30 results on '"Ripke, Stephan"'
Search Results
2. Distinct genetic liability profiles define clinically relevant patient strata across common diseases.
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Trastulla, Lucia, Dolgalev, Georgii, Moser, Sylvain, Jiménez-Barrón, Laura T., Andlauer, Till F. M., von Scheidt, Moritz, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Ruderfer, Douglas M., Ripke, Stephan, McQuillin, Andrew, Stahl, Eli A., Domenici, Enrico, Adolfsson, Rolf, Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A., and Begemann, Martin
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CORONARY artery disease ,GENE expression profiling ,INDIVIDUALIZED medicine ,OLANZAPINE - Abstract
Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms. Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient 'biotypes' characterized by partially distinct disease mechanisms. [ABSTRACT FROM AUTHOR]
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- 2024
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3. Polygenetic risk scores and phenotypic constellations of obsessive–compulsive disorder in clozapine-treated schizophrenia.
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Morgenroth, Carla Lou, Kleymann, Philipp, Ripke, Stephan, Awasthi, Swapnil, Wagner, Elias, Oviedo-Salcedo, Tatiana, Okhuijsen-Pfeifer, Cynthia, Luykx, Jurjen J., van der Horst, Marte Z., Hasan, Alkomiet, Bermpohl, Felix, Gutwinski, Stefan, and Schreiter, Stefanie
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DISEASE risk factors ,OBSESSIVE-compulsive disorder ,PATHOLOGICAL psychology ,PHENOTYPES ,SCHIZOPHRENIA - Abstract
Obsessive–compulsive symptoms (OCS) are frequently observed in individuals with schizophrenia (SCZ) treated with clozapine (CLZ). This study aimed to analyze prevalence of OCS and obsessive–compulsive disorder (OCD) in this subgroup and find possible correlations with different phenotypes. Additionally, this is the first study to examine polygenetic risk scores (PRS) in individuals with SCZ and OCS. A multicenter cohort of 91 individuals with SCZ who were treated with CLZ was recruited and clinically and genetically assessed. Symptom severity was examined using the Positive and Negative Symptom Scale (PANSS), Clinical Global Impression Scale (CGI), the Calgary Depression Scale for Schizophrenia (CDSS), Global Assessment of Functioning Scale (GAF) and Yale–Brown Obsessive–Compulsive Scale (Y-BOCS). Participants were divided into subgroups based on phenotypic OCS or OCD using Y-BOCS scores. Genomic-wide data were generated, and PRS analyses were performed to evaluate the association between either phenotypic OCD or OCS severity and genotype-predicted predisposition for OCD, SCZ, cross-disorder, and CLZ/norclozapine (NorCLZ) ratio, CLZ metabolism and NorCLZ metabolism. OCS and OCD were frequent comorbidities in our sample of CLZ-treated SCZ individuals, with a prevalence of 39.6% and 27.5%, respectively. Furthermore, the Y-BOCS total score correlated positively with the duration of CLZ treatment in years (r = 0.28; p = 0.008) and the PANSS general psychopathology subscale score (r = 0.23; p = 0.028). A significant correlation was found between OCD occurrence and PRS for CLZ metabolism. We found no correlation between OCS severity and PRS for CLZ metabolism. We found no correlation for either OCD or OCS and PRS for OCD, cross-disorder, SCZ, CLZ/NorCLZ ratio or NorCLZ metabolism. Our study was able to replicate previous findings on clinical characteristics of CLZ-treated SCZ individuals. OCS is a frequent comorbidity in this cohort and is correlated with CLZ treatment duration in years and PANSS general psychopathology subscale score. We found a correlation between OCD and PRS for CLZ metabolism, which should be interpreted as incidental for now. Future research is necessary to replicate significant findings and to assess possible genetic predisposition of CLZ-treated individuals with SCZ to OCS/OCD. Limitations attributed to the small sample size or the inclusion of subjects on co-medication must be considered. If the association between OCD and PRS for CLZ metabolism can be replicated, it should be further evaluated if CYP1A2 alteration, respectively lower CLZ plasma level, is relevant for OCD development. [ABSTRACT FROM AUTHOR]
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- 2024
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4. Evidence for a shared genetic contribution to loneliness and borderline personality disorder.
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Schulze, Anna, Streit, Fabian, Zillich, Lea, Awasthi, Swapnil, Hall, Alisha S. M., Jungkunz, Martin, Kleindienst, Nikolaus, Frank, Josef, Schwarze, Cornelia E., Dahmen, Norbert, Schott, Björn H., Nöthen, Markus, Mobascher, Arian, Rujescu, Dan, Lieb, Klaus, Roepke, Stefan, Herpertz, Sabine C., Schmahl, Christian, Bohus, Martin, and Ripke, Stephan
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- 2023
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5. Oxytocin vs. placebo effects on intrusive memory consolidation using a trauma film paradigm: a randomized, controlled experimental study in healthy women.
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Maslahati, Tolou, Wingenfeld, Katja, Hellmann-Regen, Julian, Kraft, Julia, Lyu, Jing, Keinert, Marie, Voß, Aline, Cho, An Bin, Ripke, Stephan, Otte, Christian, Schultebraucks, Katharina, and Roepke, Stefan
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- 2023
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6. Hair cortisol in twins:heritability and genetic overlap with psychological variables and stress-system genes
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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
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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
7. Complement genes contribute sex-biased vulnerability in diverse disorders.
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Kamitaki, Nolan, Sekar, Aswin, Handsaker, Robert E., de Rivera, Heather, Tooley, Katherine, Morris, David L., Taylor, Kimberly E., Whelan, Christopher W., Tombleson, Philip, Loohuis, Loes M. Olde, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Ripke, Stephan, Neale, Benjamin M., Corvin, Aiden, Walters, James T. R., Farh, Kai-How, Holmans, Peter A., Lee, Phil, Bulik-Sullivan, Brendan, and Collier, David A.
- Abstract
Many common illnesses, for reasons that have not been identified, differentially affect men and women. For instance, the autoimmune diseases systemic lupus erythematosus (SLE) and Sjögren's syndrome affect nine times more women than men1, whereas schizophrenia affects men with greater frequency and severity relative to women2. All three illnesses have their strongest common genetic associations in the major histocompatibility complex (MHC) locus, an association that in SLE and Sjögren's syndrome has long been thought to arise from alleles of the human leukocyte antigen (HLA) genes at that locus3–6. Here we show that variation of the complement component 4 (C4) genes C4A and C4B, which are also at the MHC locus and have been linked to increased risk for schizophrenia7, generates 7-fold variation in risk for SLE and 16-fold variation in risk for Sjögren's syndrome among individuals with common C4 genotypes, with C4A protecting more strongly than C4B in both illnesses. The same alleles that increase risk for schizophrenia greatly reduce risk for SLE and Sjögren's syndrome. In all three illnesses, C4 alleles act more strongly in men than in women: common combinations of C4A and C4B generated 14-fold variation in risk for SLE, 31-fold variation in risk for Sjögren's syndrome, and 1.7-fold variation in schizophrenia risk among men (versus 6-fold, 15-fold and 1.26-fold variation in risk among women, respectively). At a protein level, both C4 and its effector C3 were present at higher levels in cerebrospinal fluid and plasma8,9 in men than in women among adults aged between 20 and 50 years, corresponding to the ages of differential disease vulnerability. Sex differences in complement protein levels may help to explain the more potent effects of C4 alleles in men, women's greater risk of SLE and Sjögren's syndrome and men's greater vulnerability to schizophrenia. These results implicate the complement system as a source of sexual dimorphism in vulnerability to diverse illnesses. Sexual dimorphism in genetic vulnerability to schizophrenia, systemic lupus erythematosus and Sjögren's syndrome is linked to differential protein abundance from alleles of complement component 4. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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8. A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank.
- Author
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Shen, Xueyi, Howard, David M., Adams, Mark J., Hill, W. David, Clarke, Toni-Kim, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, McIntosh, Andrew M., Deary, Ian J., Wray, Naomi R., Ripke, Stephan, Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Agerbo, Esben, Air, Tracy M., Andlauer, Till F. M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, and Beekman, Aartjan T. F.
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ENVIRONMENTAL exposure ,MENTAL health ,GENOMICS ,RISK - Abstract
Depression is a leading cause of worldwide disability but there remains considerable uncertainty regarding its neural and behavioural associations. Here, using non-overlapping Psychiatric Genomics Consortium (PGC) datasets as a reference, we estimate polygenic risk scores for depression (depression-PRS) in a discovery (N = 10,674) and replication (N = 11,214) imaging sample from UK Biobank. We report 77 traits that are significantly associated with depression-PRS, in both discovery and replication analyses. Mendelian Randomisation analysis supports a potential causal effect of liability to depression on brain white matter microstructure (β: 0.125 to 0.868, p
FDR < 0.043). Several behavioural traits are also associated with depression-PRS (β: 0.014 to 0.180, pFDR : 0.049 to 1.28 × 10−14 ) and we find a significant and positive interaction between depression-PRS and adverse environmental exposures on mental health outcomes. This study reveals replicable associations between depression-PRS and white matter microstructure. Our results indicate that white matter microstructure differences may be a causal consequence of liability to depression. Depression is correlated with many brain-related traits. Here, Shen et al. perform phenome-wide association studies of a depression polygenic risk score (PRS) and find associations with 51 behavioural and 26 neuroimaging traits which are further followed up on using Mendelian randomization and mediation analyses. [ABSTRACT FROM AUTHOR]- Published
- 2020
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9. Genome-wide association analysis identifies 13 new risk loci for schizophrenia
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Ripke, Stephan, O'Dushlaine, Colm, Chambert, Kimberly, Moran, Jennifer L, Kähler, Anna K, Akterin, Susanne, Bergen, Sarah E, Collins, Ann L, Crowley, James J, Fromer, Menachem, Kim, Yunjung, Lee, Sang Hong, Magnusson, Patrik KE, Sanchez, Nick, Stahl, Eli A, Williams, Stephanie, Wray, Naomi R, Xia, Kai, Bettella, Francesco, Borglum, Anders D, Bulik-Sullivan, Brendan K, Cormican, Paul, Craddock, Nick, de Leeuw, Christiaan, Durmishi, Naser, Gill, Michael, Golimbet, Vera, Hamshere, Marian L, Holmans, Peter, Hougaard, David M, Kendler, Kenneth S, Lin, Kuang, Morris, Derek W, Mors, Ole, Mortensen, Preben B, Neale, Benjamin M, O'Neill, Francis A, Owen, Michael J, Milovancevic, Milica Pejovic, Posthuma, Danielle, Powell, John, Richards, Alexander L, Riley, Brien P, Ruderfer, Douglas, Rujescu, Dan, Sigurdsson, Engilbert, Silagadze, Teimuraz, Smit, August B, Stefansson, Hreinn, Steinberg, Stacy, Suvisaari, Jaana, Tosato, Sarah, Verhage, Matthijs, Walters, James T, Multicenter Genetic Studies of Schizophrenia Consortium, Levinson, Douglas F, Gejman, Pablo V, Laurent, Claudine, Mowry, Bryan J, O'Donovan, Michael C, Pulver, Ann E, Schwab, Sibylle G, Wildenauer, Dieter B, Dudbridge, Frank, Shi, Jianxin, Albus, Margot, Alexander, Madeline, Campion, Dominique, Cohen, David, Dikeos, Dimitris, Duan, Jubao, Eichhammer, Peter, Godard, Stephanie, Hansen, Mark, Lerer, F Bernard, Liang, Kung-Yee, Maier, Wolfgang, Mallet, Jacques, Nertney, Deborah A, Nestadt, Gerald, Norton, Nadine, Papadimitriou, George N, Ribble, Robert, Sanders, Alan R, Silverman, Jeremy M, Walsh, Dermot, Williams, Nigel M, Wormley, Brandon, Psychosis Endophenotypes International Consortium, Arranz, Maria J, Bakker, Steven, Bender, Stephan, Bramon, Elvira, Collier, David, Crespo-Facorro, Benedicto, Hall, Jeremy, Iyegbe, Conrad, Jablensky, Assen, Kahn, Rene S, Kalaydjieva, Luba, Lawrie, Stephen, Lewis, Cathryn M, Linszen, Don H, Mata, Ignacio, McIntosh, Andrew, Murray, Robin M, Ophoff, Roel A, Van Os, Jim, Walshe, Muriel, Weisbrod, Matthias, Wiersma, Durk, Wellcome Trust Case Control Consortium 2, Donnelly, Peter, Barroso, Ines, Blackwell, Jenefer M, Brown, Matthew A, Casas, Juan P, Corvin, Aiden P, Deloukas, Panos, Duncanson, Audrey, Jankowski, Janusz, Markus, Hugh S, Mathew, Christopher G, Palmer, Colin NA, Plomin, Robert, Rautanen, Anna, Sawcer, Stephen J, Trembath, Richard C, Viswanathan, Ananth C, Wood, Nicholas W, Spencer, Chris CA, Band, Gavin, Bellenguez, Céline, Freeman, Colin, Hellenthal, Garrett, Giannoulatou, Eleni, Pirinen, Matti, Pearson, Richard D, Strange, Amy, Su, Zhan, Vukcevic, Damjan, Langford, Cordelia, Hunt, Sarah E, Edkins, Sarah, Gwilliam, Rhian, Blackburn, Hannah, Bumpstead, Suzannah J, Dronov, Serge, Gillman, Matthew, Gray, Emma, Hammond, Naomi, Jayakumar, Alagurevathi, McCann, Owen T, Liddle, Jennifer, Potter, Simon C, Ravindrarajah, Radhi, Ricketts, Michelle, Tashakkori-Ghanbaria, Avazeh, Waller, Matthew J, Weston, Paul, Widaa, Sara, Whittaker, Pamela, McCarthy, Mark I, Stefansson, Kari, Scolnick, Edward, Purcell, Shaun, McCarroll, Steven A, Sklar, Pamela, Hultman, Christina M, and Sullivan, Patrick F
- Abstract
Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.
- Published
- 2013
10. Improving genetic prediction by leveraging genetic correlations among human diseases and traits.
- Author
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Maier, Robert M., Zhihong Zhu, Sang Hong Lee, Trzaskowski, Maciej, Ruderfer, Douglas M., Stahl, Eli A., Ripke, Stephan, Wray, Naomi R., ian Yang, Visscher, Peter M., and Robinson, Matthew R.
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GENETIC correlations ,TYPE 2 diabetes ,MULTITRAIT multimethod techniques ,INDIVIDUALIZED medicine ,BIPOLAR disorder ,22Q11 deletion syndrome - Abstract
Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7% for height to 47% for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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11. Partitioning heritability by functional annotation using genome-wide association summary statistics.
- Author
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Finucane, Hilary K, Bulik-Sullivan, Brendan, Trynka, Gosia, Anttila, Verneri, Farh, Kyle, Ripke, Stephan, Purcell, Shaun, Okada, Yukinori, Raychaudhuri, Soumya, Daly, Mark J, Neale, Benjamin M, Price, Alkes L, Gusev, Alexander, Loh, Po-Ru, Lindstrom, Sara, Reshef, Yakir, Xu, Han, Zang, Chongzhi, Day, Felix R, and Perry, John R B
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HERITABILITY ,IMMUNOLOGIC diseases ,LINKAGE disequilibrium ,MENARCHE ,SMOKING - Abstract
Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here we analyze a broad set of functional elements, including cell type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits with an average sample size of 73,599. To enable this analysis, we introduce a new method, stratified LD score regression, for partitioning heritability from GWAS summary statistics while accounting for linked markers. This new method is computationally tractable at very large sample sizes and leverages genome-wide information. Our findings include a large enrichment of heritability in conserved regions across many traits, a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers and many cell type-specific enrichments, including significant enrichment of central nervous system cell types in the heritability of body mass index, age at menarche, educational attainment and smoking behavior. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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12. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations.
- Author
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Shah, Tejas, Barrett, Jeffrey C, Daryani, Naser E, B K, Thelma, Orchard, Timothy R, Ng, Siew C, Weersma, Rinse K, Jostins, Luke, Vahedi, Homayon, Juyal, Ramesh C, Midha, Vandana, Ripke, Stephan, Daly, Mark J, Alberts, Rudi, Poustchi, Hossein, Kim, Won Ho, Kubo, Michiaki, Juyal, Garima, Newman, William G, and Franke, Andre
- Subjects
INFLAMMATORY bowel diseases ,GENE frequency ,HLA histocompatibility antigens ,SINGLE nucleotide polymorphisms ,GENETICS - Abstract
Ulcerative colitis and Crohn's disease are the two main forms of inflammatory bowel disease (IBD). Here we report the first trans-ancestry association study of IBD, with genome-wide or Immunochip genotype data from an extended cohort of 86,640 European individuals and Immunochip data from 9,846 individuals of East Asian, Indian or Iranian descent. We implicate 38 loci in IBD risk for the first time. For the majority of the IBD risk loci, the direction and magnitude of effect are consistent in European and non-European cohorts. Nevertheless, we observe genetic heterogeneity between divergent populations at several established risk loci driven by differences in allele frequency (NOD2) or effect size (TNFSF15 and ATG16L1) or a combination of these factors (IL23R and IRGM). Our results provide biological insights into the pathogenesis of IBD and demonstrate the usefulness of trans-ancestry association studies for mapping loci associated with complex diseases and understanding genetic architecture across diverse populations. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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13. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies.
- Author
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Bulik-Sullivan, Brendan K, Daly, Mark J, Neale, Benjamin M, Loh, Po-Ru, Finucane, Hilary K, Ripke, Stephan, Yang, Jian, Patterson, Nick, and Price, Alkes L
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GENOMICS ,LINKAGE disequilibrium ,MONOGENIC & polygenic inheritance (Genetics) ,REGRESSION analysis ,SCHIZOPHRENIA - Abstract
Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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14. High-density mapping of the MHC identifies a shared role for HLA-DRB1*01:03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis.
- Author
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Boucher, Gabrielle, Ellinghaus, Eva, Franke, Andre, Daly, Mark J, Goyette, Philippe, Barrett, Jeffrey C, Schumm, L Philip, Carrington, Mary N, Karlsen, Tom H, Ripke, Stephan, Oksenberg, Jorge R, Leslie, Stephen, McGovern, Dermot P B, Rioux, John D, Mallon, Dermot, Kosmoliaptsis, Vasilis, Thomsen, Ingo, Jostins, Luke, Huang, Hailiang, and Gusareva, Elena S
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INFLAMMATORY bowel disease diagnosis ,INFLAMMATORY bowel diseases ,ULCERATIVE colitis ,MAJOR histocompatibility complex ,HLA histocompatibility antigen genetics ,INTESTINAL diseases ,GENETICS ,DISEASE risk factors - Abstract
Genome-wide association studies of the related chronic inflammatory bowel diseases (IBD) known as Crohn's disease and ulcerative colitis have shown strong evidence of association to the major histocompatibility complex (MHC). This region encodes a large number of immunological candidates, including the antigen-presenting classical human leukocyte antigen (HLA) molecules. Studies in IBD have indicated that multiple independent associations exist at HLA and non-HLA genes, but they have lacked the statistical power to define the architecture of association and causal alleles. To address this, we performed high-density SNP typing of the MHC in >32,000 individuals with IBD, implicating multiple HLA alleles, with a primary role for HLA-DRB1*01:03 in both Crohn's disease and ulcerative colitis. Noteworthy differences were observed between these diseases, including a predominant role for class II HLA variants and heterozygous advantage observed in ulcerative colitis, suggesting an important role of the adaptive immune response in the colonic environment in the pathogenesis of IBD. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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15. Most genetic risk for autism resides with common variation.
- Author
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Gaugler, Trent, Klei, Lambertus, Sanders, Stephan J, Bodea, Corneliu A, Goldberg, Arthur P, Lee, Ann B, Mahajan, Milind, Manaa, Dina, Pawitan, Yudi, Reichert, Jennifer, Ripke, Stephan, Sandin, Sven, Sklar, Pamela, Svantesson, Oscar, Reichenberg, Abraham, Hultman, Christina M, Devlin, Bernie, Roeder, Kathryn, and Buxbaum, Joseph D
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AUTISM spectrum disorders ,ALLELES ,MEDICAL genetics ,PERVASIVE child development disorders ,HUMAN genetics - Abstract
A key component of genetic architecture is the allelic spectrum influencing trait variability. For autism spectrum disorder (herein termed autism), the nature of the allelic spectrum is uncertain. Individual risk-associated genes have been identified from rare variation, especially de novo mutations. From this evidence, one might conclude that rare variation dominates the allelic spectrum in autism, yet recent studies show that common variation, individually of small effect, has substantial impact en masse. At issue is how much of an impact relative to rare variation this common variation has. Using a unique epidemiological sample from Sweden, new methods that distinguish total narrow-sense heritability from that due to common variation and synthesis of results from other studies, we reach several conclusions about autism's genetic architecture: its narrow-sense heritability is ∼52.4%, with most due to common variation, and rare de novo mutations contribute substantially to individual liability, yet their contribution to variance in liability, 2.6%, is modest compared to that for heritable variation. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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16. Gene-gene and gene-environment interactions in ulcerative colitis.
- Author
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Wang, Ming-Hsi, Fiocchi, Claudio, Zhu, Xiaofeng, Ripke, Stephan, Kamboh, M., Rebert, Nancy, Duerr, Richard, and Achkar, Jean-Paul
- Subjects
GENOTYPE-environment interaction ,ULCERATIVE colitis ,INFLAMMATORY bowel diseases ,REGRESSION analysis ,DNA replication ,GENETICS - Abstract
Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene-gene and gene-environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case-Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high-order interactions. Exploratory genotype correlations with UC sub-phenotypes [extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)] were conducted. The combination of 133 UC loci yielded good UC risk predictability [area under the curve (AUC) of 0.86]. A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P = 3.26E−05). Explained UC variance increased from 37 to 42 % after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high-order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene-gene and gene-environment interactions. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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17. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs.
- Author
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Lee, S Hong, Ripke, Stephan, Neale, Benjamin M, Faraone, Stephen V, Purcell, Shaun M, Perlis, Roy H, Mowry, Bryan J, Thapar, Anita, Goddard, Michael E, Witte, John S, Absher, Devin, Agartz, Ingrid, Akil, Huda, Amin, Farooq, Andreassen, Ole A, Anjorin, Adebayo, Anney, Richard, Anttila, Verneri, Arking, Dan E, and Asherson, Philip
- Subjects
- *
MENTAL illness genetics , *PATHOLOGICAL physiology , *SINGLE nucleotide polymorphisms , *HUMAN genetic variation , *ETIOLOGY of diseases , *EMPIRICAL research - Abstract
Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders. [ABSTRACT FROM AUTHOR]
- Published
- 2013
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18. A mega-analysis of genome-wide association studies for major depressive disorder.
- Author
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Ripke, Stephan, Wray, Naomi R, Lewis, Cathryn M, Hamilton, Steven P, Weissman, Myrna M, Breen, Gerome, Byrne, Enda M, Blackwood, Douglas H R, Boomsma, Dorret I, Cichon, Sven, Heath, Andrew C, Holsboer, Florian, Lucae, Susanne, Madden, Pamela A F, Martin, Nicholas G, McGuffin, Peter, Muglia, Pierandrea, Noethen, Markus M, Penninx, Brenda P, and Pergadia, Michele L
- Subjects
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MENTAL depression , *THERAPEUTICS , *X chromosome , *SINGLE nucleotide polymorphisms , *HERITABILITY , *RETINAL degeneration - Abstract
Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10−8), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10−9 at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status. [ABSTRACT FROM AUTHOR]
- Published
- 2013
- Full Text
- View/download PDF
19. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease.
- Author
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Jostins, Luke, Ripke, Stephan, Weersma, Rinse K., Duerr, Richard H., McGovern, Dermot P., Hui, Ken Y., Lee, James C., Philip Schumm, L., Sharma, Yashoda, Anderson, Carl A., Essers, Jonah, Mitrovic, Mitja, Ning, Kaida, Cleynen, Isabelle, Theatre, Emilie, Spain, Sarah L., Raychaudhuri, Soumya, Goyette, Philippe, Wei, Zhi, and Abraham, Clara
- Subjects
- *
INFLAMMATORY bowel diseases , *CROHN'S disease , *ULCERATIVE colitis , *PHENOTYPES , *AUTOPHAGY , *GENETICS - Abstract
Crohn's disease and ulcerative colitis, the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry, with rising prevalence in other populations. Genome-wide association studies and subsequent meta-analyses of these two diseases as separate phenotypes have implicated previously unsuspected mechanisms, such as autophagy, in their pathogenesis and showed that some IBD loci are shared with other inflammatory diseases. Here we expand on the knowledge of relevant pathways by undertaking a meta-analysis of Crohn's disease and ulcerative colitis genome-wide association scans, followed by extensive validation of significant findings, with a combined total of more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci, that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional (consistently favouring one allele over the course of human history) and balancing (favouring the retention of both alleles within populations) selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe considerable overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD. [ABSTRACT FROM AUTHOR]
- Published
- 2012
- Full Text
- View/download PDF
20. Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs.
- Author
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Lee, S Hong, DeCandia, Teresa R, Ripke, Stephan, Yang, Jian, Sullivan, Patrick F, Goddard, Michael E, Keller, Matthew C, Visscher, Peter M, and Wray, Naomi R
- Subjects
DISEASE susceptibility ,SCHIZOPHRENIA ,GENETICS ,GENOMES ,CENTRAL nervous system - Abstract
Schizophrenia is a complex disorder caused by both genetic and environmental factors. Using 9,087 affected individuals, 12,171 controls and 915,354 imputed SNPs from the Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (PGC-SCZ), we estimate that 23% (s.e. = 1%) of variation in liability to schizophrenia is captured by SNPs. We show that a substantial proportion of this variation must be the result of common causal variants, that the variance explained by each chromosome is linearly related to its length (r = 0.89, P = 2.6 × 10
?8 ), that the genetic basis of schizophrenia is the same in males and females, and that a disproportionate proportion of variation is attributable to a set of 2,725 genes expressed in the central nervous system (CNS; P = 7.6 × 10?8 ). These results are consistent with a polygenic genetic architecture and imply more individual SNP associations will be detected for this disease as sample size increases. [ABSTRACT FROM AUTHOR]- Published
- 2012
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21. A rare penetrant mutation in CFH confers high risk of age-related macular degeneration.
- Author
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Raychaudhuri, Soumya, Iartchouk, Oleg, Chin, Kimberly, Tan, Perciliz L, Tai, Albert K, Ripke, Stephan, Gowrisankar, Sivakumar, Vemuri, Soumya, Montgomery, Kate, Yu, Yi, Reynolds, Robyn, Zack, Donald J, Campochiaro, Betsy, Campochiaro, Peter, Katsanis, Nicholas, Daly, Mark J, and Seddon, Johanna M
- Subjects
RETINAL degeneration ,HEMOLYTIC-uremic syndrome ,LIGAND binding (Biochemistry) ,GENETIC mutation ,BIOLOGICAL variation - Abstract
Two common variants in the gene encoding complement factor H (CFH), the Y402H substitution (rs1061170, c.1204C>T) and the intronic rs1410996 SNP, explain 17% of age-related macular degeneration (AMD) liability. However, proof for the involvement of CFH, as opposed to a neighboring transcript, and knowledge of the potential mechanism of susceptibility alleles are lacking. Assuming that rare functional variants might provide mechanistic insights, we used genotype data and high-throughput sequencing to discover a rare, high-risk CFH haplotype with a c.3628C>T mutation that resulted in an R1210C substitution. This allele has been implicated previously in atypical hemolytic uremic syndrome, and it abrogates C-terminal ligand binding. Genotyping R1210C in 2,423 AMD cases and 1,122 controls demonstrated high penetrance (present in 40 cases versus 1 control, P = 7.0 × 10
?6 ) and an association with a 6-year-earlier onset of disease (P = 2.3 × 10?6 ). This result suggests that loss-of-function alleles at CFH are likely to drive AMD risk. This finding represents one of the first instances in which a common complex disease variant has led to the discovery of a rare penetrant mutation. [ABSTRACT FROM AUTHOR]- Published
- 2011
- Full Text
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22. Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease.
- Author
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Rivas, Manuel A, Beaudoin, Mélissa, Gardet, Agnes, Stevens, Christine, Sharma, Yashoda, Zhang, Clarence K, Boucher, Gabrielle, Ripke, Stephan, Ellinghaus, David, Burtt, Noel, Fennell, Tim, Kirby, Andrew, Latiano, Anna, Goyette, Philippe, Green, Todd, Halfvarson, Jonas, Haritunians, Talin, Korn, Joshua M, Kuruvilla, Finny, and Lagacé, Caroline
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INFLAMMATORY bowel diseases ,GENOMICS ,GENOMES ,CROHN'S disease ,ULCERATIVE colitis ,GENETICS - Abstract
More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 × 10
?16 , odds ratio ? 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models. [ABSTRACT FROM AUTHOR]- Published
- 2011
- Full Text
- View/download PDF
23. Genome-wide association study identifies five new schizophrenia loci.
- Author
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Ripke, Stephan, Sanders, Alan R, Kendler, Kenneth S, Levinson, Douglas F, Sklar, Pamela, Holmans, Peter A, Lin, Dan-Yu, Duan, Jubao, Ophoff, Roel A, Andreassen, Ole A, Scolnick, Edward, Cichon, Sven, St. Clair, David, Corvin, Aiden, Gurling, Hugh, Werge, Thomas, Rujescu, Dan, Blackwood, Douglas H R, Pato, Carlos N, and Malhotra, Anil K
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GENETICS of schizophrenia , *REPLICATION (Experimental design) , *TRANSCRIPTION factors , *LOCUS (Genetics) , *GENETICS of bipolar disorder - Abstract
We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10?11) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10?9), ANK3 (rs10994359, P = 2.5 × 10?8) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10?9). [ABSTRACT FROM AUTHOR]
- Published
- 2011
- Full Text
- View/download PDF
24. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4.
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Sklar, Pamela, Ripke, Stephan, Scott, Laura J, Andreassen, Ole A, Cichon, Sven, Craddock, Nick, Edenberg, Howard J, Nurnberger, John I, Rietschel, Marcella, Blackwood, Douglas, Corvin, Aiden, Flickinger, Matthew, Guan, Weihua, Mattingsdal, Morten, McQuillin, Andrew, Kwan, Phoenix, Wienker, Thomas F, Daly, Mark, Dudbridge, Frank, and Holmans, Peter A
- Subjects
- *
GENETICS of bipolar disorder , *GENETICS of schizophrenia , *LOCUS (Genetics) , *CALCIUM channels , *HERITABILITY - Abstract
We conducted a combined genome-wide association study (GWAS) of 7,481 individuals with bipolar disorder (cases) and 9,250 controls as part of the Psychiatric GWAS Consortium. Our replication study tested 34 SNPs in 4,496 independent cases with bipolar disorder and 42,422 independent controls and found that 18 of 34 SNPs had P < 0.05, with 31 of 34 SNPs having signals with the same direction of effect (P = 3.8 × 10?7). An analysis of all 11,974 bipolar disorder cases and 51,792 controls confirmed genome-wide significant evidence of association for CACNA1C and identified a new intronic variant in ODZ4. We identified a pathway comprised of subunits of calcium channels enriched in bipolar disorder association intervals. Finally, a combined GWAS analysis of schizophrenia and bipolar disorder yielded strong association evidence for SNPs in CACNA1C and in the region of NEK4-ITIH1-ITIH3-ITIH4. Our replication results imply that increasing sample sizes in bipolar disorder will confirm many additional loci. [ABSTRACT FROM AUTHOR]
- Published
- 2011
- Full Text
- View/download PDF
25. Novel Genetic Risk Markers for Ulcerative Colitis in the IL2/IL21 Region Are in Epistasis With IL23R and Suggest a Common Genetic Background for Ulcerative Colitis and Celiac Disease.
- Author
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Glas, Jürgen, Stallhofer, Johannes, Ripke, Stephan, Wetzke, Martin, Pfennig, Simone, Klein, Wolfram, Epplen, Jörg T., Griga, Thomas, Schiemann, Uwe, Lacher, Martin, Koletzko, Sibylle, Folwaczny, Matthias, Lohse, Peter, Göke, Burkhard, Ochsenkühn, Thomas, Müller-Myhsok, Bertram, and Brand, Stephan
- Subjects
INFLAMMATORY bowel diseases ,ULCERATIVE colitis ,GENETIC polymorphisms ,CHROMOSOMES ,GENOMES - Abstract
OBJECTIVES:Recently, a genome-wide association study showed that single-nucleotide polymorphisms (SNPs) in the chromosome 4q27 region containing IL2 and IL21 are associated with celiac disease. Given the increased prevalence of inflammatory bowel disease (IBD) among celiac disease patients, we investigated the possible involvement of these SNPs in IBD.METHODS:Five SNPs strongly associated with celiac disease within the KIAA1109/TENR/IL2/IL21 linkage disequilibrium block on chromosome 4q27 and one coding SNP within the IL21 gene were analyzed in a large German IBD cohort. The study population comprised a total of 2,948 Caucasian individuals, including 1,461 IBD patients (ulcerative colitis (UC): n=514, Crohn's disease (CD): n=947) and 1,487 healthy unrelated controls.RESULTS:Three of the five celiac disease risk markers had a protective effect on UC susceptibility, and this effect remained significant after correcting for multiple testing: rs6840978: P=0.0082, P
corr =0.049, odds ratio (OR) 0.77, 95% confidence interval (CI) 0.63–0.93; rs6822844: P=0.0028, Pcorr =0.017, OR 0.73, 95% CI 0.59–0.90; rs13119723: P=0.0058, Pcorr =0.035, OR 0.75, 95% CI 0.61–0.92. A haplotype consisting of the six SNPs tested was markedly associated with UC susceptibility (P=0.0025, Pcorr =0.015, OR 0.72, 95% CI 0.58–0.89). Moreover, in UC, epistasis was observed between the IL23R SNP rs1004819 and three SNPs in the KIAA1109/TENR/IL2/IL21 block (rs13151961, rs13119723, and rs6822844).CONCLUSIONS:Similar to other autoimmune diseases such as celiac disease, rheumatoid arthritis, type 1 diabetes, Graves’ disease, and psoriatic arthritis, genetic variation in the chromosome 4q27 region predisposes to UC, suggesting a common genetic background for these diseases.Am J Gastroenterol 2009; 104:1737–1744; doi:10.1038/ajg.2009.163; published online 19 May 2009 [ABSTRACT FROM AUTHOR]- Published
- 2009
- Full Text
- View/download PDF
26. Genome-wide association study of restless legs syndrome identifies common variants in three genomic regions.
- Author
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Winkelmann, Juliane, Schormair, Barbara, Lichtner, Peter, Ripke, Stephan, Lan Xiong, Jalilzadeh, Shapour, Fulda, Stephany, Pütz, Benno, Eckstein, Gertrud, Hauk, Stephanie, Trenkwalder, Claudia, Zimprich, Alexander, Stiasny-Kolster, Karin, Oertel, Wolfgang, Bachmann, Cornelius G., Paulus, Walter, Peglau, Ines, Eisensehr, Ilonka, Montplaisir, Jacques, and Turecki, Gustavo
- Subjects
RESTLESS legs syndrome ,NERVOUS system abnormalities ,SLEEP disorders ,HOMEOBOX genes ,HUMAN gene mapping ,DEVELOPMENTAL disabilities ,PROTEIN kinases - Abstract
Restless legs syndrome (RLS) is a frequent neurological disorder characterized by an imperative urge to move the legs during night, unpleasant sensation in the lower limbs, disturbed sleep and increased cardiovascular morbidity. In a genome-wide association study we found highly significant associations between RLS and intronic variants in the homeobox gene MEIS1, the BTBD9 gene encoding a BTB(POZ) domain as well as variants in a third locus containing the genes encoding mitogen-activated protein kinase MAP2K5 and the transcription factor LBXCOR1 on chromosomes 2p, 6p and 15q, respectively. Two independent replications confirmed these association signals. Each genetic variant was associated with a more than 50% increase in risk for RLS, with the combined allelic variants conferring more than half of the risk. MEIS1 has been implicated in limb development, raising the possibility that RLS has components of a developmental disorder. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
27. Associations of CFHR1–CFHR3 deletion and a CFH SNP to age-related macular degeneration are not independent.
- Author
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Raychaudhuri, Soumya, Ripke, Stephan, Li, Mingyao, Neale, Benjamin M, Fagerness, Jesen, Reynolds, Robyn, Sobrin, Lucia, Swaroop, Anand, Abecasis, Gonçalo, Seddon, Johanna M, and Daly, Mark J
- Subjects
- *
LETTERS to the editor , *RETINAL degeneration - Abstract
A letter to the editor is presented in response to the article on the association of the common deletion of CFHR1 and CFHR3 genes with lower risk of age-related macular degeneration (AMD) by A. E. Hughes and colleagues in the 2006 issue.
- Published
- 2010
- Full Text
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28. PTPRD (protein tyrosine phosphatase receptor type delta) is associated with restless legs syndrome.
- Author
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Schormair, Barbara, Kemlink, David, Roeske, Darina, Eckstein, Gertrud, Lan Xiong, Lichtner, Peter, Ripke, Stephan, Trenkwalder, Claudia, Zimprich, Alexander, Stiasny-Kolster, Karin, Oertel, Wolfgang, Bachmann, Cornelius G., Paulus, Walter, Högl, Birgit, Frauscher, Birgit, Gschliesser, Viola, Poewe, Werner, Peglau, Ines, Vodicka, Pavel, and Vávrová, Jana
- Subjects
RESTLESS legs syndrome ,PROTEIN-tyrosine phosphatase ,PHENOTYPES ,CENTRAL nervous system ,GENOMES - Abstract
We identified association of restless legs syndrome (RLS) with PTPRD at 9p23–24 in 2,458 affected individuals and 4,749 controls from Germany, Austria, Czechia and Canada. Two independent SNPs in the 5′ UTR of splice variants expressed predominantly in the central nervous system showed highly significant P values (rs4626664, P
nominal/λ corrected = 5.91 × 10−10 , odds ratio (OR) = 1.44; rs1975197, Pnominal/λ corrected = 5.81 × 10−9 , OR = 1.31). This work identifies PTPRD as the fourth genome-wide significant locus for RLS. [ABSTRACT FROM AUTHOR]- Published
- 2008
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- View/download PDF
29. Genome-wide meta-analysis in alopecia areata resolves HLA associations and reveals two new susceptibility loci.
- Author
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Betz, Regina C., Petukhova, Lynn, Ripke, Stephan, Huang, Hailiang, Menelaou, Androniki, Redler, Silke, Becker, Tim, Heilmann, Stefanie, Yamany, Tarek, Duvic, Madeliene, Hordinsky, Maria, Norris, David, Price, Vera H., Mackay-Wiggan, Julian, de Jong, Annemieke, DeStefano, Gina M., Moebus, Susanne, Böhm, Markus, Blume-Peytavi, Ulrike, and Wolff, Hans
- Published
- 2015
- Full Text
- View/download PDF
30. Clozapine-induced agranulocytosis is associated with rare HLA-DQB1 and HLA-B alleles.
- Author
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Goldstein, Jacqueline I., Fredrik Jarskog, L., Hilliard, Chris, Alfirevic, Ana, Duncan, Laramie, Fourches, Denis, Huang, Hailiang, Lek, Monkol, Neale, Benjamin M., Ripke, Stephan, Shianna, Kevin, Szatkiewicz, Jin P., Tropsha, Alexander, van den Oord, Edwin JCG, Cascorbi, Ingolf, Dettling, Michael, Gazit, Ephraim, Goff, Donald C., Holden, Arthur L., and Kelly, Deanna L.
- Published
- 2014
- Full Text
- View/download PDF
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