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Huan T, Joehanes R, Schurmann C, Schramm K, Pilling LC, Peters MJ, Mägi R, DeMeo D, O'Connor GT, Ferrucci L, Teumer A, Homuth G, Biffar R, Völker U, Herder C, Waldenberger M, Peters A, Zeilinger S, Metspalu A, Hofman A, Uitterlinden AG, Hernandez DG, Singleton AB, Bandinelli S, Munson PJ, Lin H, Benjamin EJ, Esko T, Grabe HJ, Prokisch H, van Meurs JBJ, Melzer D, Levy D. A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking. Hum Mol Genet 2018; 25:4611-4623. [PMID: 28158590 DOI: 10.1093/hmg/ddw288] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Revised: 07/21/2016] [Accepted: 08/25/2016] [Indexed: 01/03/2023] Open
Abstract
Cigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a meta-analysis of transcriptome-wide gene expression using whole blood-derived RNA from 10,233 participants of European ancestry in six cohorts (including 1421 current and 3955 former smokers) to identify associations between smoking and altered gene expression levels. At a false discovery rate (FDR) <0.1, we identified 1270 differentially expressed genes in current vs. never smokers, and 39 genes in former vs. never smokers. Expression levels of 12 genes remained elevated up to 30 years after smoking cessation, suggesting that the molecular consequence of smoking may persist for decades. Gene ontology analysis revealed enrichment of smoking-related genes for activation of platelets and lymphocytes, immune response, and apoptosis. Many of the top smoking-related differentially expressed genes, including LRRN3 and GPR15, have DNA methylation loci in promoter regions that were recently reported to be hypomethylated among smokers. By linking differential gene expression with smoking-related disease phenotypes, we demonstrated that stroke and pulmonary function show enrichment for smoking-related gene expression signatures. Mediation analysis revealed the expression of several genes (e.g. ALAS2) to be putative mediators of the associations between smoking and inflammatory biomarkers (IL6 and C-reactive protein levels). Our transcriptomic study provides potential insights into the effects of cigarette smoking on gene expression in whole blood and their relations to smoking-related diseases. The results of such analyses may highlight attractive targets for treating or preventing smoking-related health effects.
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Affiliation(s)
- Tianxiao Huan
- Boston University’s Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Roby Joehanes
- Boston University’s Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA.,Hebrew SeniorLife, Harvard Medical School, Boston, MA, USA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.,Genetics of Obesity & Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Katharina Schramm
- Institute of Human Genetics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Luke C Pilling
- Epidemiology and Public Health Group, Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - Marjolein J Peters
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands.,The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands
| | - Reedik Mägi
- The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands
| | | | - George T O'Connor
- Boston University School of Medicine and School of Public Health, Boston, MA, USA
| | - Luigi Ferrucci
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Alexander Teumer
- Institute for Community Medicine, University of Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Reiner Biffar
- Department of Prosthetic Dentistry, Gerostomatology and Dental Materials, Center of Oral Health, University Medicine Greifswald, Greifswald, Germany
| | - Uwe Völker
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Christian Herder
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Research Unit of Molecular Epidemiology, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Epidemiology II, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Sonja Zeilinger
- Institute of Epidemiology II, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Andres Metspalu
- The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands.,The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands.,The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands
| | - Albert Hofman
- The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus Medical Center Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands.,The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus Medical Center Rotterdam, The Netherlands
| | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | | | - Peter J Munson
- Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, MD, USA
| | - Honghuang Lin
- Boston University School of Medicine and School of Public Health, Boston, MA, USA
| | - Emelia J Benjamin
- Boston University’s Framingham Heart Study, Framingham, MA, USA.,The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands.,The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands.,Boston University School of Medicine and School of Public Health, Boston, MA, USA.,The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands
| | - Tõnu Esko
- The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands.,Division of Endocrinology, Boston Children's Hospital, Boston, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.,German Center for Neurodegenerative Diseases DZNE, Site Rostock/Greifswald, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands.,The Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging (NGI-NCHA), Leiden/Rotterdam, The Netherlands
| | - David Melzer
- Epidemiology and Public Health Group, Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK
| | - Daniel Levy
- Boston University’s Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
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2
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Peters MJ, Joehanes R, Pilling LC, Schurmann C, Conneely KN, Powell J, Reinmaa E, Sutphin GL, Zhernakova A, Schramm K, Wilson YA, Kobes S, Tukiainen T, Ramos YF, Göring HHH, Fornage M, Liu Y, Gharib SA, Stranger BE, De Jager PL, Aviv A, Levy D, Murabito JM, Munson PJ, Huan T, Hofman A, Uitterlinden AG, Rivadeneira F, van Rooij J, Stolk L, Broer L, Verbiest MMPJ, Jhamai M, Arp P, Metspalu A, Tserel L, Milani L, Samani NJ, Peterson P, Kasela S, Codd V, Peters A, Ward-Caviness CK, Herder C, Waldenberger M, Roden M, Singmann P, Zeilinger S, Illig T, Homuth G, Grabe HJ, Völzke H, Steil L, Kocher T, Murray A, Melzer D, Yaghootkar H, Bandinelli S, Moses EK, Kent JW, Curran JE, Johnson MP, Williams-Blangero S, Westra HJ, McRae AF, Smith JA, Kardia SLR, Hovatta I, Perola M, Ripatti S, Salomaa V, Henders AK, Martin NG, Smith AK, Mehta D, Binder EB, Nylocks KM, Kennedy EM, Klengel T, Ding J, Suchy-Dicey AM, Enquobahrie DA, Brody J, Rotter JI, Chen YDI, Houwing-Duistermaat J, Kloppenburg M, Slagboom PE, Helmer Q, den Hollander W, Bean S, Raj T, Bakhshi N, Wang QP, Oyston LJ, Psaty BM, Tracy RP, Montgomery GW, Turner ST, Blangero J, Meulenbelt I, Ressler KJ, Yang J, Franke L, Kettunen J, Visscher PM, Neely GG, Korstanje R, Hanson RL, Prokisch H, Ferrucci L, Esko T, Teumer A, van Meurs JBJ, Johnson AD. The transcriptional landscape of age in human peripheral blood. Nat Commun 2015; 6:8570. [PMID: 26490707 PMCID: PMC4639797 DOI: 10.1038/ncomms9570] [Citation(s) in RCA: 407] [Impact Index Per Article: 45.2] [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: 01/16/2015] [Accepted: 09/07/2015] [Indexed: 02/08/2023] Open
Abstract
Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the ‘transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts. Ageing increases the risk of many diseases. Here the authors compare blood cell transcriptomes of over 14,000 individuals and identify a set of about 1,500 genes that are differently expressed with age, shedding light on transcriptional programs linked to the ageing process and age-associated diseases.
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Affiliation(s)
- Marjolein J Peters
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands
| | - Roby Joehanes
- The National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts 01702, USA.,Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20817, USA
| | - Luke C Pilling
- Epidemiology and Public Health, University of Exeter Medical School, Exeter EX4 1DB, UK
| | - Claudia Schurmann
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17493, Germany.,The Charles Bronfman Institute for Personalized Medicine, Genetics of Obesity &Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York 10029, USA
| | - Karen N Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, Georgia 30301, USA
| | - Joseph Powell
- Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, University of Queensland, St Lucia, Brisbane, Queensland 4000, Australia.,The Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4000, Australia
| | - Eva Reinmaa
- Estonian Genome Center, University of Tartu, Tartu 0794, Estonia
| | - George L Sutphin
- Nathan Shock Center of Excellence in the Basic Biology of Aging, The Jackson Laboratory, Bar Harbor, Maine 04609, USA
| | - Alexandra Zhernakova
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen 9700RB, The Netherlands
| | - Katharina Schramm
- Institute of Human Genetics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany.,Institute of Human Genetics, Technical University Munich, Munich 85540, Germany
| | - Yana A Wilson
- Neuroscience Division, Garvan Institute of Medical Research, Australia and Charles Perkins Centre and School of Molecular Bioscience, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona 85001, USA
| | - Taru Tukiainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki 00131, Finland.,Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00131, Finland
| | | | - Yolande F Ramos
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands
| | - Harald H H Göring
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78201, USA
| | - Myriam Fornage
- Division of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Sciences, Center at Houston, Texas 77001, USA.,Institute of Molecular Medicine, University of Texas Health Sciences Center at Houston, Houston, Texas 77001, USA
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina 27101, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, University of Washington, Seattle, Washington 98101, USA
| | - Barbara E Stranger
- Section of Genetic Medicine, Institute for Genomics and Systems Biology, University of Chicago, Chicago, Illinois 60290, USA
| | - Philip L De Jager
- Program in Translational NeuroPsychiatric Genomics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02108, USA
| | - Abraham Aviv
- Center of Human Development and Aging, New Jersey Medical School, Newark 07101, USA
| | - Daniel Levy
- The National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts 01702, USA.,Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20817, USA
| | - Joanne M Murabito
- The National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts 01702, USA.,General Internal Medicine Section, Boston University, Boston, Massachusetts 02108, USA
| | - Peter J Munson
- The Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health, Bethesda, Maryland 20817, USA
| | - Tianxiao Huan
- The National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts 01702, USA.,Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20817, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000CA, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands.,Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000CA, The Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands.,Department of Epidemiology, Erasmus Medical Center, Rotterdam 3000CA, The Netherlands
| | - Jeroen van Rooij
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands
| | - Lisette Stolk
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands
| | - Linda Broer
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands
| | - Michael M P J Verbiest
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands
| | - Mila Jhamai
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands
| | - Pascal Arp
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 0794, Estonia
| | - Liina Tserel
- Molecular Pathology, Institute of Biomedicine, University of Tartu, Tartu 0794, Estonia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu 0794, Estonia
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE1, UK.,National Institute for Health Research Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE1, UK
| | - Pärt Peterson
- Molecular Pathology, Institute of Biomedicine, University of Tartu, Tartu 0794, Estonia
| | - Silva Kasela
- Institute of Molecular and Cell Biology, Estonian Genome Center, University of Tartu, Tartu 0794, Estonia
| | - Veryan Codd
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE1, UK.,National Institute for Health Research Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE1, UK
| | - Annette Peters
- Institute of Epidemiologie II, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Cavin K Ward-Caviness
- Institute of Epidemiologie II, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Christian Herder
- Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf 40593, Germany
| | - Melanie Waldenberger
- Institute of Epidemiologie II, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Michael Roden
- Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf 40593, Germany.,Division of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf 40593, Germany
| | - Paula Singmann
- Institute of Epidemiologie II, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Sonja Zeilinger
- Institute of Epidemiologie II, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Neuherberg 85764, Germany
| | - Thomas Illig
- Hannover Unified Biobank, Hannover Medical School, Hannover 30519, Germany
| | - Georg Homuth
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17493, Germany
| | - Hans-Jörgen Grabe
- Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, University Medicine Greifswald, Greifswald 17489, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald 17489, Germany
| | - Leif Steil
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17493, Germany
| | - Thomas Kocher
- Unit of Periodontology, Department of Restorative Dentistry, Periodontology and Endodontology, University Medicine Greifswald, Greifswald 17489, Germany
| | - Anna Murray
- Epidemiology and Public Health, University of Exeter Medical School, Exeter EX4 1DB, UK
| | - David Melzer
- Epidemiology and Public Health, University of Exeter Medical School, Exeter EX4 1DB, UK
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK
| | | | - Eric K Moses
- Centre for Genetic Origins of Health and Disease, The University of Western Australia, and Faculty of Health Sciences, Curtin University, Perth, Western Australia 9011, Australia
| | - Jack W Kent
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78201, USA
| | - Joanne E Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78201, USA
| | - Matthew P Johnson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78201, USA
| | | | - Harm-Jan Westra
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen 9700RB, The Netherlands.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge 02138, USA.,Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02108, USA.,Partners Center for Personalized Genetic Medicine, Boston, Massachusetts 02108, USA
| | - Allan F McRae
- The Queensland Brain Institute, University of Queensland, Brisbane, Queensland 4000, Australia.,University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4000, Australia
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan 48103, USA
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan 48103, USA
| | - Iiris Hovatta
- Department of Biosciences, University of Helsinki, Helsinki 00100, Finland.,Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, Helsinki 00100, Finland
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu 0794, Estonia.,Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki 00131, Finland.,Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00131, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki 00131, Finland.,Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00131, Finland.,Wellcome Trust Sanger Institute, Hinxton, Cambridge CB4, UK.,Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki 00100, Finland
| | - Veikko Salomaa
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00131, Finland
| | - Anjali K Henders
- The Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland 4000, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4000, Australia
| | - Alicia K Smith
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia 30301, USA
| | - Divya Mehta
- Max-Planck Institute of Psychiatry, Munich 80331, Germany
| | | | - K Maria Nylocks
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia 30301, USA
| | - Elizabeth M Kennedy
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, Georgia 30301, USA
| | | | - Jingzhong Ding
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27101, USA
| | - Astrid M Suchy-Dicey
- Department of Epidemiology, University of Washington, Seattle, Washington 98101, USA
| | - Daniel A Enquobahrie
- Department of Epidemiology, University of Washington, Seattle, Washington 98101, USA
| | - Jennifer Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington 98101, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90501, USA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California 90501, USA
| | | | - Margreet Kloppenburg
- Department of Rheumatology, Leiden University Medical Center, Leiden 2300RC, The Netherlands.,Department of Clinical Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands
| | - P Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands
| | - Quinta Helmer
- Department of Medical Statistics, Leiden University Medical Center, Leiden 2300RC, The Netherlands
| | - Wouter den Hollander
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands
| | - Shannon Bean
- Nathan Shock Center of Excellence in the Basic Biology of Aging, The Jackson Laboratory, Bar Harbor, Maine 04609, USA
| | - Towfique Raj
- Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts 02138, USA
| | - Noman Bakhshi
- Neuroscience Division, Garvan Institute of Medical Research, Australia and Charles Perkins Centre and School of Molecular Bioscience, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Qiao Ping Wang
- Neuroscience Division, Garvan Institute of Medical Research, Australia and Charles Perkins Centre and School of Molecular Bioscience, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Lisa J Oyston
- Neuroscience Division, Garvan Institute of Medical Research, Australia and Charles Perkins Centre and School of Molecular Bioscience, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington 98195, USA.,Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA.,Cardiovascular Health Research Unit, Department of Health Services, University of Washington, Seattle, Washington 98195, USA.,Group Health Research Institute, Group Health Cooperative, Seattle, Washington 98195, USA
| | - Russell P Tracy
- Department of Pathology, University of Vermont College of Medicine, Colchester, Vermont 98195, USA
| | - Grant W Montgomery
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4000, Australia
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, Minnesota 55901, USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, Texas 78201, USA
| | - Ingrid Meulenbelt
- Department of Molecular Epidemiology, Leiden University Medical Center, Leiden 2300RC, The Netherlands
| | - Kerry J Ressler
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia 30301, USA
| | - Jian Yang
- The Queensland Brain Institute, University of Queensland, Brisbane, Queensland 4000, Australia.,University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4000, Australia
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen 9700RB, The Netherlands
| | - Johannes Kettunen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki 00131, Finland.,Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki 00131, Finland.,Computational Medicine, Institute of Health Sciences, Faculty of Medicine, University of Oulu, Oulu 90570, Finland
| | - Peter M Visscher
- The Queensland Brain Institute, University of Queensland, Brisbane, Queensland 4000, Australia.,University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4000, Australia
| | - G Gregory Neely
- Neuroscience Division, Garvan Institute of Medical Research, Australia and Charles Perkins Centre and School of Molecular Bioscience, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Ron Korstanje
- Nathan Shock Center of Excellence in the Basic Biology of Aging, The Jackson Laboratory, Bar Harbor, Maine 04609, USA
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Disease, National Institutes of Health, Phoenix, Arizona 85001, USA
| | - Holger Prokisch
- Institute of Human Genetics, Helmholz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany.,Institute of Human Genetics, Technical University Munich, Munich 85540, Germany
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland 21218, USA
| | - Tonu Esko
- Estonian Genome Center, University of Tartu, Tartu 0794, Estonia.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge 02138, USA.,Division of Endocrinology, Children's Hospital Boston, Boston, Massachusetts 02108, USA.,Department of Genetics, Harvard Medical School, Boston, Massachusetts 02108, USA
| | - Alexander Teumer
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald 17493, Germany
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus Medical Centre Rotterdam, Rotterdam 3000CA, The Netherlands
| | - Andrew D Johnson
- The National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, Massachusetts 01702, USA.,Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20817, USA
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3
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Zeller T, Haase T, Müller C, Riess H, Lau D, Zeller S, Krause J, Baumert J, Pless O, Dupuis J, Wild PS, Eleftheriadis M, Waldenberger M, Zeilinger S, Ziegler A, Peters A, Tiret L, Proust C, Marzi C, Munzel T, Strauch K, Prokisch H, Lackner KJ, Herder C, Thorand B, Benjamin EJ, Blankenberg S, Koenig W, Schnabel RB. Molecular Characterization of the NLRC4 Expression in Relation to Interleukin-18 Levels. ACTA ACUST UNITED AC 2015; 8:717-26. [PMID: 26362438 DOI: 10.1161/circgenetics.115.001079] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2015] [Accepted: 08/24/2015] [Indexed: 01/27/2023]
Abstract
BACKGROUND Interleukin-18 (IL-18) is a pleiotropic cytokine centrally involved in the cytokine cascade with complex immunomodulatory functions in innate and acquired immunity. Circulating IL-18 concentrations are associated with type 2 diabetes mellitus, cardiovascular events, and diverse inflammatory and autoimmune disorders. METHODS AND RESULTS To identify causal variants affecting circulating IL-18 concentrations, we applied various omics and molecular biology approaches. By genome-wide association study, we confirmed association of IL-18 levels with a single nucleotide polymorphism in the untranslated exon 2 of the inflammasome component NLRC4 (NLR family, caspase recruitment domain-containing 4) gene on chromosome 2 (rs385076; P=2.4 × 10(-45)). Subsequent molecular analyses by gene expression analysis and reporter gene assays indicated an effect of rs385076 on NLRC4 expression and differential isoform usage by modulating binding of the transcription factor PU.1. CONCLUSIONS Our study provides evidence for the functional causality of single nucleotide polymorphism rs385076 within the NLRC4 gene in relation to IL-18 activation.
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4
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Flaquer A, Rospleszcz S, Reischl E, Zeilinger S, Prokisch H, Meitinger T, Meisinger C, Peters A, Waldenberger M, Grallert H, Strauch K. Mitochondrial GWA Analysis of Lipid Profile Identifies Genetic Variants to Be Associated with HDL Cholesterol and Triglyceride Levels. PLoS One 2015; 10:e0126294. [PMID: 25945934 PMCID: PMC4422732 DOI: 10.1371/journal.pone.0126294] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Accepted: 03/31/2015] [Indexed: 11/18/2022] Open
Abstract
It has been suggested that mitochondrial dysfunction has an influence on lipid metabolism. The fact that mitochondrial defects can be accumulated over time as a normal part of aging may explain why cholesterol levels often are altered with age. To test the hypothesis whether mitochondrial variants are associated with lipid profile (total cholesterol, LDL, HDL, and triglycerides) we analyzed a total number of 978 mitochondrial single nucleotide polymorphisms (mtSNPs) in a sample of 2,815 individuals participating in the population-based KORA F4 study. To assess mtSNP association while taking the presence of heteroplasmy into account we used the raw signal intensity values measured on the microarray and applied linear regression. Ten mtSNPs (mt3285, mt3336, mt5285, mt6591, mt6671, mt9163, mt13855, mt13958, mt14000, and mt14580) were significantly associated with HDL cholesterol and one mtSNP (mt15074) with triglycerides levels. These results highlight the importance of the mitochondrial genome among the factors that contribute to the regulation of lipid levels. Focusing on mitochondrial variants may lead to further insights regarding the underlying physiological mechanisms, or even to the development of innovative treatments. Since this is the first mitochondrial genome-wide association analysis (mtGWAS) for lipid profile, further analyses are needed to follow up on the present findings.
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Affiliation(s)
- Antònia Flaquer
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany; Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Rospleszcz
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany; Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Eva Reischl
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Sonja Zeilinger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Christa Meisinger
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany; Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany; Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
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5
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Lee KWK, Richmond R, Hu P, French L, Shin J, Bourdon C, Reischl E, Waldenberger M, Zeilinger S, Gaunt T, McArdle W, Ring S, Woodward G, Bouchard L, Gaudet D, Smith GD, Relton C, Paus T, Pausova Z. Prenatal exposure to maternal cigarette smoking and DNA methylation: epigenome-wide association in a discovery sample of adolescents and replication in an independent cohort at birth through 17 years of age. Environ Health Perspect 2015; 123:193-9. [PMID: 25325234 PMCID: PMC4314251 DOI: 10.1289/ehp.1408614] [Citation(s) in RCA: 117] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2014] [Accepted: 10/16/2014] [Indexed: 05/17/2023]
Abstract
BACKGROUND Prenatal exposure to maternal cigarette smoking (prenatal smoke exposure) had been associated with altered DNA methylation (DNAm) at birth. OBJECTIVE We examined whether such alterations are present from birth through adolescence. METHODS We used the Infinium HumanMethylation450K BeadChip to search across 473,395 CpGs for differential DNAm associated with prenatal smoke exposure during adolescence in a discovery cohort (n = 132) and at birth, during childhood, and during adolescence in a replication cohort (n = 447). RESULTS In the discovery cohort, we found five CpGs in MYO1G (top-ranking CpG: cg12803068, p = 3.3 × 10-11) and CNTNAP2 (cg25949550, p = 4.0 × 10-9) to be differentially methylated between exposed and nonexposed individuals during adolescence. The CpGs in MYO1G and CNTNAP2 were associated, respectively, with higher and lower DNAm in exposed versus nonexposed adolescents. The same CpGs were differentially methylated at birth, during childhood, and during adolescence in the replication cohort. In both cohorts and at all developmental time points, the differential DNAm was in the same direction and of a similar magnitude, and was not altered appreciably by adjustment for current smoking by the participants or their parents. In addition, four of the five EWAS (epigenome-wide association study)-significant CpGs in the adolescent discovery cohort were also among the top sites of differential methylation in a previous birth cohort, and differential methylation of CpGs in CYP1A1, AHRR, and GFI1 observed in that study was also evident in our discovery cohort. CONCLUSIONS Our findings suggest that modifications of DNAm associated with prenatal maternal smoking may persist in exposed offspring for many years-at least until adolescence.
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Affiliation(s)
- Ken W K Lee
- The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
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6
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Sharma V, Michel S, Gaertner V, Franke A, Vogelberg C, von Berg A, Bufe A, Heinzmann A, Laub O, Rietschel E, Simma B, Frischer T, Genuneit J, Zeilinger S, Illig T, Schedel M, Potaczek DP, Kabesch M. Fine-mapping of IgE-associated loci 1q23, 5q31, and 12q13 using 1000 Genomes Project data. Allergy 2014; 69:1077-84. [PMID: 24930997 DOI: 10.1111/all.12431] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/17/2014] [Indexed: 12/21/2022]
Abstract
BACKGROUND Genome-wide association studies (GWAS) repeatedly identified 1q23 (FCER1A), 5q31 (RAD50-IL13 and IL4), and 12q13 (STAT6) as major susceptibility loci influencing the regulation of total serum IgE levels. As GWAS may be insufficient to capture causal variants, we performed fine-mapping and re-genotyping of the three loci using 1000 Genomes Project datasets. METHODS Linkage disequilibrium tagging polymorphisms and polymorphisms of putative functional relevance were genotyped by chip technology (24 polymorphisms) or MALDI-TOF-MS (40 polymorphisms) in at least 1303 German children (651 asthmatics). The effect of polymorphisms on total serum IgE, IgE percentiles, and atopic diseases was assessed, and a risk score model was applied for gene-by-gene interaction analyses. Functional effects of putative causal variants from these three loci were studied in silico. RESULTS Associations from GWAS were confirmed and extended. For 1q23 and 5q31, the majority of associations were found with mild to moderately elevated IgE levels, while in the 12q13 locus, single-nucleotide polymorphisms (SNPs) were associated with strongly elevated IgE levels. Gene-by-gene interaction analyses suggested that the presence of mutations in all three loci increases the risk for elevated IgE up to fourfold. CONCLUSION This fine-mapping study confirmed previous associations and identified novel associations of SNPs in 1q23, 5q31, and 12q13 with different levels of serum IgE and their concomitant contribution to IgE regulation.
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Affiliation(s)
- V. Sharma
- Department of Pediatric Pneumology, Allergy and Neonatology; Hannover Medical School; Hannover Germany
| | - S. Michel
- Department of Pediatric Pneumology, Allergy and Neonatology; Hannover Medical School; Hannover Germany
- Department of Pediatric Pneumology and Allergy; University Children's Hospital Regensburg (KUNO); Regensburg Germany
| | - V. Gaertner
- Department of Pediatric Pneumology and Allergy; University Children's Hospital Regensburg (KUNO); Regensburg Germany
| | - A. Franke
- Institute of Clinical Molecular Biology; Christian-Albrechts-University Kiel; Kiel Germany
| | - C. Vogelberg
- University Children's Hospital; Technical University Dresden; Dresden Germany
| | - A. von Berg
- Children's Department; Research Institute for the Prevention of Allergic Diseases; Marien-Hospital; Wesel Germany
| | - A. Bufe
- Department of Experimental Pneumology; Ruhr-University; Bochum Germany
| | - A. Heinzmann
- University Children's Hospital; Albert Ludwigs University; Freiburg Germany
| | - O. Laub
- Kinder-und Jugendarztpraxis Laub; Rosenheim Germany
| | - E. Rietschel
- University Children's Hospital; University of Cologne; Cologne Germany
| | - B. Simma
- Children's Department; University Teaching Hospital; Landeskrankenhaus Feldkirch; Feldkirch Austria
| | - T. Frischer
- University Children's Hospital Vienna; Vienna Austria
| | - J. Genuneit
- Institute of Epidemiology and Medical Biometry; Ulm University; Ulm Germany
| | - S. Zeilinger
- Research Unit of Molecular Epidemiology; Helmholtz Zentrum Munich; Neuherberg Germany
| | - T. Illig
- Research Unit of Molecular Epidemiology; Helmholtz Zentrum Munich; Neuherberg Germany
- Hannover Unified Biobank; Hannover Medical School; Hannover Germany
| | - M. Schedel
- Division of Cell Biology; Department of Pediatrics; National Jewish Health; Denver CO USA
| | - D. P. Potaczek
- Department of Pediatric Pneumology, Allergy and Neonatology; Hannover Medical School; Hannover Germany
- Institute of Laboratory Medicine; Philipps-Universität Marburg; Marburg Germany
| | - M. Kabesch
- Department of Pediatric Pneumology, Allergy and Neonatology; Hannover Medical School; Hannover Germany
- Department of Pediatric Pneumology and Allergy; University Children's Hospital Regensburg (KUNO); Regensburg Germany
- German Lung Research Center (DZL)
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7
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Wahl S, Fenske N, Zeilinger S, Suhre K, Gieger C, Waldenberger M, Grallert H, Schmid M. On the potential of models for location and scale for genome-wide DNA methylation data. BMC Bioinformatics 2014; 15:232. [PMID: 24994026 PMCID: PMC4227139 DOI: 10.1186/1471-2105-15-232] [Citation(s) in RCA: 13] [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: 03/18/2014] [Accepted: 06/26/2014] [Indexed: 01/05/2023] Open
Abstract
Background With the help of epigenome-wide association studies (EWAS), increasing knowledge on the role of epigenetic mechanisms such as DNA methylation in disease processes is obtained. In addition, EWAS aid the understanding of behavioral and environmental effects on DNA methylation. In terms of statistical analysis, specific challenges arise from the characteristics of methylation data. First, methylation β-values represent proportions with skewed and heteroscedastic distributions. Thus, traditional modeling strategies assuming a normally distributed response might not be appropriate. Second, recent evidence suggests that not only mean differences but also variability in site-specific DNA methylation associates with diseases, including cancer. The purpose of this study was to compare different modeling strategies for methylation data in terms of model performance and performance of downstream hypothesis tests. Specifically, we used the generalized additive models for location, scale and shape (GAMLSS) framework to compare beta regression with Gaussian regression on raw, binary logit and arcsine square root transformed methylation data, with and without modeling a covariate effect on the scale parameter. Results Using simulated and real data from a large population-based study and an independent sample of cancer patients and healthy controls, we show that beta regression does not outperform competing strategies in terms of model performance. In addition, Gaussian models for location and scale showed an improved performance as compared to models for location only. The best performance was observed for the Gaussian model on binary logit transformed β-values, referred to as M-values. Our results further suggest that models for location and scale are specifically sensitive towards violations of the distribution assumption and towards outliers in the methylation data. Therefore, a resampling procedure is proposed as a mode of inference and shown to diminish type I error rate in practically relevant settings. We apply the proposed method in an EWAS of BMI and age and reveal strong associations of age with methylation variability that are validated in an independent sample. Conclusions Models for location and scale are promising tools for EWAS that may help to understand the influence of environmental factors and disease-related phenotypes on methylation variability and its role during disease development.
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Affiliation(s)
- Simone Wahl
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany.
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8
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Albrecht E, Waldenberger M, Krumsiek J, Evans AM, Jeratsch U, Breier M, Adamski J, Koenig W, Zeilinger S, Fuchs C, Klopp N, Theis FJ, Wichmann HE, Suhre K, Illig T, Strauch K, Peters A, Gieger C, Kastenmüller G, Doering A, Meisinger C. Metabolite profiling reveals new insights into the regulation of serum urate in humans. Metabolomics 2014; 10:141-151. [PMID: 24482632 PMCID: PMC3890072 DOI: 10.1007/s11306-013-0565-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [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: 02/22/2013] [Accepted: 07/03/2013] [Indexed: 01/27/2023]
Abstract
Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia.
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Affiliation(s)
- Eva Albrecht
- 0000 0004 0483 2525grid.4567.0Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Melanie Waldenberger
- 0000 0004 0483 2525grid.4567.0Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jan Krumsiek
- 0000 0004 0483 2525grid.4567.0Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Anne M. Evans
- grid.429438.0Metabolon, Inc., 617 Davis Drive, Suite 400, Durham, NC 27713 USA
| | - Ulli Jeratsch
- 0000 0004 0483 2525grid.4567.0Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Michaela Breier
- 0000 0004 0483 2525grid.4567.0Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- 0000 0004 0483 2525grid.4567.0Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 0000000123222966grid.6936.aLehrstuhl für Experimentelle Genetik, Technische Universität München, Munich, Germany
- grid.452622.5Member of German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Wolfgang Koenig
- grid.410712.1Department of Internal Medicine II-Cardiology, University of Ulm Medical Center, Ulm, Germany
| | - Sonja Zeilinger
- 0000 0004 0483 2525grid.4567.0Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Christiane Fuchs
- 0000 0004 0483 2525grid.4567.0Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Norman Klopp
- 0000 0004 0483 2525grid.4567.0Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 0000 0000 9529 9877grid.10423.34Hanover Unified Biobank, Hanover Medical School, Hanover, Germany
| | - Fabian J. Theis
- 0000 0004 0483 2525grid.4567.0Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - H.-Erich Wichmann
- 0000 0004 0483 2525grid.4567.0Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 0000 0004 1936 973Xgrid.5252.0Institute of Medical Informatics, Biometry, and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- 0000 0004 0477 2585grid.411095.8Klinikum Grosshadern, Munich, Germany
| | - Karsten Suhre
- 0000 0004 0483 2525grid.4567.0Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 0000 0004 0582 4340grid.416973.eDepartment of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Education City-Qatar Foundation, Doha, Qatar
| | - Thomas Illig
- 0000 0004 0483 2525grid.4567.0Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 0000 0000 9529 9877grid.10423.34Hanover Unified Biobank, Hanover Medical School, Hanover, Germany
| | - Konstantin Strauch
- 0000 0004 1936 973Xgrid.5252.0Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- 0000 0004 0483 2525grid.4567.0Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- 0000 0004 0483 2525grid.4567.0Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 0000 0004 0483 2525grid.4567.0Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Munich Heart Alliance, Munich, Germany
| | - Christian Gieger
- 0000 0004 0483 2525grid.4567.0Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Gabi Kastenmüller
- 0000 0004 0483 2525grid.4567.0Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Angela Doering
- 0000 0004 0483 2525grid.4567.0Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 0000 0004 0483 2525grid.4567.0Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Christa Meisinger
- 0000 0004 0483 2525grid.4567.0Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- 0000 0000 9312 0220grid.419801.5Central Hospital of Augsburg, Monitoring Trends and Determinants on Cardiovascular Diseases/Cooperative Research in the Region of Augsburg Myocardial Infarction Registry, Augsburg, Germany
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9
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Schieck M, Michel S, Suttner K, Illig T, Zeilinger S, Franke A, Vogelberg C, von Berg A, Bufe A, Heinzmann A, Laub O, Rietschel E, Simma B, Frischer T, Genuneit J, Kerzel S, Kabesch M. Genetic variation in TH17 pathway genes, childhood asthma, and total serum IgE levels. J Allergy Clin Immunol 2013; 133:888-91. [PMID: 24184148 DOI: 10.1016/j.jaci.2013.08.048] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2013] [Revised: 07/04/2013] [Accepted: 08/26/2013] [Indexed: 10/26/2022]
Affiliation(s)
- Maximilian Schieck
- Department of Pediatric Pneumology and Allergy, University Children's Hospital Regensburg (KUNO), Regensburg, Germany; Department of Pediatric Pneumology, Allergy and Neonatology, Hannover Medical School, Hannover, Germany
| | - Sven Michel
- Department of Pediatric Pneumology and Allergy, University Children's Hospital Regensburg (KUNO), Regensburg, Germany; Department of Pediatric Pneumology, Allergy and Neonatology, Hannover Medical School, Hannover, Germany
| | - Kathrin Suttner
- Department of Pediatric Pneumology, Allergy and Neonatology, Hannover Medical School, Hannover, Germany; ZAUM - Center of Allergy and Environment, Technische Universität München and Helmholtz Center Munich, Munich, Germany; German Lung Research Center (DZL), Germany
| | - Thomas Illig
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany; Research Unit of Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
| | - Sonja Zeilinger
- Research Unit of Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Christian Vogelberg
- University Children's Hospital, Technical University Dresden, Dresden, Germany
| | - Andrea von Berg
- Research Institute for the Prevention of Allergic Diseases, Children's Department, Marien-Hospital, Wesel, Germany
| | - Albrecht Bufe
- Department of Experimental Pneumology, Ruhr-University, Bochum, Germany
| | - Andrea Heinzmann
- University Children's Hospital, Albert Ludwigs University, Freiburg, Germany
| | - Otto Laub
- Kinder- und Jugendarztpraxis Laub, Rosenheim, Germany
| | - Ernst Rietschel
- University Children's Hospital, University of Cologne, Cologne, Germany
| | - Burkhard Simma
- Children's Department, University Teaching Hospital, Landeskrankenhaus Feldkirch, Feldkirch, Austria
| | | | - Jon Genuneit
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - Sebastian Kerzel
- Department of Pediatric Pneumology and Allergy, University Children's Hospital Regensburg (KUNO), Regensburg, Germany
| | - Michael Kabesch
- Department of Pediatric Pneumology and Allergy, University Children's Hospital Regensburg (KUNO), Regensburg, Germany; Department of Pediatric Pneumology, Allergy and Neonatology, Hannover Medical School, Hannover, Germany; German Lung Research Center (DZL), Germany.
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10
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Petersen AK, Zeilinger S, Kastenmüller G, Römisch-Margl W, Brugger M, Peters A, Meisinger C, Strauch K, Hengstenberg C, Pagel P, Huber F, Mohney RP, Grallert H, Illig T, Adamski J, Waldenberger M, Gieger C, Suhre K. Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits. Hum Mol Genet 2013; 23:534-45. [PMID: 24014485 PMCID: PMC3869358 DOI: 10.1093/hmg/ddt430] [Citation(s) in RCA: 130] [Impact Index Per Article: 11.8] [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: 12/21/2022] Open
Abstract
Previously, we reported strong influences of genetic variants on metabolic phenotypes, some of them with clinical relevance. Here, we hypothesize that DNA methylation may have an important and potentially independent effect on human metabolism. To test this hypothesis, we conducted what is to the best of our knowledge the first epigenome-wide association study (EWAS) between DNA methylation and metabolic traits (metabotypes) in human blood. We assess 649 blood metabolic traits from 1814 participants of the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) population study for association with methylation of 457 004 CpG sites, determined on the Infinium HumanMethylation450 BeadChip platform. Using the EWAS approach, we identified two types of methylome–metabotype associations. One type is driven by an underlying genetic effect; the other type is independent of genetic variation and potentially driven by common environmental and life-style-dependent factors. We report eight CpG loci at genome-wide significance that have a genetic variant as confounder (P = 3.9 × 10−20 to 2.0 × 10−108, r2 = 0.036 to 0.221). Seven loci display CpG site-specific associations to metabotypes, but do not exhibit any underlying genetic signals (P = 9.2 × 10−14 to 2.7 × 10−27, r2 = 0.008 to 0.107). We further identify several groups of CpG loci that associate with a same metabotype, such as 4-vinylphenol sulfate and 4-androsten-3-beta,17-beta-diol disulfate. In these cases, the association between CpG-methylation and metabotype is likely the result of a common external environmental factor, including smoking. Our study shows that analysis of EWAS with large numbers of metabolic traits in large population cohorts are, in principle, feasible. Taken together, our data suggest that DNA methylation plays an important role in regulating human metabolism.
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Potaczek DP, Michel S, Sharma V, Zeilinger S, Vogelberg C, von Berg A, Bufe A, Heinzmann A, Laub O, Rietschel E, Simma B, Frischer T, Genuneit J, Illig T, Kabesch M. Different FCER1A polymorphisms influence IgE levels in asthmatics and non-asthmatics. Pediatr Allergy Immunol 2013; 24:441-9. [PMID: 23725541 DOI: 10.1111/pai.12083] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/10/2013] [Indexed: 01/31/2023]
Abstract
BACKGROUND Recently, three genome-wide association studies (GWAS) demonstrated FCER1A, the gene encoding a ligand-binding subunit of the high-affinity IgE receptor, to be a major susceptibility locus for serum IgE levels. The top association signal differed between the two studies from the general population and the one based on an asthma case-control design. In this study, we investigated whether different FCER1A polymorphisms are associated with total serum IgE in the general population and asthmatics specifically. METHODS Nineteen polymorphisms were studied in FCER1A based on a detailed literature search and a tagging approach. Polymorphisms were genotyped by the Illumina HumanHap300Chip (6 polymorphisms) or MALDI-TOF MS (13 polymorphisms) in at least 1303 children (651 asthmatics) derived from the German International Study of Asthma and Allergies in Childhood II and Multicentre Asthma Genetics in Childhood Study. RESULTS Similar to two population-based GWAS, the peak association with total serum IgE was observed for SNPs rs2511211, rs2427837, and rs2251746 (mean r(2) > 0.8), with the lowest p-value of 4.37 × 10(-6). The same 3 polymorphisms showed the strongest association in non-asthmatics (lowest p = 0.0003). While these polymorphisms were also associated with total serum IgE in asthmatics (lowest p = 0.003), additional polymorphisms (rs3845625, rs7522607, and rs2427829) demonstrated associations with total serum IgE in asthmatics only (lowest p = 0.01). CONCLUSIONS These data suggest that FCER1A polymorphisms not only drive IgE levels in the general population but that specific polymorphisms may also influence IgE in association with asthma, suggesting that disease-specific mechanisms in IgE regulation exist.
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Affiliation(s)
- Daniel P Potaczek
- Department of Pediatric Pneumology, Allergy and Neonatology, Hannover Medical School, Hannover, Germany
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12
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Zeilinger S, Kühnel B, Klopp N, Baurecht H, Kleinschmidt A, Gieger C, Weidinger S, Lattka E, Adamski J, Peters A, Strauch K, Waldenberger M, Illig T. Tobacco smoking leads to extensive genome-wide changes in DNA methylation. PLoS One 2013; 8:e63812. [PMID: 23691101 PMCID: PMC3656907 DOI: 10.1371/journal.pone.0063812] [Citation(s) in RCA: 567] [Impact Index Per Article: 51.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2012] [Accepted: 04/05/2013] [Indexed: 11/19/2022] Open
Abstract
Environmental factors such as tobacco smoking may have long-lasting effects on DNA methylation patterns, which might lead to changes in gene expression and in a broader context to the development or progression of various diseases. We conducted an epigenome-wide association study (EWAs) comparing current, former and never smokers from 1793 participants of the population-based KORA F4 panel, with replication in 479 participants from the KORA F3 panel, carried out by the 450K BeadChip with genomic DNA obtained from whole blood. We observed wide-spread differences in the degree of site-specific methylation (with p-values ranging from 9.31E-08 to 2.54E-182) as a function of tobacco smoking in each of the 22 autosomes, with the percent of variance explained by smoking ranging from 1.31 to 41.02. Depending on cessation time and pack-years, methylation levels in former smokers were found to be close to the ones seen in never smokers. In addition, methylation-specific protein binding patterns were observed for cg05575921 within AHRR, which had the highest level of detectable changes in DNA methylation associated with tobacco smoking (–24.40% methylation; p = 2.54E-182), suggesting a regulatory role for gene expression. The results of our study confirm the broad effect of tobacco smoking on the human organism, but also show that quitting tobacco smoking presumably allows regaining the DNA methylation state of never smokers.
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Affiliation(s)
- Sonja Zeilinger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Brigitte Kühnel
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Norman Klopp
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
| | - Hansjörg Baurecht
- Department of Dermatology, Allergology, and Venerology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
- Graduate School of Information Science in Health (GSISH), Technische Universität München, Munich, Germany
| | - Anja Kleinschmidt
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Stephan Weidinger
- Department of Dermatology, Allergology, and Venerology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Eva Lattka
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Neuherberg, Germany
- Chair of Experimental Genetics, Technische Universität München, Munich, Germany
| | - Annette Peters
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- * E-mail:
| | - Thomas Illig
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
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Kormann MSD, Hector A, Marcos V, Mays LE, Kappler M, Illig T, Klopp N, Zeilinger S, Carevic M, Rieber N, Eickmeier O, Zielen S, Gaggar A, Moepps B, Griese M, Hartl D. CXCR1 and CXCR2 haplotypes synergistically modulate cystic fibrosis lung disease. Eur Respir J 2011; 39:1385-90. [PMID: 22088968 DOI: 10.1183/09031936.00130011] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Cystic fibrosis (CF) lung disease severity is largely independent on the CF transmembrane conductance regulator (CFTR) genotype, indicating the contribution of genetic modifiers. The chemokine receptors CXCR1 and CXCR2 have been found to play essential roles in the pathogenesis of CF lung disease. Here, we determine whether genetic variation of CXCR1 and CXCR2 influences CF lung disease severity. Genomic DNA of CF patients in Germany (n = 442) was analysed for common variations in CXCR1 and CXCR2 using a single-nucleotide polymorphism (SNP) tagging approach. Associations of CXCR1 and CXCR2 SNPs and haplotypes with CF lung disease severity, CXCR1 and CXCR2 expression, and neutrophil effector functions were assessed. Four SNPs in CXCR1 and three in CXCR2 strongly correlated with age-adjusted lung function in CF patients. SNPs comprising haplotypes CXCR1_Ha and CXCR2_Ha were in high linkage disequilibrium and patients heterozygous for the CXCR1-2 haplotype cluster (CXCR1-2_Ha) had lower lung function compared with patients with homozygous wild-type alleles (forced expiratory volume in 1 s ≤ 70% predicted, OR 7.24; p = 2.30 × 10(-5)). CF patients carrying CXCR1-2_Ha showed decreased CXCR1 combined with increased CXCR2 mRNA and protein expression, and displayed disturbed antibacterial effector functions. CXCR1 and CXCR2 genotypes modulate lung function and antibacterial host defence in CF lung disease.
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Affiliation(s)
- Michael S D Kormann
- Children's hospital and Interdisciplinary Center for Infectious Diseases, University of Tübingen, Tübingen, Germany.
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14
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Koletzko B, Lattka E, Zeilinger S, Illig T, Steer C. Genetic variants of the fatty acid desaturase gene cluster predict amounts of red blood cell docosahexaenoic and other polyunsaturated fatty acids in pregnant women: findings from the Avon Longitudinal Study of Parents and Children. Am J Clin Nutr 2011; 93:211-9. [PMID: 21106917 DOI: 10.3945/ajcn.110.006189] [Citation(s) in RCA: 134] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Blood and tissue long-chain polyunsaturated fatty acid (LC-PUFA) amounts, which have been associated with early development and lifelong health, depend on dietary intake and endogenous conversion of precursor fatty acids (FAs) by the enzymes Δ⁵-desaturase and Δ⁶-desaturase. Polymorphisms in the desaturase encoding genes FADS1 and FADS2 have been associated with several n-6 (omega-6) and n-3 (omega-3) FAs and especially with arachidonic acid (AA) amounts. Associations with docosahexaenoic acid (DHA), which is considered particularly important for brain and retina development, are hardly existent. OBJECTIVE We explored the relation between FADS gene cluster polymorphisms and red blood cell (RBC) FA amounts in > 4000 pregnant women participating in the Avon Longitudinal Study of Parents and Children. DESIGN Linear regression analysis of 17 single nucleotide polymorphisms (SNPs) in the FADS gene cluster was conducted with RBC phospholipid FAs from 6711 samples from 4457 women obtained throughout pregnancy (mean ± SD gestational age: 26.8 ± 8.2 wk). RESULTS Independent of dietary effects, the minor alleles were consistently positively associated with precursor FAs and negatively associated with LC-PUFAs and product:substrate ratios of the n-6 (AA:linoleic acid ratio) and n-3 (eicosapentaenoic acid:α-linolenic acid ratio) pathways. In contrast to previous studies, we also showed significant inverse associations with DHA. Similar but weaker associations were shown for the FADS3 SNP rs174455. CONCLUSIONS FADS genotypes influence DHA amounts in maternal RBC phospholipids and might affect the child's DHA supply during pregnancy. It is highly likely that a gene product of FADS3 has a desaturating activity.
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Affiliation(s)
- Berthold Koletzko
- Department of Pediatrics, Dr von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany.
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Abstract
BACKGROUND Allergic inflammation can trigger neuronal dysfunction and structural changes in the airways and the skin. Levels of brain-derived neurotrophic factor (BDNF) are strongly up regulated at the location of allergic inflammation. AIM We systematically investigated whether polymorphisms in the BDNF gene influence the development or severity of asthma and atopic diseases. METHODS The BDNF gene was screened for mutations in 80 chromosomes. Genotyping of six BDNF tagging polymorphisms was performed in a cross-sectional study population of 3099 children from Dresden and Munich (age 9-11 years, ISAAC II). Furthermore, polymorphisms were also investigated in an additional 655 asthma cases analysed with a random sample of 767 children selected from ISAAC II. Associations were calculated via chi-square test and anova using SAS Genetics and spss. RESULTS We identified nine polymorphisms with minor allele frequency >or=0.03, one of them leading to an amino acid change from Valine to Methionine. In the cross-sectional study population, no significant association was found with asthma or any atopic disease. However, when more severe asthma cases from the MAGIC study were analysed, significant asthma effects were observed with rs6265 (odds ratio 1.37, 95% confidence interval 1.14-1.64, P = 0.001), rs11030101 (OR 0.82, 95%CI 0.70-0.95, P = 0.009) and rs11030100 (OR 1.19, 95%CI 1.00-1.42, P = 0.05). CONCLUSIONS As in previous studies, effects of BDNF polymorphisms on asthma remain controversial. The data may suggest that BDNF polymorphisms contribute to severe forms of asthma.
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Affiliation(s)
- S Zeilinger
- University Children's Hospital, Ludwig Maximilian's University Munich, Germany
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Zeilinger S, Schmoll M, Pail M, Mach RL, Kubicek CP. Nucleosome transactions on the Hypocrea jecorina (Trichoderma reesei) cellulase promoter cbh2 associated with cellulase induction. Mol Genet Genomics 2003; 270:46-55. [PMID: 12905071 DOI: 10.1007/s00438-003-0895-2] [Citation(s) in RCA: 79] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2003] [Accepted: 06/30/2003] [Indexed: 10/26/2022]
Abstract
The 5' regulatory region of the cbh2 gene of Hypocrea jecorina contains the cbh2 activating element (CAE) which is essential for induction of cbh2 gene expression by sophorose and cellulose. The CAE consists of two motifs, a CCAAT box on the template strand and a GTAATA box on the coding strand, which cooperate during induction. Northern analyses of cbh2 gene expression has revealed an absolute dependence on induction, but no direct effect of Cre1-mediated carbon catabolite repression. Investigation of the chromatin structure in the wild-type strain showed that, under repressing conditions, there is a nucleosome free region (nfr) around the CAE, which is flanked by strictly positioned nucleosomes. Induction results in a loss of positioning of nucleosomes -1 and -2 downstream of the CAE, thus making the TATA box accessible. Simultaneous mutation of both motifs of the CAE, or of the CCAAT-box alone, also leads to shifting of nucleosome -1, which normally covers the TATA-box under repressing conditions, whereas mutation of the GTAATA element results in a narrowing of the nfr, indicating that the proteins that bind to both motifs in the CAE interact with chromatin, although in different ways. A cellulase-negative mutant strain, which has previously been shown to be altered in protein binding to the CAE, still displayed the induction-specific changes in nucleosome structure, indicating that none of the proteins that directly interact with CAE are affected, and that nucleosome rearrangement and induction of cbh2 expression are uncoupled. Interestingly, the carbon catabolite repressor Cre1 is essential for strict nucleosome positioning in the 5' regulatory sequences of cbh2 under all of the conditions tested, and induction can occur in a promoter that lacks positioned nucleosomes. These data suggest that Cre1, the Hap2/3/5 complex and the GTAATA-binding protein are all involved in nucleosome assembly on the cbh2 promoter, and that the latter two respond to inducing conditions by repositioning nucleosome -1.
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Affiliation(s)
- S Zeilinger
- Microbial Biochemistry and Gene Technology Department, Institute for Chemical Engineering, Technical University of Vienna, Getreidemarkt 9/166-5, 1060 Wien, Austria.
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Mach RL, Zeilinger S. Regulation of gene expression in industrial fungi: Trichoderma. Appl Microbiol Biotechnol 2003; 60:515-22. [PMID: 12536250 DOI: 10.1007/s00253-002-1162-x] [Citation(s) in RCA: 143] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2002] [Revised: 09/30/2002] [Accepted: 10/04/2002] [Indexed: 10/25/2022]
Abstract
The genus Trichoderma comprises a group of filamentous ascomycetes that are now widely used in industrial applications because of their ability to produce extracellular hydrolases in large amounts. In addition, strong inducible promoters together with high secretory capacity have made Trichoderma an attractive host for heterologous protein production. Several promoters of genes encoding hydrolytic enzymes have been investigated in detail regarding their cis-acting elements and trans-acting factors. Potent inducer molecules, for both xylanolytic and cellulolytic enzyme systems, have been identified and characterized. Furthermore, models for the recognition of the insoluble substrates cellulose and xylan have been developed based on a large set of experiments. This mini-review summarises the considerable amount of data accumulated over the past three decades.
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Affiliation(s)
- R L Mach
- Institute of Biochemical Engineering, Microbial Biochemistry and Gene Technology Group, Getreidemarkt 9/166, 1060 Vienna, Austria.
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Zeilinger S, Ebner A, Marosits T, Mach R, Kubicek CP. The Hypocrea jecorina HAP 2/3/5 protein complex binds to the inverted CCAAT-box (ATTGG) within the cbh2 (cellobiohydrolase II-gene) activating element. Mol Genet Genomics 2001; 266:56-63. [PMID: 11589578 DOI: 10.1007/s004380100518] [Citation(s) in RCA: 93] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
The 5' regulatory region of the chh2 gene, encoding cellobiohydrolase II, of the filamentous fungus Hypocrea jecorina contains the cbh2 activating element (CAE) which is essential for cbh2 expression. The CAE consists of two separate, adjacent motifs, a CCAAT box on the template strand (ATTGG) and a GTAATA box on the coding strand, which co-operate in the induction of the gene by cellulose or sophorose. EMSA supershift experiments using an antibody against Aspergillus nidulans HAPC suggested that the complex which binds to the H. jecorina CCAAT box contains a HAPC homolog. To obtain direct evidence for this, we have cloned the hap2, hap3 and hap5 genes from H. jecorina. They encode proteins whose core regions display great similarity to Aspergillus HAPB, HAPC and HAPE and to known HAP homologs from other organisms. All three genes are transcribed in a carbon source-independent manner. A. nidulans deltahap strains were functionally complemented in vitro by the overexpressed H. jecorina HAP2, HAP3 and HAP5 proteins, and they thus represent subunits of the CCAAT-binding complex. Furthermore, all three proteins (HAP2, HAP3 and HAP5) were needed to bind to the CAE in the H. jecorina cbh2 gene promoter in vitro. We conclude that the CCAAT box on the template strand in CAE is bound by the H. jecorina equivalent of the HAP protein complex.
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Affiliation(s)
- S Zeilinger
- Abteilung für Mikrobielle Biochemie, Institut für Biochemische Technologie und Mikrobiologie, Technische Universität Wien, Austria.
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Abstract
The "cbh2 activating element," CAE, consisting of two separate boxes (ATTGG = CCAAT and GTAATA, respectively) is essential for cellobiohydrolase II gene expression in the filamentous fungus Hypcrea jecorina. Here we report that cell-free extracts from a cellulase-negative mutant form CAE-protein complexes with higher mobility and lower binding-strength compared to the wild type. EMSA analysis demonstrated an increased mobility of the GTAATA-binding protein complex and, supported by in vivo footprinting, a lowered binding strength of the HAP2/3/5 proteins. However, the hap2/hap3/hap5 genes of the mutant are unaltered and transcribed normally. A nucleotide fragment of the cbh1 promoter containing a (GG)CTAATA motif without an adjacent CCAAT box is also bound by cell-free extracts of H. jecorina, and the protein-DNA complex of the mutant shows the characteristic increase in mobility. We conclude that this mutant is defective in the functional formation of the CAE-protein complexes but not in their binding to the target sequences itself.
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Affiliation(s)
- S Zeilinger
- Section Microbial Biochemistry, Institute of Biochemical Technology and Microbiology, Technical University of Vienna, Getreidemarkt 9, Wien, A-1060, Austria.
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Mach RL, Peterbauer CK, Payer K, Jaksits S, Woo SL, Zeilinger S, Kullnig CM, Lorito M, Kubicek CP. Expression of two major chitinase genes of Trichoderma atroviride (T. harzianum P1) is triggered by different regulatory signals. Appl Environ Microbiol 1999; 65:1858-63. [PMID: 10223970 PMCID: PMC91267 DOI: 10.1128/aem.65.5.1858-1863.1999] [Citation(s) in RCA: 121] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Regulation of the expression of the two major chitinase genes, ech42 (encoding the CHIT42 endochitinase) and nag1 (encoding the CHIT73 N-acetyl-beta-D-glucosaminidase), of the chitinolytic system of the mycoparasitic biocontrol fungus Trichoderma atroviride (= Trichoderma harzianum P1) was investigated by using a reporter system based on the Aspergillus niger glucose oxidase. Strains harboring fusions of the ech42 or nag1 5' upstream noncoding sequences with the A. niger goxA gene displayed a glucose oxidase activity pattern that was consistent under various conditions with expression of the native ech42 and nag1 genes, as assayed by Northern analysis. The expression product of goxA in the mutants was completely secreted into the medium, detectable on Western blots, and quantifiable by enzyme-linked immunosorbent assay. nag1 gene expression was triggered during growth on fungal (Botrytis cinerea) cell walls and on the chitin degradation product N-acetylglucosamine. N-Acetylglucosamine, di-N-acetylchitobiose, or tri-N-acetylchitotriose also induced nag1 gene expression when added to mycelia pregrown on different carbon sources. ech42 expression was also observed during growth on fungal cell walls but, in contrast, was not triggered by addition of chitooligomers to pregrown mycelia. Significant ech42 expression was observed after prolonged carbon starvation, independent of the use of glucose or glycerol as a carbon source, suggesting that relief of carbon catabolite repression was not involved in induction during starvation. In addition, ech42 gene transcription was triggered by physiological stress, such as low temperature, high osmotic pressure, or the addition of ethanol. Four copies of a putative stress response element (CCCCT) were found in the ech42 promoter.
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Affiliation(s)
- R L Mach
- Abteilung für Mikrobielle Biochemie, Institut für Biochemische Technologie und Mikrobiologie, TU Wien, A-1060 Vienna, Austria.
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Zeilinger S, Galhaup C, Payer K, Woo SL, Mach RL, Fekete C, Lorito M, Kubicek CP. Chitinase gene expression during mycoparasitic interaction of Trichoderma harzianum with its host. Fungal Genet Biol 1999; 26:131-40. [PMID: 10328983 DOI: 10.1006/fgbi.1998.1111] [Citation(s) in RCA: 190] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
For monitoring chitinase expression during mycoparasitism of Trichoderma harzianum in situ, we constructed strains containing fusions of green fluorescent protein (GFP) to the 5'-regulatory sequences of the T. harzianum nag1 (N-acetyl-beta-d-glucosaminidase-encoding) and ech42 (42-kDa endochitinase-encoding) genes. Confronting these strains with Rhizoctonia solani led to induction of gene expression before (ech42) or after (nag1) physical contact. A 12-kDa cut-off membrane separating the two fungi abolished ech42 expression, indicating that macromolecules are involved in its precontact activation. No ech42 expression was triggered by culture filtrates of R. solani or by placing T. harzianum onto plates previously colonized by R. solani. Instead, high expression occurred upon incubation of T. harzianum with the supernatant of R. solani cell walls digested with culture filtrates or purified endochitinase 42 (CHIT42, encoded by ech42) from T. harzianum. The chitinase inhibitor allosamidin blocked ech42 expression and reduced inhibition of R. solani growth during confrontation. The results indicate that ech42 is expressed before contact of T. harzianum with R. solani and its induction is triggered by soluble chitooligosaccharides produced by constitutive activity of CHIT42 and/or other chitinolytic enzymes.
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Affiliation(s)
- S Zeilinger
- Abteilung für Mikrobielle Biochemie, Institut für Biochemische Technologie und Mikrobiologie, TU Wien, Getreidemarkt 9, Wien, A-1060, Austria
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Zeilinger S, Mach RL, Kubicek CP. Two adjacent protein binding motifs in the cbh2 (cellobiohydrolase II-encoding) promoter of the fungus Hypocrea jecorina (Trichoderma reesei) cooperate in the induction by cellulose. J Biol Chem 1998; 273:34463-71. [PMID: 9852114 DOI: 10.1074/jbc.273.51.34463] [Citation(s) in RCA: 73] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The cellulase system of the filamentous fungus Hypocrea jecorina (Trichoderma reesei) consists of several cellobiohydrolases, endoglucanases, and beta-glucosidases, encoded by separate genes, which are coordinately expressed in the presence of cellulose or the disaccharide sophorose. Using cell-free extracts from sophorose-induced and noninduced mycelia and various fragments of the cbh2 promoter of H. jecorina in electrophoretic mobility shift assay (EMSA) analysis and performing in vitro and in vivo footprinting analysis, we detected the nucleotide sequence 5'-ATTGGGTAATA-3' (consequently named cbh2-activating element (CAE)) to bind a protein complex with different migration in EMSA of induced and noninduced cell-free extracts. EMSA analysis, employing oligonucleotide fragments containing specifically mutated versions of CAE, revealed that protein binding requires the presence of an intact copy of either one of two adjacent motifs: a CCAAT (=ATTGG) box on the template strand and a GTAATA box on the coding strand, whereas a simultaneous mutation in both completely abolished binding. H. jecorina transformants, containing correspondingly mutated versions of the cbh2 promoter fused to the Escherichia coli hph gene as a reporter, expressed hph in a manner paralleling the efficacy of CAE-protein complex formation in EMSA, suggesting that the presence of either of both motifs is required for induction of cbh2 gene transcription. Antibody supershift experiments with anti-HapC antiserum as well as EMSA competition experiments with CCAAT binding promoter fragments of the Aspergillus nidulans amdS promoter suggest that the H. jecorina CCAAT box binding complex contains a homologue of HapC. The nature of the adjacent, GTAATA-binding protein(s) and its cooperation with the HapC homologue in cbh2 gene induction is discussed.
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Affiliation(s)
- S Zeilinger
- Abteilung für Mikrobielle Biochemie, Institut für Biochemische Technologie und Mikrobiologie, Technische Universität Wien, Getreidemarkt 9/1725, A-1060 Wien, Austria
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Mach RL, Zeilinger S, Kristufek D, Kubicek CP. Ca2+-calmodulin antagonists interfere with xylanase formation and secretion in Trichoderma reesei. Biochim Biophys Acta 1998; 1403:281-9. [PMID: 9685681 DOI: 10.1016/s0167-4889(98)00068-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The addition of Ca2+-antagonizers (La2+), Ca2+-ionophores (A23187) and Ca2+-complexing agents (EGTA) inhibited the formation of xylanase activity in resting mycelia of Trichoderma reesei. The inhibition by the ionophore was reversed by the addition of Ca2+ ions. A similar inhibitory effect was obtained by the addition of the calmodulin inhibitors, trifluoroperazine, chlorpromazine and quinacrine, hence suggesting that the observed effect of Ca2+ on xylanase formation occurred via calmodulin. The inhibition of xylanase formation by trifluoroperazine was accompanied by an inhibition of formation of the xyn2 transcript, and of the hph (hygromycin B-phosphotransferase-encoding) gene when fused downstream of the 5'-regulatory signals of the T. reesei xyn2 gene, indicating that calmodulin is required for xyn2 induction. At trifluoroperazine concentrations, which inhibited extracellular xylanase formation only slightly (about 30%), the cell-free extracts exhibited slightly increased xylanase activities. Subcellular fractionation showed that in these mycelia, the XYN II protein was distributed over a range of light vesicular fractions. This accumulated XYN II protein had the same Mr as the secreted, extracellular enzyme, indicating that it had already passed Golgi-located preprotein processing. Trifluoroperazine also specifically interfered with the endogenous, Ca2+-dependent phosphorylation of a 20-kDa protein, which was predominantly observed in cell-free extracts from mycelia growing on xylan. From these data, we conclude that calmodulin is required for xylanase II formation by T. reesei both at a transcriptional level as well as at a post-Golgi step of the secretory pathway. We also suggest that at least one of these two steps may be mediated via Ca2+-calmodulin-dependent phosphorylation.
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Affiliation(s)
- R L Mach
- Abteilung für Mikrobielle Biochemie, Institut für Biochemische Technologie und Mikrobiologie, TU Wien, Getreidemarkt 9/172-5, A-1060 Vienna, Austria
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Zeilinger S, Mach RL, Schindler M, Herzog P, Kubicek CP. Different inducibility of expression of the two xylanase genes xyn1 and xyn2 in Trichoderma reesei. J Biol Chem 1996; 271:25624-9. [PMID: 8810338 DOI: 10.1074/jbc.271.41.25624] [Citation(s) in RCA: 89] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Regulation of formation of the extracellular xylanase system of Trichoderma reesei QM 9414 during growth on xylan, cellulose, and replacement onto a number of soluble inducers was investigated by Northern analysis of xyn1 and xyn2 transcripts and by the use of the Escherichia coli hph (hygromycin B-phosphotransferase-encoding) gene as a reporter. Whereas the xyn1 promoter is active in the presence of xylan and xylose, and virtually silenced in the presence of glucose, the xyn2 promoter enables basal transcription at a low level, but is enhanced in the presence of xylan and xylobiose and also of sophorose or cellobiose. The respective regulatory nucleotide regions were localized on a 221-base pair fragment and a 55-base pair fragment of the xyn1 and xyn2 5'-upstream noncoding sequences, respectively. Electrophoretic mobility shift assays, using cell-free extracts, identified induction-specific protein-DNA complexes: one complex of high mobility was observed under basal, noninduced conditions (glucose) with xyn2, which was in part replaced by a slow-migrating complex upon induction by xylan or sophorose. Both complexes bound to a CCAAT box. With xyn1, the induced complex also binds to a CCAAT box, but this binding is not observed in the presence of the carbon catabolite repressor Cre1, which binds to a nearby located consensus motif.
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Affiliation(s)
- S Zeilinger
- Abteilung für Mikrobielle Biochemie, Institut für Biochemische Technologie und Mikrobiologie, TU Wien, A-1060 Wien, Austria
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Abstract
The filamentous fungus Trichoderma reesei forms two specific, xylan-inducible xylanases encoded by xyn1 and xyn2 to degrade the beta-1,4-D-xylan backbone of hemicelluloses. This enzyme system is formed in the presence of xylan, but not glucose. The molecular basis of the absence of xylanase I formation on glucose was the purpose of this study. Northern blotting of the xyn1 transcript as well as the use of the Escherichia coli hygromycin B phosphotransferase-encoding gene (hph) as a reporter consistently showed that the basal expression of xyn1 was affected by glucose, whereas its induction by xylan remained uninfluenced. The repression of basal xyn1 transcription is mediated by the carbon catabolite repressor protein Cre1, which in vivo binds to two of four consensus sites (5'-SYG-GRG-3') in the xyn1 promoter, which occurred in the form of an inverted repeat. T. reesei strains, bearing a xyn1::hph reporter construct, in which four nucleotides from the middle of the inverted repeat had been removed, expressed hph on glucose at a level comparable to that observed during growth on a carbon catabolite derepressing carbon source. Northern analysis of xyn1 expression in a T. reesei mutant strain (RUT C-30), which contains a truncated, non-functional cre1 gene, also confirmed basal transcription of xyn1. In this strain, xyn1 transcription was still inducible by xylose or xylan to an even higher degree than in the wild-type strain, suggesting that induction overcomes glucose repression at the level of xyn1 expression. Based on these data, we postulate that basal transcription of xyn1 is repressed by glucose and mediated by an inverted repeat of the consensus motif for Cre1-mediated carbon catabolite repression.
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Affiliation(s)
- R L Mach
- Abteilung für Mikrobielle Biochemie, Institut für Biochemische Technologie und Mikrobiologie, TU Wien, Austria
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Abstract
In order to investigate the mechanism of carbon catabolite repression in the industrially important fungus Trichoderma reesei, degenerated PCR-primers were designed to amplify a 0.7-bp fragment of the cre1 gene, which was used to clone the entire gene. It encodes a 402-amino acid protein with a calculated M(r) of 43.6 kDa. Its aa-sequence shows 55.6% and 54.7% overall similarity to the corresponding genes of Aspergillus nidulans and A. niger, respectively. Similarity was restricted to the aa-region containing the C2H2 zinc finger and several aa-regions rich in proline and basic amino acids, which may be involved in the interaction with other proteins. Another aa-region rich in the SPXX-motif that has been considered analogous to a region of yeast RGR1p, was instead identified as a domain occurring in several eucaryotic transcription factors. The presence of the cre1 translation product was demonstrated with polyclonal antibodies against Cre1, which identified a protein of 43 (+/- 2) kDa in cell-free extracts from T. reesei. A Cre1 protein fragment from the two zinc fingers to the region similar to the aa-sequence of eucaryotic transcription factors, was expressed in Escherichia coli as a fusion protein with glutathione S-transferase. EMSA and in vitro footprinting revealed binding of the fusion protein to the sequence 5'-GCGGAG-3', which matches well with the A. nidulans consensus sequence for CreA binding (5'-SYGGRG-3'). Cell-free extracts of T. reesei formed different complexes with DNA-fragments carrying this binding sites, and the presence of Cre1 and additional proteins in these complexes was demonstrated. We conclude that T. reesei Cre1 is the functional homologue of Aspergillus CreA and that it binds to its target sequence probably as a protein complex.
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Affiliation(s)
- J Strauss
- Abteilung für Mikrobielle Biochemie, Institut für Biochemische Technologie und Mikrobiologie, Wien, Austria
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Zeilinger S, Kristufek D, Arisan-Atac I, Hodits R, Kubicek CP. Conditions of formation, purification, and characterization of an alpha-galactosidase of Trichoderma reesei RUT C-30. Appl Environ Microbiol 1993; 59:1347-53. [PMID: 8390816 PMCID: PMC182088 DOI: 10.1128/aem.59.5.1347-1353.1993] [Citation(s) in RCA: 63] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Trichoderma reesei RUT C-30 formed an extracellular alpha-galactosidase when it was grown in a batch culture containing lactose or locust bean gum as a carbon source. Short-chain alpha-galactosides (melibiose, raffinose, stachyose), as well as the monosaccharides galactose, dulcitol, arabinose, and arabitol, also induced alpha-galactosidase activity both when they were used as carbon sources (at a concentration of 1%) in batch cultures and in resting mycelia (at concentrations in the millimolar range). The addition of 50 mM glucose did not affect the induction of alpha-galactosidase formation by galactose. alpha-Galactosidase from T. reesei RUT C-30 was purified to homogeneity from culture fluids of galactose-induced mycelia. The active enzyme was a 50 +/- 3-kDa, nonglycosylated monomer which had an isoelectric point of 5.2. It was active against several alpha-galactosides (p-nitrophenyl-alpha-D-galactoside, melibiose, raffinose, and stachyose) and galactomannan (locust bean gum) and was inhibited by the product galactose. It released galactose from locust bean gum and exhibited synergism with T. reesei beta-mannanase. Its activity was optimal at pH 4, and it displayed broad pH stability (pH 4 to 8). Its temperature stability was moderate (60 min at 50 degrees C resulted in recovery of 70% of activity), and its highest level of activity occurred at 60 degrees C. Its action on galactomannan was increased by the presence of beta-mannanase.
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Affiliation(s)
- S Zeilinger
- Abteilung für Mikrobielle Biochemie, Technische Universität Wien, Austria
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