The Oregon ADHD-1000: A new longitudinal data resource enriched for clinical cases and multiple levels of analysis.

Autor:	Nigg JT; Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA. Electronic address: niggj@ohsu.edu., Karalunas SL; Department of Psychological Sciences, Purdue University, USA., Mooney MA; Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, USA., Wilmot B; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, USA., Nikolas MA; Department of Psychological and Brain Sciences, University of Iowa, USA., Martel MM; Department of Psychology, University of Kentucky, USA., Tipsord J; Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA., Nousen EK; Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA., Schmitt C; Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA., Ryabinin P; Knight Cancer Institute, Oregon Health & Science University, USA., Musser ED; Department of Psychology, Florida International University, USA., Nagel BJ; Department of Psychiatry & Behavioral Neuroscience, Oregon Health & Science University, USA., Fair DA; Department of Pediatrics, Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, University of Minnesota, USA. Electronic address: faird@umn.edu.
Jazyk:	angličtina
Zdroj:	Developmental cognitive neuroscience [Dev Cogn Neurosci] 2023 Apr; Vol. 60, pp. 101222. Date of Electronic Publication: 2023 Feb 24.
DOI:	10.1016/j.dcn.2023.101222
Abstrakt:	The fields of developmental psychopathology, developmental neuroscience, and behavioral genetics are increasingly moving toward a data sharing model to improve reproducibility, robustness, and generalizability of findings. This approach is particularly critical for understanding attention-deficit/hyperactivity disorder (ADHD), which has unique public health importance given its early onset, high prevalence, individual variability, and causal association with co-occurring and later developing problems. A further priority concerns multi-disciplinary/multi-method datasets that can span different units of analysis. Here, we describe a public dataset using a case-control design for ADHD that includes: multi-method, multi-measure, multi-informant, multi-trait data, and multi-clinician evaluation and phenotyping. It spans > 12 years of annual follow-up with a lag longitudinal design allowing age-based analyses spanning age 7-19 + years with a full age range from 7 to 21. Measures span genetic and epigenetic (DNA methylation) array data; EEG, functional and structural MRI neuroimaging; and psychophysiological, psychosocial, clinical and functional outcomes data. The resource also benefits from an autism spectrum disorder add-on cohort and a cross sectional case-control ADHD cohort from a different geographical region for replication and generalizability. Datasets allowing for integration from genes to nervous system to behavior represent the "next generation" of researchable cohorts for ADHD and developmental psychopathology. Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests. Damien A. Fair reports a relationship with NOUS Imaging Inc that includes: board membership and equity or stocks. (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Databáze:	MEDLINE
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