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The Oregon ADHD-1000: A new longitudinal data resource enriched for clinical cases and multiple levels of analysis
Journal article   Open access   Peer reviewed

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

Joel T. Nigg, Sarah L. Karalunas, Michael A. Mooney, Beth Wilmot, Molly A. Nikolas, Michelle M. Martel, Jessica Tipsord, Elizabeth K. Nousen, Colleen Schmitt, Peter Ryabinin, …
Developmental cognitive neuroscience, Vol.60, 101222
02/24/2023
DOI: 10.1016/j.dcn.2023.101222
PMCID: PMC9984785
PMID: 36848718
url
https://doi.org/10.1016/j.dcn.2023.101222View
Published (Version of record) Open Access

Abstract

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.
 Neuroimaging Attention-deficit/hyperactivity disorder Case-control longitudinal Design Genetic and epigenetic array Public dataset Pyschophysiological

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