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      Genome-wide association meta-analysis identifies new endometriosis risk loci

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          Abstract

          We conducted a genome-wide association (GWA) meta-analysis of 4,604 endometriosis cases and 9,393 controls of Japanese 1 and European 2 ancestry. We show that rs12700667 on chromosome 7p15.2, previously found in Europeans, replicates in Japanese ( P = 3.6 × 10 −3), and confirm association of rs7521902 on 1p36.12 near WNT4. In addition, we establish association of rs13394619 in GREB1 on 2p25.1 and identify a novel locus on 12q22 near VEZT (rs10859871). Excluding European cases with minimal or unknown severity, we identified additional novel loci on 2p14 (rs4141819), 6p22.3 (rs7739264) and 9p21.3 (rs1537377). All seven SNP effects were replicated in an independent cohort and produced P < 5 × 10 −8 in a combined analysis. Finally, we found a significant overlap in polygenic risk for endometriosis between the European and Japanese GWA cohorts ( P = 8.8 × 10 −11), indicating that many weakly associated SNPs represent true endometriosis risk loci and risk prediction and future targeted disease therapy may be transferred across these populations.

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          Genotype imputation.

          Yun Li, Cristen Willer, Serena Sanna … (2009)
          Genotype imputation is now an essential tool in the analysis of genome-wide association scans. This technique allows geneticists to accurately evaluate the evidence for association at genetic markers that are not directly genotyped. Genotype imputation is particularly useful for combining results across studies that rely on different genotyping platforms but also increases the power of individual scans. Here, we review the history and theoretical underpinnings of the technique. To illustrate performance of the approach, we summarize results from several gene mapping studies. Finally, we preview the role of genotype imputation in an era when whole genome resequencing is becoming increasingly common.
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            Female development in mammals is regulated by Wnt-4 signalling.

            S Vainio, M. Heikkilä, A Kispert … (1999)
            In the mammalian embryo, both sexes are initially morphologically indistinguishable: specific hormones are required for sex-specific development. Mullerian inhibiting substance and testosterone secreted by the differentiating embryonic testes result in the loss of female (Mullerian) or promotion of male (Wolffian) reproductive duct development, respectively. The signalling molecule Wnt-4 is crucial for female sexual development. At birth, sexual development in males with a mutation in Wnt-4 appears to be normal; however, Wnt-4-mutant females are masculinized-the Mullerian duct is absent while the Wolffian duct continues to develop. Wnt-4 is initially required in both sexes for formation of the Mullerian duct, then Wnt-4 in the developing ovary appears to suppress the development of Leydig cells; consequently, Wnt-4-mutant females ectopically activate testosterone biosynthesis. Wnt-4 may also be required for maintenance of the female germ line. Thus, the establishment of sexual dimorphism is under the control of both local and systemic signals.
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              Heterogeneity in Meta-Analyses of Genome-Wide Association Investigations

              John Ioannidis, Nikolaos Patsopoulos, Evangelos Evangelou (2007)
              Background Meta-analysis is the systematic and quantitative synthesis of effect sizes and the exploration of their diversity across different studies. Meta-analyses are increasingly applied to synthesize data from genome-wide association (GWA) studies and from other teams that try to replicate the genetic variants that emerge from such investigations. Between-study heterogeneity is important to document and may point to interesting leads. Methodology/Principal Findings To exemplify these issues, we used data from three GWA studies on type 2 diabetes and their replication efforts where meta-analyses of all data using fixed effects methods (not incorporating between-study heterogeneity) have already been published. We considered 11 polymorphisms that at least one of the three teams has suggested as susceptibility loci for type 2 diabetes. The I2 inconsistency metric (measuring the amount of heterogeneity not due to chance) was different from 0 (no detectable heterogeneity) for 6 of the 11 genetic variants; inconsistency was moderate to very large (I2 = 32–77%) for 5 of them. For these 5 polymorphisms, random effects calculations incorporating between-study heterogeneity revealed more conservative p-values for the summary effects compared with the fixed effects calculations. These 5 associations were perused in detail to highlight potential explanations for between-study heterogeneity. These include identification of a marker for a correlated phenotype (e.g. FTO rs8050136 being associated with type 2 diabetes through its effect on obesity); differential linkage disequilibrium across studies of the identified genetic markers with the respective culprit polymorphisms (e.g., possibly the case for CDKAL1 polymorphisms or for rs9300039 and markers in linkage disequilibrium, as shown by additional studies); and potential bias. Results were largely similar, when we treated the discovery and replication data from each GWA investigation as separate studies. Significance Between-study heterogeneity is useful to document in the synthesis of data from GWA investigations and can offer valuable insights for further clarification of gene-disease associations.
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 9216904
                Journal ID (pubmed-jr-id): 2419
                Journal ID (nlm-ta): Nat Genet
                Journal ID (iso-abbrev): Nat. Genet.
                Title: Nature genetics
                ISSN (Print): 1061-4036
                ISSN (Electronic): 1546-1718
                Publication date Nihms-submitted: 13 December 2012
                Publication date (Electronic): 28 October 2012
                Publication date (Print): 28 October 2012
                Publication date PMC-release: 20 December 2012
                Volume: 44
                Issue: 12
                Pages: 1355-1359
                Affiliations
                [1 ]Queensland Institute of Medical Research, Brisbane, QLD 4029, Australia.
                [2 ]Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, Japan.
                [3 ]Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 2HH, UK.
                [4 ]First Department of Surgery, Sapporo Medical University, School of Medicine, Sapporo, Japan.
                [5 ]Genetic and Genomic Epidemiology Unit, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK.
                [6 ]Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Newcastle, NSW 2308, Australia.
                [7 ]Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia.
                [8 ]School of Medicine and Public Health, University of Newcastle, Newcastle, NSW 2308, Australia.
                [9 ]Public Health Research Program, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia.
                [10 ]School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW 2308, Australia.
                [11 ]Division of Genetics, Hunter Area Pathology Service, Newcastle, NSW 2305, Australia.
                [12 ]Nuffield Department of Obstetrics and Gynaecology, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
                [13 ]Centre for Military and Veterans’ Health, University of Queensland, Mayne Medical School, 288 Herston Road, QLD 4006, Australia.
                [14 ]Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women’s Hospital and Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA.
                [15 ]Department of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Niigata, Japan.
                Author notes
                [16]

                These authors contributed equally to this work.

                [17]

                These authors jointly directed this work.

                Correspondence should be addressed to D.R.N ( dale.nyholt@ 123456qimr.edu.au ), K.T.Z. ( krina.zondervan@ 123456well.ox.ac.uk ), H.Z ( zembutsh@ 123456ims.u-tokyo.ac.jp ) or G.W.M ( grant.montgomery@ 123456qimr.edu.au ).; Corresponding (submitting) author: A/Prof Dale R Nyholt Queensland Institute of Medical Research Locked Bag 2000, Royal Brisbane Hospital, Herston, Qld 4029, Australia Tel: +61 7 3362 0258 Fax: +61 7 3362 0101 dale.nyholt@ 123456qimr.edu.au
                Article
                Manuscript ID: EMS50444
                DOI: 10.1038/ng.2445
                PMC ID: 3527416
                PubMed ID: 23104006
                SO-VID: d41eafc8-5ec6-4442-9662-09492f8bfb82
                History
                Funding
                Funded by: Wellcome Trust :
                Award ID: 085235 || WT
                Funded by: Wellcome Trust :
                Award ID: 084766 || WT
                Categories
                Subject: Article

                ScienceOpen disciplines: Genetics
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                ScienceOpen disciplines: Genetics

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