275 results on '"Bennett L. Leventhal"'
Search Results
2. Synaptic processes and immune-related pathways implicated in Tourette syndrome
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Fotis Tsetsos, Dongmei Yu, Jae Hoon Sul, Alden Y. Huang, Cornelia Illmann, Lisa Osiecki, Sabrina M. Darrow, Matthew E. Hirschtritt, Erica Greenberg, Kirsten R. Muller-Vahl, Manfred Stuhrmann, Yves Dion, Guy A. Rouleau, Harald Aschauer, Mara Stamenkovic, Monika Schlögelhofer, Paul Sandor, Cathy L. Barr, Marco A. Grados, Harvey S. Singer, Markus M. Nöthen, Johannes Hebebrand, Anke Hinney, Robert A. King, Thomas V. Fernandez, Csaba Barta, Zsanett Tarnok, Peter Nagy, Christel Depienne, Yulia Worbe, Andreas Hartmann, Cathy L. Budman, Renata Rizzo, Gholson J. Lyon, William M. McMahon, James R. Batterson, Danielle C. Cath, Irene A. Malaty, Michael S. Okun, Cheston Berlin, Douglas W. Woods, Paul C. Lee, Joseph Jankovic, Mary M. Robertson, Donald L. Gilbert, Lawrence W. Brown, Barbara J. Coffey, Andrea Dietrich, Pieter J. Hoekstra, Samuel Kuperman, Samuel H. Zinner, Michael Wagner, James A. Knowles, A. Jeremy Willsey, Jay A. Tischfield, Gary A. Heiman, Nancy J. Cox, Nelson B. Freimer, Benjamin M. Neale, Lea K. Davis, Giovanni Coppola, Carol A. Mathews, Jeremiah M. Scharf, Peristera Paschou, on behalf of the Tourette Association of America International Consortium for Genetics, Sabrina Darrow, Roger Kurlan, James F. Leckman, Jan H. Smit, the Gilles de la Tourette GWAS Replication Initiative, Harald Aschauer Harald Aschauer, Anastasios Konstantinidis, Kirsten Müller-Vahl, Tomasz Wolanczyk, the Tourette International Collaborative Genetics Study, Lawrence Brown, Keun-Ah Cheon, Blanca Garcia-Delgar, Donald Gilbert, Dorothy E. Grice, Julie Hagstrøm, Tammy Hedderly, Isobel Heyman, Chaim Huyser, Young Key Kim, Young-Shin Kim, Yun-Joo Koh, Sodahm Kook, Bennett L. Leventhal, Marcos Madruga-Garrido, Pablo Mir, Astrid Morer, Alexander Münchau, Kerstin J. Plessen, Veit Roessner, Eun-Young Shin, Dong-Ho Song, Jungeun Song, Samuel Zinner, and the Psychiatric Genomics Consortium Tourette Syndrome Working Group, Thomas Fernandez, Gary Heiman, Pieter Hoekstra, Jay Tischfield, and Douglas Woods
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Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Abstract Tourette syndrome (TS) is a neuropsychiatric disorder of complex genetic architecture involving multiple interacting genes. Here, we sought to elucidate the pathways that underlie the neurobiology of the disorder through genome-wide analysis. We analyzed genome-wide genotypic data of 3581 individuals with TS and 7682 ancestry-matched controls and investigated associations of TS with sets of genes that are expressed in particular cell types and operate in specific neuronal and glial functions. We employed a self-contained, set-based association method (SBA) as well as a competitive gene set method (MAGMA) using individual-level genotype data to perform a comprehensive investigation of the biological background of TS. Our SBA analysis identified three significant gene sets after Bonferroni correction, implicating ligand-gated ion channel signaling, lymphocytic, and cell adhesion and transsynaptic signaling processes. MAGMA analysis further supported the involvement of the cell adhesion and trans-synaptic signaling gene set. The lymphocytic gene set was driven by variants in FLT3, raising an intriguing hypothesis for the involvement of a neuroinflammatory element in TS pathogenesis. The indications of involvement of ligand-gated ion channel signaling reinforce the role of GABA in TS, while the association of cell adhesion and trans-synaptic signaling gene set provides additional support for the role of adhesion molecules in neuropsychiatric disorders. This study reinforces previous findings but also provides new insights into the neurobiology of TS.
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- 2021
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3. Testing an individualized digital decision assist system for the diagnosis and management of mental and behavior disorders in children and adolescents
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Carolyn E. Clausen, Bennett L. Leventhal, Øystein Nytrø, Roman Koposov, Odd Sverre Westbye, Thomas Brox Røst, Victoria Bakken, Kaban Koochakpour, Ketil Thorvik, and Norbert Skokauskas
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Child and adolescent mental health services (CAMHS) ,Clinical decision support system (CDSS) ,Innovation ,Attention-deficit/hyperactivity disorder (ADHD) ,IDDEAS ,Norway ,Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
Abstract Background Nearly half of all mental health disorders develop prior to the age of 15. Early assessments, diagnosis, and treatment are critical to shortening single episodes of care, reducing possible comorbidity and long-term disability. In Norway, approximately 20% of all children and adolescents are experiencing mental health problems. To address this, health officials in Norway have called for the integration of innovative approaches. A clinical decision support system (CDSS) is an innovative, computer-based program that provides health professionals with clinical decision support as they care for patients. CDSS use standardized clinical guidelines and big data to provide guidance and recommendations to clinicians in real-time. IDDEAS (Individualised Digital DEcision Assist System) is a CDSS for diagnosis and treatment of child and adolescent mental health disorders. The aim of IDDEAS is to enhance quality, competency, and efficiency in child and adolescent mental health services (CAMHS). Methods/design IDDEAS is a mixed-methods innovation and research project, which consists of four stages: 1) Assessment of Needs and Preparation of IDDEAS; 2) The Development of IDDEAS CDSS Model; 3) The Evaluation of the IDDEAS CDSS; and, 4) Implementation & Dissemination. Both qualitative and quantitative methods will be used for the evaluation of IDDEAS CDSS model. Child and adolescent psychologists and psychiatrists (n = 30) will evaluate the IDDEAS` usability, acceptability and relevance for diagnosis and treatment of attention-deficit/hyperactivity disorder. Discussion The IDDEAS CDSS model is the first guidelines and data-driven CDSS to improve efficiency of diagnosis and treatment of child and adolescent mental health disorders in Norway. Ultimately, IDDEAS will help to improve patient health outcomes and prevent long-term adverse outcomes by providing each patient with evidence-based, customized clinical care. Trial registration ISRCTN, ISRCTN12094788. Ongoing study, registered prospectively 8 April 2020 https://doi.org/10.1186/ISRCTN12094788
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- 2020
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4. Pharmacotherapy of restricted/repetitive behavior in autism spectrum disorder:a systematic review and meta-analysis
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Yanjie Yu, Ashmita Chaulagain, Sindre Andre Pedersen, Stian Lydersen, Bennett L. Leventhal, Peter Szatmari, Branko Aleksic, Norio Ozaki, and Norbert Skokauskas
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Autism Spectrum disorder ,Restricted/repetitive behavior ,Pharmacotherapy ,Systematic review ,Meta -analysis ,Psychiatry ,RC435-571 - Abstract
Abstract Background This paper is a systematic review and meta-analysis of the efficacy of available medications for the treatment of restricted/repetitive behavior (RRBs) in Autism Spectrum Disorder (ASD). Method We searched MEDLINE, Embase, PsycINFO, The Cochrane Library (Cochrane Database of Systematic Reviews (CDRS), the Cochrane Central Register of Controlled Trials (CENTRAL), database of Abstracts of Reviews of Effects (DARE)), Scopus, Epistimonikos, Clinicaltrials.gov, and included all randomized controlled trials published after 1993 that were directed at RRBs in patients with ASD of all ages. We extracted the relevant data from the published studies with a predefined data extraction form and assessed the risk of bias. The primary outcomes were change in restricted/repetitive behavior. We performed a meta-analysis using the random effect model and included studies with given mean and standard deviation. This study is registered with PROSPERO number CRD42018092660). Results We identified 14 randomized controlled trials that met initial inclusion criteria. After closer inspection, nine trials – involving 552 patients in total – were included in the final analysis. The meta-analysis found no significant difference between medications (including fluvoxamine, risperidone, fluoxetine, citalopram, oxytocin, N-Acetylcysteine, buspirone) and placebo in the treatment of RRBs in ASD (P = 0.20). Similarly, the sub-group meta-analysis also showed no significant difference between Selective Serotonin Reuptake Inhibitor (SSRIs) and placebo in the treatment of RRBs in ASD (P = 0.68). There was no evidence of publication bias. Conclusion This meta-analysis finds little support for the routine use of medications to treat restricted/repetitive behaviors in Autism Spectrum Disorder. Further research of large, balanced trials with precise assessment tools and long-term follow-up are needed. Trial registration The study protocol is registered in PROSPERO (Reference number: CRD42018092660) .
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- 2020
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5. Challenges in Interpreting Norwegian Child and Adolescent Mental Health Records.
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Kaban Koochakpour, Frida Sofie Solheim, øystein Nytrø, Carolyn E. Clausen, Thomas Frodl, Roman Koposov, Bennett L. Leventhal, Dipendra Pant, Thomas Brox Røst, Line Stien, Odd Sverre Westbye, and Norbert Skokauskas
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- 2023
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6. A review of information sources and analysis methods for data driven decision aids in child and adolescent mental health services.
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Kaban Koochakpour, øystein Nytrø, Bennett L. Leventhal, Odd Sverre Westbye, Thomas Brox Røst, Roman Koposov, Thomas Frodl, Carolyn E. Clausen, Line Stien, and Norbert Skokauskas
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- 2024
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7. Success Factors of an Early EHR System for Child and Adolescent Mental Health: Lessons Learned for Future Practice Data-Driven Decision Aids.
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Kaban Koochakpour, øystein Nytrø, Odd Sverre Westbye, Bennett L. Leventhal, Roman Koposov, Victoria Bakken, Carolyn E. Clausen, Thomas Brox Røst, and Norbert Skokauskas
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- 2021
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8. Beta-adrenergic Blockade at Memory Encoding, but Not Retrieval, Decreases the Subjective Sense of Recollection.
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Ulrike Rimmele, Sandra F. Lackovic, Russell H. Tobe, Bennett L. Leventhal, and Elizabeth A. Phelps
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- 2016
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9. Genome-wide Association Study Points to Novel Locus for Gilles de la Tourette Syndrome
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Fotis Tsetsos, Apostolia Topaloudi, Pritesh Jain, Zhiyu Yang, Dongmei Yu, Petros Kolovos, Zeynep Tumer, Renata Rizzo, Andreas Hartmann, Christel Depienne, Yulia Worbe, Kirsten R. Müller-Vahl, Danielle C. Cath, Dorret I. Boomsma, Tomasz Wolanczyk, Cezary Zekanowski, Csaba Barta, Zsofia Nemoda, Zsanett Tarnok, Shanmukha S. Padmanabhuni, Joseph D. Buxbaum, Dorothy Grice, Jeffrey Glennon, Hreinn Stefansson, Bastian Hengerer, Evangelia Yannaki, John A. Stamatoyannopoulos, Noa Benaroya-Milshtein, Francesco Cardona, Tammy Hedderly, Isobel Heyman, Chaim Huyser, Pablo Mir, Astrid Morer, Norbert Mueller, Alexander Munchau, Kerstin J. Plessen, Cesare Porcelli, Veit Roessner, Susanne Walitza, Anette Schrag, Davide Martino, Jay A. Tischfield, Gary A. Heiman, A. Jeremy Willsey, Andrea Dietrich, Lea K. Davis, James J. Crowley, Carol A. Mathews, Jeremiah M. Scharf, Marianthi Georgitsi, Pieter J. Hoekstra, Peristera Paschou, Cathy L. Barr, James R. Batterson, Cheston Berlin, Cathy L. Budman, Giovanni Coppola, Nancy J. Cox, Sabrina Darrow, Yves Dion, Nelson B. Freimer, Marco A. Grados, Erica Greenberg, Matthew E. Hirschtritt, Alden Y. Huang, Cornelia Illmann, Robert A. King, Roger Kurlan, James F. Leckman, Gholson J. Lyon, Irene A. Malaty, William M. McMahon, Benjamin M. Neale, Michael S. Okun, Lisa Osiecki, Mary M. Robertson, Guy A. Rouleau, Paul Sandor, Harvey S. Singer, Jan H. Smit, Jae Hoon Sul, Christos Androutsos, Entela Basha, Luca Farkas, Jakub Fichna, Piotr Janik, Mira Kapisyzi, Iordanis Karagiannidis, Anastasia Koumoula, Peter Nagy, Joanna Puchala, Natalia Szejko, Urszula Szymanska, Vaia Tsironi, Alan Apter, Juliane Ball, Benjamin Bodmer, Emese Bognar, Judith Buse, Marta Correa Vela, Carolin Fremer, Blanca Garcia-Delgar, Mariangela Gulisano, Annelieke Hagen, Julie Hagstrøm, Marcos Madruga-Garrido, Alessandra Pellico, Daphna Ruhrman, Jaana Schnell, Paola Rosaria Silvestri, Liselotte Skov, Tamar Steinberg, Friederike Tagwerker Gloor, Victoria L. Turner, Elif Weidinger, John Alexander, Tamas Aranyi, Wim R. Buisman, Jan K. Buitelaar, Nicole Driessen, Petros Drineas, Siyan Fan, Natalie J. Forde, Sarah Gerasch, Odile A. van den Heuvel, Cathrine Jespersgaard, Ahmad S. Kanaan, Harald E. Möller, Muhammad S. Nawaz, Ester Nespoli, Luca Pagliaroli, Geert Poelmans, Petra J.W. Pouwels, Francesca Rizzo, Dick J. Veltman, Ysbrand D. van der Werf, Joanna Widomska, Nuno R. Zilhäo, Lawrence W. Brown, Keun-Ah Cheon, Barbara J. Coffey, Thomas V. Fernandez, Donald L. Gilbert, Hyun Ju Hong, Laura Ibanez-Gomez, Eun-Joo Kim, Young Key Kim, Young-Shin Kim, Yun-Joo Koh, Sodahm Kook, Samuel Kuperman, Bennett L. Leventhal, Athanasios Maras, Tara L. Murphy, Eun-Young Shin, Dong-Ho Song, Jungeun Song, Matthew W. State, Frank Visscher, Sheng Wang, Samuel H. Zinner, Psychiatry, APH - Mental Health, APH - Methodology, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Anatomy and neurosciences, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Neurodegeneration, Radiology and nuclear medicine, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Systems & Network Neuroscience, Biological Psychology, and Amsterdam Reproduction & Development
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meta-analysis ,Medizin ,GWAS ,Biological Psychiatry ,NR2F1 ,Tourette Syndrome - Abstract
Background: Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder of complex genetic architecture and is characterized by multiple motor tics and at least one vocal tic persisting for more than 1 year. Methods: We performed a genome-wide meta-analysis integrating a novel TS cohort with previously published data, resulting in a sample size of 6133 individuals with TS and 13,565 ancestry-matched control participants. Results: We identified a genome-wide significant locus on chromosome 5q15. Integration of expression quantitative trait locus, Hi-C (high-throughput chromosome conformation capture), and genome-wide association study data implicated the NR2F1 gene and associated long noncoding RNAs within the 5q15 locus. Heritability partitioning identified statistically significant enrichment in brain tissue histone marks, while polygenic risk scoring of brain volume data identified statistically significant associations with right and left thalamus volumes and right putamen volume. Conclusions: Our work presents novel insights into the neurobiology of TS, thereby opening up new directions for future studies.
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- 2023
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10. Investigation of gene-environment interactions in relation to tic severity
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Frank Visscher, Kerstin J. Plessen, Tammy Hedderly, Jungeun Song, Bennett L. Leventhal, Eun-Young Shin, Lawrence W. Brown, Alexander Münchau, Robert A. King, Young Key Kim, Young Shin Kim, Veit Roessner, Andrea Dietrich, Samuel Kuperman, Thomas V. Fernandez, Keun-Ah Cheon, Carol A. Mathews, Athanasios Maras, Donald L. Gilbert, Yun-Joo Koh, Laura Ibanez-Gomez, Dongmei Yu, Astrid Morer, Sodahm Kook, Marcos Madruga-Garrido, Julie Hagstrøm, Dorothy E. Grice, Jay A. Tischfield, Lisa Osiecki, Mohamed Abdulkadir, Blanca Garcia-Delgar, Samuel H. Zinner, Chaim Huyser, Barbara J. Coffey, Dong-Ho Song, Gary A. Heiman, Pieter J. Hoekstra, Hyun Ju Hong, Pablo Mir, Isobel Heyman, Jeremiah M. Scharf, National Institute of Mental Health (US), Tourette Syndrome Association of New Jersey, Judah Foundation, Tourette Association of America, National Institutes of Health (US), Instituto de Salud Carlos III, Junta de Andalucía, Sociedad Andaluza de Neurología, Fundación Alicia Koplowitz, Fundación Mutua Madrileña, Jacques and Gloria Gossweiler Foundation, Generalitat de Catalunya, German Research Foundation, National Institute of Environmental Health Sciences (US), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Child Psychiatry, Paediatric Psychosocial Care, and Amsterdam Neuroscience - Cellular & Molecular Mechanisms
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Candidate gene ,Tic severity ,Autism Spectrum Disorder ,Autism ,Intellectual and Developmental Disabilities (IDD) ,Single-nucleotide polymorphism ,Genome-wide association study ,Neurodegenerative ,Tourette syndrome ,Severity of Illness Index ,Attention Deficit Disorder with Hyperactivity/genetics ,Autism Spectrum Disorder/genetics ,Female ,Gene-Environment Interaction ,Genome-Wide Association Study ,Humans ,Pregnancy ,Tics ,Tourette Syndrome ,Gene–environment interaction ,Pre- and perinatal complications ,mental disorders ,medicine ,Genetics ,SNP ,2.1 Biological and endogenous factors ,Psychology ,Aetiology ,Biological Psychiatry ,Genetic association ,Pediatric ,Neurology & Neurosurgery ,business.industry ,Psychiatry and Preclinical Psychiatric Studies - Original Article ,Human Genome ,Neurosciences ,medicine.disease ,Serious Mental Illness ,Gene-environment interaction ,Brain Disorders ,Psychiatry and Mental health ,Mental Health ,Neurology ,Autism spectrum disorder ,Attention Deficit Disorder with Hyperactivity ,Neurology (clinical) ,business - Abstract
Tourette syndrome (TS) is a neuropsychiatric disorder with involvement of genetic and environmental factors. We investigated genetic loci previously implicated in Tourette syndrome and associated disorders in interaction with pre- and perinatal adversity in relation to tic severity using a case-only (N = 518) design. We assessed 98 single-nucleotide polymorphisms (SNPs) selected from (I) top SNPs from genome-wide association studies (GWASs) of TS; (II) top SNPs from GWASs of obsessive–compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD); (III) SNPs previously implicated in candidate-gene studies of TS; (IV) SNPs previously implicated in OCD or ASD; and (V) tagging SNPs in neurotransmitter-related candidate genes. Linear regression models were used to examine the main effects of the SNPs on tic severity, and the interaction effect of these SNPs with a cumulative pre- and perinatal adversity score. Replication was sought for SNPs that met the threshold of significance (after correcting for multiple testing) in a replication sample (N = 678). One SNP (rs7123010), previously implicated in a TS meta-analysis, was significantly related to higher tic severity. We found a gene–environment interaction for rs6539267, another top TS GWAS SNP. These findings were not independently replicated. Our study highlights the future potential of TS GWAS top hits in gene–environment studies., This research was funded by National Institute of Mental Health (NIMH) grant R01MH092293 (to GAH and JAT) and NJCTS (New Jersey Center for Tourette Syndrome and Associated Disorders; to GAH and JAT). This work was also supported by grants from the Judah Foundation, the Tourette Association of America, National Institute of Health (NIH) Grants NS40024, NS016648, MH079489, MH073250, the American Recovery and Re-investment Act (ARRA) Grants NS040024-07S1; NS16648-29S1; NS040024-09S1; MH092289; MH092290; MH092291; MH092292; R01MH092293; MH092513; MH092516; MH092520; MH071507; MH079489; MH079487; MH079488; and MH079494. Dr. Mir has received grants from the Instituto de Salud Carlos III (PI10/01674, PI13/01461), the Consejería de Economía, Innovación, Ciencia y Empresa de la Junta de Andalucía (CVI-02526, CTS-7685), the Consejería de Salud y Bienestar Social de la Junta de Andalucía (PI-0741/2010, PI-0437-2012, PI-0471-2013), the Sociedad Andaluza de Neurología, the Fundación Alicia Koplowitz, the Fundación Mutua Madrileña and the Jaques and Gloria Gossweiler Foundation. Dr. Morer has received grants from the Fundacion Alicia Koplowitz and belongs to the research group of the Comissionat per Universitats i Recerca del Departmanent d’Innovacio (DIUE) 2009SGR1119. Dr. Münchau has received grants from the Deutsche Forschungsgemeinschaft (DFG: MU 1692/3-1, MU 1692/4-1 and FOR 2698). This study was also supported by a Grant from the National Institute for Environmental Health Science (R01 ES021462).
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- 2021
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11. MRI Findings in Prematurely-Born Adolescents and Young Adults Who Screen Positive for Autism Spectrum Disorder
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Hosanna Kim, Young Shin Kim, Bennett L. Leventhal, Somer Bishop, A. James Barkovich, and Dawn Gano
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Young Adult ,Developmental Neuroscience ,Neurology ,Adolescent ,Autism Spectrum Disorder ,Pediatrics, Perinatology and Child Health ,Infant, Newborn ,Humans ,Neurology (clinical) ,Magnetic Resonance Imaging ,Infant, Premature - Published
- 2022
12. Prevalence of and Factors Associated with School Bullying in Students with Autism Spectrum Disorder: A Cross-Cultural Meta-Analysis
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Michio Takahashi, Bora Kim, Jeongsoo Lee, Jared Gong, In Hwan Park, Bennett L. Leventhal, Gregory L. Lyons, Young Shin Kim, Seung-yeon Lee, and Tomoya Hirota
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associated factors ,Cross-Cultural Comparison ,Male ,Adolescent ,Autism Spectrum Disorder ,education ,prevalence ,Poison control ,Review Article ,030204 cardiovascular system & hematology ,Suicide prevention ,03 medical and health sciences ,Young Adult ,0302 clinical medicine ,Injury prevention ,medicine ,Psychiatry, Psychology ,Humans ,Interpersonal Relations ,Child ,Students ,cultural difference ,Crime Victims ,Human factors and ergonomics ,Bullying ,General Medicine ,medicine.disease ,Moderation ,Social relation ,methodological quality ,Autism spectrum disorder ,030220 oncology & carcinogenesis ,Meta-analysis ,Child, Preschool ,Female ,Students with ASD ,Psychology ,Clinical psychology - Abstract
Through this meta-analysis, we sought to examine the prevalence of, risks for, and factors associated with bullying involvement (victimization, perpetration, perpetration-victimization) among students with autism spectrum disorder (ASD). Additionally, we attempted to examine sources of variance in the prevalence and effect sizes of bullying in students with ASD across studies. Systematic database and literature review identified 34 relevant studies (31 for Western countries, three for Eastern countries). Pooled prevalence estimates for victimization, perpetration, and perpetration-victimization in general were 67%, 29%, and 14%, respectively. The risk of victimization in students with ASD was significantly higher than that in typically developing students and students with other disabilities. Further, deficits in social interaction and communication, externalizing symptoms, internalizing symptoms, and integrated inclusive school settings were related to higher victimization, and externalizing symptoms were related to higher perpetration. Finally, moderation analyses revealed significant variations in the pooled prevalences thereof depending on culture, age, school settings, and methodological quality and in the pooled effect sizes according to publication year and methodological quality. Our results highlight needs for bullying intervention for students with ASD, especially those who are younger, are in an inclusive school setting, and have higher social difficulties and externalizing/internalizing symptoms; for intensive research of bullying experiences among students with ASD in Eastern countries; and for efforts to improve the methodological quality of such research.
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- 2020
13. Social attention to activities in children and adults with autism spectrum disorder: effects of context and age
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Andrew Skalkin, Frederick Shic, Robert L. Hendren, Dzmitry A. Kaliukhovich, Matthew S. Goodwin, Abigail Bangerter, Bennett L. Leventhal, Nikolay V. Manyakov, Caitlin M. Hudac, Gahan Pandina, Seth Ness, Geraldine Dawson, and Jessica Bradshaw
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Male ,Autism Spectrum Disorder ,Autism ,lcsh:RC346-429 ,Developmental psychology ,0302 clinical medicine ,Task Performance and Analysis ,Intellectual disability ,Attention ,Aetiology ,Autism spectrum disorder ,Child ,Pediatric ,05 social sciences ,Age Factors ,Neuropsychology ,Middle Aged ,Psychiatry and Mental health ,Mental Health ,Social attention ,Activity monitoring ,Female ,social and economic factors ,Psychology ,050104 developmental & child psychology ,Adult ,Pediatric Research Initiative ,Adolescent ,Intellectual and Developmental Disabilities (IDD) ,Clinical Sciences ,Context (language use) ,Young Adult ,03 medical and health sciences ,Developmental Neuroscience ,Clinical Research ,2.3 Psychological ,Behavioral and Social Science ,mental disorders ,medicine ,Humans ,0501 psychology and cognitive sciences ,Social Behavior ,Set (psychology) ,Molecular Biology ,lcsh:Neurology. Diseases of the nervous system ,Eye tracking ,Research ,Neurosciences ,medicine.disease ,Gaze ,Brain Disorders ,Photic Stimulation ,030217 neurology & neurosurgery ,Biomarkers ,Developmental Biology - Abstract
Background Diminished visual monitoring of faces and activities of others is an early feature of autism spectrum disorder (ASD). It is uncertain whether deficits in activity monitoring, identified using a homogeneous set of stimuli, persist throughout the lifespan in ASD, and thus, whether they could serve as a biological indicator (“biomarker”) of ASD. We investigated differences in visual attention during activity monitoring in children and adult participants with autism compared to a control group of participants without autism. Methods Eye movements of participants with autism (n = 122; mean age [SD] = 14.5 [8.0] years) and typically developing (TD) controls (n = 40, age = 16.4 [13.3] years) were recorded while they viewed a series of videos depicting two female actors conversing while interacting with their hands over a shared task. Actors either continuously focused their gaze on each other’s face (mutual gaze) or on the shared activity area (shared focus). Mean percentage looking time was computed for the activity area, actors’ heads, and their bodies. Results Compared to TD participants, participants with ASD looked longer at the activity area (mean % looking time: 58.5% vs. 53.8%, p p Δ = − 6.4%, p Δ = + 3.5%, p Δ = + 1.6%, p Limitations The TD participants were not as well characterized as the participants with ASD. Inclusion criteria regarding the cognitive ability [intelligence quotient (IQ) > 60] limited the ability to include individuals with substantial intellectual disability. Conclusions Differences in attention to faces could constitute a feature discriminative between individuals with and without ASD across the lifespan, whereas between-group differences in looking at activities may shift with development. These findings may have applications in the search for underlying biological indicators specific to ASD. Trial registration ClinicalTrials.gov identifier NCT02668991.
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- 2020
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14. Reducing mental-illness stigma via high school clubs: A matched-pair, cluster-randomized trial
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Shaikh I. Ahmad, Brittany N. Nielsen, Stephen P. Hinshaw, and Bennett L. Leventhal
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medicine.medical_specialty ,Social Psychology ,Health Policy ,Public Health, Environmental and Occupational Health ,Stigma (botany) ,Mental illness ,medicine.disease ,Mental health ,Matched pair ,Psychiatry and Mental health ,Clinical Psychology ,medicine ,Health education ,Construal level theory ,Cluster randomised controlled trial ,Psychiatry ,School based intervention ,Psychology - Published
- 2020
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15. 3.47 Social Interaction Via Online Peer Groups Promotes Social Communication for Individuals with ASD
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Hye-Ryeon Lee, Faraz Fadavi, Young-Shin Kim, and Bennett L. Leventhal
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Psychiatry and Mental health ,Developmental and Educational Psychology - Published
- 2022
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16. 2.82 Functional Activity, Cognition, Emotion and Thinking Scale (FACETS): Initial Examination of Reliability and Utility
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Bennett L. Leventhal, Kseniia Konishcheva, Elie Rotenberg, Anirudh Krishnakumar, Naima Page, Laure Gares, Laetitia Almaraz, Bruno Falissard, Arno Klein, and Ariel B. Lindner
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Psychiatry and Mental health ,Developmental and Educational Psychology - Published
- 2022
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17. 3.74 Validation of the Child Behavior Checklist and Achenbach Test Observation Form for Use With american indian Children in the Navajo Nation
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Jaehwa Choi, Bennett L. Leventhal, Somer Bishop, Brandon Rennie, Amber Leckie, Ellen Geib, Joseph Davis, Ashley Wegele, Carolyn Roman, Johnney Lewis, Debra MacKenzie, and Young-Shin Kim
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Psychiatry and Mental health ,Developmental and Educational Psychology - Published
- 2022
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18. 3.41 Effects of COVID-19 and Social Distancing in Individuals With ASD in a Korean General Population
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Yoon Jae Cho, Eunjoo Kim, Hosanna Kim, Jihyun Kim, Jaehwa Choi, Bokyoung Shin, Adriana Di Martino, Bennett L. Leventhal, and Young-Shin Kim
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Psychiatry and Mental health ,Developmental and Educational Psychology - Published
- 2022
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19. A longitudinal resource for studying connectome development and its psychiatric associations during childhood
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Russell H, Tobe, Anna, MacKay-Brandt, Ryan, Lim, Melissa, Kramer, Melissa M, Breland, Lucia, Tu, Yiwen, Tian, Kristin Dietz, Trautman, Caixia, Hu, Raj, Sangoi, Lindsay, Alexander, Vilma, Gabbay, F Xavier, Castellanos, Bennett L, Leventhal, R Cameron, Craddock, Stanley J, Colcombe, Alexandre R, Franco, and Michael P, Milham
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Diffusion Magnetic Resonance Imaging ,Mental Health ,Adolescent ,Connectome ,Brain ,Humans ,Child - Abstract
Most psychiatric disorders are chronic, associated with high levels of disability and distress, and present during pediatric development. Scientific innovation increasingly allows researchers to probe brain-behavior relationships in the developing human. As a result, ambitions to (1) establish normative pediatric brain development trajectories akin to growth curves, (2) characterize reliable metrics for distinguishing illness, and (3) develop clinically useful tools to assist in the diagnosis and management of mental health and learning disorders have gained significant momentum. To this end, the NKI-Rockland Sample initiative was created to probe lifespan development as a large-scale multimodal dataset. The NKI-Rockland Sample Longitudinal Discovery of Brain Development Trajectories substudy (N = 369) is a 24- to 30-month multi-cohort longitudinal pediatric investigation (ages 6.0-17.0 at enrollment) carried out in a community-ascertained sample. Data include psychiatric diagnostic, medical, behavioral, and cognitive phenotyping, as well as multimodal brain imaging (resting fMRI, diffusion MRI, morphometric MRI, arterial spin labeling), genetics, and actigraphy. Herein, we present the rationale, design, and implementation of the Longitudinal Discovery of Brain Development Trajectories protocol.
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- 2021
20. Visual Preference for Biological Motion in Children and Adults with Autism Spectrum Disorder: An Eye-Tracking Study
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Seth Ness, Robert L. Hendren, Bennett L. Leventhal, Matthew Boice, Matthew S. Goodwin, Andrew Skalkin, Frederick Shic, Abigail Bangerter, Gahan Pandina, Dzmitry A. Kaliukhovich, Nikolay V. Manyakov, and Geraldine Dawson
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Male ,Visual perception ,Eye Movements ,Autism Spectrum Disorder ,Autism ,Motion Perception ,Audiology ,Motion (physics) ,0302 clinical medicine ,Task Performance and Analysis ,Developmental and Educational Psychology ,Attention ,Prospective Studies ,Child ,Eye-Tracking Technology ,Pediatric ,05 social sciences ,Middle Aged ,Biological motion ,Fixation ,Mental Health ,Autism spectrum disorder ,Female ,Psychology ,050104 developmental & child psychology ,Adult ,medicine.medical_specialty ,Adolescent ,Intellectual and Developmental Disabilities (IDD) ,Developmental & Child Psychology ,Fixation, Ocular ,Education ,03 medical and health sciences ,Young Adult ,Clinical Research ,Ocular ,medicine ,Humans ,0501 psychology and cognitive sciences ,Original Paper ,Psychology and Cognitive Sciences ,Eye movement ,Videotape Recording ,medicine.disease ,Brain Disorders ,Fixation (visual) ,Eye tracking ,Eye-tracking ,030217 neurology & neurosurgery ,Photic Stimulation ,Biomarkers - Abstract
Participants with autism spectrum disorder (ASD) (n = 121, mean [SD] age: 14.6 [8.0] years) and typically developing (TD) controls (n = 40, 16.4 [13.3] years) were presented with a series of videos representing biological motion on one side of a computer monitor screen and non-biological motion on the other, while their eye movements were recorded. As predicted, participants with ASD spent less overall time looking at presented stimuli than TD participants (P –3) and showed less preference for biological motion (P –5). Participants with ASD also had greater average latencies than TD participants of the first fixation on both biological (P P
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- 2021
21. Shaping the future of child and adolescent psychiatry
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Dainius Pūras, Bruno Falissard, Daniel Fung, Vlatka Boričević, Kai von Klitzing, Inna Feldman, Ciaran Clark, Bennett L. Leventhal, María Beatriz Moyano, Tarun Dua, Norbert Skokauskas, Chiara Servili, Lois T. Flaherty, George C Patton, Panos Vostanis, and Anthony P. S. Guerrero
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medicine.medical_specialty ,lcsh:RC435-571 ,Context (language use) ,Psykiatri ,03 medical and health sciences ,0302 clinical medicine ,Forensic psychiatry ,lcsh:Psychiatry ,medicine ,Child and adolescent psychiatry ,0501 psychology and cognitive sciences ,Psychiatry ,Infant mental health ,Right to health ,Public health ,age-of-onset ,mental-health ,epidemiology ,disorders ,05 social sciences ,lcsh:RJ1-570 ,lcsh:Pediatrics ,medicine.disease ,Mental health ,030227 psychiatry ,Substance abuse ,Psychiatry and Mental health ,Editorial ,Pediatrics, Perinatology and Child Health ,Psychology ,050104 developmental & child psychology - Abstract
Child and adolescent psychiatry is in a unique position to respond to the growing public health challenges associated with the large number of mental disorders arising early in life, but some changes may be necessary to meet these challenges. In this context, the future of child and adolescent psychiatry was considered by the Section on Child and Adolescent Psychiatry of the World Psychiatric Association (WPA CAP), the International Association for Child and Adolescent Psychiatry and Allied Professions (IACAPAP), the World Association for Infant Mental Health (WAIMH), the International Society for Adolescent Psychiatry and Psychology (ISAPP), the UN Special Rapporteur on the Right to Health, representatives of the WHO Department of Mental Health and Substance Abuse, and other experts. We take this opportunity to outline four consensus priorities for child and adolescent psychiatry over the next decade: increase the workforce necessary for providing care for children, adolescents and families facing mental disorders; reorienting child and adolescent mental health services to be more responsive to broader public health needs; increasing research and research training while also integrating new research finding promptly and efficiently into clinical practice and research training; Increasing efforts in advocacy.
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- 2019
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22. Investigation of gene-environment interactions in relation to tic severity
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Hyun Ju Hong, Y.-J. Koh, Andrea Dietrich, J. Song, Pablo Mir, Dong-Ho Song, Samuel Kuperman, Keun-Ah Cheon, Pieter J. Hoekstra, Gary A. Heiman, Barbara J. Coffey, Jeremiah M. Scharf, Tammy Hedderly, Young Shin Kim, Jay A. Tischfield, Chaim Huyser, Lawrence W. Brown, Mohamed Abdulkadir, Blanca Garcia-Delgar, Marcos Madruga-Garrido, Laura Ibanez-Gomez, Bennett L. Leventhal, Frank Visscher, Astrid Morer, Robert A. King, Dorothy E. Grice, Carol A. Mathews, Donald L. Gilbert, Dongmei Yu, Veit Roessner, Alexander Münchau, Samuel H. Zinner, Eun-Young Shin, Thomas V. Fernandez, Isobel Heyman, Athanasios Maras, Lisa Osiecki, Kerstin J. Plessen, Sodahm Kook, Yongsun Kim, and J. Hagstroem
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Genetics ,Candidate gene ,Autism spectrum disorder ,mental disorders ,Multiple comparisons problem ,medicine ,SNP ,Genome-wide association study ,Single-nucleotide polymorphism ,Biology ,medicine.disease ,Tourette syndrome ,Genetic association - Abstract
Tourette syndrome (TS) is a neuropsychiatric disorder with involvement of genetic and environmental factors. We investigated genetic loci previously implicated in Tourette syndrome and associated disorders in interaction with pre- and perinatal adversity in relation to tic severity using a case-only (N=518) design. We assessed 98 single nucleotide polymorphisms (SNPs) selected from (I) top SNPs from genome-wide association studies (GWASs) of TS; (II) top SNPs from GWASs of obsessive-compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD); (III) SNPs previously implicated in candidate gene-studies of TS; (IV) SNPs previously implicated in OCD or ASD; and (V) tagging SNPs in neurotransmitter-related candidate genes. Linear regression models were used to examine the main effects of the SNPs on tic severity, and the interaction effect of these SNPs with a cumulative pre- and perinatal adversity score. Replication was sought for SNPs that met the threshold of significance (after correcting for multiple testing) in a replication sample (N = 678). One SNP (rs7123010), previously implicated in a TS meta-analysis, was significantly related to higher tic severity. We found a gene-environment interaction for rs6539267, another top TS GWAS SNP. These findings were not independently replicated. Our study highlights the future potential of TS GWAS top hits in gene-environment studies.
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- 2021
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23. Prenatal Exposure to Paternal Smoking and likelihood for Autism Spectrum Disorder
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Stephen Sanders, Shan Dong, Bora Kim, Young Shin Kim, Seung-Jin Yoo, Patricia S. Hong, Ki-Chung Paik, Ho-Jang Kwon, Yun-Joo Koh, Young-Suk Kim, Myung Ho Lim, Bennett L. Leventhal, Mina Ha, and Hosanna Kim
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Autism Spectrum Disorder ,Autism ,Reproductive health and childbirth ,0302 clinical medicine ,Pregnancy ,Risk Factors ,Epidemiology ,Developmental and Educational Psychology ,2.1 Biological and endogenous factors ,Psychology ,Spectrum disorder ,Aetiology ,Pediatric ,0303 health sciences ,Smoking ,risk factor epidemiology ,Causality ,Mental Health ,Autism spectrum disorder ,Prenatal Exposure Delayed Effects ,Specialist Studies in Education ,Cognitive Sciences ,Female ,Biological plausibility ,social and economic factors ,Clinical psychology ,medicine.medical_specialty ,autism spectrum disorders ,Intellectual and Developmental Disabilities (IDD) ,Developmental & Child Psychology ,Article ,03 medical and health sciences ,environmental factors ,2.3 Psychological ,030225 pediatrics ,Behavioral and Social Science ,Tobacco ,mental disorders ,medicine ,Genetics ,Humans ,Family ,Risk factor ,Prenatal exposure ,030304 developmental biology ,Tobacco Smoke and Health ,Prevention ,medicine.disease ,Brain Disorders ,Etiology - Abstract
Genetics, environment, and their interactions impact autism spectrum disorder etiology. Smoking is a suspected autism spectrum disorder risk factor due to biological plausibility and high prevalence. Using two large epidemiological samples, we examined whether autism spectrum disorder was associated with prenatal paternal smoking in a Discovery sample ( N = 10,245) and an independent Replication sample ( N = 29,773). Paternal smoking was retrospectively assessed with questionnaires. Likelihood of having autism spectrum disorder was estimated with the Autism Spectrum Screening Questionnaire at three levels: low (Lay abstract What is Already Known about This Subject: Genetics, (including de novo mutations), environmental factors (including toxic exposures), and their interactions impact autism spectrum disorder etiology. Paternal smoking is a candidate risk for autism spectrum disorder due to biological plausibility, high prevalence, and potential intervention. What This Study Adds: This original study and its replication confirms that paternal factors can substantially contribute to autism spectrum disorder risk for their offspring. It specifically indicates that paternal smoking both before and during pregnancy contributes significantly to autism spectrum disorder risk. Implications for practice, research, or policy: Smoking prevention, especially in pregnancy planning, may decrease autism spectrum disorder risk in offspring.
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- 2021
24. 45.7 Hidden in Plain Sight: Users of Mental Health Services Want to Participate in Research
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Victoria Bakken, Kaban Koochakpour, Øystein Nytrø, Bennett L. Leventhal, Norbert Skokauskas, Odd Sverre Westbye, Thomas Brox Røst, Carolyn E. Clausen, and Roman A. Koposov
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Sight ,Psychiatry and Mental health ,business.industry ,Internet privacy ,Developmental and Educational Psychology ,business ,Psychology ,Mental health - Published
- 2021
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25. A longitudinal resource for studying connectome development and its psychiatric associations during childhood
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Lindsay Alexander, Hu C, Francisco X. Castellanos, Michael P. Milham, Tobe Rh, Melissa Kramer, Sangoi R, Melissa Breland, Gabbay, Anna MacKay-Brandt, Bennett L. Leventhal, Stanley J. Colcombe, Craddock Rc, Franco Ar, Trautman Kd, Tu L, and Ryan Lim
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Distress ,medicine.medical_specialty ,Neuroimaging ,Connectome ,medicine ,Normative ,Actigraphy ,Cognition ,Psychiatry ,Psychology ,Mental health ,Diffusion MRI - Abstract
Most psychiatric disorders are chronic, associated with high levels of disability and distress, and present during pediatric development. Scientific innovation increasingly allows researchers to probe brain-behavior relationships in the developing human. As a result, ambitions to (1) establish normative pediatric brain development trajectories akin to growth curves, (2) characterize reliable metrics for distinguishing illness, and (3) develop clinically useful tools to assist in the diagnosis and management of mental health and learning disorders have gained significant momentum. To this end, the NKI-Rockland Sample initiative was created to probe lifespan development as a large-scale multimodal dataset. The NKI-Rockland Sample Longitudinal Discovery of Brain Development Trajectories substudy (N=369) is a 24- to 30-month multi-cohort longitudinal pediatric investigation (ages 6.0-17.0 at enrollment) carried out in a community-ascertained sample. Data include psychiatric diagnostic, medical, behavioral, and cognitive phenotyping, as well as multimodal brain imaging (resting fMRI, diffusion MRI, morphometric MRI, arterial spin labeling), genetics, and actigraphy. Herein, we present the rationale, design, and implementation of the Longitudinal Discovery of Brain Development Trajectories protocol.
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- 2021
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26. Differences in the Severity and Variability of Restricted and Repetitive Behaviors in ASD Children With and Without Service Experiences
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Ju Hee Park, Yun-Joo Koh, Young Shin Kim, and Bennett L. Leventhal
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030506 rehabilitation ,Group membership ,School age child ,genetic structures ,05 social sciences ,medicine.disease ,behavioral disciplines and activities ,Article ,03 medical and health sciences ,Psychiatry and Mental health ,Clinical Psychology ,Autism spectrum disorder ,mental disorders ,Developmental and Educational Psychology ,medicine ,Autism ,0501 psychology and cognitive sciences ,0305 other medical science ,Psychology ,050104 developmental & child psychology ,Clinical psychology - Abstract
Background Despite the importance of restricted and repetitive behaviors (RRBs) in diagnosing autism spectrum disorder (ASD), specific RRBs that distinguish children with ASD who are receiving services from those who have ASD but are unidentified and untreated until school age remain unclear. This study examined the differences in the severity and variability of RRBs among three groups (ASD with service experiences [ASDws], ASD without service experiences [ASDwos], and No ASD) and investigated specific RRBs predicting group membership. Method A total of 296 children who screened positive for ASD completed confirmative diagnostic assessments. The severity and variability scores of RRBs were obtained using 16 items of the Autism Diagnostic Interview-Revised. Results Both ASD groups had higher proportions of children with severe RRBs for the majority of RRBs and exhibited a greater number of RRBs than the No ASD group. However, discrepancies between the ASDwos and the No ASD groups were not as apparent as those between the ASDws and the No ASD groups. RRBs characterized by a repetitive motor/physical component and unusual sensory responses differentiated the ASDws group from the ASDwos group. Conversely, RRBs characterized by rigid adherence to routine, and ritualistic behavior increased the odds of membership in the ASDwos group over the No ASD group. Conclusions Our results may improve the ability of clinicians and parents to detect ASD in the community by observing specific RRBs, especially in cognitively intact school-aged children who show significant compulsive/ritualistic behaviors and rigidity to routines/sameness RRBs, even in the absence of multiple RRBs or severe repetitive sensorimotor behaviors.
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- 2020
27. Familial coaggregation of major psychiatric disorders in first-degree relatives of individuals with autism spectrum disorder: a nationwide population-based study
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Tzeng Ji Chen, Hohui E. Wang, Tung Ping Su, Kai Lin Huang, Chih Ming Cheng, Mu Hong Chen, Ya Mei Bai, Shih-Jen Tsai, Ju Wei Hsu, Cheng Ta Li, and Bennett L. Leventhal
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medicine.medical_specialty ,Bipolar Disorder ,Autism Spectrum Disorder ,Population ,behavioral disciplines and activities ,03 medical and health sciences ,0302 clinical medicine ,mental disorders ,Intellectual disability ,medicine ,Humans ,Bipolar disorder ,First-degree relatives ,education ,Psychiatry ,Applied Psychology ,030304 developmental biology ,0303 health sciences ,education.field_of_study ,Depressive Disorder, Major ,business.industry ,medicine.disease ,Psychiatry and Mental health ,Autism spectrum disorder ,Schizophrenia ,Attention Deficit Disorder with Hyperactivity ,Cohort ,Major depressive disorder ,business ,030217 neurology & neurosurgery - Abstract
BackgroundFamily coaggregation of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD) and schizophrenia have been presented in previous studies. The shared genetic and environmental factors among psychiatric disorders remain elusive.MethodsThis nationwide population-based study examined familial coaggregation of major psychiatric disorders in first-degree relatives (FDRs) of individuals with ASD. Taiwan's National Health Insurance Research Database was used to identify 26 667 individuals with ASD and 67 998 FDRs of individuals with ASD. The cohort was matched in 1:4 ratio to 271 992 controls. The relative risks (RRs) and 95% confidence intervals (CI) of ADHD, ASD, BD, MDD and schizophrenia were assessed among FDRs of individuals with ASD and ASD with intellectual disability (ASD-ID).ResultsFDRs of individuals with ASD have higher RRs of major psychiatric disorders compared with controls: ASD 17.46 (CI 15.50–19.67), ADHD 3.94 (CI 3.72–4.17), schizophrenia 3.05 (CI 2.74–3.40), BD 2.22 (CI 1.98–2.48) and MDD 1.88 (CI 1.76–2.00). Higher RRs of schizophrenia (4.47, CI 3.95–5.06) and ASD (18.54, CI 16.18–21.23) were observed in FDRs of individuals with both ASD-ID, compared with ASD only.ConclusionsThe risk for major psychiatric disorders was consistently elevated across all types of FDRs of individuals with ASD. FDRs of individuals with ASD-ID are at further higher risk for ASD and schizophrenia. Our results provide leads for future investigation of shared etiologic pathways of ASD, ID and major psychiatric disorders and highlight the importance of mental health care delivered to at-risk families for early diagnoses and interventions.
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- 2020
28. Clinical Decision Support Systems: An Innovative Approach to Enhancing Child and Adolescent Mental Health Services
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Øystein Nytrø, Norbert Skokauskas, Bennett L. Leventhal, Roman A. Koposov, Carolyn E. Clausen, Odd Sverre Westbye, Thomas Brox Røst, Kaban Koochakpour, Victoria Bakken, and Ketil Thorvik
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Mental Health Services ,Adolescent ,Mental Disorders ,MEDLINE ,Decision Support Systems, Clinical ,Clinical decision support system ,Mental health ,Child and adolescent ,Psychiatry and Mental health ,Nursing ,Adolescent Health Services ,Developmental and Educational Psychology ,Humans ,Psychology ,Child - Published
- 2020
29. Clinical Validation of the Autism Behavior Inventory: Caregiver-Rated Assessment of Core and Associated Symptoms of Autism Spectrum Disorder
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Matthew S. Goodwin, Abigail Bangerter, Robert L. Hendren, Geraldine Dawson, Kai Fai Ho, Michael G. Aman, Seth Ness, Bennett L. Leventhal, Frederick Shic, Anna J. Esbensen, David Lewin, Gahan Pandina, and Mark Opler
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Male ,Autism Spectrum Disorder ,Autism ,0302 clinical medicine ,Clinical trials ,Caregiver-reported outcomes ,Developmental and Educational Psychology ,Medical diagnosis ,Autism spectrum disorder ,Child ,Reliability (statistics) ,Pediatric ,Core (anatomy) ,screening and diagnosis ,05 social sciences ,Behavior change ,Detection ,Mental Health ,Caregivers ,Female ,Psychology ,Rating scales and instruments ,050104 developmental & child psychology ,Clinical psychology ,4.2 Evaluation of markers and technologies ,Adult ,Psychometrics ,Intellectual and Developmental Disabilities (IDD) ,Developmental & Child Psychology ,Assessment ,behavioral disciplines and activities ,Education ,03 medical and health sciences ,Rating scale ,Clinical Research ,mental disorders ,medicine ,Humans ,0501 psychology and cognitive sciences ,cardiovascular diseases ,Original Paper ,Psychology and Cognitive Sciences ,Construct validity ,Reproducibility of Results ,medicine.disease ,Brain Disorders ,body regions ,sense organs ,030217 neurology & neurosurgery - Abstract
There is a need for measures to track symptom change in autism spectrum disorder (ASD). We conducted a validation study on a revised version of the Autism Behavior Inventory (ABI), and a short form (ABI-S). Caregivers of individuals (6–54 years) with confirmed diagnoses of ASD (N = 144) completed the ABI and other rating scales at 4 time points. Scale consistency for each domain, 3–5 day test–retest reliability, and construct validity, determined by comparison to pre-specified scales, were all good. Change in the ABI was congruent with changes in other instruments. Collectively, results suggest incipient suitability of the ABI as a measure of changes in core and associated symptoms of ASD. Trial Registration NCT02299700. Electronic supplementary material The online version of this article (10.1007/s10803-019-03965-7) contains supplementary material, which is available to authorized users.
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- 2020
30. Prevalence and cumulative incidence of autism spectrum disorders and the patterns of co-occurring neurodevelopmental disorders in a total population sample of 5-year-old children
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Yui Sakamoto, Masaki Adachi, Manabu Saito, Michio Takahashi, Ayako Osato-Kaneda, Sumi Kato, Amy Shui, Bennett L. Leventhal, Tomoya Hirota, Young Shin Kim, and Kazuhiko Nakamura
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Male ,Pediatrics ,Neurology ,Cumulative incidence ,Autism Spectrum Disorder ,Autism ,Comorbidity ,Total population ,lcsh:RC346-429 ,0302 clinical medicine ,Japan ,Risk Factors ,Prevalence ,Medicine ,Aetiology ,Child ,Pediatric ,Incidence ,05 social sciences ,Neuropsychology ,Cognition ,a total population sample ,Psychiatry and Mental health ,Mental Health ,Autism spectrum disorder ,Child, Preschool ,Population Surveillance ,Female ,050104 developmental & child psychology ,Pediatric Research Initiative ,medicine.medical_specialty ,Intellectual and Developmental Disabilities (IDD) ,prevalence ,Clinical Sciences ,Sample (statistics) ,Risk Assessment ,behavioral disciplines and activities ,03 medical and health sciences ,Co occurring ,Developmental Neuroscience ,Clinical Research ,mental disorders ,Humans ,0501 psychology and cognitive sciences ,Preschool ,Molecular Biology ,lcsh:Neurology. Diseases of the nervous system ,A total population study ,business.industry ,Research ,Neurosciences ,Infant ,medicine.disease ,Confidence interval ,Brain Disorders ,Cross-Sectional Studies ,Socioeconomic Factors ,Neurodevelopmental Disorders ,Sample size determination ,Co-existing neurodevelopmental disorders ,business ,030217 neurology & neurosurgery ,2.4 Surveillance and distribution ,Developmental Biology - Abstract
Background: Whether there is a true increase in Autism Spectrum Disorder (ASD) frequency or not remains unclear. Additionally, the rates of co-existing neurodevelopmental disorders (NDD) in a total population sample hasn't been fully examined before. Methods: All 5-year-old children in the catchment area in Japan underwent the screening annually from the year 2013 - 2016. Screen-positive children were invited to a comprehensive assessment, including child and parent interview, behavioral observation, and cognitive and motor function testing. All cases were reviewed by a multidisciplinary team. ASD prevalence and cumulative incidence were computed. Outcomes: Caregivers of 3,954 children returned the screening, among which 559 children underwent the assessment with 87 children receiving an ASD diagnosis. Adjusted ASD prevalence was 3.22% (95% Confidence Interval (CI): 2.66 - 3.76). The male to female ratio of the crude prevalence was 2.2:1. The cumulative incidence of ASD up to 5 years of age for the total study years was 1.31 (95% CI: 1.00 - 1.62). A generalized linear model revealed no significant linear trends in 5-year cumulative incidence over the study years. Only 11.5% of children had ASD alone; the remaining 88.5% were found to have at least one co-existing NDD. Interpretation: Our findings demonstrate the stability of the 5-year cumulative incidence of ASD, implying no true rise in ASD incident cases over the 4-year study period in the study catchment area. High rates of co-existing NDDs reflect the importance of investigating broad developmental challenges in ASD children. Funding: Grants-in-Aid for Scientific Research and Hirosaki Institute of Neuroscience. Declaration of Interest: The authors have no financial relationships relevant to this article to disclose. Ethical Approval: This study was approved by the Committee of Medical Ethics of Hirosaki University Graduate School of Medicine. Moreover, the information security policies of the city and committee were followed to protect the personal data of the participants.
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- 2020
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31. Testing an individualized digital decision assist system for the diagnosis and management of mental and behavior disorders in children and adolescents
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Bennett L. Leventhal, Carolyn E. Clausen, Odd Sverre Westbye, Roman A. Koposov, Norbert Skokauskas, Kaban Koochakpour, Thomas Brox Røst, Øystein Nytrø, Victoria Bakken, and Ketil Thorvik
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medicine.medical_specialty ,Adolescent ,VDP::Social science: 200::Psychology: 260 ,Attention-deficit/hyperactivity disorder (ADHD) ,Health Informatics ,Comorbidity ,Health outcomes ,lcsh:Computer applications to medicine. Medical informatics ,Clinical decision support system ,Health informatics ,IDDEAS ,03 medical and health sciences ,Study Protocol ,0302 clinical medicine ,medicine ,Humans ,0501 psychology and cognitive sciences ,VDP::Medisinske Fag: 700 ,030212 general & internal medicine ,Child ,Innovation ,Clinical decision support system (CDSS) ,Episode of care ,Diagnostic Tests, Routine ,business.industry ,Norway ,Health Policy ,05 social sciences ,Usability ,Child and adolescent mental health services (CAMHS) ,Decision Support Systems, Clinical ,medicine.disease ,Mental health ,Computer Science Applications ,Attention Deficit Disorder with Hyperactivity ,Family medicine ,VDP::Samfunnsvitenskap: 200::Psykologi: 260 ,lcsh:R858-859.7 ,business ,050104 developmental & child psychology - Abstract
Background Nearly half of all mental health disorders develop prior to the age of 15. Early assessments, diagnosis, and treatment are critical to shortening single episodes of care, reducing possible comorbidity and long-term disability. In Norway, approximately 20% of all children and adolescents are experiencing mental health problems. To address this, health officials in Norway have called for the integration of innovative approaches. A clinical decision support system (CDSS) is an innovative, computer-based program that provides health professionals with clinical decision support as they care for patients. CDSS use standardized clinical guidelines and big data to provide guidance and recommendations to clinicians in real-time. IDDEAS (Individualised Digital DEcision Assist System) is a CDSS for diagnosis and treatment of child and adolescent mental health disorders. The aim of IDDEAS is to enhance quality, competency, and efficiency in child and adolescent mental health services (CAMHS). Methods/design IDDEAS is a mixed-methods innovation and research project, which consists of four stages: 1) Assessment of Needs and Preparation of IDDEAS; 2) The Development of IDDEAS CDSS Model; 3) The Evaluation of the IDDEAS CDSS; and, 4) Implementation & Dissemination. Both qualitative and quantitative methods will be used for the evaluation of IDDEAS CDSS model. Child and adolescent psychologists and psychiatrists (n = 30) will evaluate the IDDEAS` usability, acceptability and relevance for diagnosis and treatment of attention-deficit/hyperactivity disorder. Discussion The IDDEAS CDSS model is the first guidelines and data-driven CDSS to improve efficiency of diagnosis and treatment of child and adolescent mental health disorders in Norway. Ultimately, IDDEAS will help to improve patient health outcomes and prevent long-term adverse outcomes by providing each patient with evidence-based, customized clinical care. © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
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- 2020
32. Visual Exploration in Autism Spectrum Disorder: Exploring Age Differences and Dynamic Features Using Recurrence Quantification Analysis
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Meenakshi Chatterjee, Andrew Skalkin, David Lewin, Robert L. Hendren, Luke Mason, Seth Ness, Bennett L. Leventhal, Geraldine Dawson, Abigail Bangerter, Matthew Boice, Gahan Pandina, Nikolay V. Manyakov, Frederick Shic, and Matthew S. Goodwin
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genetic structures ,Age differences ,General Neuroscience ,05 social sciences ,medicine.disease ,Gaze ,03 medical and health sciences ,0302 clinical medicine ,Autism spectrum disorder ,Recurrence quantification analysis ,Fixation (visual) ,medicine ,Eye tracking ,Autism ,0501 psychology and cognitive sciences ,Neurology (clinical) ,Disengagement theory ,Psychology ,030217 neurology & neurosurgery ,Genetics (clinical) ,050104 developmental & child psychology ,Cognitive psychology - Abstract
Eye-tracking studies have demonstrated that individuals with autism spectrum disorder sometimes show differences in attention and gaze patterns. This includes preference for certain nonsocial objects, heightened attention to detail, and more difficulty with attention shifting and disengagement, which may be associated with restricted and repetitive behaviors. This study utilized a visual exploration task and replicates findings of reduced number of objects explored and increased fixation duration on high autism interest objects in a large sample of individuals with autism spectrum disorder (n = 129, age 6-54 years) in comparison with a typically developing group. These findings correlated with parent-reported repetitive behaviors. Additionally, we applied recurrent quantification analysis to enable identification of new eye-tracking features, which accounted for temporal and spatial differences in viewing patterns. These new features were found to discriminate between autism spectrum disorder and typically developing groups and were correlated with parent-reported repetitive behaviors. Original and novel eye-tracking features identified by recurrent quantification analysis differed in their relationships to reported behaviors and were dependent on age. Trial Registration: NCT02299700. Autism Research 2018, 11: 1554-1566. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Using eye-tracking technology and a visual exploration task, we showed that people with autism spectrum disorder (ASD) spend more time looking at particular kinds of objects, like trains and clocks, and look at fewer objects overall than people without ASD. Where people look and the order in which they look at objects were related to the restricted and repetitive behaviors reported by parents. Eye-tracking may be a useful addition to parent reports for measuring changes in behavior in individuals with ASD.
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- 2018
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33. A systematic review of screening tools in non-young children and adults for autism spectrum disorder
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Young Shin Kim, Bennett L. Leventhal, Tomoya Hirota, Ryuhei So, and Richard A. Epstein
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Adult ,Adolescent ,Autism Spectrum Disorder ,Population ,MEDLINE ,CINAHL ,Cochrane Library ,Autism Diagnostic Observation Schedule ,Young Adult ,03 medical and health sciences ,0302 clinical medicine ,030225 pediatrics ,mental disorders ,Developmental and Educational Psychology ,medicine ,Humans ,Mass Screening ,0501 psychology and cognitive sciences ,Child ,education ,education.field_of_study ,Autism Diagnostic Interview ,05 social sciences ,Reproducibility of Results ,medicine.disease ,Clinical Psychology ,Autism spectrum disorder ,Child, Preschool ,Autism ,Psychology ,050104 developmental & child psychology ,Clinical psychology - Abstract
Background Existing reviews of screening tools for Autism Spectrum Disorder (ASD) focus on young children, and not all screening tools have been examined against validated diagnostic procedures. Aims To examine the validity of screening tools for ASD in non-young children and adults to provide clinical recommendations about the use of these tools in a variety of clinical settings. Methods and Procedures Electronic databases, including MEDLINE, EMBASE, PsychINFO, Cochrane Library and CINAHL, were searched through March 2017. Studies examining the validity of ASD screening tools against the Autism Diagnostic Observation Schedule and/or the Autism Diagnostic Interview - Revised in non-young children (age 4 or above) and adults were included. Three authors independently reviewed each article for data extraction and quality assessment. Outcomes and Results 14 studies met the inclusion criteria, of which 11 studies were with children (4–18 years of age) and 3 studies included adults only (19 years of age and above). Included studies were conducted in a general population/low-risk sample (N = 3) and a clinically referred/high-risk sample (N = 11). In total 11 tools were included. Conclusions and Implications Only three screening tools (the Autism-Spectrum Quotient, the Social Communication Questionnaire, and the Social Responsiveness Scale) were examined in more than 2 studies. These tools may assist in differentiating ASD from other neurodevelopmental and psychiatric disorders or typically developed children. In young adult populations, the paucity of the existing research in this group limits definitive conclusion and recommendations.
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- 2018
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34. De Novo Sequence and Copy Number Variants Are Strongly Associated with Tourette Disorder and Implicate Cell Polarity in Pathogenesis
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Sheng Wang, Jeffrey D. Mandell, Yogesh Kumar, Nawei Sun, Montana T. Morris, Juan Arbelaez, Cara Nasello, Shan Dong, Clif Duhn, Xin Zhao, Zhiyu Yang, Shanmukha S. Padmanabhuni, Dongmei Yu, Robert A. King, Andrea Dietrich, Najah Khalifa, Niklas Dahl, Alden Y. Huang, Benjamin M. Neale, Giovanni Coppola, Carol A. Mathews, Jeremiah M. Scharf, Thomas V. Fernandez, Joseph D. Buxbaum, Silvia De Rubeis, Dorothy E. Grice, Jinchuan Xing, Gary A. Heiman, Jay A. Tischfield, Peristera Paschou, A. Jeremy Willsey, Matthew W. State, Mohamed Abdulkadir, Benjamin Bodmer, Yana Bromberg, Lawrence W. Brown, Keun-Ah Cheon, Barbara J. Coffey, Li Deng, Lonneke Elzerman, Carolin Fremer, Blanca Garcia-Delgar, Donald L. Gilbert, Julie Hagstrøm, Tammy Hedderly, Isobel Heyman, Pieter J. Hoekstra, Hyun Ju Hong, Chaim Huyser, Eun-Joo Kim, Young Key Kim, Young-Shin Kim, Yun-Joo Koh, Sodahm Kook, Samuel Kuperman, Bennett L Leventhal, Andrea G. Ludolph, Marcos Madruga-Garrido, Athanasios Maras, Pablo Mir, Astrid Morer, Montana T Morris, Kirsten Müller-Vahl, Alexander Münchau, Tara L. Murphy, Kerstin J. Plessen, Hannah Poisner, Veit Roessner, Stephan J. Sanders, Eun-Young Shin, Dong-Ho Song, Jungeun Song, Joshua K. Thackray, Jennifer Tübing, Frank Visscher, Sina Wanderer, A Jeremy Willsey, Martin Woods, Yeting Zhang, Samuel H. Zinner, Christos Androutsos, Csaba Barta, Luca Farkas, Jakub Fichna, Marianthi Georgitsi, Piotr Janik, Iordanis Karagiannidis, Anastasia Koumoula, Peter Nagy, Joanna Puchala, Renata Rizzo, Natalia Szejko, Urszula Szymanska, Zsanett Tarnok, Vaia Tsironi, Tomasz Wolanczyk, Cezary Zekanowski, Cathy L. Barr, James R. Batterson, Cheston Berlin, Ruth D. Bruun, Cathy L. Budman, Danielle C. Cath, Sylvain Chouinard, Nancy J. Cox, Sabrina Darrow, Lea K. Davis, Yves Dion, Nelson B. Freimer, Marco A. Grados, Matthew E. Hirschtritt, Cornelia Illmann, Roger Kurlan, James F. Leckman, Gholson J. Lyon, Irene A. Malaty, William M. MacMahon, Michael S. Okun, Lisa Osiecki, David L. Pauls, Danielle Posthuma, Vasily Ramensky, Mary M. Robertson, Guy A. Rouleau, Paul Sandor, Harvey S. Singer, Jan Smit, Jae-Hoon Sul, Tourette International Collaborative Genetics Study (TIC Genetics), Tourette Syndrome Genetics Southern and Eastern Europe Initiative (TSGENESEE), Tourette Association of America International Consortium for Genetics (TAAICG), Abdulkadir, M., Arbelaez, J., Bodmer, B., Bromberg, Y., Brown, L.W., Cheon, K.A., Coffey, B.J., Deng, L., Dietrich, A., Dong, S., Duhn, C., Elzerman, L., Fernandez, T.V., Fremer, C., Garcia-Delgar, B., Gilbert, D.L., Grice, D.E., Hagstrøm, J., Hedderly, T., Heiman, G.A., Heyman, I., Hoekstra, P.J., Hong, H.J., Huyser, C., Kim, E.J., Kim, Y.K., Kim, Y.S., King, R.A., Koh, Y.J., Kook, S., Kuperman, S., Leventhal, B.L., Ludolph, A.G., Madruga-Garrido, M., Mandell, J.D., Maras, A., Mir, P., Morer, A., Morris, M.T., Müller-Vahl, K., Münchau, A., Murphy, T.L., Nasello, C., Plessen, K.J., Poisner, H., Roessner, V., Sanders, S.J., Shin, E.Y., Song, D.H., Song, J., State, M.W., Sun, N., Thackray, J.K., Tischfield, J.A., Tübing, J., Visscher, F., Wanderer, S., Wang, S., Willsey, A.J., Woods, M., Xing, J., Zhang, Y., Zhao, X., Zinner, S.H., Androutsos, C., Barta, C., Farkas, L., Fichna, J., Georgitsi, M., Janik, P., Karagiannidis, I., Koumoula, A., Nagy, P., Paschou, P., Puchala, J., Rizzo, R., Szejko, N., Szymanska, U., Tarnok, Z., Tsironi, V., Wolanczyk, T., Zekanowski, C., Barr, C.L., Batterson, J.R., Berlin, C., Bruun, R.D., Budman, C.L., Cath, D.C., Chouinard, S., Coppola, G., Cox, N.J., Darrow, S., Davis, L.K., Dion, Y., Freimer, N.B., Grados, M.A., Hirschtritt, M.E., Huang, A.Y., Illmann, C., Kurlan, R., Leckman, J.F., Lyon, G.J., Malaty, I.A., Mathews, C.A., MacMahon, W.M., Neale, B.M., Okun, M.S., Osiecki, L., Pauls, D.L., Posthuma, D., Ramensky, V., Robertson, M.M., Rouleau, G.A., Sandor, P., Scharf, J.M., Singer, H.S., Smit, J., Sul, J.H., and Yu, D.
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Adult ,Male ,0301 basic medicine ,medicine.medical_specialty ,DNA Copy Number Variations ,Receptors, Cell Surface ,Biology ,Genome ,Article ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,0302 clinical medicine ,RARE ,SCHIZOPHRENIA ,medicine ,Humans ,Copy-number variation ,Child ,NEURODEVELOPMENTAL DISORDERS ,Gene ,lcsh:QH301-705.5 ,Exome sequencing ,030304 developmental biology ,Medicinsk genetik ,Sequence (medicine) ,Genetics ,0303 health sciences ,SEVERE INTELLECTUAL DISABILITY ,Cadherin ,MUTATIONS ,AUTISM SPECTRUM DISORDER ,Cell Polarity ,OBSESSIVE-COMPULSIVE DISORDER ,Cadherins ,medicine.disease ,Pedigree ,PREVALENCE ,CONGENITAL HEART-DISEASE ,GENOME ,030104 developmental biology ,lcsh:Biology (General) ,Schizophrenia ,Medical genetics ,Female ,Cadherins/genetics ,Receptors, Cell Surface/genetics ,Tourette Syndrome/genetics ,Tourette Syndrome/pathology ,TIC Genetics ,Tourette disorder ,cell polarity ,copy number variants ,de novo variants ,gene discovery ,microarray genotyping ,multiplex ,simplex ,whole exome sequencing ,Medical Genetics ,030217 neurology & neurosurgery ,Tourette Syndrome - Abstract
SUMMARY We previously established the contribution of de novo damaging sequence variants to Tourette disorder (TD) through whole-exome sequencing of 511 trios. Here, we sequence an additional 291 TD trios and analyze the combined set of 802 trios. We observe an overrepresentation of de novo damaging variants in simplex, but not multiplex, families; we identify a high-confidence TD risk gene, CELSR3 (cadherin EGF LAG seven-pass G-type receptor 3); we find that the genes mutated in TD patients are enriched for those related to cell polarity, suggesting a common pathway underlying pathobiology; and we confirm a statistically significant excess of de novo copy number variants in TD. Finally, we identify significant overlap of de novo sequence variants between TD and obsessive-compulsive disorder and de novo copy number variants between TD and autism spectrum disorder, consistent with shared genetic risk., In Brief Wang et al. expand their earlier exome-sequencing work in TD, adding 291 trios and conducting combined analyses suggesting de novo variants carry more risk in individuals with unaffected parents, establishing de novo structural variants as risk factors, identifying CELSR3 as a risk gene, and implicating cell polarity in pathogenesis., Graphical Abstract
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- 2018
35. Investigation of previously implicated genetic variants in chronic tic disorders
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Samuel Kuperman, Frank Visscher, Kirsten R. Müller-Vahl, Eun-Young Shin, Jennifer Tübing, Els van den Ban, Sina Wanderer, Hyun Ju Hong, Yun-Joo Koh, Jungeun Song, Gary A. Heiman, Lonneke Elzerman, Donald L. Gilbert, Derek Gordon, Laura Ibanez-Gomez, Keun-Ah Cheon, Douglas Londono, Young Key Kim, Bennett L. Leventhal, Alexander Münchau, Odette Fründt, Andrea G. Ludolph, Astrid Morer, Sodahm Kook, Thomas V. Fernandez, Lawrence W. Brown, Marcos Madruga-Garrido, Ewgeni Jakubovski, Jay A. Tischfield, Mohamed Abdulkadir, Blanca Garcia-Delgar, Carolin Fremer, Samuel H. Zinner, Pablo Mir, Robert A. King, Martin Woods, Veit Roessner, Young Shin Kim, Isobel Heyman, Tara Murphy, Athanasios Maras, Dong-Ho Song, Pieter J. Hoekstra, Tammy Hedderly, Barbara J. Coffey, Andrea Dietrich, Chaim Huyser, Dorothy E. Grice, Kerstin J. Plessen, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Child Psychiatry, and Child and Adolescent Psychiatry / Psychology
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0301 basic medicine ,Male ,Candidate gene ,Genome-wide association study ,Tryptophan Hydroxylase ,Obsessive–compulsive disorder ,Severity of Illness Index ,Linkage Disequilibrium ,PICALM ,0302 clinical medicine ,Candidate gene study ,Obsessive-compulsive disorder ,Pharmacology (medical) ,Child ,POPULATION ,Psychiatry ,Genetics ,LA-TOURETTE-SYNDROME ,education.field_of_study ,SLITRK1 GENE ,Single Nucleotide ,General Medicine ,Transmission disequilibrium test ,Middle Aged ,3. Good health ,Psychiatry and Mental health ,COMPREHENSIVE METAANALYSIS ,Child, Preschool ,HISTIDINE-DECARBOXYLASE ,Cognitive Sciences ,Female ,Microtubule-Associated Proteins ,Adult ,Adolescent ,Genotype ,Clinical Sciences ,Population ,Single-nucleotide polymorphism ,Biology ,Polymorphism, Single Nucleotide ,03 medical and health sciences ,Young Adult ,SNP ,Humans ,Polymorphism ,GENOME-WIDE ASSOCIATION ,AUTISM ,Preschool ,education ,Biological Psychiatry ,FAMILY-BASED ASSOCIATION ,Genetic association ,Family Health ,Original Paper ,Tourette syndrome ,Neurosciences ,OBSESSIVE-COMPULSIVE DISORDER ,Transmission Disequilibrium Test ,CROSS-DISORDER ,030104 developmental biology ,Attention-deficit/hyperactivity disorder ,Tic Disorders ,030217 neurology & neurosurgery ,Genome-Wide Association Study - Abstract
Genetic studies in Tourette syndrome (TS) are characterized by scattered and poorly replicated findings. We aimed to replicate findings from candidate gene and genome-wide association studies (GWAS). Our cohort included 465 probands with chronic tic disorder (93% TS) and both parents from 412 families (some probands were siblings). We assessed 75 single nucleotide polymorphisms (SNPs) in 465 parent–child trios; 117 additional SNPs in 211 trios; and 4 additional SNPs in 254 trios. We performed SNP and gene-based transmission disequilibrium tests and compared nominally significant SNP results with those from a large independent case–control cohort. After quality control 71 SNPs were available in 371 trios; 112 SNPs in 179 trios; and 3 SNPs in 192 trios. 17 were candidate SNPs implicated in TS and 2 were implicated in obsessive–compulsive disorder (OCD) or autism spectrum disorder (ASD); 142 were tagging SNPs from eight monoamine neurotransmitter-related genes (including dopamine and serotonin); 10 were top SNPs from TS GWAS; and 13 top SNPs from attention-deficit/hyperactivity disorder, OCD, or ASD GWAS. None of the SNPs or genes reached significance after adjustment for multiple testing. We observed nominal significance for the candidate SNPs rs3744161 (TBCD) and rs4565946 (TPH2) and for five tagging SNPs; none of these showed significance in the independent cohort. Also, SLC1A1 in our gene-based analysis and two TS GWAS SNPs showed nominal significance, rs11603305 (intergenic) and rs621942 (PICALM). We found no convincing support for previously implicated genetic polymorphisms. Targeted re-sequencing should fully appreciate the relevance of candidate genes. Electronic supplementary material The online version of this article (doi:10.1007/s00406-017-0808-8) contains supplementary material, which is available to authorized users.
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- 2018
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36. Sex difference in risk period for completed suicide following prior attempts: Korea National Suicide Survey (KNSS)
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Se Hyun Kim, Young Shin Kim, Kyooseob Ha, Bora Kim, Eun Young Kim, Bennett L. Leventhal, Yong Min Ahn, and Joongyub Lee
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Adult ,Male ,medicine.medical_specialty ,Health Behavior ,Suicide, Attempted ,Suicidal Ideation ,03 medical and health sciences ,Risk-Taking ,0302 clinical medicine ,Risk Factors ,Surveys and Questionnaires ,Republic of Korea ,medicine ,Humans ,030212 general & internal medicine ,Significant risk ,Psychiatry ,Suicidal ideation ,Aged ,Suicide attempters ,Sex Characteristics ,Suicide mortality ,Middle Aged ,Self Concept ,030227 psychiatry ,Suicide death ,Completed Suicide ,Suicide ,Psychiatry and Mental health ,Clinical Psychology ,Preventive intervention ,Female ,medicine.symptom ,Psychology ,Sex characteristics - Abstract
Objectives We provide an opportunity for implementing preventive interventions to decrease suicide mortality among prior suicide attempters. We aim to identify sex-specific high risk periods and factors for later suicide death among suicide attempters. Methods 8537 suicide attempters of Korea National Suicide Survey were collected from January 1, 2007 to December 31, 2011 and data on suicide death was obtained as of December 31, 2012. The risk period and risk factors for later suicide death was computed by Kaplan-Meier survival estimates and by plotting the hazard function using the Epanechnikov Kernal smoothing method and cox proportional hazard regression modeling. Results The hazard for later suicide death was significant up to 10 months for females and 20 months for males. Age 50–69 years (HR, 3.29; [CI: 1.80–6.02] and not being intoxicated with alcohol (HR, 1.94 [1.27–2.97])) in male attempters were significant risk factors for later suicide death. Conclusion Risk for later suicide death was significantly increased during the first full year following index attempts for all with an addition 8 months of risk for males, especially those of advanced age who were sober at the time of attempt.
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- 2018
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37. 6.11 Clinician and Parent Reporting of Autism Spectrum Disorder Behaviors: Development of a Clinician Version of the Autism Behavior Inventory
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Gahan Pandina, Michael G. Aman, Abigail Bangerter, Robin Halter, Robert L. Hendren, Rachel Ochs-Ross, Bennett L. Leventhal, Martine Meyer, and Jeremiah J. Trudeau
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Psychiatry and Mental health ,Autism spectrum disorder ,Developmental and Educational Psychology ,medicine ,Autism ,medicine.disease ,Psychology ,Clinical psychology - Published
- 2021
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38. 43.1 MACRO INTERVENTIONS IN CHILD AND ADOLESCENT PSYCHIATRY: A HISTORICAL PERSPECTIVE
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Bennett L. Leventhal
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Psychiatry and Mental health ,medicine.medical_specialty ,Psychotherapist ,Perspective (graphical) ,Developmental and Educational Psychology ,Child and adolescent psychiatry ,medicine ,Psychological intervention ,Macro ,Psychology - Published
- 2021
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39. 6.13 What Happens to Children With Autism Spectrum Disorder After Online Group Social Skills Training? A Pilot Study Using an Online, Personalized Peer Group for Application of the Learned Social Skills
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Young Shin Kim, Hye-Ryeon Lee, Faraz Fadavi, Hosanna Kim, and Bennett L. Leventhal
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Psychiatry and Mental health ,Social skills ,Group (mathematics) ,Autism spectrum disorder ,Developmental and Educational Psychology ,medicine ,Peer group ,Psychology ,medicine.disease ,Developmental psychology - Published
- 2021
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40. Autism Spectrum Disorder and School Bullying: Who is the Victim? Who is the Perpetrator?
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Yun Joo Koh, Young S. Kim, Bennett L. Leventhal, and Soonjo Hwang
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Male ,medicine.medical_specialty ,Autism Spectrum Disorder ,Poison control ,Comorbidity ,behavioral disciplines and activities ,Suicide prevention ,Article ,DSM-5 ,03 medical and health sciences ,0302 clinical medicine ,030225 pediatrics ,mental disorders ,Injury prevention ,Developmental and Educational Psychology ,medicine ,Humans ,0501 psychology and cognitive sciences ,Longitudinal Studies ,Child ,Students ,Psychiatry ,Crime Victims ,Schools ,05 social sciences ,Bullying ,medicine.disease ,Cross-Sectional Studies ,Autism spectrum disorder ,Autism ,Female ,Psychology ,050104 developmental & child psychology ,Clinical psychology ,Psychopathology - Abstract
While a growing number of studies indicate associations between experiences of bullying and Autism Spectrum Disorder (ASD), it is not clear what roles comorbid behavioral problems may play. We investigated the experiences of children with ASD as victims and/or perpetrators of bullying. Children with ASD epidemiologically ascertained participated in a cross-sectional study. Although children with ASD showed significantly increased risk for bullying involvement compared to community children, after controlling for comorbid psychopathology and other demographic factors, increased risks for being perpetrators or victim-perpetrators disappeared while risk for being bullied/teased continued to be significantly elevated. This finding will help guide medical, educational and community personnel to effectively identify children with ASD at risk for school bullying and develop interventions.
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- 2017
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41. Clinical decision support systems in child and adolescent psychiatry: a systematic review
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Michael P. Milham, Norbert Skokauskas, Hans-Ulrich Prokosch, Thomas Frodl, María de la Iglesia Vayá, Silvana Quaglini, Bennett L. Leventhal, Øystein Nytrø, Massimo Molteni, Andre Sourander, Roman A. Koposov, Nicola Barbarini, Sturla Fossum, and Francisco X. Castellanos
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medicine.medical_specialty ,Adolescent ,Best practice ,Clinical decision support system ,03 medical and health sciences ,0302 clinical medicine ,Adolescent Psychiatry ,Developmental and Educational Psychology ,medicine ,Child and adolescent psychiatry ,Humans ,030212 general & internal medicine ,Child ,Psychiatry ,Child Psychiatry ,business.industry ,Public health ,General Medicine ,Decision Support Systems, Clinical ,Mental health ,Psychiatry and Mental health ,Systematic review ,Child protection ,Family medicine ,Pediatrics, Perinatology and Child Health ,business ,Inclusion (education) ,030217 neurology & neurosurgery - Abstract
Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13:395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.
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- 2017
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42. Discrepancy in perception of bullying experiences and later internalizing and externalizing behavior: A prospective study
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Yun Joo Koh, Bennett L. Leventhal, Soonjo Hwang, Young Shin Kim, and Somer L. Bishop
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Male ,Adolescent ,media_common.quotation_subject ,education ,Poison control ,050109 social psychology ,Suicide prevention ,Peer Group ,Occupational safety and health ,Developmental psychology ,Arts and Humanities (miscellaneous) ,Risk Factors ,Intervention (counseling) ,Perception ,Dental Anxiety ,Injury prevention ,Developmental and Educational Psychology ,Humans ,0501 psychology and cognitive sciences ,Prospective Studies ,Child ,Child Behavior Checklist ,Crime Victims ,General Psychology ,Defense Mechanisms ,media_common ,Depression ,05 social sciences ,Bullying ,Human factors and ergonomics ,Aggression ,Female ,Self Report ,Psychology ,Follow-Up Studies ,050104 developmental & child psychology ,Clinical psychology - Abstract
Discrepancy in perception of bullying experiences may lead to later internalizing or externalizing behavior in adolescents. A 1,663 South Korean 7th and 8th graders (mean age: 13.1 and 14.1 years old), were seen for a follow-up study to examine the relationships between the discrepancy in perception of their bullying experiences (defined as discrepancy between self- and peer-reports of bullying experiences) and internalizing or externalizing behavior at follow-up. Bullying was assessed by self- and peer-report. The discrepancy in perception of bullying experiences was defined by the concordance or discordance between self- and peer-reports. Internalizing and externalizing behavior was evaluated using the Youth Self Report and Child Behavior Checklist, at baseline and follow-up. Two by two ANCOVA was performed with a factorial design, categorizing discrepancy in perception of bullying experiences based on the agreement between self-report and peer-report. Internalizing/externalizing behavior-at-follow-up was used as an outcome, adjusting for other known risk factors for internalizing/externalizing behavior, including baseline internalizing/externalizing behavior, and bullying experiences. Adolescents with perceptions of bullying experiences discrepant from peer-reports showed increased internalizing/externalizing behavior at follow-up. Bullying also stands out as an independent risk factor for the development of future externalizing behavior even among adolescents with accurate perceptions of bullying experiences. These specific groups of youth warrant more focused assessment and intervention.
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- 2017
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43. Data-Driven Phenotypic Categorization for Neurobiological Analyses: Beyond DSM-5 Labels
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James J. Hudziak, Michael P. Milham, Russell H. Tobe, Nicholas T. Van Dam, R. Cameron Craddock, Vilma Gabbay, Bennett L. Leventhal, David H. O’Connor, Enitan T Marcelle, Erica J. Ho, and Francisco X. Castellanos
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0301 basic medicine ,Multivariate statistics ,Multivariate analysis ,Multivariate distance matrix regression ,Neuropsychological Tests ,Hierarchical clustering ,Developmental psychology ,0302 clinical medicine ,Cluster Analysis ,0303 health sciences ,medicine.diagnostic_test ,Psychopathology ,Mental Disorders ,Psychiatric assessment ,Brain ,Middle Aged ,Anxiety Disorders ,Magnetic Resonance Imaging ,Exploratory factor analysis ,Regression ,Diagnostic and Statistical Manual of Mental Disorders ,Phenotypes ,Phenotype ,Categorization ,Connectome ,Resting state fMRI ,Psychology ,Clinical psychology ,Adult ,Adolescent ,Biology ,Models, Psychological ,Article ,Young Adult ,03 medical and health sciences ,medicine ,RDoC ,Humans ,Cluster analysis ,Biological Psychiatry ,030304 developmental biology ,Extraversion and introversion ,030104 developmental biology ,Cross-Sectional Studies ,Multivariate Analysis ,Functional magnetic resonance imaging ,030217 neurology & neurosurgery - Abstract
BackgroundData-driven approaches can capture behavioral and biological variation currently unaccounted for by contemporary diagnostic categories, thereby enhancing the ability of neurobiological studies to characterize brain-behavior relationships.MethodsA community-ascertained sample of individuals (N=347, ages 18–59) completed a battery of behavioral measures, psychiatric assessment, and resting state functional magnetic resonance imaging (R-fMRI) in a cross-sectional design. Bootstrap-based exploratory factor analysis was applied to 49 phenotypic subscales from 10 measures. Hybrid Hierarchical Clustering was applied to resultant factor scores to identify nested groups. Adjacent groups were compared via independent samples t-tests and chi-square tests of factor scores, syndrome scores, and psychiatric prevalence. Multivariate Distance Matrix Regression examined functional connectome differences between adjacent groups.ResultsReduction yielded six factors, which explained 77.8% and 65.4% of the variance in exploratory and constrained exploratory models, respectively. Hybrid Hierarchical Clustering of these 6 factors identified 2, 4, and 8 nested groups (i.e., phenotypic communities). At the highest clustering level, the algorithm differentiated functionally adaptive and maladaptive groups. At the middle clustering level, groups were separated by problem type (maladaptive groups; internalizing vs. externalizing problems) and behavioral type (adaptive groups; sensation-seeking vs. extraverted/emotionally stable). Unique phenotypic profiles were also evident at the lowest clustering level. Group comparisons exhibited significant differences in intrinsic functional connectivity at the highest clustering level in somatomotor, thalamic, basal ganglia, and limbic networks.ConclusionsData-driven approaches for identifying homogenous subgroups, spanning typical function to dysfunction not only yielded clinically meaningful groups, but captured behavioral and neurobiological variation among healthy individuals as well.
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- 2017
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44. Supporting children of healthcare workers during the COVID-19 pandemic
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Norbert Skokauskas, Judith Cohen, Jannike Kaasbøll, Myron L. Belfer, Bennett L. Leventhal, and Emma Cardeli
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2019-20 coronavirus outbreak ,medicine.medical_specialty ,Coronavirus disease 2019 (COVID-19) ,business.industry ,SARS-CoV-2 ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Health Personnel ,MEDLINE ,COVID-19 ,General Medicine ,Psychiatry and Mental health ,Cross-Sectional Studies ,Family medicine ,Pediatrics, Perinatology and Child Health ,Health care ,Pandemic ,Developmental and Educational Psychology ,Child and adolescent psychiatry ,Medicine ,Humans ,Pediatrics, Perinatology, and Child Health ,business ,Child ,Letter to the Editor ,Pandemics - Published
- 2020
45. ASPI: a public–private partnership to develop treatments for autism
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Declan G. Murphy, Kyle Wathen, Abigail Bangerter, Husseini K. Manji, Gahan Pandina, Geraldine Dawson, Robert L. Hendren, Nikolay V. Manyakov, Bennett L. Leventhal, Shyla Jagannatha, Wayne C. Drevets, and Seth Ness
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0301 basic medicine ,Pharmacology ,medicine.medical_specialty ,General Medicine ,medicine.disease ,behavioral disciplines and activities ,03 medical and health sciences ,Public–private partnership ,030104 developmental biology ,0302 clinical medicine ,Autism spectrum disorder ,030220 oncology & carcinogenesis ,General partnership ,mental disorders ,Drug Discovery ,medicine ,Autism ,Psychiatry ,Psychology - Abstract
Numerous potential therapeutic targets are being investigated in autism spectrum disorder (ASD). Here, we discuss a platform trial approach for designing proof-of-concept (POC) clinical studies of ASD — via the Autism Spectrum POC Initiative (ASPI) — that can be conducted through a public–private partnership with the aim of finding effective treatments in the most expeditious manner. Numerous potential therapeutic targets are being investigated in autism spectrum disorder (ASD). Here, we discuss a platform trial approach for designing proof-of-concept (POC) clinical studies of ASD — via the Autism Spectrum POC Initiative (ASPI) — that can be conducted through a public–private partnership with the aim of finding effective treatments in the most expeditious manner.
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- 2020
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46. Automated recognition of spontaneous facial expression in individuals with autism spectrum disorder: parsing response variability
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Robert L. Hendren, Abigail Bangerter, Matthew S. Goodwin, Frederick Shic, Meenakshi Chatterjee, Joseph Manfredonia, Andrew Skalkin, Seth Ness, Matthew Boice, Bennett L. Leventhal, Nikolay V. Manyakov, Geraldine Dawson, and Gahan Pandina
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Male ,Neurology ,Autism Spectrum Disorder ,Autism ,Emotions ,Audiology ,lcsh:RC346-429 ,0302 clinical medicine ,Theoretical ,Models ,Medicine ,Psychology ,Multicenter Studies as Topic ,Child ,Clinical Trials as Topic ,05 social sciences ,Neuropsychology ,Middle Aged ,Response Variability ,Psychiatry and Mental health ,Mental Health ,Autism spectrum disorder ,Child, Preschool ,Female ,medicine.symptom ,Algorithms ,050104 developmental & child psychology ,Adult ,medicine.medical_specialty ,Facial expression ,Adolescent ,Intellectual and Developmental Disabilities (IDD) ,Clinical Sciences ,Impulsivity ,03 medical and health sciences ,Young Adult ,Developmental Neuroscience ,mental disorders ,Reaction Time ,Humans ,0501 psychology and cognitive sciences ,Preschool ,Molecular Biology ,lcsh:Neurology. Diseases of the nervous system ,business.industry ,Research ,Neurosciences ,Recognition, Psychology ,Models, Theoretical ,medicine.disease ,Expression (mathematics) ,Brain Disorders ,Recognition ,Case-Control Studies ,Multiple comparisons problem ,Impulsive behavior ,business ,Emotional regulation ,030217 neurology & neurosurgery ,Photic Stimulation ,Developmental Biology - Abstract
Background Reduction or differences in facial expression are a core diagnostic feature of autism spectrum disorder (ASD), yet evidence regarding the extent of this discrepancy is limited and inconsistent. Use of automated facial expression detection technology enables accurate and efficient tracking of facial expressions that has potential to identify individual response differences. Methods Children and adults with ASD (N = 124) and typically developing (TD, N = 41) were shown short clips of “funny videos.” Using automated facial analysis software, we investigated differences between ASD and TD groups and within the ASD group in evidence of facial action unit (AU) activation related to the expression of positive facial expression, in particular, a smile. Results Individuals with ASD on average showed less evidence of facial AUs (AU12, AU6) relating to positive facial expression, compared to the TD group (p < .05, r = − 0.17). Using Gaussian mixture model for clustering, we identified two distinct distributions within the ASD group, which were then compared to the TD group. One subgroup (n = 35), termed “over-responsive,” expressed more intense positive facial expressions in response to the videos than the TD group (p < .001, r = 0.31). The second subgroup (n = 89), (“under-responsive”), displayed fewer, less intense positive facial expressions in response to videos than the TD group (p < .001; r = − 0.36). The over-responsive subgroup differed from the under-responsive subgroup in age and caregiver-reported impulsivity (p < .05, r = 0.21). Reduced expression in the under-responsive, but not the over-responsive group, was related to caregiver-reported social withdrawal (p < .01, r = − 0.3). Limitations This exploratory study does not account for multiple comparisons, and future work will have to ascertain the strength and reproducibility of all results. Reduced displays of positive facial expressions do not mean individuals with ASD do not experience positive emotions. Conclusions Individuals with ASD differed from the TD group in their facial expressions of positive emotion in response to “funny videos.” Identification of subgroups based on response may help in parsing heterogeneity in ASD and enable targeting of treatment based on subtypes. Trial registration ClinicalTrials.gov, NCT02299700. Registration date: November 24, 2014
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- 2019
47. Identifying the Medical Lethality of Suicide Attempts Using Network Analysis and Deep Learning: Nationwide Study (Preprint)
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Bora Kim, Younghoon Kim, C Hyung Keun Park, Sang Jin Rhee, Young Shin Kim, Bennett L Leventhal, Yong Min Ahn, and Hyojung Paik
- Abstract
BACKGROUND Suicide is one of the leading causes of death among young and middle-aged people. However, little is understood about the behaviors leading up to actual suicide attempts and whether these behaviors are specific to the nature of suicide attempts. OBJECTIVE The goal of this study was to examine the clusters of behaviors antecedent to suicide attempts to determine if they could be used to assess the potential lethality of the attempt. To accomplish this goal, we developed a deep learning model using the relationships among behaviors antecedent to suicide attempts and the attempts themselves. METHODS This study used data from the Korea National Suicide Survey. We identified 1112 individuals who attempted suicide and completed a psychiatric evaluation in the emergency room. The 15-item Beck Suicide Intent Scale (SIS) was used for assessing antecedent behaviors, and the medical outcomes of the suicide attempts were measured by assessing lethality with the Columbia Suicide Severity Rating Scale (C-SSRS; lethal suicide attempt >3 and nonlethal attempt ≤3). RESULTS Using scores from the SIS, individuals who had lethal and nonlethal attempts comprised two different network nodes with the edges representing the relationships among nodes. Among the antecedent behaviors, the conception of a method’s lethality predicted suicidal behaviors with severe medical outcomes. The vectorized relationship values among the elements of antecedent behaviors in our deep learning model (E-GONet) increased performances, such as F1 and area under the precision-recall gain curve (AUPRG), for identifying lethal attempts (up to 3% for F1 and 32% for AUPRG), as compared with other models (mean F1: 0.81 for E-GONet, 0.78 for linear regression, and 0.80 for random forest; mean AUPRG: 0.73 for E-GONet, 0.41 for linear regression, and 0.69 for random forest). CONCLUSIONS The relationships among behaviors antecedent to suicide attempts can be used to understand the suicidal intent of individuals and help identify the lethality of potential suicide attempts. Such a model may be useful in prioritizing cases for preventive intervention.
- Published
- 2019
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48. Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders
- Author
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Laura M. Thornton, Paul Lichtenstein, Verneri Anttila, Diego Albani, Josep Antoni Ramos-Quiroga, Roger A.H. Adan, Monika Schlögelhofer, Stephen Sanders, Enrique Castelao, Klaus Berger, Nina Dalkner, Urs Heilbronner, Engilbert Sigurdsson, Pablo Mir, Fuquan Zhang, James T.R. Walters, Patrick F. Sullivan, Fragiskos Gonidakis, F. Kyle Satterstrom, Sara Marsal, Per Hoffmann, Amy Perry, Valentina Ciullo, Beate Herpertz-Dahlmann, Catharina Lavebratt, Kieran C. Murphy, Tammy Hedderly, Hyun Ju Hong, Evald Saemundsen, Sascha B. Fischer, Hailiang Huang, Andrew D. Grotzinger, Nienke Vulink, Murray B. Stein, Mark A. Frye, Laura J. Scott, David Curtis, Todd Lencz, Janiece E. DeSocio, Richard A. Belliveau, Eduard Vieta, Andrea Dietrich, Wade H. Berrettini, Kenneth S. Kendler, Marquis P. Vawter, Paul S. Nestadt, Michael E. Talkowski, Manuel Mattheisen, Ingrid Agartz, Elisa Docampo, Bernhard T. Baune, Stefan Ehrlich, Jolanta Lissowska, Felecia Cerrato, Terje Nærland, Robin M. Murray, Jennifer Reichert, Annette M. Hartmann, Hannelore Ehrenreich, Howard J. Edenberg, Katherine A. Halmi, Qingqin S. Li, Peristera Paschou, Marie Bækvad-Hansen, Esther Walton, Alessio Maria Monteleone, Ted Reichborn-Kjennerud, Frank Bellivier, Jungeun Song, D. Blake Woodside, Young Shin Kim, Jochen Seitz, Jacques Pantel, Palmiero Monteleone, Erika L. Nurmi, Rodney J. Scott, Kang Sim, Ekaterina A. Khramtsova, Udo Dannlowski, Rolf Adolfsson, Danielle Posthuma, Melissa J. Green, Laura Ibanez-Gomez, Jakob Grove, Elvira Bramon, Gregory L. Hanna, Cynthia M. Bulik, Yiran Guo, Stephan Ripke, Mary M. Robertson, Harald N. Aschauer, Adebayo Anjorin, Joanna Martin, Bertram Müller-Myhsok, Deborah Kaminská, Jose Guzman-Parra, Benedetta Nacmias, Erik G. Jönsson, Jonathan R. I. Coleman, Douglas F. Levinson, Hamdi Mbarek, Gun Peggy Knudsen, Karin Egberts, Mette Nyegaard, Patrik K. E. Magnusson, Mark Adams, Douglas Blackwood, Elisabeth B. Binder, Marcus Ising, Anna R. 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D., Anjorin, A., Backlund, L., Bass, N., Bauer, M., Baune, B. T., Bellivier, F., Bergen, S. E., Berrettini, W. H., Biernacka, J. M., Blackwood, D. H. R., Boen, E., Budde, M., Bunney, W., Burmeister, M., Byerley, W., Byrne, E. M., Cichon, S., Clarke, T. -K., Coleman, J. R. I., Craddock, N., Curtis, D., Czerski, P. M., Dale, A. M., Dalkner, N., Dannlowski, U., Degenhardt, F., Di Florio, A., Elvsashagen, T., Etain, B., Fischer, S. B., Forstner, A. J., Forty, L., Frank, J., Frye, M., Fullerton, J. M., Gade, K., Gaspar, H. A., Gershon, E. S., Gill, M., Goes, F. S., Gordon, S. D., Gordon-Smith, K., Green, M. J., Greenwood, T. A., Grigoroiu-Serbanescu, M., Guzman-Parra, J., Hauser, J., Hautzinger, M., Heilbronner, U., Herms, S., Hoffmann, P., Holland, D., Jamain, S., Jones, I., Jones, L. A., Kandaswamy, R., Kelsoe, J. R., Kennedy, J. L., Joachim, O. K., Kittel-Schneider, S., Kogevinas, M., Koller, A. C., Lavebratt, C., Lewis, C. M., Li, Q. S., Lissowska, J., Loohuis, L. M. O., Lucae, S., Maaser, A., Malt, U. F., Martin, N. G., Martinsson, L., Mcelroy, S. L., Mcmahon, F. J., Mcquillin, A., Melle, I., Metspalu, A., Millischer, V., Mitchell, P. B., Montgomery, G. W., Morken, G., Morris, D. W., Muller-Myhsok, B., Mullins, N., Myers, R. M., Nievergelt, C. M., Nordentoft, M., Adolfsson, A. N., Nothen, M. M., Ophoff, R. A., Owen, M. J., Paciga, S. A., Pato, C. N., Pato, M. T., Perlis, R. H., Perry, A., Potash, J. B., Reinbold, C. S., Rietschel, M., Rivera, M., Roberson, M., Schalling, M., Schofield, P. R., Schulze, T. G., Scott, L. J., Serretti, A., Sigurdsson, E., Smeland, O. B., Stordal, E., Streit, F., Strohmaier, J., Thorgeirsson, T. E., Treutlein, J., Turecki, G., Vaaler, A. E., Vieta, E., Vincent, J. B., Wang, Y., Witt, S. H., Zandi, P., Adan, R. A. H., Alfredsson, L., Ando, T., Aschauer, H., Baker, J. H., Bencko, V., Bergen, A. W., Birgegard, A., Perica, V. B., Brandt, H., Burghardt, R., Carlberg, L., Cassina, M., Clementi, M., Courtet, P., Crawford, S., Crow, S., Crowley, J. J., Danner, U. N., Davis, O. S. P., Degortes, D., Desocio, J. E., Dick, D. M., Dina, C., Docampo, E., Egberts, K., Ehrlich, S., Espeseth, T., Fernandez-Aranda, F., Fichter, M. M., Foretova, L., Forzan, M., Gambaro, G., Giegling, I., Gonidakis, F., Gorwood, P., Mayora, M. G., Guo, Y., Halmi, K. A., Hatzikotoulas, K., Hebebrand, J., Helder, S. G., Herpertz-Dahlmann, B., Herzog, W., Hinney, A., Imgart, H., Jimenez-Murcia, S., Johnson, C., Jordan, J., Julia, A., Kaminska, D., Karhunen, L., Karwautz, A., Kas, M. J. H., Kaye, W. H., Kennedy, M. A., Kim, Y. -R., Klareskog, L., Klump, K. L., Knudsen, G. P. S., Landen, M., Le Hellard, S., Levitan, R. D., Li, D., Lichtenstein, P., Maj, M., Marsal, S., Mcdevitt, S., Mitchell, J., Monteleone, P., Monteleone, A. M., Munn-Chernoff, M. A., Nacmias, B., Navratilova, M., O'Toole, J. K., Padyukov, L., Pantel, J., Papezova, H., Rabionet, R., Raevuori, A., Ramoz, N., Reichborn-Kjennerud, T., Ricca, V., Roberts, M., Rujescu, D., Rybakowski, F., Scherag, A., Schmidt, U., Seitz, J., Slachtova, L., Slof-Op't Landt, M. C. T., Slopien, A., Sorbi, S., Southam, L., Strober, M., Tortorella, A., Tozzi, F., Treasure, J., Tziouvas, K., van Elburg, A. A., Wade, T. D., Wagner, G., Walton, E., Watson, H. J., Wichmann, H. -E., Woodside, D. B., Zeggini, E., Zerwas, S., Zipfel, S., Adams, M. J., Andlauer, T. F. M., Berger, K., Binder, E. B., Boomsma, D. I., Castelao, E., Colodro-Conde, L., Direk, N., Docherty, A. R., Domenici, E., Domschke, K., Dunn, E. C., Foo, J. C., D, e. Geus E. J. C., Grabe, H. J., Hamilton, S. P., Horn, C., Hottenga, J. -J., Howard, D., Ising, M., Kloiber, S., Levinson, D. F., Lewis, G., Magnusson, P. K. E., Mbarek, H., Middeldorp, C. M., Mostafavi, S., Nyholt, D. R., Penninx, B. W., Peterson, R. E., Pistis, G., Porteous, D. J., Preisig, M., Quiroz, J. A., Schaefer, C., Schulte, E. C., Shi, J., Smith, D. J., Thomson, P. A., Tiemeier, H., Uher, R., van der Auwera, S., Weissman, M. M., Alexander, M., Begemann, M., Bramon, E., Buccola, N. G., Cairns, M. J., Campion, D., Carr, V. J., Cloninger, C. R., Cohen, D., Collier, D. A., Corvin, A., Delisi, L. E., Donohoe, G., Dudbridge, F., Duan, J., Freedman, R., Gejman, P. V., Golimbet, V., Godard, S., Ehrenreich, H., Hartmann, A. M., Henskens, F. A., Ikeda, M., Iwata, N., Jablensky, A. V., Joa, I., Jonsson, E. G., Kelly, B. J., Knight, J., Konte, B., Laurent-Levinson, C., Lee, J., Lencz, T., Lerer, B., Loughland, C. M., Malhotra, A. K., Mallet, J., Mcdonald, C., Mitjans, M., Mowry, B. J., Murphy, K. C., Murray, R. M., O'Neill, F. A., Oh, S. -Y., Palotie, A., Pantelis, C., Pulver, A. E., Petryshen, T. L., Quested, D. J., Riley, B., Sanders, A. R., Schall, U., Schwab, S. G., Scott, R. J., Sham, P. C., Silverman, J. M., Sim, K., Steixner, A. A., Tooney, P. A., van Os, J., Vawter, M. P., Walsh, D., Weiser, M., Wildenauer, D. B., Williams, N. M., Wormley, B. K., Zhang, F., Androutsos, C., Arnold, P. D., Barr, C. L., Barta, C., Bey, K., Bienvenu, O. J., Black, D. W., Brown, L. W., Budman, C., Cath, D., Cheon, K. -A., Ciullo, V., Coffey, B. J., Cusi, D., Davis, L. K., Denys, D., Depienne, C., Dietrich, A., Eapen, V., Falkai, P., Fernandez, T. V., Garcia-Delgar, B., Geller, D. A., Gilbert, D. L., Grados, M. A., Greenberg, E., Grunblatt, E., Hagstrom, J., Hanna, G. L., Hartmann, A., Hedderly, T., Heiman, G. A., Heyman, I., Hong, H. J., Huang, A., Huyser, C., Ibanez-Gomez, L., Khramtsova, E. A., Kim, Y. K., Kim, Y. -S., King, R. A., Koh, Y. -J., Konstantinidis, A., Kook, S., Kuperman, S., Leventhal, B. L., Lochner, C., Ludolph, A. G., Madruga-Garrido, M., Malaty, I., Maras, A., Mccracken, J. T., Meijer, I. A., Mir, P., Morer, A., Muller-Vahl, K. R., Munchau, A., Murphy, T. L., Naarden, A., Nagy, P., Nestadt, G., Nestadt, P. S., Nicolini, H., Nurmi, E. L., Okun, M. S., Paschou, P., Piras, F., Pittenger, C., Plessen, K. J., Richter, M. A., Rizzo, R., Robertson, M., Roessner, V., Ruhrmann, S., Samuels, J. F., Sandor, P., Schlogelhofer, M., Shin, E. -Y., Singer, H., Song, D. -H., Song, J., Spalletta, G., Stein, D. J., Stewart, S. E., Storch, E. A., Stranger, B., Stuhrmann, M., Tarnok, Z., Tischfield, J. A., Tubing, J., Visscher, F., Vulink, N., Wagner, M., Walitza, S., Wanderer, S., Woods, M., Worbe, Y., Zai, G., Zinner, S. H., Sullivan, P. F., Franke, B., Daly, M. J., Bulik, C. M., Mcintosh, A. M., O'Donovan, M. C., Zheutlin, A., Andreassen, O. A., Borglum, A. D., Breen, G., Edenberg, H. J., Fanous, A. H., Faraone, S. V., Gelernter, J., Mathews, C. A., Mattheisen, M., Mitchell, K. S., Neale, M. C., Nurnberger, J. I., Ripke, S., Santangelo, S. L., Scharf, J. M., Stein, M. B., Thornton, L. M., Walters, J. T. R., Wray, N. R., Geschwind, D. H., Neale, B. M., Kendler, K. S., and Smoller, J. W.
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Netherlands Twin Register (NTR) ,cross-disorder genetics ,Medizin ,Genome-wide association study ,Tourette syndrome ,functional genomics ,gene expression ,genetic architecture ,genetic correlation ,GWAS ,neurodevelopment ,pleiotropy ,psychiatric disorders ,Psychiatric genetics ,0302 clinical medicine ,Pleiotropy ,functional genomic ,WIDE ASSOCIATION ,cross-disorder genetic ,0303 health sciences ,Mental Disorders ,Genetic Pleiotropy ,HUMAN BRAIN ,INSIGHTS ,Autism spectrum disorder ,Schizophrenia ,DISEASES ,GENETIC CORRELATIONS ,medicine.medical_specialty ,Neurogenesis ,Quantitative Trait Loci ,BF ,Biology ,GENOTYPE IMPUTATION ,Psychiatric geneticscross-disorder geneticspsychiatric disorderspleiotropyneurodevelopmentGWASgenetic correlationgene expressiongenetic architecturefunctional genomics ,Article ,General Biochemistry, Genetics and Molecular Biology ,psychiatric disorder ,03 medical and health sciences ,SDG 3 - Good Health and Well-being ,medicine ,Humans ,Genetic Predisposition to Disease ,Bipolar disorder ,TRANSCRIPTOME ,Psychiatry ,030304 developmental biology ,Gwas ,Psychiatric Genetics ,Cross-disorder Genetics ,Functional Genomics ,Gene Expression ,Genetic Architecture ,Genetic Correlation ,Neurodevelopment ,Psychiatric Disorders ,Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7] ,IDENTIFICATION ,MUTATIONS ,medicine.disease ,Genetic architecture ,DEMETHYLASE ,RC0321 ,1182 Biochemistry, cell and molecular biology ,030217 neurology & neurosurgery ,Genome-Wide Association Study - Abstract
Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.
- Published
- 2019
- Full Text
- View/download PDF
49. Prevention of bullying-related morbidity and mortality: a call for public health policies
- Author
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Jorge C Srabstein and Bennett L Leventhal
- Subjects
Public aspects of medicine ,RA1-1270 - Published
- 2010
50. Often Asked but Rarely Answered: Can Asians Meet DSM-5/ICD-10 Autism Spectrum Disorder Criteria?
- Author
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Soo Jeong Kim, So Hyun Kim, Yun-Joo Koh, Young Shin Kim, Eun-Chung Lim, and Bennett L. Leventhal
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Male ,medicine.medical_specialty ,Adolescent ,Autism Spectrum Disorder ,Sensitivity and Specificity ,behavioral disciplines and activities ,DSM-5 ,Autism Diagnostic Observation Schedule ,03 medical and health sciences ,0302 clinical medicine ,Asian People ,International Classification of Diseases ,Republic of Korea ,mental disorders ,medicine ,Humans ,0501 psychology and cognitive sciences ,Pharmacology (medical) ,Medical diagnosis ,Child ,Social Behavior ,Psychiatry ,business.industry ,05 social sciences ,ICD-10 ,Original Articles ,Gold standard (test) ,medicine.disease ,Diagnostic and Statistical Manual of Mental Disorders ,Psychiatry and Mental health ,Phenotype ,Autism spectrum disorder ,Pediatrics, Perinatology and Child Health ,Cohort ,Autism ,Female ,Factor Analysis, Statistical ,business ,030217 neurology & neurosurgery ,050104 developmental & child psychology ,Clinical psychology - Abstract
To evaluate whether Asian (Korean children) populations can be validly diagnosed with autism spectrum disorder (ASD) using Western-based diagnostic instruments and criteria based on Diagnostic and Statistical Manual on Mental Disorders, 5th edition (DSM-5).Participants included an epidemiologically ascertained 7-14-year-old (N = 292) South Korean cohort from a larger prevalence study (N = 55,266). Main outcomes were based on Western-based diagnostic methods for Korean children using gold standard instruments, Autism Diagnostic Interview-Revised, and Autism Diagnostic Observation Schedule. Factor analysis and ANOVAs were performed to examine factor structure of autism symptoms and identify phenotypic differences between Korean children with ASD and non-ASD diagnoses.Using Western-based diagnostic methods, Korean children with ASD were successfully identified with moderate-to-high diagnostic validity (sensitivities/specificities ranging 64%-93%), strong internal consistency, and convergent/concurrent validity. The patterns of autism phenotypes in a Korean population were similar to those observed in a Western population with two symptom domains (social communication and restricted and repetitive behavior factors). Statistically significant differences in the use of socially acceptable communicative behaviors (e.g., direct gaze, range of facial expressions) emerged between ASD versus non-ASD cases (mostly p 0.001), ensuring that these can be a similarly valid part of the ASD phenotype in both Asian and Western populations.Despite myths, biases, and stereotypes about Asian social behavior, Asians (at least Korean children) typically use elements of reciprocal social interactions similar to those in the West. Therefore, standardized diagnostic methods widely used for ASD in Western culture can be validly used as part of the assessment process and research with Koreans and, possibly, other Asians.
- Published
- 2016
- Full Text
- View/download PDF
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