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Qi X, Yang J, Liu L, Hao J, Pan C, Wen Y, Zhang N, Wei W, Kang M, Cheng B, Cheng S, Zhang F. Socioeconomic inequalities, genetic susceptibility, and risks of depression and anxiety: A large-observational study. J Affect Disord 2024; 367:174-183. [PMID: 39236878 DOI: 10.1016/j.jad.2024.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 06/26/2024] [Accepted: 09/02/2024] [Indexed: 09/07/2024]
Abstract
OBJECTIVES This study aimed to investigate the interplay between genetic susceptibility and socioeconomic disparities on psychiatric disorders. METHODS In this study, we utilized data from the UK Biobank to analyze the Generalized Anxiety Disorder (GAD)-7 scale (N = 74,425) and the Patient Health Questionnaire (PHQ)-9 (N = 74,101), along with the Index of Multiple Deprivation (IMD). The polygenic risk score (PRS) was calculated to assess the genetic risk associated with GAD-7/PHQ-9 scores, and the individuals were classified into low, medium, and high genetic risk groups according to tertiles of PRSs related to the GAD-7/PHQ-9. Linear regression models were used to explore the relationships between GAD-7/PHQ-9 scores and IMD scores in patients with different genetic susceptibilities. RESULTS Disadvantaged socioeconomic status was associated with the risk of anxiety and depression across all strata of genetic risk, and stronger associations were shown for individuals with greater genetic susceptibility. From low to high genetic risk, the risk of psychiatric disorders increased for the GAD-7 (β = 0.002 to 0.032) and PHQ-9 (β = 0.003 to 0.045) scores. In addition, strong associations of high genetic risk with anxiety (β = 0.875) and depression (β = 1.152) were detected in the IMD quartile 4 group compared with the least deprivation quartile group. Furthermore, income and employment were estimated to contribute strongly to anxiety (βemployment = 7.331, βincome = 4.492) and depression (βemployment = 9.951, βincome = 6.453) in the high genetic risk group. CONCLUSION The results suggest that we should pay more attention to psychiatric disorders with high genetic susceptibility and try to improve their socioeconomic status to prevent the development of psychiatric disorders.
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Affiliation(s)
- Xin Qi
- Precision medicine center, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China; Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Jin Yang
- Precision medicine center, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China; Department of Medical Oncology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Jingcan Hao
- Medical department, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China
| | - Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Na Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Wenming Wei
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Meijuan Kang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China; Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, PR China.
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Martini MI, Butwicka A, Du Rietz E, Kanina A, Rosenqvist MA, Larsson H, Lichtenstein P, Taylor MJ. Age effects on autism heritability and etiological stability of autistic traits. J Child Psychol Psychiatry 2024; 65:1135-1144. [PMID: 38239074 DOI: 10.1111/jcpp.13949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/19/2023] [Indexed: 02/20/2024]
Abstract
BACKGROUND Autism and autistic traits onset in childhood but persist into adulthood. Little is known about how genetic and environmental factors influence autism and autistic traits into adulthood. We aimed to determine age effects on the heritability of clinically diagnosed autism and the etiological stability of autistic traits from childhood to adulthood using twin methods. METHODS From 23,849 twin pairs in the Swedish Twin Register born between 1959 and 2010, we identified 485 individuals (1.01%, 31.5% female) with a clinical autism diagnosis. We estimated and compared the relative contribution of genetic, shared, and nonshared environmental influences to autism in childhood and adulthood. We further used multivariate twin analysis with four measurement points among 1,348 twin pairs in the longitudinal Twin Study of Child and Adolescent Development to assess the phenotypic and etiological stability of autistic traits - measured with three scales from the Child Behavior Checklist - from childhood to adulthood. RESULTS Autism heritability was comparable from childhood, (96% [95% CI, 76-99%]) to adulthood (87% [67-96%]). Autistic traits were moderately stable (phenotypic correlation = 0.35-0.61) from childhood to adulthood, and their heritability varied between 52 and 71%. We observed stable as well as newly emerging genetic influences on autistic traits from ages 8-9 to 19-20, and unique nonshared environmental influences at each age. CONCLUSIONS Genetic factors are important for autism and autistic traits in adulthood and separate genetic studies in adults are warranted.
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Affiliation(s)
- Miriam I Martini
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Agnieszka Butwicka
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Division of Mental Health Services, R&D Department, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz, Poland
| | - Ebba Du Rietz
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Aleksandra Kanina
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mina A Rosenqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mark J Taylor
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Repetto L, Chen J, Yang Z, Zhai R, Timmers PRHJ, Feng X, Li T, Yao Y, Maslov D, Timoshchuk A, Tu F, Twait EL, May-Wilson S, Muckian MD, Prins BP, Png G, Kooperberg C, Johansson Å, Hillary RF, Wheeler E, Pan L, He Y, Klasson S, Ahmad S, Peters JE, Gilly A, Karaleftheri M, Tsafantakis E, Haessler J, Gyllensten U, Harris SE, Wareham NJ, Göteson A, Lagging C, Ikram MA, van Duijn CM, Jern C, Landén M, Langenberg C, Deary IJ, Marioni RE, Enroth S, Reiner AP, Dedoussis G, Zeggini E, Sharapov S, Aulchenko YS, Butterworth AS, Mälarstig A, Wilson JF, Navarro P, Shen X. The genetic landscape of neuro-related proteins in human plasma. Nat Hum Behav 2024:10.1038/s41562-024-01963-z. [PMID: 39210026 DOI: 10.1038/s41562-024-01963-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/22/2024] [Indexed: 09/04/2024]
Abstract
Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioural traits and the disease aetiology of neuropsychiatric disorders. Here the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,000 individuals for 184 neuro-related proteins in human plasma. The analysis identified 125 cis-regulatory protein quantitative trait loci (cis-pQTL) and 164 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. At the cis-pQTL, multiple proteins shared a genetic basis with human behavioural traits such as alcohol and food intake, smoking and educational attainment, as well as neurological conditions and psychiatric disorders such as pain, neuroticism and schizophrenia. Integrating with established drug information, the causal inference analysis validated 52 out of 66 matched combinations of protein targets and diseases or side effects with available drugs while suggesting hundreds of repurposing and new therapeutic targets.
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Affiliation(s)
- Linda Repetto
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Health Data Science Centre, Fondazione Human Technopole, Milan, Italy
| | - Jiantao Chen
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Zhijian Yang
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ranran Zhai
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Xiao Feng
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Ting Li
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Yue Yao
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China
| | - Denis Maslov
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Anna Timoshchuk
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
| | - Fengyu Tu
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Emma L Twait
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, Netherlands
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Marisa D Muckian
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Bram P Prins
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Grace Png
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM), TUM School of Medicine and Health, Munich, Germany
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Lu Pan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yazhou He
- Department of Epidemiology and Medical Statistics, Division of Oncology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Sofia Klasson
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - James E Peters
- Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, UK
| | - Arthur Gilly
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | | | | | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Sarah E Harris
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Andreas Göteson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Cecilia Lagging
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Genetics and Genomics, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | | | | | - Christina Jern
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Genetics and Genomics, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Mikael Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Stefan Enroth
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Alexander P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Center and Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine and Health, Munich, Germany
| | - Sodbo Sharapov
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
- Biostatistics Unit-Population and Medical Genomics Programme, Genomics Research Centre, Fondazione Human Technopole, Milan, Italy
| | - Yurii S Aulchenko
- MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia
- Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia
| | - Adam S Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Emerging Science and Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, UK
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Pau Navarro
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Xia Shen
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China.
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK.
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
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Reed ZE, Thomas R, Boyd A, Griffith GJ, Morris TT, Rai D, Manley D, Davey Smith G, Davis OSP. Mapping associations of polygenic scores with autistic and ADHD traits in a single city region. J Child Psychol Psychiatry 2024. [PMID: 39143033 DOI: 10.1111/jcpp.14047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/10/2024] [Indexed: 08/16/2024]
Abstract
BACKGROUND The genetic and environmental aetiology of autistic and Attention Deficit Hyperactivity Disorder (ADHD) traits is known to vary spatially, but does this translate into variation in the association of specific common genetic variants? METHODS We mapped associations between polygenic scores for autism and ADHD and their respective traits in the Avon Longitudinal Study of Parents and Children (N = 4,255-6,165) across the area surrounding Bristol, UK, and compared them to maps of environments associated with the prevalence of autism and ADHD. RESULTS Our results suggest genetic associations vary spatially, with consistent patterns for autistic traits across polygenic scores constructed at different p-value thresholds. Patterns for ADHD traits were more variable across thresholds. We found that the spatial distributions often correlated with known environmental influences. CONCLUSIONS These findings shed light on the factors that contribute to the complex interplay between the environment and genetic influences in autistic and ADHD traits.
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Affiliation(s)
- Zoe E Reed
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Richard Thomas
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andy Boyd
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Population Health Sciences, ALSPAC, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gareth J Griffith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tim T Morris
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, UK
| | - Dheeraj Rai
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
- Avon and Wiltshire Partnership NHS Mental Health Trust, Bath, UK
| | - David Manley
- School of Geographical Sciences, University of Bristol, Bristol, UK
- Department of Urbanism, Delft University of Technology, Delft, The Netherlands
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Oliver S P Davis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
- Alan Turing Institute, London, UK
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Al-Mehmadi SO, Halawani AT, Sulaimani MT, Al-Mehmadi TO. Electronic device usage among preschool children and its association with mental health status in Saudi Arabian kindergartens. Saudi Med J 2024; 45:945-951. [PMID: 39218475 PMCID: PMC11376694 DOI: 10.15537/smj.2024.45.9.20240354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Accepted: 07/09/2024] [Indexed: 09/04/2024] Open
Abstract
OBJECTIVES To estimate the prevalence of electronic device usage and its association with mental health status among preschool children aged 3-6 years. METHODS A cross-sectional study was conducted among preschool children aged 3-6 years in kindergartens in Makkah city in 2023-2024, using an electronic questionnaire. An Arabic version of the Strengths and Difficulties Questionnaire was used to assess mental health. RESULTS We recruited a total of 399 children. The prevalence of electronic device usage was 91.5%. The number of hours spent using electronic devices ranged from 0 to 12 hour (h)/day, with a mean of 3.1 h/day. We found a significant positive correlation between the number of hours spent using electronic devices and emotional problems (r=0.200, p<0.001), conduct problems (r=0.149, p=0.003), hyperactivity (r=0.279, p<0.001), peer problems (r=0.104, p=0.038), and total difficulty scores (r=0.263, p<0.001). We also found a significant negative correlation between the number of hours spent using electronic devices and the prosocial score (r= -0.128, p=0.011), and most of the included children had scores within the "close to average" category across all scales of mental health status. CONCLUSION There was a high prevalence of electronic device usage among preschool children, which exceeded the recommended time limit. A significant correlation was observed between electronic device use and mental health scores. Further longitudinal studies are required to understand the nature of this association and its implications for child development.
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Affiliation(s)
- Siham O Al-Mehmadi
- From the Department of Preventive Medicine (S. Al-Mehmadi), Saudi Board of Preventive Medicine Al-Madinah joint program, Makkah Healthcare Cluster, Makkah; from the Department of Preventive Medicine, (Halawani), Ministry of Health, Al-Madinah Health Cluster, Al-Madinah Al-Munawarah; from the Department of Preventive Medicine (Sulaimani) Saudi Board of Preventive Medicine Makkah joint program, Makkah Healthcare Cluster, Makkah; and from the Neonatal Intensive Care Unit (T. Al-Mehmadi), Maternity and Children Hospital, Makkah Healthcare Cluster, Makkah, Kingdom of Saudi Arabia
| | - Abdulrahman T Halawani
- From the Department of Preventive Medicine (S. Al-Mehmadi), Saudi Board of Preventive Medicine Al-Madinah joint program, Makkah Healthcare Cluster, Makkah; from the Department of Preventive Medicine, (Halawani), Ministry of Health, Al-Madinah Health Cluster, Al-Madinah Al-Munawarah; from the Department of Preventive Medicine (Sulaimani) Saudi Board of Preventive Medicine Makkah joint program, Makkah Healthcare Cluster, Makkah; and from the Neonatal Intensive Care Unit (T. Al-Mehmadi), Maternity and Children Hospital, Makkah Healthcare Cluster, Makkah, Kingdom of Saudi Arabia
| | - Mrnan T Sulaimani
- From the Department of Preventive Medicine (S. Al-Mehmadi), Saudi Board of Preventive Medicine Al-Madinah joint program, Makkah Healthcare Cluster, Makkah; from the Department of Preventive Medicine, (Halawani), Ministry of Health, Al-Madinah Health Cluster, Al-Madinah Al-Munawarah; from the Department of Preventive Medicine (Sulaimani) Saudi Board of Preventive Medicine Makkah joint program, Makkah Healthcare Cluster, Makkah; and from the Neonatal Intensive Care Unit (T. Al-Mehmadi), Maternity and Children Hospital, Makkah Healthcare Cluster, Makkah, Kingdom of Saudi Arabia
| | - Tamim O Al-Mehmadi
- From the Department of Preventive Medicine (S. Al-Mehmadi), Saudi Board of Preventive Medicine Al-Madinah joint program, Makkah Healthcare Cluster, Makkah; from the Department of Preventive Medicine, (Halawani), Ministry of Health, Al-Madinah Health Cluster, Al-Madinah Al-Munawarah; from the Department of Preventive Medicine (Sulaimani) Saudi Board of Preventive Medicine Makkah joint program, Makkah Healthcare Cluster, Makkah; and from the Neonatal Intensive Care Unit (T. Al-Mehmadi), Maternity and Children Hospital, Makkah Healthcare Cluster, Makkah, Kingdom of Saudi Arabia
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Lebeña A, Faresjö Å, Jones MP, Bengtsson F, Faresjö T, Ludvigsson J. Early environmental predictors for attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and their co-occurrence: The prospective ABIS-Study. Sci Rep 2024; 14:14759. [PMID: 38926504 PMCID: PMC11208583 DOI: 10.1038/s41598-024-65067-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 06/17/2024] [Indexed: 06/28/2024] Open
Abstract
ADHD and ASD are highly heritable and show a high co-occurrence and persistence into adulthood. This study aimed to identify pre and perinatal risk factors, and early psychosocial exposures related to later diagnosis of ADHD, ASD, and their co-occurrence. 16,365 children born 1997-1999 and their families, involved in the prospective population-based ABIS study (All Babies in Southeast Sweden), were included in this sub-study. Pre and perinatal factors and early environmental psychosocial exposures were collected from parental-questionnaires at birth and 1-year follow-up. Diagnoses from birth up to 23 years of age were obtained from the Swedish National Diagnosis Register in 2020. The cumulative incidence of ADHD, ASD, and their co-occurrence in the ABIS-cohort Study were 4.6%, 1.7%, and 1.1%, respectively. Being male was associated with an increased risk for ADHD, ASD, and their co-occurrence (aOR 1.30, 1.56, and 1.91, respectively), while higher household income reduced it (aOR 0.82, 0.73, and 0.64). Serious life events during pregnancy (aOR 1.40) and maternal smoking (aOR 1.51) increased the risk of ADHD, while older maternal age (aOR 0.96), higher parental education (aOR 0.72 maternal and aOR 0.74 paternal) and longer exclusive breastfeeding (aOR 0.72) reduced it. Non-Swedish paternal nationality (aOR 0.40) and higher maternal education (aOR 0.74) were associated with a lower risk of ASD, while a family history of autoimmune diseases increased the risk of the co-occurrence of both disorders (aOR 1.62). Obtained results suggest that the etiology of ADHD, ASD, and their co-occurrence is independently associated with environmental psychosocial predictors. The co-occurrence seems to overlap the etiology of ADHD, in which psychosocial determinants have a larger role, however, it is also independently influenced by a family history of autoimmune diseases.
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Affiliation(s)
- Andrea Lebeña
- Division of Pediatrics, Department of Biomedical and Clinical Sciences, Linköping University, US Campus, Building 511 (14, 09B), 581 83, Linköping, Sweden.
| | - Åshild Faresjö
- Department of Medicine and Health, Community Medicine, Linköping University, Linköping, Sweden
| | - Michael P Jones
- School of Psychological Sciences, Macquarie University, North Ryde, NSW, Australia
| | - Felicia Bengtsson
- Department of Medicine and Health, Community Medicine, Linköping University, Linköping, Sweden
| | - Tomas Faresjö
- Department of Medicine and Health, Community Medicine, Linköping University, Linköping, Sweden
| | - Johnny Ludvigsson
- Division of Pediatrics, Department of Biomedical and Clinical Sciences, Linköping University, US Campus, Building 511 (14, 09B), 581 83, Linköping, Sweden
- Crown Princess Victoria Children's Hospital, Region Östergötland, Linköping, Sweden
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7
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Farré X, Blay N, Espinosa A, Castaño-Vinyals G, Carreras A, Garcia-Aymerich J, Cardis E, Kogevinas M, Goldberg X, de Cid R. Decoding depression by exploring the exposome-genome edge amidst COVID-19 lockdown. Sci Rep 2024; 14:13562. [PMID: 38866890 PMCID: PMC11169603 DOI: 10.1038/s41598-024-64200-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 06/06/2024] [Indexed: 06/14/2024] Open
Abstract
Risk of depression increased in the general population after the COVID-19 pandemic outbreak. By examining the interplay between genetics and individual environmental exposures during the COVID-19 lockdown, we have been able to gain an insight as to why some individuals are more vulnerable to depression, while others are more resilient. This study, conducted on a Spanish cohort of 9218 individuals (COVICAT), includes a comprehensive non-genetic risk analysis, the exposome, complemented by a genomics analysis in a subset of 2442 participants. Depression levels were evaluated using the Hospital Anxiety and Depression Scale. Together with Polygenic Risk Scores (PRS), we introduced a novel score; Poly-Environmental Risk Scores (PERS) for non-genetic risks to estimate the effect of each cumulative score and gene-environment interaction. We found significant positive associations for PERSSoc (Social and Household), PERSLife (Lifestyle and Behaviour), and PERSEnv (Wider Environment and Health) scores across all levels of depression severity, and for PRSB (Broad depression) only for moderate depression (OR 1.2, 95% CI 1.03-1.40). On average OR increased 1.2-fold for PERSEnv and 1.6-fold for PERLife and PERSoc from mild to severe depression level. The complete adjusted model explained 16.9% of the variance. We further observed an interaction between PERSEnv and PRSB showing a potential mitigating effect. In summary, stressors within the social and behavioral domains emerged as the primary drivers of depression risk in this population, unveiling a mitigating interaction effect that should be interpreted with caution.
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Affiliation(s)
- Xavier Farré
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
- Research Group on the Impact of Chronic Diseases and Their Trajectories (GRIMTra), Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Natalia Blay
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
- Research Group on the Impact of Chronic Diseases and Their Trajectories (GRIMTra), Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Ana Espinosa
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Gemma Castaño-Vinyals
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Anna Carreras
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Judith Garcia-Aymerich
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Elisabeth Cardis
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Manolis Kogevinas
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
| | - Ximena Goldberg
- ISGlobal, Barcelona, Spain.
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
- CIBER Salud Mental (CIBERSAM), Madrid, Spain.
| | - Rafael de Cid
- Genomes for Life-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain.
- Research Group on the Impact of Chronic Diseases and Their Trajectories (GRIMTra), Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain.
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8
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Arildskov TW, Thomsen PH, Sonuga-Barke EJS, Lambek R, Østergaard SD, Virring A. Is Attention-Deficit/Hyperactivity Disorder (ADHD) a Dimension or a Category? What Does the Relationship Between ADHD Traits and Psychosocial Quality of Life Tell Us? J Atten Disord 2024; 28:1035-1044. [PMID: 38281108 DOI: 10.1177/10870547231222228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2024]
Abstract
OBJECTIVE The question of whether attention-deficit/hyperactivity disorder (ADHD) is a discrete category or a continuous dimension remains clinically relevant. We report the first examination of this question from the viewpoint of the relationship between ADHD traits and psychosocial quality of life (QoL), and whether the level of QoL declines markedly around a certain high ADHD trait range suggestive of a categorical boundary. METHODS Parents/caregivers of 1,967 schoolchildren aged 6 to 11 from the general population completed the Pediatric Quality of Life Inventory and the ADHD-Rating Scale IV. Piecewise linear and non-linear regression analyses were performed. RESULTS No evidence for a non-linear association or an abrupt change in the rate of decrease in QoL was observed in the high end of the ADHD traits continuum. Instead, the relationship was consistent with linearity. CONCLUSION Psychosocial QoL gradually declines in a linear manner as ADHD trait levels increase providing further support for a dimensional model.
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Affiliation(s)
- Trine Wigh Arildskov
- Department of Child and Adolescent Psychiatry, Aarhus University Hospital, Psychiatry, Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, Denmark
| | - Per Hove Thomsen
- Department of Child and Adolescent Psychiatry, Aarhus University Hospital, Psychiatry, Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, Denmark
| | - Edmund J S Sonuga-Barke
- Department of Clinical Medicine, Aarhus University, Denmark
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
| | - Rikke Lambek
- Department of Psychology and Behavioral Sciences, Aarhus University, Aarhus, Denmark
| | - Søren D Østergaard
- Department of Clinical Medicine, Aarhus University, Denmark
- Department of Affective Disorders, Aarhus University Hospital, Psychiatry, Aarhus N, Denmark
| | - Anne Virring
- Department of Child and Adolescent Psychiatry, Aarhus University Hospital, Psychiatry, Aarhus N, Denmark
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9
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López-Otín C, Kroemer G. The missing hallmark of health: psychosocial adaptation. Cell Stress 2024; 8:21-50. [PMID: 38476764 PMCID: PMC10928495 DOI: 10.15698/cst2024.03.294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 03/14/2024] Open
Abstract
The eight biological hallmarks of health that we initially postulated (Cell. 2021 Jan 7;184(1):33-63) include features of spatial compartmentalization (integrity of barriers, containment of local perturbations), maintenance of homeostasis over time (recycling & turnover, integration of circuitries, rhythmic oscillations) and an array of adequate responses to stress (homeostatic resilience, hormetic regulation, repair & regeneration). These hallmarks affect all eight somatic strata of the human body (molecules, organelles, cells, supracellular units, organs, organ systems, systemic circuitries and meta-organism). Here we postulate that mental and socioeconomic factors must be added to this 8×8 matrix as an additional hallmark of health ("psychosocial adaptation") and as an additional stratum ("psychosocial interactions"), hence building a 9×9 matrix. Potentially, perturbation of each of the somatic hallmarks and strata affects psychosocial factors and vice versa. Finally, we discuss the (patho)physiological bases of these interactions and their implications for mental health improvement.
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Affiliation(s)
- Carlos López-Otín
- Centre de Recherche des Cordeliers, Equipe labellisée par la Ligue contre le cancer, Université Paris Cité, Sorbonne Université, Inserm U1138, Institut Universitaire de France, Paris, France
- Facultad de Ciencias de la Vida y la Naturaleza, Universidad Nebrija, Madrid, Spain
- Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo
| | - Guido Kroemer
- Centre de Recherche des Cordeliers, Equipe labellisée par la Ligue contre le cancer, Université Paris Cité, Sorbonne Université, Inserm U1138, Institut Universitaire de France, Paris, France
- Metabolomics and Cell Biology Platforms, Institut Gustave Roussy, Villejuif, France
- Institut du Cancer Paris CARPEM, Department of Biology, Hôpital Européen Georges Pompidou, AP-HP, Paris, France
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10
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Faraone SV, Bellgrove MA, Brikell I, Cortese S, Hartman CA, Hollis C, Newcorn JH, Philipsen A, Polanczyk GV, Rubia K, Sibley MH, Buitelaar JK. Attention-deficit/hyperactivity disorder. Nat Rev Dis Primers 2024; 10:11. [PMID: 38388701 DOI: 10.1038/s41572-024-00495-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/16/2024] [Indexed: 02/24/2024]
Abstract
Attention-deficit/hyperactivity disorder (ADHD; also known as hyperkinetic disorder) is a common neurodevelopmental condition that affects children and adults worldwide. ADHD has a predominantly genetic aetiology that involves common and rare genetic variants. Some environmental correlates of the disorder have been discovered but causation has been difficult to establish. The heterogeneity of the condition is evident in the diverse presentation of symptoms and levels of impairment, the numerous co-occurring mental and physical conditions, the various domains of neurocognitive impairment, and extensive minor structural and functional brain differences. The diagnosis of ADHD is reliable and valid when evaluated with standard diagnostic criteria. Curative treatments for ADHD do not exist but evidence-based treatments substantially reduce symptoms and/or functional impairment. Medications are effective for core symptoms and are usually well tolerated. Some non-pharmacological treatments are valuable, especially for improving adaptive functioning. Clinical and neurobiological research is ongoing and could lead to the creation of personalized diagnostic and therapeutic approaches for this disorder.
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Affiliation(s)
- Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, USA.
| | - Mark A Bellgrove
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Isabell Brikell
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Solent NHS Trust, Southampton, UK
- Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York City, NY, USA
- DiMePRe-J-Department of Precision and Rigenerative Medicine-Jonic Area, University of Bari "Aldo Moro", Bari, Italy
| | - Catharina A Hartman
- Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Chris Hollis
- National Institute for Health and Care Research (NIHR) MindTech MedTech Co-operative and NIHR Nottingham Biomedical Research Centre, Institute of Mental Health, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jeffrey H Newcorn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexandra Philipsen
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Guilherme V Polanczyk
- Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Katya Rubia
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neurosciences, King's College London, London, UK
- Department of Child & Adolescent Psychiatry, Transcampus Professor KCL-Dresden, Technical University, Dresden, Germany
| | | | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands
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11
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McGuinn LA, Gutiérrez-Avila I, Rosa MJ, Just A, Coull B, Kloog I, Ortiz MT, Harari H, Martinez S, Osorio-Valencia E, Téllez-Rojo MM, Klein DN, Wright RJ, Wright RO. Association between prenatal and childhood PM 2.5 exposure and preadolescent anxiety and depressive symptoms. Environ Epidemiol 2024; 8:e283. [PMID: 38343740 PMCID: PMC10852372 DOI: 10.1097/ee9.0000000000000283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 11/14/2023] [Indexed: 03/13/2024] Open
Abstract
Background Fine particulate matter (PM2.5) exposure has been linked to anxiety and depression in adults; however, there is limited research in the younger populations, in which symptoms often first arise. Methods We examined the association between early-life PM2.5 exposure and symptoms of anxiety and depression in a cohort of 8-11-year-olds in Mexico City. Anxiety and depressive symptoms were assessed using the Spanish versions of the Revised Children's Manifest Anxiety Scale and Children's Depression Inventory. Daily PM2.5 was estimated using a satellite-based exposure model and averaged over several early and recent exposure windows. Linear and logistic regression models were used to estimate the change in symptoms with each 5-µg/m3 increase in PM2.5. Models were adjusted for child's age, child's sex, maternal age, maternal socioeconomic status, season of conception, and temperature. Results Average anxiety and depressive symptom T-scores were 51.0 (range 33-73) and 53.4 (range 44-90), respectively. We observed consistent findings for exposures around the fourth year of life, as this was present for both continuous and dichotomized anxiety symptoms, in both independent exposure models and distributed lag modeling approaches. This window was also observed for elevated depressive symptoms. An additional consistent finding was for PM2.5 exposure during early pregnancy in relation to both clinically elevated anxiety and depressive symptoms, this was seen in both traditional and distributed lag modeling approaches. Conclusion Both early life and recent PM2.5 exposure were associated with higher mental health symptoms in the child highlighting the role of PM2.5 in the etiology of these conditions.
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Affiliation(s)
- Laura A. McGuinn
- Institute for Population and Precision Health, University of Chicago, Chicago, Illinois
- Department of Family Medicine, University of Chicago, Chicago, Illinois
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, New York
| | - Iván Gutiérrez-Avila
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, New York
| | - Maria José Rosa
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, New York
| | - Allan Just
- Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island
| | - Brent Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Itai Kloog
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, New York
| | - Marcela Tamayo Ortiz
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York City, New York
| | - Homero Harari
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, New York
| | | | | | - Martha Maria Téllez-Rojo
- Center for Nutrition and Health Research, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Daniel N. Klein
- Department of Psychology, Stony Brook University, Stony Brook, New York
| | - Rosalind J. Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, New York
- Kravis Children’s Hospital, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York City, New York
| | - Robert O. Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York City, New York
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12
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Glans MR, Nilsson J, Bejerot S. Tattoos, piercings, and symptoms of ADHD in non-clinical adults: a cross-sectional study. Front Psychiatry 2024; 14:1224811. [PMID: 38234366 PMCID: PMC10791871 DOI: 10.3389/fpsyt.2023.1224811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 11/27/2023] [Indexed: 01/19/2024] Open
Abstract
Introduction Tattoos and piercings are associated with impulsive and risk-taking personality traits, which are also common along the ADHD continuum. However, studies on ADHD and body modification are lacking. Thus, this study aimed to assess the association between body modification and subclinical ADHD symptom severity and to investigate if body modification can serve as an indication for ADHD examination. Methods A total of 762 adults (529 women and 233 men) without a diagnosis of ADHD completed the adult ADHD Self-Report Scale (ASRS) and answered questions concerning body modification. Two different ASRS versions were utilized: the 18-item ASRS Symptom Checklist and the 6-item ASRS Screener. Three categorizations of body modifications were analyzed: (i) having at least one tattoo, (ii) having at least one piercing other than ear piercing, and (iii) the combination of simultaneously having at least one tattoo and one piercing. Mean 18-item ASRS total and subscale scores and the proportion of positive results on the 6-item ASRS Screener were compared between those with and those without body modifications while adjusting for covariates age and sex. Additional analyses were performed for ≥2 and ≥3 body modifications. Results In our cohort, 26% had a tattoo, 14% had a piercing other than ear piercing, and 8% had a combination of tattoo and piercing. Having any kind of body modification was associated with more pronounced symptoms of ADHD and with a cutoff score on the ASRS screener indicating ADHD. Whereas, the effect sizes were small for tattoos, medium to large effect sizes were seen for ≥2 piercings in the ASRS. Moreover, moderately strong associations emerged for ≥1 piercing and a positive ASRS screening result. Conclusion Our results suggest that acquiring a body modification, especially a tattoo, is entering the mainstream in Sweden. Correspondingly, differences in subclinical ADHD symptomatology between non-clinical adults with and without body modifications are subtle. Having ≥2 piercings other than ear piercings, on the other hand, is associated with clinically relevant differences in ADHD symptoms. Moreover, piercing status may serve as an indicator, among others, for further ADHD assessments. However, more research is needed to ascertain the possible signaling functions of body modifications in clinical settings.
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Affiliation(s)
- Martin Ragnar Glans
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
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13
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Shakeshaft A, Heron J, Blakey R, Riglin L, Smith GD, Stergiakouli E, Tilling K, Thapar A. Co-development of attention deficit hyperactivity disorder and autistic trait trajectories from childhood to early adulthood. J Child Psychol Psychiatry 2023; 64:1596-1607. [PMID: 37350028 PMCID: PMC7615536 DOI: 10.1111/jcpp.13851] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/12/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND Attention deficit hyperactivity disorder (ADHD) and autism, defined as traits or disorders, commonly co-occur. Developmental trajectories of ADHD and autistic traits both show heterogeneity in onset and course, but little is known about how symptom trajectories co-develop into adulthood. METHODS Using data from a population cohort, the Avon Longitudinal Study of Parents and Children, we examined correlations between ADHD and autistic traits across development, using the Social Communication Disorders Checklist and ADHD subscale of the Strengths and Difficulties Questionnaire. We modelled joint developmental trajectories of parent-reported ADHD and autistic traits between 4 and 25 years, then characterised trajectory classes based on sociodemographic, perinatal, psychopathology, cognition and social functioning variables and tested for associations with neurodevelopmental/psychiatric polygenic scores (PGS). RESULTS Three classes of trajectories were identified; a typically developing majority with low-stable ADHD-autistic traits (87%), a male-predominant subgroup with child/adolescent-declining traits (6%) and a subgroup with late-emerging traits (6%). ADHD-autistic trait correlations were greatest in young adulthood for the two nontypically developing classes. There were higher rates of emotional and conduct problems, low IQ, childhood seizures and poor social functioning in the declining and late-emerging classes compared to the low-stable class. Emotional, conduct and peer problems were more prevalent during childhood in the childhood/adolescent-declining class compared to other classes, but were more prevalent in young adulthood in the late-emerging class. Neurodevelopmental/psychiatric PGS also differed: both nontypically developing classes showed elevated ADHD PGS compared to the low-stable group, and the late-emerging group additionally showed elevated schizophrenia PGS and decreased executive function PGS, whereas the declining group showed elevated broad depression PGS. CONCLUSIONS Distinct patterns of ADHD-autism co-development are present across development in the general population, each with different characterising factors and genetic signatures as indexed by PGS.
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Affiliation(s)
- Amy Shakeshaft
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
- Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
| | - Jon Heron
- Population Health Sciences and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Rachel Blakey
- Population Health Sciences and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Lucy Riglin
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
- Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
| | - George Davey Smith
- Population Health Sciences and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Evie Stergiakouli
- Population Health Sciences and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Kate Tilling
- Population Health Sciences and MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, UK
- Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
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14
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Taylor MJ, Martin J, Butwicka A, Lichtenstein P, D'Onofrio B, Lundström S, Larsson H, Rosenqvist MA. A twin study of genetic and environmental contributions to attention-deficit/hyperactivity disorder over time. J Child Psychol Psychiatry 2023; 64:1608-1616. [PMID: 37409759 DOI: 10.1111/jcpp.13854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/16/2023] [Indexed: 07/07/2023]
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is an increasingly commonly diagnosed neurodevelopmental condition. One possibility is that this reflects a genuine increase in the prevalence of ADHD due to secular environmental changes, yet this hypothesis remains untested. We therefore investigated whether the genetic and environmental variance underlying ADHD, and traits of ADHD, has changed over time. METHODS We identified twins born from 1982 to 2008 from the Swedish Twin Registry (STR). We linked the STR with the Swedish National Patient Register and Prescribed Drug Register to identify diagnoses of ADHD and prescriptions of ADHD medication for these twins. We also utilized data collected from participants in the Child and Adolescent Twin Study in Sweden (CATSS), born from 1992 to 2008. Their parents completed a structured ADHD screening tool, which was used to measure traits of ADHD and assign broad screening diagnoses of ADHD. We used the classical twin design to test whether the degree to which variation in these measures was influenced by genetic and environmental variation changed over time. RESULTS We included 22,678 twin pairs from the STR and 15,036 pairs from CATSS. The heritability of ADHD in the STR ranged from 66% to 86% over time, although these fluctuations were not statistically significant. We observed a modest increase in variance in ADHD traits, from 0.98 to 1.09. This was driven by small increases in the underlying genetic and environmental variance, with heritability estimated as 64%-65%. No statistically significant changes in variance in screening diagnoses were observed. CONCLUSIONS The relative contribution of genetic and environmental factors to ADHD has remained stable over time, despite its increasing prevalence. Thus, changes in the underlying etiology of ADHD over time are unlikely to explain the increase in ADHD diagnoses.
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Affiliation(s)
- Mark J Taylor
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Joanna Martin
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Agnieszka Butwicka
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Child Psychiatry, Medical University of Warsaw, Warsaw, Poland
- Child and Adolescent Psychiatry, Stockholm Health Care Service, Region Stockholm, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Brian D'Onofrio
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychological and Brain Science, Indiana University, Bloomington, IN, USA
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, Centre for Ethics, Law and Mental Health, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Mina A Rosenqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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15
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Sakkaki S, Cresto N, Chancel R, Jaulmes M, Zub E, Blaquière M, Sicard P, Maurice T, Ellero-Simatos S, Gamet-Payrastre L, Marchi N, Perroy J. Dual-Hit: Glyphosate exposure at NOAEL level negatively impacts birth and glia-behavioural measures in heterozygous shank3 mutants. ENVIRONMENT INTERNATIONAL 2023; 180:108201. [PMID: 37769447 DOI: 10.1016/j.envint.2023.108201] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 09/06/2023] [Accepted: 09/11/2023] [Indexed: 09/30/2023]
Abstract
The omnipresence of environmental contaminants represents a health danger with ramifications for adverse neurological trajectories. Here, we tested the dual-hit hypothesis that continuous exposure to non-observable adverse effect level (NOAEL) glyphosate from pre-natal to adulthood represents a risk factor for neurological-associated adaptations when in the presence of the heterozygote or homozygote mutation of the Shank3 synaptic gene. Ultrasound analysis of pregnant dams revealed patterns of pre-natal mortality with effects dependent on wild-type, Shank3ΔC/+, or Shank3ΔC/ΔC genotypes exposed to NOAEL glyphosate (GLY) compared to unexposed conditions. The postnatal survival rate was negatively impacted, specifically in Shank3ΔC/+ exposed to GLY. Next, the resulting six groups of pups were tracked into adulthood and analyzed for signs of neuroinflammation and neurological adaptions. Sholl's analysis revealed cortical microgliosis across groups exposed to GLY, with Shank3ΔC/+ mice presenting the most significant modifications. Brain tissues were devoid of astrocytosis, except for the perivascular compartment in the cortex in response to GLY. Distinct behavioral adaptations accompanied these cellular modifications, as locomotion and social preference were decreased in Shank3ΔC/+ mice exposed to GLY. Notably, GLY exposure from weaning did not elicit glial or neurological adaptations across groups, indicating the importance of pre-natal contaminant exposure. These results unveil the intersection between continuous pre-natal to adulthood environmental input and a pre-existing synaptic mutation. In an animal model, NOAEL GLY predominantly impacted Shank3ΔC/+ mice, compounding an otherwise mild phenotype compared to Shank3ΔC/ΔC. The possible relevance of these findings to neurodevelopmental risk is critically discussed, along with avenues for future research.
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Affiliation(s)
- Sophie Sakkaki
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Noemie Cresto
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Raphaël Chancel
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Maé Jaulmes
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Emma Zub
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Marine Blaquière
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Pierre Sicard
- PhyMedExp, INSERM, CNRS, CHU Montpellier, University of Montpellier, 34295 Montpellier, France
| | - Tangui Maurice
- MMDN, Univ Montpellier, EPHE, INSERM, Montpellier, France
| | | | | | - Nicola Marchi
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France.
| | - Julie Perroy
- IGF, University of Montpellier, CNRS, INSERM, Montpellier, France.
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Okagbue HI, Ijezie OA, Ugwoke PO, Adeyemi-Kayode TM, Jonathan O. Single-label machine learning classification revealed some hidden but inter-related causes of five psychotic disorder diseases. Heliyon 2023; 9:e19422. [PMID: 37674848 PMCID: PMC10477489 DOI: 10.1016/j.heliyon.2023.e19422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 08/04/2023] [Accepted: 08/22/2023] [Indexed: 09/08/2023] Open
Abstract
Psychotic disorder diseases (PDD) or mental illnesses are group of illnesses that affect the minds and impair the cognitive ability, retard emotional ability and obstruct the process of communication and relationship with others and are characterized by delusions, hallucinations and disoriented or disordered pattern of thinking. Prognosis of PDD is not sufficient because of the nature of the diseases and as such adequate form of diagnosis is required to detect, manage and treat the illness. This paper applied the single-label classification (SLC) machine learning approach in mining of electronic health records of people with PDD in Nigeria using eleven independent (demographic) variables and five PDD as target variables. The five PDDs are Insomnia, Schizophrenia, Minimal Brain dysfunction (MBD), which is also known as Attention-Deficit/Hyperactivity Disorder (ADHD), Vascular Dementia (VD) and Bipolar Disorder (BD). The aim of using SLC is that it would be easier to detect some PDDs that are related to each other without the loss of information, which is a plus over multi-label classification (MLC). ReliefF algorithm was used at each experiment to precipitate the order of importance of the independent variables and redundant variables were excluded from the analysis. The order of the variables in feature selection was matched with feature importance after the classifications and quantified using the Spearman rank correlation coefficient. The data was divided into: 70% for training and 30% for testing. Four new performance metrics adapted from the root mean square (RMSE) were proposed and used to measure the differences between the performance results of the 10 Machine learning models in terms of the training and testing and secondly, feature and without feature selection. The new metrics are close to zero which is an indication that the use of feature selection and cross validation may not greatly affects the accuracy of the SLC. When the PDDs are included as predictors for classifying others, there was a tremendous improvement as revealed by the four new metrics for classification accuracy (CA), precision and recall. Analysis of variance showed the four different metrics differs significantly for classification accuracy (CA) and precision. However, there were no significant difference between the CA and precision when the duo are compared together across the four evaluation metrics at p value less than 0.05.
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Affiliation(s)
| | - Ogochukwu A. Ijezie
- Faculty of Science and Technology, Bournemouth University, Poole, BH12 5BB, UK
| | - Paulinus O. Ugwoke
- Department of Computer Science, University of Nigeria, Nsukka, Nigeria
- Digital Bridge Institute, International Centre for Information & Communications Technology Studies, Abuja, Nigeria
| | | | - Oluranti Jonathan
- Department of Computer & Information Sciences, Covenant University, Ota, Nigeria
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Jonsson L, Martin J, Lichtenstein P, Magnusson PKE, Lundström S, Westberg L, Tammimies K. Examining neurodevelopmental problems in 15q11.2 (BP1-BP2) copy number variation carriers at ages 9/12 and 18 in a Swedish twin sample. Mol Genet Genomic Med 2023; 11:e2191. [PMID: 37156729 PMCID: PMC10422071 DOI: 10.1002/mgg3.2191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 03/16/2023] [Accepted: 04/21/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND Several copy number variations (CNVs) are associated with increased risk for neurodevelopmental and psychiatric disorders. The CNV 15q11.2 (BP1-BP2) deletion has been associated with learning difficulties, attention deficit hyperactivity disorder (ADHD), epilepsy, and brain morphology; however, many carriers present mild or no symptoms. Carrying the reciprocal duplication does not seem to confer risk for these disorders or traits. Our aim was to examine the impact of carrying either 15q11.2 deletion and reciprocal duplication on neurodevelopmental problems in a population-based sample of children. METHODS Twins with genotype and phenotype information in the Child and Adolescent Twin Study in Sweden (CATSS) were included (N = 12,040). We included measures of neurodevelopmental problems (NDPs), including learning problems, from the questionnaire Autism-Tics, ADHD, and other Comorbidities inventory (A-TAC) at age 9/12, ADHD and autism spectrum disorder (ASD) questionnaires at age 18, as well as information about lifetime psychiatric diagnoses and epileptic seizures. We tested the association between these phenotypic measurements and carrying the 15q11.2 deletion, the reciprocal duplication, and other CNVs with previously reported strong associations with neurodevelopmental and psychiatric disorders (i.e., psychiatric CNVs). RESULTS We identified 57 carriers of the 15q11.2 deletion, 75 carriers of the reciprocal duplication, and 67 carriers of other psychiatric CNVs. We did not find an increased risk for NDPs or psychiatric diagnoses in the 15q11.2 deletion carriers. For 15q11.2 duplication carriers, we found an increased risk for math learning problems and fewer self-reported ADHD symptoms at age 18 but not for other NDPs. In line with previous studies, we found an increased risk of NDPs and other evaluated phenotypes in carriers of psychiatric CNVs. CONCLUSIONS Our results support previous findings that carrying 15q11.2 deletion does not have a large effect on NDPs in children.
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Affiliation(s)
- Lina Jonsson
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiology at the Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
| | - Joanna Martin
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Centre for Neuropsychiatric Genetics and GenomicsDivision of Psychological Medicine and Clinical NeurosciencesCardiff UniversityCardiffUK
| | - Paul Lichtenstein
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry CentreInstitute of Neuroscience and Physiology at the Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
| | - Lars Westberg
- Department of PharmacologyInstitute of Neuroscience and Physiology at the Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
| | - Kristiina Tammimies
- Center of Neurodevelopmental Disorders (KIND)Centre for Psychiatry ResearchDepartment of Women's and Children's HealthKarolinska Institutet and Child and Adolescent PsychiatryStockholm Health Care Services, Stockholm County CouncilStockholmSweden
- Astrid Lindgren Children's HospitalKarolinska University Hospital, Region StockholmSolnaSweden
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18
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Simon SS, Brucki SMD, Fonseca LM, Becker J, Cappi C, Marques AH, Heyn PC, Gonçalves PD, Martins SS, Busatto G, Bertola L, Suemoto CK, Nitrini R, Caramelli P, Yassuda MS, Miotto EC, Grinberg LT, Arce Renteria M, Alegria M, Stern Y, Rivera‐Mindt M. The (in)visible Brazilians: A perspective review on the need for brain health and dementia research with Brazilian immigrants in the United States. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2023; 9:e12425. [PMID: 37744309 PMCID: PMC10517444 DOI: 10.1002/trc2.12425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 08/23/2023] [Accepted: 08/26/2023] [Indexed: 09/26/2023]
Abstract
Introduction The Brazilian population in the United States (U.S.), a Latinx subgroup, is rapidly growing and aging but remains underrepresented in U.S. health research. In addition to group-specific genetic and environmental risks, Brazilian immigrants and their offspring in the U.S. likely have cumulative risks for health inequities.It is estimated that 71% of Brazilian immigrants in the U.S. are undocumented, which may limit healthcare access/utilization. Furthermore, mental health is reported as a health priority by Brazilian immigrants in the U.S., and there is a lack of research on Alzheimer's disease and related dementia (AD/ADRD) in this population. Methods We reviewed the scientific literature using traditional (e.g., PubMed) sources and databases generated by U.S. and Brazilian governments, as well as international organizations, and press articles. Results This perspective review lists recommendations for researchers, health providers, and policymakers to promote greater inclusion of U.S. Brazilian populations in health research and care. The review identifies research areas in need of attention to address health inequities and promote mental/brain health in Brazilian immigrants and their offspring living in the U.S. These research areas are: 1) epidemiological studies to map the prevalence and incidence of mental/brain health conditions; 2) research on aging and AD/ADRD risk factors among Brazilian populations in the U.S.; and 3) the need for greater representation of U.S-residing Brazilian population in other relevant research areas involving genetics, neuropathology, and clinical trials. Conclusions The recommendation and research efforts proposed should help to pave the way for the development of community-engagement research and to promote mental/brain health education, improvement of mental/brain health and AD/ADRD services, and the development of culturally-informed intervention to the U.S.-residing Brazilian communities. HIGHLIGHTS The Brazilian population in the United States is growing but is underrepresented in U.S. health research.Approximately 71% of Brazilian immigrants in the United States are undocumented, with an increased risk for health inequities.Mental health is reported as a central health priority by Brazilian immigrants in the United States.There is a lack of research on Alzheimer's disease and other dementias (ADRD) in Brazilian immigrants in the United States.Epidemiological research is needed to map the prevalence/incidence of mental health conditions and ADRD risk factors among Brazilian immigrants in the United States.
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Affiliation(s)
- Sharon Sanz Simon
- Cognitive Neuroscience DivisionDepartment of NeurologyColumbia UniversityVagelos College of Physicians and SurgeonsNew YorkNew YorkUSA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of NeurologyColumbia UniversityVagelos College of Physicians and SurgeonsNew YorkNew YorkUSA
- Old Age Research Group, Department of PsychiatryUniversity of São Paulo Medical SchoolSão PauloSão PauloBrazil
| | | | - Luciana Mascarenhas Fonseca
- Old Age Research Group, Department of PsychiatryUniversity of São Paulo Medical SchoolSão PauloSão PauloBrazil
- Department of Community and Behavioral HealthElson S. Floyd College of MedicineWashington State UniversitySpokaneWashingtonUSA
| | - Jacqueline Becker
- Division of General Internal MedicineIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Carolina Cappi
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Seaver Autism Center for Research and TreatmentIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of PsychiatryClinics HospitalUniversity of São PauloSchool of MedicineSão PauloSão PauloBrazil
| | - Andrea Horvath Marques
- Elliott School International AffairsThe George Washington UniversityWashingtonDistrict of ColumbiaUSA
| | - Patricia C. Heyn
- Center for Optimal AgingDepartment of Physical TherapyMarymount UniversityArlingtonVirginiaUSA
| | - Priscila Dib Gonçalves
- Department of EpidemiologyColumbia University Mailman School of Public HealthNew YorkNew YorkUSA
| | - Silvia S. Martins
- Department of EpidemiologyColumbia University Mailman School of Public HealthNew YorkNew YorkUSA
| | - Geraldo Busatto
- Laboratory of Psychiatric Neuroimaging (LIM‐21)Department of PsychiatryUniversity of São Paulo Medical SchoolSão PauloSão PauloBrazil
| | - Laiss Bertola
- Department of PsychiatryEscola Paulista de Medicina, Universidade Federal de São PauloSão PauloBrazil
| | - Claudia Kimie Suemoto
- Division of GeriatricsDepartment of Clinical MedicineUniversity of São Paulo Medical SchoolSão PauloSão PauloBrazil
| | - Ricardo Nitrini
- Old Age Research Group, Department of PsychiatryUniversity of São Paulo Medical SchoolSão PauloSão PauloBrazil
| | - Paulo Caramelli
- Behavioral and Cognitive Neurology Research GroupFaculdade de MedicinaUniversidade Federal de Minas GeraisBelo HorizonteMinas GeraisBrazil
| | - Monica Sanches Yassuda
- Department of NeurologyUniversity of São Paulo Medical SchoolSão PauloSão PauloBrazil
- Gerontology, School of Arts, Sciences, and HumanitiesUniversity of São PauloSão PauloSão PauloBrazil
| | - Eliane Correa Miotto
- Old Age Research Group, Department of PsychiatryUniversity of São Paulo Medical SchoolSão PauloSão PauloBrazil
| | - Lea Tenenholz Grinberg
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Department of PathologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- LIM‐22Department of PathologyUniversity of São Paulo Medical SchoolSão PauloSão PauloBrazil
- Global Brain Health InstituteUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Miguel Arce Renteria
- Cognitive Neuroscience DivisionDepartment of NeurologyColumbia UniversityVagelos College of Physicians and SurgeonsNew YorkNew YorkUSA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of NeurologyColumbia UniversityVagelos College of Physicians and SurgeonsNew YorkNew YorkUSA
| | - Margarita Alegria
- Disparities Research UnitDepartment of MedicineMassachusetts General HospitalBostonMassachusettsUSA
- Department of MedicineHarvard Medical SchoolBostonMassachusettsUSA
- Department of PsychiatryHarvard Medical SchoolBostonMassachusettsUSA
| | - Yaakov Stern
- Cognitive Neuroscience DivisionDepartment of NeurologyColumbia UniversityVagelos College of Physicians and SurgeonsNew YorkNew YorkUSA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of NeurologyColumbia UniversityVagelos College of Physicians and SurgeonsNew YorkNew YorkUSA
| | - Monica Rivera‐Mindt
- Department of PsychologyFordham UniversityNew YorkNew YorkUSA
- Department of NeurologyIcahn School of MedicineNew YorkNew YorkUSA
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Blanco-Vieira T, Radua J, Marcelino L, Bloch M, Mataix-Cols D, do Rosário MC. The genetic epidemiology of obsessive-compulsive disorder: a systematic review and meta-analysis. Transl Psychiatry 2023; 13:230. [PMID: 37380645 PMCID: PMC10307810 DOI: 10.1038/s41398-023-02433-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 04/04/2023] [Accepted: 04/14/2023] [Indexed: 06/30/2023] Open
Abstract
The first systematic review and meta-analysis of obsessive-compulsive disorder (OCD) genetic epidemiology was published approximately 20 years ago. Considering the relevance of all the studies published since 2001, the current study aimed to update the state-of-art knowledge on the field. All published data concerning the genetic epidemiology of OCD from the CENTRAL, MEDLINE, EMBASE, BVS, and OpenGrey databases were searched by two independent researchers until September 30, 2021. To be included, the articles had to fulfill the following criteria: OCD diagnosis provided by standardized and validated instruments; or medical records; inclusion of a control group for comparison and case-control, cohort or twin study designs. The analysis units were the first-degree relatives (FDRs) of OCD or control probands and the co-twins in twin pairs. The outcomes of interest were the familial recurrence rates of OCD and the correlations of OCS in monozygotic compared with dizygotic twins. Nineteen family, twenty-nine twin, and six population-based studies were included. The main findings were that OCD is a prevalent and highly familial disorder, especially among the relatives of children and adolescent probands, that OCD has a phenotypic heritability of around 50%; and that the higher OCS correlations between MZ twins were mainly due to additive genetic or to non-shared environmental components.
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Affiliation(s)
- Thiago Blanco-Vieira
- Child and Adolescent Psychiatry Unit (UPIA), Department of Psychiatry, Federal University of São Paulo (UNIFESP), São Paulo, Brazil.
| | - Joaquim Radua
- Institut d'Investigacions Biomediques August Pi i Sunyer, CIBERSAM, Instituto de Salud Carlos III, University of Barcelona, Barcelona, Spain
| | - Lívia Marcelino
- Child and Adolescent Psychiatry Unit (UPIA), Department of Psychiatry, Federal University of São Paulo (UNIFESP), São Paulo, Brazil
| | - Michael Bloch
- Yale Child Study Center, Yale University, School of Medicine, New Heaven, USA
| | - David Mataix-Cols
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
| | - Maria Conceição do Rosário
- Child and Adolescent Psychiatry Unit (UPIA), Department of Psychiatry, Federal University of São Paulo (UNIFESP), São Paulo, Brazil.
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Askeland RB, Hannigan LJ, O'Connell KS, Corfield EC, Frei O, Thapar A, Smith GD, Reichborn-Kjennerud T, Andreassen OA, Ask H, Havdahl A. Developmental manifestations of polygenic risk for bipolar disorder from infancy to middle childhood. Transl Psychiatry 2023; 13:222. [PMID: 37353490 PMCID: PMC10290060 DOI: 10.1038/s41398-023-02522-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 05/31/2023] [Accepted: 06/13/2023] [Indexed: 06/25/2023] Open
Abstract
Knowledge on how genetic risk for bipolar disorder manifests in developmental, emotional or behavioral traits during childhood is lacking. This issue is important to address to inform early detection and intervention efforts. We investigated whether polygenic risk for bipolar disorder is associated with developmental outcomes during early to middle childhood in the general population, and if associations differ between boys and girls. Our sample consisted of 28 001 children from the Norwegian Mother, Father and Child Cohort study, a prospective pregnancy cohort with available genotype and developmental data. Mothers reported on a range of developmental outcomes in their children at 6 and 18 months, 3, 5 and 8 years. Polygenic risk scores reflecting common variant liability to bipolar disorder were calculated. Linear regression models were used in a multi-group framework to investigate associations between polygenic risk score and developmental outcomes, using sex as a grouping variable. We found robust evidence for an association between polygenic risk scores for bipolar disorder and conduct difficulties (β = 0.041, CI = 0.020-0.062) and oppositional defiant difficulties (β = 0.032, CI = 0.014-0.051) at 8 years. Associations with most other outcomes were estimated within the region of practical equivalence to zero (equivalence range D = -0.1 to 0.1), with the exceptions of negative association for activity levels (β = -0.028, CI = -0.047- -0.010) at age 5 and benevolence (β = -0.025, CI = -0.043 to -0.008) at age 8, and positive association for motor difficulties (β = 0.025, CI = 0.008-0.043) at age 3, inattention (β = 0.021, CI = 0.003-0.041) and hyperactivity (β = 0.025, CI = 0.006-0.044) at age 8. Our results suggest that genetic risk for bipolar disorder manifests as disruptive behaviors like oppositional defiant and conduct difficulties in childhood in the general population.
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Affiliation(s)
- Ragna Bugge Askeland
- Department of Mental Disorders, Norwegian Institute of Public Health, 0473, Oslo, Norway.
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK.
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
| | - Laurie J Hannigan
- Department of Mental Disorders, Norwegian Institute of Public Health, 0473, Oslo, Norway
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Spångbergveien 25, 0853, Oslo, Norway
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, 0473, Oslo, Norway
| | - Kevin S O'Connell
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Elizabeth C Corfield
- Department of Mental Disorders, Norwegian Institute of Public Health, 0473, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Spångbergveien 25, 0853, Oslo, Norway
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, 0473, Oslo, Norway
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences; Centre for Neuropsychiatric Genetics and Genomics; Wolfson Centre for Young People's Mental Health, Cardiff University School of Medicine, Cardiff, Wales, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, 0473, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- KGJ Centre for Neurodevelopment, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Helga Ask
- Department of Mental Disorders, Norwegian Institute of Public Health, 0473, Oslo, Norway
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, 0473, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, 0373, Oslo, Norway
| | - Alexandra Havdahl
- Department of Mental Disorders, Norwegian Institute of Public Health, 0473, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Spångbergveien 25, 0853, Oslo, Norway
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, 0473, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, 0373, Oslo, Norway
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21
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Mooney MA, Ryabinin P, Morton H, Selah K, Gonoud R, Kozlowski M, Nousen E, Tipsord J, Antovich D, Schwartz J, Herting MM, Faraone SV, Nigg JT. Joint polygenic and environmental risks for childhood attention-deficit/hyperactivity disorder (ADHD) and ADHD symptom dimensions. JCPP ADVANCES 2023; 3:e12152. [PMID: 37753156 PMCID: PMC10519744 DOI: 10.1002/jcv2.12152] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 02/10/2023] [Indexed: 03/18/2023] Open
Abstract
Background attention-deficit/hyperactivity disorder (ADHD) is associated with both polygenic liability and environmental exposures, both intrinsic to the family, such as family conflict, and extrinsic, such as air pollution. However, much less is known about the interplay between environmental and genetic risks relevant to ADHD-a better understanding of which could inform both mechanistic models and clinical prediction algorithms. Methods Two independent data sets, the population-based Adolescent Brain Cognitive Development Study (ABCD) (N = 11,876) and the case-control Oregon-ADHD-1000 (N = 1449), were used to examine additive (G + E) and interactive (GxE) effects of selected polygenic risk scores (PRS) and environmental factors in a cross-sectional design. Genetic risk was measured using PRS for nine mental health disorders/traits. Exposures included family income, family conflict/negative sentiment, and geocoded measures of area deprivation, lead exposure risk, and air pollution exposure (nitrogen dioxide and fine particulate matter). Results ADHD PRS and family conflict jointly predicted concurrent ADHD symptoms in both cohorts. Additive-effects models, including both genetic and environmental factors, explained significantly more variation in symptoms than any individual factor alone (joint R 2 = .091 for total symptoms in ABCD; joint R 2 = .173 in Oregon-ADHD-1000; all delta-R 2 p-values <2e-7). Significant effect size heterogeneity across ancestry groups was observed for genetic and environmental factors (e.g., Q = 9.01, p = .011 for major depressive disorder PRS; Q = 13.34, p = .001 for area deprivation). GxE interactions observed in the full ABCD cohort suggested stronger environmental effects when genetic risk is low, though they did not replicate. Conclusions Reproducible additive effects of PRS and family environment on ADHD symptoms were found, but GxE interaction effects were not replicated and appeared confounded by ancestry. Results highlight the potential value of combining exposures and PRS in clinical prediction algorithms. The observed differences in risks across ancestry groups warrant further study to avoid health care disparities.
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Affiliation(s)
- Michael A. Mooney
- Division of Bioinformatics and Computational BiologyDepartment of Medical Informatics and Clinical EpidemiologyOregon Health & Science UniversityPortlandOregonUSA
- Knight Cancer InstituteOregon Health & Science UniversityPortlandOregonUSA
| | - Peter Ryabinin
- Knight Cancer InstituteOregon Health & Science UniversityPortlandOregonUSA
| | - Hannah Morton
- Department of PsychiatryCenter for ADHD ResearchOregon Health & Science UniversityPortlandOregonUSA
| | - Katharine Selah
- Department of PsychiatryCenter for ADHD ResearchOregon Health & Science UniversityPortlandOregonUSA
| | - Rose Gonoud
- Department of PsychiatryCenter for ADHD ResearchOregon Health & Science UniversityPortlandOregonUSA
| | - Michael Kozlowski
- Department of PsychiatryCenter for ADHD ResearchOregon Health & Science UniversityPortlandOregonUSA
| | - Elizabeth Nousen
- Department of PsychiatryCenter for ADHD ResearchOregon Health & Science UniversityPortlandOregonUSA
| | - Jessica Tipsord
- Department of PsychiatryCenter for ADHD ResearchOregon Health & Science UniversityPortlandOregonUSA
| | - Dylan Antovich
- Department of PsychiatryCenter for ADHD ResearchOregon Health & Science UniversityPortlandOregonUSA
| | - Joel Schwartz
- Department of Environmental HealthHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Megan M. Herting
- Department of Population and Public Health SciencesKeck School of Medicine of the University of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of PediatricsChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
| | - Stephen V. Faraone
- Department of PsychiatrySUNY Upstate Medical UniversitySyracuseNew YorkUSA
| | - Joel T. Nigg
- Department of PsychiatryCenter for ADHD ResearchOregon Health & Science UniversityPortlandOregonUSA
- Department of Behavioral NeuroscienceOregon Health & Science UniversityPortlandOregonUSA
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Dayan H, Shoham R, Berger I, Khoury-Kassabri M, Pollak Y. Features of attention deficit/hyperactivity disorder and antisocial behaviour in a general population-based sample of adults. CRIMINAL BEHAVIOUR AND MENTAL HEALTH : CBMH 2023; 33:172-184. [PMID: 37057691 DOI: 10.1002/cbm.2288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 03/29/2023] [Indexed: 06/03/2023]
Abstract
BACKGROUND Attention deficit/hyperactivity disorder (ADHD) is known to be a risk factor for antisocial and delinquent behaviour, but there is still a lack of information on how features of ADHD relate to offending behaviour among adults not already defined by their offending. AIMS Our aim was to add to knowledge about relationships between ADHD and antisocial behaviour among adults in the general population by answering the following questions: (A) Does the level of self-reported ADHD features relate to criminal and non-criminal antisocial behaviour? (B) To what extent are self-ratings of ADHD features independent of socio-demographic features previously identified as predictors of antisocial behaviour? METHODS A sample of adults was originally recruited to study public response to the COVID-19 outbreak through an online panel to be representative of the Israeli population. Among other scales, the 2025 participants completed an ADHD self-report scale, an antisocial behaviour self-report scale and a socio-demographic questionnaire probing for age, gender, urbanity, place of birth, socioeconomic status (education and income), family status (being in a relationship and having children) and religiosity. RESULTS Higher mean totals for the inattention and hyperactivity ADHD scale scores were associated with higher mean antisocial behaviour scores. These relationships were only slightly affected by socio-demographic variables, including sex, age, education and income. CONCLUSION Our findings suggest that not only may features of ADHD, even below a diagnostic threshold, constitute a risk factor for antisocial behaviour, but also that the self-rated levels of these problems covary. These findings are important for informing the early detection of risk of antisocial behaviour in the general population and its prevention.
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Affiliation(s)
- Haym Dayan
- Hebrew University of Jerusalem, Jerusalem, Israel
| | | | - Itai Berger
- Hebrew University of Jerusalem, Jerusalem, Israel
- Assuta Ashdod University Medical Center, Ashdod, Israel
- Faculty of Health Sciences, Ben-Gurion University, Beersheba, Israel
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23
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de la Paz L, Mooney MA, Ryabinin P, Neighbor C, Antovich D, Nigg JT, Nikolas MA. Youth Polygenic Scores, Youth ADHD Symptoms, and Parenting Dimensions: An Evocative Gene-Environment Correlation Study. Res Child Adolesc Psychopathol 2023; 51:665-677. [PMID: 36645612 PMCID: PMC10560546 DOI: 10.1007/s10802-023-01024-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/05/2023] [Indexed: 01/17/2023]
Abstract
Parenting practices and parental symptoms of attention-deficit/hyperactivity disorder (ADHD) have been linked to severity and course of youth ADHD. However, genetically influenced behaviors related to ADHD in youth may also influence parenting behaviors. Polygenic scores (PGS) have been widely used to quantify genetic vulnerability for ADHD but has rarely been used to examine gene-environment correlation effects. The current study examined the direct effects of youth ADHD PGS and its evocative effects on parenting behaviors via youth ADHD symptoms. 803 youth aged 6-18 years (58.5% male) completed a multistage, multi-informant assessment that included measures of parenting practices and youth and parental ADHD symptoms. A mediation model was used to evaluate direct and evocative effects. Furthermore, we examined if these evocative effects remain after controlling for parental ADHD symptoms. Sensitivity analyses across age, sex, and socioeconomic status (SES) as well as restricting ancestry groups to European only ancestry were also conducted. Results indicated that youth ADHD PGS reliably predicted youth ADHD symptoms across all models (βs ranging from 0.18 to 0.26), including across age, sex, and SES and held even with ancestry restricted to the largest group (northern European). Evocative effects emerged such that higher youth PGS significantly predicted more youth ADHD symptoms, which in turn, significantly predicted lower levels of parental involvement and higher levels of poor supervision/monitoring and inconsistent discipline. These effects remained after controlling for parent ADHD symptoms.
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Affiliation(s)
- Leiana de la Paz
- Department of Psychological and Brain Sciences, G60 Psychological and Brain Sciences Bldg., 340 Iowa Ave, Iowa City, IA, 52242, USA.
| | - Michael A Mooney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Peter Ryabinin
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | | | - Dylan Antovich
- Division of Psychology, Department of Psychiatry, Portland, OR, USA
| | - Joel T Nigg
- Division of Psychology, Department of Psychiatry, Portland, OR, USA
| | - Molly A Nikolas
- Department of Psychological and Brain Sciences, G60 Psychological and Brain Sciences Bldg., 340 Iowa Ave, Iowa City, IA, 52242, USA
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24
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Mollon J, Almasy L, Jacquemont S, Glahn DC. The contribution of copy number variants to psychiatric symptoms and cognitive ability. Mol Psychiatry 2023; 28:1480-1493. [PMID: 36737482 PMCID: PMC10213133 DOI: 10.1038/s41380-023-01978-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 01/18/2023] [Accepted: 01/20/2023] [Indexed: 02/05/2023]
Abstract
Copy number variants (CNVs) are deletions and duplications of DNA sequence. The most frequently studied CNVs, which are described in this review, are recurrent CNVs that occur in the same locations on the genome. These CNVs have been strongly implicated in neurodevelopmental disorders, namely autism spectrum disorder (ASD), intellectual disability (ID), and developmental delay (DD), but also in schizophrenia. More recent work has also shown that CNVs increase risk for other psychiatric disorders, namely, depression, bipolar disorder, and post-traumatic stress disorder. Many of the same CNVs are implicated across all of these disorders, and these neuropsychiatric CNVs are also associated with cognitive ability in the general population, as well as with structural and functional brain alterations. Neuropsychiatric CNVs also show incomplete penetrance, such that carriers do not always develop any psychiatric disorder, and may show only mild symptoms, if any. Variable expressivity, whereby the same CNVs are associated with many different phenotypes of varied severity, also points to highly complex mechanisms underlying disease risk in CNV carriers. Comprehensive and longitudinal phenotyping studies of individual CNVs have provided initial insights into these mechanisms. However, more work is needed to estimate and predict the effect of non-recurrent, ultra-rare CNVs, which also contribute to psychiatric and cognitive outcomes. Moreover, delineating the broader phenotypic landscape of neuropsychiatric CNVs in both clinical and general population cohorts may also offer important mechanistic insights.
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Affiliation(s)
- Josephine Mollon
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Laura Almasy
- Department of Genetics, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, USA
| | - Sebastien Jacquemont
- Department of Pediatrics, Université de Montréal, Montreal, QC, Canada
- Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, QC, Canada
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
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25
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Elkrief L, Lin B, Marchi M, Afzali MH, Banaschewski T, Bokde ALW, Quinlan EB, Desrivières S, Flor H, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Martinot MLP, Nees F, Orfanos DP, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Luykx J, Boks MP, Conrod PJ. Independent contribution of polygenic risk for schizophrenia and cannabis use in predicting psychotic-like experiences in young adulthood: testing gene × environment moderation and mediation. Psychol Med 2023; 53:1759-1769. [PMID: 37310336 PMCID: PMC10106286 DOI: 10.1017/s0033291721003378] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 07/20/2021] [Accepted: 07/26/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND It has not yet been determined if the commonly reported cannabis-psychosis association is limited to individuals with pre-existing genetic risk for psychotic disorders. METHODS We examined whether the relationship between polygenic risk score for schizophrenia (PRS-Sz) and psychotic-like experiences (PLEs), as measured by the Community Assessment of Psychic Experiences-42 (CAPE-42) questionnaire, is mediated or moderated by lifetime cannabis use at 16 years of age in 1740 of the individuals of the European IMAGEN cohort. Secondary analysis examined the relationships between lifetime cannabis use, PRS-Sz and the various sub-scales of the CAPE-42. Sensitivity analyses including covariates, including a PRS for cannabis use, were conducted and results were replicated using data from 1223 individuals in the Dutch Utrecht cannabis cohort. RESULTS PRS-Sz significantly predicted cannabis use (p = 0.027) and PLE (p = 0.004) in the IMAGEN cohort. In the full model, considering PRS-Sz and covariates, cannabis use was also significantly associated with PLE in IMAGEN (p = 0.007). Results remained consistent in the Utrecht cohort and through sensitivity analyses. Nevertheless, there was no evidence of a mediation or moderation effects. CONCLUSIONS These results suggest that cannabis use remains a risk factor for PLEs, over and above genetic vulnerability for schizophrenia. This research does not support the notion that the cannabis-psychosis link is limited to individuals who are genetically predisposed to psychosis and suggests a need for research focusing on cannabis-related processes in psychosis that cannot be explained by genetic vulnerability.
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Affiliation(s)
- Laurent Elkrief
- Sainte-Justine Hospital Research Center, Montréal, Québec, Canada
- Département de psychiatrie et d'addictologie, Université de Montréal, Montréal, QC, Canada
| | - Bochao Lin
- Department of Translational Neuroscience, Brain Center University Medical Center, Utrecht University, Utrecht, the Netherlands
| | - Mattia Marchi
- Department Psychiatry, Brain Center University Medical Center Utrecht, Utrecht, the Netherlands
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi, 287–41125 Modena, Italy
| | - Mohammad H Afzali
- Sainte-Justine Hospital Research Center, Montréal, Québec, Canada
- Département de psychiatrie et d'addictologie, Université de Montréal, Montréal, QC, Canada
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L. W. Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, United Kingdom
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, United Kingdom
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, Vermont, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Charité – Universitätsmedizin Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2 - 12, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Saclay, University Paris Descartes - Sorbonne Paris Cité; and Maison de Solenn, Paris, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud, University Paris Descartes; and AP-HP.Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Tomáš Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H. Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N. Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Charité – Universitätsmedizin Berlin, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charitéplatz 1, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, United Kingdom
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
- PONS Research Group, Dept of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, Berlin and Leibniz Institute for Neurobiology, Magdeburg, Germany, and Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, P.R. China
| | - Jurjen Luykx
- Department Psychiatry, Brain Center University Medical Center Utrecht, Utrecht, the Netherlands
| | - Marco P. Boks
- Department Psychiatry, Brain Center University Medical Center Utrecht, Utrecht, the Netherlands
| | - Patricia J. Conrod
- Sainte-Justine Hospital Research Center, Montréal, Québec, Canada
- Département de psychiatrie et d'addictologie, Université de Montréal, Montréal, QC, Canada
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26
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Repetto L, Chen J, Yang Z, Zhai R, Timmers PRHJ, Li T, Twait EL, May-Wilson S, Muckian MD, Prins BP, Png G, Kooperberg C, Johansson Å, Hillary RF, Wheeler E, Pan L, He Y, Klasson S, Ahmad S, Peters JE, Gilly A, Karaleftheri M, Tsafantakis E, Haessler J, Gyllensten U, Harris SE, Wareham NJ, Göteson A, Lagging C, Ikram MA, van Duijn CM, Jern C, Landén M, Langenberg C, Deary IJ, Marioni RE, Enroth S, Reiner AP, Dedoussis G, Zeggini E, Butterworth AS, Mälarstig A, Wilson JF, Navarro P, Shen X. Unraveling Neuro-Proteogenomic Landscape and Therapeutic Implications for Human Behaviors and Psychiatric Disorders. RESEARCH SQUARE 2023:rs.3.rs-2720355. [PMID: 37034613 PMCID: PMC10081382 DOI: 10.21203/rs.3.rs-2720355/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioral traits and the disease etiology of neuropsychiatric disorders. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits such as sleeping, smoking, feelings, alcohol intake, mental health, and psychiatric disorders. Integrating with established drug information, we validated 13 out of 13 matched combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets. This consortium effort provides a large-scale proteogenomic resource for biomedical research on human behaviors and other neuro-related phenotypes.
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Affiliation(s)
- Linda Repetto
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
| | - Jiantao Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Zhijian Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Ranran Zhai
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Paul R. H. J. Timmers
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ting Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Emma L. Twait
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrechtand Utrecht University, Utrecht, Netherlands
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Marisa D. Muckian
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Bram P. Prins
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Grace Png
- Institute of Translational Genomics, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM), School of Medicine, 81675 Munich, Germany
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle USA
| | - Åsa Johansson
- Dept. Immunology, Genetics and Pathology, Science for life laboratory, Uppsala University, Sweden
| | - Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, United Kingdom
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Lu Pan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yazhou He
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Sofia Klasson
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Shahzad Ahmad
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands
| | - James E. Peters
- Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Arthur Gilly
- Institute of Translational Genomics, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
| | | | | | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle USA
| | - Ulf Gyllensten
- Dept. Immunology, Genetics and Pathology, Science for life laboratory, Uppsala University, Sweden
| | - Sarah E. Harris
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Andreas Göteson
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Cecilia Lagging
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Clinical Genetics and Genomics, Gothenburg, Sweden
| | | | | | - Christina Jern
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Mikael Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité – Universitätsmedizin Berlin, Germany
| | - Ian J. Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, United Kingdom
| | - Stefan Enroth
- Dept. Immunology, Genetics and Pathology, Science for life laboratory, Uppsala University, Sweden
| | - Alexander P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Center and Department of Epidemiology, University of Washington, Seattle USA
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | - Adam S. Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Emerging Science and Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, UK
| | - James F. Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Pau Navarro
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Xia Shen
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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27
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Wolff B, Franco VR, Magiati I, Cooper MN, Roberts R, Skoss R, Glasson EJ. Individual-Level Risk and Resilience Factors Associated with Mental Health in Siblings of Individuals with Neurodevelopmental Conditions: A Network Analysis. Dev Neuropsychol 2023; 48:112-134. [PMID: 36942456 DOI: 10.1080/87565641.2023.2190119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
Siblings of individuals with neurodevelopmental conditions (NDCs) are exposed to unique family environments and experience a range of psychosocial risk and resilience factors. Networks of self-reported risk, resilience, and neuropsychiatric variables were estimated for siblings of individuals with (n = 235) and without (n = 480) NDCs (N = 715, mean age 22.40 years, 76% female, 74% White Caucasian). The NDC group reported more depressive (g = 0.39) and anxious (g = 0.43) symptoms than controls, and 71.5% of the NDC group reported at least one neuropsychiatric diagnosis compared to 36.9% of controls. Self-reported sleep and post-traumatic stress disorders were high amongst NDC siblings. Everyday executive functioning difficulties (cognitive inflexibility, hyperactivity/impulsivity) and emotion dysregulation were the most influential transdiagnostic risk factors for poorer functioning within the NDC group network.
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Affiliation(s)
- Brittany Wolff
- School of Psychological Science, The University of Western Australia, Perth, Australia
- Telethon Kids Institute , Centre for Child Health Research, The University of Western Australia, Perth, Australia
| | - Vithor R Franco
- Department of Psych ology, São Francisco University, Campinas, Brazil
| | - Iliana Magiati
- School of Psychological Science, The University of Western Australia, Perth, Australia
| | - Matthew N Cooper
- Telethon Kids Institute , Centre for Child Health Research, The University of Western Australia, Perth, Australia
| | - Rachel Roberts
- School of Psychology, The University of Adelaide, Adelaide, Australia
| | - Rachel Skoss
- Telethon Kids Institute , Centre for Child Health Research, The University of Western Australia, Perth, Australia
- Institute for Health Research, The University of Notre Dame Australia, Perth, Australia
- School of Population and Global Health, The University of Western Australia
| | - Emma J Glasson
- Telethon Kids Institute , Centre for Child Health Research, The University of Western Australia, Perth, Australia
- Discipline of Psychiatry, Medical School, The University of Western Australia, WA, Perth, Australia
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28
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Maxwell J, Ronald A, Cardno AG, Breen G, Rimfeld K, Vassos E. Genetic and Geographical Associations With Six Dimensions of Psychotic Experiences in Adolesence. Schizophr Bull 2023; 49:319-328. [PMID: 36287640 PMCID: PMC10016405 DOI: 10.1093/schbul/sbac149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND AND HYPOTHESIS Large-scale epidemiological and genetic research have shown that psychotic experiences in the community are risk factors for adverse physical and psychiatric outcomes. We investigated the associations of six types of specific psychotic experiences and negative symptoms assessed in mid-adolescence with well-established environmental and genetic risk factors for psychosis. STUDY DESIGN Fourteen polygenic risk scores (PRS) and nine geographical environmental variables from 3590 participants of the Twins Early Development Study (mean age 16) were associated with paranoia, hallucinations, cognitive disorganization, grandiosity, anhedonia, and negative symptoms scales. The predictors were modeled using LASSO regularization separately (Genetic and Environmental models) and jointly (GE model). STUDY RESULTS In joint GE models, we found significant genetic associations of negative symptoms with educational attainment PRS (β = -.07; 95% CI = -0.12 to -0.04); cognitive disorganization with neuroticism PRS (β = .05; 95% CI = 0.03-0.08); paranoia with MDD (β = .07; 95% CI = 0.04-0.1), BMI (β = .05; 95% CI = 0.02-0.08), and neuroticism PRS (β = .05; 95% CI = 0.02-0.08). From the environmental measures only family SES (β = -.07, 95% CI = -0.10 to -0.03) and regional education levels (β = -.06; 95% CI = -0.09 to -0.02) were associated with negative symptoms. CONCLUSIONS Our findings advance understanding of how genetic propensity for psychiatric, cognitive, and anthropometric traits, as well as environmental factors, together play a role in creating vulnerability for specific psychotic experiences and negative symptoms in mid-adolescence.
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Affiliation(s)
- Jessye Maxwell
- Social Genetic and Developmental Psychiatric Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Angelica Ronald
- Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Alastair G Cardno
- Division of Psychological and Social Medicine, University of Leeds, Leeds, UK
| | - Gerome Breen
- Social Genetic and Developmental Psychiatric Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Kaili Rimfeld
- Social Genetic and Developmental Psychiatric Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- Department of Psychology, Royal Holloway, University of London, Surrey, UK
| | - Evangelos Vassos
- Social Genetic and Developmental Psychiatric Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
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29
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Fan HC, Chiang KL, Chang KH, Chen CM, Tsai JD. Epilepsy and Attention Deficit Hyperactivity Disorder: Connection, Chance, and Challenges. Int J Mol Sci 2023; 24:ijms24065270. [PMID: 36982345 PMCID: PMC10049646 DOI: 10.3390/ijms24065270] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/20/2023] [Accepted: 03/01/2023] [Indexed: 03/12/2023] Open
Abstract
Comorbidities are common in children with epilepsy, with nearly half of the patients having at least one comorbidity. Attention deficit hyperactivity disorder (ADHD) is a psychiatric disorder characterized by hyperactivity and inattentiveness level disproportional to the child’s developmental stage. The burden of ADHD in children with epilepsy is high and can adversely affect the patients’ clinical outcomes, psychosocial aspects, and quality of life. Several hypotheses were proposed to explain the high burden of ADHD in childhood epilepsy; the well-established bidirectional connection and shared genetic/non-genetic factors between epilepsy and comorbid ADHD largely rule out the possibility of a chance in this association. Stimulants are effective in children with comorbid ADHD, and the current body of evidence supports their safety within the approved dose. Nonetheless, safety data should be further studied in randomized, double-blinded, placebo-controlled trials. Comorbid ADHD is still under-recognized in clinical practice. Early identification and management of comorbid ADHD are crucial to optimize the prognosis and reduce the risk of adverse long-term neurodevelopmental outcomes. The identification of the shared genetic background of epilepsy and ADHD can open the gate for tailoring treatment options for these patients through precision medicine.
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Affiliation(s)
- Hueng-Chuen Fan
- Department of Pediatrics, Tungs’ Taichung Metroharbor Hospital, Wuchi, Taichung 435, Taiwan
- Department of Rehabilitation, Jen-Teh Junior College of Medicine, Nursing and Management, Miaoli 356, Taiwan
- Department of Life Sciences, Agricultural Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan
| | - Kuo-Liang Chiang
- Department of Pediatric Neurology, Kuang-Tien General Hospital, Taichung 433, Taiwan
- Department of Nutrition, Hungkuang University, Taichung 433, Taiwan
| | - Kuang-Hsi Chang
- Department of Medical Research, Tungs’ Taichung Metroharbor Hospital, Wuchi, Taichung 435, Taiwan
| | - Chuan-Mu Chen
- Department of Life Sciences, Agricultural Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan
- The iEGG and Animal Biotechnology Center, and Rong Hsing Research Center for Translational Medicine, National Chung Hsing University, Taichung 402, Taiwan
- Correspondence: (C.-M.C.); (J.-D.T.); Tel.: +886-4-22840319-701 (C.-M.C.); +886-4-24730022-21731 (J.-D.T.)
| | - Jeng-Dau Tsai
- School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
- Department of Pediatrics, Chung Shan Medical University Hospital, Taichung 402, Taiwan
- Correspondence: (C.-M.C.); (J.-D.T.); Tel.: +886-4-22840319-701 (C.-M.C.); +886-4-24730022-21731 (J.-D.T.)
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30
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Gustavson DE, Coleman PL, Wang Y, Nitin R, Petty LE, Bush CT, Mosing MA, Wesseldijk LW, Ullén F, Below JE, Cox NJ, Gordon RL. Exploring the genetics of rhythmic perception and musical engagement in the Vanderbilt Online Musicality Study. Ann N Y Acad Sci 2023; 1521:140-154. [PMID: 36718543 PMCID: PMC10038917 DOI: 10.1111/nyas.14964] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Uncovering the genetic underpinnings of musical ability and engagement is a foundational step for exploring their wide-ranging associations with cognition, health, and neurodevelopment. Prior studies have focused on using twin and family designs, demonstrating moderate heritability of musical phenotypes. The current study used genome-wide complex trait analysis and polygenic score (PGS) approaches utilizing genotype data to examine genetic influences on two musicality traits (rhythmic perception and music engagement) in N = 1792 unrelated adults in the Vanderbilt Online Musicality Study. Meta-analyzed heritability estimates (including a replication sample of Swedish individuals) were 31% for rhythmic perception and 12% for self-reported music engagement. A PGS derived from a recent study on beat synchronization ability predicted both rhythmic perception (β = 0.11) and music engagement (β = 0.19) in our sample, suggesting that genetic influences underlying self-reported beat synchronization ability also influence individuals' rhythmic discrimination aptitude and the degree to which they engage in music. Cross-trait analyses revealed a modest contribution of PGSs from several nonmusical traits (from the cognitive, personality, and circadian chronotype domains) to individual differences in musicality (β = -0.06 to 0.07). This work sheds light on the complex relationship between the genetic architecture of musical rhythm processing, beat synchronization, music engagement, and other nonmusical traits.
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Affiliation(s)
- Daniel E Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peyton L Coleman
- School of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Youjia Wang
- Department of Otolaryngology - Head & Neck Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Rachana Nitin
- Department of Otolaryngology - Head & Neck Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Catherine T Bush
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Miriam A Mosing
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Cognitive Neuropsychology, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany
- Melbourne School of Psychological Sciences, Faculty of Medicine, Dentistry, and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Laura W Wesseldijk
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Cognitive Neuropsychology, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany
- Melbourne School of Psychological Sciences, Faculty of Medicine, Dentistry, and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Fredrik Ullén
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Cognitive Neuropsychology, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Reyna L Gordon
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Otolaryngology - Head & Neck Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Psychology, Vanderbilt University, Nashville, Tennessee, USA
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31
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Dinkler L, Wronski ML, Lichtenstein P, Lundström S, Larsson H, Micali N, Taylor MJ, Bulik CM. Etiology of the Broad Avoidant Restrictive Food Intake Disorder Phenotype in Swedish Twins Aged 6 to 12 Years. JAMA Psychiatry 2023; 80:260-269. [PMID: 36723946 PMCID: PMC9978946 DOI: 10.1001/jamapsychiatry.2022.4612] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Importance Avoidant restrictive food intake disorder (ARFID) is characterized by an extremely limited range and/or amount of food eaten, resulting in the persistent failure to meet nutritional and/or energy needs. Its etiology is poorly understood, and knowledge of genetic and environmental contributions to ARFID is needed to guide future research. Objective To estimate the extent to which genetic and environmental factors contribute to the liability to the broad ARFID phenotype. Design, Setting, and Participants This nationwide Swedish twin study includes 16 951 twin pairs born between 1992 and 2010 whose parents participated in the Child and Adolescent Twin Study in Sweden (CATSS) at twin age 9 or 12 years. CATSS was linked to the National Patient Register (NPR) and the Prescribed Drug Register (PDR). Data were collected from July 2004 to April 2020, and data were analyzed from October 2021 to October 2022. Main Outcomes and Measures From CATSS, NPR, and PDR, all parent reports, diagnoses, procedures, and prescribed drugs that were relevant to the DSM-5 ARFID criteria were extracted when twin pairs were aged 6 to 12 years and integrated into a composite measure for the ARFID phenotype (ie, avoidant/restrictive eating with clinically significant impact, such as low weight or nutritional deficiency, and with fear of weight gain as an exclusion). In sensitivity analyses, autism and medical conditions that could account for the eating disturbance were controlled for. Univariate liability threshold models were fitted to estimate the relative contribution of genetic and environmental variation to the liability to the ARFID phenotype. Results Of 33 902 included children, 17 151 (50.6%) were male. A total of 682 children (2.0%) with the ARFID phenotype were identified. The heritability of ARFID was 0.79 (95% CI, 0.70-0.85), with significant contributions from nonshared environmental factors (0.21; 95% CI, 0.15-0.30). Heritability was very similar when excluding children with autism (0.77; 95% CI, 0.67-0.84) or medical illnesses that could account for the eating disturbance (0.79; 95% CI, 0.70-0.86). Conclusions and Relevance Prevalence and sex distribution of the broad ARFID phenotype were similar to previous studies, supporting the use of existing epidemiological data to identify children with ARFID. This study of the estimated genetic and environmental etiology of ARFID suggests that ARFID is highly heritable, encouraging future twin and molecular genetic studies.
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Affiliation(s)
- Lisa Dinkler
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Marie-Louis Wronski
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany,Neuroendocrine Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Nadia Micali
- Mental Health Services in the Capital Region of Denmark, Eating Disorders Research Unit, Psychiatric Centre Ballerup, Copenhagen, Denmark,Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Mark J. Taylor
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Cynthia M. Bulik
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden,Department of Psychiatry, University of North Carolina at Chapel Hill,Department of Nutrition, University of North Carolina at Chapel Hill
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32
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Prenatal Androgen Exposure and Traits of Autism Spectrum Disorder in the Offspring: Odense Child Cohort. J Autism Dev Disord 2023; 53:1053-1065. [PMID: 35124780 DOI: 10.1007/s10803-022-05446-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2022] [Indexed: 10/19/2022]
Abstract
Fetal androgen exposure may be associated with autism spectrum disorder (ASD). We studied 1777 mother-child pairs in the prospective Odense Child Cohort. Prenatal androgen exposure was assessed by maternal 3rd trimester testosterone concentrations, maternal polycystic ovary syndrome (PCOS), and 3 months offspring anogenital distance. ASD traits were assessed at age 3 years with the ASD-symptom scale of the Child Behavior Checklist for ages 1½-5 years. Maternal testosterone was positively associated with traits of ASD in boys (p < 0.05). Maternal PCOS was associated with increased offspring ASD traits (p = 0.046), but became non-significant after excluding parental psychiatric diagnosis. Offspring anogenital distance was not linked to ASD traits. Higher prevalence of ASD in boys could be linked to higher susceptibility to fetal androgen exposure.
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33
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Repetto L, Chen J, Yang Z, Zhai R, Timmers PRHJ, Li T, Twait EL, May-Wilson S, Muckian MD, Prins BP, Png G, Kooperberg C, Johansson Å, Hillary RF, Wheeler E, Pan L, He Y, Klasson S, Ahmad S, Peters JE, Gilly A, Karaleftheri M, Tsafantakis E, Haessler J, Gyllensten U, Harris SE, Wareham NJ, Göteson A, Lagging C, Ikram MA, van Duijn CM, Jern C, Landén M, Langenberg C, Deary IJ, Marioni RE, Enroth S, Reiner AP, Dedoussis G, Zeggini E, Butterworth AS, Mälarstig A, Wilson JF, Navarro P, Shen X. Genetic mechanisms of 184 neuro-related proteins in human plasma. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.10.23285650. [PMID: 36824751 PMCID: PMC9949195 DOI: 10.1101/2023.02.10.23285650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Understanding the genetic basis of neuro-related proteins is essential for dissecting the disease etiology of neuropsychiatric disorders and other complex traits and diseases. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-reiated proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-reiated traits as well as complex diseases such as hypertension, high cholesterol, immune-related disorders, and psychiatric disorders. Integrating with established drug information, we validated 13 combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets for diseases and comorbidities. This consortium effort provides a large-scale proteogenomic resource for biomedical research.
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Affiliation(s)
- Linda Repetto
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
| | - Jiantao Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Zhijian Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Ranran Zhai
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Paul R. H. J. Timmers
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ting Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Emma L. Twait
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, Netherlands
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Marisa D. Muckian
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Bram P. Prins
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Grace Png
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM), School of Medicine, 81675 Munich, Germany
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle USA
| | - Åsa Johansson
- Dept. Immunology, Genetics and Pathology, Science for life laboratory, Uppsala University, Sweden
| | - Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, United Kingdom
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Lu Pan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yazhou He
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Sofia Klasson
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Shahzad Ahmad
- Department of Epidemiology, ErasmusMC, Rotterdam, The Netherlands
| | - James E. Peters
- Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Arthur Gilly
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | | | | | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle USA
| | - Ulf Gyllensten
- Dept. Immunology, Genetics and Pathology, Science for life laboratory, Uppsala University, Sweden
| | - Sarah E. Harris
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Andreas Göteson
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Cecilia Lagging
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Clinical Genetics and Genomics, Gothenburg, Sweden
| | | | | | - Christina Jern
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Mikael Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Biomedicine, Department of Laboratory Medicine, the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Germany
| | - Ian J. Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ, United Kingdom
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, United Kingdom
| | - Stefan Enroth
- Dept. Immunology, Genetics and Pathology, Science for life laboratory, Uppsala University, Sweden
| | - Alexander P. Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Center and Department of Epidemiology, University of Washington, Seattle USA
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University of Athens, Athens, Greece
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany
| | - Adam S. Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
| | - Anders Mälarstig
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Emerging Science and Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, UK
| | - James F. Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Pau Navarro
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Xia Shen
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University, Guangzhou, China
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Division of Public Health Sciences, Fred Hutchinson Cancer Center and Department of Epidemiology, University of Washington, Seattle USA
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34
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Cortese S, Solmi M, Michelini G, Bellato A, Blanner C, Canozzi A, Eudave L, Farhat LC, Højlund M, Köhler-Forsberg O, Leffa DT, Rohde C, de Pablo GS, Vita G, Wesselhoeft R, Martin J, Baumeister S, Bozhilova NS, Carlisi CO, Leno VC, Floris DL, Holz NE, Kraaijenvanger EJ, Sacu S, Vainieri I, Ostuzzi G, Barbui C, Correll CU. Candidate diagnostic biomarkers for neurodevelopmental disorders in children and adolescents: a systematic review. World Psychiatry 2023; 22:129-149. [PMID: 36640395 PMCID: PMC9840506 DOI: 10.1002/wps.21037] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/07/2022] [Indexed: 01/15/2023] Open
Abstract
Neurodevelopmental disorders - including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disability, motor disorders, specific learning disorders, and tic disorders - manifest themselves early in development. Valid, reliable and broadly usable biomarkers supporting a timely diagnosis of these disorders would be highly relevant from a clinical and public health standpoint. We conducted the first systematic review of studies on candidate diagnostic biomarkers for these disorders in children and adolescents. We searched Medline and Embase + Embase Classic with terms relating to biomarkers until April 6, 2022, and conducted additional targeted searches for genome-wide association studies (GWAS) and neuroimaging or neurophysiological studies carried out by international consortia. We considered a candidate biomarker as promising if it was reported in at least two independent studies providing evidence of sensitivity and specificity of at least 80%. After screening 10,625 references, we retained 780 studies (374 biochemical, 203 neuroimaging, 133 neurophysiological and 65 neuropsychological studies, and five GWAS), including a total of approximately 120,000 cases and 176,000 controls. While the majority of the studies focused simply on associations, we could not find any biomarker for which there was evidence - from two or more studies from independent research groups, with results going into the same direction - of specificity and sensitivity of at least 80%. Other important metrics to assess the validity of a candidate biomarker, such as positive predictive value and negative predictive value, were infrequently reported. Limitations of the currently available studies include mostly small sample size, heterogeneous approaches and candidate biomarker targets, undue focus on single instead of joint biomarker signatures, and incomplete accounting for potential confounding factors. Future multivariable and multi-level approaches may be best suited to find valid candidate biomarkers, which will then need to be validated in external, independent samples and then, importantly, tested in terms of feasibility and cost-effectiveness, before they can be implemented in daily clinical practice.
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Affiliation(s)
- Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Solent NHS Trust, Southampton, UK
- Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York, NY, USA
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
| | - Marco Solmi
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada
- Department of Mental Health, Ottawa Hospital, Ottawa, ON, Canada
- Ottawa Hospital Research Institute (OHRI) Clinical Epidemiology Program, University of Ottawa, Ottawa, ON, Canada
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
| | - Giorgia Michelini
- Department of Biological & Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Alessio Bellato
- School of Psychology, University of Nottingham, Semenyih, Malaysia
| | - Christina Blanner
- Mental Health Center, Glostrup, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
| | - Andrea Canozzi
- Department of Neuroscience, Biomedicine, and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Luis Eudave
- Faculty of Education and Psychology, University of Navarra, Pamplona, Spain
| | - Luis C Farhat
- Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Mikkel Højlund
- Department of Psychiatry Aabenraa, Mental Health Services in the Region of Southern Denmark, Aabenraa, Denmark
- Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Ole Köhler-Forsberg
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Douglas Teixeira Leffa
- ADHD Outpatient Program & Development Psychiatry Program, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Christopher Rohde
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Affective Disorders, Aarhus University Hospital - Psychiatry, Aarhus, Denmark
| | - Gonzalo Salazar de Pablo
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Child and Adolescent Mental Health Services, South London and Maudsley NHS Foundation Trust, London, UK
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, CIBERSAM, Madrid, Spain
| | - Giovanni Vita
- Department of Neuroscience, Biomedicine, and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Rikke Wesselhoeft
- Clinical Pharmacology, Pharmacy, and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Child and Adolescent Mental Health Odense, Mental Health Services in the Region of Southern Denmark, Odense, Denmark
| | - Joanna Martin
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Natali S Bozhilova
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- School of Psychology, University of Surrey, Guilford, UK
| | - Christina O Carlisi
- Division of Psychology and Language Sciences, University College London, London, UK
| | - Virginia Carter Leno
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Dorothea L Floris
- Department of Psychology, University of Zurich, Zurich, Switzerland
- Donders Institute for Brain, Cognition, and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Nathalie E Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
- Donders Institute for Brain, Cognition, and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | - Eline J Kraaijenvanger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Seda Sacu
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Isabella Vainieri
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Giovanni Ostuzzi
- Department of Neuroscience, Biomedicine, and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Corrado Barbui
- Department of Neuroscience, Biomedicine, and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Christoph U Correll
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
- Psychiatry Research, Northwell Health, Zucker Hillside Hospital, New York, NY, USA
- Department of Psychiatry and Molecular Medicine, Zucker School of Medicine, Hempstead, NY, USA
- Center for Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA
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35
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Baldwin JR, Sallis HM, Schoeler T, Taylor MJ, Kwong ASF, Tielbeek JJ, Barkhuizen W, Warrier V, Howe LD, Danese A, McCrory E, Rijsdijk F, Larsson H, Lundström S, Karlsson R, Lichtenstein P, Munafò M, Pingault JB. A genetically informed Registered Report on adverse childhood experiences and mental health. Nat Hum Behav 2023; 7:269-290. [PMID: 36482079 PMCID: PMC7614239 DOI: 10.1038/s41562-022-01482-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 10/13/2022] [Indexed: 12/13/2022]
Abstract
Children who experience adversities have an elevated risk of mental health problems. However, the extent to which adverse childhood experiences (ACEs) cause mental health problems remains unclear, as previous associations may partly reflect genetic confounding. In this Registered Report, we used DNA from 11,407 children from the United Kingdom and the United States to investigate gene-environment correlations and genetic confounding of the associations between ACEs and mental health. Regarding gene-environment correlations, children with higher polygenic scores for mental health problems had a small increase in odds of ACEs. Regarding genetic confounding, elevated risk of mental health problems in children exposed to ACEs was at least partially due to pre-existing genetic risk. However, some ACEs (such as childhood maltreatment and parental mental illness) remained associated with mental health problems independent of genetic confounding. These findings suggest that interventions addressing heritable psychiatric vulnerabilities in children exposed to ACEs may help reduce their risk of mental health problems.
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Affiliation(s)
- Jessie R Baldwin
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, University College London, London, UK.
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Hannah M Sallis
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol Medical School, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tabea Schoeler
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - Mark J Taylor
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Alex S F Kwong
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol Medical School, University of Bristol, Bristol, UK
- Division of Psychiatry, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Jorim J Tielbeek
- CNCR, Amsterdam Neuroscience Campus, VU University, Amsterdam, the Netherlands
| | - Wikus Barkhuizen
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrea Danese
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National and Specialist CAMHS Trauma, Anxiety, and Depression Clinic, South London and Maudsley NHS Foundation Trust, London, UK
| | - Eamon McCrory
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, University College London, London, UK
- Anna Freud National Centre for Children and Families, London, UK
| | - Fruhling Rijsdijk
- Psychology Department, Faculty of Social Sciences, Anton de Kom University, Paramaribo, Suriname
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Centre for Ethics, Law and Mental Health (CELAM), Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Marcus Munafò
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol Medical School, University of Bristol, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Jean-Baptiste Pingault
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, University College London, London, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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da Silva BS, Grevet EH, Silva LCF, Ramos JKN, Rovaris DL, Bau CHD. An overview on neurobiology and therapeutics of attention-deficit/hyperactivity disorder. DISCOVER MENTAL HEALTH 2023; 3:2. [PMID: 37861876 PMCID: PMC10501041 DOI: 10.1007/s44192-022-00030-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 12/29/2022] [Indexed: 10/21/2023]
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent psychiatric condition characterized by developmentally inappropriate symptoms of inattention and/or hyperactivity/impulsivity, which leads to impairments in the social, academic, and professional contexts. ADHD diagnosis relies solely on clinical assessment based on symptom evaluation and is sometimes challenging due to the substantial heterogeneity of the disorder in terms of clinical and pathophysiological aspects. Despite the difficulties imposed by the high complexity of ADHD etiology, the growing body of research and technological advances provide good perspectives for understanding the neurobiology of the disorder. Such knowledge is essential to refining diagnosis and identifying new therapeutic options to optimize treatment outcomes and associated impairments, leading to improvements in all domains of patient care. This review is intended to be an updated outline that addresses the etiological and neurobiological aspects of ADHD and its treatment, considering the impact of the "omics" era on disentangling the multifactorial architecture of ADHD.
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Affiliation(s)
- Bruna Santos da Silva
- ADHD and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
- Department of Genetics and Graduate Program in Genetics and Molecular Biology, Instituto de Biociências, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
- Department of Physiology and Biophysics, Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Institute of Biomedical Sciences, University of Sao Paulo, São Paulo, Brazil
| | - Eugenio Horacio Grevet
- ADHD and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
- Department of Psychiatry and Graduate Program in Psychiatry and Behavioral Sciences, Faculdade de Medicina, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
| | - Luiza Carolina Fagundes Silva
- ADHD and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
- Department of Psychiatry and Graduate Program in Psychiatry and Behavioral Sciences, Faculdade de Medicina, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil
| | - João Kleber Neves Ramos
- Department of Physiology and Biophysics, Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Institute of Biomedical Sciences, University of Sao Paulo, São Paulo, Brazil
| | - Diego Luiz Rovaris
- Department of Physiology and Biophysics, Instituto de Ciencias Biomedicas Universidade de Sao Paulo, São Paulo, Brazil
- Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Institute of Biomedical Sciences, University of Sao Paulo, São Paulo, Brazil
| | - Claiton Henrique Dotto Bau
- ADHD and Developmental Psychiatry Programs, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil.
- Department of Genetics and Graduate Program in Genetics and Molecular Biology, Instituto de Biociências, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil.
- Department of Psychiatry and Graduate Program in Psychiatry and Behavioral Sciences, Faculdade de Medicina, Universidade Federal Do Rio Grande Do Sul, Porto Alegre, Brazil.
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Fan HC, Chen CM, Tsai JD, Chiang KL, Tsai SCS, Huang CY, Lin CL, Hsu CY, Chang KH. Association between Exposure to Particulate Matter Air Pollution during Early Childhood and Risk of Attention-Deficit/Hyperactivity Disorder in Taiwan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph192316138. [PMID: 36498210 PMCID: PMC9740780 DOI: 10.3390/ijerph192316138] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 11/23/2022] [Accepted: 11/27/2022] [Indexed: 05/23/2023]
Abstract
(1) Background: Recently, a growing number of studies have provided evidence to suggest a strong correlation between air pollution exposure and attention-deficit/hyperactivity disorder (ADHD). In this study, we assessed the relationship between early-life exposure to particulate matter (PM)10, PM2.5, and ADHD; (2) Methods: The National Health Insurance Research Database (NHIRD) contains the medical records, drug information, inspection data, etc., of the people of Taiwan, and, thus, could serve as an important research resource. Air pollution data were based on daily data from the Environmental Protection Administration Executive Yuan, R.O.C. (Taiwan). These included particulate matter (PM2.5 and PM10). The two databases were merged according to the living area of the insured and the location of the air quality monitoring station; (3) Results: The highest levels of air pollutants, including PM2.5 (adjusted hazard ratio (aHR) = 1.79; 95% confidence interval (CI) = 1.58-2.02) and PM10 (aHR = 1.53; 95% CI = 1.37-1.70), had a significantly higher risk of ADHD; (4) Conclusions: As such, measures for air quality control that meet the WHO air quality guidelines should be strictly and uniformly implemented by Taiwanese government authorities.
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Affiliation(s)
- Hueng-Chuen Fan
- Department of Pediatrics, Tungs’ Taichung Metroharbor Hospital, Wuchi, Taichung 435, Taiwan
- Department of Rehabilitation, Jen-Teh Junior College of Medicine, Nursing and Management, Miaoli 356, Taiwan
- Department of Life Sciences, Agricultural Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan
| | - Chuan-Mu Chen
- The iEGG and Animal Biotechnology Center, and Rong Hsing Research Center for Translational Medicine, National Chung Hsing University, Taichung 402, Taiwan
- Ph.D. Program in Translational Medicine, Department of Life Sciences, National Chung Hsing University, Taichung 402, Taiwan
- Rong Hsing Research Center for Translational Medicine, College of Life Sciences, National Chung Hsing University, Taichung 402, Taiwan
| | - Jeng-Dau Tsai
- School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
- Department of Pediatrics, Chung Shan Medical University Hospital, Taichung 402, Taiwan
| | - Kuo-Liang Chiang
- Department of Pediatric Neurology, Kuang-Tien General Hospital, Taichung 433, Taiwan
- Department of Nutrition, Hungkuang University, Taichung 433, Taiwan
| | - Stella Chin-Shaw Tsai
- Ph.D. Program in Translational Medicine, Department of Life Sciences, National Chung Hsing University, Taichung 402, Taiwan
- Rong Hsing Research Center for Translational Medicine, College of Life Sciences, National Chung Hsing University, Taichung 402, Taiwan
- Department of Otolaryngology, Tungs’ Taichung MetroHarbor Hospital, Taichung 435, Taiwan
| | - Ching-Ying Huang
- Department of Food Science and Biotechnology, National Chung Hsing University, Taichung 402, Taiwan
| | - Cheng-Li Lin
- Management Office for Health Data, China Medical University Hospital, Taichung 404, Taiwan
| | - Chung Y. Hsu
- Graduate Institute of Clinical Medical Science, China Medical University, Taichung 404, Taiwan
| | - Kuang-Hsi Chang
- Ph.D. Program in Translational Medicine, Department of Life Sciences, National Chung Hsing University, Taichung 402, Taiwan
- Department of Medical Research, Tungs’ Taichung MetroHarbor Hospital, Taichung 435, Taiwan
- Center for General Education, China Medical University, Taichung 404, Taiwan
- General Education Center, Jen-Teh Junior College of Medicine, Nursing and Management, Miaoli 356, Taiwan
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38
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Taylor MJ. Genetic tests for neurodevelopmental differences: Can we and should we? Dev Med Child Neurol 2022; 64:1432-1433. [PMID: 36039698 DOI: 10.1111/dmcn.15386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 07/28/2022] [Indexed: 01/31/2023]
Affiliation(s)
- Mark J Taylor
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Wu J, Li P, Luo H, Lu Y. Complementary and Alternative Medicine Use by ADHD Patients: A Systematic Review. J Atten Disord 2022; 26:1833-1845. [PMID: 35880494 DOI: 10.1177/10870547221111557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVE This study aimed to review the prevalence of complementary and alternative medicine (CAM) use and its different used types, characteristics of the studied cohorts, the reasoning for CAM use, and possible predictive factors for its use amongst ADHD patients. METHOD The Web of Science Core Collection, PubMed, and Scopus were searched from inception to 10 February 2022. All of the original papers published in English which report data on CAM use by patients with ADHD were included. RESULTS Twelve original researches including 4,447 patients were included. The prevalence of CAM use varied from 7.5% to 67.6%. The most-reported CAM modalities were dietary modifications and natural products. Moreover, higher parental education should be considered as a predictive factor for CAM use. CONCLUSION CAM use by ADHD patients seems to be prevalent. Healthcare providers should be trained about the most commonly used CAM therapies and their possible adverse events.
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Affiliation(s)
| | - Ping Li
- Sichuan University, Chengdu, China
| | - Hong Luo
- Sichuan University, Chengdu, China
| | - You Lu
- Sichuan University, Chengdu, China
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40
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Plomin R. The next 10 years of behavioural genomic research. JCPP ADVANCES 2022; 2:e12112. [PMID: 37431418 PMCID: PMC10242940 DOI: 10.1002/jcv2.12112] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 09/23/2022] [Indexed: 12/10/2023] Open
Abstract
Background The explosion caused by the fusion of quantitative genetics and molecular genetics will transform behavioural genetic research in child and adolescent psychology and psychiatry. Methods Although the fallout has not yet settled, the goal of this paper is to predict the next 10 years of research in what could be called behavioural genomics. Results I focus on three research directions: the genetic architecture of psychopathology, causal modelling of gene-environment interplay, and the use of DNA as an early warning system. Conclusion Eventually, whole-genome sequencing will be available for all newborns, which means that behavioural genomics could potentially be applied ubiquitously in research and clinical practice.
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Affiliation(s)
- Robert Plomin
- King's College LondonInstitute of PsychiatryPsychology and NeuroscienceLondonUK
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41
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Hartwig CAM, Robiyanto R, de Vos S, Bos JHJ, van Puijenbroek EP, Hak E, Schuiling-Veninga CCM. In utero antidepressant exposure not associated with ADHD in the offspring: A case control sibling design. Front Pharmacol 2022; 13:1000018. [PMID: 36438827 PMCID: PMC9684082 DOI: 10.3389/fphar.2022.1000018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 10/27/2022] [Indexed: 11/11/2022] Open
Abstract
Recent studies have reported an association between antidepressant (AD) use during pregnancy and the risk to develop attention-deficit/hyperactivity disorder (ADHD) in the offspring. However, the association might be confounded by risk factors in the pregnant parent. To control for unmeasured factors between pregnancies carried by the same parent, we set up a case-control sibling study using the University of Groningen prescription database IADB.nl. Children receiving medication for ADHD (cases) before the age of 16 years were matched to siblings not receiving such medication (controls). Exposure was defined as at least two prescriptions for any AD during pregnancy, i.e., the period of 39 weeks before the birth date of the offspring. Secondary analyses were performed to assess the effects of the degree of exposure (the amount of Defined Daily Doses) and the type of AD exposed to. Univariate and multivariate logistic regression was used to estimate odds ratios (ORs) with corresponding 95% confidence intervals (CI). In total, 2,833 children (1,304 cases and 1,529 controls) were included in the analysis. Exposure rate to ADs among cases and controls was 2.2% and 2.4%, respectively. After adjusting for the birth date of the child (as a proxy for the date of pregnancy), age of the pregnant parent at birth, use of psychostimulants, opioids, and antiepileptic drugs by the pregnant parent in the 15 months before birth of the child, an adjusted OR of 1.11 (95% CI 0.67–1.83) was found for the risk of ADHD in the offspring when exposed in utero to ADs. This indicates no increased risk of ADHD in offspring following in utero exposure to ADs. The secondary analyses revealed no statistically significant associations either. The present study provides further evidence that an association between in utero AD exposure and ADHD in offspring might not exist. This perceived association may be caused (at least partially) by confounding by indication. The extent to which depression in the pregnant parent could cause mental disorders such as ADHD in offspring, and the mechanisms involved, should be investigated in further studies.
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Affiliation(s)
- C. A. M. Hartwig
- PharmacoTherapy, Epidemiology and Economics, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, Netherlands
| | - R. Robiyanto
- PharmacoTherapy, Epidemiology and Economics, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, Netherlands
- Program Studi Farmasi, Fakultas Kedokteran, Universitas Tanjungpura, Pontianak, Indonesia
- *Correspondence: R. Robiyanto,
| | - S. de Vos
- PharmacoTherapy, Epidemiology and Economics, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, Netherlands
| | - J. H. J. Bos
- PharmacoTherapy, Epidemiology and Economics, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, Netherlands
| | - E. P. van Puijenbroek
- PharmacoTherapy, Epidemiology and Economics, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, Netherlands
- Pharmacovigilance Centre Lareb, ‘s-Hertogenbosch, Netherlands
| | - E. Hak
- PharmacoTherapy, Epidemiology and Economics, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, Netherlands
| | - C. C. M. Schuiling-Veninga
- PharmacoTherapy, Epidemiology and Economics, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, Netherlands
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The Link between ADHD Symptoms and Antisocial Behavior: The Moderating Role of the Protective Factor Sense of Coherence. Brain Sci 2022; 12:brainsci12101336. [PMID: 36291270 PMCID: PMC9599088 DOI: 10.3390/brainsci12101336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 12/03/2022] Open
Abstract
Numerous studies have established the link between ADHD and antisocial behavior, one of the most serious functional impairments caused by the disorder. However, research on protective factors that mitigate this link is still lacking. The Salutogenic Model of Health offers the “Sense of Coherence” (SOC), establishing that individuals who see their lives as logical, meaningful, and manageable are more resistant to various risk factors and diseases. The present study examines for the first time whether SOC is also a protective factor against different ADHD-related types of antisocial behaviors (severe/mild violent behavior, verbal violence, property crimes, public disorder, and drug abuse). A total of 3180 participants aged 15−50 completed online questionnaires assessing the level of ADHD symptoms, antisocial behaviors, and SOC. Structural equation modeling was applied to examine the research hypothesis. An interaction between ADHD symptoms and SOC was found in predicting each type of antisocial behavior (beta = −0.06−−0.17, p < 0.01). The link between ADHD symptoms and antisocial behavior was significantly weaker for high than low SOC participants, regardless of age group. The current study found that people with high SOC are protected against the effect of ADHD symptoms on one of the most serious functional impairments, antisocial behavior. These findings suggest that SOC is a protective factor from the adverse effects of ADHD symptoms, justifying further prospective and intervention studies.
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43
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Zhang W, Paul SE, Winkler A, Bogdan R, Bijsterbosch JD. Shared brain and genetic architectures between mental health and physical activity. Transl Psychiatry 2022; 12:428. [PMID: 36192376 PMCID: PMC9530213 DOI: 10.1038/s41398-022-02172-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 11/15/2022] Open
Abstract
Physical activity is correlated with, and effectively treats various forms of psychopathology. However, whether biological correlates of physical activity and psychopathology are shared remains unclear. Here, we examined the extent to which the neural and genetic architecture of physical activity and mental health are shared. Using data from the UK Biobank (N = 6389), we applied canonical correlation analysis to estimate associations between the amplitude and connectivity strength of subnetworks of three major neurocognitive networks (default mode, DMN; salience, SN; central executive networks, CEN) with accelerometer-derived measures of physical activity and self-reported mental health measures (primarily of depression, anxiety disorders, neuroticism, subjective well-being, and risk-taking behaviors). We estimated the genetic correlation between mental health and physical activity measures, as well as putative causal relationships by applying linkage disequilibrium score regression, genomic structural equational modeling, and latent causal variable analysis to genome-wide association summary statistics (GWAS N = 91,105-500,199). Physical activity and mental health were associated with connectivity strength and amplitude of the DMN, SN, and CEN (r's ≥ 0.12, p's < 0.048). These neural correlates exhibited highly similar loading patterns across mental health and physical activity models even when accounting for their shared variance. This suggests a largely shared brain network architecture between mental health and physical activity. Mental health and physical activity (including sleep) were also genetically correlated (|rg| = 0.085-0.121), but we found no evidence for causal relationships between them. Collectively, our findings provide empirical evidence that mental health and physical activity have shared brain and genetic architectures and suggest potential candidate subnetworks for future studies on brain mechanisms underlying beneficial effects of physical activity on mental health.
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Affiliation(s)
- Wei Zhang
- Radiology Department, Washington University School of Medicine, St. Louis, MO, USA.
| | - Sarah E Paul
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Anderson Winkler
- National Institute of Mental Health/National Institutes of Health, Rockville, MD, USA
| | - Ryan Bogdan
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
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Kleine Deters R, Ruisch IH, Faraone SV, Hartman CA, Luman M, Franke B, Oosterlaan J, Buitelaar JK, Naaijen J, Dietrich A, Hoekstra PJ. Polygenic risk scores for antisocial behavior in relation to amygdala morphology across an attention deficit hyperactivity disorder case-control sample with and without disruptive behavior. Eur Neuropsychopharmacol 2022; 62:63-73. [PMID: 35914510 DOI: 10.1016/j.euroneuro.2022.07.182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 07/13/2022] [Accepted: 07/15/2022] [Indexed: 11/04/2022]
Abstract
Antisocial and aggressive behaviors show considerable heritability and are central to disruptive behavior disorders (DBDs), but are also frequently observed in attention deficit hyperactivity disorder (ADHD). While the amygdala is implicated as a key neural structure, it remains unclear whether common genetic variants underlie this brain-behavior association. We hypothesized that polygenic (risk) scores for antisocial and aggressive behaviors (ASB-PRS) would be related to amygdala morphology. Using the Broad Antisocial Behavior Consortium genome-wide association study (GWAS; mostly population based cohorts), we calculated ASB-PRS in the NeuroIMAGE I ADHD case-control sample with varying levels of DBD symptomatology (n=679 from 379 families, aged 7 - 29). We first investigated associations of several ASB-PRS p value thresholds with the presence of DBD symptoms and self-reported antisocial behavior (ASB) to determine the threshold for further analyses. This PRS was then related to amygdala volume and shape using regression and vertex-wise analyses. Our results showed associations of ASB-PRS with the presence of DBD symptoms, self-reported ASB, and left basolateral amygdala shape, independent of ADHD symptom severity and ADHD-PRS, with a relative outward displacement of the vertices. No associations of ASB-PRS, DBD symptoms or self-reported ASB with amygdala volume were found. Our results indicate that genetic risk for antisocial and aggressive behaviors is related to amygdala shape alterations, and point to genetic sharing across different DBD and ASB and aggression-related phenotypes as a spectrum of genetically related quantitative traits. Additionally, our findings support the utility of vertex-based shape analyses in genetic studies of ASB, aggression, and DBDs.
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Affiliation(s)
- Renee Kleine Deters
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, the Netherlands; Accare Child Study Center, Groningen, the Netherlands.
| | - I Hyun Ruisch
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, the Netherlands; Accare Child Study Center, Groningen, the Netherlands
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, State University of New York (SUNY) Upstate Medical University, Syracuse, NY, United States
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Marjolein Luman
- Emma Children's Hospital Amsterdam UMC, University of Amsterdam, Department of Pediatrics, Emma Neuroscience Group, Amsterdam Reproduction & Development research institute, Amsterdam, the Netherlands; Vrije Universiteit Amsterdam, Clinical Neuropsychology Section, Amsterdam, the Netherlands
| | - Barbara Franke
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands; Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Jaap Oosterlaan
- Emma Children's Hospital Amsterdam UMC, University of Amsterdam, Department of Pediatrics, Emma Neuroscience Group, Amsterdam Reproduction & Development research institute, Amsterdam, the Netherlands; Vrije Universiteit Amsterdam, Clinical Neuropsychology Section, Amsterdam, the Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands; Karakter Child and Adolescent Psychiatry University Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Jilly Naaijen
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Andrea Dietrich
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, the Netherlands; Accare Child Study Center, Groningen, the Netherlands
| | - Pieter J Hoekstra
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry, Groningen, the Netherlands; Accare Child Study Center, Groningen, the Netherlands
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Langley K, Martin J, Thapar A. Genetics of Attention-Deficit Hyperactivity Disorder. Curr Top Behav Neurosci 2022; 57:243-268. [PMID: 35538303 DOI: 10.1007/7854_2022_338] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Attention-Deficit Hyperactivity Disorder (ADHD) has long been recognized as being a highly heritable condition and our understanding of the genetic contributions to ADHD has grown over the past few decades. This chapter will discuss the studies that have examined its heritability and the efforts to identify specific genetic risk-variants at the molecular genetic level. We outline the various techniques that have been used to characterize genetic contributions to ADHD, describing what we have learnt so far, what there is still to learn and the methodologies that can be used to further our knowledge. In doing so we will discuss research into rare and common genetic variants, polygenic risk scores, and gene-environment interplay, while also describing what genetic studies have revealed about the biological processes involved in ADHD and what they have taught us about the overlap between ADHD and other psychiatric and somatic disorders. Finally, we will discuss the strengths and limitations of the current methodologies and clinical implications of genetic research to date.
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Affiliation(s)
- Kate Langley
- School of Psychology, Cardiff University, Cardiff, UK. .,MRC Centre for Psychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.
| | - Joanna Martin
- MRC Centre for Psychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.,Division of Psychological Medicine, School of Medicine, Cardiff University, Cardiff, UK.,Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
| | - Anita Thapar
- MRC Centre for Psychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.,Division of Psychological Medicine, School of Medicine, Cardiff University, Cardiff, UK.,Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
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46
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Einziger T, Berger A. Individual differences in sensitivity to positive home environment among children "at risk" for attention-deficit/hyperactivity disorder: A review. Front Psychiatry 2022; 13:927411. [PMID: 35935437 PMCID: PMC9353058 DOI: 10.3389/fpsyt.2022.927411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 07/04/2022] [Indexed: 12/02/2022] Open
Abstract
Although the evidence for the genetic basis of attention-deficit/hyperactivity disorder (ADHD) is strong, environmental factors, such as the quality of parenting or the home environment, may moderate such genetic liability. The plausible negative effect of a low-quality home environment and negative parenting on child outcomes is well-established; however, the positive effect of a high-quality environment and positive parenting remained largely uninvestigated. Due to the presence of genetic, temperamental, or physiological factors, children who were traditionally considered at-risk for ADHD may be more sensitive to aspects of their environment compared to children who are not at such risk. Therefore, they would be more affected by their environmental experience, either for good or bad. Under supportive environmental conditions, such at-risk individuals might actually outperform their non-vulnerable peers, suggesting that these individual factors might be considered susceptibility factors rather than risk factors. Little is known regarding the positive effect of the environment in the ADHD literature, but it has been demonstrated in cognitive functions that are closely associated with ADHD, such as executive functions (EF). We review this literature and examine the extant empirical support for sensitivity to aspects of the home environment and parenting in the case of ADHD and EF. Moreover, we review factors that could help identify the specific aspects of the home environment and parenting that these children might be more susceptible to. Such knowledge could be valuable when designing preventive interventions and identifying those children that are especially sensitive and could benefit from such interventions. Recommendations for future studies are discussed as well.
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Affiliation(s)
- Tzlil Einziger
- Department of Behavioral Sciences, Ruppin Academic Center, Emek Hefer, Israel
| | - Andrea Berger
- Department of Psychology, Ben-Gurion University of the Negev, Beer Sheva, Israel
- Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer Sheva, Israel
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Sari NP, Jansen PW, Blanken LME, Ruigrok ANV, Prinzie P, Tiemeier H, Baron-Cohen S, van IJzendoorn MH, White T. Maternal age, autistic-like traits and mentalizing as predictors of child autistic-like traits in a population-based cohort. Mol Autism 2022; 13:26. [PMID: 35705965 PMCID: PMC9199218 DOI: 10.1186/s13229-022-00507-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 06/03/2022] [Indexed: 11/10/2022] Open
Abstract
Background Many empirical studies suggest that higher maternal age increases the likelihood of having an autistic child. However, little is known about factors that may explain this relationship or if higher maternal age is related to the number of autistic-like traits in offspring. One possibility is that mothers who have a higher number of autistic-like traits, including greater challenges performing mentalizing skills, are delayed in finding a partner. The goal of our study is to assess the relationship between maternal age, mentalizing skills and autistic-like traits as independent predictors of the number of autistic-like traits in offspring. Methods In a population-based study in the Netherlands, information on maternal age was collected during pre- and perinatal enrolment. Maternal mentalizing skills and autistic-like traits were assessed using the Reading the Mind in the Eyes Test and the Autism Spectrum Quotient, respectively. Autistic-like traits in children were assessed with the Social Responsiveness Scale. A total of 5718 mother/child dyads had complete data (Magechild = 13.5 years; 50.2% girls). Results The relationship between maternal age and autistic-like traits in offspring best fits a U-shaped curve. Furthermore, higher levels of autistic features in mothers are linked to higher levels of autistic-like traits in their children. Lower mentalizing performance in mothers is linked to higher levels of autistic-like traits in their children. Limitations We were able to collect data on both autistic-like traits and the mentalizing skills test in a large population of mothers, but we did not collect these data in a large number of the fathers. Conclusions The relationships between older and younger mothers may have comparable underlying mechanisms, but it is also possible that the tails of the U-shaped curve are influenced by disparate mechanisms. Supplementary Information The online version contains supplementary material available at 10.1186/s13229-022-00507-4.
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Affiliation(s)
- Novika Purnama Sari
- Department Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands. .,Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, The Netherlands. .,Generation R Study Group, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Pauline W Jansen
- Department Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Laura M E Blanken
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Psychiatry, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, The Netherlands
| | - Amber N V Ruigrok
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Peter Prinzie
- Department Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, The Netherlands.,Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Marinus H van IJzendoorn
- Department Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands.,Research Department of Clinical Educational and Health Psychology, UCL, University of London, London, UK
| | - Tonya White
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands
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48
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Yao Y, Li C, Meng P, Cheng B, Cheng S, Liu L, Yang X, Jia Y, Wen Y, Zhang F. An atlas of genetic correlations between gestational age and common psychiatric disorders. Autism Res 2022; 15:1008-1017. [PMID: 35384380 DOI: 10.1002/aur.2719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 03/02/2022] [Accepted: 03/21/2022] [Indexed: 11/11/2022]
Abstract
We aim to systematically explore the potential genetic correlations between five major psychiatric disorders and gestational ages. Genome-wide association study (GWAS) summary datasets of attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) in discovery were downloaded from the Psychiatric GWAS Consortium (PGC) website. Suggestive (Raw p < 0.05) genetic associations in the discovery phrase were further replicated in independent GWASs which downloaded from PGC, the FinnGen study or Integrative Psychiatric Research (iPSYCH) website. GWASs of gestational duration, preterm and post-term birth were derived from previous studies of infants from the Early Growth Genetics (EGG) Consortium, the iPSYCH study, and the Genomic and Proteomic Network for Preterm Birth Research (GPN). We calculated genetic correlations using linkage disequilibrium score (LDSC) regression. Mendelian randomization (MR) analyses were performed to investigate the causal effects. We identified four suggestive genetic correlations between psychiatric disorders and gestational age factors in discovery LDSC and two replicated in a confirmation LDSC: gestational duration and ADHD (rg = -0.1405, FDR p = 0.0406), post-term birth and SCZ (rg = -0.2003, FDR p = 0.0042). We also observed causal effect of post-term birth on SCZ by MR (PWeighted median = 0.037, PInverse variance weighted = 0.007). Our analysis suggested no significant evidence of horizontal pleiotropy and heterogeneity. This study showed the genetic correlation evidences between gestational age phenotypes and psychiatric disorders, providing novel clues for understanding the pathogenic factors of common psychiatric disorders. LAY SUMMARY: Whereas gestational age factors were reported to be associated with psychiatric disorders, the genetic relationship and causality remain to be revealed. The present study reported the first large-scale genetic correlations investigation of the associations between gestational age phenotypes and psychiatric disorders. Results indicate causal relationships between post-term birth and schizophrenia (SCZ), as well as suggestive genetic correlations between gestational duration and attention deficit/hyperactivity disorder (ADHD). This study provided novel clues for understanding the pathogenic factors of common psychiatric disorders.
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Affiliation(s)
- Yao Yao
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Chun'e Li
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, China
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49
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Balogh L, Pulay AJ, Réthelyi JM. Genetics in the ADHD Clinic: How Can Genetic Testing Support the Current Clinical Practice? Front Psychol 2022; 13:751041. [PMID: 35350735 PMCID: PMC8957927 DOI: 10.3389/fpsyg.2022.751041] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 01/03/2022] [Indexed: 12/12/2022] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with a childhood prevalence of 5%. In about two-thirds of the cases, ADHD symptoms persist into adulthood and often cause significant functional impairment. Based on the results of family and twin studies, the estimated heritability of ADHD approximates 80%, suggests a significant genetic component in the etiological background of the disorder; however, the potential genetic effects on disease risk, symptom severity, and persistence are unclear. This article provides a brief review of the genome-wide and candidate gene association studies with a focus on the clinical aspects, summarizing findings of ADHD disease risk, ADHD core symptoms as dimensional traits, and other traits frequently associated with ADHD, which may contribute to the susceptibility to other comorbid psychiatric disorders. Furthermore, neuropsychological impairment and measures from neuroimaging and electrophysiological paradigms, emerging as potential biomarkers, also provide a prominent target for molecular genetic studies, since they lie in the pathway from genes to behavior; therefore, they can contribute to the understanding of the underlying neurobiological mechanisms and the interindividual heterogeneity of clinical symptoms. Beyond the aforementioned aspects, throughout the review, we also give a brief summary of the genetic results, including polygenic risk scores that can potentially predict individual response to different treatment options and may offer a possibility for personalized treatment for the therapy of ADHD in the future.
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Affiliation(s)
- Lívia Balogh
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Attila J Pulay
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - János M Réthelyi
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
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Landgren V, Fernell E, Gillberg C, Landgren M, Johnson M. Deficits in attention, motor control and perception childhood to age 30 years: prospective case-control study of outcome predictors. BMJ Open 2022; 12:e054424. [PMID: 35301207 PMCID: PMC8932285 DOI: 10.1136/bmjopen-2021-054424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE Investigate predictors of adverse outcome in children with and without attention-deficit/hyperactivity disorder (ADHD) combined with developmental coordination disorder (DCD) at 6 years of age. DESIGN Prospective population-based cohort study. SETTING Western Sweden. PARTICIPANTS From a screening-based population cohort of 589 individuals, 62 (11 female) diagnosed with ADHD+DCD at mean age 6.6 years, and a comparison group of 51 population-matched (10 female) children were followed prospectively. OUTCOME MEASURES Drawn from a clinical reassessment at age 9 years of 110 of the 113 individuals, neuropsychiatric symptoms, continuous performance test results and measures of motor function were used as predictors of outcome in linear regression models. Participants were followed in national registers up to 30-31 years of age for outcomes in adulthood. Predictors were regressed onto an adverse outcome score (range 0-7) comprising seven binary endpoints, and when applicable onto each continuous outcome separately (low educational attainment, low occupation level, psychiatric disorder, psychotropic medication prescription, sick pension, high dependence on social benefits and criminal conviction). RESULTS Of the 110 individuals, 3 had died. In univariable regression onto the adverse outcome score, the strongest predictors at age 9 years were symptoms of conduct disorder, oppositional defiant disorder, ADHD and motor dysfunction, with an R2 around 25%, followed by autistic traits (R2=15%) and depressive symptoms (R2=8%). Combining these six strongest predictors in a multivariable model yielded an adjusted R2=38%. Subgroup analyses were similar, except for a strong association of autistic traits with the adverse outcome score in females (n=20, R2=50%). CONCLUSION Several neurodevelopmental symptoms, including ADHD severity at age 9 years, accounted for a considerable amount of the variance in terms of adulthood adverse outcome. Broad neurodevelopmental profiling irrespective of diagnostic thresholds should inform research and clinical practice. The study highlights the importance of considering associated comorbidities and problems in ADHD.
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Affiliation(s)
- Valdemar Landgren
- Psychiatry, Skaraborg Hospital Skövde, Skövde, Sweden
- Gillberg Neuropsychiatry Centre, University of Gothenburg Sahlgrenska Academy, Gothenburg, Sweden
| | - Elisabeth Fernell
- Gillberg Neuropsychiatry Centre, University of Gothenburg Sahlgrenska Academy, Gothenburg, Sweden
| | - Christopher Gillberg
- Gillberg Neuropsychiatry Centre, University of Gothenburg Sahlgrenska Academy, Gothenburg, Sweden
| | - Magnus Landgren
- Gillberg Neuropsychiatry Centre, University of Gothenburg Sahlgrenska Academy, Gothenburg, Sweden
- Pediatrics, Skaraborg Hospital Mariestad, Mariestad, Sweden
| | - Mats Johnson
- Gillberg Neuropsychiatry Centre, University of Gothenburg Sahlgrenska Academy, Gothenburg, Sweden
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