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4. A Genome-wide Association Meta-analysis of Preschool Internalizing Problems

Author

Benke, Kelly S., Nivard, Michel G., Velders, Fleur P., Walters, Raymond K., Pappa, Irene, Scheet, Paul A., Xiao, Xiangjun, Ehli, Erik A., Palmer, Lyle J., Whitehouse, Andrew J.O., Verhulst, Frank C., Jaddoe, Vincent W., Rivadeneira, Fernando, Groen-Blokhuis, Maria M., van Beijsterveldt, Catharina E.M., Davies, Gareth E., Hudziak, James J., Lubke, Gitta H., Boomsma, Dorret I., Pennell, Craig E., Tiemeier, Henning, and Middeldorp, Christel M.

Published
2014
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5. The Generation R Study: A Review of Design, Findings to Date, and a Study of the 5-HTTLPR by Environmental Interaction from Fetal Life Onward

Author

Tiemeier, Henning, Velders, Fleur P., and Szekely, Eszter

Abstract

Objective: First, we give an overview of child psychiatric research in the Generation R Study, a population-based cohort from fetal life forward. Second, we examine within Generation R whether the functional polymorphism (5-HTTLPR) in the promoter of the serotonin transporter gene interacts with prenatal maternal chronic difficulties, prenatal maternal anxiety or postnatal maternal anxiety to influence child emotional development. Method: A total of 2,136 northern European children were genotyped for 5-HTTLPR and rs25531. Mothers reported chronic difficulties and anxiety symptoms at 20 weeks' pregnancy and when the child was 3 years old. Child emotion recognition was observed at 3 years, and child emotional problems were assessed with the CBCL/1 1/2-5 at 5 years. Results: There were consistent main effects of maternal difficulties and anxiety on child emotional problems, but no main effect of 5-HTTLPR. Moreover, children with the s allele were at increased risk for emotional problems if their mothers reported prenatal anxiety symptoms (beta = 2.02, p less than 0.001) or postnatal anxiety symptoms (beta = 1.64, p less than 0.001). Also, in children of mothers with prenatal anxiety symptoms, the s allele was associated with less accurate emotion-matching (beta = -0.11, p = 0.004). Conclusions: This population-based study shows that vulnerability due to 5-HTTLPR is not specific for certain adverse exposures or severe events, but suggests that the small effects of gene-environment interaction on emotional development become manifest early in life. (Contains 10 tables and 3 figures.)

Published
2012
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6. Information extraction from free text for aiding transdiagnostic psychiatry: constructing NLP pipelines tailored to clinicians’ needs

Author

Ontwikkelingsstoornissen Med., Psychiatrie_Medisch, Brain, Turner, Rosanne J., Coenen, Femke, Roelofs, Femke, Hagoort, Karin, Härmä, Aki, Grünwald, Peter D., Velders, Fleur P., Scheepers, Floortje E., Ontwikkelingsstoornissen Med., Psychiatrie_Medisch, Brain, Turner, Rosanne J., Coenen, Femke, Roelofs, Femke, Hagoort, Karin, Härmä, Aki, Grünwald, Peter D., Velders, Fleur P., and Scheepers, Floortje E.

Published
2022

7. Additional file 1 of Information extraction from free text for aiding transdiagnostic psychiatry: constructing NLP pipelines tailored to clinicians’ needs

Author

Turner, Rosanne J., Coenen, Femke, Roelofs, Femke, Hagoort, Karin, Härmä, Aki, Grünwald, Peter D., Velders, Fleur P., and Scheepers, Floortje E.

Subjects
mental disorders, behavioral disciplines and activities
Abstract

Additional file 1: Table 1. Examples from the lists used for rule-based filtering ofthe four themes and change phrases. Table 2. Overview of clinical trials in psychiatry where atransdiagnostic outcome measurewas used, studied diagnoses and the outcome measures. Table 3. Ten most prevalent global outcome measures within the 362included clinical trials. Table 4. Clinical trials in psychiatry that both used the HDRS and theSF36 as outcome measures. For HDRS and SF36 scores in each intervention group,see the additional excel file (additional information 2). Table 5. Correlation coefficients ofthe HDRS and SF36 subscores. Table6. Specificity, sensitivity and positive predictive value of the SF36subcomponents for severity of depression, as compared to the HDRS. Table 7. EHR sourced assessed for extracting information on each outcomemeasure theme.

Published
2022
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12. Hair cortisol in twins:heritability and genetic overlap with psychological variables and stress-system genes

Author

Rietschel, Liz, Streit, Fabian, McGrath, John, Davies, Gareth, Davies, Gail, de Geus, Eco J C, De Jager, Philip, Deary, Ian J, Degenhardt, Franziska, Dunn, Erin C, Ehli, Erik A, Eley, Thalia C, Escott-Price, Valentina, Hickie, Ian B, Esko, Tõnu, Finucane, Hilary K, Gill, Michael, Gordon, Scott D, Grove, Jakob, Hall, Lynsey S, Hansen, Thomas F, Søholm Hansen, Christine, Heath, Andrew C, Hansell, Narelle K, Henders, Anjali K, Herms, Stefan, Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke- Jan, Hougaard, David, Huang, Hailiang, Ising, Marcus, Jansen, Rick, Wright, Margaret J, Jorgenson, Eric, Kloiber, Stefan, Knowles, James A, Kretzschmar, Warren W, Krogh, Jesper, Kutalik, Zoltán, Lang, Maren, Lewis, Glyn, Li, Yihan, MacIntyre, Donald J, Gillespie, Nathan A, Madden, Pamela Af, Marchine, Jonathan, Mbarek, Hamdi, McGuffin, Peter, Mehta, Divya, Metspalu, Andres, Middeldorp, Christel M, Mihailov, Evelin, Milani, Lili, Montgomery, Grant W, Forstner, Andreas J, Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nordentoft, Merete, Nyholt, Dale R, O'Donovan, Michael C, O'Reilly, Paul F, Oskarsson, Hogni, Owen, Michael J, Schulze, Thomas G, Paciga, Sara A, Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Pedersen, Nancy L, Pergadia, Michele L, Peterson, Roseann E, Pettersson, Erik, Peyrot, Wouter J, Porteous, David J, Posthuma, Danielle, Wüst, Stefan, Potash, James B, Quiroz, Jorge A, Rice, John P, Riley, Brien P, Rivera, Margarita, Ruderfer, Douglas M, Saeed Mirza, Saira, Schoevers, Robert, Shen, Ling, Shi, Jianxin, Nöthen, Markus M, Sigurdsson, Engilbert, Sinnamon, Grant Cb, Smit, Johannes H, Smith, Daniel J, Smoller, Jordan W, Stephansson, Hreinn, Steinberg, Stacy, Strohmaier, Jana, Tansey, Katherine E, Teumer, Alexander, Baumgartner, Markus R, Thompson, Wesley, Thomson, Pippa A, Thorgeirsson, Thorgeir E, Treutlein, Jens, Trzaskowski, Maciej, Umbricht, Daniel, van der Auwera, Sandra, van Grootheest, Gerard, van Hemert, Albert M, Viktorin, Alexander, Zhu, Gu, Walker, Brian R, Völzke, Henry, Wang, Yunpeng, Webb, Bradley T, Weissman, Myrna M, Wellmann, Jürgen, Willemsen, Gonneke, Xi, Hualin S, Baune, Bernhard T, Blackwood, Douglas H R, Boomsma, Dorret I, Crawford, Andrew A, Børglum, Anders D, Buttenschøn, Henriette N, Cichon, Sven, Domenici, Enrico, Flint, Jonathan, Grabe, Hans J, Hamilton, Steven P, Kendler, Kenneth S, Li, Qingqin S, Lucae, Susanne, Colodro-Conde, Lucía, Magnusson, Patrik K, McIntosh, Andrew M, Mors, Ole, Bo Mortensen, Preben, Müller-Myhsok, Bertram, Penninx, Brenda Wjh, Perlis, Roy H, Preisig, Martin, Schaefer, Catherine, Medland, Sarah E, Stephansson, Kari, Tiemeier, Henning, Uher, Rudolf, Werge, Thomas, Winslow, Ashley R, Breen, Gerome, Levinson, Douglas F, Lewis, Cathryn M, Wray, Naomi R, Sullivan, Patrick F, Martin, Nicholas G, Rietschel, Marcella, Bolton, Jennifer L, Hayward, Caroline, Direk, Nese, Anderson, Anna, McAloney, Kerrie, Huffman, Jennifer, Wilson, James F, Campbell, Harry, Rudan, Igor, Wright, Alan, Hastie, Nicholas, Wild, Sarah H, Velders, Fleur P, Hofman, Albert, Uitterlinden, Andre G, Frank, Josef, Lahti, Jari, Räikkönen, Katri, Kajantie, Eero, Widen, Elisabeth, Palotie, Aarno, Eriksson, Johan G, Kaakinen, Marika, Järvelin, Marjo-Riitta, Timpson, Nicholas J, Davey Smith, George, Couvy-Duchesne, Baptiste, Ring, Susan M, Evans, David M, St Pourcain, Beate, Tanaka, Toshiko, Milaneschi, Yuri, Bandinelli, Stefania, Ferrucci, Luigi, van der Harst, Pim, Rosmalen, Judith Gm, Bakker, Stephen Jl, Witt, Stephanie H, Verweij, Niek, Dullaart, Robin Pf, Mahajan, Anubha, Lindgren, Cecilia M, Morris, Andrew, Lind, Lars, Ingelsson, Erik, Anderson, Laura N, Pennell, Craig E, Lye, Stephen J, Binz, Tina M, Matthews, Stephen G, Eriksson, Joel, Mellstrom, Dan, Ohlsson, Claes, Price, Jackie F, Strachan, Mark Wj, Reynolds, Rebecca M, Ripke, Stephan, Mattheisen, Manuel, CORtisolNETwork, Abdellaoui, Abdel, Adams, Mark J, Agerbo, Esben, Air, Tracy M, Andlauer, Till Fm, Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan Tf, Bennett, David A, Berger, Klaus, Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics, Bigdeli, Tim B, Bybjerg-Grauholm, Jonas, Byrne, Enda M, Cai, Na, Castelao, Enrique, Clarke, Toni-Kim, Coleman, Jonathan Ri, Consortium, Converge, Craddock, Nick, Dannlowski, Udo, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, APH - Mental Health, Internal medicine, Amsterdam Reproduction & Development (AR&D), Human genetics, APH - Methodology, APH - Digital Health, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Research Programs Unit, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, University of Zurich, Rietschel, Liz, Biological Psychology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Health Behaviors & Chronic Diseases, and APH - Personalized Medicine

Subjects
Male, Oncology, Netherlands Twin Register (NTR), Multifactorial Inheritance, Hydrocortisone, lcsh:Medicine, 340 Law, Genome-wide association study, 3124 Neurology and psychiatry, 0302 clinical medicine, Twins, Dizygotic, SOCIOECONOMIC-STATUS, Young adult, lcsh:Science, Child, 610 Medicine & health, Genetics, Multidisciplinary, Depression, PSYCHIATRIC-DISORDERS, 10218 Institute of Legal Medicine, Neuroticism, DEPRESSIVE SYMPTOMS, MORNING CORTISOL, Female, FUTURE-DIRECTIONS, Adult, medicine.medical_specialty, Cortisol awakening response, Adolescent, PERCEIVED STRESS, Biology, Genetic correlation, Article, LONG-TERM CORTISOL, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Internal medicine, medicine, Journal Article, Humans, neoplasms, Behavioural genetics, 1000 Multidisciplinary, Models, Genetic, lcsh:R, Twins, Monozygotic, ADRENAL AXIS ACTIVITY, MAJOR DEPRESSION, Heritability, Twin study, R1, digestive system diseases, 030227 psychiatry, ddc:000, INTRAINDIVIDUAL STABILITY, lcsh:Q, Stress, Psychological, 030217 neurology & neurosurgery, Hair
Abstract

Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables. Consortia CORtisolNETwork (CORNET) Consortium Jennifer L. Bolton21 Caroline Hayward23 Nese Direk24,25 Anna Anderson21 Jennifer Huffman23 James F. Wilson26 Harry Campbell26 Igor Rudan26 Alan Wright23 Nicholas Hastie23 Sarah H. Wild26 Fleur P. Velders24 Albert Hofman24 Andre G. Uitterlinden24,27 Jari Lahti28 Katri Räikkönen28 Eero Kajantie29 Elisabeth Widen30 Aarno Palotie30,31 Johan G. Eriksson29,32,33,34,35 Marika Kaakinen36 Marjo-Riitta Järvelin36,37,38,39 Nicholas J. Timpson40 George Davey Smith40 Susan M. Ring41 David M. Evans40 Beate St Pourcain41 Toshiko Tanaka42 Yuri Milaneschi42,43 Stefania Bandinelli44 Luigi Ferrucci42 Pim van der Harst45,46,47 Judith GM Rosmalen48 Stephen JL Bakker49 Niek Verweij45 Robin PF Dullaart49 Anubha Mahajan50 Cecilia M. Lindgren50 Andrew Morris50 Lars Lind51 Erik Ingelsson51 Laura N. Anderson52 Craig E. Pennell53 Stephen J. Lye52 Stephen G. Matthews54 Joel Eriksson55 Dan Mellstrom55 Claes Ohlsson55 Jackie F. Price26 Mark WJ Strachan21 Rebecca M. Reynolds21 Henning Tiemeier24,56,57 Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium (PGC) Stephan Ripke58,59,60 Manuel Mattheisen61,62,63 Abdel Abdellaoui64 Mark J. Adams65 Esben Agerbo66,8,67 Tracy M. Air68 Till FM Andlauer69,70 Silviu-Alin Bacanu71 Marie Bækvad-Hansen67,72 Aartjan TF Beekman43 David A. Bennett73 Klaus Berger74 Tim B. Bigdeli71,11 Jonas Bybjerg-Grauholm67,72 Enda M. Byrne5 Na Cai75 Enrique Castelao76 Toni-Kim Clarke65 Jonathan RI Coleman77 Converge Consortium78 Nick Craddock79 Udo Dannlowski80,81 Gareth Davies82 Gail Davies83 Eco. J. C. de Geus64,84 Philip De Jager85 Ian J. Deary83 Franziska Degenhardt12,13 Erin C. Dunn86,87,88 Erik A. Ehli82 Thalia C. Eley77 Valentina Escott-Price89 Tõnu Esko58,90,91,92 Hilary K. Finucane93,94 Michael Gill95 Scott D. Gordon96 Jakob Grove61,62,67,97 Lynsey S. Hall65,98 Thomas F. Hansen99,100 Christine Søholm Hansen67,72 Thomas F. Hansen101 Andrew C. Heath102 Anjali K. Henders5 Stefan Herms12,13,15 Per Hoffmann12,13,15 Georg Homuth103 Carsten Horn104 Jouke- Jan Hottenga64 David Hougaard67,72 Hailiang Huang59,86,105 Marcus Ising106 Rick Jansen43 Eric Jorgenson107 Stefan Kloiber108,109 James A Knowles110 Warren W. Kretzschmar50 Jesper Krogh111 Zoltán Kutalik112,113 Maren Lang3 Glyn Lewis114 Yihan Li50 Donald J. MacIntyre115,116 Pamela AF Madden102 Jonathan Marchine117 Hamdi Mbarek118,64 Peter McGuffin77 Divya Mehta119 Andres Metspalu92,120 Christel M. Middeldorp64 Evelin Mihailov92,121 Lili Milani92 Grant W. Montgomery122 Sara Mostafavi123,124 Niamh Mullins77 Matthias Nauck125,126 Bernard Ng124 Merete Nordentoft67,127 Dale R. Nyholt128 Michael C. O’Donovan129 Paul F. O’Reilly77 Hogni Oskarsson130 Michael J. Owen129 Sara A. Paciga131 Carsten Bøcker Pedersen66,67,8 Marianne Giørtz Pedersen66,67,8 Nancy L. Pedersen132 Michele L. Pergadia133 Roseann E. Peterson11,71 Erik Pettersson134 Wouter J. Peyrot43 David J. Porteous135 Danielle Posthuma136,137 James B. Potash138 Jorge A. Quiroz139 John P. Rice102 Brien P. Riley71 Margarita Rivera77,140 Douglas M. Ruderfer141 Saira Saeed Mirza24 Robert Schoevers142 Ling Shen107 Jianxin Shi143 Engilbert Sigurdsson144 Grant CB Sinnamon145 Johannes H. Smit43 Daniel J. Smith146 Jordan W. Smoller86 Hreinn Stephansson147 Stacy Steinberg147 Jana Strohmaier3 Katherine E. Tansey148 Alexander Teumer149 Wesley Thompson100,135,150,151,152 Pippa A. Thomson135 Thorgeir E. Thorgeirsson147 Jens Treutlein3 Maciej Trzaskowski153 Daniel Umbricht154 Sandra van der Auwera155 Gerard van Grootheest43 Albert M. van Hemert156 Alexander Viktorin132 Henry Völzke149 Yunpeng Wang67,100,151 Bradley T. Webb157 Myrna M. Weissman158,159 Jürgen Wellmann74 Gonneke Willemsen64 Hualin S. Xi160 Bernhard T. Baune68 Douglas H. R. Blackwood65 Dorret I. Boomsma64 Anders D. Børglum61,62,67 Henriette N. Buttenschøn62,67,161 Sven Cichon12,162,163,164 Enrico Domenici165 Jonathan Flint50,166 Hans J. Grabe155 Steven P. Hamilton167 Kenneth S. Kendler71 Qingqin S. Li168 Susanne Lucae106 Patrik K. Magnusson132 Andrew M. McIntosh65,83 Ole Mors67,169 Preben Bo Mortensen62,8,67 Bertram Müller-Myhsok69,70,170 Brenda WJH Penninx43 Roy H. Perlis87,171 Martin Preisig76 Catherine Schaefer107 Jordan W. Smoller87,88 Kari Stephansson147 Henning Tiemeier24,56,57 Rudolf Uher172 Thomas Werge100,150,173 Ashley R. Winslow174,175 Gerome Breen77,176 Douglas F. Levinson177 Cathryn M. Lewis77,178 Naomi R. Wray5,153 Patrick F. Sullivan134,179,180 23MRC Human Genetics Unit, Institute for Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. 24Department of Epidemiology, Erasmus Medical Centre, Rotterdam, Netherlands. 25Psychiatry, Dokuz Eylul University School Of Medicine, Izmir, TR, Turkey. 26Centre for Population Health Sciences, Institute for Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH8 9AG, UK. 27Internal Medicine, Erasmus MC, Rotterdam, NL, Netherlands. 28Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland. 29National Institute for Health and Welfare, Helsinki, Finland. 30Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. 31Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland. 32Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland. 33Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland. 34Folkhalsan Research Centre, Helsinki, Finland. 35Vasa Central Hospital, Vasa, Finland. 36Institute of Health Sciences and Biocenter Oulu, University of Oulu, Oulu, Finland. 37Department of Children and Yond People and Families, National Institute for Health and elfare, Oulu, Finland. 38Department of Epidemiology and Biostatistics, MRC-HPA Centre for Environment and Health, Imperial College London, London, UK. 39Unit of Primary Care, Oulu University Hospital, Oulu, Finland. 40MRC Centre for Causal Analyses in Translational Epidemiology, School of Social and Community Medicine, University of Bristol, Bristol, UK. 41School of Social and Community Medicine, University of Bristol, Bristol, UK. 42Longitudinal Studies Section, Clinical Research Branch, National Institute on Aging, Baltimore, MD, USA. 43Department of Psychiatry, VU University Medical Center/GGZ inGeest, Amsterdam, Netherlands. 44Geriatric Unit, ASF, Florence, Italy. 45University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, Netherlands. 46University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, Netherlands. 47Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, Netherlands. 48University of Groningen, University Medical Center Groningen, Interdisciplinary Center for Psychiatric Epidemiology, Groningen, Netherlands. 49University of Groningen, University Medical Center Groningen, Department of Internal Medicine, Groningen, Netherlands. 50Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. 51Department of Medical Sciences, Uppsala University, Uppsala, Sweden. 52Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. 53School of Women’s and Infant’s Health, The University of Western Australia, Crawley, Australia. 54Department of Physiology, University of Toronto, Toronto, Ontario, Canada. 55Center for Bone and Arthritis Research, Institute of Medicin, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. 56Child and Adolescent Psychiatry, Erasmus MC, Rotterdam, Netherlands. 57Psychiatry, Erasmus MC, Rotterdam, Netherlands. 58Medical and Population Genetics, Broad Institute, Cambridge, USA. 59Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, USA. 60Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, Germany. 61Department of Biomedicine, Aarhus University, Aarhus, Denmark. 62iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark. 63iSPYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark. 64Dept of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands. 65Division of Psychiatry, University of Edinburgh, Edinburgh, UK. 66Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark. 67iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark. 68Discipline of Psychiatry, University of Adelaide, Adelaide, Australia. 69Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany. 70Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. 71Department of Psychiatry, Virginia Commonwealth University, Richmond, USA. 72Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark. 73Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, USA. 74Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, UK. 75Human Genetics, Wellcome Trust Sanger Institute, Cambridge, UK. 76Department of Psychiatry, University Hospital of Lausanne, Prilly, Switzerland. 77MRC Social Genetic and Developmental Psychiatry Centre, King’s College London, London, UK. 78University of Oxford, Oxford, UK. 79Psychological Medicine, Cardiff University, Cardiff, UK. 80Department of Psychiatry, University of Marburg, Marburg, Germany. 81Department of Psychiatry, University of Münster, Münster, Germany. 82Avera Institute for Human Genetics, Sioux Falls, USA. 83Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK. 84EMGO+ Institute, VU University Medical Center, Amsterdam, Netherlands. 85Neurology, Brigham and Women’s Hospital, Boston, USA. 86Stanley Center for Psychiatric Research, Broad Institute, Cambridge, USA. 87Department of Psychiatry, Massachusetts General Hospital, Boston, USA. 88Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, USA. 89Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK. 90Division of Endocrinology, Children’s Hospital Boston, Boston, USA. 91Department of Genetics, Harvard Medical School, Boston, USA. 92Estonian Genome Center, University of Tartu, Tartu, Estonia. 93Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA. 94Department of Mathematics, Massachusetts Institute of Technology, Cambridge, USA. 95Department of Psychiatry, Trinity College Dublin, Dublin, Ireland. 96Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia. 97Bioinformatics Research Centre (BiRC), Aarhus University, Aarhus, Denmark. 98Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK. 99Danish Headache Centre, Department of Neurology, Rigshospitalet Glostrup, Glostrup, Denmark. 100Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Capital Region of Denmark, Roskilde, Denmark. 101iPSYCH, The Lundbeck Foundation Initiative for Psychiatric Research, Copenhagen, Denmark. 102Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, USA. 103Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine and Ernst Moritz Arndt University Greifswald, Greifswald, Germany. 104Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland. 105Department of Medicine, Harvard Medical School, Boston, USA. 106Max Planck Institute of Psychiatry, Munich, Germany. 107Division of Research, Kaiser Permanente Northern California, Oakland, USA. 108Centre for Addiction and Mental Health, Toronto, Canada. 109Department of Psychiatry, University of Toronto, Toronto, Canada. 110Psychiatry & The Behavioral Sciences, University of Southern California, Los Angeles, USA. 111Department of Endocrinology at Herlev University Hospital, University of Copenhagen, Copenhagen, Denmark. 112Swiss Institute of Bioinformatics, Lausanne, Switzerland. 113Institute of Social and Preventive Medicine (IUMSP), Lausanne University Hospital, Lausanne, Switzerland. 114Division of Psychiatry, University College London, London, UK. 115Mental Health NHS 24, Glasgow, UK. 116Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. 117Statistics, University of Oxford, Oxford, UK. 118EMGO+ Institute for Health and Care Research, Amsterdam, Netherlands. 119School of Psychology and Counseling, Queensland University of Technology, Brisbane, Australia. 120Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia. 121Estonian Biocentre, Tartu, Estonia. 122Institute for Molecular Biology, University of Queensland, Brisbane, Australia. 123Medical Genetics, University of British Columbia, Vancouver, Canada. 124Statistics, University of British Columbia, Vancouver, Canada. 125DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Matthias Nauck, Greifswald, Germany. 126Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany. 127Mental Health Centre Copenhagen, Copenhagen Universtity Hospital, Copenhagen, Denmark. 128Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia. 129MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK. 130Humus, Reykjavik, Iceland. 131Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Groton, USA. 132Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 133Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, USA. 134Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 135Medical Genetics Section, CGEM, IGMM, University of Edinburgh, Edinburgh, UK. 136Complex Trait Genetics, VU University Amsterdam, Amsterdam, Netherlands. 137Clinical Genetics, VU University Medical Center, Amsterdam, Netherlands. 138Psychiatry, University of Iowa, Iowa City, USA. 139Solid GT, Boston, USA. 140Department of Biochemistry and Molecular Biology II, Institute of Neurosciences, Center for Biomedical Research, University of Granada, Granada, Spain. 141Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA. 142Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, Netherlands. 143Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, USA. 144Faculty of Medicine, Department of Psychiatry, School of Health Sciences, University of Iceland, Reykjavik, Iceland. 145School of Medicine and Dentistry, James Cook University, Townsville, Australia. 146Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK. 147deCODE Genetics/Amgen, Reykjavik, Iceland. 148College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK. 149Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. 150iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark. 151KG Jebsen Centre for Psychosis Research, Norway Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. 152Department of Psychiatry, University of California, San Diego, San Diego, USA. 153Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia. 154Roche Pharmaceutical Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases Discovery & Translational Medicine Area, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland. 155Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany. 156Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands. 157Virginia Institute of Psychiatric & Behavioral Genetics, Virginia Commonwealth University, Richmond, USA. 158Psychiatry, Columbia University College of Physicians and Surgeons, New York, USA. 159Division of Epidemiology, New York State Psychiatric Institute, New York, USA. 160Computational Sciences Center of Emphasis, Pfizer Global Research and Development, Cambridge, USA. 161Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark. 162Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany. 163Department of Biomedicine, University of Basel, Basel, CH, Switzerland. 164Division of Medical Genetics, University of Basel, Basel, CH, Switzerland. 165Centre for Integrative Biology, Università degli Studi di Trento, Trento, Italy. 166Psychiatry, University of California Los Angeles, Los Angeles, USA. 167Psychiatry, Kaiser Permanente Northern California, San Francisco, USA. 168Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, USA. 169Psychosis Research Unit, Aarhus University Hospital, Risskov, Aarhus, Denmark. 170Institute of Translational Medicine, University of Liverpool, Liverpool, UK. 171Psychiatry, Harvard Medical School, Boston, USA. 172Psychiatry, Dalhousie University, Halifax, Canada. 173Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark. 174Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Cambridge, USA. 175Orphan Disease Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA. 176NIHR BRC for Mental Health, King’s College London, London, UK. 177Psychiatry & Behavioral Sciences, Stanford University, Stanford, USA. 178Department of Medical & Molecular Genetics, King’s College London, London, UK. 179Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, USA. 180Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, USA.

Published
2017

13. A genome-wide approach to children's aggressive behavior : The EAGLE consortium.

Author

Pappa, Irene, St Pourcain, Beate, Benke, Kelly, Cavadino, Alana, Hakulinen, Christian, Nivard, Michel G, Nolte, Ilja M, Tiesler, Carla M T, Bakermans-Kranenburg, Marian J, Davies, Gareth E, Evans, David M, Geoffroy, Marie-Claude, Grallert, Harald, Groen-Blokhuis, Maria M, Hudziak, James J, Kemp, John P, Keltikangas-Järvinen, Liisa, McMahon, George, Mileva-Seitz, Viara R, Motazedi, Ehsan, Power, Christine, Raitakari, Olli T, Ring, Susan M, Rivadeneira, Fernando, Rodriguez, Alina, Scheet, Paul A, Seppälä, Ilkka, Snieder, Harold, Standl, Marie, Thiering, Elisabeth, Timpson, Nicholas J, Veenstra, René, Velders, Fleur P, Whitehouse, Andrew J O, Smith, George Davey, Heinrich, Joachim, Hypponen, Elina, Lehtimäki, Terho, Middeldorp, Christel M, Oldehinkel, Albertine J, Pennell, Craig E, Boomsma, Dorret I, Tiemeier, Henning, Pappa, Irene, St Pourcain, Beate, Benke, Kelly, Cavadino, Alana, Hakulinen, Christian, Nivard, Michel G, Nolte, Ilja M, Tiesler, Carla M T, Bakermans-Kranenburg, Marian J, Davies, Gareth E, Evans, David M, Geoffroy, Marie-Claude, Grallert, Harald, Groen-Blokhuis, Maria M, Hudziak, James J, Kemp, John P, Keltikangas-Järvinen, Liisa, McMahon, George, Mileva-Seitz, Viara R, Motazedi, Ehsan, Power, Christine, Raitakari, Olli T, Ring, Susan M, Rivadeneira, Fernando, Rodriguez, Alina, Scheet, Paul A, Seppälä, Ilkka, Snieder, Harold, Standl, Marie, Thiering, Elisabeth, Timpson, Nicholas J, Veenstra, René, Velders, Fleur P, Whitehouse, Andrew J O, Smith, George Davey, Heinrich, Joachim, Hypponen, Elina, Lehtimäki, Terho, Middeldorp, Christel M, Oldehinkel, Albertine J, Pennell, Craig E, Boomsma, Dorret I, and Tiemeier, Henning

Abstract

Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of aggressive behavior in children. We analyzed data from nine population-based studies and assessed aggressive behavior using well-validated parent-reported questionnaires. This is the largest sample exploring children's aggressive behavior to date (N = 18,988), with measures in two developmental stages (N = 15,668 early childhood and N = 16,311 middle childhood/early adolescence). First, we estimated the additive genetic variance of children's aggressive behavior based on genome-wide SNP information, using genome-wide complex trait analysis (GCTA). Second, genetic associations within each study were assessed using a quasi-Poisson regression approach, capturing the highly right-skewed distribution of aggressive behavior. Third, we performed meta-analyses of genome-wide associations for both the total age-mixed sample and the two developmental stages. Finally, we performed a gene-based test using the summary statistics of the total sample. GCTA quantified variance tagged by common SNPs (10-54%). The meta-analysis of the total sample identified one region in chromosome 2 (2p12) at near genome-wide significance (top SNP rs11126630, P = 5.30 × 10(-8) ). The separate meta-analyses of the two developmental stages revealed suggestive evidence of association at the same locus. The gene-based analysis indicated association of variation within AVPR1A with aggressive behavior. We conclude that common variants at 2p12 show suggestive evidence for association with childhood aggression. Replication of these initial findings is needed, and further studies should clarify its biological meaning. © 2015 Wiley Periodicals, Inc.

Published
2016
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14. Common variation near ROBO2 is associated with expressive vocabulary in infancy

Author

St Pourcain, Beate, Cents, Rolieke A.M., Whitehouse, Andrew J.O., Haworth, Claire M.A., Davis, Oliver S.P., O'Reilly, Paul F., Roulstone, Susan, Wren, Yvonne, Ang, Qi W., Velders, Fleur P., Evans, David M., Kemp, John P., Warrington, Nicole M., Miller, Laura, Timpson, Nicholas J., Ring, Susan M., Verhulst, Frank C., Hofman, Albert, Rivadeneira, Fernando, Meaburn, Emma L., Price, Thomas S., Dale, Philip S., Pillas, Demetris, Yliherva, Anneli, Rodriguez, Alina, Golding, Jean, Jaddoe, Vincent W.v., Jarvelin, Marjo-riitta, Plomin, Robert, Pennell, Craig E., Tiemeier, Henning, Davey Smith, George, Child and Adolescent Psychiatry / Psychology, Epidemiology, Internal Medicine, and Erasmus MC other

Subjects
Male, Genetic Linkage, European Continental Ancestry Group, Quantitative Trait Loci, Gene Expression, CHROMOSOME-3, Language Development, Polymorphism, Single Nucleotide, Speech Sound Disorder, Vocabulary, White People, Article, psyc, Dyslexia, C841 Health Psychology, MD Multidisciplinary, TOOL, Humans, Speech, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, AUTISM, Autistic Disorder, Receptors, Immunologic, LANGUAGE-DEVELOPMENT SURVEY, AXON-GUIDANCE RECEPTORS, GENE-EXPRESSION, Language, Language Disorders, Science & Technology, Chromosome Mapping, Infant, GENOTYPES, C420 Human Genetics, P1, Multidisciplinary Sciences, ENHANCERS, Phenotype, Child, Preschool, MIDLINE, Science & Technology - Other Topics, Female, Genome-Wide Association Study
Abstract

Twin studies suggest that expressive vocabulary at ~24 months is modestly heritable. However, the genes influencing this early linguistic phenotype are unknown. Here we conduct a genome-wide screen and follow-up study of expressive vocabulary in toddlers of European descent from up to four studies of the EArly Genetics and Lifecourse Epidemiology consortium, analysing an early (15–18 months, ‘one-word stage’, NTotal=8,889) and a later (24–30 months, ‘two-word stage’, NTotal=10,819) phase of language acquisition. For the early phase, one single-nucleotide polymorphism (rs7642482) at 3p12.3 near ROBO2, encoding a conserved axon-binding receptor, reaches the genome-wide significance level (P=1.3 × 10−8) in the combined sample. This association links language-related common genetic variation in the general population to a potential autism susceptibility locus and a linkage region for dyslexia, speech-sound disorder and reading. The contribution of common genetic influences is, although modest, supported by genome-wide complex trait analysis (meta-GCTA h215–18-months=0.13, meta-GCTA h224–30-months=0.14) and in concordance with additional twin analysis (5,733 pairs of European descent, h224-months=0.20)., The genetic basis of expressive vocabulary in children around 2 years old is poorly understood. Here, the authors show that a genetic variant near the ROBO2 gene is associated with early language acquisition in the general population and highlight a potential genetic link between language-related common genetic variation and a linkage region for dyslexia, speech-sound disorder and reading.

Published
2014

15. A genome-wide approach to children's aggressive behavior:The EAGLE consortium

Author

Pappa, Irene, primary, St Pourcain, Beate, additional, Benke, Kelly, additional, Cavadino, Alana, additional, Hakulinen, Christian, additional, Nivard, Michel G., additional, Nolte, Ilja M., additional, Tiesler, Carla M. T., additional, Bakermans-Kranenburg, Marian J., additional, Davies, Gareth E., additional, Evans, David M., additional, Geoffroy, Marie-Claude, additional, Grallert, Harald, additional, Groen-Blokhuis, Maria M., additional, Hudziak, James J., additional, Kemp, John P., additional, Keltikangas-Järvinen, Liisa, additional, McMahon, George, additional, Mileva-Seitz, Viara R., additional, Motazedi, Ehsan, additional, Power, Christine, additional, Raitakari, Olli T., additional, Ring, Susan M., additional, Rivadeneira, Fernando, additional, Rodriguez, Alina, additional, Scheet, Paul A., additional, Seppälä, Ilkka, additional, Snieder, Harold, additional, Standl, Marie, additional, Thiering, Elisabeth, additional, Timpson, Nicholas J., additional, Veenstra, René, additional, Velders, Fleur P., additional, Whitehouse, Andrew J. O., additional, Smith, George Davey, additional, Heinrich, Joachim, additional, Hypponen, Elina, additional, Lehtimäki, Terho, additional, Middeldorp, Christel M., additional, Oldehinkel, Albertine J., additional, Pennell, Craig E., additional, Boomsma, Dorret I., additional, and Tiemeier, Henning, additional

Published
2015
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16. Genome Wide Association Identifies Common Variants at the SERPINA6/SERPINA1 Locus Influencing Plasma Cortisol and Corticosteroid Binding Globulin

Author

Bolton, Jennifer L., Hayward, Caroline, Direk, Nese, Lewis, John G., Hammond, Geoffrey L., Hill, Lesley A., Anderson, Anna, Huffman, Jennifer, Wilson, James F., Campbell, Harry, Rudan, Igor, Wright, Alan, Hastie, Nicholas, Wild, Sarah H., Velders, Fleur P., Hofman, Albert, Uitterlinden, Andre G., Lahti, Jari, Raikkonen, Katri, Kajantie, Eero, Widen, Elisabeth, Palotie, Aarno, Eriksson, Johan G., Kaakinen, Marika, Jarvelin, Marjo-Riitta, Timpson, Nicholas J., Smith, George Davey, Ring, Susan M., Evans, David M., St Pourcain, Beate, Tanaka, Toshiko, Milaneschi, Yuri, Bandinelli, Stefania, Ferrucci, Luigi, van der Harst, Pim, Rosmalen, Judith G. M., Bakker, Stephen J. L., Verweij, Niek, Dullaart, Robin P. F., Mahajan, Anubha, Lindgren, Cecilia M., Morris, Andrew, Lind, Lars, Ingelsson, Erik, Anderson, Laura N., Pennell, Craig E., Lye, Stephen J., Matthews, Stephen G., Eriksson, Joel, Mellstrom, Dan, Ohlsson, Claes, Price, Jackie F., Strachan, Mark W. J., Reynolds, Rebecca M., Tiemeier, Henning, Walker, Brian R., Bolton, Jennifer L., Hayward, Caroline, Direk, Nese, Lewis, John G., Hammond, Geoffrey L., Hill, Lesley A., Anderson, Anna, Huffman, Jennifer, Wilson, James F., Campbell, Harry, Rudan, Igor, Wright, Alan, Hastie, Nicholas, Wild, Sarah H., Velders, Fleur P., Hofman, Albert, Uitterlinden, Andre G., Lahti, Jari, Raikkonen, Katri, Kajantie, Eero, Widen, Elisabeth, Palotie, Aarno, Eriksson, Johan G., Kaakinen, Marika, Jarvelin, Marjo-Riitta, Timpson, Nicholas J., Smith, George Davey, Ring, Susan M., Evans, David M., St Pourcain, Beate, Tanaka, Toshiko, Milaneschi, Yuri, Bandinelli, Stefania, Ferrucci, Luigi, van der Harst, Pim, Rosmalen, Judith G. M., Bakker, Stephen J. L., Verweij, Niek, Dullaart, Robin P. F., Mahajan, Anubha, Lindgren, Cecilia M., Morris, Andrew, Lind, Lars, Ingelsson, Erik, Anderson, Laura N., Pennell, Craig E., Lye, Stephen J., Matthews, Stephen G., Eriksson, Joel, Mellstrom, Dan, Ohlsson, Claes, Price, Jackie F., Strachan, Mark W. J., Reynolds, Rebecca M., Tiemeier, Henning, and Walker, Brian R.

Abstract

Variation in plasma levels of cortisol, an essential hormone in the stress response, is associated in population-based studies with cardio-metabolic, inflammatory and neuro-cognitive traits and diseases. Heritability of plasma cortisol is estimated at 30-60% but no common genetic contribution has been identified. The CORtisol NETwork (CORNET) consortium undertook genome wide association meta-analysis for plasma cortisol in 12,597 Caucasian participants, replicated in 2,795 participants. The results indicate that <1% of variance in plasma cortisol is accounted for by genetic variation in a single region of chromosome 14. This locus spans SERPINA6, encoding corticosteroid binding globulin (CBG, the major cortisol-binding protein in plasma), and SERPINA1, encoding alpha 1-antitrypsin (which inhibits cleavage of the reactive centre loop that releases cortisol from CBG). Three partially independent signals were identified within the region, represented by common SNPs; detailed biochemical investigation in a nested sub-cohort showed all these SNPs were associated with variation in total cortisol binding activity in plasma, but some variants influenced total CBG concentrations while the top hit (rs12589136) influenced the immunoreactivity of the reactive centre loop of CBG. Exome chip and 1000 Genomes imputation analysis of this locus in the CROATIA-Korcula cohort identified missense mutations in SERPINA6 and SERPINA1 that did not account for the effects of common variants. These findings reveal a novel common genetic source of variation in binding of cortisol by CBG, and reinforce the key role of CBG in determining plasma cortisol levels. In turn this genetic variation may contribute to cortisol-associated degenerative diseases.

Published
2014
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17. Genome Wide Association Identifies Common Variants at the SERPINA6/SERPINA1 Locus Influencing Plasma Cortisol and Corticosteroid Binding Globulin

Author

University of Helsinki, Institute of Behavioural Sciences, University of Helsinki, Hospital for Children and Adolescents, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Clinicum, Bolton, Jennifer L., Hayward, Caroline, Direk, Nese, Lewis, John G., Hammond, Geoffrey L., Hill, Lesley A., Anderson, Anna, Huffman, Jennifer, Wilson, James F., Campbell, Harry, Rudan, Igor, Wright, Alan, Hastie, Nicholas, Wild, Sarah H., Velders, Fleur P., Hofman, Albert, Uitterlinden, Andre G., Lahti, Jari, Räikkönen, Katri, Kajantie, Eero, Widen, Elisabeth, Palotie, Aarno, Eriksson, Johan G., Kaakinen, Marika, Jarvelin, Marjo-Riitta, Timpson, Nicholas J., Smith, George Davey, Ring, Susan M., Evans, David M., St Pourcain, Beate, Tanaka, Toshiko, Milaneschi, Yuri, Bandinelli, Stefania, Ferrucci, Luigi, van der Harst, Pim, Rosmalen, Judith G. M., Bakker, Stephen J. L., Verweij, Niek, Dullaart, Robin P. F., Mahajan, Anubha, Lindgren, Cecilia M., Morris, Andrew, Lind, Lars, Ingelsson, Erik, Anderson, Laura N., Pennell, Craig E., Lye, Stephen J., Matthews, Stephen G., Eriksson, Joel, Mellstrom, Dan, Ohlsson, Claes, Price, Jackie F., Strachan, Mark W. J., Reynolds, Rebecca M., Tiemeier, Henning, Walker, Brian R., University of Helsinki, Institute of Behavioural Sciences, University of Helsinki, Hospital for Children and Adolescents, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Clinicum, Bolton, Jennifer L., Hayward, Caroline, Direk, Nese, Lewis, John G., Hammond, Geoffrey L., Hill, Lesley A., Anderson, Anna, Huffman, Jennifer, Wilson, James F., Campbell, Harry, Rudan, Igor, Wright, Alan, Hastie, Nicholas, Wild, Sarah H., Velders, Fleur P., Hofman, Albert, Uitterlinden, Andre G., Lahti, Jari, Räikkönen, Katri, Kajantie, Eero, Widen, Elisabeth, Palotie, Aarno, Eriksson, Johan G., Kaakinen, Marika, Jarvelin, Marjo-Riitta, Timpson, Nicholas J., Smith, George Davey, Ring, Susan M., Evans, David M., St Pourcain, Beate, Tanaka, Toshiko, Milaneschi, Yuri, Bandinelli, Stefania, Ferrucci, Luigi, van der Harst, Pim, Rosmalen, Judith G. M., Bakker, Stephen J. L., Verweij, Niek, Dullaart, Robin P. F., Mahajan, Anubha, Lindgren, Cecilia M., Morris, Andrew, Lind, Lars, Ingelsson, Erik, Anderson, Laura N., Pennell, Craig E., Lye, Stephen J., Matthews, Stephen G., Eriksson, Joel, Mellstrom, Dan, Ohlsson, Claes, Price, Jackie F., Strachan, Mark W. J., Reynolds, Rebecca M., Tiemeier, Henning, and Walker, Brian R.

Published
2014

20. Variation in the Glucocorticoid Receptor Gene at rs41423247 Moderates the Effect of Prenatal Maternal Psychological Symptoms on Child Cortisol Reactivity and Behavior

Author

Velders, Fleur P, primary, Dieleman, Gwen, additional, Cents, Rolieke AM, additional, Bakermans-Kranenburg, Marian J, additional, Jaddoe, Vincent WV, additional, Hofman, Albert, additional, Van IJzendoorn, Marinus H, additional, Verhulst, Frank C, additional, and Tiemeier, Henning, additional

Published
2012
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24. Genome Wide Association Identifies Common Variants at the SERPINA6/SERPINA1 Locus Influencing Plasma Cortisol and Corticosteroid Binding Globulin.

Author

Bolton, Jennifer L., Hayward, Caroline, Direk, Nese, Lewis, John G., Hammond, Geoffrey L., Hill, Lesley A., Anderson, Anna, Huffman, Jennifer, Wilson, James F., Campbell, Harry, Rudan, Igor, Wright, Alan, Hastie, Nicholas, Wild, Sarah H., Velders, Fleur P., Hofman, Albert, Uitterlinden, Andre G., Lahti, Jari, Räikkönen, Katri, and Kajantie, Eero

Subjects
HYDROCORTISONE, COGNITION disorders research, HERITABILITY, CORTICOSTEROIDS, DEGENERATION (Pathology)
Abstract

Variation in plasma levels of cortisol, an essential hormone in the stress response, is associated in population-based studies with cardio-metabolic, inflammatory and neuro-cognitive traits and diseases. Heritability of plasma cortisol is estimated at 30–60% but no common genetic contribution has been identified. The CORtisol NETwork (CORNET) consortium undertook genome wide association meta-analysis for plasma cortisol in 12,597 Caucasian participants, replicated in 2,795 participants. The results indicate that <1% of variance in plasma cortisol is accounted for by genetic variation in a single region of chromosome 14. This locus spans SERPINA6, encoding corticosteroid binding globulin (CBG, the major cortisol-binding protein in plasma), and SERPINA1, encoding α1-antitrypsin (which inhibits cleavage of the reactive centre loop that releases cortisol from CBG). Three partially independent signals were identified within the region, represented by common SNPs; detailed biochemical investigation in a nested sub-cohort showed all these SNPs were associated with variation in total cortisol binding activity in plasma, but some variants influenced total CBG concentrations while the top hit (rs12589136) influenced the immunoreactivity of the reactive centre loop of CBG. Exome chip and 1000 Genomes imputation analysis of this locus in the CROATIA-Korcula cohort identified missense mutations in SERPINA6 and SERPINA1 that did not account for the effects of common variants. These findings reveal a novel common genetic source of variation in binding of cortisol by CBG, and reinforce the key role of CBG in determining plasma cortisol levels. In turn this genetic variation may contribute to cortisol-associated degenerative diseases. [ABSTRACT FROM AUTHOR]

Published
2014
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25. The role of maternal stress during pregnancy, maternal discipline, and child COMT Val158Met genotype in the development of compliance.

Author

Kok, Rianne, Bakermans‐Kranenburg, Marian J., van IJzendoorn, Marinus H., Velders, Fleur P., Linting, Mariëlle, Jaddoe, Vincent W.V., Hofman, Albert, Verhulst, Frank C., and Tiemeier, Henning

Abstract

Maternal discipline is an important predictor of child committed compliance. Maternal stress can affect both parenting and child development. In a large population-based cohort study ( N = 613) we examined whether maternal discipline mediated the association between maternal stress during pregnancy and child compliance, and whether COMT or DRD4 polymorphisms moderated the association between maternal discipline and child compliance. Family-related and general stress were measured through maternal self-report and genetic material was collected through cord blood sampling at birth. Mother-child dyads were observed at 36 months in disciplinary tasks in which the child was not allowed to touch attractive toys. Maternal discipline and child compliance were observed in two different tasks and independently coded. The association between family stress during pregnancy and child committed compliance was mediated by maternal positive discipline. Children with more COMT Met alleles seemed more susceptible to maternal positive discipline than children with more COMT Val alleles. © 2012 Wiley Periodicals, Inc. Dev Psychobiol 55: 451-464, 2013 [ABSTRACT FROM AUTHOR]

Published
2013
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26. A genome-wide approach to children's aggressive behavior: the EAGLE consortium

Author

Pappa, Irene, St Pourcain, Beate, Benke, Kelly, Cavadino, Alana, Hakulinen, Christian, Nivard, Michel G., Nolte, Ilja M., Tiesler, Carla M. T., Bakermans-Kranenburg, Marian J., Davies, Gareth E., Evans, David M., Geoffroy, Marie-Claude, Grallert, Harald, Groen-Blokhuis, Maria M., Hudziak, James J., Kemp, John P., Keltikangas-Järvinen, Liisa, McMahon, George, Mileva-Seitz, Viara R., Motazedi, Ehsan, Power, Christine, Raitakari, Olli T., Ring, Susan M., Rivadeneira, Fernando, Rodriguez, Alina, Scheet, Paul A., Seppälä, Ilkka, Snieder, Harold, Standl, Marie, Thiering, Elisabeth, Timpson, Nicholas J., Veenstra, René, Velders, Fleur P., Whitehouse, Andrew J. O., Smith, George Davey, Heinrich, Joachim, Hypponen, Elina, Lehtimäki, Terho, Middeldorp, Christel M., Oldehinkel, Albertine J., Pennell, Craig E., Boomsma, Dorret I., Tiemeier, Henning, Pappa, Irene, St Pourcain, Beate, Benke, Kelly, Cavadino, Alana, Hakulinen, Christian, Nivard, Michel G., Nolte, Ilja M., Tiesler, Carla M. T., Bakermans-Kranenburg, Marian J., Davies, Gareth E., Evans, David M., Geoffroy, Marie-Claude, Grallert, Harald, Groen-Blokhuis, Maria M., Hudziak, James J., Kemp, John P., Keltikangas-Järvinen, Liisa, McMahon, George, Mileva-Seitz, Viara R., Motazedi, Ehsan, Power, Christine, Raitakari, Olli T., Ring, Susan M., Rivadeneira, Fernando, Rodriguez, Alina, Scheet, Paul A., Seppälä, Ilkka, Snieder, Harold, Standl, Marie, Thiering, Elisabeth, Timpson, Nicholas J., Veenstra, René, Velders, Fleur P., Whitehouse, Andrew J. O., Smith, George Davey, Heinrich, Joachim, Hypponen, Elina, Lehtimäki, Terho, Middeldorp, Christel M., Oldehinkel, Albertine J., Pennell, Craig E., Boomsma, Dorret I., and Tiemeier, Henning

Abstract

Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of aggressive behavior in children. We analyzed data from nine population-based studies and assessed aggressive behavior using well-validated parent-reported questionnaires. This is the largest sample exploring children's aggressive behavior to date (N = 18,988), with measures in two developmental stages (N = 15,668 early childhood and N = 16,311 middle childhood/early adolescence). First, we estimated the additive genetic variance of children's aggressive behavior based on genome-wide SNP information, using genome-wide complex trait analysis (GCTA). Second, genetic associations within each study were assessed using a quasi-Poisson regression approach, capturing the highly right-skewed distribution of aggressive behavior. Third, we performed meta-analyses of genome-wide associations for both the total age-mixed sample and the two developmental stages. Finally, we performed a gene-based test using the summary statistics of the total sample. GCTA quantified variance tagged by common SNPs (10–54%). The meta-analysis of the total sample identified one region in chromosome 2 (2p12) at near genome-wide significance (top SNP rs11126630, P = 5.30 × 10−8). The separate meta-analyses of the two developmental stages revealed suggestive evidence of association at the same locus. The gene-based analysis indicated association of variation within AVPR1A with aggressive behavior. We conclude that common variants at 2p12 show suggestive evidence for association with childhood aggression. Replication of these initial findings is needed, and further studies should clarify its biological meaning. © 2015 Wiley Periodicals, Inc.

27. Common variation near ROBO2 is associated with expressive vocabulary in infancy

Author

St Pourcain, Beate, Cents, Rolieke A. M., Whitehouse, Andrew J. O., Haworth, Claire M. A., Davis, Oliver S. P., O’Reilly, Paul F., Roulstone, Susan, Wren, Yvonne, Ang, Qi W., Velders, Fleur P., Evans, David M., Kemp, John P., Warrington, Nicole M., Miller, Laura, Timpson, Nicholas J., Ring, Susan M., Verhulst, Frank C., Hofman, Albert, Rivadeneira, Fernando, Meaburn, Emma L., Price, Thomas S., Dale, Philip S., Pillas, Demetris, Yliherva, Anneli, Rodriguez, Alina, Golding, Jean, Jaddoe, Vincent W. V., Jarvelin, Marjo-Riitta, Plomin, Robert, Pennell, Craig E., Tiemeier, Henning, Davey Smith, George, St Pourcain, Beate, Cents, Rolieke A. M., Whitehouse, Andrew J. O., Haworth, Claire M. A., Davis, Oliver S. P., O’Reilly, Paul F., Roulstone, Susan, Wren, Yvonne, Ang, Qi W., Velders, Fleur P., Evans, David M., Kemp, John P., Warrington, Nicole M., Miller, Laura, Timpson, Nicholas J., Ring, Susan M., Verhulst, Frank C., Hofman, Albert, Rivadeneira, Fernando, Meaburn, Emma L., Price, Thomas S., Dale, Philip S., Pillas, Demetris, Yliherva, Anneli, Rodriguez, Alina, Golding, Jean, Jaddoe, Vincent W. V., Jarvelin, Marjo-Riitta, Plomin, Robert, Pennell, Craig E., Tiemeier, Henning, and Davey Smith, George

Abstract

Twin studies suggest that expressive vocabulary at ~24 months is modestly heritable. However, the genes influencing this early linguistic phenotype are unknown. Here we conduct a genome-wide screen and follow-up study of expressive vocabulary in toddlers of European descent from up to four studies of the EArly Genetics and Lifecourse Epidemiology consortium, analysing an early (15–18 months, ‘one-word stage’, NTotal=8,889) and a later (24–30 months, ‘two-word stage’, NTotal=10,819) phase of language acquisition. For the early phase, one single-nucleotide polymorphism (rs7642482) at 3p12.3 near ​ROBO2, encoding a conserved axon-binding receptor, reaches the genome-wide significance level (P=1.3 × 10−8) in the combined sample. This association links language-related common genetic variation in the general population to a potential autism susceptibility locus and a linkage region for dyslexia, speech-sound disorder and reading. The contribution of common genetic influences is, although modest, supported by genome-wide complex trait analysis (meta-GCTA h215–18-months=0.13, meta-GCTA h224–30-months=0.14) and in concordance with additional twin analysis (5,733 pairs of European descent, h224-months=0.20).

28. A genome-wide approach to children's aggressive behavior: The EAGLE consortium.

Author

Pappa I, St Pourcain B, Benke K, Cavadino A, Hakulinen C, Nivard MG, Nolte IM, Tiesler CM, Bakermans-Kranenburg MJ, Davies GE, Evans DM, Geoffroy MC, Grallert H, Groen-Blokhuis MM, Hudziak JJ, Kemp JP, Keltikangas-Järvinen L, McMahon G, Mileva-Seitz VR, Motazedi E, Power C, Raitakari OT, Ring SM, Rivadeneira F, Rodriguez A, Scheet PA, Seppälä I, Snieder H, Standl M, Thiering E, Timpson NJ, Veenstra R, Velders FP, Whitehouse AJ, Smith GD, Heinrich J, Hypponen E, Lehtimäki T, Middeldorp CM, Oldehinkel AJ, Pennell CE, Boomsma DI, and Tiemeier H

Subjects
Adolescent, Aggression psychology, Behavior, Child, Female, Genetic Association Studies methods, Genetic Predisposition to Disease genetics, Genetic Variation, Genetics, Behavioral methods, Genome-Wide Association Study, Humans, Male, Polymorphism, Single Nucleotide genetics, Receptors, Vasopressin genetics, Receptors, Vasopressin physiology, Surveys and Questionnaires, Aggression physiology
Abstract

Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of aggressive behavior in children. We analyzed data from nine population-based studies and assessed aggressive behavior using well-validated parent-reported questionnaires. This is the largest sample exploring children's aggressive behavior to date (N = 18,988), with measures in two developmental stages (N = 15,668 early childhood and N = 16,311 middle childhood/early adolescence). First, we estimated the additive genetic variance of children's aggressive behavior based on genome-wide SNP information, using genome-wide complex trait analysis (GCTA). Second, genetic associations within each study were assessed using a quasi-Poisson regression approach, capturing the highly right-skewed distribution of aggressive behavior. Third, we performed meta-analyses of genome-wide associations for both the total age-mixed sample and the two developmental stages. Finally, we performed a gene-based test using the summary statistics of the total sample. GCTA quantified variance tagged by common SNPs (10-54%). The meta-analysis of the total sample identified one region in chromosome 2 (2p12) at near genome-wide significance (top SNP rs11126630, P = 5.30 × 10(-8) ). The separate meta-analyses of the two developmental stages revealed suggestive evidence of association at the same locus. The gene-based analysis indicated association of variation within AVPR1A with aggressive behavior. We conclude that common variants at 2p12 show suggestive evidence for association with childhood aggression. Replication of these initial findings is needed, and further studies should clarify its biological meaning. © 2015 Wiley Periodicals, Inc., (© 2015 Wiley Periodicals, Inc.)

Published
2016
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29. Common variation near ROBO2 is associated with expressive vocabulary in infancy.

Author

St Pourcain B, Cents RA, Whitehouse AJ, Haworth CM, Davis OS, O'Reilly PF, Roulstone S, Wren Y, Ang QW, Velders FP, Evans DM, Kemp JP, Warrington NM, Miller L, Timpson NJ, Ring SM, Verhulst FC, Hofman A, Rivadeneira F, Meaburn EL, Price TS, Dale PS, Pillas D, Yliherva A, Rodriguez A, Golding J, Jaddoe VW, Jarvelin MR, Plomin R, Pennell CE, Tiemeier H, and Davey Smith G

Subjects
Autistic Disorder ethnology, Autistic Disorder physiopathology, Child, Preschool, Chromosome Mapping, Dyslexia ethnology, Dyslexia physiopathology, Female, Gene Expression, Genetic Linkage, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Infant, Language, Language Disorders ethnology, Language Disorders physiopathology, Male, Phenotype, Polymorphism, Single Nucleotide, Speech physiology, Speech Sound Disorder, Vocabulary, White People, Autistic Disorder genetics, Dyslexia genetics, Language Development, Language Disorders genetics, Quantitative Trait Loci, Receptors, Immunologic genetics
Abstract

Twin studies suggest that expressive vocabulary at ~24 months is modestly heritable. However, the genes influencing this early linguistic phenotype are unknown. Here we conduct a genome-wide screen and follow-up study of expressive vocabulary in toddlers of European descent from up to four studies of the EArly Genetics and Lifecourse Epidemiology consortium, analysing an early (15-18 months, 'one-word stage', N(Total) = 8,889) and a later (24-30 months, 'two-word stage', N(Total)=10,819) phase of language acquisition. For the early phase, one single-nucleotide polymorphism (rs7642482) at 3p12.3 near ROBO2, encoding a conserved axon-binding receptor, reaches the genome-wide significance level (P=1.3 × 10(-8)) in the combined sample. This association links language-related common genetic variation in the general population to a potential autism susceptibility locus and a linkage region for dyslexia, speech-sound disorder and reading. The contribution of common genetic influences is, although modest, supported by genome-wide complex trait analysis (meta-GCTA h(2)(15-18-months) = 0.13, meta-GCTA h(2)(24-30-months) = 0.14) and in concordance with additional twin analysis (5,733 pairs of European descent, h(2)(24-months) = 0.20).

Published
2014
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30. Genome wide association identifies common variants at the SERPINA6/SERPINA1 locus influencing plasma cortisol and corticosteroid binding globulin.

Author

Bolton JL, Hayward C, Direk N, Lewis JG, Hammond GL, Hill LA, Anderson A, Huffman J, Wilson JF, Campbell H, Rudan I, Wright A, Hastie N, Wild SH, Velders FP, Hofman A, Uitterlinden AG, Lahti J, Räikkönen K, Kajantie E, Widen E, Palotie A, Eriksson JG, Kaakinen M, Järvelin MR, Timpson NJ, Davey Smith G, Ring SM, Evans DM, St Pourcain B, Tanaka T, Milaneschi Y, Bandinelli S, Ferrucci L, van der Harst P, Rosmalen JG, Bakker SJ, Verweij N, Dullaart RP, Mahajan A, Lindgren CM, Morris A, Lind L, Ingelsson E, Anderson LN, Pennell CE, Lye SJ, Matthews SG, Eriksson J, Mellstrom D, Ohlsson C, Price JF, Strachan MW, Reynolds RM, Tiemeier H, and Walker BR

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Cohort Studies, Exome genetics, Female, Humans, Male, Middle Aged, Mutation, Polymorphism, Single Nucleotide genetics, Protein Binding, Transcortin metabolism, alpha 1-Antitrypsin metabolism, Genome-Wide Association Study, Hydrocortisone blood, Transcortin genetics, alpha 1-Antitrypsin genetics
Abstract

Variation in plasma levels of cortisol, an essential hormone in the stress response, is associated in population-based studies with cardio-metabolic, inflammatory and neuro-cognitive traits and diseases. Heritability of plasma cortisol is estimated at 30-60% but no common genetic contribution has been identified. The CORtisol NETwork (CORNET) consortium undertook genome wide association meta-analysis for plasma cortisol in 12,597 Caucasian participants, replicated in 2,795 participants. The results indicate that <1% of variance in plasma cortisol is accounted for by genetic variation in a single region of chromosome 14. This locus spans SERPINA6, encoding corticosteroid binding globulin (CBG, the major cortisol-binding protein in plasma), and SERPINA1, encoding α1-antitrypsin (which inhibits cleavage of the reactive centre loop that releases cortisol from CBG). Three partially independent signals were identified within the region, represented by common SNPs; detailed biochemical investigation in a nested sub-cohort showed all these SNPs were associated with variation in total cortisol binding activity in plasma, but some variants influenced total CBG concentrations while the top hit (rs12589136) influenced the immunoreactivity of the reactive centre loop of CBG. Exome chip and 1000 Genomes imputation analysis of this locus in the CROATIA-Korcula cohort identified missense mutations in SERPINA6 and SERPINA1 that did not account for the effects of common variants. These findings reveal a novel common genetic source of variation in binding of cortisol by CBG, and reinforce the key role of CBG in determining plasma cortisol levels. In turn this genetic variation may contribute to cortisol-associated degenerative diseases.

Published
2014
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