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Crouse JJ, Park SH, Byrne EM, Mitchell BL, Scott J, Medland SE, Lin T, Wray NR, Martin NG, Hickie IB. Patterns of stressful life events and polygenic scores for five mental disorders and neuroticism among adults with depression. Mol Psychiatry 2024:10.1038/s41380-024-02492-x. [PMID: 38575805 DOI: 10.1038/s41380-024-02492-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 02/08/2024] [Accepted: 02/20/2024] [Indexed: 04/06/2024]
Abstract
The dominant ('general') version of the diathesis-stress theory of depression views stressors and genetic vulnerability as independent risks. In the Australian Genetics of Depression Study (N = 14,146; 75% female), we tested whether polygenic scores (PGS) for major depression, bipolar disorder, schizophrenia, anxiety, ADHD, and neuroticism were associated with reported exposure to 32 childhood, past-year, lifetime, and accumulated stressful life events (SLEs). In false discovery rate-corrected models, the clearest PGS-SLE relationships were for the ADHD- and depression-PGSs, and to a lesser extent, the anxiety- and schizophrenia-PGSs. We describe the associations for childhood and accumulated SLEs, and the 2-3 strongest past-year/lifetime SLE associations. Higher ADHD-PGS was associated with all childhood SLEs (emotional abuse, emotional neglect, physical neglect; ORs = 1.09-1.14; p's < 1.3 × 10-5), more accumulated SLEs, and reported exposure to sudden violent death (OR = 1.23; p = 3.6 × 10-5), legal troubles (OR = 1.15; p = 0.003), and sudden accidental death (OR = 1.14; p = 0.006). Higher depression-PGS was associated with all childhood SLEs (ORs = 1.07-1.12; p's < 0.013), more accumulated SLEs, and severe human suffering (OR = 1.17; p = 0.003), assault with a weapon (OR = 1.12; p = 0.003), and living in unpleasant surroundings (OR = 1.11; p = 0.001). Higher anxiety-PGS was associated with childhood emotional abuse (OR = 1.08; p = 1.6 × 10-4), more accumulated SLEs, and serious accident (OR = 1.23; p = 0.004), physical assault (OR = 1.08; p = 2.2 × 10-4), and transportation accident (OR = 1.07; p = 0.001). Higher schizophrenia-PGS was associated with all childhood SLEs (ORs = 1.12-1.19; p's < 9.3-8), more accumulated SLEs, and severe human suffering (OR = 1.16; p = 0.003). Higher neuroticism-PGS was associated with living in unpleasant surroundings (OR = 1.09; p = 0.007) and major financial troubles (OR = 1.06; p = 0.014). A reversed pattern was seen for the bipolar-PGS, with lower odds of reported physical assault (OR = 0.95; p = 0.014), major financial troubles (OR = 0.93; p = 0.004), and living in unpleasant surroundings (OR = 0.92; p = 0.007). Genetic risk for several mental disorders influences reported exposure to SLEs among adults with moderately severe, recurrent depression. Our findings emphasise that stressors and diatheses are inter-dependent and challenge diagnosis and subtyping (e.g., reactive/endogenous) based on life events.
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Affiliation(s)
- Jacob J Crouse
- Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Shin Ho Park
- Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Enda M Byrne
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
- Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jan Scott
- Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
- Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle, UK
- Norwegian University of Science and Technology, Trondheim, Norway
- Université de Paris, Paris, France
| | - Sarah E Medland
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Tian Lin
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Department of Psychiatry, University of Oxford, Oxford, UK
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Nicholas G Martin
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Ian B Hickie
- Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
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Peyrot WJ, Panagiotaropoulou G, Olde Loohuis LM, Adams MJ, Awasthi S, Ge T, McIntosh AM, Mitchell BL, Mullins N, O'Connell KS, Penninx BWJH, Posthuma D, Ripke S, Ruderfer DM, Uffelmann E, Vilhjalmsson BJ, Zhu Z, Smoller JW, Price AL. Distinguishing different psychiatric disorders using DDx-PRS. medRxiv 2024:2024.02.02.24302228. [PMID: 38352307 PMCID: PMC10862992 DOI: 10.1101/2024.02.02.24302228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/24/2024]
Abstract
Despite great progress on methods for case-control polygenic prediction (e.g. schizophrenia vs. control), there remains an unmet need for a method that genetically distinguishes clinically related disorders (e.g. schizophrenia (SCZ) vs. bipolar disorder (BIP) vs. depression (MDD) vs. control); such a method could have important clinical value, especially at disorder onset when differential diagnosis can be challenging. Here, we introduce a method, Differential Diagnosis-Polygenic Risk Score (DDx-PRS), that jointly estimates posterior probabilities of each possible diagnostic category (e.g. SCZ=50%, BIP=25%, MDD=15%, control=10%) by modeling variance/covariance structure across disorders, leveraging case-control polygenic risk scores (PRS) for each disorder (computed using existing methods) and prior clinical probabilities for each diagnostic category. DDx-PRS uses only summary-level training data and does not use tuning data, facilitating implementation in clinical settings. In simulations, DDx-PRS was well-calibrated (whereas a simpler approach that analyzes each disorder marginally was poorly calibrated), and effective in distinguishing each diagnostic category vs. the rest. We then applied DDx-PRS to Psychiatric Genomics Consortium SCZ/BIP/MDD/control data, including summary-level training data from 3 case-control GWAS ( N =41,917-173,140 cases; total N =1,048,683) and held-out test data from different cohorts with equal numbers of each diagnostic category (total N =11,460). DDx-PRS was well-calibrated and well-powered relative to these training sample sizes, attaining AUCs of 0.66 for SCZ vs. rest, 0.64 for BIP vs. rest, 0.59 for MDD vs. rest, and 0.68 for control vs. rest. DDx-PRS produced comparable results to methods that leverage tuning data, confirming that DDx-PRS is an effective method. True diagnosis probabilities in top deciles of predicted diagnosis probabilities were considerably larger than prior baseline probabilities, particularly in projections to larger training sample sizes, implying considerable potential for clinical utility under certain circumstances. In conclusion, DDx-PRS is an effective method for distinguishing clinically related disorders.
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Meng X, Navoly G, Giannakopoulou O, Levey DF, Koller D, Pathak GA, Koen N, Lin K, Adams MJ, Rentería ME, Feng Y, Gaziano JM, Stein DJ, Zar HJ, Campbell ML, van Heel DA, Trivedi B, Finer S, McQuillin A, Bass N, Chundru VK, Martin HC, Huang QQ, Valkovskaya M, Chu CY, Kanjira S, Kuo PH, Chen HC, Tsai SJ, Liu YL, Kendler KS, Peterson RE, Cai N, Fang Y, Sen S, Scott LJ, Burmeister M, Loos RJF, Preuss MH, Actkins KV, Davis LK, Uddin M, Wani AH, Wildman DE, Aiello AE, Ursano RJ, Kessler RC, Kanai M, Okada Y, Sakaue S, Rabinowitz JA, Maher BS, Uhl G, Eaton W, Cruz-Fuentes CS, Martinez-Levy GA, Campos AI, Millwood IY, Chen Z, Li L, Wassertheil-Smoller S, Jiang Y, Tian C, Martin NG, Mitchell BL, Byrne EM, Awasthi S, Coleman JRI, Ripke S, Sofer T, Walters RG, McIntosh AM, Polimanti R, Dunn EC, Stein MB, Gelernter J, Lewis CM, Kuchenbaecker K. Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference. Nat Genet 2024; 56:222-233. [PMID: 38177345 PMCID: PMC10864182 DOI: 10.1038/s41588-023-01596-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 10/26/2023] [Indexed: 01/06/2024]
Abstract
Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.
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Affiliation(s)
| | | | | | - Daniel F Levey
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Dora Koller
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain
| | - Gita A Pathak
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Nastassja Koen
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - J Michael Gaziano
- Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Dan J Stein
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Heather J Zar
- SAMRC Unit on Child and Adolescent Health, Department of Paediatrics and Child Health, University of Cape Town, Cape Town, South Africa
| | - Megan L Campbell
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | | | - Bhavi Trivedi
- Blizard Institute, Queen Mary University of London, London, UK
| | - Sarah Finer
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | | | - Nick Bass
- Division of Psychiatry, UCL, London, UK
| | | | | | | | | | | | - Susan Kanjira
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Po-Hsiu Kuo
- Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Hsi-Chung Chen
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
- Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan
| | - Shih-Jen Tsai
- Institute of Brain Science and Division of Psychiatry, National Yang-Ming Chiao Tung University, Taipei, Taiwan
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli County, Taiwan
| | | | - Roseann E Peterson
- Department of Psychiatry, VCU, Richmond, VA, USA
- Department of Psychiatry, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Munich, Neuherberg, Germany
- Computational Health Centre, Helmholtz Munich, Neuherberg, Germany
- Department of Medicine, Technical University of Munich, Munich, Germany
| | - Yu Fang
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
| | - Srijan Sen
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Laura J Scott
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Margit Burmeister
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Michael H Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ky'Era V Actkins
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lea K Davis
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Monica Uddin
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Agaz H Wani
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Derek E Wildman
- Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA
| | - Allison E Aiello
- Robert N. Butler Columbia Aging Center, Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Robert J Ursano
- Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Masahiro Kanai
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jill A Rabinowitz
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Brion S Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - George Uhl
- Neurology and Pharmacology, University of Maryland, Maryland VA Healthcare System, Baltimore, MD, USA
| | - William Eaton
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Carlos S Cruz-Fuentes
- Departamento de Genética, Instituto Nacional de Psiquiatría 'Ramón de la Fuente Muñíz', Mexico City, Mexico
| | - Gabriela A Martinez-Levy
- Departamento de Genética, Instituto Nacional de Psiquiatría 'Ramón de la Fuente Muñíz', Mexico City, Mexico
| | - Adrian I Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | | | - Yunxuan Jiang
- Department of Biostatistics, Emory University, Atlanta, GA, USA
- 23andMe, Inc., Mountain View, CA, USA
| | - Chao Tian
- 23andMe, Inc., Mountain View, CA, USA
| | - Nicholas G Martin
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Enda M Byrne
- Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Swapnil Awasthi
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
| | - Jonathan R I Coleman
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Stephan Ripke
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin, Berlin, Germany
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Cambridge, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Institute for Genomics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Renato Polimanti
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare Center, West Haven, CT, USA
| | - Erin C Dunn
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | - Murray B Stein
- Department of Psychiatry, UC San Diego School of Medicine, La Jolla, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity, University of California San Diego, La Jolla, CA, USA
- Psychiatry Service, VA San Diego Healthcare System, San Diego, CA, USA
| | - Joel Gelernter
- Department of Psychiatry, VA CT Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
| | - Cathryn M Lewis
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
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Panagiotaropoulou G, Hellberg KLG, Coleman JRI, Seok D, Kalman J, Mitchell PB, Schofield PR, Forstner AJ, Bauer M, Scott LJ, Pato CN, Pato MT, Li QS, Kirov G, Landén M, Jonsson L, Müller-Myhsok B, Smoller JW, Binder EB, Brückl TM, Czamara D, der Auwera SV, Grabe HJ, Homuth G, Schmidt CO, Potash JB, DePaulo RJ, Goes FS, MacKinnon DF, Mondimore FM, Weissman MM, Shi J, Frye MA, Biernacka JM, Reif A, Witt SH, Kahn RR, Boks MM, Owen MJ, Gordon-Smith K, Mitchell BL, Martin NG, Medland SE, Jones L, Knowles JA, Levinson DF, O'Donovan MC, Lewis CM, Breen G, Werge T, Schork AJ, Ophoff R, Ripke S, Loohuis LO. Identifying genetic differences between bipolar disorder and major depression through multiple GWAS. medRxiv 2024:2024.01.29.24301816. [PMID: 38410442 PMCID: PMC10896417 DOI: 10.1101/2024.01.29.24301816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Background Accurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD). Aims Here, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis. Methods Based on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses. Results While our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD. Conclusions We find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.
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Affiliation(s)
| | - Kajsa-Lotta Georgii Hellberg
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jonathan R I Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK
| | - Darsol Seok
- Department of Psychiatry, University of California, Los Angeles, CA, USA
| | - Janos Kalman
- Institute for Psychiatric Phenomics and Genomics, Ludwig Maximilian University, Munich, Germany
| | - Philip B Mitchell
- Discipline of Psychiatry and Mental Health, School of Medicine and Health, University of New South Wales, Sydney, Australia
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, University of New South Wales, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, University of New South Wales, Australia
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Medical Faculty, Technische Universität Dresden, Dresden, Germany
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Carlos N Pato
- Department of Psychiatry, Rutgers University, Rutgers Health, Piscataway, NJ, USA
| | - Michele T Pato
- Department of Psychiatry, Rutgers University, Rutgers Health, Piscataway, NJ, USA
| | - Qingqin S Li
- Janssen Research and Development, Neuroscience, Titusville, NJ, USA
| | - George Kirov
- Cardiff University, Division of Psychological Medicine and Clinical Neuroscience, Cardiff, UK
| | - Mikael Landén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Lina Jonsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
| | | | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Elisabeth B Binder
- Department Genes and Environment, Max Planck Institute of Psychiatry, Munich
| | - Tanja M Brückl
- Department Genes and Environment, Max Planck Institute of Psychiatry, Munich
| | - Darina Czamara
- Department Genes and Environment, Max Planck Institute of Psychiatry, Munich
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute of Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Carsten O Schmidt
- Institute for Community Medicine, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - James B Potash
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Raymond J DePaulo
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fernando S Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dean F MacKinnon
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Francis M Mondimore
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Myrna M Weissman
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Psychiatry, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, US
- Division of Translational Epidemiology & Mental Health Equity, New York State Psychiatric Institute, New York, NY, US
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Joanna M Biernacka
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Andreas Reif
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Frankfurt, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Frankfurt am Main, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - René R Kahn
- Department of Psychiatry and Behavioral Health System, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Marco M Boks
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
| | | | - Brittany L Mitchell
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nicholas G Martin
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah E Medland
- Mental Health and Neuroscience, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Lisa Jones
- Psychological Medicine, University of Worcester, Worcester, UK
| | - James A Knowles
- Department of Genetics, Rutgers University, Piscataway, NJ, US
| | - Douglas F Levinson
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, US
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
| | - Roel Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- German Center for Mental Health (DZPG), Site Berlin-Potsdam, Germany
| | - Loes Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Genetics and Genomics, University of California Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California Los Angeles, Los Angeles, CA, USA
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5
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Crouse JJ, Park SH, Byrne EM, Mitchell BL, Chan K, Scott J, Medland SE, Martin NG, Wray NR, Hickie IB. Evening chronotypes with depression report poorer outcomes of SSRIs: A survey-based study of self-ratings. Biol Psychiatry 2024:S0006-3223(24)00002-7. [PMID: 38185236 DOI: 10.1016/j.biopsych.2023.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 12/20/2023] [Accepted: 12/28/2023] [Indexed: 01/09/2024]
Abstract
BACKGROUND Preliminary evidence suggests evening chronotype relates to poorer efficacy of selective-serotonin reuptake inhibitors (SSRIs). It is unknown whether this is specific to particular medications, self-rated chronotype, or efficacy. METHODS In the Australian Genetics of Depression Study (N=15,108; 75% female; 18-90 years; 68% with ≥1 other lifetime diagnosis), a survey assessed experiences with 10 antidepressants and the reduced Morningness-Evening Questionnaire; a chronotype polygenic score (PGS) was calculated. Age- and sex-adjusted regression models (Bonferroni-corrected) estimated associations among antidepressants variables ("how well the antidepressant worked" [efficacy], duration of symptom improvement, side effects, discontinuation due to side effects) and self-rated and genetic chronotypes. RESULTS The chronotype-PGS explained 4% of the variance in self-rated chronotype (r=0.21). Higher self-rated eveningness was associated with poorer efficacy of escitalopram (OR=1.04; 95% CI 1.02-1.06; p=0.000035), fluoxetine (OR=1.03; 95% CI 1.01-1.05; p=0.001), sertraline (OR=1.02; 95% CI 1.01-1.04; p=0.0008), and desvenlafaxine (OR=1.03; 95% CI 1.01-1.05; p=0.004), and a profile of increased side effects (80% of those recorded; ORs=0.93-0.98), with 'difficulty getting to sleep' most likely. Self-rated chronotype was not related to duration of improvement or discontinuation due to side effects. The chronotype-PGS was only associated with suicidal thoughts and attempted suicide (self-reported). While our measures are imperfect, and not of circadian phase under controlled conditions, the model coefficients suggest that dysregulation of phenotypic chronotype relative to its genetic proxy was driving relationships with antidepressant outcomes. CONCLUSIONS The idea that variation in circadian factors influences antidepressant responses was supported and encourages exploration of circadian mechanisms of depressive disorders and antidepressant treatments.
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Affiliation(s)
- Jacob J Crouse
- Brain and Mind Centre, The University of Sydney, NSW, Australia.
| | - Shin Ho Park
- Brain and Mind Centre, The University of Sydney, NSW, Australia
| | - Enda M Byrne
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia; Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Karina Chan
- Brain and Mind Centre, The University of Sydney, NSW, Australia
| | - Jan Scott
- Brain and Mind Centre, The University of Sydney, Australia; Institute of Neuroscience, Newcastle University, United Kingdom
| | - Sarah E Medland
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Naomi R Wray
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom; Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Ian B Hickie
- Brain and Mind Centre, The University of Sydney, NSW, Australia
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6
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Reyes-Pérez P, García-Marín LM, Aman AM, Antar T, Flores-Ocampo V, Mitchell BL, Medina-Rivera A, Rentería ME. Investigating the Shared Genetic Etiology Between Parkinson's Disease and Depression. J Parkinsons Dis 2024; 14:483-493. [PMID: 38457145 DOI: 10.3233/jpd-230176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/09/2024]
Abstract
Background Depression is a common symptom in Parkinson's disease (PD), resulting from underlying neuropathological processes and psychological factors. However, the extent to which shared genetic risk factors contribute to the relationship between depression and PD is poorly understood. Objective To examine the effects of common genetic variants influencing the etiology of PD and depression risk at the genome-wide and local genomic regional level. Methods We comprehensively investigated the genetic relationship between PD and depression using genome-wide association studies data. First, we estimated the genetic correlation at the genome-wide level using linkage-disequilibrium score regression, followed by local genetic correlation analysis using the GWAS-pairwise method and functional annotation to identify genes that may jointly influence the risk for both traits. Also, we performed Latent Causal Variable, Latent Heritable Confounder Mendelian Randomization, and traditional Mendelian Randomization analyses to investigate the potential causal relationship. Results Although the genetic correlation between PD and depression was not statistically significant at the genome-wide level, GWAS-pairwise analyses identified 16 genomic segments associated with PD and depression, implicating nine genes. Further analyses revealed distinct patterns within individual genes, suggesting an intricate pattern. These genes involve various biological processes, including neurotransmitter regulation, senescence, and nucleo-cytoplasmic transport mechanisms. We did not observe genetic evidence of causality between PD and depression. Conclusions Our findings did not support a genome-wide genetic correlation or a causal association between both conditions. However, we identified genomic segments but identified genomic segments linked to distinct biological pathways influencing their etiology.Further research is needed to understand their functional consequences.
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Affiliation(s)
- Paula Reyes-Pérez
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Luis M García-Marín
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Asma M Aman
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Tarek Antar
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Victor Flores-Ocampo
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
- Licenciatura en Ciencias Genómicas, Escuela Nacional de Estudios Superiores Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Brittany L Mitchell
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Alejandra Medina-Rivera
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Miguel E Rentería
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD,Australia
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7
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Gomez LM, Mitchell BL, McAloney K, Adsett J, Garden N, Wood M, Diaz-Torres S, Garcia-Marin LM, Breakspear M, Martin NG, Lupton MK. The Effect of Genetic Predisposition to Alzheimer's Disease and Related Traits on Recruitment Bias in a Study of Cognitive Aging. Twin Res Hum Genet 2023; 26:209-214. [PMID: 37476981 DOI: 10.1017/thg.2023.26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
The recruitment of participants for research studies may be subject to bias. The Prospective Imaging Study of Ageing (PISA) aims to characterize the phenotype and natural history of healthy adult Australians at high future risk of Alzheimer's disease (AD). Participants approached to take part in PISA were selected from existing cohort studies with available genomewide genetic data for both successfully and unsuccessfully recruited participants, allowing us to investigate the genetic contribution to voluntary recruitment, including the genetic predisposition to AD. We use a polygenic risk score (PRS) approach to test to what extent the genetic risk for AD, and related risk factors predict participation in PISA. We did not identify a significant association of genetic risk for AD with study participation, but we did identify significant associations with PRS for key causal risk factors for AD, IQ, household income and years of education. We also found that older and female participants were more likely to take part in the study. Our findings highlight the importance of considering bias in key risk factors for AD in the recruitment of individuals for cohort studies.
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Affiliation(s)
- Lina M Gomez
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jessica Adsett
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Natalie Garden
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Madeline Wood
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Santiago Diaz-Torres
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Luis M Garcia-Marin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Michael Breakspear
- School of Psychological Sciences, The University of Newcastle, Newcastle, New South Wales, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Michelle K Lupton
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Queensland, Australia
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8
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García-Marín LM, Reyes-Pérez P, Diaz-Torres S, Medina-Rivera A, Martin NG, Mitchell BL, Rentería ME. Shared molecular genetic factors influence subcortical brain morphometry and Parkinson's disease risk. NPJ Parkinsons Dis 2023; 9:73. [PMID: 37164954 PMCID: PMC10172359 DOI: 10.1038/s41531-023-00515-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 04/28/2023] [Indexed: 05/12/2023] Open
Abstract
Parkinson's disease (PD) is a late-onset and genetically complex neurodegenerative disorder. Here we sought to identify genes and molecular pathways underlying the associations between PD and the volume of ten brain structures measured through magnetic resonance imaging (MRI) scans. We leveraged genome-wide genetic data from several cohorts, including the International Parkinson's Disease Genomics Consortium (IPDG), the UK Biobank, the Adolescent Brain Cognitive Development (ABCD) study, the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), the Enhancing Neuroimaging Genetics through Meta-Analyses (ENIGMA), and 23andMe. We observed significant positive genetic correlations between PD and intracranial and subcortical brain volumes. Genome-wide association studies (GWAS) - pairwise analyses identified 210 genomic segments with shared aetiology between PD and at least one of these brain structures. Pathway enrichment results highlight potential links with chronic inflammation, the hypothalamic-pituitary-adrenal pathway, mitophagy, disrupted vesicle-trafficking, calcium-dependent, and autophagic pathways. Investigations for putative causal genetic effects suggest that a larger putamen volume could influence PD risk, independently of the potential causal genetic effects of intracranial volume (ICV) on PD. Our findings suggest that genetic variants influencing larger intracranial and subcortical brain volumes, possibly during earlier stages of life, influence the risk of developing PD later in life.
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Affiliation(s)
- Luis M García-Marín
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
- Laboratorio Internacional de Investigación del Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México.
| | - Paula Reyes-Pérez
- Laboratorio Internacional de Investigación del Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Santiago Diaz-Torres
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Alejandra Medina-Rivera
- Laboratorio Internacional de Investigación del Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Nicholas G Martin
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Miguel E Rentería
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
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9
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Campos AI, Ingold N, Huang Y, Mitchell BL, Kho PF, Han X, García-Marín LM, Ong JS, Law MH, Yokoyama JS, Martin NG, Dong X, Cuellar-Partida G, MacGregor S, Aslibekyan S, Rentería ME. Discovery of genomic loci associated with sleep apnea risk through multi-trait GWAS analysis with snoring. Sleep 2023; 46:6918774. [PMID: 36525587 PMCID: PMC9995783 DOI: 10.1093/sleep/zsac308] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 11/11/2022] [Indexed: 12/23/2022] Open
Abstract
STUDY OBJECTIVES Despite its association with severe health conditions, the etiology of sleep apnea (SA) remains understudied. This study sought to identify genetic variants robustly associated with SA risk. METHODS We performed a genome-wide association study (GWAS) meta-analysis of SA across five cohorts (NTotal = 523 366), followed by a multi-trait analysis of GWAS (multi-trait analysis of genome-wide association summary statistics [MTAG]) to boost power, leveraging the high genetic correlation between SA and snoring. We then adjusted our results for the genetic effects of body mass index (BMI) using multi-trait-based conditional and joint analysis (mtCOJO) and sought replication of lead hits in a large cohort of participants from 23andMe, Inc (NTotal = 1 477 352; Ncases = 175 522). We also explored genetic correlations with other complex traits and performed a phenome-wide screen for causally associated phenotypes using the latent causal variable method. RESULTS Our SA meta-analysis identified five independent variants with evidence of association beyond genome-wide significance. After adjustment for BMI, only one genome-wide significant variant was identified. MTAG analyses uncovered 49 significant independent loci associated with SA risk. Twenty-nine variants were replicated in the 23andMe GWAS adjusting for BMI. We observed genetic correlations with several complex traits, including multisite chronic pain, diabetes, eye disorders, high blood pressure, osteoarthritis, chronic obstructive pulmonary disease, and BMI-associated conditions. CONCLUSION Our study uncovered multiple genetic loci associated with SA risk, thus increasing our understanding of the etiology of this condition and its relationship with other complex traits.
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Affiliation(s)
- Adrian I Campos
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Nathan Ingold
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | | | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Pik-Fang Kho
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Xikun Han
- Program in Genetic Epidemiology and Statistical Genetics, Harvard University T.H. Chan School of Public Health, Boston, MA, USA
| | - Luis M García-Marín
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Jue-Sheng Ong
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - Matthew H Law
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Jennifer S Yokoyama
- Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA.,Weill Institute of Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | | | - Xianjun Dong
- Genomics and Bioinformatics Hub, Brigham and Women's Hospital, Boston, MA, USA.,Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - Miguel E Rentería
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
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10
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Thorp JG, Mitchell BL, Gerring ZF, Ong J, Gharahkhani P, Derks EM, Lupton MK. Genetic evidence that the causal association of educational attainment with reduced risk of Alzheimer’s disease is driven by intelligence. Alzheimers Dement 2022. [DOI: 10.1002/alz.061144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Jackson G Thorp
- The University of Queensland Brisbane QLD Australia
- QIMR Berghofer Medical Research Institute Brisbane QLD Australia
| | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute Brisbane QLD Australia
- Queensland University of Technology Brisbane QLD Australia
| | | | - Jue‐Sheng Ong
- QIMR Berghofer Medical Research Institute Brisbane QLD Australia
| | - Puya Gharahkhani
- QIMR Berghofer Medical Research Institute Brisbane QLD Australia
| | - Eske M Derks
- QIMR Berghofer Medical Research Institute Brisbane QLD Australia
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11
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Tielbeek JJ, Uffelmann E, Williams BS, Colodro-Conde L, Gagnon É, Mallard TT, Levitt BE, Jansen PR, Johansson A, Sallis HM, Pistis G, Saunders GRB, Allegrini AG, Rimfeld K, Konte B, Klein M, Hartmann AM, Salvatore JE, Nolte IM, Demontis D, Malmberg ALK, Burt SA, Savage JE, Sugden K, Poulton R, Harris KM, Vrieze S, McGue M, Iacono WG, Mota NR, Mill J, Viana JF, Mitchell BL, Morosoli JJ, Andlauer TFM, Ouellet-Morin I, Tremblay RE, Côté SM, Gouin JP, Brendgen MR, Dionne G, Vitaro F, Lupton MK, Martin NG, Castelao E, Räikkönen K, Eriksson JG, Lahti J, Hartman CA, Oldehinkel AJ, Snieder H, Liu H, Preisig M, Whipp A, Vuoksimaa E, Lu Y, Jern P, Rujescu D, Giegling I, Palviainen T, Kaprio J, Harden KP, Munafò MR, Morneau-Vaillancourt G, Plomin R, Viding E, Boutwell BB, Aliev F, Dick DM, Popma A, Faraone SV, Børglum AD, Medland SE, Franke B, Boivin M, Pingault JB, Glennon JC, Barnes JC, Fisher SE, Moffitt TE, Caspi A, Polderman TJC, Posthuma D. Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis. Mol Psychiatry 2022; 27:4453-4463. [PMID: 36284158 PMCID: PMC10902879 DOI: 10.1038/s41380-022-01793-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 08/03/2022] [Accepted: 09/09/2022] [Indexed: 01/14/2023]
Abstract
Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg = -0.58, father's age at death rg = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.
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Affiliation(s)
- Jorim J Tielbeek
- Center for Neurogenomics and Cognitive Research, Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands.
| | - Emil Uffelmann
- Center for Neurogenomics and Cognitive Research, Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - Benjamin S Williams
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, 2020 West Main Street, Durham, NC, 27705, USA
| | - Lucía Colodro-Conde
- Psychiatric Genetics, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia
| | - Éloi Gagnon
- Research Unit on Children's Psychosocial Maladjustment, École de psychologie, Université Laval, 2523 Allée des Bibliothèques, Quebec City, QC, G1V 0A6, Canada
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brandt E Levitt
- Carolina Population Center, University of North Carolina at Chapel Hill, 123 Franklin St, Chapel Hill, NC, 27516, USA
| | - Philip R Jansen
- Center for Neurogenomics and Cognitive Research, Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - Ada Johansson
- Department of Psychology, Faculty of Arts, Psychology, and Theology, Åbo Akademi University, Tuomiokirkontori 3, FI-20500, Turku, Finland
| | - Hannah M Sallis
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield Road, Bristol, BS8 2BN, UK
| | - Giorgio Pistis
- Center for Psychiatric Epidemiology and Psychopathology, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Route de Cery 25, CH-1008, Prilly, Vaud, Switzerland
| | - Gretchen R B Saunders
- Department of Psychology, University of Minnesota, 75 E. River Road, Minneapolis, MN, 55455, USA
| | - Andrea G Allegrini
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, DeCrespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, DeCrespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Bettina Konte
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Marieke Klein
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Geert Groteplein 10, 6500 HB, Nijmegen, The Netherlands
| | - Annette M Hartmann
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Jessica E Salvatore
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - Ditte Demontis
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000, Aarhus C, Aarhus, Denmark
| | - Anni L K Malmberg
- Department of Psychology and Logopedics, University of Helsinki, Haartmaninkatu 3, 00014, Helsinki, Finland
| | | | - Jeanne E Savage
- Center for Neurogenomics and Cognitive Research, Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
| | - Karen Sugden
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, 2020 West Main Street, Durham, NC, 27705, USA
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, Dunedin, New Zealand
| | - Kathleen Mullan Harris
- Department of Sociology, University of North Carolina at Chapel Hill, CB# 3210, 201 Hamilton Hall, Chapel Hill, NC, 27599, USA
| | - Scott Vrieze
- Department of Psychology, University of Minnesota, 75 E. River Road, Minneapolis, MN, 55455, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, 75 E. River Road, Minneapolis, MN, 55455, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, 75 E. River Road, Minneapolis, MN, 55455, USA
| | - Nina Roth Mota
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Geert Groteplein 10, 6500 HB, Nijmegen, The Netherlands
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Joana F Viana
- The Institute of Metabolism and Systems Research (IMSR), University of Birmingham, Edgbaston, Birmingham, UK
| | - Brittany L Mitchell
- Genetic Epidemiology, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia
| | - Jose J Morosoli
- Psychiatric Genetics, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia
| | - Till F M Andlauer
- Department of Neurology, Technical University of Munich, 22 Ismaninger St., 81675, Munich, Germany
| | - Isabelle Ouellet-Morin
- Research Unit on Children's Psychosocial Maladjustment, École de criminologie, Université of Montreal, 3150 Rue Jean-Brillant, Montreal, QC, H3T 1N8, Canada
| | - Richard E Tremblay
- Research Unit on Children's Psychosocial Maladjustment, Département de pédiatrie et de psychologie, University of Montreal, 90 Avenue Vincent d'Indy, Montreal, QC, H2V 2S9, Canada
| | - Sylvana M Côté
- Research Unit on Children's Psychosocial Maladjustment, CHU Ste-Justine Research Center and Department of Social and Preventive Medicine, University of Montreal, 3175 Chemin de la Côte Ste-Catherine, Montreal, QC, H3T 1C5, Canada
| | - Jean-Philippe Gouin
- Department of Psychology, Concordia University, 7141 Sherbrooke St. West, Montreal, QC, H4B 1R6, Canada
| | - Mara R Brendgen
- Research Unit on Children's Psychosocial Maladjustment, Département de psychologie, Université du Québec à Montréal, CP 8888 succursale Centre-ville, Montreal, QC, H3C 3P8, Canada
| | - Ginette Dionne
- Research Unit on Children's Psychosocial Maladjustment, École de psychologie, Université Laval, 2523 Allée des Bibliothèques, Quebec City, QC, G1V 0A6, Canada
| | - Frank Vitaro
- Research Unit on Children's Psychosocial Maladjustment, CHU Sainte-Justine Research Center and University of Montreal, 3175 Chemin de la Côte Ste-Catherine, Montreal, QC, H3T 1C5, Canada
| | - Michelle K Lupton
- Genetic Epidemiology, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia
| | - Nicholas G Martin
- Genetic Epidemiology, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia
| | - Enrique Castelao
- Center for Psychiatric Epidemiology and Psychopathology, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Route de Cery 25, CH-1008, Prilly, Vaud, Switzerland
| | - Katri Räikkönen
- Department of Psychology and Logopedics, University of Helsinki, Haartmaninkatu 3, 00014, Helsinki, Finland
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Tukholmankatu 8 B, Helsinki, Finland
| | - Jari Lahti
- Department of Psychology and Logopedics, University of Helsinki, Haartmaninkatu 3, 00014, Helsinki, Finland
| | - Catharina A Hartman
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | - Hexuan Liu
- School of Criminal Justice, University of Cincinnati, 2840 Bearcat Way, Cincinnati, OH, 45221, USA
| | - Martin Preisig
- Center for Psychiatric Epidemiology and Psychopathology, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Route de Cery 25, CH-1008, Prilly, Vaud, Switzerland
| | - Alyce Whipp
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, PO Box 4, (Yliopistonkatu 3), 00014, Helsinki, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, PO Box 4, (Yliopistonkatu 3), 00014, Helsinki, Finland
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
| | - Patrick Jern
- Department of Psychology, Faculty of Arts, Psychology, and Theology, Åbo Akademi University, Tuomiokirkontori 3, FI-20500, Turku, Finland
| | - Dan Rujescu
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Ina Giegling
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, PO Box 4, (Yliopistonkatu 3), 00014, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, PO Box 4, (Yliopistonkatu 3), 00014, Helsinki, Finland
| | - Kathryn Paige Harden
- Department of Psychology and Population Research Center, University of Texas at Austin, 108 E Dean Keeton Stop #A8000, Austin, TX, 78712, USA
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield Road, Bristol, BS8 2BN, UK
| | - Geneviève Morneau-Vaillancourt
- Research Unit on Children's Psychosocial Maladjustment, École de psychologie, Université Laval, 2523 Allée des Bibliothèques, Quebec City, QC, G1V 0A6, Canada
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, DeCrespigny Park, Denmark Hill, London, SE5 8AF, UK
| | - Essi Viding
- Division of Psychology and Language Sciences, University College London, London, UK
| | - Brian B Boutwell
- School of Applied Sciences, University of Mississippi, John D. Bower School of Population Health, University of Mississippi Medical Center, 84 Dormitory Row West, University, MS, 38677, USA
| | - Fazil Aliev
- Department of Psychology, Virginia Commonwealth University, Box 842018, 806W Franklin St, Richmond, VA, 23284, USA
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, Box 842018, 806W Franklin St, Richmond, VA, 23284, USA
| | - Arne Popma
- Amsterdam UMC, VKC Psyche, Child and Adolescent Psychiatry & Psychosocial Care, Amsterdam, The Netherlands
| | - Stephen V Faraone
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Anders D Børglum
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, 8000, Aarhus C, Aarhus, Denmark
| | - Sarah E Medland
- Psychiatric Genetics, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaivour, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Michel Boivin
- Research Unit on Children's Psychosocial Maladjustment, École de psychologie, Université Laval, 2523 Allée des Bibliothèques, Quebec City, QC, G1V 0A6, Canada
| | - Jean-Baptiste Pingault
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Jeffrey C Glennon
- Conway Institute of Biomolecular and Biomedical Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - J C Barnes
- School of Criminal Justice, University of Cincinnati, 2840 Bearcat Way, Cincinnati, OH, 45221, USA
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Wundtlaan 1, 6525 XD, Nijmegen, The Netherlands
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, 2020 West Main Street, Durham, NC, 27705, USA
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, 2020 West Main Street, Durham, NC, 27705, USA
| | - Tinca J C Polderman
- Amsterdam UMC, VKC Psyche, Child and Adolescent Psychiatry & Psychosocial Care, Amsterdam, The Netherlands
| | - Danielle Posthuma
- Center for Neurogenomics and Cognitive Research, Department of Complex Trait Genetics, Vrije Universiteit Amsterdam, De Boelelaan 1105, 1081 HV, Amsterdam, The Netherlands
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12
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Mitchell BL, Hansell NK, McAloney K, Martin NG, Wright MJ, Renteria ME, Grasby KL. Polygenic influences associated with adolescent cognitive skills. Intelligence 2022. [DOI: 10.1016/j.intell.2022.101680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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13
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Thorp JG, Mitchell BL, Gerring ZF, Ong JS, Gharahkhani P, Derks EM, Lupton MK. Genetic evidence that the causal association of educational attainment with reduced risk of Alzheimer's disease is driven by intelligence. Neurobiol Aging 2022; 119:127-135. [DOI: 10.1016/j.neurobiolaging.2022.07.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 07/23/2022] [Accepted: 07/27/2022] [Indexed: 10/31/2022]
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14
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Crouse JJ, Ho N, Scott J, Parker R, Park SH, Couvy-Duchesne B, Mitchell BL, Byrne EM, Hermens DF, Medland SE, Martin NG, Gillespie NA, Hickie IB. Dynamic networks of psychological symptoms, impairment, substance use, and social support: The evolution of psychopathology among emerging adults. Eur Psychiatry 2022; 65:e32. [PMID: 35694845 PMCID: PMC9280922 DOI: 10.1192/j.eurpsy.2022.23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Subthreshold/attenuated syndromes are established precursors of full-threshold mood and psychotic disorders. Less is known about the individual symptoms that may precede the development of subthreshold syndromes and associated social/functional outcomes among emerging adults. METHODS We modeled two dynamic Bayesian networks (DBN) to investigate associations among self-rated phenomenology and personal/lifestyle factors (role impairment, low social support, and alcohol and substance use) across the 19Up and 25Up waves of the Brisbane Longitudinal Twin Study. We examined whether symptoms and personal/lifestyle factors at 19Up were associated with (a) themselves or different items at 25Up, and (b) onset of a depression-like, hypo-manic-like, or psychotic-like subthreshold syndrome (STS) at 25Up. RESULTS The first DBN identified 11 items that when endorsed at 19Up were more likely to be reendorsed at 25Up (e.g., hypersomnia, impaired concentration, impaired sleep quality) and seven items that when endorsed at 19Up were associated with different items being endorsed at 25Up (e.g., earlier fatigue and later role impairment; earlier anergia and later somatic pain). In the second DBN, no arcs met our a priori threshold for inclusion. In an exploratory model with no threshold, >20 items at 19Up were associated with progression to an STS at 25Up (with lower statistical confidence); the top five arcs were: feeling threatened by others and a later psychotic-like STS; increased activity and a later hypo-manic-like STS; and anergia, impaired sleep quality, and/or hypersomnia and a later depression-like STS. CONCLUSIONS These probabilistic models identify symptoms and personal/lifestyle factors that might prove useful targets for indicated preventative strategies.
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Affiliation(s)
- Jacob J Crouse
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Nicholas Ho
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Jan Scott
- Academic Psychiatry, Institute of Neuroscience, Newcastle University, Newcastle, United Kingdom.,Université de Paris, Paris, France.,Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Richard Parker
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Shin Ho Park
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Baptiste Couvy-Duchesne
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.,Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.,Paris Brain Institute (ICM), INSERM U 1127, CNRS UMR 7225, Sorbonne University, Inria, Aramis Project-Team, 75013Paris, France
| | | | - Enda M Byrne
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Daniel F Hermens
- Thompson Institute, University of the Sunshine Coast, Birtinya, Queensland, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Ian B Hickie
- Youth Mental Health & Technology Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
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15
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Bivol S, Mellick GD, Gratten J, Parker R, Mulcahy A, Mosley PE, Poortvliet PC, Campos AI, Mitchell BL, Garcia-Marin LM, Cross S, Ferguson M, Lind PA, Loesch DZ, Visscher PM, Medland SE, Scherzer CR, Martin NG, Rentería ME. Australian Parkinson's Genetics Study (APGS): pilot (n=1532). BMJ Open 2022; 12:e052032. [PMID: 35217535 PMCID: PMC8883215 DOI: 10.1136/bmjopen-2021-052032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 01/31/2022] [Indexed: 11/04/2022] Open
Abstract
PURPOSE Parkinson's disease (PD) is a neurodegenerative disorder associated with progressive disability. While the precise aetiology is unknown, there is evidence of significant genetic and environmental influences on individual risk. The Australian Parkinson's Genetics Study seeks to study genetic and patient-reported data from a large cohort of individuals with PD in Australia to understand the sociodemographic, genetic and environmental basis of PD susceptibility, symptoms and progression. PARTICIPANTS In the pilot phase reported here, 1819 participants were recruited through assisted mailouts facilitated by Services Australia based on having three or more prescriptions for anti-PD medications in their Pharmaceutical Benefits Scheme records. The average age at the time of the questionnaire was 64±6 years. We collected patient-reported information and sociodemographic variables via an online (93% of the cohort) or paper-based (7%) questionnaire. One thousand five hundred and thirty-two participants (84.2%) met all inclusion criteria, and 1499 provided a DNA sample via traditional post. FINDINGS TO DATE 65% of participants were men, and 92% identified as being of European descent. A previous traumatic brain injury was reported by 16% of participants and was correlated with a younger age of symptom onset. At the time of the questionnaire, constipation (36% of participants), depression (34%), anxiety (17%), melanoma (16%) and diabetes (10%) were the most reported comorbid conditions. FUTURE PLANS We plan to recruit sex-matched and age-matched unaffected controls, genotype all participants and collect non-motor symptoms and cognitive function data. Future work will explore the role of genetic and environmental factors in the aetiology of PD susceptibility, onset, symptoms, and progression, including as part of international PD research consortia.
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Affiliation(s)
- Svetlana Bivol
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - George D Mellick
- Griffith Institute for Drug Discovery (GRIDD), Griffith University, Brisbane, QLD, Australia
| | - Jacob Gratten
- Mater Research, Translational Research Institute, Brisbane, QLD, Australia
| | - Richard Parker
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Aoibhe Mulcahy
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Philip E Mosley
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Peter C Poortvliet
- Griffith Institute for Drug Discovery (GRIDD), Griffith University, Brisbane, QLD, Australia
| | - Adrian I Campos
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Luis M Garcia-Marin
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Simone Cross
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Mary Ferguson
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Penelope A Lind
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Danuta Z Loesch
- School of Psychology and Public Health, La Trobe University, Melbourne, VIC, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Psychology, The University of Queensland, Brisbane, QLD, Australia
| | - Clemens R Scherzer
- Center for Advanced Parkinson Research, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Precision Neurology Program, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
- Program in Neuroscience, Harvard Medical School, Boston, MA, USA
| | | | - Miguel E Rentería
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Center for Advanced Parkinson Research, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
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16
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Rabinowitz JA, Campos AI, Ong JS, García-Marín LM, Alcauter S, Mitchell BL, Grasby KL, Cuéllar-Partida G, Gillespie NA, Huhn AS, Martin NG, Thompson PM, Medland SE, Maher BS, Rentería ME. Shared Genetic Etiology between Cortical Brain Morphology and Tobacco, Alcohol, and Cannabis Use. Cereb Cortex 2022; 32:796-807. [PMID: 34379727 PMCID: PMC8841600 DOI: 10.1093/cercor/bhab243] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 06/23/2021] [Accepted: 06/24/2021] [Indexed: 12/13/2022] Open
Abstract
Genome-wide association studies (GWAS) have identified genetic variants associated with brain morphology and substance use behaviors (SUB). However, the genetic overlap between brain structure and SUB has not been well characterized. We leveraged GWAS summary data of 71 brain imaging measures and alcohol, tobacco, and cannabis use to investigate their genetic overlap using linkage disequilibrium score regression. We used genomic structural equation modeling to model a "common SUB genetic factor" and investigated its genetic overlap with brain structure. Furthermore, we estimated SUB polygenic risk scores (PRS) and examined whether they predicted brain imaging traits using the Adolescent Behavior and Cognitive Development (ABCD) study. We identified 8 significant negative genetic correlations, including between (1) alcoholic drinks per week and average cortical thickness, and (2) intracranial volume with age of smoking initiation. We observed 5 positive genetic correlations, including those between (1) insula surface area and lifetime cannabis use, and (2) the common SUB genetic factor and pericalcarine surface area. SUB PRS were associated with brain structure variation in ABCD. Our findings highlight a shared genetic etiology between cortical brain morphology and SUB and suggest that genetic variants associated with SUB may be causally related to brain structure differences.
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Affiliation(s)
- Jill A Rabinowitz
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Adrian I Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Jue-Sheng Ong
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
| | - Luis M García-Marín
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Sarael Alcauter
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro 76230, México
| | - Brittany L Mitchell
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
- School of Biomedical Science, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Queensland 4059, Australia
| | - Katrina L Grasby
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
| | - Gabriel Cuéllar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Queensland 4102, Australia
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Andrew S Huhn
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Baltimore, MD 21205, USA
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA 90007, USA
| | - Sarah E Medland
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
| | - Brion S Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4006, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4072, Australia
- School of Biomedical Science, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Queensland 4059, Australia
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17
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Mitchell BL, Saklatvala JR, Dand N, Hagenbeek FA, Li X, Min JL, Thomas L, Bartels M, Jan Hottenga J, Lupton MK, Boomsma DI, Dong X, Hveem K, Løset M, Martin NG, Barker JN, Han J, Smith CH, Rentería ME, Simpson MA. Genome-wide association meta-analysis identifies 29 new acne susceptibility loci. Nat Commun 2022; 13:702. [PMID: 35132056 PMCID: PMC8821634 DOI: 10.1038/s41467-022-28252-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 01/13/2022] [Indexed: 02/08/2023] Open
Abstract
Acne vulgaris is a highly heritable skin disorder that primarily impacts facial skin. Severely inflamed lesions may leave permanent scars that have been associated with long-term psychosocial consequences. Here, we perform a GWAS meta-analysis comprising 20,165 individuals with acne from nine independent European ancestry cohorts. We identify 29 novel genome-wide significant loci and replicate 14 of the 17 previously identified risk loci, bringing the total number of reported acne risk loci to 46. Using fine-mapping and eQTL colocalisation approaches, we identify putative causal genes at several acne susceptibility loci that have previously been implicated in Mendelian hair and skin disorders, including pustular psoriasis. We identify shared genetic aetiology between acne, hormone levels, hormone-sensitive cancers and psychiatric traits. Finally, we show that a polygenic risk score calculated from our results explains up to 5.6% of the variance in acne liability in an independent cohort.
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Affiliation(s)
- Brittany L Mitchell
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Australia
| | - Jake R Saklatvala
- Department of Medical and Molecular Genetics, King's College London, London, UK
| | - Nick Dand
- Department of Medical and Molecular Genetics, King's College London, London, UK
- Health Data Research UK, London, UK
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health research institute, Amsterdam, The Netherlands
| | - Xin Li
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, US
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, US
| | - Josine L Min
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Laurent Thomas
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health research institute, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health research institute, Amsterdam, The Netherlands
| | - Michelle K Lupton
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health research institute, Amsterdam, The Netherlands
| | - Xianjun Dong
- Genomics and Bioinformatics Hub, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Mari Løset
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Dermatology, Clinic of Orthopaedy, Rheumatology and Dermatology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jonathan N Barker
- St John's Institute of Dermatology, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Jiali Han
- Department of Epidemiology, Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, US
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, US
| | - Catherine H Smith
- St John's Institute of Dermatology, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Australia.
| | - Michael A Simpson
- Department of Medical and Molecular Genetics, King's College London, London, UK.
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18
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Campos AI, Byrne EM, Mitchell BL, Wray NR, Lind PA, Licinio J, Medland SE, Martin NG, Hickie IB, Rentería ME. Impact of CYP2C19 metaboliser status on SSRI response: a retrospective study of 9500 participants of the Australian Genetics of Depression Study. Pharmacogenomics J 2022; 22:130-135. [PMID: 35094016 PMCID: PMC8975743 DOI: 10.1038/s41397-022-00267-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 01/10/2022] [Accepted: 01/11/2022] [Indexed: 01/31/2023]
Abstract
Background Variation within the CYP2C19 gene has been linked to differential metabolism of selective serotonin reuptake inhibitors (SSRIs). Pharmacogenetic recommendations based on the effect of CYP2C19 variants have been made available and are used increasingly by clinical practitioners. Nonetheless, the underlying assumption linking differential metabolism to efficacy or adverse side effects remains understudied. Here, we aim to fill this gap by studying CYP2C19 polymorphisms and inferred metabolism and patient-reported antidepressant response in a sample of 9531 Australian adults who have taken SSRIs. Methods Metaboliser status was inferred for participants based on CYP2C19 alleles. Primary analysis consisted of assessing differences in treatment efficacy and tolerability between normal (reference) and: ultrarapid, rapid, intermediate and poor metabolisers. Results Across medications, poor metabolisers reported a higher efficacy, whereas rapid metabolisers reported higher tolerability. When stratified by drug, associations between metaboliser status and efficacy did not survive multiple testing correction. Intermediate metabolisers were at greater odds of reporting any side effect for sertraline and higher number of side effects across medications and for sertraline. Conclusions The effects between metaboliser status and treatment efficacy, tolerability and side effects were in the expected direction. Our power analysis suggests we would detect moderate to large effects, at least nominally. Reduced power may also be explained by heterogeneity in antidepressant dosages or concomitant medications, which we did not measure. The fact that we identify slower metabolisers to be at higher risk of side effects even without adjusting for clinical titration, and the nominally significant associations consistent with the expected metabolic effects provide new evidence for the link between CYP2C19 metabolism and SSRI response. Nonetheless, longitudinal and interventional designs such as randomized clinical trials that stratify by metaboliser status are necessary to establish the effects of CYP2C19 metabolism on SSRI treatment efficacy or adverse effects.
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Affiliation(s)
- Adrian I Campos
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. .,Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia. .,Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.
| | - Enda M Byrne
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Penelope A Lind
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.,School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Julio Licinio
- Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - Miguel E Rentería
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. .,Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia. .,School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia.
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19
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Arends RM, Pasman JA, Verweij KJ, Derks EM, Gordon SD, Hickie I, Thomas NS, Aliev F, Zietsch BP, Zee MD, Mitchell BL, Martin NG, Dick DM, Gillespie NA, Geus EJ, Boomsma DI, Schellekens AF, Vink JM. Associations between the CADM2 gene, substance use, risky sexual behavior, and self-control: A phenome-wide association study. Addict Biol 2021; 26:e13015. [PMID: 33604983 PMCID: PMC8596397 DOI: 10.1111/adb.13015] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 11/05/2020] [Accepted: 01/15/2021] [Indexed: 01/15/2023]
Abstract
Risky behaviors, such as substance use and unprotected sex, are associated with various physical and mental health problems. Recent genome-wide association studies indicated that variation in the cell adhesion molecule 2 (CADM2) gene plays a role in risky behaviors and self-control. In this phenome-wide scan for risky behavior, it was tested if underlying common vulnerability could be (partly) explained by pleiotropic effects of this gene and how large the effects were. Single nucleotide polymorphism (SNP)-level and gene-level association tests within four samples (25 and Up, Spit for Science, Netherlands Twin Register, and UK Biobank and meta-analyses over all samples (combined sample of 362,018 participants) were conducted to test associations between CADM2, substance- and sex-related risk behaviors, and various measures related to self-control. We found significant associations between the CADM2 gene, various risky behaviors, and different measures of self-control. The largest effect sizes were found for cannabis use, sensation seeking, and disinhibition. Effect sizes ranged from 0.01% to 0.26% for single top SNPs and from 0.07% to 3.02% for independent top SNPs together, with sufficient power observed only in the larger samples and meta-analyses. In the largest cohort, we found indications that risk-taking proneness mediated the association between CADM2 and latent factors for lifetime smoking and regular alcohol use. This study extends earlier findings that CADM2 plays a role in risky behaviors and self-control. It also provides insight into gene-level effect sizes and demonstrates the feasibility of testing mediation. These findings present a good starting point for investigating biological etiological pathways underlying risky behaviors.
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Affiliation(s)
- Rachel M. Arends
- Department of Psychiatry Radboud University Medical Center The Netherlands
- Donders Center for Medical Neuroscience Donders Institute for Brain, Cognition and Behavior The Netherlands
- Tactus Addiction Care The Netherlands
| | - Joëlle A. Pasman
- Behavioural Science Institute Radboud University The Netherlands
| | - Karin J.H. Verweij
- Faculty of Medicine Amsterdam Medical Centre and University of Amsterdam The Netherlands
| | - Eske M. Derks
- Genetic Epidemiology, Statistical Genetics and Translational Neurogenomics Laboratories QIMR Berghofer Medical Research Institute Australia
| | - Scott D. Gordon
- Genetic Epidemiology, Statistical Genetics and Translational Neurogenomics Laboratories QIMR Berghofer Medical Research Institute Australia
| | - Ian Hickie
- Brain and Mind Centre University of Sydney Australia
| | | | - Fazil Aliev
- Faculty of Business Karbük University Turkey
- Department of African American Studies Virginia Commonwealth University Richmond VA USA
| | - Brendan P. Zietsch
- School of Medicine and School of Psychology University of Queensland Australia
| | - Matthijs D. Zee
- Department of Biological Psychology Vrije Universiteit Amsterdam The Netherlands
- Netherlands Twin Register The Netherlands
| | - Brittany L. Mitchell
- Department of Genetics and Computational Biology QIMR Berghofer Medical Research Institute Australia
- School of Biomedical Sciences and Institute of Health and Biomedical Innovation Queensland University of Technology Australia
| | - Nicholas G. Martin
- Genetic Epidemiology, Statistical Genetics and Translational Neurogenomics Laboratories QIMR Berghofer Medical Research Institute Australia
- School of Medicine and School of Psychology University of Queensland Australia
| | - Danielle M. Dick
- Department of Psychology Virginia Commonwealth University Richmond VA USA
| | - Nathan A. Gillespie
- Genetic Epidemiology, Statistical Genetics and Translational Neurogenomics Laboratories QIMR Berghofer Medical Research Institute Australia
- School of Medicine and School of Psychology University of Queensland Australia
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry Virginia Commonwealth University Richmond VA USA
| | - Eco J.C. Geus
- Faculty of Medicine Amsterdam Medical Centre and University of Amsterdam The Netherlands
- Netherlands Twin Register The Netherlands
| | - Dorret I. Boomsma
- Faculty of Medicine Amsterdam Medical Centre and University of Amsterdam The Netherlands
- Department of Biological Psychology Vrije Universiteit Amsterdam The Netherlands
- Netherlands Twin Register The Netherlands
| | - Arnt F.A. Schellekens
- Department of Psychiatry Radboud University Medical Center The Netherlands
- Donders Center for Medical Neuroscience Donders Institute for Brain, Cognition and Behavior The Netherlands
- Nijmegen Institute for Scientist‐Practitioners in Addiction The Netherlands
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20
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Mitchell BL, Thorp JG, Wu Y, Campos AI, Nyholt DR, Gordon SD, Whiteman DC, Olsen CM, Hickie IB, Martin NG, Medland SE, Wray NR, Byrne EM. Polygenic Risk Scores Derived From Varying Definitions of Depression and Risk of Depression. JAMA Psychiatry 2021; 78:1152-1160. [PMID: 34379077 PMCID: PMC8358814 DOI: 10.1001/jamapsychiatry.2021.1988] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies. OBJECTIVE To use a large, well-phenotyped single study of MDD to investigate how different definitions of depression used in genetic studies are associated with estimation of MDD and phenotypes of MDD, using polygenic risk scores (PRSs). DESIGN, SETTING, AND PARTICIPANTS In this case-control polygenic risk score analysis, patients meeting diagnostic criteria for a diagnosis of MDD were drawn from the Australian Genetics of Depression Study, a cross-sectional, population-based study of depression, and controls and patients with self-reported depression were drawn from QSkin, a population-based cohort study. Data analyzed herein were collected before September 2018, and data analysis was conducted from September 10, 2020, to January 27, 2021. MAIN OUTCOME AND MEASURES Polygenic risk scores generated from genome-wide association studies using different definitions of depression were evaluated for estimation of MDD in and within individuals with MDD for an association with age at onset, adverse childhood experiences, comorbid psychiatric and somatic disorders, and current physical and mental health. RESULTS Participants included 12 106 (71% female; mean age, 42.3 years; range, 18-88 years) patients meeting criteria for MDD and 12 621 (55% female; mean age, 60.9 years; range, 43-87 years) control participants with no history of psychiatric disorders. The effect size of the PRS was proportional to the discovery sample size, with the largest study having the largest effect size with the odds ratio for MDD (1.75; 95% CI, 1.73-1.77) per SD of PRS and the PRS derived from ICD-10 codes documented in hospitalization records in a population health cohort having the lowest odds ratio (1.14; 95% CI, 1.12-1.16). When accounting for differences in sample size, the PRS from a genome-wide association study of patients meeting diagnostic criteria for MDD and control participants was the best estimator of MDD, but not in those with self-reported depression, and associations with higher odds ratios with childhood adverse experiences and measures of somatic distress. CONCLUSIONS AND RELEVANCE These findings suggest that increasing sample sizes, regardless of the depth of phenotyping, may be most informative for estimating risk of depression. The next generation of genome-wide association studies should, like the Australian Genetics of Depression Study, have both large sample sizes and extensive phenotyping to capture genetic risk factors for MDD not identified by other definitions of depression.
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Affiliation(s)
- Brittany L. Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, Australia,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia
| | - Jackson G. Thorp
- QIMR Berghofer Medical Research Institute, Brisbane, Australia,Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Yeda Wu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Adrian I. Campos
- QIMR Berghofer Medical Research Institute, Brisbane, Australia,Faculty of Medicine, The University of Queensland, Brisbane, Australia,School of Biomedical Sciences, The University of Queensland, Brisbane, Australia
| | - Dale R. Nyholt
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Australia,Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Australia
| | - Scott D. Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | | | - Ian B. Hickie
- Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | | | | | - Naomi R. Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia,Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Enda M. Byrne
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia,Child Health Research Centre, The University of Queensland, Brisbane, Australia
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21
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van der Laan CM, Morosoli-García JJ, van de Weijer SGA, Colodro-Conde L, Lupton MK, Mitchell BL, McAloney K, Parker R, Burns JM, Hickie IB, Pool R, Hottenga JJ, Martin NG, Medland SE, Nivard MG, Boomsma DI. Continuity of Genetic Risk for Aggressive Behavior Across the Life-Course. Behav Genet 2021; 51:592-606. [PMID: 34390460 PMCID: PMC8390412 DOI: 10.1007/s10519-021-10076-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/23/2021] [Indexed: 11/24/2022]
Abstract
We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N = 13,471) and Australia (N = 5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12-70 years, Australia: 16-73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a 'rolling weights' model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41-70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life.
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Affiliation(s)
- Camiel M van der Laan
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.
- The Netherlands Institute for the Study of Crime and Law Enforcement, Amsterdam, The Netherlands.
| | | | - Steve G A van de Weijer
- The Netherlands Institute for the Study of Crime and Law Enforcement, Amsterdam, The Netherlands
| | | | | | | | - Kerrie McAloney
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Richard Parker
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jane M Burns
- Faculty of Health Sciences, The University of Sydney, Sydney, Australia
| | - Ian B Hickie
- Brain and Mind Centre, University of Sydney, Camperdown, Australia
| | - René Pool
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | | | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Michel G Nivard
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Biological Psychology, Vrije Universiteit, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
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22
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Hwang LD, Mitchell BL, Medland SE, Martin NG, Neale MC, Evans DM. Correction to: The Augmented Classical Twin Design: Incorporating Genome-Wide Identity by Descent Sharing Into Twin Studies in Order to Model Violations of the Equal Environments Assumption. Behav Genet 2021; 51:441-442. [PMID: 34043138 DOI: 10.1007/s10519-021-10065-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Liang-Dar Hwang
- The University of Queensland Diamantina Institute, The University of Queensland, Level 7, 37 Kent St, Brisbane, Australia.,QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.,School of Biomedical Science, Institute of Health and Biomedical Innovation, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.,School of Biomedical Science, Institute of Health and Biomedical Innovation, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Australia
| | - Michael C Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - David M Evans
- The University of Queensland Diamantina Institute, The University of Queensland, Level 7, 37 Kent St, Brisbane, Australia. .,QIMR Berghofer Medical Research Institute, Brisbane, Australia. .,MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK. .,Translational Research Institute, Woolloongabba, QLD, 4102, Australia.
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23
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Fieder M, Mitchell BL, Gordon S, Huber S, Martin NG. Ethnic Identity and Genome Wide Runs of Homozygosity. Behav Genet 2021; 51:405-413. [PMID: 33723681 PMCID: PMC8225526 DOI: 10.1007/s10519-021-10053-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 02/23/2021] [Indexed: 10/25/2022]
Abstract
It is long known that inbreeding increases the detrimental effects of recessive sequence variants in "Runs of Homozygosity" (ROHs). However, although the phenotypic association of ROH has been investigated for a variety of traits, the statistical power of the results often remains limited as a sufficiently high number of cases are available for only a restricted number of traits. In the present study, we aim to analyze the association of runs of homozygosity with the trait "in-group ethnic favoritism". This analysis assumes that if ethnic identity is important for an individual, that individual may tend to marry more frequently within their own group and therefore ROH are expected to increase. We hypothesize that an attitude preferring one's own ethnic group may be associated with a stronger tendency of inbreeding and, as a result, with more and longer ROHs. Accordingly, we investigated the association between the attitude to someone's own ethnicity and ROH, using the Wisconsin Longitudinal data (WLS, total N ~ 9000) as discovery data set and the Brisbane Twin data as replication data set (N ~ 8000). We find that both the number as well as the total length of homozygous segments are significantly positively associated with "in-group ethnic favoritism", independent of the method used for ROH calculation.
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Affiliation(s)
- Martin Fieder
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria. .,Research Centre of Religion and Transformation in Contemporary Society, University of Vienna, Vienna, Austria.
| | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.,Faculty of Health, School of Biomedical Sciences, Queensland University of Technology (QUT), Brisbane, Australia
| | - Scott Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Susanne Huber
- Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria
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24
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Hwang LD, Mitchell BL, Medland SE, Martin NG, Neale MC, Evans DM. The Augmented Classical Twin Design: Incorporating Genome-Wide Identity by Descent Sharing Into Twin Studies in Order to Model Violations of the Equal Environments Assumption. Behav Genet 2021; 51:223-236. [PMID: 33582897 DOI: 10.1007/s10519-021-10044-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 01/21/2021] [Indexed: 01/09/2023]
Abstract
The Classical Twin Method (CTM) compares the similarity of monozygotic (MZ) twins with that of dizygotic (DZ) twins to make inferences about the relative importance of genes and environment in the etiology of individual differences. The design has been applied to thousands of traits across the biomedical, behavioral and social sciences and is arguably the most widely used natural experiment known to science. The fundamental assumption of the CTM is that trait relevant environmental covariation within MZ pairs is the same as that found within DZ pairs, so that zygosity differences in within-pair variance must be due to genetic factors uncontaminated by the environment. This equal environments assumption (EEA) has been, and still is hotly contested, and has been mentioned as a possible contributing factor to the missing heritability conundrum. In this manuscript, we introduce a new model for testing the EEA, which we call the Augmented Classical Twin Design which uses identity by descent (IBD) sharing between DZ twin pairs to estimate separate environmental variance components for MZ and DZ twin pairs, and provides a test of whether these are equal. We show through simulation that given large samples of DZ twin pairs, the model provides unbiased estimates of variance components and valid tests of the EEA under strong assumptions (e.g. no epistatic variance, IBD sharing in DZ twins estimated accurately etc.) which may not hold in reality. Sample sizes in excess of 50,000 DZ twin pairs with genome-wide genetic data are likely to be required in order to detect substantial violations of the EEA with moderate power. Consequently, we recommend that the Augmented Classical Twin Design only be applied to datasets with very large numbers of DZ twin pairs (> 50,000 DZ twin pairs), and given the strong assumptions relating to the absence of epistatic variance, appropriate caution be exercised regarding interpretation of the results.
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Affiliation(s)
- Liang-Dar Hwang
- The University of Queensland Diamantina Institute, The University of Queensland, Level 7, 37 Kent St, Brisbane, Australia.,QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Brittany L Mitchell
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.,School of Biomedical Science, Institute of Health and Biomedical Innovation, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Nicholas G Martin
- QIMR Berghofer Medical Research Institute, Brisbane, Australia.,School of Biomedical Science, Institute of Health and Biomedical Innovation, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Australia
| | - Michael C Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - David M Evans
- The University of Queensland Diamantina Institute, The University of Queensland, Level 7, 37 Kent St, Brisbane, Australia. .,QIMR Berghofer Medical Research Institute, Brisbane, Australia. .,MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK. .,Translational Research Institute, Woolloongabba, QLD, 4102, Australia.
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25
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Mitchell BL, Thorp JG, Evans DM, Nyholt DR, Martin NG, Lupton MK. Exploring the genetic relationship between hearing impairment and Alzheimer's disease. Alzheimers Dement (Amst) 2020; 12:e12108. [PMID: 33005726 PMCID: PMC7517507 DOI: 10.1002/dad2.12108] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 08/21/2020] [Accepted: 08/26/2020] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Hearing loss has been identified as the potentially largest modifiable risk factor for Alzheimer's disease (AD), estimated to account for a similar increase in AD risk as the apolipoprotein E (APOE) gene. METHODS We investigated the genetic relationship between hearing loss and AD, and sought evidence for a causal relationship. RESULTS We found a significant genetic overlap between hearing impairment and AD and a polygenic risk score for AD was able to significantly predict hearing loss in an independent cohort. Additionally, regions of the genome involved in inflammation were identified to be shared between hearing difficulty and AD. However, causality tests found no significant evidence of a causal relationship between these traits in either direction. DISCUSSION Overall, these results show that the relationship between hearing difficulty and AD may, in part, be due to shared genes and immune response pathways between the traits. However, currently available data do not support a causal relationship.
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Affiliation(s)
- Brittany L. Mitchell
- School of Biomedical Science and Institute of Health and Biomedical Innovation, Faculty of HealthQueensland University of Technology (QUT)BrisbaneQueenslandAustralia
- Department of Genetics and Computational BiologyQIMR Berghofer Medical Research InstituteBrisbaneQueenslandAustralia
| | - Jackson G. Thorp
- Department of Genetics and Computational BiologyQIMR Berghofer Medical Research InstituteBrisbaneQueenslandAustralia
- Faculty of MedicineUniversity of QueenslandBrisbaneQueenslandAustralia
| | - David M. Evans
- The University of Queensland Diamantina InstituteThe University of QueenslandBrisbaneQueenslandAustralia
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUnited Kingdom
| | - Dale R. Nyholt
- School of Biomedical Science and Institute of Health and Biomedical Innovation, Faculty of HealthQueensland University of Technology (QUT)BrisbaneQueenslandAustralia
| | - Nicholas G. Martin
- School of Biomedical Science and Institute of Health and Biomedical Innovation, Faculty of HealthQueensland University of Technology (QUT)BrisbaneQueenslandAustralia
- Department of Genetics and Computational BiologyQIMR Berghofer Medical Research InstituteBrisbaneQueenslandAustralia
| | - Michelle K. Lupton
- School of Biomedical Science and Institute of Health and Biomedical Innovation, Faculty of HealthQueensland University of Technology (QUT)BrisbaneQueenslandAustralia
- Department of Genetics and Computational BiologyQIMR Berghofer Medical Research InstituteBrisbaneQueenslandAustralia
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26
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Mitchell BL, Cuéllar-Partida G, Grasby KL, Campos AI, Strike LT, Hwang LD, Okbay A, Thompson PM, Medland SE, Martin NG, Wright MJ, Rentería ME. Educational attainment polygenic scores are associated with cortical total surface area and regions important for language and memory. Neuroimage 2020; 212:116691. [PMID: 32126298 DOI: 10.1016/j.neuroimage.2020.116691] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 02/06/2020] [Accepted: 02/26/2020] [Indexed: 02/01/2023] Open
Abstract
It is well established that higher cognitive ability is associated with larger brain size. However, individual variation in intelligence exists despite brain size and recent studies have shown that a simple unifactorial view of the neurobiology underpinning cognitive ability is probably unrealistic. Educational attainment (EA) is often used as a proxy for cognitive ability since it is easily measured, resulting in large sample sizes and, consequently, sufficient statistical power to detect small associations. This study investigates the association between three global (total surface area (TSA), intra-cranial volume (ICV) and average cortical thickness) and 34 regional cortical measures with educational attainment using a polygenic scoring (PGS) approach. Analyses were conducted on two independent target samples of young twin adults with neuroimaging data, from Australia (N = 1097) and the USA (N = 723), and found that higher EA-PGS were significantly associated with larger global brain size measures, ICV and TSA (R2 = 0.006 and 0.016 respectively, p < 0.001) but not average thickness. At the regional level, we identified seven cortical regions-in the frontal and temporal lobes-that showed variation in surface area and average cortical thickness over-and-above the global effect. These regions have been robustly implicated in language, memory, visual recognition and cognitive processing. Additionally, we demonstrate that these identified brain regions partly mediate the association between EA-PGS and cognitive test performance. Altogether, these findings advance our understanding of the neurobiology that underpins educational attainment and cognitive ability, providing focus points for future research.
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Affiliation(s)
- Brittany L Mitchell
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
| | - Gabriel Cuéllar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Katrina L Grasby
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Adrian I Campos
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Lachlan T Strike
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Liang-Dar Hwang
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sarah E Medland
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nicholas G Martin
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Miguel E Rentería
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
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Mitchell BL. Out of the glass house: Robert Todd Lincoln's crucial decade. Timeline 2001; 5:2-17. [PMID: 11618215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/21/2023]
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Chace DH, DiPerna JC, Mitchell BL, Sgroi B, Hofman LF, Naylor EW. Electrospray tandem mass spectrometry for analysis of acylcarnitines in dried postmortem blood specimens collected at autopsy from infants with unexplained cause of death. Clin Chem 2001; 47:1166-82. [PMID: 11427446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
BACKGROUND Deaths from inherited metabolic disorders may remain undiagnosed after postmortem examination and may be classified as sudden infant death syndrome. Tandem mass spectrometry (MS/MS) may reveal disorders of fatty acid oxidation in deaths of previously unknown cause. METHODS We obtained filter-paper blood from 7058 infants from United States and Canadian Medical Examiners. Acylcarnitine and amino acid profiles were obtained by MS/MS. Specialized interpretation was used to evaluate profiles for disorders of fatty acid, organic acid, and amino acid metabolism. The analyses of postmortem blood specimens were compared with the analyses of bile specimens, newborn blood specimens, and specimens obtained from older infants at risk for metabolic disorders. RESULTS Results on 66 specimens suggested diagnoses of metabolic disorders. The most frequently detected disorders were medium-chain and very-long-chain acyl-CoA dehydrogenase deficiencies (23 and 9 cases, respectively), glutaric acidemia type I and II deficiencies (3 and 8 cases, respectively), carnitine palmitoyl transferase type II/translocase deficiencies (6 cases), severe carnitine deficiency (4 cases), isovaleric acidemia/2-methylbutyryl-CoA dehydrogenase deficiencies (4 cases), and long-chain hydroxyacyl-CoA dehydrogenase/trifunctional protein deficiencies (4 cases). CONCLUSIONS Postmortem metabolic screening can explain deaths in infants and children and provide estimates of the number of infant deaths attributable to inborn errors of metabolism. MS/MS is cost-effective for analysis of postmortem specimens and should be considered for routine use by Medical Examiners and pathologists in unexpected/unknown infant and child death.
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Affiliation(s)
- D H Chace
- Neo Gen Screening, PO Box 219, Bridgeville, PA 15017, USA.
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Shih WJ, Runge VV, Mitchell BL, Pulmano C. Comparison of bone SPECT, magnetic resonance imaging, and computed tomography in the demonstration of vertebral metastases from bronchogenic carcinoma: an autopsy-documented case. Clin Nucl Med 2000; 25:647-9. [PMID: 10944033 DOI: 10.1097/00003072-200008000-00025] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- W J Shih
- Nuclear Medicine Service, Lexington VA Medical Center, 40511, USA.
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Gaweco AS, Mitchell BL, Lucas BA, McClatchey KD, Van Thiel DH. CD40 expression on graft infiltrates and parenchymal CD154 (CD40L) induction in human chronic renal allograft rejection. Kidney Int 1999; 55:1543-52. [PMID: 10201021 DOI: 10.1046/j.1523-1755.1999.00379.x] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
BACKGROUND CD40-CD154 (CD40L) costimulatory signaling plays a pivotal role in the effector mechanisms of transplant graft rejection. In animal models, CD40-CD154 blockade induces long-term graft acceptance concurrent with an absence of chronic rejection (CR) lesions. Given the critical importance of CD40-CD154 interactions in the development of chronic transplant allograft rejection, the relevance of in situ CD40 and CD154 expression was assessed in human chronic renal allograft rejection. METHODS The expression of CD40, CD154, CD68, and T-cell receptor (TCR)alpha/beta was analyzed by immunohistochemistry. Serial cryostat sections of snap-frozen core renal allograft biopsies were obtained from 30 renal transplant patients. Biopsy specimens received diagnoses of CR (N = 23) according to the Banff classification and were compared with controls (N = 7) consisting of stable allografts and normal kidney tissue. RESULTS Striking CD40 staining of graft cellular infiltrates (P = 0.016) was observed in renal allografts with CR compared with controls. The CD40+ cellular infiltrates in CR were predominantly TCR alpha/beta + T cells and some CD68+ macrophages. These findings were contrasted by the low-level CD40 expression detected in glomeruli and tubules of CR and controls. However, glomerular induction of CD154 was observed in CR allografts (P = 0.028) as compared with controls. CD154 immunoreactivity was demonstrated on glomerular endothelial, epithelial, and mesangial cells. Moderate CD154 expression was detected on tubular epithelial cells, and only weak CD154 immunoreactivity was observed on the infiltrates in isolated CR cases. CONCLUSION In human chronic renal allograft rejection, CD40 is expressed on graft-infiltrating cells of the T cell and macrophage compartments. CD154 expression is induced on glomerular and tubular epithelial cells during CR, demonstrating another novel source of CD154 expression. The data substantiate the potential contributory role of an interaction between CD40+ graft-destructive effector T cells and macrophages with CD154+ renal allograft parenchymal cells in the development of chronic renal allograft rejection.
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Affiliation(s)
- A S Gaweco
- Department of Medicine, Loyola University Medical Center, Loyola University Chicago, Maywood, Illinois, USA.
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Gaweco AS, Mitchell BL, Lucas B, McClatchey KD, Van Thiel DH. CD40 upregulation in TCR alpha/beta+ CD68+ cells and parenchymal CD40L induction and associated with NF-kappa B activation in chronic rejecting human renal allografts. Transplant Proc 1999; 31:1359-60. [PMID: 10083602 DOI: 10.1016/s0041-1345(98)02027-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- A S Gaweco
- Department of Medicine, Loyola University Medical Center, Loyola University Chicago, Maywood, IL 60153, USA.
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Oakley BR, Rinehart JE, Mitchell BL, Oakley CE, Carmona C, Gray GL, May GS. Cloning, mapping and molecular analysis of the pyrG (orotidine-5'-phosphate decarboxylase) gene of Aspergillus nidulans. Gene 1987; 61:385-99. [PMID: 3328733 DOI: 10.1016/0378-1119(87)90201-0] [Citation(s) in RCA: 142] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
We have modified the transformation procedures of Ballance et al. [Biochem. Biophys. Res. Commun. 112 (1983) 284-289] to give increased rates of transformation in Aspergillus nidulans. With the modified procedures we have been able to complement pyrG89, a mutation in the orotidine-5'-phosphate decarboxylase gene of A. nidulans, by transformation with a library of wild-type (wt) sequences in pBR329. We have recovered, by marker rescue from one such transformant, a plasmid (pJR15) that carries an A. nidulans sequence that complements pyrG89 efficiently. In three experiments, this plasmid gave an average of 1985 stable transformants/micrograms of transforming DNA. We have analyzed ten of these genetically and by Southern hybridization. In five transformants a single copy of the transforming plasmid had integrated at the pyrG locus, in one transformant several copies of pJR15 had integrated at this locus, in one transformant several copies of the plasmid had integrated into other sites, and in three transformants, the wt allele had apparently replaced the mutant allele with no integration of pBR329 sequences. Sequence and S1 nuclease protection analysis revealed that pJR15 contains a gene that predicts an amino acid sequence with regions of strong homology to the orotidine-5'-phosphate decarboxylases of Neurospora crassa and Saccharomyces cerevisiae. We conclude that this gene is the wt pyrG allele. Finally, we have compared the 5'- and 3'-noncoding sequences and intron splice sequences to other genes of A. nidulans and have mapped the pyrG locus to a region between the fpaB and galD loci on linkage group I.
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Affiliation(s)
- B R Oakley
- Department of Molecular Genetics, Ohio State University, Columbus 43210
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Simon MW, Mitchell BL, O'Connor WN, Noonan JA, Davis CA, Wyatt RJ. Glomerulonephritis, pulmonary hemorrhage and coagulopathy associated with Haemophilus parainfluenzae endocarditis. Pediatr Infect Dis 1985; 4:183-8. [PMID: 3982981 DOI: 10.1097/00006454-198503000-00015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Wyatt RJ, Julian BA, Bhathena DB, Mitchell BL, Holland NH, Malluche HH. Iga nephropathy: presentation, clinical course, and prognosis in children and adults. Am J Kidney Dis 1984; 4:192-200. [PMID: 6475950 DOI: 10.1016/s0272-6386(84)80071-2] [Citation(s) in RCA: 55] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Eighty-two patients, 56 male and 26 female, biopsied since 1972 had IgA nephropathy. At the time of kidney biopsy, 24 patients were children and 58 were adults. In both groups the clinical course was documented in sufficient detail to allow prediction of disease outcome. Twenty-six (45%) of the adult patients had chronic renal insufficiency either at first evaluation or subsequently. Fourteen eventually required chronic hemodialysis. Hypertension as the initial sign of disease was seen more frequently in patients with chronic renal insufficiency. Adult males were more likely to have chronic renal insufficiency. The life table method was used to predict age at initiation of dialysis and kidney survival from date of onset of clinically apparent disease. Thirty-five percent of the male patients were predicted to require dialysis by age 40. Kidney death was predicted at 10 years from onset for 33% of male and 22% of all patients biopsied as adults. While all patients with progressive disease had over 2.0 g/24 h urinary protein excretion at least once, many individuals with serum creatinine concentration below 1.5 mg/dL showed marked fluctuation in degree of proteinuria, often exceeding 2.0 g/24 h. Thus, in some cases, degree of proteinuria was not a reliable predictor of outcome.
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Ellis AR, Mayers DL, Martone WJ, Mitchell BL, Atuk NO, Guerrant RL. Rapidly expanding pulmonary nodule caused by Pittsburgh pneumonia agent. JAMA 1981; 245:1558-9. [PMID: 7009903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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Oleson FB, Mitchell BL, Dipple A, Lieberman MW. Distribution of DNA damage in chromatin and its relation to repair in human cells treated with 7-bromomethylbenz(a) anthracene. Nucleic Acids Res 1979; 7:1343-61. [PMID: 514816 PMCID: PMC342307 DOI: 10.1093/nar/7.5.1343] [Citation(s) in RCA: 36] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
We have examined the relationship between the distribution of DNA damage and repair in chromatin from confluent human fibroblasts treated with the carcinogen 7-bromomethylbenz (a) anthracene. Analysis of staphylococcal nuclease (SN)4 digestion kinetics and gel electrophoresis revealed that more total damage occurs in nucleosome core DNA (approximately 80-85% of chromatin DNA) than in SN sensitive DNA (APPROXIMATELY15-20%). Furthermore, over a 24 hr period, damage is removed at about the same rate from these two regions. In contrast, virtually all of the nucleotides incorporated during repair synthesis are initially SN sensitive even when measured at 12 hr after damage. With time many repair-incorporated nucleotides become SN resistant and coelectrophorese with nucleosome core DNA. To explain these data we propose a model whereby excision repair occurs in both linker and core DNA; however, in core DNA the repair process induces conformational changes resulting in temporarily increased SN sensitivity; subsequently, rearrangement occurs and results in the re-establishment of native or near-native nucleosome conformation and SN resistance.
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Koffsky RM, Litwak RS, Mitchell BL, Jurado RA. A simple left heart assist device for use after intracardiac surgery: development, deployment and clinical experience. Artif Organs 1978; 2:257-62. [PMID: 708287 DOI: 10.1111/j.1525-1594.1978.tb03462.x] [Citation(s) in RCA: 19] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
A simple left heart assist device (LHAD) has been developed and employed in nineteen patients with severe left ventricular dysfunction who could not be weaned from cardiopulmonary bypass following intracardiac surgery. It has been used when all other means of weaning, including maximum pharmacologic therapy and intra-aortic balloon counterpulsation (IABC), had failed. The device utilizes specially designed and constructed obturated cannulae in the left atrium and the ascending aorta, and an extracorporeal roller pump to partially bypass the left ventricle. With improved cardiac performance, the patient may be separated from the device without need for thoracic reentry. Of the nineteen patients having LHAD support (2-500 hours), thirteen were eventually weaned from the device and seven were discharged from the hospital. Five patients remain alive and well (18 to 50 months postoperatively).
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