Cargando…

Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study

Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instant...

Descripción completa

Detalles Bibliográficos
Autores principales: Owens, Max M., Allgaier, Nicholas, Hahn, Sage, Yuan, DeKang, Albaugh, Matthew, Adise, Shana, Chaarani, Bader, Ortigara, Joseph, Juliano, Anthony, Potter, Alexandra, Garavan, Hugh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7813832/
https://www.ncbi.nlm.nih.gov/pubmed/33462190
http://dx.doi.org/10.1038/s41398-020-01192-8
_version_ 1783637938119114752
author Owens, Max M.
Allgaier, Nicholas
Hahn, Sage
Yuan, DeKang
Albaugh, Matthew
Adise, Shana
Chaarani, Bader
Ortigara, Joseph
Juliano, Anthony
Potter, Alexandra
Garavan, Hugh
author_facet Owens, Max M.
Allgaier, Nicholas
Hahn, Sage
Yuan, DeKang
Albaugh, Matthew
Adise, Shana
Chaarani, Bader
Ortigara, Joseph
Juliano, Anthony
Potter, Alexandra
Garavan, Hugh
author_sort Owens, Max M.
collection PubMed
description Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R(2) = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R(2) = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.
format Online
Article
Text
id pubmed-7813832
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-78138322021-01-25 Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study Owens, Max M. Allgaier, Nicholas Hahn, Sage Yuan, DeKang Albaugh, Matthew Adise, Shana Chaarani, Bader Ortigara, Joseph Juliano, Anthony Potter, Alexandra Garavan, Hugh Transl Psychiatry Article Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R(2) = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R(2) = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task. Nature Publishing Group UK 2021-01-18 /pmc/articles/PMC7813832/ /pubmed/33462190 http://dx.doi.org/10.1038/s41398-020-01192-8 Text en © The Author(s) 2021, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Owens, Max M.
Allgaier, Nicholas
Hahn, Sage
Yuan, DeKang
Albaugh, Matthew
Adise, Shana
Chaarani, Bader
Ortigara, Joseph
Juliano, Anthony
Potter, Alexandra
Garavan, Hugh
Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study
title Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study
title_full Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study
title_fullStr Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study
title_full_unstemmed Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study
title_short Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study
title_sort multimethod investigation of the neurobiological basis of adhd symptomatology in children aged 9-10: baseline data from the abcd study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7813832/
https://www.ncbi.nlm.nih.gov/pubmed/33462190
http://dx.doi.org/10.1038/s41398-020-01192-8
work_keys_str_mv AT owensmaxm multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT allgaiernicholas multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT hahnsage multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT yuandekang multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT albaughmatthew multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT adiseshana multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT chaaranibader multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT ortigarajoseph multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT julianoanthony multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT potteralexandra multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy
AT garavanhugh multimethodinvestigationoftheneurobiologicalbasisofadhdsymptomatologyinchildrenaged910baselinedatafromtheabcdstudy