Genome-Wide Meta-Analysis of Myopia and Hyperopia Provides Evidence for Replication of 11 Loci

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Abstract

Refractive error (RE) is a complex, multifactorial disorder characterized by a mismatch between the optical power of the eye and its axial length that causes object images to be focused off the retina. The two major subtypes of RE are myopia (nearsightedness) and hyperopia (farsightedness), which represent opposite ends of the distribution of the quantitative measure of spherical refraction. We performed a fixed effects meta-analysis of genome-wide association results of myopia and hyperopia from 9 studies of European-derived populations: AREDS, KORA, FES, OGP-Talana, MESA, RSI, RSII, RSIII and ERF. One genome-wide significant region was observed for myopia, corresponding to a previously identified myopia locus on 8q12 (p = 1.25×10 ⁻⁸), which has been reported by Kiefer et al. as significantly associated with myopia age at onset and Verhoeven et al. as significantly associated to mean spherical-equivalent (MSE) refractive error. We observed two genome-wide significant associations with hyperopia. These regions overlapped with loci on 15q14 (minimum p value = 9.11×10 ⁻¹¹) and 8q12 (minimum p value 1.82×10 ⁻¹¹) previously reported for MSE and myopia age at onset. We also used an intermarker linkage- disequilibrium-based method for calculating the effective number of tests in targeted regional replication analyses. We analyzed myopia (which represents the closest phenotype in our data to the one used by Kiefer et al.) and showed replication of 10 additional loci associated with myopia previously reported by Kiefer et al. This is the first replication of these loci using myopia as the trait under analysis. “Replication-level” association was also seen between hyperopia and 12 of Kiefer et al.'s published loci. For the loci that show evidence of association to both myopia and hyperopia, the estimated effect of the risk alleles were in opposite directions for the two traits. This suggests that these loci are important contributors to variation of refractive error across the distribution.

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Most cited references 56

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Shaun Purcell, Benjamin M. Neale, Kathe Todd-Brown … (2007)

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

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METAL: fast and efficient meta-analysis of genomewide association scans

Cristen Willer, Yun Li, Gonçalo R Abecasis (2010)

Summary: METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats. Availability and implementation: METAL, including source code, documentation, examples, and executables, is available at http://www.sph.umich.edu/csg/abecasis/metal/ Contact: goncalo@umich.edu

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Newly identified loci that influence lipid concentrations and risk of coronary artery disease.

Cristen J Willer, Serena Sanna, Anne U. Jackson … (2008)

To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls.

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Author and article information

Contributors

Xiaoping Miao: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Electronic): 1932-6203

Publication date Collection: 2014

Publication date (Electronic): 18 September 2014

Volume: 9

Issue: 9

Electronic Location Identifier: e107110

Affiliations

[1 ]National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland, United States of America

[2 ]Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America

[3 ]Institute of Human Genetics, Technische Universität München, Munich, Germany

[4 ]Institute of Population Genetics, National Research Council of Italy, Sassari, Italy

[5 ]Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America

[6 ]Department of Ophthalmology, Erasmus Medical Center, Rotterdam, the Netherlands

[7 ]Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands

[8 ]MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, United Kingdom

[9 ]Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia

[10 ]Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada, and DCCT/EDIC Research Group, The Diabetes Control and Complications Trial and Follow-up Study, The Biostatistics Center, The George Washington University, Rockville, Maryland, United States of America

[11 ]Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas' Hospital, London, United Kingdom

[12 ]Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America

[13 ]Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, Maryland, United States of America

[14 ]Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America

[15 ]Singapore Eye Research Institute, National University of Singapore, Singapore, Singapore

[16 ]Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute, University of Sydney, Sydney, Australia

[17 ]Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

[18 ]Dipartimento di Scienze Chirurgiche, Clinica Oculistica Universita' degli studi di Cagliari, Cagliari, Italy

[19 ]The Diabetes Control and Complications Trial and Follow-up Study, The Biostatistics Center, The George Washington University, Rockville, Maryland, United States of America

[20 ]Croatian Centre for Global Health, University of Split Medical School, Split, Croatia

[21 ]Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom

[22 ]Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, the Netherlands

[23 ]Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands

[24 ]Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, The Hague, the Netherlands

[25 ]Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany

[26 ]Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany

[27 ]Department of Ophthalmology, Hospital “Sestre Milosrdnice”, Zagreb, Croatia

[28 ]Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany

[29 ]Princess Alexandra Eye Pavilion, Edinburgh, United Kingdom

[30 ]MRC Centre of Epidemiology for Child Health, Institute of Child Health, University College London, London, United Kingdom

[31 ]Institute of Ophthalmology, University College London, London, United Kingdom

[32 ]Ulverscroft Vision Research Group, Institute of Child Health, University College London, London, United Kingdom

[33 ]Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America

MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, China

Author notes

* E-mail: jebw@ 123456mail.nih.gov

Competing Interests: The authors have declared that no competing interests exist.

Conceived and designed the experiments: DS JEBW TM RW CLS KO VV MS LIR MFC EC BEKK RK TYW CMvD PM SMS JJW HC IR BAO AGU AH FR NA LCK JRV AD TB GB CG HW JFW BF JSR CJH CH AFW ADP PNB CCWK JIR MP DCCT/EDIC. Analyzed the data: RW CLS KO FM LP XL VJMV VV MS SMH PGH CV PMC CJH PNB JEBW. Wrote the paper: CLS RW KO JEBW DS. Enrolled participants and collected study data: KO LJR MFC EC BEKK RK TYW CMvD RM SMS MF JJW OP BAO AGU AH FR NA LCK JRV AD TB GB CG HW JFW BF JSR CJH CH ADP CCWK JIR TM DCCT/EDIC.

¶ CLS, RW and KO are joint first authors on this work.

Article

Publisher ID: PONE-D-13-45662

DOI: 10.1371/journal.pone.0107110

PMC ID: 4169415

PubMed ID: 25233373

SO-VID: 51d4cfe5-2de8-4599-8cb6-028afb6d76bc

License:

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

History

Date received : 16 December 2013

Date accepted : 12 August 2014

Page count

Pages: 19

Funding

This work was funded in part by the Intramural Research Program of the National Human Genome Research Institute (JEBW, RW, CLS) and the National Eye Institute (MFC, EC), National Institutes of Health, and NIH R01EY020483 (DS, TM, JEBW). The KORA Study is supported by funds from Helmholtz Center Munich and the German Federal Ministry of Education and Research (BMBF). The Multi-Ethnic Study of Atherosclerosis (MESA) and MESA SNP Health Association Resource (SHARe) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support is provided by grants and contracts N01 HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169 and RR-024156. Funding for SHARe genotyping was provided by NHLBI Contract N02-HL-6-4278. Funding for the collection of refractive error data was supported by the Intramural Research Program of the National Eye Institute (ZIAEY000403). Support was also provided by the National Center for Research Resources, Grant UL1RR033176, and is now at the National Center for Advancing Translational Sciences, Grant UL1TR000124. The Blue Mountains Eye Study was supported by the Australian National Health & Medical Research Council (NHMRC) project grants (IDs 974159, 991407, 211069 and 457349) and Centre for Clinical Research Excellence (CCRE) in Translational Clinical Research in Eye Diseases, CCRE in TCR-Eye (ID 529923). The Blue Mountains Eye Study GWAS and genotyping costs were supported by Australian NHMRC project grants (IDs 512423, 475604, 529912 and 590204), and the Wellcome Trust, United Kingdom, as part of Wellcome Trust Case Control Consortium 2 (grant IDs 085475/B/08/Z and 085475/08/Z). EGH (631096), PNB (1028444) and JJW (358702 and 632909) are supported by the NHMRC fellowship scheme. The Centre for Eye Research Australia receives Operational Infrastructure Support from the Victorian government. OGP-Talana was supported by grants from the Italian Ministry of Education, University and Research (MIUR) no. 5571/DSPAR/2002 and (FIRB) D.M no. 718/Ric/2005. The DCCT Research Group is sponsored through research contracts from the National Institute of Diabetes, Endocrinology and Metabolic Diseases of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK, N01-DK-6-2204, R01-DK-077510) and the National Institutes of Health. ADP holds a Canada Research Chair in the Genetics of Complex Diseases. The Rotterdam Study and ERF were supported by the Netherlands Organisation of Scientific Research (NWO) (Vidi 91796357); Erasmus Medical Center and Erasmus University, Rotterdam, The Netherlands; Netherlands Organization for Health Research and Development (ZonMw); UitZicht; the Research Institute for Diseases in the Elderly; the Ministry of Education, Culture and Science; the Ministry for Health, Welfare and Sports; the European Commission (DG XII); the Municipality of Rotterdam; the Netherlands Genomics Initiative/NWO; Center for Medical Systems Biology of NGI; Lijf en Leven; M. D. Fonds; Henkes Stichting; Stichting Nederlands Oogheelkundig Onderzoek; Swart van Essen; Bevordering van Volkskracht; Blindenhulp; Landelijke Stichting voor Blinden en Slechtzienden; Rotterdamse Vereniging voor Blindenbelangen; OOG; Algemene Nederlandse Vereniging ter Voorkoming van Blindheid; the Rotterdam Eye Hospital Research Foundation; and Topcon Europe. The Croatian studies were funded by grants from the Medical Research Council (United Kingdom), from the Republic of Croatia Ministry of Science, Education and Sports (108-1080315-0302). The authors acknowledge the Wellcome Trust Clinical facility (Edinburgh) for the genotyping of the CROATIA-Vis study, an EU framework 6 project EUROSPAN (contract no LSHG-CT-2006-018947) for the genotyping of the CROATIA-Korcula study that was performed at the Helmholtz Zentrum Munchen (Munich, Germany). ORCADES was supported by the Chief Scientist Office of the Scottish Government, the Royal Society, the Medical Research Council Human Genetics Unit and the European Union framework program 6 EUROSPAN project (contract no. LSHG-CT-2006-018947). The authors acknowledge the Wellcome Trust Clinical facility (Edinburgh) for DNA extraction for the ORCADES study and Peter Lichner and the Helmholtz Zentrum Munchen genotyping staff (Munich, Germany) for genotyping. The GWAS of the 1958 British birth cohort was funded by the Wellcome Trust. This work was carried out at the UCL Institutes of Child Health and Institutes of Ophthalmology which also receive funding from the NIHR Biomedical Research Centres in Child Health and Ophthalmology respectively. The Wisconsin Epidemiologic Study of Diabetic Retinopathy was funded by NIH grant R01EY016379. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Genome-Wide Meta-Analysis of Myopia and Hyperopia Provides Evidence for Replication of 11 Loci

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Most cited references 56

PLINK: a tool set for whole-genome association and population-based linkage analyses.

METAL: fast and efficient meta-analysis of genomewide association scans

Newly identified loci that influence lipid concentrations and risk of coronary artery disease.

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