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Farrell SF, Sterling M, Klyne DM, Mustafa S, Campos AI, Kho PF, Lundberg M, Rentería ME, Ngo TT, Cuéllar-Partida G. Genetic impact of blood C-reactive protein levels on chronic spinal & widespread pain. Eur Spine J 2023; 32:2078-2085. [PMID: 37069442 DOI: 10.1007/s00586-023-07711-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 02/27/2023] [Accepted: 04/06/2023] [Indexed: 04/19/2023]
Abstract
PURPOSE Causal mechanisms underlying systemic inflammation in spinal & widespread pain remain an intractable experimental challenge. Here we examined whether: (i) associations between blood C-reactive protein (CRP) and chronic back, neck/shoulder & widespread pain can be explained by shared underlying genetic variants; and (ii) higher CRP levels causally contribute to these conditions. METHODS Using genome-wide association studies (GWAS) of chronic back, neck/shoulder & widespread pain (N = 6063-79,089 cases; N = 239,125 controls) and GWAS summary statistics for blood CRP (Pan-UK Biobank N = 400,094 & PAGE consortium N = 28,520), we employed cross-trait bivariate linkage disequilibrium score regression to determine genetic correlations (rG) between these chronic pain phenotypes and CRP levels (FDR < 5%). Latent causal variable (LCV) and generalised summary data-based Mendelian randomisation (GSMR) analyses examined putative causal associations between chronic pain & CRP (FDR < 5%). RESULTS Higher CRP levels were genetically correlated with chronic back, neck/shoulder & widespread pain (rG range 0.26-0.36; P ≤ 8.07E-9; 3/6 trait pairs). Although genetic causal proportions (GCP) did not explain this finding (GCP range - 0.32-0.08; P ≥ 0.02), GSMR demonstrated putative causal effects of higher CRP levels contributing to each pain type (beta range 0.027-0.166; P ≤ 9.82E-03; 3 trait pairs) as well as neck/shoulder pain effects on CRP levels (beta [S.E.] 0.030 [0.021]; P = 6.97E-04). CONCLUSION This genetic evidence for higher CRP levels in chronic spinal (back, neck/shoulder) & widespread pain warrants further large-scale multimodal & prospective longitudinal studies to accelerate the identification of novel translational targets and more effective therapeutic strategies.
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Affiliation(s)
- Scott F Farrell
- RECOVER Injury Research Centre, The University of Queensland, Level 7 STARS Hospital, 296 Herston Rd, Herston, QLD, 4029, Australia.
- NHMRC Centre of Research Excellence: Better Health Outcomes for Compensable Injury, The University of Queensland, Herston, QLD, Australia.
- Tess Cramond Pain & Research Centre, Royal Brisbane & Women's Hospital, Herston, QLD, Australia.
| | - Michele Sterling
- RECOVER Injury Research Centre, The University of Queensland, Level 7 STARS Hospital, 296 Herston Rd, Herston, QLD, 4029, Australia
- NHMRC Centre of Research Excellence: Better Health Outcomes for Compensable Injury, The University of Queensland, Herston, QLD, Australia
| | - David M Klyne
- NHMRC Centre of Clinical Research Excellence in Spinal Pain, Injury & Health; School of Health & Rehabilitation Sciences, The University of Queensland, St Lucia, QLD, Australia
| | - Sanam Mustafa
- Davies Livestock Research Centre, The University of Adelaide, Roseworthy, SA, Australia
| | - Adrián I Campos
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
- Genetic Epidemiology Laboratory, Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Pik-Fang Kho
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Molecular Cancer Epidemiology Laboratory, Population Health Program, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Mischa Lundberg
- Institute of Biological Psychiatry, Boserupvej 2, 4000, Roskilde, Denmark
- Transformational Bioinformatics, CSIRO Health & Biosecurity, North Ryde, NSW, Australia
- UQ Diamantina Institute, The University of Queensland & Translational Research Institute, Woolloongabba, QLD, Australia
| | - Miguel E Rentería
- Genetic Epidemiology Laboratory, Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Trung Thanh Ngo
- RECOVER Injury Research Centre, The University of Queensland, Level 7 STARS Hospital, 296 Herston Rd, Herston, QLD, 4029, Australia
| | - Gabriel Cuéllar-Partida
- UQ Diamantina Institute, The University of Queensland & Translational Research Institute, Woolloongabba, QLD, Australia
- Gilead Sciences, Foster City, CA, USA
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2
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Campos AI, Ingold N, Huang Y, Mitchell BL, Kho PF, Han X, García-Marín LM, Ong JS, Law MH, Yokoyama JS, Martin NG, Dong X, Cuellar-Partida G, MacGregor S, Aslibekyan S, Rentería ME. Discovery of genomic loci associated with sleep apnea risk through multi-trait GWAS analysis with snoring. Sleep 2023; 46:6918774. [PMID: 36525587 PMCID: PMC9995783 DOI: 10.1093/sleep/zsac308] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 11/11/2022] [Indexed: 12/23/2022] Open
Abstract
STUDY OBJECTIVES Despite its association with severe health conditions, the etiology of sleep apnea (SA) remains understudied. This study sought to identify genetic variants robustly associated with SA risk. METHODS We performed a genome-wide association study (GWAS) meta-analysis of SA across five cohorts (NTotal = 523 366), followed by a multi-trait analysis of GWAS (multi-trait analysis of genome-wide association summary statistics [MTAG]) to boost power, leveraging the high genetic correlation between SA and snoring. We then adjusted our results for the genetic effects of body mass index (BMI) using multi-trait-based conditional and joint analysis (mtCOJO) and sought replication of lead hits in a large cohort of participants from 23andMe, Inc (NTotal = 1 477 352; Ncases = 175 522). We also explored genetic correlations with other complex traits and performed a phenome-wide screen for causally associated phenotypes using the latent causal variable method. RESULTS Our SA meta-analysis identified five independent variants with evidence of association beyond genome-wide significance. After adjustment for BMI, only one genome-wide significant variant was identified. MTAG analyses uncovered 49 significant independent loci associated with SA risk. Twenty-nine variants were replicated in the 23andMe GWAS adjusting for BMI. We observed genetic correlations with several complex traits, including multisite chronic pain, diabetes, eye disorders, high blood pressure, osteoarthritis, chronic obstructive pulmonary disease, and BMI-associated conditions. CONCLUSION Our study uncovered multiple genetic loci associated with SA risk, thus increasing our understanding of the etiology of this condition and its relationship with other complex traits.
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Affiliation(s)
- Adrian I Campos
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Nathan Ingold
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | | | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Pik-Fang Kho
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Xikun Han
- Program in Genetic Epidemiology and Statistical Genetics, Harvard University T.H. Chan School of Public Health, Boston, MA, USA
| | - Luis M García-Marín
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Jue-Sheng Ong
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - Matthew H Law
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Jennifer S Yokoyama
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA.,Weill Institute of Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | | | - Xianjun Dong
- Genomics and Bioinformatics Hub, Brigham and Women's Hospital, Boston, MA, USA.,Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - Miguel E Rentería
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
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3
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Farrell SF, Kho PF, Lundberg M, Campos AI, Rentería ME, de Zoete RMJ, Sterling M, Ngo TT, Cuéllar-Partida G. A Shared Genetic Signature for Common Chronic Pain Conditions and its Impact on Biopsychosocial Traits. J Pain 2023; 24:369-386. [PMID: 36252619 DOI: 10.1016/j.jpain.2022.10.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 09/28/2022] [Accepted: 10/06/2022] [Indexed: 11/11/2022]
Abstract
The multiple comorbidities & dimensions of chronic pain present a formidable challenge in disentangling its aetiology. Here, we performed genome-wide association studies of 8 chronic pain types using UK Biobank data (N =4,037-79,089 cases; N = 239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. We report evidence of a shared genetic signature across chronic pain types as their genetic correlations and GCP directions were broadly consistent across an array of biopsychosocial traits. Across 5,942 significant genetic correlations, 570 trait pairs could be explained by a causal association (|GCP| >0.6; 5% false discovery rate), including 82 traits affected by pain while 410 contributed to an increased risk of chronic pain (cf. 78 with a decreased risk) such as certain somatic pathologies (eg, musculoskeletal), psychiatric traits (eg, depression), socioeconomic factors (eg, occupation) and medical comorbidities (eg, cardiovascular disease). This data-driven phenome-wide association analysis has demonstrated a novel and efficient strategy for identifying genetically supported risk & protective traits to enhance the design of interventional trials targeting underlying causal factors and accelerate the development of more effective treatments with broader clinical utility. PERSPECTIVE: Through large-scale phenome-wide association analyses of >1,400 biopsychosocial traits, this article provides evidence for a shared genetic signature across 8 common chronic pain types. It lays the foundation for further translational studies focused on identifying causal genetic variants and pathophysiological pathways to develop novel diagnostic & therapeutic technologies and strategies.
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Affiliation(s)
- Scott F Farrell
- RECOVER Injury Research Centre, The University of Queensland, Herston, Queensland, Australia; NHMRC Centre of Research Excellence: Better Health Outcomes for Compensable Injury, The University of Queensland, Herston, Queensland, Australia; Tess Cramond Pain & Research Centre, Royal Brisbane & Women's Hospital, Herston, Queensland, Australia.
| | - Pik-Fang Kho
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California; Molecular Cancer Epidemiology Laboratory, Population Health Program, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia; School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Mischa Lundberg
- UQ Diamantina Institute, The University of Queensland & Translational Research Institute, Woolloongabba, Queensland, Australia; Transformational Bioinformatics, CSIRO Health & Biosecurity, North Ryde, New South Wales, Australia
| | - Adrián I Campos
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia; Genetic Epidemiology Laboratory, Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Miguel E Rentería
- Genetic Epidemiology Laboratory, Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Rutger M J de Zoete
- School of Allied Health Science and Practice, The University of Adelaide, Adelaide, South Australia, Australia
| | - Michele Sterling
- RECOVER Injury Research Centre, The University of Queensland, Herston, Queensland, Australia; NHMRC Centre of Research Excellence: Better Health Outcomes for Compensable Injury, The University of Queensland, Herston, Queensland, Australia
| | - Trung Thanh Ngo
- RECOVER Injury Research Centre, The University of Queensland, Herston, Queensland, Australia
| | - Gabriel Cuéllar-Partida
- UQ Diamantina Institute, The University of Queensland & Translational Research Institute, Woolloongabba, Queensland, Australia
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4
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Farrell SF, Campos AI, Kho PF, de Zoete RMJ, Sterling M, Rentería ME, Ngo TT, Cuéllar-Partida G. Genetic basis to structural grey matter associations with chronic pain. Brain 2021; 144:3611-3622. [PMID: 34907416 DOI: 10.1093/brain/awab334] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/06/2021] [Accepted: 08/12/2021] [Indexed: 01/26/2023] Open
Abstract
Structural neuroimaging studies of individuals with chronic pain conditions have often observed decreased regional grey matter at a phenotypic level. However, it is not known if this association can be attributed to genetic factors. Here we employed a novel integrative data-driven and hypothesis-testing approach to determine whether there is a genetic basis to grey matter morphology differences in chronic pain. Using publicly available genome-wide association study summary statistics for regional chronic pain conditions (n = 196 963) and structural neuroimaging measures (n = 19 629-34 000), we applied bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine the genetic correlations (rG) and genetic causal proportion (GCP) between these complex traits, respectively. Five a priori brain regions (i.e. prefrontal cortex, cingulate cortex, insula, thalamus and superior temporal gyrus) were selected based on systematic reviews of grey matter morphology studies in chronic pain. Across this evidence-based selection of five brain regions, 10 significant negative genetic correlations (out of 369) were found (false discovery rate < 5%), suggesting a shared genetic basis to both reduced regional grey matter morphology and the presence of chronic pain. Specifically, negative genetic correlations were observed between reduced insula grey matter morphology and chronic pain in the abdomen (mean insula cortical thickness), hips (left insula volume) and neck/shoulders (left and right insula volume). Similarly, a shared genetic basis was found for reduced posterior cingulate cortex volume in chronic pain of the hip (left and right posterior cingulate), neck/shoulder (left posterior cingulate) and chronic pain at any site (left posterior cingulate); and for reduced pars triangularis volume in chronic neck/shoulder (left pars triangularis) and widespread pain (right pars triangularis). Across these negative genetic correlations, a significant genetic causal proportion was only found between mean insula thickness and chronic abdominal pain [rG (standard error, SE) = -0.25 (0.08), P = 1.06 × 10-3; GCP (SE) = -0.69 (0.20), P = 4.96 × 10-4]. This finding suggests that the genes underlying reduced cortical thickness of the insula causally contribute to an increased risk of chronic abdominal pain. Altogether, these results provide independent corroborating evidence for observational reports of decreased grey matter of particular brain regions in chronic pain. Further, we show for the first time that this association is mediated (in part) by genetic factors. These novel findings warrant further investigation into the neurogenetic pathways that underlie the development and prolongation of chronic pain conditions.
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Affiliation(s)
- Scott F Farrell
- RECOVER Injury Research Centre, The University of Queensland, Herston, QLD, Australia.,NHMRC Centre for Research Excellence in Road Traffic Injury Recovery, The University of Queensland, Herston, QLD, Australia.,Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - Adrián I Campos
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, St Lucia, QLD, Australia.,Genetic Epidemiology Laboratory, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Pik-Fang Kho
- Molecular Cancer Epidemiology Laboratory, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia.,School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Rutger M J de Zoete
- School of Allied Health Science and Practice, The University of Adelaide, Adelaide, SA, Australia
| | - Michele Sterling
- RECOVER Injury Research Centre, The University of Queensland, Herston, QLD, Australia.,NHMRC Centre for Research Excellence in Road Traffic Injury Recovery, The University of Queensland, Herston, QLD, Australia
| | - Miguel E Rentería
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, St Lucia, QLD, Australia.,Genetic Epidemiology Laboratory, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Trung Thanh Ngo
- Diamantina Institute, The University of Queensland and Translational Research Institute, Woolloongabba, QLD, Australia
| | - Gabriel Cuéllar-Partida
- Diamantina Institute, The University of Queensland and Translational Research Institute, Woolloongabba, QLD, Australia
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5
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García-Marín LM, Campos AI, Kho PF, Martin NG, Cuéllar-Partida G, Rentería ME. Phenome-wide screening of GWAS data reveals the complex causal architecture of obesity. Hum Genet 2021; 140:1253-1265. [PMID: 34057592 DOI: 10.1007/s00439-021-02298-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 05/26/2021] [Indexed: 02/07/2023]
Abstract
OBJECTIVE In the present study, we sought to identify causal relationships between obesity and other complex traits and conditions using a data-driven hypothesis-free approach that uses genetic data to infer causal associations. METHODS We leveraged available summary-based genetic data from genome-wide association studies on 1498 phenotypes and applied the latent causal variable method (LCV) between obesity and all traits. RESULTS We identified 110 traits causally associated with obesity. Of those, 109 were causal outcomes of obesity, while only leg pain in calves was a causal determinant of obesity. Causal outcomes of obesity included 26 phenotypes associated with cardiovascular diseases, 22 anthropometric measurements, nine with the musculoskeletal system, nine with behavioural or lifestyle factors including loneliness or isolation, six with respiratory diseases, five with body bioelectric impedances, four with psychiatric phenotypes, four related to the nervous system, four with disabilities or long-standing illness, three with the gastrointestinal system, three with use of analgesics, two with metabolic diseases, one with inflammatory response and one with the neurodevelopmental disorder ADHD, among others. In particular, some causal outcomes of obesity included hypertension, stroke, ever having a period of extreme irritability, low forced vital capacity and forced expiratory volume, diseases of the musculoskeletal system, diabetes, carpal tunnel syndrome, loneliness or isolation, high leukocyte count, and ADHD. CONCLUSIONS Our results indicate that obesity causally affects a wide range of traits and comorbid diseases, thus providing an overview of the metabolic, physiological, and neuropsychiatric impact of obesity on human health.
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Affiliation(s)
- Luis M García-Marín
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Adrián I Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Pik-Fang Kho
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Gabriel Cuéllar-Partida
- University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia.
- 23andMe, Inc, Sunnyvale, CA, USA.
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia.
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6
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Kho PF, Amant F, Annibali D, Ashton K, Attia J, Auer PL, Beckmann MW, Black A, Brinton L, Buchanan DD, Chanock SJ, Chen C, Chen MM, Cheng THT, Cook LS, Crous-Bous M, Czene K, De Vivo I, Dennis J, Dörk T, Dowdy SC, Dunning AM, Dürst M, Easton DF, Ekici AB, Fasching PA, Fridley BL, Friedenreich CM, García-Closas M, Gaudet MM, Giles GG, Goode EL, Gorman M, Haiman CA, Hall P, Hankinson SE, Hein A, Hillemanns P, Hodgson S, Hoivik EA, Holliday EG, Hunter DJ, Jones A, Kraft P, Krakstad C, Lambrechts D, Le Marchand L, Liang X, Lindblom A, Lissowska J, Long J, Lu L, Magliocco AM, Martin L, McEvoy M, Milne RL, Mints M, Nassir R, Otton G, Palles C, Pooler L, Proietto T, Rebbeck TR, Renner SP, Risch HA, Rübner M, Runnebaum I, Sacerdote C, Sarto GE, Schumacher F, Scott RJ, Setiawan VW, Shah M, Sheng X, Shu XO, Southey MC, Tham E, Tomlinson I, Trovik J, Turman C, Tyrer JP, Van Den Berg D, Wang Z, Wentzensen N, Xia L, Xiang YB, Yang HP, Yu H, Zheng W, Webb PM, Thompson DJ, Spurdle AB, Glubb DM, O'Mara TA. Mendelian randomization analyses suggest a role for cholesterol in the development of endometrial cancer. Int J Cancer 2021; 148:307-319. [PMID: 32851660 PMCID: PMC7757859 DOI: 10.1002/ijc.33206] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 05/08/2020] [Accepted: 05/26/2020] [Indexed: 01/14/2023]
Abstract
Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10-8 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.
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Affiliation(s)
- Pik-Fang Kho
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Frederic Amant
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals KU Leuven, University of Leuven, Leuven, Belgium
| | - Daniela Annibali
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals KU Leuven, University of Leuven, Leuven, Belgium
| | - Katie Ashton
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, New South Wales, Australia
- Centre for Information Based Medicine, University of Newcastle, Callaghan, New South Wales, Australia
- Discipline of Medical Genetics, School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - John Attia
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, New South Wales, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Paul L. Auer
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, Washington
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin
| | - Matthias W. Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Amanda Black
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Louise Brinton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Daniel D. Buchanan
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Victoria, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia
| | - Stephen J. Chanock
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Chu Chen
- Epidemiology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Maxine M. Chen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Timothy H. T. Cheng
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Linda S. Cook
- University of New Mexico Health Sciences Center, Albuquerque, New Mexico
- Department of Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, Alberta, Canada
| | - Marta Crous-Bous
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Immaculata De Vivo
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Sean C. Dowdy
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Mayo Clinic, Rochester, Minnesota
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Matthias Dürst
- Department of Gynaecology, Jena University Hospital - Friedrich Schiller University, Jena, Germany
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Arif B. Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Peter A. Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
- David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, California
| | - Brooke L. Fridley
- Department of Biostatistics, Kansas University Medical Center, Kansas City, Kansas
| | - Christine M. Friedenreich
- Department of Cancer Epidemiology and Prevention Research, Alberta Health Services, Calgary, Alberta, Canada
| | - Montserrat García-Closas
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Mia M. Gaudet
- Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia
| | - Graham G. Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Ellen L. Goode
- Department of Health Science Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
| | - Maggie Gorman
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Susan E. Hankinson
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
- Department of Biostatistics & Epidemiology, University of Massachusetts, Amherst, Amherst, Massachusetts
| | - Alexander Hein
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Peter Hillemanns
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Shirley Hodgson
- Department of Clinical Genetics, St George's, University of London, London, UK
| | - Erling A. Hoivik
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Elizabeth G. Holliday
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, New South Wales, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - David J. Hunter
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Angela Jones
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Camilla Krakstad
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Diether Lambrechts
- VIB Center for Cancer Biology, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Xiaolin Liang
- Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Jolanta Lissowska
- Department of Cancer Epidemiology and Prevention, M. Sklodowska-Curie Cancer Center, Oncology Institute, Warsaw, Poland
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Lingeng Lu
- Chronic Disease Epidemiology, Yale School of Medicine, New Haven, Connecticut
| | - Anthony M. Magliocco
- Department of Anatomic Pathology, Moffitt Cancer Center & Research Institute, Tampa, Florida
| | - Lynn Martin
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Mark McEvoy
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Roger L. Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Miriam Mints
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Rami Nassir
- Department of Biochemistry and Molecular Medicine, University of California Davis, Davis, California
| | - Geoffrey Otton
- School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Claire Palles
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Loreall Pooler
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Tony Proietto
- School of Medicine and Public Health, University of Newcastle, Callaghan, New South Wales, Australia
| | - Timothy R. Rebbeck
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Stefan P. Renner
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Harvey A. Risch
- Chronic Disease Epidemiology, Yale School of Medicine, New Haven, Connecticut
| | - Matthias Rübner
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Ingo Runnebaum
- Department of Gynaecology, Jena University Hospital - Friedrich Schiller University, Jena, Germany
| | - Carlotta Sacerdote
- Center for Cancer Prevention (CPO-Peimonte), Turin, Italy
- Human Genetics Foundation (HuGeF), Turin, Italy
| | - Gloria E. Sarto
- Department of Obstetrics and Gynecology, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin
| | - Fredrick Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio
| | - Rodney J. Scott
- Hunter Medical Research Institute, John Hunter Hospital, Newcastle, New South Wales, Australia
- Discipline of Medical Genetics, School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Callaghan, New South Wales, Australia
- Division of Molecular Medicine, Pathology North, John Hunter Hospital, Newcastle, New South Wales, Australia
| | - V. Wendy Setiawan
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Xin Sheng
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Melissa C. Southey
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Emma Tham
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Clinical Genetics, Karolinska Institutet, Stockholm, Sweden
| | - Ian Tomlinson
- Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Jone Trovik
- Centre for Cancer Biomarkers CCBIO, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Jonathan P. Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - David Van Den Berg
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Lucy Xia
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Yong-Bing Xiang
- State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Hannah P. Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland
| | - Herbert Yu
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Penelope M. Webb
- Population Health Department, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Deborah J. Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Amanda B. Spurdle
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Dylan M. Glubb
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tracy A. O'Mara
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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7
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Cuellar-Partida G, Williams KM, Yazar S, Guggenheim JA, Hewitt AW, Williams C, Wang JJ, Kho PF, Saw SM, Cheng CY, Wong TY, Aung T, Young TL, Tideman JWL, Jonas JB, Mitchell P, Wojciechowski R, Stambolian D, Hysi P, Hammond CJ, Mackey DA, Lucas RM, MacGregor S. Genetically low vitamin D concentrations and myopic refractive error: a Mendelian randomization study. Int J Epidemiol 2018; 46:1882-1890. [PMID: 28586461 DOI: 10.1093/ije/dyx068] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2017] [Indexed: 01/08/2023] Open
Abstract
Background Myopia prevalence has increased in the past 20 years, with many studies linking the increase to reduced time spent outdoors. A number of recent observational studies have shown an inverse association between vitamin D [25(OH)D] serum levels and myopia. However, in such studies it is difficult to separate the effects of time outdoors and vitamin D levels. In this work we use Mendelian randomization (MR) to assess if genetically determined 25(OH)D levels contribute to the degree of myopia. Methods We performed MR using results from a meta-analysis of refractive error (RE) genome-wide association study (GWAS) that included 37 382 and 8 376 adult participants of European and Asian ancestry, respectively, published by the Consortium for Refractive Error And Myopia (CREAM). We used single nucleotide polymorphisms (SNPs) in the DHCR7, CYP2R1, GC and CYP24A1 genes with known effects on 25(OH)D concentration as instrumental variables (IV). We estimated the effect of 25(OH)D on myopia level using a Wald-type ratio estimator based on the effect estimates from the CREAM GWAS. Results Using the combined effect attributed to the four SNPs, the estimate for the effect of 25(OH)D on refractive error was -0.02 [95% confidence interval (CI) -0.09, 0.04] dioptres (D) per 10 nmol/l increase in 25(OH)D concentration in Caucasians and 0.01 (95% CI -0.17, 0.19) D per 10 nmol/l increase in Asians. Conclusions The tight confidence intervals on our estimates suggest the true contribution of vitamin D levels to degree of myopia is very small and indistinguishable from zero. Previous findings from observational studies linking vitamin D levels to myopia were likely attributable to the effects of confounding by time spent outdoors.
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Affiliation(s)
- Gabriel Cuellar-Partida
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,University of Queensland Diamantina Institute, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Katie M Williams
- Department of Ophthalmology.,Department of Ophthalmology and Twin Research, King's College London, London, UK
| | - Seyhan Yazar
- Lions Eye Institute, University of Western Australia, Perth, WA, Australia
| | | | - Alex W Hewitt
- Menzies Research Institute Tasmania, University of Tasmania, Hobart, Australia
| | - Cathy Williams
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Jie Jin Wang
- Centre for Vision Research, Department of Ophthalmology and Westmead Institute for Medical Research, University of Sydney, Camperdown, NSW, Australia
| | - Pik-Fang Kho
- Department of Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD,Australia
| | - Seang Mei Saw
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Graduate Medical School.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Graduate Medical School.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Graduate Medical School.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Graduate Medical School.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Terri L Young
- Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - J Willem L Tideman
- Department of Ophthalmology and Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jost B Jonas
- Beijing Institute of Ophthalmology, Capital University of Medical Science, Beijing Ophthalmology & Visual Sciences Key Laboratory, Beijing, China.,Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University Heidelberg, Seegartenklinik Heidelberg, Germany
| | | | - Paul Mitchell
- Centre for Vision Research, Department of Ophthalmology and Westmead Institute for Medical Research, University of Sydney, Camperdown, NSW, Australia
| | | | - Dwight Stambolian
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, PA, USA
| | - Pirro Hysi
- Department of Ophthalmology and Twin Research, King's College London, London, UK
| | - Christopher J Hammond
- Department of Ophthalmology.,Department of Ophthalmology and Twin Research, King's College London, London, UK
| | - David A Mackey
- Lions Eye Institute, University of Western Australia, Perth, WA, Australia
| | - Robyn M Lucas
- National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University, Canberra, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
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