30]. CYP17A1 is involved in \nestrogen biosynthesis and metabolism so that certain genetic \npolymorphisms in the gene could be associated with in-\ncreased risk of developing endometriosis. The differences in \nthe results may relate to study power (sample size) or popu-\nlation differences. We estimated power for our case-control \nstudy based on total sample of 768 cases and 768 controls. \nThere is over 80% power to detect allele frequency of 0.05, \n0.25 and 0.5 contributing a dominant genotype relative risk \n(GRR) of 1.7, 1.5 and 1.8, respectively. In contrast, when the  \n \nsample size changed to total sample of 100 cases and 100 \ncontrols, there is only 10% power to detect allele frequency \nof 0.05, 0.25 and 0.5 contributing the similar genotype rela-\ntive risk as stated above. These calculations demonstrate our \nsample has high power to detect novel gene associations of \nmoderate effect. However, because our cases are highly se-\nlected in terms of family history, compared to a standard \ncase-control association study, our sample will have consid-\nerably more power to detect gene associations. \n We examined variation in CYP17A1 in cases from fami-\nlies contributing to the linkage peak in this region of chro-\nmosome 10q and genotyped 7 CYP17A1 SNPs including \nrs743572 in 768 endometriosis and 768 controls. We found \nno evidence for association with either SNP rs743572 in the \npromoter of CYP17A1 or the other 6 SNPs  in the gene in our \nAustralian sample. Strong linkage disequilibrium (LD) was \ndetected between SNP rs743572 and the other three SNPs in \nthe gene (rs3740397, r\n2=0.948; rs6163, r2=0.958; rs6162, \nr2=0.919) in our sample. It is unlikely that any asymptomatic \ncases present in the control samples would affect the conclu-\nsion from this study for a disease with a prevalence of 8-10% \n[31]. \n IFIT1  is a hormonally responsive gene expressed in \nsheep endometrium following stimulation with IFNT [9, 19]. \nTo test for association between IFIT1 variants and human \nendometriosis we typed 10 common IFIT1 SNPs in our 768 \nendometriosis cases and 768 unrelated controls. There was \nno evidence for association between the individual SNPs and \nendometriosis. Analysis of the SNPs across the IFIT1 locus  \n \nTable 1. Association Analysis of 17 SNPs Across the IFIT1 and CYP17A1 Gene Locus Genotyped in 768 Endometriosis Cases and \n768 Controls \n \ndbSNP ID SNP Position Gene(s) Role Alleles MAF-Cases MAF-Controls \u00012 P Value OR \nrs304478 chr10:91140902 IFIT1 Promoter G>T 0.456 0.463 0.139 0.709 0.972 \nrs303218 chr10:91142573 IFIT1 Intron G>A 0.175 0.186 0.620 0.431 0.929 \nrs303217 chr10:91143679 IFIT1 Intron T>C 0.470 0.469 0.002 0.968 1.003 \nrs303216 chr10:91145166 IFIT1 Intron C>T 0.169 0.182 0.858 0.354 0.915 \nrs303215 chr10:91146811 IFIT1 Intron T>C 0.170 0.182 0.754 0.385 0.921 \nrs304484 chr10:91149303 IFIT1 Intron G>T 0.231 0.244 0.770 0.380 0.928 \nrs304485 chr10:91149890 IFIT1 Intron T>A 0.484 0.498 0.578 0.447 0.946 \nrs303212 chr10:91151335 IFIT1 Intron T>C 0.232 0.241 0.357 0.550 0.950 \nrs303211 chr10:91152477 IFIT1 Coding exon G>A 0.058 0.072 2.581 0.108 0.790 \nrs303210 chr10:91152657 IFIT1 Coding exon C>T 0.169 0.182 0.822 0.365 0.916 \nrs619824 chr10:104571278  CYP17A1 3' UTR G>T 0.414 0.443 2.633 0.105 0.888 \nrs3740397 chr10:104582665 CYP17A1 Intron (boundary) C>G 0.375 0.396 1.404 0.236 0.916 \nrs4919687 chr10:104585238 CYP17A1 Intron (boundary) G>A 0.347 0.359 0.539 0.463 0.946 \nrs6163 chr10:104586914  CYP17A1 Coding exon C>A 0.376 0.395 1.058 0.304 0.926 \nrs6162 chr10:104586971  CYP17A1 Coding exon G>A 0.389 0.403 0.573 0.449 0.945 \nrs743572 chr10:104587142  CYP17A1 5' UTR T>C 0.386 0.397 0.376 0.540 0.954 \nrs2486758 chr10:104587470 CYP17A1 5' UTR T>C 0.230 0.200 3.870 0.049 1.189 \nMAF: minor allele frequency. \ndbSNP ID: database SNP identification. \nUTR: untranslated region. \n\n38    The Open Reproductive Science Journal, 2008, Volume 1 Zhao et al. \n \n \nFig. (1). Variants typed in the human IFIT1 and CYP17A1 genes (a) the genomic structure of the IFIT1 and CYP17A1 genes showing the \nlocation of the 17 SNPs genotyped ( b) the linkage disequilibrium plot of single nucleotide polymorphism estimated as \u00012 using Haploview \n(c) common haplotypes and association analysis with endometriosis. Shading key: white \u00012=0; shades of grey 0> \u00012<1; black \u00012=1  \na) \n \n \nb) \n \n \nc) \n \n91.140M 91.144M 91.148M 91.152M 104.580M 104.582M 104.584M 104.586M 104.588M\nrs304478 \nrs303218 \nrs303217 \nrs303216 \nrs303215 \nrs304484 \nrs304485 \n2Exons \n \n1 \nIFIT1  \nrs303212 \nrs303211\nrs303210\n        \n8 76 54 2 3 1 \nrs619824 rs3740397 rs4919687 \nrs6163 \nrs743572\nrs6162 \nrs2486758\nCYP17A1  \n \n\nVariation in CYP17A1 and IFIT1 and Risk of Endometriosis The Open Reproductive Science Journal, 2008, Volume 1    39 \nshowed strong linkage disequilibrium, with two haplotype \nblocks and three major haplotypes accounting for 87% of the \nchromosomes in our case samples. Our data also show strong \nlinkage disequilibrium (LD) in two blocks covering most of \nthe gene in our samples (Fig. 1b). We did not find any evi-\ndence for association between SNP haplotype frequencies \nand endometriosis. IFIT1 may be important in uterine devel-\nopment and function, but common variation is not associated \nwith risk of endometriosis. \n In this study, we examined the association between en-\ndometriosis and individual common SNPs and haplotypes in \nthe IFIT1 and CYP17A1 genes on chromosome 10q in an \nAustralian population including a functional SNP in the \nCYP17A1 promoter region. Our data does not provide evi-\ndence supporting an association between common variation \nin the IFIT1 and CYP17A1 genes and endometriosis suscep-\ntibility. We have previously demonstrated significant linkage \nto endometriosis on chromosome 10q [6]. Results of the pre-\nsent study demonstrate that variation in the CYP17A1 and \nIFIT1 genes does not explain linkage to endometriosis in this \nregion of chromosome 10. Both genes are good candidates \nfor endometriosis but the linkage region spans approximately \n8.5 million DNA base pairs and contains over 50 known \ngenes within the 95% confidence interval for the linkage \npeak. Many of these other genes can also be considered can-\ndidates for endometriosis and variation in one or more of \nthese genes may explain the linkage signal in this region. We \nconclude that common variants in the IFIT1 and CYP17A1 \ngenes do not play a key role in the pathogenesis of endome-\ntriosis. \nACKNOWLEDGMENTS \n We thank Dr. Daniel T. O’Connor for confirmation of \ndiagnosis and staging of disease from clinical records of 295 \ncases; Barbara Haddon for co-ordination of family recruit-\nment, blood and phenotype collection; Anjali Henders, Me-\ngan Campbell and staff of the Molecular Epidemiology\n \nLaboratory for sample processing and DNA preparation. \nThis study was supported by the Australian Government’s \nCooperative Research Centre’s Program and National Health \nand Medical Research Council of Australia (339430, \n339446). \nREFERENCES \n[1]  Kennedy S, Mardon H, Barlow D. Familial e ndometriosis. J Assist \nReprod Genet 1995; 12: 32-4. \n[2]  Treloar SA, O'Connor DT, O'Connor VM, Martin NG. Genetic \ninfluences on endometriosis in an Australian twin sample. Fertil \nSteril 1999; 71: 701-10. \n[3]  Hadfield RM, Mardon HJ, Barlow DH, Kennedy SH. Endometrio-\nsis in monozygotic twins. Fertil Steril 1997; 68: 941-2. \n[4]  Stefansson H, Geirsson RT, Steinthorsdottir V,  et al . 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Ge-\nnetic polymorphisms of cytochrome P450cl7alpha (CYP17) and \nprogesterone receptor genes (PROGINS) in the assessment of \nendometriosis risk. Gynecol Endocrinol 2007; 23: 29-33. \n[30] Guo SW. Association of endometriosis risk and genetic poly-\nmorphisms involving sex steroid biosynthesis and their receptors: a \nmeta-analysis. Gynecol Obstet Invest 2006; 61: 90-105. \n[31] Moskvina V, Holmans P, Schmidt KM, Craddock N. Design of \ncase-controls studies with unscreened controls. Ann Hum Genet \n2005; 69: 566-76. \n \n \nReceived: April 23, 2008 Revised: June 17, 2008 Accepted: June 17, 2008 \n \n© Zhao et al.; Licensee Bentham Open. \n \nThis is an open access article distributed under the terms of the Creative Commons Attribution License (http ://creativecommons.org/licenses/by/2.5/), which \npermits unrestrictive use, distribution, and reproduction in any medium, provided the original work is properly cited.","source_license":"CC0","license_restricted":false}