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Lee S, Hecker J, Hahn G, Mullin K, Lutz SM, Tanzi RE, Lange C, Prokopenko D. On the effect heterogeneity of established disease susceptibility loci for Alzheimer's disease across different genetic ancestries. Alzheimers Dement 2024; 20:3397-3405. [PMID: 38563508 PMCID: PMC11095441 DOI: 10.1002/alz.13796] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 02/14/2024] [Accepted: 02/23/2024] [Indexed: 04/04/2024]
Abstract
INTRODUCTION Genome-wide association studies have identified numerous disease susceptibility loci (DSLs) for Alzheimer's disease (AD). However, only a limited number of studies have investigated the dependence of the genetic effect size of established DSLs on genetic ancestry. METHODS We utilized the whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP) including 35,569 participants. A total of 25,459 subjects in four distinct populations (African ancestry, non-Hispanic White, admixed Hispanic, and Asian) were analyzed. RESULTS We found that nine DSLs showed significant heterogeneity across populations. Single nucleotide polymorphism (SNP) rs2075650 in translocase of outer mitochondrial membrane 40 (TOMM40) showed the largest heterogeneity (Cochran's Q = 0.00, I2 = 90.08), followed by other SNPs in apolipoprotein C1 (APOC1) and apolipoprotein E (APOE). Two additional loci, signal-induced proliferation-associated 1 like 2 (SIPA1L2) and solute carrier 24 member 4 (SLC24A4), showed significant heterogeneity across populations. DISCUSSION We observed substantial heterogeneity for the APOE-harboring 19q13.32 region with TOMM40/APOE/APOC1 genes. The largest risk effect was seen among African Americans, while Asians showed a surprisingly small risk effect.
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Affiliation(s)
- Sanghun Lee
- Department of Medical ConsilienceDivision of MedicineGraduate schoolDankook UniversityYongin‐siGyeonggi‐doSouth Korea
- Channing Division of Network MedicineBrigham and Women's HospitalBostonMassachusettsUSA
- Department of BiostatisticsHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Julian Hecker
- Channing Division of Network MedicineBrigham and Women's HospitalBostonMassachusettsUSA
| | - Georg Hahn
- Department of BiostatisticsHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Kristina Mullin
- Genetics and Aging Unit and McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalCharlestownMassachusettsUSA
| | | | - Sharon M. Lutz
- Department of BiostatisticsHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
- Department of Population MedicineHarvard Medical School and Harvard Pilgrim Healthcare InstituteBostonMassachusettsUSA
| | - Rudolph E. Tanzi
- Genetics and Aging Unit and McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalCharlestownMassachusettsUSA
| | - Christoph Lange
- Channing Division of Network MedicineBrigham and Women's HospitalBostonMassachusettsUSA
- Department of BiostatisticsHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain HealthDepartment of NeurologyMassachusetts General HospitalCharlestownMassachusettsUSA
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Shrine N, Guyatt AL, Erzurumluoglu AM, Jackson VE, Hobbs BD, Melbourne CA, Batini C, Fawcett KA, Song K, Sakornsakolpat P, Li X, Boxall R, Reeve NF, Obeidat M, Zhao JH, Wielscher M, Weiss S, Kentistou KA, Cook JP, Sun BB, Zhou J, Hui J, Karrasch S, Imboden M, Harris SE, Marten J, Enroth S, Kerr SM, Surakka I, Vitart V, Lehtimäki T, Allen RJ, Bakke PS, Beaty TH, Bleecker ER, Bossé Y, Brandsma CA, Chen Z, Crapo JD, Danesh J, DeMeo DL, Dudbridge F, Ewert R, Gieger C, Gulsvik A, Hansell AL, Hao K, Hoffman JD, Hokanson JE, Homuth G, Joshi PK, Joubert P, Langenberg C, Li X, Li L, Lin K, Lind L, Locantore N, Luan J, Mahajan A, Maranville JC, Murray A, Nickle DC, Packer R, Parker MM, Paynton ML, Porteous DJ, Prokopenko D, Qiao D, Rawal R, Runz H, Sayers I, Sin DD, Smith BH, Artigas MS, Sparrow D, Tal-Singer R, Timmers PRHJ, Van den Berge M, Whittaker JC, Woodruff PG, Yerges-Armstrong LM, Troyanskaya OG, Raitakari OT, Kähönen M, Polašek O, Gyllensten U, Rudan I, Deary IJ, Probst-Hensch NM, Schulz H, James AL, Wilson JF, Stubbe B, Zeggini E, Jarvelin MR, Wareham N, Silverman EK, Hayward C, Morris AP, Butterworth AS, Scott RA, Walters RG, Meyers DA, Cho MH, Strachan DP, Hall IP, Tobin MD, Wain LV. Author Correction: New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries. Nat Genet 2024; 56:1032-1033. [PMID: 38641645 DOI: 10.1038/s41588-024-01752-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Affiliation(s)
- Nick Shrine
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Anna L Guyatt
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Victoria E Jackson
- Department of Health Sciences, University of Leicester, Leicester, UK
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia
| | - Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Carl A Melbourne
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Chiara Batini
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Kijoung Song
- Target Sciences, GlaxoSmithKline, Collegeville, PA, USA
| | - Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Xingnan Li
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Ruth Boxall
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Nicola F Reeve
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Ma'en Obeidat
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada
| | - Jing Hua Zhao
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, UK
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Katherine A Kentistou
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - James P Cook
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Benjamin B Sun
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jian Zhou
- Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Jennie Hui
- Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Crawley, Western Australia, Australia
- School of Pathology and Laboratory Medicine, The University of Western Australia, Crawley, Western Australia, Australia
| | - Stefan Karrasch
- Institute of Epidemiology, Helmholtz Zentrum Muenchen-German Research Center for Environmental Health, Neuherberg, Germany
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-Universität, Munich, Germany
- Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Stefan Enroth
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala Universitet, Uppsala, Sweden
| | - Shona M Kerr
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ida Surakka
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- The National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Richard J Allen
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Per S Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins University School of Public Health, Baltimore, MD, USA
| | - Eugene R Bleecker
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Yohan Bossé
- Department of Molecular Medicine, Laval University, Québec, Canada
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Québec, Canada
| | - Corry-Anke Brandsma
- University of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, GRIAC Research Institute, University of Groningen, Groningen, The Netherlands
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - James D Crapo
- National Jewish Health, Denver, CO, USA
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, CO, USA
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cambridge Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK
- Department of Human Genetics, Wellcome Trust Sanger Institute, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Ralf Ewert
- Department of Internal Medicine B - Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany
| | - Amund Gulsvik
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anna L Hansell
- Centre for Environmental Health & Sustainability, University of Leicester, Leicester, UK
- UK Small Area Health Statistics Unit, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - John E Hokanson
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Philippe Joubert
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Québec, Canada
- Department of Molecular Biology, Medical Biochemistry, and Pathology, Laval University, Québec, Canada
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Xuan Li
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada
| | - Liming Li
- Department of Epidemiology & Biostatistics, Peking University Health Science Center, Beijing, China
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Lars Lind
- Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden
| | | | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Alison Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - David C Nickle
- MRL, Merck & Co., Inc, Kenilworth, NJ, USA
- Gossamer Bio, San Diego, CA, USA
| | - Richard Packer
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Margaret M Parker
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Megan L Paynton
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dandi Qiao
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Rajesh Rawal
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Heiko Runz
- MRL, Merck & Co., Inc, Kenilworth, NJ, USA
| | - Ian Sayers
- Division of Respiratory Medicine and NIHR-Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Don D Sin
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada
- Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - María Soler Artigas
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
| | - David Sparrow
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | | | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Maarten Van den Berge
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, GRIAC Research Institute, University of Groningen, Groningen, The Netherlands
| | - John C Whittaker
- Target Sciences - R&D, GSK Medicines Research Centre, Stevenage, UK
| | - Prescott G Woodruff
- UCSF Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | | | - Olga G Troyanskaya
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Ozren Polašek
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- University of Split School of Medicine, Split, Croatia
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala Universitet, Uppsala, Sweden
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Nicole M Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Holger Schulz
- Institute of Epidemiology, Helmholtz Zentrum Muenchen-German Research Center for Environmental Health, Neuherberg, Germany
- Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Alan L James
- Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Beate Stubbe
- Department of Internal Medicine B - Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Eleftheria Zeggini
- Wellcome Sanger Institute, Hinxton, UK
- Institute of Translational Genomics, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UK
| | - Nick Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Robert A Scott
- Target Sciences - R&D, GSK Medicines Research Centre, Stevenage, UK
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Deborah A Meyers
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, UK
| | - Ian P Hall
- Division of Respiratory Medicine and NIHR-Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK.
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
| | - Louise V Wain
- Department of Health Sciences, University of Leicester, Leicester, UK.
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
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Hahn G, Lutz SM, Hecker J, Prokopenko D, Cho MH, Silverman EK, Weiss ST, Lange C. Fast computation of the eigensystem of genomic similarity matrices. BMC Bioinformatics 2024; 25:43. [PMID: 38273228 PMCID: PMC10811951 DOI: 10.1186/s12859-024-05650-8] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 01/11/2024] [Indexed: 01/27/2024] Open
Abstract
The computation of a similarity measure for genomic data is a standard tool in computational genetics. The principal components of such matrices are routinely used to correct for biases due to confounding by population stratification, for instance in linear regressions. However, the calculation of both a similarity matrix and its singular value decomposition (SVD) are computationally intensive. The contribution of this article is threefold. First, we demonstrate that the calculation of three matrices (called the covariance matrix, the weighted Jaccard matrix, and the genomic relationship matrix) can be reformulated in a unified way which allows for the application of a randomized SVD algorithm, which is faster than the traditional computation. The fast SVD algorithm we present is adapted from an existing randomized SVD algorithm and ensures that all computations are carried out in sparse matrix algebra. The algorithm only assumes that row-wise and column-wise subtraction and multiplication of a vector with a sparse matrix is available, an operation that is efficiently implemented in common sparse matrix packages. An exception is the so-called Jaccard matrix, which does not have a structure applicable for the fast SVD algorithm. Second, an approximate Jaccard matrix is introduced to which the fast SVD computation is applicable. Third, we establish guaranteed theoretical bounds on the accuracy (in [Formula: see text] norm and angle) between the principal components of the Jaccard matrix and the ones of our proposed approximation, thus putting the proposed Jaccard approximation on a solid mathematical foundation, and derive the theoretical runtime of our algorithm. We illustrate that the approximation error is low in practice and empirically verify the theoretical runtime scalings on both simulated data and data of the 1000 Genome Project.
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Affiliation(s)
- Georg Hahn
- T.H. Chan School of Public Health, Harvard University, Boston, MA, 02115, USA.
| | - Sharon M Lutz
- T.H. Chan School of Public Health, Harvard University, Boston, MA, 02115, USA
| | - Julian Hecker
- Channing Divsion of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Dmitry Prokopenko
- Massachusetts General Hospital, Harvard University, Boston, MA, 02114, USA
| | - Michael H Cho
- Channing Divsion of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Edwin K Silverman
- Channing Divsion of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Scott T Weiss
- Channing Divsion of Network Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Christoph Lange
- T.H. Chan School of Public Health, Harvard University, Boston, MA, 02115, USA
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Hecker J, Lee S, Kachroo P, Prokopenko D, Maaser-Hecker A, Lutz SM, Hahn G, Irizarry R, Weiss ST, DeMeo DL, Lange C. A consistent pattern of slide effects in Illumina DNA methylation BeadChip array data. Epigenetics 2023; 18:2257437. [PMID: 37731367 PMCID: PMC11062373 DOI: 10.1080/15592294.2023.2257437] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 09/01/2023] [Indexed: 09/22/2023] Open
Abstract
Background: Recent studies have identified thousands of associations between DNA methylation CpGs and complex diseases/traits, emphasizing the critical role of epigenetics in understanding disease aetiology and identifying biomarkers. However, association analyses based on methylation array data are susceptible to batch/slide effects, which can lead to inflated false positive rates or reduced statistical powerResults: We use multiple DNA methylation datasets based on the popular Illumina Infinium MethylationEPIC BeadChip array to describe consistent patterns and the joint distribution of slide effects across CpGs, confirming and extending previous results. The susceptible CpGs overlap with the Illumina Infinium HumanMethylation450 BeadChip array content.Conclusions: Our findings reveal systematic patterns in slide effects. The observations provide further insights into the characteristics of these effects and can improve existing adjustment approaches.
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Affiliation(s)
- Julian Hecker
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Sanghun Lee
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Medical Consilience, Division of Medicine, Graduate School, Dankook University, Yongin-si, South Korea
| | - Priyadarshini Kachroo
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Anna Maaser-Hecker
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Sharon M. Lutz
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Population Medicine, PRecisiOn Medicine Translational Research (PROMoTeR) Center, Harvard Pilgrim Health Care and Harvard Medical School, Boston, MA, USA
| | - Georg Hahn
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rafael Irizarry
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Scott T. Weiss
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Christoph Lange
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Neumann A, Ohlei O, Küçükali F, Bos IJ, Timsina J, Vos S, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Scheltens P, Teunissen CE, Engelborghs S, Frisoni GB, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Marsh TW, Gorijala P, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Van Broeckhoven C, Tanzi RE, Ten Kate M, Lill CM, Barkhof F, Cruchaga C, Lovestone S, Streffer J, Zetterberg H, Visser PJ, Sleegers K, Bertram L. Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning. Genome Med 2023; 15:79. [PMID: 37794492 PMCID: PMC10548686 DOI: 10.1186/s13073-023-01233-z] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 09/12/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences. METHODS We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects. RESULTS Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers. CONCLUSIONS These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.
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Affiliation(s)
- Alexander Neumann
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Isabelle J Bos
- Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Stephanie Vos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospital Leuven, Leuven, Belgium
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Universitair Ziekenhuis Brussel (UZ Brussel) and Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Giovanni B Frisoni
- Memory Center, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Oliver Blin
- Clinical Pharmacology & Pharmacovigilance Department, Marseille University Hospital, Marseille, France
| | | | - Régis Bordet
- Neuroscience & Cognition, CHU de Lille, University of Lille, Inserm, France
| | - Alberto Lleó
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Julius Popp
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zurich, Switzerland
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Thomas W Marsh
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Division of Biology & Biomedical Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Christopher Clark
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zurich, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pablo Martinez-Lage
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Mikel Tainta
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
- Zumarraga Hospital, Osakidetza, Integrated Health Organization (OSI) Goierri-Urola Garia, Basque Country, Spain
| | - Richard J B Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Boston, UK
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
- Health Data Research UK London, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - Cristina Legido-Quigley
- Steno Diabetes Center, Copenhagen, Denmark
- Institute of Pharmaceutical Science, King's College London, London, UK
| | - Christine Van Broeckhoven
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Mara Ten Kate
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Simon Lovestone
- Janssen Medical Ltd, Wycombe, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Johannes Streffer
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- AC Immune SA, Lausanne, Switzerland
- Janssen R&D, LLC, Beerse, Belgium
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute, University College London, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Pieter Jelle Visser
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany.
- Centre for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
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6
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Jorfi M, Park J, Hall CK, Lin CCJ, Chen M, von Maydell D, Kruskop JM, Kang B, Choi Y, Prokopenko D, Irimia D, Kim DY, Tanzi RE. Infiltrating CD8 + T cells exacerbate Alzheimer's disease pathology in a 3D human neuroimmune axis model. Nat Neurosci 2023; 26:1489-1504. [PMID: 37620442 DOI: 10.1038/s41593-023-01415-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 07/18/2023] [Indexed: 08/26/2023]
Abstract
Brain infiltration of peripheral immune cells and their interactions with brain-resident cells may contribute to Alzheimer's disease (AD) pathology. To examine these interactions, in the present study we developed a three-dimensional human neuroimmune axis model comprising stem cell-derived neurons, astrocytes and microglia, together with peripheral immune cells. We observed an increase in the number of T cells (but not B cells) and monocytes selectively infiltrating into AD relative to control cultures. Infiltration of CD8+ T cells into AD cultures led to increased microglial activation, neuroinflammation and neurodegeneration. Using single-cell RNA-sequencing, we identified that infiltration of T cells into AD cultures led to induction of interferon-γ and neuroinflammatory pathways in glial cells. We found key roles for the C-X-C motif chemokine ligand 10 (CXCL10) and its receptor, CXCR3, in regulating T cell infiltration and neuronal damage in AD cultures. This human neuroimmune axis model is a useful tool to study the effects of peripheral immune cells in brain disease.
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Affiliation(s)
- Mehdi Jorfi
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Center for Engineering in Medicine and Surgery, Massachusetts General Hospital, Charlestown, MA, USA.
| | - Joseph Park
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Clare K Hall
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Chih-Chung Jerry Lin
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Meng Chen
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Djuna von Maydell
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Jane M Kruskop
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Byunghoon Kang
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Younjung Choi
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Daniel Irimia
- Harvard Medical School, Boston, MA, USA
- Center for Engineering in Medicine and Surgery, Massachusetts General Hospital, Charlestown, MA, USA
- Shriners Burns Hospital, Boston, MA, USA
| | - Doo Yeon Kim
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA.
- Harvard Medical School, Boston, MA, USA.
| | - Rudolph E Tanzi
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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7
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Lee S, Hahn G, Hecker J, Lutz SM, Mullin K, Hide W, Bertram L, DeMeo DL, Tanzi RE, Lange C, Prokopenko D. A comparison between similarity matrices for principal component analysis to assess population stratification in sequenced genetic data sets. Brief Bioinform 2023; 24:bbac611. [PMID: 36585781 PMCID: PMC9851291 DOI: 10.1093/bib/bbac611] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [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: 09/13/2022] [Revised: 12/07/2022] [Accepted: 12/11/2022] [Indexed: 01/01/2023] Open
Abstract
Genetic similarity matrices are commonly used to assess population substructure (PS) in genetic studies. Through simulation studies and by the application to whole-genome sequencing (WGS) data, we evaluate the performance of three genetic similarity matrices: the unweighted and weighted Jaccard similarity matrices and the genetic relationship matrix. We describe different scenarios that can create numerical pitfalls and lead to incorrect conclusions in some instances. We consider scenarios in which PS is assessed based on loci that are located across the genome ('globally') and based on loci from a specific genomic region ('locally'). We also compare scenarios in which PS is evaluated based on loci from different minor allele frequency bins: common (>5%), low-frequency (5-0.5%) and rare (<0.5%) single-nucleotide variations (SNVs). Overall, we observe that all approaches provide the best clustering performance when computed based on rare SNVs. The performance of the similarity matrices is very similar for common and low-frequency variants, but for rare variants, the unweighted Jaccard matrix provides preferable clustering features. Based on visual inspection and in terms of standard clustering metrics, its clusters are the densest and the best separated in the principal component analysis of variants with rare SNVs compared with the other methods and different allele frequency cutoffs. In an application, we assessed the role of rare variants on local and global PS, using WGS data from multiethnic Alzheimer's disease data sets and European or East Asian populations from the 1000 Genome Project.
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Affiliation(s)
- Sanghun Lee
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medical Consilience, Division of Medicine, Graduate school, Dankook University, South Korea
- NH Institute for Natural Product Research, Myungji Hospital, South Korea
| | - Georg Hahn
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Julian Hecker
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Sharon M Lutz
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Kristina Mullin
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Winston Hide
- Harvard Medical School, Boston, MA, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Rudolph E Tanzi
- Harvard Medical School, Boston, MA, USA
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Christoph Lange
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Dmitry Prokopenko
- Harvard Medical School, Boston, MA, USA
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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Lee S, Prokopenko D, Kelly RS, Lutz S, Ann Lasky-Su J, Cho MH, Laurie C, Celedón JC, Lange C, Weiss ST, Hecker J, DeMeo DL. Zinc finger protein 33B demonstrates sex interaction with atopy-related markers in childhood asthma. Eur Respir J 2023; 61:2200479. [PMID: 35953101 PMCID: PMC10124713 DOI: 10.1183/13993003.00479-2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 03/05/2022] [Accepted: 07/14/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Sex differences related to immune responses can influence atopic manifestations in childhood asthma. While genome-wide association studies have investigated a sex-specific genetic architecture of the immune response, gene-by-sex interactions have not been extensively analysed for atopy-related markers including allergy skin tests, IgE and eosinophils in asthmatic children. METHODS We performed a genome-wide gene-by-sex interaction analysis for atopy-related markers using whole-genome sequencing data based on 889 trios from the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) and 284 trios from the Childhood Asthma Management Program (CAMP). We also tested the findings in UK Biobank participants with self-reported childhood asthma. Furthermore, downstream analyses in GACRS integrated gene expression to disentangle observed associations. RESULTS Single nucleotide polymorphism (SNP) rs1255383 at 10q11.21 demonstrated a genome-wide significant gene-by-sex interaction (pinteraction=9.08×10-10) for atopy (positive skin test) with opposite direction of effects between females and males. In the UK Biobank participants with a history of childhood asthma, the signal was consistently observed with the same sex-specific effect directions for high eosinophil count (pinteraction=0.0058). Gene expression of ZNF33B (zinc finger protein 33B), located at 10q11.21, was moderately associated with atopy in girls, but not in boys. CONCLUSIONS We report SNPs in/near a zinc finger gene as novel sex-differential loci for atopy-related markers with opposite effect directions in females and males. A potential role for ZNF33B should be studied further as an important driver of sex-divergent features of atopy in childhood asthma.
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Affiliation(s)
- Sanghun Lee
- Department of Medical Consilience, Division of Medicine, Graduate School, Dankook University, Yongin, South Korea
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- NH Institute for Natural Product Research, Myungji Hospital, Goyang-si, South Korea
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Rachel S Kelly
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Sharon Lutz
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jessica Ann Lasky-Su
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Cecelia Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Juan C Celedón
- Division of Pediatric Pulmonary Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA
| | - Christoph Lange
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Scott T Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Julian Hecker
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
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Hahn G, Lee S, Prokopenko D, Abraham J, Novak T, Hecker J, Cho M, Khurana S, Baden LR, Randolph AG, Weiss ST, Lange C. Unsupervised outlier detection applied to SARS-CoV-2 nucleotide sequences can identify sequences of common variants and other variants of interest. BMC Bioinformatics 2022; 23:547. [PMID: 36536276 PMCID: PMC9761049 DOI: 10.1186/s12859-022-05105-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 12/07/2022] [Indexed: 12/23/2022] Open
Abstract
As of June 2022, the GISAID database contains more than 11 million SARS-CoV-2 genomes, including several thousand nucleotide sequences for the most common variants such as delta or omicron. These SARS-CoV-2 strains have been collected from patients around the world since the beginning of the pandemic. We start by assessing the similarity of all pairs of nucleotide sequences using the Jaccard index and principal component analysis. As shown previously in the literature, an unsupervised cluster analysis applied to the SARS-CoV-2 genomes results in clusters of sequences according to certain characteristics such as their strain or their clade. Importantly, we observe that nucleotide sequences of common variants are often outliers in clusters of sequences stemming from variants identified earlier on during the pandemic. Motivated by this finding, we are interested in applying outlier detection to nucleotide sequences. We demonstrate that nucleotide sequences of common variants (such as alpha, delta, or omicron) can be identified solely based on a statistical outlier criterion. We argue that outlier detection might be a useful surveillance tool to identify emerging variants in real time as the pandemic progresses.
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Affiliation(s)
- Georg Hahn
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, 02115, USA.
| | - Sanghun Lee
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, 02115, USA
- Department of Medical Consilience, Graduate School, Dankook University, Yongin, South Korea
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit, Department of Neurology, McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Jonathan Abraham
- Department of Microbiology, Harvard Medical School, Blavatnik Institute, 77 Avenue Louis Pasteur, Boston, MA, 02115, USA
| | - Tanya Novak
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Julian Hecker
- Harvard Medical School, Harvard University, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Michael Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | | | - Lindsey R Baden
- Division of Infectious Diseases, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Adrienne G Randolph
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Boston, MA, 02115, USA
- Harvard Medical School, Harvard University, Boston, MA, 02115, USA
| | - Scott T Weiss
- Harvard Medical School, Harvard University, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Christoph Lange
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, MA, 02115, USA
- Harvard Medical School, Harvard University, Boston, MA, 02115, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA
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10
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Hecker J, Prokopenko D, Moll M, Lee S, Kim W, Qiao D, Voorhies K, Kim W, Vansteelandt S, Hobbs BD, Cho MH, Silverman EK, Lutz SM, DeMeo DL, Weiss ST, Lange C. A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables. PLoS Genet 2022; 18:e1010464. [PMID: 36383614 PMCID: PMC9668174 DOI: 10.1371/journal.pgen.1010464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 10/04/2022] [Indexed: 11/17/2022] Open
Abstract
The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since a.) statistical power is often limited and b.) modeling of environmental effects is nontrivial and such model misspecifications can lead to false positive interaction findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy can increase the power to detect interactions, identifying contributing genes and pathways is difficult based on these relatively global results. Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate sets of genetic variants and/or multiple environmental factors. Based on the user's choice of statistical/machine learning approaches, a screening step selects and combines potential interactions into scores with improved interpretability. In the testing step, the application of robust statistics minimizes the susceptibility to main effect misspecifications. Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios, and we show how the screening strategy influences statistical power. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified highly significant interactions based on subcomponents of genetic risk scores. While the contributing single variant interaction signals are weak, our results indicate interaction patterns that result in strong aggregated effects, providing potential insights into underlying gene-environment interaction mechanisms.
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Affiliation(s)
- Julian Hecker
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Dmitry Prokopenko
- Harvard Medical School, Boston, Massachusetts, United States of America
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Matthew Moll
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Sanghun Lee
- Department of Medical Consilience, Division of Medicine, Graduate School, Dankook University, Yongin, South Korea
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Wonji Kim
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Dandi Qiao
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Kirsten Voorhies
- Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Population Medicine, PRecisiOn Medicine Translational Research (PROMoTeR) Center, Harvard Pilgrim Health Care, Boston, Massachusetts, United States of America
| | - Woori Kim
- Harvard Medical School, Boston, Massachusetts, United States of America
- Systems Biology and Computer Science Program, Ann Romney Center for Neurological Diseases, Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Stijn Vansteelandt
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Gent, Belgium
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Brian D. Hobbs
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Michael H. Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Sharon M. Lutz
- Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Population Medicine, PRecisiOn Medicine Translational Research (PROMoTeR) Center, Harvard Pilgrim Health Care, Boston, Massachusetts, United States of America
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Scott T. Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Christoph Lange
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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11
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Lopatko Lindman K, Jonsson C, Weidung B, Olsson J, Pandey JP, Prokopenko D, Tanzi RE, Hallmans G, Eriksson S, Elgh F, Lövheim H. PILRA polymorphism modifies the effect of APOE4 and GM17 on Alzheimer's disease risk. Sci Rep 2022; 12:13264. [PMID: 35918447 PMCID: PMC9346002 DOI: 10.1038/s41598-022-17058-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 07/20/2022] [Indexed: 11/13/2022] Open
Abstract
PILRA (rs1859788 A > G) has been suggested to be a protective variant for Alzheimer's disease (AD) and is an entry co-receptor for herpes simplex virus-1. We conducted a nested case-control study of 360 1:1-matched AD subjects. Interactions between the PILRA-A allele, APOE risk variants (ε3/ε4 or ε4/ε4) and GM17 for AD risk were modelled. The associations were cross-validated using two independent whole-genome sequencing datasets. We found negative interactions between PILRA-A and GM17 (OR 0.72, 95% CI 0.52-1.00) and between PILRA-A and APOE risk variants (OR 0.56, 95% CI 0.32-0.98) in the discovery dataset. In the replication cohort, a joint effect of PILRA and PILRA × GM 17/17 was observed for the risk of developing AD (p .02). Here, we report a negative effect modification by PILRA on APOE and GM17 high-risk variants for future AD risk in two independent datasets. This highlights the complex genetics of AD.
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Affiliation(s)
- Karin Lopatko Lindman
- Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University, 901 85, Umeå, Sweden.
| | - Caroline Jonsson
- grid.12650.300000 0001 1034 3451Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University, 901 85 Umeå, Sweden
| | - Bodil Weidung
- grid.12650.300000 0001 1034 3451Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University, 901 85 Umeå, Sweden ,grid.8993.b0000 0004 1936 9457Department of Public Health and Caring Sciences, Geriatric Medicine, Uppsala University, Uppsala, Sweden
| | - Jan Olsson
- grid.12650.300000 0001 1034 3451Department of Clinical Microbiology, Umeå University, Umeå, Sweden
| | - Janardan P. Pandey
- grid.259828.c0000 0001 2189 3475Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, USA
| | - Dmitry Prokopenko
- grid.32224.350000 0004 0386 9924Genetics and Aging Unit, Department of Neurology, McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Rudolph E. Tanzi
- grid.32224.350000 0004 0386 9924Genetics and Aging Unit, Department of Neurology, McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Göran Hallmans
- grid.12650.300000 0001 1034 3451Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Sture Eriksson
- grid.12650.300000 0001 1034 3451Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University, 901 85 Umeå, Sweden ,grid.12650.300000 0001 1034 3451Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Fredrik Elgh
- grid.12650.300000 0001 1034 3451Department of Clinical Microbiology, Umeå University, Umeå, Sweden
| | - Hugo Lövheim
- grid.12650.300000 0001 1034 3451Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University, 901 85 Umeå, Sweden ,grid.12650.300000 0001 1034 3451Wallenberg Centre for Molecular Medicine (WCMM), Umeå University, Umeå, Sweden
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12
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Morgan SL, Naderi P, Koler K, Pita-Juarez Y, Prokopenko D, Vlachos IS, Tanzi RE, Bertram L, Hide WA. Most Pathways Can Be Related to the Pathogenesis of Alzheimer’s Disease. Front Aging Neurosci 2022; 14:846902. [PMID: 35813951 PMCID: PMC9263183 DOI: 10.3389/fnagi.2022.846902] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 04/11/2022] [Indexed: 11/18/2022] Open
Abstract
Alzheimer’s disease (AD) is a complex neurodegenerative disorder. The relative contribution of the numerous underlying functional mechanisms is poorly understood. To comprehensively understand the context and distribution of pathways that contribute to AD, we performed text-mining to generate an exhaustive, systematic assessment of the breadth and diversity of biological pathways within a corpus of 206,324 dementia publication abstracts. A total of 91% (325/335) of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways have publications containing an association via at least 5 studies, while 63% of pathway terms have at least 50 studies providing a clear association with AD. Despite major technological advances, the same set of top-ranked pathways have been consistently related to AD for 30 years, including AD, immune system, metabolic pathways, cholinergic synapse, long-term depression, proteasome, diabetes, cancer, and chemokine signaling. AD pathways studied appear biased: animal model and human subject studies prioritize different AD pathways. Surprisingly, human genetic discoveries and drug targeting are not enriched in the most frequently studied pathways. Our findings suggest that not only is this disorder incredibly complex, but that its functional reach is also nearly global. As a consequence of our study, research results can now be assessed in the context of the wider AD literature, supporting the design of drug therapies that target a broader range of mechanisms. The results of this study can be explored at www.adpathways.org.
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Affiliation(s)
- Sarah L. Morgan
- Harvard Medical School Initiative for RNA Medicine, Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- Blizard Institute, Department of Neuroscience, Surgery and Trauma, Queen Mary University of London, London, United Kingdom
| | - Pourya Naderi
- Harvard Medical School Initiative for RNA Medicine, Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Katjuša Koler
- Department of Computer Science, The University of Sheffield, Sheffield, United Kingdom
| | - Yered Pita-Juarez
- Harvard Medical School Initiative for RNA Medicine, Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Dmitry Prokopenko
- Harvard Medical School, Boston, MA, United States
- Genetics and Aging Research Unit, The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Ioannis S. Vlachos
- Harvard Medical School Initiative for RNA Medicine, Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Rudolph E. Tanzi
- Harvard Medical School, Boston, MA, United States
- Genetics and Aging Research Unit, The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo, Norway
| | - Winston A. Hide
- Harvard Medical School Initiative for RNA Medicine, Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- *Correspondence: Winston A. Hide,
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13
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Gauron MC, Lorden G, Prokopenko D, Tanzi R, Newton A. Novel PKC signaling in Alzheimer’s Disease. FASEB J 2022. [DOI: 10.1096/fasebj.2022.36.s1.r3731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- M. C. Gauron
- PharmacologyUniversity of California at San DiegoSan DiegoCA
| | - Gema Lorden
- PharmacologyUniversity of California at San DiegoSan DiegoCA
| | - Dmitry Prokopenko
- Department of NeurologyGenetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Massachusetts General HospitalBostonMA
- Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Massachusetts General HospitalBostonMA
| | - Rudolph Tanzi
- Department of NeurologyGenetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Massachusetts General HospitalBostonMA
- Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Massachusetts General HospitalBostonMA
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14
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Prokopenko D, Morgan SL, Lange C, Hide W, Bertram L, Tanzi RE. Reply to Neupane et al.: Replication study of AD-associated rare variants. Alzheimers Dement 2022; 18:863-864. [PMID: 35142036 PMCID: PMC9302627 DOI: 10.1002/alz.12584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 12/14/2021] [Indexed: 11/08/2022]
Affiliation(s)
- Dmitry Prokopenko
- Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Sarah L Morgan
- Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, US.,Blizard Institute, Queen Mary University of London, London, UK
| | - Christoph Lange
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, US
| | - Winston Hide
- Harvard Medical School, Boston, MA, USA.,Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, US.,Department of Neuroscience, Sheffield Institute for Translational Neurosciences, University of Sheffield, Sheffield, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Germany.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Rudolph E Tanzi
- Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
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15
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Hahn G, Prokopenko D, Lutz SM, Mullin K, Tanzi RE, Cho MH, Silverman EK, Lange C. A Smoothed Version of the Lassosum Penalty for Fitting Integrated Risk Models Using Summary Statistics or Individual-Level Data. Genes (Basel) 2022; 13:genes13010112. [PMID: 35052450 PMCID: PMC8775060 DOI: 10.3390/genes13010112] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 01/03/2022] [Accepted: 01/04/2022] [Indexed: 02/04/2023] Open
Abstract
Polygenic risk scores are a popular means to predict the disease risk or disease susceptibility of an individual based on its genotype information. When adding other important epidemiological covariates such as age or sex, we speak of an integrated risk model. Methodological advances for fitting more accurate integrated risk models are of immediate importance to improve the precision of risk prediction, thereby potentially identifying patients at high risk early on when they are still able to benefit from preventive steps/interventions targeted at increasing their odds of survival, or at reducing their chance of getting a disease in the first place. This article proposes a smoothed version of the “Lassosum” penalty used to fit polygenic risk scores and integrated risk models using either summary statistics or raw data. The smoothing allows one to obtain explicit gradients everywhere for efficient minimization of the Lassosum objective function while guaranteeing bounds on the accuracy of the fit. An experimental section on both Alzheimer’s disease and COPD (chronic obstructive pulmonary disease) demonstrates the increased accuracy of the proposed smoothed Lassosum penalty compared to the original Lassosum algorithm (for the datasets under consideration), allowing it to draw equal with state-of-the-art methodology such as LDpred2 when evaluated via the AUC (area under the ROC curve) metric.
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Affiliation(s)
- Georg Hahn
- Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, MA 02115, USA; (S.M.L.); (C.L.)
- Correspondence:
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit, McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA; (D.P.); (K.M.); (R.E.T.)
| | - Sharon M. Lutz
- Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, MA 02115, USA; (S.M.L.); (C.L.)
| | - Kristina Mullin
- Genetics and Aging Research Unit, McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA; (D.P.); (K.M.); (R.E.T.)
| | - Rudolph E. Tanzi
- Genetics and Aging Research Unit, McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA; (D.P.); (K.M.); (R.E.T.)
| | - Michael H. Cho
- Department of Medicine, Brigham and Women’s Hospital, Harvard University, Boston, MA 02115, USA; (M.H.C.); (E.K.S.)
| | - Edwin K. Silverman
- Department of Medicine, Brigham and Women’s Hospital, Harvard University, Boston, MA 02115, USA; (M.H.C.); (E.K.S.)
| | - Christoph Lange
- Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, MA 02115, USA; (S.M.L.); (C.L.)
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16
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Prokopenko D, Lee S, Hecker J, Mullin K, Morgan S, Katsumata Y, Weiner MW, Fardo DW, Laird N, Bertram L, Hide W, Lange C, Tanzi RE. Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer's disease-associated genes: DTNB and DLG2. Mol Psychiatry 2022; 27:1963-1969. [PMID: 35246634 PMCID: PMC9126808 DOI: 10.1038/s41380-022-01475-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 01/25/2022] [Accepted: 02/04/2022] [Indexed: 01/01/2023]
Abstract
Alzheimer's disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency <0.01) associated with AD in a region-based, whole-genome sequencing (WGS) association study (rvGWAS) of two independent AD family datasets (NIMH/NIA; 2247 individuals; 605 families). Employing a sliding window approach across the genome, we identified several regions that achieved association p values <10-6, using the burden test or the SKAT statistic. The genomic region around the dystobrevin beta (DTNB) gene was identified with the burden and SKAT test and replicated in case/control samples from the ADSP study reaching genome-wide significance after meta-analysis (pmeta = 4.74 × 10-8). SKAT analysis also revealed region-based association around the Discs large homolog 2 (DLG2) gene and replicated in case/control samples from the ADSP study (pmeta = 1 × 10-6). In conclusion, in a region-based rvGWAS of AD we identified two novel AD genes, DLG2 and DTNB, based on association with rare variants.
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Affiliation(s)
- Dmitry Prokopenko
- grid.32224.350000 0004 0386 9924Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Sanghun Lee
- grid.411982.70000 0001 0705 4288Department of Medical Consilience, Graduate School, Dankook University, Yongin, South Korea ,grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Julian Hecker
- grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA ,grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA USA
| | - Kristina Mullin
- grid.32224.350000 0004 0386 9924Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA USA
| | - Sarah Morgan
- grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA ,grid.239395.70000 0000 9011 8547Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA USA
| | - Yuriko Katsumata
- grid.266539.d0000 0004 1936 8438Department of Biostatistics, University of Kentucky, Lexington, KY USA ,grid.266539.d0000 0004 1936 8438Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY USA
| | | | - Michael W. Weiner
- grid.266102.10000 0001 2297 6811Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA USA
| | - David W. Fardo
- grid.266539.d0000 0004 1936 8438Department of Biostatistics, University of Kentucky, Lexington, KY USA ,grid.266539.d0000 0004 1936 8438Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY USA
| | - Nan Laird
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Lars Bertram
- grid.4562.50000 0001 0057 2672Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway
| | - Winston Hide
- grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA ,grid.239395.70000 0000 9011 8547Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA USA
| | - Christoph Lange
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Rudolph E. Tanzi
- grid.32224.350000 0004 0386 9924Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
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17
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Zhang X, Zhang C, Prokopenko D, Liang Y, Han W, Tanzi RE, Sisodia SS. Negative evidence for a role of APH1B T27I variant in Alzheimer's disease. Hum Mol Genet 2021; 29:955-966. [PMID: 31995180 DOI: 10.1093/hmg/ddaa017] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 01/15/2020] [Accepted: 01/23/2020] [Indexed: 01/10/2023] Open
Abstract
γ-secretase is a macromolecular complex that catalyzes intramembranous hydrolysis of more than 100 membrane-bound substrates. The complex is composed of presenilin (PS1 or PS2), anterior pharynx defect-1 (APH-1), nicastrin (NCT) and PEN-2 and early-onset; autosomal dominant forms of Alzheimer's disease (AD) are caused by inheritance of mutations of PS. No mutations in genes encoding NCT, or PEN-2 have been identified to date that cause AD. In this regard, a large genetic meta-analysis of four cohorts consisting of more than 600 000 individuals identified a common missense variant, rs117618017 in the APH1B gene that results in a T27I mutation, as a novel genome-wide significant locus. In order to confirm the findings that rs117618017 is associated with risk of AD, we performed a genetic screen from deep whole genome sequencing of the large NIMH family-based Alzheimer's Disease (AD) dataset. In parallel, we sought to uncover potential molecular mechanism(s) by which APH-1B T27I might be associated with AD by generating stable HEK293 cell lines, wherein endogenous APH-1A and APH-1B expression was silenced and into which either the wild type APH-1B or the APH-1B T27I variant was stably expressed. We then tested the impact of expressing either the wild type APH-1B or the APH-1B T27I variant on γ-secretase processing of human APP, the murine Notch derivative mNΔE and human neuregulin-1. We now report that we fail to confirm the association of rs1047552 with AD in our cohort and that cells expressing the APH-1B T27I variant show no discernable impact on the γ-secretase processing of established substrates compared with cells expressing wild-type APH-1B.
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Affiliation(s)
- Xulun Zhang
- Department of Neurobiology, The University of Chicago, Chicago, IL 60637, USA
| | - Can Zhang
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA 02114, USA
| | - Dmitry Prokopenko
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA 02114, USA
| | - Yingxia Liang
- Department of Neurobiology, The University of Chicago, Chicago, IL 60637, USA
| | - Weinong Han
- Department of Neurobiology, The University of Chicago, Chicago, IL 60637, USA
| | - Rudolph E Tanzi
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA 02114, USA
| | - Sangram S Sisodia
- Department of Neurobiology, The University of Chicago, Chicago, IL 60637, USA
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18
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Cuddy LK, Prokopenko D, Cunningham EP, Brimberry R, Song P, Kirchner R, Chapman BA, Hofmann O, Hide W, Procissi D, Hanania T, Leiser SC, Tanzi RE, Vassar R. Aβ-accelerated neurodegeneration caused by Alzheimer's-associated ACE variant R1279Q is rescued by angiotensin system inhibition in mice. Sci Transl Med 2021; 12:12/563/eaaz2541. [PMID: 32998969 DOI: 10.1126/scitranslmed.aaz2541] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 05/06/2020] [Indexed: 12/18/2022]
Abstract
Recent genome-wide association studies identified the angiotensin-converting enzyme gene (ACE) as an Alzheimer's disease (AD) risk locus. However, the pathogenic mechanism by which ACE causes AD is unknown. Using whole-genome sequencing, we identified rare ACE coding variants in AD families and investigated one, ACE1 R1279Q, in knockin (KI) mice. Similar to AD, ACE1 was increased in neurons, but not microglia or astrocytes, of KI brains, which became elevated further with age. Angiotensin II (angII) and angII receptor AT1R signaling were also increased in KI brains. Autosomal dominant neurodegeneration and neuroinflammation occurred with aging in KI hippocampus, which were absent in the cortex and cerebellum. Female KI mice exhibited greater hippocampal electroencephalograph disruption and memory impairment compared to males. ACE variant effects were more pronounced in female KI mice, suggesting a mechanism for higher AD risk in women. Hippocampal neurodegeneration was completely rescued by treatment with brain-penetrant drugs that inhibit ACE1 and AT1R. Although ACE variant-induced neurodegeneration did not depend on β-amyloid (Aβ) pathology, amyloidosis in 5XFAD mice crossed to KI mice accelerated neurodegeneration and neuroinflammation, whereas Aβ deposition was unchanged. KI mice had normal blood pressure and cerebrovascular functions. Our findings strongly suggest that increased ACE1/angII signaling causes aging-dependent, Aβ-accelerated selective hippocampal neuron vulnerability and female susceptibility, hallmarks of AD that have hitherto been enigmatic. We conclude that repurposed brain-penetrant ACE inhibitors and AT1R blockers may protect against AD.
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Affiliation(s)
- Leah K Cuddy
- Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA 02129, USA
| | - Eric P Cunningham
- Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Ross Brimberry
- Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Peter Song
- Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Rory Kirchner
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Brad A Chapman
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Oliver Hofmann
- Department of Clinical Pathology, University of Melbourne, Victoria 3000, Melbourne, Australia
| | - Winston Hide
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Daniele Procissi
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | | | | | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA 02129, USA.
| | - Robert Vassar
- Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA. .,Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
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19
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Lomoio S, Willen R, Kim W, Ho KZ, Robinson EK, Prokopenko D, Kennedy ME, Tanzi RE, Tesco G. Gga3 deletion and a GGA3 rare variant associated with late onset Alzheimer's disease trigger BACE1 accumulation in axonal swellings. Sci Transl Med 2021; 12:12/570/eaba1871. [PMID: 33208500 DOI: 10.1126/scitranslmed.aba1871] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 05/18/2020] [Accepted: 08/03/2020] [Indexed: 12/13/2022]
Abstract
Axonal dystrophy, indicative of perturbed axonal transport, occurs early during Alzheimer's disease (AD) pathogenesis. Little is known about the mechanisms underlying this initial sign of the pathology. This study proves that Golgi-localized γ-ear-containing ARF binding protein 3 (GGA3) loss of function, due to Gga3 genetic deletion or a GGA3 rare variant that cosegregates with late-onset AD, disrupts the axonal trafficking of the β-site APP-cleaving enzyme 1 (BACE1) resulting in its accumulation in axonal swellings in cultured neurons and in vivo. We show that BACE pharmacological inhibition ameliorates BACE1 axonal trafficking and diminishes axonal dystrophies in Gga3 null neurons in vitro and in vivo. These data indicate that axonal accumulation of BACE1 engendered by GGA3 loss of function results in local toxicity leading to axonopathy. Gga3 deletion exacerbates axonal dystrophies in a mouse model of AD before β-amyloid (Aβ) deposition. Our study strongly supports a role for GGA3 in AD pathogenesis, where GGA3 loss of function triggers BACE1 axonal accumulation independently of extracellular Aβ, and initiates a cascade of events leading to the axonal damage distinctive of the early stage of AD.
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Affiliation(s)
- Selene Lomoio
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Rachel Willen
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA
| | - WonHee Kim
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Kevin Z Ho
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Edward K Robinson
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | | | - Rudolph E Tanzi
- Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - Giuseppina Tesco
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA.
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20
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Hong S, Dobricic V, Ohlei O, Bos I, Vos SJB, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Gabel S, Scheltens P, Teunissen CE, Engelborghs S, Frisoni G, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Tanzi RE, Ten Kate M, Wittig M, Franke A, Lill CM, Barkhof F, Lovestone S, Streffer J, Zetterberg H, Visser PJ, Bertram L. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels. Alzheimers Dement 2021; 17:1628-1640. [PMID: 33991015 DOI: 10.1002/alz.12330] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [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: 07/08/2020] [Revised: 01/16/2021] [Accepted: 02/13/2021] [Indexed: 12/18/2022]
Abstract
INTRODUCTION Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. METHODS We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates. RESULTS We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1. DISCUSSION Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.
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Affiliation(s)
- Shengjun Hong
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Isabelle Bos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Ulf Andreasson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Neurology Service, University Hospital Leuven, Leuven, Belgium
| | - Silvy Gabel
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, the Netherlands
| | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.,Department of Neurology and Center for Neurosciences, UZ Brussel and Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Giovanni Frisoni
- University of Geneva, Geneva, Switzerland.,IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- AIX Marseille University, INS, Ap-hm, Marseille, France
| | | | - Regis Bordet
- Inserm, CHU Lille, University of Lille, Lille, France
| | | | - Alberto Lleó
- Memory Unit, Neurology Department. Hospital de Sant Pau, Barcelona and Centro de Investigación Biomédica en Red en enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Memory Unit, Neurology Department. Hospital de Sant Pau, Barcelona and Centro de Investigación Biomédica en Red en enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Julius Popp
- Centre for Gerontopsychiatric Medicine, Department of Geriatric Psychiatry, University Hospital of Psychiatry Zurich, Zürich, Switzerland.,Old Age Psychiatry, Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Christopher Clark
- Centre for Gerontopsychiatric Medicine, Department of Geriatric Psychiatry, University Hospital of Psychiatry Zurich, Zürich, Switzerland
| | - Gwendoline Peyratout
- Old Age Psychiatry, Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pablo Martinez-Lage
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Mikel Tainta
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Richard J B Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK.,Health Data Research UK London, University College London, London, UK.,Institute of Health Informatics, University College London, London, UK.,The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - Cristina Legido-Quigley
- Steno Diabetes Center, Copenhagen, Denmark and Institute of Pharmaceutical Sciences, King's College London, London, UK
| | - Kristel Sleegers
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium.,Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Christine Van Broeckhoven
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium.,Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Mara Ten Kate
- Alzheimer Center and Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, Amsterdam, the Netherlands.,Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Michael Wittig
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.,Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, United Kingdom
| | - Frederik Barkhof
- Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | | | - Johannes Streffer
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.,Translational Medicine Neuroscience, UCB Biopharma SPRL, Braine l'Alleud, Belgium
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, the Netherlands.,Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Instutet, Stockholm, Sweden
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany.,Department of Psychology, University of Oslo, Oslo, Norway
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21
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Prokopenko D, Morgan SL, Mullin K, Hofmann O, Chapman B, Kirchner R, Amberkar S, Wohlers I, Lange C, Hide W, Bertram L, Tanzi RE. Whole-genome sequencing reveals new Alzheimer's disease-associated rare variants in loci related to synaptic function and neuronal development. Alzheimers Dement 2021; 17:1509-1527. [PMID: 33797837 PMCID: PMC8519060 DOI: 10.1002/alz.12319] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 12/12/2022]
Abstract
Introduction Genome‐wide association studies have led to numerous genetic loci associated with Alzheimer's disease (AD). Whole‐genome sequencing (WGS) now permits genome‐wide analyses to identify rare variants contributing to AD risk. Methods We performed single‐variant and spatial clustering–based testing on rare variants (minor allele frequency [MAF] ≤1%) in a family‐based WGS‐based association study of 2247 subjects from 605 multiplex AD families, followed by replication in 1669 unrelated individuals. Results We identified 13 new AD candidate loci that yielded consistent rare‐variant signals in discovery and replication cohorts (4 from single‐variant, 9 from spatial‐clustering), implicating these genes: FNBP1L, SEL1L, LINC00298, PRKCH, C15ORF41, C2CD3, KIF2A, APC, LHX9, NALCN, CTNNA2, SYTL3, and CLSTN2. Discussion Downstream analyses of these novel loci highlight synaptic function, in contrast to common AD‐associated variants, which implicate innate immunity and amyloid processing. These loci have not been associated previously with AD, emphasizing the ability of WGS to identify AD‐associated rare variants, particularly outside of the exome.
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Affiliation(s)
- Dmitry Prokopenko
- Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Sarah L Morgan
- Department of Neuroscience, Sheffield Institute for Translational Neurosciences, University of Sheffield, Sheffield, UK.,Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, Massachusetts, USA
| | - Kristina Mullin
- Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Oliver Hofmann
- Department of Clinical Pathology, University of Melbourne, Melbourne, VIC, Australia
| | - Brad Chapman
- Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Rory Kirchner
- Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | | | - Sandeep Amberkar
- Department of Neuroscience, Sheffield Institute for Translational Neurosciences, University of Sheffield, Sheffield, UK
| | - Inken Wohlers
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Christoph Lange
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Winston Hide
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Neuroscience, Sheffield Institute for Translational Neurosciences, University of Sheffield, Sheffield, UK.,Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, Massachusetts, USA
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Rudolph E Tanzi
- Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
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22
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Zhang X, Zhang CM, Prokopenko D, Liang Y, Zhen SY, Weigle IQ, Han W, Aryal M, Tanzi RE, Sisodia SS. An APP ectodomain mutation outside of the Aβ domain promotes Aβ production in vitro and deposition in vivo. J Exp Med 2021; 218:211936. [PMID: 33822840 PMCID: PMC8034382 DOI: 10.1084/jem.20210313] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 03/03/2021] [Accepted: 03/03/2021] [Indexed: 12/28/2022] Open
Abstract
Familial Alzheimer’s disease (FAD)–linked mutations in the APP gene occur either within the Aβ-coding region or immediately proximal and are located in exons 16 and 17, which encode Aβ peptides. We have identified an extremely rare, partially penetrant, single nucleotide variant (SNV), rs145081708, in APP that corresponds to a Ser198Pro substitution in exon 5. We now report that in stably transfected cells, expression of APP harboring the S198P mutation (APPS198P) leads to elevated production of Aβ peptides by an unconventional mechanism in which the folding and exit of APPS198P from the endoplasmic reticulum is accelerated. More importantly, coexpression of APP S198P and the FAD-linked PS1ΔE9 variant in the brains of male and female transgenic mice leads to elevated steady-state Aβ peptide levels and acceleration of Aβ deposition compared with age- and gender-matched mice expressing APP and PS1ΔE9. This is the first AD-linked mutation in APP present outside of exons 16 and 17 that enhances Aβ production and deposition.
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Affiliation(s)
- Xulun Zhang
- Department of Neurobiology, University of Chicago, Chicago, IL
| | - Can Martin Zhang
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | - Dmitry Prokopenko
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | - Yingxia Liang
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | - Sherri Y Zhen
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
| | - Ian Q Weigle
- Department of Neurobiology, University of Chicago, Chicago, IL
| | - Weinong Han
- Department of Neurobiology, University of Chicago, Chicago, IL
| | - Manish Aryal
- Department of Neurobiology, University of Chicago, Chicago, IL
| | - Rudolph E Tanzi
- Department of Neurology, Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Diseases, Massachusetts General Hospital, Charlestown, MA
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23
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Ziyatdinov A, Kim J, Prokopenko D, Privé F, Laporte F, Loh PR, Kraft P, Aschard H. Estimating the effective sample size in association studies of quantitative traits. G3 (Bethesda) 2021; 11:6178001. [PMID: 33734375 PMCID: PMC8495748 DOI: 10.1093/g3journal/jkab057] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 01/06/2021] [Indexed: 01/08/2023]
Abstract
The effective sample size (ESS) is a metric used to summarize in a single term the amount of correlation in a sample. It is of particular interest when predicting the statistical power of genome-wide association studies (GWAS) based on linear mixed models. Here, we introduce an analytical form of the ESS for mixed-model GWAS of quantitative traits and relate it to empirical estimators recently proposed. Using our framework, we derived approximations of the ESS for analyses of related and unrelated samples and for both marginal genetic and gene-environment interaction tests. We conducted simulations to validate our approximations and to provide a quantitative perspective on the statistical power of various scenarios, including power loss due to family relatedness and power gains due to conditioning on the polygenic signal. Our analyses also demonstrate that the power of gene-environment interaction GWAS in related individuals strongly depends on the family structure and exposure distribution. Finally, we performed a series of mixed-model GWAS on data from the UK Biobank and confirmed the simulation results. We notably found that the expected power drop due to family relatedness in the UK Biobank is negligible.
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Affiliation(s)
- Andrey Ziyatdinov
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jihye Kim
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Florian Privé
- National Centre for Register-Based Research, Aarhus University, Aarhus, 8210, Denmark
| | - Fabien Laporte
- Department of Computational Biology-USR 3756 CNRS, Institut Pasteur, 75015 Paris, France
| | - Po-Ru Loh
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Hugues Aschard
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Department of Computational Biology-USR 3756 CNRS, Institut Pasteur, 75015 Paris, France
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24
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Hong S, Prokopenko D, Dobricic V, Kilpert F, Bos I, Vos SJB, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Cleynen I, Gabel S, Schaeverbeke J, Scheltens P, Teunissen CE, Niemantsverdriet E, Engelborghs S, Frisoni G, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Kettunen P, Wallin A, Lleó A, Sala I, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Ten Kate M, Barkhof F, Zetterberg H, Lovestone S, Streffer J, Wittig M, Franke A, Tanzi RE, Visser PJ, Bertram L. Genome-wide association study of Alzheimer's disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset. Transl Psychiatry 2020; 10:403. [PMID: 33223526 PMCID: PMC7680793 DOI: 10.1038/s41398-020-01074-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 04/23/2020] [Accepted: 05/18/2020] [Indexed: 12/11/2022] Open
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Susceptibility to AD is considerably determined by genetic factors which hitherto were primarily identified using case-control designs. Elucidating the genetic architecture of additional AD-related phenotypic traits, ideally those linked to the underlying disease process, holds great promise in gaining deeper insights into the genetic basis of AD and in developing better clinical prediction models. To this end, we generated genome-wide single-nucleotide polymorphism (SNP) genotyping data in 931 participants of the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) sample to search for novel genetic determinants of AD biomarker variability. Specifically, we performed genome-wide association study (GWAS) analyses on 16 traits, including 14 measures derived from quantifications of five separate amyloid-beta (Aβ) and tau-protein species in the cerebrospinal fluid (CSF). In addition to confirming the well-established effects of apolipoprotein E (APOE) on diagnostic outcome and phenotypes related to Aβ42, we detected novel potential signals in the zinc finger homeobox 3 (ZFHX3) for CSF-Aβ38 and CSF-Aβ40 levels, and confirmed the previously described sex-specific association between SNPs in geminin coiled-coil domain containing (GMNC) and CSF-tau. Utilizing the results from independent case-control AD GWAS to construct polygenic risk scores (PRS) revealed that AD risk variants only explain a small fraction of CSF biomarker variability. In conclusion, our study represents a detailed first account of GWAS analyses on CSF-Aβ and -tau-related traits in the EMIF-AD MBD dataset. In subsequent work, we will utilize the genomics data generated here in GWAS of other AD-relevant clinical outcomes ascertained in this unique dataset.
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Affiliation(s)
- Shengjun Hong
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Fabian Kilpert
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Isabelle Bos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, The Netherlands
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands
| | - Ulf Andreasson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospital Leuven, Leuven, Belgium
| | - Isabelle Cleynen
- Laboratory for Complex Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Silvy Gabel
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Jolien Schaeverbeke
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, The Netherlands
| | - Ellis Niemantsverdriet
- Department of Biomedical Sciences, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Center for Neurosciences, UZ Brussel and Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Giovanni Frisoni
- University of Geneva, Geneva, Switzerland
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- AIX Marseille University, INS, Ap-hm, Marseille, France
| | | | - Regis Bordet
- University of Lille, Inserm, CHU Lille, Lille, France
| | - José Luis Molinuevo
- Alzheimer's disease and other cognitive disorders unit, Hospital Clinic I Universitari, Barcelona, Spain
| | - Lorena Rami
- Alzheimer's disease and other cognitive disorders unit, Hospital Clinic I Universitari, Barcelona, Spain
| | - Petronella Kettunen
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Alberto Lleó
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona and Centro de Investigación Biomédica en Red en enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Isabel Sala
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona and Centro de Investigación Biomédica en Red en enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Julius Popp
- Geriatric Psychiatry, Department of Mental Health and Psychiatry, Geneva University Hospitals, Geneva, Switzerland
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pablo Martinez-Lage
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Mikel Tainta
- Department of Neurology, Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Richard J B Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
- Health Data Research UK London, University College London, 222 Euston Road, London, UK
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, 222 Euston Road, London, UK
| | - Cristina Legido-Quigley
- Steno Diabetes Center, Copenhagen, Denmark
- Institute of Pharmaceutical Sciences, King's College London, London, UK
| | - Kristel Sleegers
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Christine Van Broeckhoven
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Mara Ten Kate
- Alzheimer Center and Department of Neurology, Amsterdam University Medical Centers, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | | | - Johannes Streffer
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Translational Medicine Neuroscience, UCB Biopharma SPRL, Braine l'Alleud, Belgium
| | - Michael Wittig
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany.
- Department of Psychology, University of Oslo, Oslo, Norway.
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Prokopenko D, Morgan SL, Mullin K, Hofmann O, Chapman B, Kirchner R, Amberkar S, Wohlers I, Lange C, Hide W, Bertram L, Tanzi RE. Whole-genome sequencing reveals new Alzheimer's disease-associated rare variants in loci related to synaptic function and neuronal development. medRxiv 2020:2020.11.03.20225540. [PMID: 33173892 PMCID: PMC7654884 DOI: 10.1101/2020.11.03.20225540] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
INTRODUCTION Genome-wide association studies have led to numerous genetic loci associated with Alzheimer's disease (AD). Whole-genome sequencing (WGS) now permit genome-wide analyses to identify rare variants contributing to AD risk. METHODS We performed single-variant and spatial clustering-based testing on rare variants (minor allele frequency ≤1%) in a family-based WGS-based association study of 2,247 subjects from 605 multiplex AD families, followed by replication in 1,669 unrelated individuals. RESULTS We identified 13 new AD candidate loci that yielded consistent rare-variant signals in discovery and replication cohorts (4 from single-variant, 9 from spatial-clustering), implicating these genes: FNBP1L, SEL1L, LINC00298, PRKCH, C15ORF41, C2CD3, KIF2A, APC, LHX9, NALCN, CTNNA2, SYTL3, CLSTN2. DISCUSSION Downstream analyses of these novel loci highlight synaptic function, in contrast to common AD-associated variants, which implicate innate immunity. These loci have not been previously associated with AD, emphasizing the ability of WGS to identify AD-associated rare variants, particularly outside of coding regions.
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26
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Kim W, Prokopenko D, Sakornsakolpat P, Hobbs BD, Lutz SM, Hokanson JE, Wain LV, Melbourne CA, Shrine N, Tobin MD, Silverman EK, Cho MH, Beaty TH. Genome-Wide Gene-by-Smoking Interaction Study of Chronic Obstructive Pulmonary Disease. Am J Epidemiol 2020; 190:875-885. [PMID: 33106845 PMCID: PMC8096488 DOI: 10.1093/aje/kwaa227] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [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: 12/01/2019] [Revised: 09/28/2020] [Accepted: 10/13/2020] [Indexed: 01/20/2023] Open
Abstract
Risk of chronic obstructive pulmonary disease (COPD) is determined by both cigarette smoking and genetic susceptibility, but little is known about gene-by-smoking interactions. We performed a genome-wide association analysis of 179,689 controls and 21,077 COPD cases from UK Biobank subjects of European ancestry recruited from 2006 to 2010, considering genetic main effects and gene-by-smoking interaction effects simultaneously (2-degrees-of-freedom (df) test) as well as interaction effects alone (1-df interaction test). We sought to replicate significant results in COPDGene (United States, 2008-2010) and SpiroMeta Consortium (multiple countries, 1947-2015) data. We considered 2 smoking variables: 1) ever/never and 2) current/noncurrent. In the 1-df test, we identified 1 genome-wide significant locus on 15q25.1 (cholinergic receptor nicotinic β4 subunit, or CHRNB4) for ever- and current smoking and identified PI*Z allele (rs28929474) of serpin family A member 1 (SERPINA1) for ever-smoking and 3q26.2 (MDS1 and EVI1 complex locus, or MECOM) for current smoking in an analysis of previously reported COPD loci. In the 2-df test, most of the significant signals were also significant for genetic marginal effects, aside from 16q22.1 (sphingomyelin phosphodiesterase 3, or SMPD3) and 19q13.2 (Egl-9 family hypoxia inducible factor 2, or EGLN2). The significant effects at 15q25.1 and 19q13.2 loci, both previously described in prior genome-wide association studies of COPD or smoking, were replicated in COPDGene and SpiroMeta. We identified interaction effects at previously reported COPD loci; however, we failed to identify novel susceptibility loci.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Terri H Beaty
- Correspondence to Dr. Terri H. Beaty, Department of Epidemiology, Johns Hopkins School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205 (e-mail: )
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27
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Zhao X, Qiao D, Yang C, Kasela S, Kim W, Ma Y, Shrine N, Batini C, Sofer T, Taliun SAG, Sakornsakolpat P, Balte PP, Prokopenko D, Yu B, Lange LA, Dupuis J, Cade BE, Lee J, Gharib SA, Daya M, Laurie CA, Ruczinski I, Cupples LA, Loehr LR, Bartz TM, Morrison AC, Psaty BM, Vasan RS, Wilson JG, Taylor KD, Durda P, Johnson WC, Cornell E, Guo X, Liu Y, Tracy RP, Ardlie KG, Aguet F, VanDenBerg DJ, Papanicolaou GJ, Rotter JI, Barnes KC, Jain D, Nickerson DA, Muzny DM, Metcalf GA, Doddapaneni H, Dugan-Perez S, Gupta N, Gabriel S, Rich SS, O'Connor GT, Redline S, Reed RM, Laurie CC, Daviglus ML, Preudhomme LK, Burkart KM, Kaplan RC, Wain LV, Tobin MD, London SJ, Lappalainen T, Oelsner EC, Abecasis GR, Silverman EK, Barr RG, Cho MH, Manichaikul A. Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants. Nat Commun 2020; 11:5182. [PMID: 33057025 PMCID: PMC7598941 DOI: 10.1038/s41467-020-18334-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 08/19/2020] [Indexed: 12/14/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.
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Affiliation(s)
- Xutong Zhao
- Center for Statistical Genetics, and Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Dandi Qiao
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Chaojie Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Silva Kasela
- New York Genome Center, New York, NY, 10013, USA
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
| | - Wonji Kim
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Yanlin Ma
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Nick Shrine
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, United Kingdom
| | - Chiara Batini
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, United Kingdom
| | - Tamar Sofer
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Sarah A Gagliano Taliun
- Center for Statistical Genetics, and Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Pallavi P Balte
- Department of Medicine, Columbia University Medical Center, New York, NY, 10032, USA
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics & Environmental Sciences, UTHealth School of Public Health, Houston, TX, 77030, USA
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Brian E Cade
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Jiwon Lee
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, 02115, USA
| | - Sina A Gharib
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle, WA, 98109, USA
| | - Michelle Daya
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Cecelia A Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and the National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, 01702, USA
| | - Laura R Loehr
- Department of Medicine, UNC School of Medicine, Chapel Hill, NC, 27599, USA
| | - Traci M Bartz
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, 98101, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - Ramachandran S Vasan
- Boston University and the National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, 01702, USA
- Department of Preventive Medicine and Epidemiology, Boston University School of Medicine and Public Health, Boston, MA, 02118, USA
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, The Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Peter Durda
- Department of Pathology and Laboratory Medicine, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, 05405, USA
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Elaine Cornell
- Department of Pathology and Laboratory Medicine, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, 05405, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, The Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Yongmei Liu
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, 27701, USA
| | - Russell P Tracy
- Department of Pathology and Laboratory Medicine, Robert Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, 05405, USA
| | | | - François Aguet
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - David J VanDenBerg
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - George J Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, The Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Kathleen C Barnes
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, WA, 98195, USA
| | - Donna M Muzny
- The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Ginger A Metcalf
- The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | | | - Shannon Dugan-Perez
- The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Stacey Gabriel
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - George T O'Connor
- Boston University School Of Medicine, Pulmonary Center, Boston, MA, 02118, USA
| | - Susan Redline
- Department of Medicine, Harvard Medical School, Boston, MA, 02115, USA
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, 02115, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, 02215, USA
| | - Robert M Reed
- Division of Pulmonary and Critical Care Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, 60612, USA
| | | | - Kristin M Burkart
- Department of Medicine, Columbia University Medical Center, New York, NY, 10032, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, NY, 10461, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA
| | - Louise V Wain
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, United Kingdom
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK
| | - Martin D Tobin
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, LE1 7RH, United Kingdom
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Durham, NC, 27709, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, 10013, USA
- Department of Systems Biology, Columbia University, New York, NY, 10032, USA
| | - Elizabeth C Oelsner
- Department of Medicine, Columbia University Medical Center, New York, NY, 10032, USA
| | - Goncalo R Abecasis
- Center for Statistical Genetics, and Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Edwin K Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - R Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, NY, 10032, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA.
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28
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Hahn G, Lutz SM, Hecker J, Prokopenko D, Cho MH, Silverman EK, Weiss ST, Lange C. locStra: Fast analysis of regional/global stratification in whole-genome sequencing studies. Genet Epidemiol 2020; 45:82-98. [PMID: 32929743 DOI: 10.1002/gepi.22356] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [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: 04/13/2020] [Revised: 08/05/2020] [Accepted: 08/24/2020] [Indexed: 01/08/2023]
Abstract
locStra is an R -package for the analysis of regional and global population stratification in whole-genome sequencing (WGS) studies, where regional stratification refers to the substructure defined by the loci in a particular region on the genome. Population substructure can be assessed based on the genetic covariance matrix, the genomic relationship matrix, and the unweighted/weighted genetic Jaccard similarity matrix. Using a sliding window approach, the regional similarity matrices are compared with the global ones, based on user-defined window sizes and metrics, for example, the correlation between regional and global eigenvectors. An algorithm for the specification of the window size is provided. As the implementation fully exploits sparse matrix algebra and is written in C++, the analysis is highly efficient. Even on single cores, for realistic study sizes (several thousand subjects, several million rare variants per subject), the runtime for the genome-wide computation of all regional similarity matrices does typically not exceed one hour, enabling an unprecedented investigation of regional stratification across the entire genome. The package is applied to three WGS studies, illustrating the varying patterns of regional substructure across the genome and its beneficial effects on association testing.
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Affiliation(s)
- Georg Hahn
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Sharon M Lutz
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Julian Hecker
- Department of Medicine, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts, USA
| | - Dmitry Prokopenko
- Massachusetts General Hospital, Harvard University, Boston, Massachusetts, USA
| | - Michael H Cho
- Department of Medicine, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts, USA
| | - Edwin K Silverman
- Department of Medicine, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts, USA
| | - Scott T Weiss
- Department of Medicine, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts, USA
| | - Christoph Lange
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
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29
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Prokopenko D, Hecker J, Kirchner R, Chapman BA, Hoffman O, Mullin K, Hide W, Bertram L, Laird N, DeMeo DL, Lange C, Tanzi RE. Identification of Novel Alzheimer's Disease Loci Using Sex-Specific Family-Based Association Analysis of Whole-Genome Sequence Data. Sci Rep 2020; 10:5029. [PMID: 32193444 PMCID: PMC7081222 DOI: 10.1038/s41598-020-61883-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 02/17/2020] [Indexed: 11/21/2022] Open
Abstract
With the advent of whole genome-sequencing (WGS) studies, family-based designs enable sex-specific analysis approaches that can be applied to only affected individuals; tests using family-based designs are attractive because they are completely robust against the effects of population substructure. These advantages make family-based association tests (FBATs) that use siblings as well as parents especially suited for the analysis of late-onset diseases such as Alzheimer's Disease (AD). However, the application of FBATs to assess sex-specific effects can require additional filtering steps, as sensitivity to sequencing errors is amplified in this type of analysis. Here, we illustrate the implementation of robust analysis approaches and additional filtering steps that can minimize the chances of false positive-findings due to sex-specific sequencing errors. We apply this approach to two family-based AD datasets and identify four novel loci (GRID1, RIOK3, MCPH1, ZBTB7C) showing sex-specific association with AD risk. Following stringent quality control filtering, the strongest candidate is ZBTB7C (Pinter = 1.83 × 10-7), in which the minor allele of rs1944572 confers increased risk for AD in females and protection in males. ZBTB7C encodes the Zinc Finger and BTB Domain Containing 7C, a transcriptional repressor of membrane metalloproteases (MMP). Members of this MMP family were implicated in AD neuropathology.
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Affiliation(s)
- Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Julian Hecker
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Rory Kirchner
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brad A Chapman
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Oliver Hoffman
- Department of Clinical Pathology, University of Melbourne, Victoria, 3000, Melbourne, Australia
| | - Kristina Mullin
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Winston Hide
- Harvard Medical School, Boston, MA, USA
- Department of Neuroscience, Sheffield Institute for Translational Neurosciences, University of Sheffield, Sheffield, UK
- Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA, US
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Nan Laird
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Dawn L DeMeo
- Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Christoph Lange
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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30
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Prokopenko D, Sakornsakolpat P, Fier HL, Qiao D, Parker MM, McDonald MLN, Manichaikul A, Rich SS, Barr RG, Williams CJ, Brantly ML, Lange C, Beaty TH, Crapo JD, Silverman EK, Cho MH. Whole-Genome Sequencing in Severe Chronic Obstructive Pulmonary Disease. Am J Respir Cell Mol Biol 2019; 59:614-622. [PMID: 29949718 DOI: 10.1165/rcmb.2018-0088oc] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Genome-wide association studies have identified common variants associated with chronic obstructive pulmonary disease (COPD). Whole-genome sequencing (WGS) offers comprehensive coverage of the entire genome, as compared with genotyping arrays or exome sequencing. We hypothesized that WGS in subjects with severe COPD and smoking control subjects with normal pulmonary function would allow us to identify novel genetic determinants of COPD. We sequenced 821 patients with severe COPD and 973 control subjects from the COPDGene and Boston Early-Onset COPD studies, including both non-Hispanic white and African American individuals. We performed single-variant and grouped-variant analyses, and in addition, we assessed the overlap of variants between sequencing- and array-based imputation. Our most significantly associated variant was in a known region near HHIP (combined P = 1.6 × 10-9); additional variants approaching genome-wide significance included previously described regions in CHRNA5, TNS1, and SERPINA6/SERPINA1 (the latter in African American individuals). None of our associations were clearly driven by rare variants, and we found minimal evidence of replication of genes identified by previously reported smaller sequencing studies. With WGS, we identified more than 20 million new variants, not seen with imputation, including more than 10,000 of potential importance in previously identified COPD genome-wide association study regions. WGS in severe COPD identifies a large number of potentially important functional variants, with the strongest associations being in known COPD risk loci, including HHIP and SERPINA1. Larger sample sizes will be needed to identify associated variants in novel regions of the genome.
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Affiliation(s)
- Dmitry Prokopenko
- 1 Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Phuwanat Sakornsakolpat
- 1 Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Heide Loehlein Fier
- 2 Working Group of Genomic Mathematics, University of Bonn, Bonn, Germany.,3 Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts
| | - Dandi Qiao
- 1 Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Margaret M Parker
- 1 Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Merry-Lynn N McDonald
- 4 Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | - Ani Manichaikul
- 5 Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - Stephen S Rich
- 5 Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia
| | - R Graham Barr
- 6 Department of Medicine, College of Physicians and Surgeons and.,7 Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Christopher J Williams
- 8 Division of Pulmonary Critical Care and Sleep Medicine, College of Medicine, University of Florida, Gainesville, Florida
| | - Mark L Brantly
- 8 Division of Pulmonary Critical Care and Sleep Medicine, College of Medicine, University of Florida, Gainesville, Florida
| | - Christoph Lange
- 3 Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts
| | - Terri H Beaty
- 9 Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland; and
| | | | - Edwin K Silverman
- 1 Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Michael H Cho
- 1 Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
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31
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Shrine N, Guyatt AL, Erzurumluoglu AM, Jackson VE, Hobbs BD, Melbourne CA, Batini C, Fawcett KA, Song K, Sakornsakolpat P, Li X, Boxall R, Reeve NF, Obeidat M, Zhao JH, Wielscher M, Weiss S, Kentistou KA, Cook JP, Sun BB, Zhou J, Hui J, Karrasch S, Imboden M, Harris SE, Marten J, Enroth S, Kerr SM, Surakka I, Vitart V, Lehtimäki T, Allen RJ, Bakke PS, Beaty TH, Bleecker ER, Bossé Y, Brandsma CA, Chen Z, Crapo JD, Danesh J, DeMeo DL, Dudbridge F, Ewert R, Gieger C, Gulsvik A, Hansell AL, Hao K, Hoffman JD, Hokanson JE, Homuth G, Joshi PK, Joubert P, Langenberg C, Li X, Li L, Lin K, Lind L, Locantore N, Luan J, Mahajan A, Maranville JC, Murray A, Nickle DC, Packer R, Parker MM, Paynton ML, Porteous DJ, Prokopenko D, Qiao D, Rawal R, Runz H, Sayers I, Sin DD, Smith BH, Artigas MS, Sparrow D, Tal-Singer R, Timmers PRHJ, Van den Berge M, Whittaker JC, Woodruff PG, Yerges-Armstrong LM, Troyanskaya OG, Raitakari OT, Kähönen M, Polašek O, Gyllensten U, Rudan I, Deary IJ, Probst-Hensch NM, Schulz H, James AL, Wilson JF, Stubbe B, Zeggini E, Jarvelin MR, Wareham N, Silverman EK, Hayward C, Morris AP, Butterworth AS, Scott RA, Walters RG, Meyers DA, Cho MH, Strachan DP, Hall IP, Tobin MD, Wain LV. Author Correction: New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries. Nat Genet 2019; 51:1067. [PMID: 31110354 DOI: 10.1038/s41588-019-0438-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Affiliation(s)
- Nick Shrine
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Anna L Guyatt
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Victoria E Jackson
- Department of Health Sciences, University of Leicester, Leicester, UK.,Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia
| | - Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Carl A Melbourne
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Chiara Batini
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Kijoung Song
- Target Sciences, GlaxoSmithKline, Collegeville, PA, USA
| | - Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Xingnan Li
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Ruth Boxall
- Nuffield Department of Population Health, University of Oxford, Oxford, UK.,Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Nicola F Reeve
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Ma'en Obeidat
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada
| | - Jing Hua Zhao
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health,Imperial College London, London, UK
| | | | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Katherine A Kentistou
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.,Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - James P Cook
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Benjamin B Sun
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jian Zhou
- Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Jennie Hui
- Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.,School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia.,PathWest Laboratory Medicine of WA,Sir Charles Gairdner Hospital, Crawley, Western Australia, Australia.,School of Pathology and Laboratory Medicine, The University of Western Australia, Crawley, Western Australia, Australia
| | - Stefan Karrasch
- Institute of Epidemiology, Helmholtz Zentrum Muenchen-German Research Center for Environmental Health, Neuherberg, Germany.,Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-Universität, Munich, Germany.,Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Stefan Enroth
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala Universitet, Uppsala, Sweden
| | - Shona M Kerr
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ida Surakka
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,The National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Richard J Allen
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Per S Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins University School of Public Health, Baltimore, MD, USA
| | - Eugene R Bleecker
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Yohan Bossé
- Department of Molecular Medicine, Laval University, Québec, Canada.,Institut Universitaire de Cardiologie et de Pneumologie de Québec,Laval University, Québec, Canada
| | - Corry-Anke Brandsma
- University of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, GRIAC Research Institute,University of Groningen, Groningen, The Netherlands
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - James D Crapo
- National Jewish Health, Denver, CO, USA.,Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, CO, USA
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,British Heart Foundation Cambridge Centre of Excellence, Division of Cardiovascular Medicine,Addenbrooke's Hospital, Cambridge, UK.,Department of Human Genetics, Wellcome Trust Sanger Institute, Cambridge, UK.,NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Ralf Ewert
- Department of Internal Medicine B - Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany
| | - Amund Gulsvik
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anna L Hansell
- Centre for Environmental Health & Sustainability, University of Leicester, Leicester, UK.,UK Small Area Health Statistics Unit, MRC-PHE Centre for Environment and Health, School of Public Health,Imperial College London, London, UK.,Imperial College Healthcare NHS Trust,St Mary's Hospital, London, UK
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - John E Hokanson
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Philippe Joubert
- Institut Universitaire de Cardiologie et de Pneumologie de Québec,Laval University, Québec, Canada.,Department of Molecular Biology, Medical Biochemistry, and Pathology,Laval University, Québec, Canada
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Xuan Li
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada
| | - Liming Li
- Department of Epidemiology & Biostatistics, Peking University Health Science Center, Beijing, China
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Lars Lind
- Department of Medical Sciences, Cardiovascular Epidemiology,Uppsala University, Uppsala, Sweden
| | | | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Alison Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - David C Nickle
- MRL, Merck & Co., Inc, Kenilworth, NJ, USA.,Gossamer Bio, San Diego, CA, USA
| | - Richard Packer
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Margaret M Parker
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Megan L Paynton
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dandi Qiao
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Rajesh Rawal
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Heiko Runz
- MRL, Merck & Co., Inc, Kenilworth, NJ, USA
| | - Ian Sayers
- Division of Respiratory Medicine and NIHR-Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Don D Sin
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada.,Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - María Soler Artigas
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.,Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain.,Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
| | - David Sparrow
- VA Boston Healthcare System, Boston, MA, USA.,Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | | | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Maarten Van den Berge
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, GRIAC Research Institute,University of Groningen, Groningen, The Netherlands
| | - John C Whittaker
- Target Sciences - R&D, GSK Medicines Research Centre, Stevenage, UK
| | - Prescott G Woodruff
- UCSF Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | | | - Olga G Troyanskaya
- Department of Computer Science, Princeton University, Princeton, NJ, USA.,Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.,Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences,University of Tampere, Tampere, Finland
| | - Ozren Polašek
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.,University of Split School of Medicine, Split, Croatia
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala Universitet, Uppsala, Sweden
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Nicole M Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Holger Schulz
- Institute of Epidemiology, Helmholtz Zentrum Muenchen-German Research Center for Environmental Health, Neuherberg, Germany.,Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Alan L James
- Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.,Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.,School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.,Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Beate Stubbe
- Department of Internal Medicine B - Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Eleftheria Zeggini
- Wellcome Sanger Institute, Hinxton, UK.,Institute of Translational Genomics, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health,Imperial College London, London, UK.,Center for Life Course Health Research, Faculty of Medicine,University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland.,Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UK
| | - Nick Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, UK.,Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.,NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Robert A Scott
- Target Sciences - R&D, GSK Medicines Research Centre, Stevenage, UK
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Deborah A Meyers
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, UK
| | - Ian P Hall
- Division of Respiratory Medicine and NIHR-Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK. .,National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
| | - Louise V Wain
- Department of Health Sciences, University of Leicester, Leicester, UK. .,National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
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32
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Hecker J, Prokopenko D, Lange C, Fier HL. PolyGEE: a generalized estimating equation approach to the efficient and robust estimation of polygenic effects in large-scale association studies. Biostatistics 2019; 19:295-306. [PMID: 28968646 PMCID: PMC5991211 DOI: 10.1093/biostatistics/kxx040] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Accepted: 07/21/2017] [Indexed: 11/17/2022] Open
Abstract
To quantify polygenic effects, i.e. undetected genetic effects, in large-scale association studies, we propose a generalized estimating equation (GEE) based estimation framework. We develop a marginal model for single-variant association test statistics of complex diseases that generalizes existing approaches such as LD Score regression and that is applicable to population-based designs, to family-based designs or to arbitrary combinations of both. We extend the standard GEE approach so that the parameters of the proposed marginal model can be estimated based on working-correlation/linkage-disequilibrium (LD) matrices from external reference panels. Our method achieves substantial efficiency gains over standard approaches, while it is robust against misspecification of the LD structure, i.e. the LD structure of the reference panel can differ substantially from the true LD structure in the study population. In simulation studies and in applications to population-based and family-based studies, we illustrate the features of the proposed GEE framework. Our results suggest that our approach can be up to 100% more efficient than existing methodology.
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Affiliation(s)
- Julian Hecker
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA and Department of Genomic Mathematics, University of Bonn, Sigmund-Freud-Strasse 25, 53127 Bonn, Germany
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, USA
| | - Christoph Lange
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA and Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, USA
| | - Heide Loehlein Fier
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA and Department of Genomic Mathematics, University of Bonn, Sigmund-Freud-Strasse 25, 53127 Bonn, Germany
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33
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Shrine N, Guyatt AL, Erzurumluoglu AM, Jackson VE, Hobbs BD, Melbourne CA, Batini C, Fawcett KA, Song K, Sakornsakolpat P, Li X, Boxall R, Reeve NF, Obeidat M, Zhao JH, Wielscher M, Weiss S, Kentistou KA, Cook JP, Sun BB, Zhou J, Hui J, Karrasch S, Imboden M, Harris SE, Marten J, Enroth S, Kerr SM, Surakka I, Vitart V, Lehtimäki T, Allen RJ, Bakke PS, Beaty TH, Bleecker ER, Bossé Y, Brandsma CA, Chen Z, Crapo JD, Danesh J, DeMeo DL, Dudbridge F, Ewert R, Gieger C, Gulsvik A, Hansell AL, Hao K, Hoffman JD, Hokanson JE, Homuth G, Joshi PK, Joubert P, Langenberg C, Li X, Li L, Lin K, Lind L, Locantore N, Luan J, Mahajan A, Maranville JC, Murray A, Nickle DC, Packer R, Parker MM, Paynton ML, Porteous DJ, Prokopenko D, Qiao D, Rawal R, Runz H, Sayers I, Sin DD, Smith BH, Soler Artigas M, Sparrow D, Tal-Singer R, Timmers PRHJ, Van den Berge M, Whittaker JC, Woodruff PG, Yerges-Armstrong LM, Troyanskaya OG, Raitakari OT, Kähönen M, Polašek O, Gyllensten U, Rudan I, Deary IJ, Probst-Hensch NM, Schulz H, James AL, Wilson JF, Stubbe B, Zeggini E, Jarvelin MR, Wareham N, Silverman EK, Hayward C, Morris AP, Butterworth AS, Scott RA, Walters RG, Meyers DA, Cho MH, Strachan DP, Hall IP, Tobin MD, Wain LV. New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries. Nat Genet 2019; 51:481-493. [PMID: 30804560 PMCID: PMC6397078 DOI: 10.1038/s41588-018-0321-7] [Citation(s) in RCA: 257] [Impact Index Per Article: 51.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Accepted: 11/27/2018] [Indexed: 02/02/2023]
Abstract
Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function-associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.
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Affiliation(s)
- Nick Shrine
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Anna L Guyatt
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Victoria E Jackson
- Department of Health Sciences, University of Leicester, Leicester, UK
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia
| | - Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Carl A Melbourne
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Chiara Batini
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Kijoung Song
- Target Sciences, GlaxoSmithKline, Collegeville, PA, USA
| | - Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Xingnan Li
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Ruth Boxall
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Nicola F Reeve
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Ma'en Obeidat
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada
| | - Jing Hua Zhao
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Matthias Wielscher
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, UK
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Katherine A Kentistou
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - James P Cook
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Benjamin B Sun
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jian Zhou
- Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Jennie Hui
- Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Population Health, The University of Western Australia, Crawley, Western Australia, Australia
- PathWest Laboratory Medicine of WA, Sir Charles Gairdner Hospital, Crawley, Western Australia, Australia
- School of Pathology and Laboratory Medicine, The University of Western Australia, Crawley, Western Australia, Australia
| | - Stefan Karrasch
- Institute of Epidemiology, Helmholtz Zentrum Muenchen-German Research Center for Environmental Health, Neuherberg, Germany
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-Universität, Munich, Germany
- Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Stefan Enroth
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala Universitet, Uppsala, Sweden
| | - Shona M Kerr
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ida Surakka
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- The National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Richard J Allen
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Per S Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins University School of Public Health, Baltimore, MD, USA
| | - Eugene R Bleecker
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Yohan Bossé
- Department of Molecular Medicine, Laval University, Québec, Canada
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Québec, Canada
| | - Corry-Anke Brandsma
- University of Groningen, University Medical Center Groningen, Department of Pathology and Medical Biology, GRIAC Research Institute, University of Groningen, Groningen, The Netherlands
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - James D Crapo
- National Jewish Health, Denver, CO, USA
- Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, CO, USA
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Cambridge Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Cambridge, UK
- Department of Human Genetics, Wellcome Trust Sanger Institute, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Ralf Ewert
- Department of Internal Medicine B - Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany
| | - Amund Gulsvik
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Anna L Hansell
- Centre for Environmental Health & Sustainability, University of Leicester, Leicester, UK
- UK Small Area Health Statistics Unit, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, St Mary's Hospital, London, UK
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - John E Hokanson
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Philippe Joubert
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Québec, Canada
- Department of Molecular Biology, Medical Biochemistry, and Pathology, Laval University, Québec, Canada
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Xuan Li
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada
| | - Liming Li
- Department of Epidemiology & Biostatistics, Peking University Health Science Center, Beijing, China
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Lars Lind
- Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden
| | | | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Alison Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - David C Nickle
- MRL, Merck & Co., Inc, Kenilworth, NJ, USA
- Gossamer Bio, San Diego, CA, USA
| | - Richard Packer
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Margaret M Parker
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Megan L Paynton
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dandi Qiao
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Rajesh Rawal
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Heiko Runz
- MRL, Merck & Co., Inc, Kenilworth, NJ, USA
| | - Ian Sayers
- Division of Respiratory Medicine and NIHR-Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Don D Sin
- The University of British Columbia Centre for Heart Lung Innovation, St Paul's Hospital, Vancouver, British Columbia, Canada
- Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Blair H Smith
- Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - María Soler Artigas
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Psychiatry, Hospital Universitari Vall d'Hebron, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
| | - David Sparrow
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | | | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Maarten Van den Berge
- University of Groningen, University Medical Center Groningen, Department of Pulmonology, GRIAC Research Institute, University of Groningen, Groningen, The Netherlands
| | - John C Whittaker
- Target Sciences - R&D, GSK Medicines Research Centre, Stevenage, UK
| | - Prescott G Woodruff
- UCSF Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, CA, USA
| | | | - Olga G Troyanskaya
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Ozren Polašek
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- University of Split School of Medicine, Split, Croatia
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala Universitet, Uppsala, Sweden
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Nicole M Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Holger Schulz
- Institute of Epidemiology, Helmholtz Zentrum Muenchen-German Research Center for Environmental Health, Neuherberg, Germany
- Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
| | - Alan L James
- Busselton Population Medical Research Institute, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Medicine and Pharmacology, The University of Western Australia, Crawley, Western Australia, Australia
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Beate Stubbe
- Department of Internal Medicine B - Cardiology, Intensive Care, Pulmonary Medicine and Infectious Diseases, University Medicine Greifswald, Greifswald, Germany
| | - Eleftheria Zeggini
- Wellcome Sanger Institute, Hinxton, UK
- Institute of Translational Genomics, Helmholtz Zentrum Muenchen - German Research Center for Environmental Health, Neuherberg, Germany
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UK
| | - Nick Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Robert A Scott
- Target Sciences - R&D, GSK Medicines Research Centre, Stevenage, UK
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Deborah A Meyers
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, UK
| | - Ian P Hall
- Division of Respiratory Medicine and NIHR-Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK.
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
| | - Louise V Wain
- Department of Health Sciences, University of Leicester, Leicester, UK.
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK.
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34
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Sakornsakolpat P, Prokopenko D, Lamontagne M, Reeve NF, Guyatt AL, Jackson VE, Shrine N, Qiao D, Bartz TM, Kim DK, Lee MK, Latourelle JC, Li X, Morrow JD, Obeidat M, Wyss AB, Bakke P, Barr RG, Beaty TH, Belinsky SA, Brusselle GG, Crapo JD, de Jong K, DeMeo DL, Fingerlin TE, Gharib SA, Gulsvik A, Hall IP, Hokanson JE, Kim WJ, Lomas DA, London SJ, Meyers DA, O'Connor GT, Rennard SI, Schwartz DA, Sliwinski P, Sparrow D, Strachan DP, Tal-Singer R, Tesfaigzi Y, Vestbo J, Vonk JM, Yim JJ, Zhou X, Bossé Y, Manichaikul A, Lahousse L, Silverman EK, Boezen HM, Wain LV, Tobin MD, Hobbs BD, Cho MH. Genetic landscape of chronic obstructive pulmonary disease identifies heterogeneous cell-type and phenotype associations. Nat Genet 2019; 51:494-505. [PMID: 30804561 PMCID: PMC6546635 DOI: 10.1038/s41588-018-0342-2] [Citation(s) in RCA: 194] [Impact Index Per Article: 38.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Accepted: 12/20/2018] [Indexed: 11/09/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide new insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci associated with P < 5 × 10-8; 47 of these were previously described in association with either COPD or population-based measures of lung function. Of the remaining 35 new loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified functional enrichment of COPD risk loci in lung tissue, smooth muscle, and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups based on associations with quantitative imaging features and comorbidities. Our analyses provide further support for the genetic susceptibility and heterogeneity of COPD.
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Affiliation(s)
- Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Genetics and Aging Research Unit, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Maxime Lamontagne
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Quebec, Canada
| | - Nicola F Reeve
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Anna L Guyatt
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Victoria E Jackson
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Nick Shrine
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
| | - Dandi Qiao
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Deog Kyeom Kim
- Seoul National University College of Medicine, SMG-SNU Boramae Medical Center, Seoul, South Korea
| | - Mi Kyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Raleigh, NC, USA
| | - Jeanne C Latourelle
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Xingnan Li
- Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Jarrett D Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ma'en Obeidat
- University of British Columbia Center for Heart Lung Innovation, St. Paul's Hospital, Vancouver, British Columbia, Canada
| | - Annah B Wyss
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Raleigh, NC, USA
| | - Per Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - R Graham Barr
- Department of Medicine, College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Guy G Brusselle
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Department of Respiratory Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - James D Crapo
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, National Jewish Health, Denver, CO, USA
| | - Kim de Jong
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, the Netherlands
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tasha E Fingerlin
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
- Department of Biostatistics and Informatics, University of Colorado Denver, Aurora, CO, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Amund Gulsvik
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ian P Hall
- Division of Respiratory Medicine, Queen's Medical Centre, University of Nottingham, Nottingham, UK
- National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham, UK
| | - John E Hokanson
- Department of Epidemiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, School of Medicine, Kangwon National University, Chuncheon, South Korea
| | - David A Lomas
- UCL Respiratory, University College London, London, UK
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Raleigh, NC, USA
| | | | - George T O'Connor
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Pulmonary Center, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Stephen I Rennard
- Pulmonary, Critical Care, Sleep and Allergy Division, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Clinical Discovery Unit, AstraZeneca, Cambridge, UK
| | - David A Schwartz
- Department of Medicine, School of Medicine, University of Colorado Denver, Aurora, CO, USA
- Department of Immunology, School of Medicine, University of Colorado Denver, Aurora, CO, USA
| | - Pawel Sliwinski
- 2nd Department of Respiratory Medicine, Institute of Tuberculosis and Lung Diseases, Warsaw, Poland
| | - David Sparrow
- VA Boston Healthcare System and Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - David P Strachan
- Population Health Research Institute, St. George's University of London, London, UK
| | | | | | - Jørgen Vestbo
- School of Biological Sciences, University of Manchester, Manchester, UK
| | - Judith M Vonk
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, the Netherlands
| | - Jae-Joon Yim
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Xiaobo Zhou
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Yohan Bossé
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Quebec, Canada
- Department of Molecular Medicine, Laval University, Québec, Québec, Canada
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Lies Lahousse
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Bioanalysis, Ghent University, Ghent, Belgium
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - H Marike Boezen
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
- University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, the Netherlands
| | - Louise V Wain
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Martin D Tobin
- Genetic Epidemiology Group, Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA.
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Qiao D, Ameli A, Prokopenko D, Chen H, Kho AT, Parker MM, Morrow J, Hobbs BD, Liu Y, Beaty TH, Crapo JD, Barnes KC, Nickerson DA, Bamshad M, Hersh CP, Lomas DA, Agusti A, Make BJ, Calverley PMA, Donner CF, Wouters EF, Vestbo J, Paré PD, Levy RD, Rennard SI, Tal-Singer R, Spitz MR, Sharma A, Ruczinski I, Lange C, Silverman EK, Cho MH. Whole exome sequencing analysis in severe chronic obstructive pulmonary disease. Hum Mol Genet 2018; 27:3801-3812. [PMID: 30060175 PMCID: PMC6196654 DOI: 10.1093/hmg/ddy269] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2018] [Revised: 07/09/2018] [Accepted: 07/17/2018] [Indexed: 12/13/2022] Open
Abstract
Chronic obstructive pulmonary disease (COPD), one of the leading causes of death worldwide, is substantially influenced by genetic factors. Alpha-1 antitrypsin deficiency demonstrates that rare coding variants of large effect can influence COPD susceptibility. To identify additional rare coding variants in patients with severe COPD, we conducted whole exome sequencing analysis in 2543 subjects from two family-based studies (Boston Early-Onset COPD Study and International COPD Genetics Network) and one case-control study (COPDGene). Applying a gene-based segregation test in the family-based data, we identified significant segregation of rare loss of function variants in TBC1D10A and RFPL1 (P-value < 2x10-6), but were unable to find similar variants in the case-control study. In single-variant, gene-based and pathway association analyses, we were unable to find significant findings that replicated or were significant in meta-analysis. However, we found that the top results in the two datasets were in proximity to each other in the protein-protein interaction network (P-value = 0.014), suggesting enrichment of these results for similar biological processes. A network of these association results and their neighbors was significantly enriched in the transforming growth factor beta-receptor binding and cilia-related pathways. Finally, in a more detailed examination of candidate genes, we identified individuals with putative high-risk variants, including patients harboring homozygous mutations in genes associated with cutis laxa and Niemann-Pick Disease Type C. Our results likely reflect heterogeneity of genetic risk for COPD along with limitations of statistical power and functional annotation, and highlight the potential of network analysis to gain insight into genetic association studies.
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Affiliation(s)
- Dandi Qiao
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Asher Ameli
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Physics, Northeastern University, Boston, Massachusetts, United States of America
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
- Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Alvin T Kho
- Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Margaret M Parker
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Jarrett Morrow
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Brian D Hobbs
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yanhong Liu
- Dan L. Duncan Comprehensive Cancer Center, Department of Medicine, Baylor College of Medicine, Houston, Texas, United States of America
| | - Terri H Beaty
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - James D Crapo
- National Jewish Health, Denver, Colorado, United States of America
| | - Kathleen C Barnes
- Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
| | - Michael Bamshad
- Division of Genetic Medicine, Department of Pediatrics, University of Washington and Seattle Children’s Hospital, Seattle, Washington , United States of America
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | | | - Alvar Agusti
- Respiratory Institute, Hospital Clinic, IDIBAPS, University of Barcelona, CIBERES, Barcelona, Spain
| | - Barry J Make
- National Jewish Health, Denver, Colorado, United States of America
| | | | - Claudio F Donner
- Mondo Medico di I.F.I.M. srl, Multidisciplinary and Rehabilitation Outpatient Clinic, Borgomanero, Novara, Italy
| | - Emiel F Wouters
- Department of Respiratory Medicine, Maastricht University Medical Center, AZ Maastricht, The Netherlands
| | - Jørgen Vestbo
- University of Manchester, Manchester, United Kingdom
| | - Peter D Paré
- Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, British Columbia V6T, Canada
| | - Robert D Levy
- Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, British Columbia V6T, Canada
| | - Stephen I Rennard
- University of Nebraska Medical Center, Omaha, Nebraska, United States of America
- AstraZeneca, Cambridge CB2 0RE, United Kingdom
| | - Ruth Tal-Singer
- GSK Research and Development, KingOf Prussia, Pennsylvania, United States of America
| | - Margaret R Spitz
- Dan L. Duncan Comprehensive Cancer Center, Department of Medicine, Baylor College of Medicine, Houston, Texas, United States of America
| | - Amitabh Sharma
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Christoph Lange
- Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Channing Division of Network Medicine, Longwood Avenue, Boston, MA, USA
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Loehlein Fier H, Prokopenko D, Hecker J, Cho MH, Silverman EK, Weiss ST, Tanzi RE, Lange C. On the association analysis of genome-sequencing data: A spatial clustering approach for partitioning the entire genome into nonoverlapping windows. Genet Epidemiol 2017; 41:332-340. [PMID: 28318110 DOI: 10.1002/gepi.22040] [Citation(s) in RCA: 9] [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: 10/18/2016] [Revised: 12/20/2016] [Accepted: 02/04/2017] [Indexed: 12/16/2022]
Abstract
For the association analysis of whole-genome sequencing (WGS) studies, we propose an efficient and fast spatial-clustering algorithm. Compared to existing analysis approaches for WGS data, that define the tested regions either by sliding or consecutive windows of fixed sizes along variants, a meaningful grouping of nearby variants into consecutive regions has the advantage that, compared to sliding window approaches, the number of tested regions is likely to be smaller. In comparison to consecutive, fixed-window approaches, our approach is likely to group nearby variants together. Given existing biological evidence that disease-associated mutations tend to physically cluster in specific regions along the chromosome, the identification of meaningful groups of nearby located variants could thus lead to a potential power gain for association analysis. Our algorithm defines consecutive genomic regions based on the physical positions of the variants, assuming an inhomogeneous Poisson process and groups together nearby variants. As parameters are estimated locally, the algorithm takes the differing variant density along the chromosome into account and provides locally optimal partitioning of variants into consecutive regions. An R-implementation of the algorithm is provided. We discuss the theoretical advances of our algorithm compared to existing, window-based approaches and show the performance and advantage of our introduced algorithm in a simulation study and by an application to Alzheimer's disease WGS data. Our analysis identifies a region in the ITGB3 gene that potentially harbors disease susceptibility loci for Alzheimer's disease. The region-based association signal of ITGB3 replicates in an independent data set and achieves formally genome-wide significance. Software Implementation: An implementation of the algorithm in R is available at: https://github.com/heidefier/cluster_wgs_data.
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Affiliation(s)
- Heide Loehlein Fier
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.,Working Group of Genomic Mathematics, University of Bonn, Bonn, Germany
| | - Dmitry Prokopenko
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Julian Hecker
- Working Group of Genomic Mathematics, University of Bonn, Bonn, Germany
| | - Michael H Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Edwin K Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Scott T Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Rudolph E Tanzi
- Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, United States of America
| | - Christoph Lange
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
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Prokopenko D, Hecker J, Silverman EK, Pagano M, Nöthen MM, Dina C, Lange C, Fier HL. Utilizing the Jaccard index to reveal population stratification in sequencing data: a simulation study and an application to the 1000 Genomes Project. Bioinformatics 2015; 32:1366-72. [PMID: 26722118 DOI: 10.1093/bioinformatics/btv752] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Accepted: 12/19/2015] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Population stratification is one of the major sources of confounding in genetic association studies, potentially causing false-positive and false-negative results. Here, we present a novel approach for the identification of population substructure in high-density genotyping data/next generation sequencing data. The approach exploits the co-appearances of rare genetic variants in individuals. The method can be applied to all available genetic loci and is computationally fast. Using sequencing data from the 1000 Genomes Project, the features of the approach are illustrated and compared to existing methodology (i.e. EIGENSTRAT). We examine the effects of different cutoffs for the minor allele frequency on the performance of the approach. We find that our approach works particularly well for genetic loci with very small minor allele frequencies. The results suggest that the inclusion of rare-variant data/sequencing data in our approach provides a much higher resolution picture of population substructure than it can be obtained with existing methodology. Furthermore, in simulation studies, we find scenarios where our method was able to control the type 1 error more precisely and showed higher power. AVAILABILITY AND IMPLEMENTATION CONTACT dmitry.prokopenko@uni-bonn.de SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Julian Hecker
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany
| | | | - Marcello Pagano
- Department of Biostatistics, Harvard School of Public Health, Boston, USA
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Christian Dina
- Institut National de la Santé et de la Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, l'institut du thorax, Nantes, France, Centre National de la Recherche Scientifique (CNRS) UMR 6291, l'institut du thorax, Nantes, France, Université de Nantes, l'institut du thorax, Nantes, France and Centre Hospitalier Universitaire (CHU) de Nantes, l'institut du thorax, Service de Cardiologie, Nantes, France
| | - Christoph Lange
- Channing Division of Network Medicine, Brigham and Women's Hospital, Department of Biostatistics, Harvard School of Public Health, Boston, USA
| | - Heide Loehlein Fier
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany, Department of Biostatistics, Harvard School of Public Health, Boston, USA
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38
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Hecker J, Prokopenko D, Lange C, Fier HL. On the Recombination Rate Estimation in the Presence of Population Substructure. PLoS One 2015; 10:e0145152. [PMID: 26716445 PMCID: PMC4696844 DOI: 10.1371/journal.pone.0145152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2015] [Accepted: 11/25/2015] [Indexed: 11/19/2022] Open
Abstract
As recombination events are not uniformly distributed along the human genome, the estimation of fine-scale recombination maps, e.g. HapMap Project, has been one of the major research endeavors over the last couple of years. For simulation studies, these estimates provide realistic reference scenarios to design future study and to develop novel methodology. To achieve a feasible framework for the estimation of such recombination maps, existing methodology uses sample probabilities for a two-locus model with recombination, with recent advances allowing for computationally fast implementations. In this work, we extend the existing theoretical framework for the recombination rate estimation to the presence of population substructure. We show under which assumptions the existing methodology can still be applied. We illustrate our extension of the methodology by an extensive simulation study.
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Affiliation(s)
- Julian Hecker
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany
- * E-mail:
| | | | - Christoph Lange
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany
- Department of Biostatistics, Harvard School of Public Health, Boston, United States of America
- Channing Laboratory, Brigham and Women’s Hospital, Boston, United States of America
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Heide Löhlein Fier
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany
- Department of Biostatistics, Harvard School of Public Health, Boston, United States of America
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39
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Prokopenko D, Hecker J, Silverman E, Nöthen MM, Schmid M, Lange C, Loehlein Fier H. Using Network Methodology to Infer Population Substructure. PLoS One 2015; 10:e0130708. [PMID: 26098940 PMCID: PMC4476755 DOI: 10.1371/journal.pone.0130708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2015] [Accepted: 05/22/2015] [Indexed: 11/24/2022] Open
Abstract
One of the main caveats of association studies is the possible affection by bias due to population stratification. Existing methods rely on model-based approaches like structure and ADMIXTURE or on principal component analysis like EIGENSTRAT. Here we provide a novel visualization technique and describe the problem of population substructure from a graph-theoretical point of view. We group the sequenced individuals into triads, which depict the relational structure, on the basis of a predefined pairwise similarity measure. We then merge the triads into a network and apply community detection algorithms in order to identify homogeneous subgroups or communities, which can further be incorporated as covariates into logistic regression. We apply our method to populations from different continents in the 1000 Genomes Project and evaluate the type 1 error based on the empirical p-values. The application to 1000 Genomes data suggests that the network approach provides a very fine resolution of the underlying ancestral population structure. Besides we show in simulations, that in the presence of discrete population structures, our developed approach maintains the type 1 error more precisely than existing approaches.
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Affiliation(s)
- Dmitry Prokopenko
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- * E-mail:
| | - Julian Hecker
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Edwin Silverman
- Channing Laboratory, Brigham and Women's Hospital, Boston, United States of America
| | | | - Matthias Schmid
- Institute of Medical Biometrics, Informatics and Epidemiology, University of Bonn, Bonn, Germany
| | - Christoph Lange
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany
- Department of Biostatistics, Harvard School of Public Health, Boston, United States of America
- Channing Laboratory, Brigham and Women's Hospital, Boston, United States of America
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Heide Loehlein Fier
- Institute of Genomic Mathematics, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
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Fier H, Won S, Prokopenko D, AlChawa T, Ludwig KU, Fimmers R, Silverman EK, Pagano M, Mangold E, Lange C. 'Location, Location, Location': a spatial approach for rare variant analysis and an application to a study on non-syndromic cleft lip with or without cleft palate. Bioinformatics 2012; 28:3027-33. [PMID: 23044548 PMCID: PMC3516147 DOI: 10.1093/bioinformatics/bts568] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Motivation: For the analysis of rare variants in sequence data, numerous approaches have been suggested. Fixed and flexible threshold approaches collapse the rare variant information of a genomic region into a test statistic with reduced dimensionality. Alternatively, the rare variant information can be combined in statistical frameworks that are based on suitable regression models, machine learning, etc. Although the existing approaches provide powerful tests that can incorporate information on allele frequencies and prior biological knowledge, differences in the spatial clustering of rare variants between cases and controls cannot be incorporated. Based on the assumption that deleterious variants and protective variants cluster or occur in different parts of the genomic region of interest, we propose a testing strategy for rare variants that builds on spatial cluster methodology and that guides the identification of the biological relevant segments of the region. Our approach does not require any assumption about the directions of the genetic effects. Results: In simulation studies, we assess the power of the clustering approach and compare it with existing methodology. Our simulation results suggest that the clustering approach for rare variants is well powered, even in situations that are ideal for standard methods. The efficiency of our spatial clustering approach is not affected by the presence of rare variants that have opposite effect size directions. An application to a sequencing study for non-syndromic cleft lip with or without cleft palate (NSCL/P) demonstrates its practical relevance. The proposed testing strategy is applied to a genomic region on chromosome 15q13.3 that was implicated in NSCL/P etiology in a previous genome-wide association study, and its results are compared with standard approaches. Availability: Source code and documentation for the implementation in R will be provided online. Currently, the R-implementation only supports genotype data. We currently are working on an extension for VCF files. Contact:heide.fier@googlemail.com
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Affiliation(s)
- Heide Fier
- Department of Genomic Mathematics, University of Bonn, 53127, Germany.
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