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, Erica D. Musser, Bonnie J. Nagel, Damien A. Fair

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Article number101222
JournalDevelopmental Cognitive Neuroscience
Volume60
DOIs
StatePublished - Apr 2023

Bibliographical note

Funding Information:
Critical philanthropic support was provided by the Abracadbra Foundation (Stephen and Patricia Sharp). Multiple NIMH grants supported the development of these cohorts: 1R01-MH59105 (Nigg); R01-MH63146 (Nigg); R01-MH070004 (Friderici); 1R01MH86654 (Nigg-Fair); R01MH099064 (Nigg); 1R37MH59105 (Nigg); 2R56MH086654 (Nigg); R01MH115357 (Fair-Nigg); 2R37MH59105 (Nigg); R01 MH096773 (Fair); K23 MH108656 (Karalunas). An integrated SQL data base at OHSU has housed all the data and is supported by the Oregon Clinical and Translational Research Institute funded by a grant from the National Center for Advancing Translational Sciences ( NCATS ), National Institutes of Health , through Grant Award Number UL1TR002369 . The material in this paper does not necessarily reflect the opinion of the National Institutes of Health or the National Institute of Mental Health.

Funding Information:
Critical philanthropic support was provided by the Abracadbra Foundation (Stephen and Patricia Sharp). Multiple NIMH grants supported the development of these cohorts: 1R01-MH59105 (Nigg); R01-MH63146 (Nigg); R01-MH070004 (Friderici); 1R01MH86654 (Nigg-Fair); R01MH099064 (Nigg); 1R37MH59105 (Nigg); 2R56MH086654 (Nigg); R01MH115357 (Fair-Nigg); 2R37MH59105 (Nigg); R01 MH096773 (Fair); K23 MH108656 (Karalunas). An integrated SQL data base at OHSU has housed all the data and is supported by the Oregon Clinical and Translational Research Institute funded by a grant from the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through Grant Award Number UL1TR002369. The material in this paper does not necessarily reflect the opinion of the National Institutes of Health or the National Institute of Mental Health.

Publisher Copyright:
© 2023 The Authors

Keywords

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

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

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