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Walters RG, Millwood IY, Lin K, Schmidt Valle D, McDonnell P, Hacker A, Avery D, Edris A, Fry H, Cai N, Kretzschmar WW, Ansari MA, Lyons PA, Collins R, Donnelly P, Hill M, Peto R, Shen H, Jin X, Nie C, Xu X, Guo Y, Yu C, Lv J, Clarke RJ, Li L, Chen Z. Genotyping and population characteristics of the China Kadoorie Biobank. CELL GENOMICS 2023; 3:100361. [PMID: 37601966 PMCID: PMC10435379 DOI: 10.1016/j.xgen.2023.100361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 02/09/2023] [Accepted: 06/24/2023] [Indexed: 08/22/2023]
Abstract
The China Kadoorie Biobank (CKB) is a population-based prospective cohort of >512,000 adults recruited from 2004 to 2008 from 10 geographically diverse regions across China. Detailed data from questionnaires and physical measurements were collected at baseline, with additional measurements at three resurveys involving ∼5% of surviving participants. Analyses of genome-wide genotyping, for >100,000 participants using custom-designed Axiom arrays, reveal extensive relatedness, recent consanguinity, and signatures reflecting large-scale population movements from recent Chinese history. Systematic genome-wide association studies of incident disease, captured through electronic linkage to death and disease registries and to the national health insurance system, replicate established disease loci and identify 14 novel disease associations. Together with studies of candidate drug targets and disease risk factors and contributions to international genetics consortia, these demonstrate the breadth, depth, and quality of the CKB data. Ongoing high-throughput omics assays of collected biosamples and planned whole-genome sequencing will further enhance the scientific value of this biobank.
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Affiliation(s)
- Robin G. Walters
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Iona Y. Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Dan Schmidt Valle
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Pandora McDonnell
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Alex Hacker
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Daniel Avery
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Ahmed Edris
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Hannah Fry
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Na Cai
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | | | - M. Azim Ansari
- Nuffield Department of Medicine, Oxford University, Oxford OX1 3SY, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
| | - Paul A. Lyons
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Rory Collins
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Peter Donnelly
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Michael Hill
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Richard Peto
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Hongbing Shen
- Department of Epidemiology, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing 211116, China
| | - Xin Jin
- BGI-Shenzhen, Shenzhen 518083, China
| | - Chao Nie
- BGI-Shenzhen, Shenzhen 518083, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen 518083, China
| | - Yu Guo
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Robert J. Clarke
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
| | - China Kadoorie Biobank Collaborative Group
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Nuffield Department of Medicine, Oxford University, Oxford OX1 3SY, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford OX3 9DU, UK
- Cambridge Institute for Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge CB2 0AW, UK
- Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
- Department of Epidemiology, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing 211116, China
- BGI-Shenzhen, Shenzhen 518083, China
- Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing 100191, China
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Zhao B, Li Y, Fan Z, Wu Z, Shu J, Yang X, Yang Y, Wang X, Li B, Wang X, Copana C, Yang Y, Lin J, Li Y, Stein JL, O'Brien JM, Li T, Zhu H. Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.16.23286035. [PMID: 36824893 PMCID: PMC9949187 DOI: 10.1101/2023.02.16.23286035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
As an anatomical extension of the brain, the retina of the eye is synaptically connected to the visual cortex, establishing physiological connections between the eye and the brain. Despite the unique opportunity retinal structures offer for assessing brain disorders, less is known about their relationship to brain structure and function. Here we present a systematic cross-organ genetic architecture analysis of eye-brain connections using retina and brain imaging endophenotypes. Novel phenotypic and genetic links were identified between retinal imaging biomarkers and brain structure and function measures derived from multimodal magnetic resonance imaging (MRI), many of which were involved in the visual pathways, including the primary visual cortex. In 65 genomic regions, retinal imaging biomarkers shared genetic influences with brain diseases and complex traits, 18 showing more genetic overlaps with brain MRI traits. Mendelian randomization suggests that retinal structures have bidirectional genetic causal links with neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, cross-organ imaging genetics reveals a genetic basis for eye-brain connections, suggesting that the retinal images can elucidate genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yujue Li
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zhenyi Wu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Juan Shu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Xiaochen Yang
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yilin Yang
- Department of Computer and Information Science and Electrical and Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Xiyao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Carlos Copana
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jinjie Lin
- Yale School of Management, Yale University, New Haven, CT 06511, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joan M. O'Brien
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Diseases, PA, 19104, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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3
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Tomasoni M, Beyeler MJ, Vela SO, Mounier N, Porcu E, Corre T, Krefl D, Button AL, Abouzeid H, Lazaros K, Bochud M, Schlingemann R, Bergin C, Bergmann S. Genome-Wide Association Studies of Retinal Vessel Tortuosity Identify Numerous Novel Loci Revealing Genes and Pathways Associated with Ocular and Cardiometabolic Diseases. OPHTHALMOLOGY SCIENCE 2023; 3:100288. [PMID: 37131961 PMCID: PMC10149284 DOI: 10.1016/j.xops.2023.100288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 02/03/2023] [Accepted: 02/09/2023] [Indexed: 02/18/2023]
Abstract
Purpose To identify novel susceptibility loci for retinal vascular tortuosity, to better understand the molecular mechanisms modulating this trait, and reveal causal relationships with diseases and their risk factors. Design Genome-wide Association Studies (GWAS) of vascular tortuosity of retinal arteries and veins followed by replication meta-analysis and Mendelian randomization (MR). Participants We analyzed 116 639 fundus images of suitable quality from 63 662 participants from 3 cohorts, namely the UK Biobank (n = 62 751), the Swiss Kidney Project on Genes in Hypertension (n = 397), and OphtalmoLaus (n = 512). Methods Using a fully automated retina image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, we computed the median arterial, venous and combined vessel tortuosity measured by the distance factor (the length of a vessel segment over its chord length), as well as by 6 alternative measures that integrate over vessel curvature. We then performed the largest GWAS of these traits to date and assessed gene set enrichment using the novel high-precision statistical method PascalX. Main Outcome Measure We evaluated the genetic association of retinal tortuosity, measured by the distance factor. Results Higher retinal tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, metacohort. We estimated heritability at ∼25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 116 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that retinal tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, MR revealed causal effects between tortuosity, body mass index, and low-density lipoprotein. Conclusions Several alleles associated with retinal vessel tortuosity suggest a common genetic architecture of this trait with ocular diseases (glaucoma, myopia), cardiovascular diseases, and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images. Financial Disclosures The author(s) have no proprietary or commercial interest in any materials discussed in this article.
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Affiliation(s)
- Mattia Tomasoni
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Jules-Gonin Eye Hospital, Lausanne, Switzerland
| | - Michael Johannes Beyeler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sofia Ortin Vela
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ninon Mounier
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Eleonora Porcu
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Tanguy Corre
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Daniel Krefl
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Alexander Luke Button
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Hana Abouzeid
- Division of Ophthalmology, Geneva University Hospitals, Geneva, Switzerland
- Clinical Eye Research Center Memorial Adolphe de Rothschild, Geneva, Switzerland
| | | | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Reinier Schlingemann
- Jules-Gonin Eye Hospital, Lausanne, Switzerland
- Department of Ophthalmology, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | | | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
- Correspondence: Sven Bergmann, PhD, University of Lausanne, Genopode, Lausanne 1016, Switzerland.
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Choquet H, Khawaja AP, Jiang C, Yin J, Melles RB, Glymour MM, Hysi PG, Jorgenson E. Association Between Myopic Refractive Error and Primary Open-Angle Glaucoma: A 2-Sample Mendelian Randomization Study. JAMA Ophthalmol 2022; 140:864-871. [PMID: 35900730 PMCID: PMC9335248 DOI: 10.1001/jamaophthalmol.2022.2762] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 05/31/2022] [Indexed: 11/14/2022]
Abstract
Importance Refractive error (RE) is the most common form of visual impairment, and myopic RE is associated with an increased risk of primary open-angle glaucoma (POAG). Whether this association represents a causal role of RE in the etiology of POAG remains unknown. Objective To evaluate shared genetic influences and investigate the association of myopic RE with the risk for POAG. Design, Setting, and Participants Observational analyses were used to evaluate the association between mean spherical equivalent (MSE) RE (continuous trait) or myopia (binary trait) and POAG risk in individuals from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. To quantify genetic overlap, genome-wide genetic correlation analyses were performed using genome-wide association studies (GWAS) of MSE RE or myopia and POAG from GERA. Potential causal effects were assessed between MSE RE and POAG using 2-sample Mendelian randomization. Genetic variants associated with MSE RE were derived using GWAS summary statistics from a GWAS of RE conducted in 102 117 UK Biobank participants. For POAG, we used GWAS summary statistics from our previous GWAS (3836 POAG cases and 48 065 controls from GERA). Data analyses occurred between July 2020 and October 2021. Main Outcomes and Measure Our main outcome was POAG risk as odds ratio (OR) caused by per-unit difference in MSE RE (in diopters). Results Our observational analyses included data for 54 755 non-Hispanic White individuals (31 926 [58%] females and 22 829 [42%] males). Among 4047 individuals with POAG, mean (SD) age was 73.64 (9.20) years; mean (SD) age of the 50 708 controls was 65.38 (12.24) years. Individuals with POAG had a lower refractive MSE and were more likely to have myopia or high myopia compared with the control participants (40.2% vs 34.1%, P = 1.31 × 10-11 for myopia; 8.5% vs 6.8%, P = .004 for high myopia). Our genetic correlation analyses demonstrated that POAG was genetically correlated with MSE RE (rg, -0.24; SE, 0.06; P = 3.90 × 10-5), myopia (rg, 0.21; SE, 0.07; P = .004), and high myopia (rg, 0.23; SE, 0.09; P = .01). Genetically assessed refractive MSE was negatively associated with POAG risk (inverse-variance weighted model: OR per diopter more hyperopic MSE = 0.94; 95% CI, 0.89-0.99; P = .01). Conclusions and Relevance These findings demonstrate a shared genetic basis and an association between myopic RE and POAG risk. This may support population POAG risk stratification and screening strategies, based on RE information.
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Affiliation(s)
- Hélène Choquet
- Division of Research, Kaiser Permanente Northern California, Oakland
| | - Anthony P. Khawaja
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom
| | - Chen Jiang
- Division of Research, Kaiser Permanente Northern California, Oakland
| | - Jie Yin
- Division of Research, Kaiser Permanente Northern California, Oakland
| | - Ronald B. Melles
- Department of Ophthalmology, Kaiser Permanente Northern California, Redwood City
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Pirro G. Hysi
- King’s College London, Section of Ophthalmology, School of Life Course Sciences, London, United Kingdom
- King’s College London, Department of Twin Research and Genetic Epidemiology, London, United Kingdom
- University College London, Great Ormond Street Hospital Institute of Child Health, London, United Kingdom
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5
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Suzuki M, Tomita M. Genetic Variations of Vitamin A-Absorption and Storage-Related Genes, and Their Potential Contribution to Vitamin A Deficiency Risks Among Different Ethnic Groups. Front Nutr 2022; 9:861619. [PMID: 35571879 PMCID: PMC9096837 DOI: 10.3389/fnut.2022.861619] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 03/23/2022] [Indexed: 12/01/2022] Open
Abstract
Vitamin A, an essential fat-soluble micronutrient, plays a critical role in the body, by regulating vision, immune responses, and normal development, for instance. Vitamin A deficiency (VAD) is a major cause of xerophthalmia and increases the risk of death from infectious diseases. It is also emerging that prenatal exposure to VAD is associated with disease risks later in life. The overall prevalence of VAD has significantly declined over recent decades; however, the rate of VAD is still high in many low- and mid-income countries and even in high-income countries among specific ethnic/race groups. While VAD occurs when dietary intake is insufficient to meet demands, establishing a strong association between food insecurity and VAD, and vitamin A supplementation is the primary solution to treat VAD, genetic contributions have also been reported to effect serum vitamin A levels. In this review, we discuss genetic variations associated with vitamin A status and vitamin A bioactivity-associated genes, specifically those linked to uptake of the vitamin in the small intestine and its storage in the liver, as well as their potential contribution to vitamin A deficiency risks among different ethnic groups.
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Affiliation(s)
- Masako Suzuki
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, United States
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6
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Li X, Long J, Liu Y, Cai Q, Zhao Y, Jin L, Liu M, Li C. Association of MTOR and PDGFRA gene polymorphisms with different degrees of myopia severity. Exp Eye Res 2022; 217:108962. [DOI: 10.1016/j.exer.2022.108962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 12/17/2021] [Accepted: 01/23/2022] [Indexed: 11/04/2022]
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Kondratyev NV, Alfimova MV, Golov AK, Golimbet VE. Bench Research Informed by GWAS Results. Cells 2021; 10:3184. [PMID: 34831407 PMCID: PMC8623533 DOI: 10.3390/cells10113184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/11/2021] [Accepted: 11/11/2021] [Indexed: 12/15/2022] Open
Abstract
Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.
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Affiliation(s)
| | | | - Arkadiy K. Golov
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
- Institute of Gene Biology, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Vera E. Golimbet
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
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8
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Zukerman R, Harris A, Oddone F, Siesky B, Verticchio Vercellin A, Ciulla TA. Glaucoma Heritability: Molecular Mechanisms of Disease. Genes (Basel) 2021; 12:genes12081135. [PMID: 34440309 PMCID: PMC8391305 DOI: 10.3390/genes12081135] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 07/19/2021] [Accepted: 07/22/2021] [Indexed: 02/06/2023] Open
Abstract
Glaucoma is one of the world’s leading causes of irreversible blindness. A complex, multifactorial disease, the underlying pathogenesis and reasons for disease progression are not fully understood. The most common form of glaucoma, primary open-angle glaucoma (POAG), was traditionally understood to be the result of elevated intraocular pressure (IOP), leading to optic nerve damage and functional vision loss. Recently, researchers have suggested that POAG may have an underlying genetic component. In fact, studies of genetic association and heritability have yielded encouraging results showing that glaucoma may be influenced by genetic factors, and estimates for the heritability of POAG and disease-related endophenotypes show encouraging results. However, the vast majority of the underlying genetic variants and their molecular mechanisms have not been elucidated. Several genes have been suggested to have molecular mechanisms contributing to alterations in key endophenotypes such as IOP (LMX1B, MADD, NR1H3, and SEPT9), and VCDR (ABCA1, ELN, ASAP1, and ATOH7). Still, genetic studies about glaucoma and its molecular mechanisms are limited by the multifactorial nature of the disease and the large number of genes that have been identified to have an association with glaucoma. Therefore, further study into the molecular mechanisms of the disease itself are required for the future development of therapies targeted at genes leading to POAG endophenotypes and, therefore, increased risk of disease.
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Affiliation(s)
- Ryan Zukerman
- Department of Ophthalmology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, USA; (R.Z.); (A.H.); (B.S.); (A.V.V.)
- Department of Ophthalmology, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Alon Harris
- Department of Ophthalmology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, USA; (R.Z.); (A.H.); (B.S.); (A.V.V.)
| | | | - Brent Siesky
- Department of Ophthalmology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, USA; (R.Z.); (A.H.); (B.S.); (A.V.V.)
| | - Alice Verticchio Vercellin
- Department of Ophthalmology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, USA; (R.Z.); (A.H.); (B.S.); (A.V.V.)
| | - Thomas A. Ciulla
- Midwest Eye Institute, Indianapolis, IN 46290, USA
- Correspondence: ; Tel.: +1-(317)-506-0334 or +1-(317)-817-1822; Fax: +1-(317)-817-1898
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9
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Alipanahi B, Hormozdiari F, Behsaz B, Cosentino J, McCaw ZR, Schorsch E, Sculley D, Dorfman EH, Foster PJ, Peng LH, Phene S, Hammel N, Carroll A, Khawaja AP, McLean CY. Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology. Am J Hum Genet 2021; 108:1217-1230. [PMID: 34077760 PMCID: PMC8322934 DOI: 10.1016/j.ajhg.2021.05.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 05/10/2021] [Indexed: 02/06/2023] Open
Abstract
Genome-wide association studies (GWASs) require accurate cohort phenotyping, but expert labeling can be costly, time intensive, and variable. Here, we develop a machine learning (ML) model to predict glaucomatous optic nerve head features from color fundus photographs. We used the model to predict vertical cup-to-disc ratio (VCDR), a diagnostic parameter and cardinal endophenotype for glaucoma, in 65,680 Europeans in the UK Biobank (UKB). A GWAS of ML-based VCDR identified 299 independent genome-wide significant (GWS; p ≤ 5 × 10-8) hits in 156 loci. The ML-based GWAS replicated 62 of 65 GWS loci from a recent VCDR GWAS in the UKB for which two ophthalmologists manually labeled images for 67,040 Europeans. The ML-based GWAS also identified 93 novel loci, significantly expanding our understanding of the genetic etiologies of glaucoma and VCDR. Pathway analyses support the biological significance of the novel hits to VCDR: select loci near genes involved in neuronal and synaptic biology or harboring variants are known to cause severe Mendelian ophthalmic disease. Finally, the ML-based GWAS results significantly improve polygenic prediction of VCDR and primary open-angle glaucoma in the independent EPIC-Norfolk cohort.
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Affiliation(s)
| | | | | | | | | | | | - D Sculley
- Google Health, Cambridge, MA 02142, USA
| | | | - Paul J Foster
- NIHR Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology, London EC1V 9EL, UK
| | | | | | | | | | - Anthony P Khawaja
- NIHR Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology, London EC1V 9EL, UK; MRC Epidemiology Unit, University of Cambridge, Cambridge CB2 0SL, UK
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10
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Han X, Steven K, Qassim A, Marshall HN, Bean C, Tremeer M, An J, Siggs OM, Gharahkhani P, Craig JE, Hewitt AW, Trzaskowski M, MacGregor S. Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA. Am J Hum Genet 2021; 108:1204-1216. [PMID: 34077762 DOI: 10.1016/j.ajhg.2021.05.005] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 05/10/2021] [Indexed: 02/06/2023] Open
Abstract
Cupping of the optic nerve head, a highly heritable trait, is a hallmark of glaucomatous optic neuropathy. Two key parameters are vertical cup-to-disc ratio (VCDR) and vertical disc diameter (VDD). However, manual assessment often suffers from poor accuracy and is time intensive. Here, we show convolutional neural network models can accurately estimate VCDR and VDD for 282,100 images from both UK Biobank and an independent study (Canadian Longitudinal Study on Aging), enabling cross-ancestry epidemiological studies and new genetic discovery for these optic nerve head parameters. Using the AI approach, we perform a systematic comparison of the distribution of VCDR and VDD and compare these with intraocular pressure and glaucoma diagnoses across various genetically determined ancestries, which provides an explanation for the high rates of normal tension glaucoma in East Asia. We then used the large number of AI gradings to conduct a more powerful genome-wide association study (GWAS) of optic nerve head parameters. Using the AI-based gradings increased estimates of heritability by ∼50% for VCDR and VDD. Our GWAS identified more than 200 loci associated with both VCDR and VDD (double the number of loci from previous studies) and uncovered dozens of biological pathways; many of the loci we discovered also confer risk for glaucoma.
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11
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Murray GK, Lin T, Austin J, McGrath JJ, Hickie IB, Wray NR. Could Polygenic Risk Scores Be Useful in Psychiatry?: A Review. JAMA Psychiatry 2021; 78:210-219. [PMID: 33052393 DOI: 10.1001/jamapsychiatry.2020.3042] [Citation(s) in RCA: 131] [Impact Index Per Article: 43.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
IMPORTANCE Polygenic risk scores (PRS) are predictors of the genetic susceptibility to diseases, calculated for individuals as weighted counts of thousands of risk variants in which the risk variants and their weights have been identified in genome-wide association studies. Polygenic risk scores show promise in aiding clinical decision-making in many areas of medical practice. This review evaluates the potential use of PRS in psychiatry. OBSERVATIONS On their own, PRS will never be able to establish or definitively predict a diagnosis of common complex conditions (eg, mental health disorders), because genetic factors only contribute part of the risk and PRS will only ever capture part of the genetic contribution. Combining PRS with other risk factors has potential to improve outcome prediction and aid clinical decision-making (eg, determining follow-up options for individuals seeking help who are at clinical risk of future illness). Prognostication of adverse physical health outcomes or response to treatment in clinical populations are of great interest for psychiatric practice, but data from larger samples are needed to develop and evaluate PRS. CONCLUSIONS AND RELEVANCE Polygenic risk scores will contribute to risk assessment in clinical psychiatry as it evolves to combine information from molecular, clinical, and lifestyle metrics. The genome-wide genotype data needed to calculate PRS are inexpensive to generate and could become available to psychiatrists as a by-product of practices in other medical specialties. The utility of PRS in clinical psychiatry, as well as ethical issues associated with their use, should be evaluated in the context of realistic expectations of what PRS can and cannot deliver. Clinical psychiatry has lagged behind other fields of health care in its use of new technologies and routine clinical data for research. Now is the time to catch up.
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Affiliation(s)
- Graham K Murray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia.,Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Tian Lin
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
| | - Jehannine Austin
- Departments of Psychiatry and Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.,BC Mental Health and Substance Use Services Research Institute, Vancouver, British Columbia, Canada
| | - John J McGrath
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia.,Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, Australia.,National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
| | - Ian B Hickie
- Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia.,Queensland Brain Institute, The University of Queensland, Brisbane, Australia
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12
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Wray NR, Lin T, Austin J, McGrath JJ, Hickie IB, Murray GK, Visscher PM. From Basic Science to Clinical Application of Polygenic Risk Scores: A Primer. JAMA Psychiatry 2021; 78:101-109. [PMID: 32997097 DOI: 10.1001/jamapsychiatry.2020.3049] [Citation(s) in RCA: 148] [Impact Index Per Article: 49.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
IMPORTANCE Polygenic risk scores (PRS) are predictors of the genetic susceptibilities of individuals to diseases. All individuals have DNA risk variants for all common diseases, but genetic susceptibility differences between people reflect the cumulative burden of these. Polygenic risk scores for an individual are calculated as weighted counts of thousands of risk variants that they carry, where the risk variants and their weights have been identified in genome-wide association studies. Here, we review the underlying basic science of PRS, providing a foundation for understanding the potential clinical utility and limitations of PRS. OBSERVATIONS Polygenic risk scores can be calculated for a wide range of diseases from a saliva or blood sample using genotyping technologies that are inexpensive. While genotyping only needs to be done once for each individual in their lifetime, the PRS can be recalculated as identification of risk variants improves. On their own, PRS will never be able to establish or definitively predict future diagnoses of common complex conditions because genetic factors only contribute part of the risk, and PRS will only ever capture part of the genetic contributions. Nonetheless, just as clinical medicine uses a multitude of other predictive measures, PRS either on their own or as part of multivariable predictive algorithms could play a role. CONCLUSIONS AND RELEVANCE Utility of PRS in clinical medicine and ethical issues related to their use should be evaluated in the context of realistic expectations of what PRS can and cannot deliver. For different diseases, PRS could have utility in community settings (stratification to better triage people into established screening programs) or could contribute to clinical decision-making for those presenting with symptoms but where formal diagnosis is unclear. In principle, PRS could contribute to treatment choices, but more data are needed to allow development of PRS in this context.
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Affiliation(s)
- Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.,Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Tian Lin
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Jehannine Austin
- Departments of Psychiatry and Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada.,BC Mental Health and Substance Use Services Research Institute, Vancouver, British Columbia, Canada
| | - John J McGrath
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.,Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, Queensland, Australia.,National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
| | - Ian B Hickie
- Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, England
| | - Graham K Murray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, England.,Department of Psychiatry, University of Cambridge, Cambridge, England
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
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Sakurada Y, Mabuchi F, Kashiwagi K. Genetics of primary open-angle glaucoma and its endophenotypes. PROGRESS IN BRAIN RESEARCH 2020; 256:31-47. [PMID: 32958214 DOI: 10.1016/bs.pbr.2020.06.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Glaucoma is a neurodegenerative disorder characterized by the loss of retinal ganglion cells and optic nerve fibers, resulting in the loss of visual field. Primary open-angle glaucoma (POAG) is the most prevalent subtype of glaucoma. Recent genome-wide association studies (GWASs) identified more than 100 variants associated with POAG and multiple loci associated with endophenotypes including the disc area, vertical cup-to-disc ratio (VCDR), and intraocular pressure (IOP). Especially, several GWASs reported the association between VCDR and variants near CDKN2B/CDKN2B-AS1, ATOH7, and CHEK2, and between IOP and variants near TMCO1, CAV1/CAV2, GAS7, and ARHGEF12. However, the effect of each variant on endophenotypes is modest; therefore, it is useful to construct a genetic risk score (GRS) based on the effect on endophenotypes by combining susceptible genetic variants. Several studies demonstrated that higher GRS was closely associated with endophenotypes including the VCDR, IOP, and age of diagnosis. Henceforth, by quantifying GRS, identification of high risk group before the disease onset, prediction of visual prognosis and early intervention may be possible.
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Affiliation(s)
- Yoichi Sakurada
- Department of Ophthalmology, Faculty of Medicine, University of Yamanashi, Kofu, Japan.
| | - Fumihiko Mabuchi
- Department of Ophthalmology, Faculty of Medicine, University of Yamanashi, Kofu, Japan
| | - Kenji Kashiwagi
- Department of Ophthalmology, Faculty of Medicine, University of Yamanashi, Kofu, Japan
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McCombe PA, Garton FC, Katz M, Wray NR, Henderson RD. What do we know about the variability in survival of patients with amyotrophic lateral sclerosis? Expert Rev Neurother 2020; 20:921-941. [PMID: 32569484 DOI: 10.1080/14737175.2020.1785873] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
INTRODUCTION ALS is a fatal neurodegenerative disease. However, patients show variability in the length of survival after symptom onset. Understanding the mechanisms of long survival could lead to possible avenues for therapy. AREAS COVERED This review surveys the reported length of survival in ALS, the clinical features that predict survival in individual patients, and possible factors, particularly genetic factors, that could cause short or long survival. The authors also speculate on possible mechanisms. EXPERT OPINION a small number of known factors can explain some variability in ALS survival. However, other disease-modifying factors likely exist. Factors that alter motor neurone vulnerability and immune, metabolic, and muscle function could affect survival by modulating the disease process. Knowing these factors could lead to interventions to change the course of the disease. The authors suggest a broad approach is needed to quantify the proportion of variation survival attributable to genetic and non-genetic factors and to identify and estimate the effect size of specific factors. Studies of this nature could not only identify novel avenues for therapeutic research but also play an important role in clinical trial design and personalized medicine.
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Affiliation(s)
- Pamela A McCombe
- Centre for Clinical Research, The University of Queensland , Brisbane, Australia.,Department of Neurology, Royal Brisbane and Women's Hospital , Brisbane, Australia
| | - Fleur C Garton
- Institute for Molecular Biosciences, The University of Queensland , Brisbane, Australia
| | - Matthew Katz
- Department of Neurology, Royal Brisbane and Women's Hospital , Brisbane, Australia
| | - Naomi R Wray
- Institute for Molecular Biosciences, The University of Queensland , Brisbane, Australia.,Queensland Brain Institute, The University of Queensland , Brisbane, Australia
| | - Robert D Henderson
- Centre for Clinical Research, The University of Queensland , Brisbane, Australia
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15
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Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression. Nat Genet 2020; 52:160-166. [PMID: 31959993 DOI: 10.1038/s41588-019-0556-y] [Citation(s) in RCA: 154] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 11/21/2019] [Indexed: 11/08/2022]
Abstract
Glaucoma, a disease characterized by progressive optic nerve degeneration, can be prevented through timely diagnosis and treatment. We characterize optic nerve photographs of 67,040 UK Biobank participants and use a multitrait genetic model to identify risk loci for glaucoma. A glaucoma polygenic risk score (PRS) enables effective risk stratification in unselected glaucoma cases and modifies penetrance of the MYOC variant encoding p.Gln368Ter, the most common glaucoma-associated myocilin variant. In the unselected glaucoma population, individuals in the top PRS decile reach an absolute risk for glaucoma 10 years earlier than the bottom decile and are at 15-fold increased risk of developing advanced glaucoma (top 10% versus remaining 90%, odds ratio = 4.20). The PRS predicts glaucoma progression in prospectively monitored, early manifest glaucoma cases (P = 0.004) and surgical intervention in advanced disease (P = 3.6 × 10-6). This glaucoma PRS will facilitate the development of a personalized approach for earlier treatment of high-risk individuals, with less intensive monitoring and treatment being possible for lower-risk groups.
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