File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Abnormalities of gray matter volume and structural covariance in children with attention-deficit/hyperactivity disorder subtypes: implications for clinical correlations

TitleAbnormalities of gray matter volume and structural covariance in children with attention-deficit/hyperactivity disorder subtypes: implications for clinical correlations
Authors
KeywordsADHD subtypes
Clinical symptoms
Gray matter volume
Medication-naive
Neuroimaging
Structural covariance
Structural MRI
Issue Date2025
Citation
European Archives of Psychiatry and Clinical Neuroscience, 2025, v. 275, n. 7, p. 1897-1911 How to Cite?
AbstractAttention deficit and hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by attention deficits, hyperactivity, and impulsivity. This study investigated brain structural differences in children with ADHD compared to typically developing children. Our sample included 199 ADHD children (114 ADHD-predominantly inattentive; 85 ADHD-combined presentation subtypes) and 94 typically developing controls. All participants completed clinical assessments and MRI scans. We conducted whole-brain voxel-based morphometry (VBM) analysis, structural covariance analysis, and clinical correlation. We used Analysis of Covariance (ANCOVA) and Multivariate Analysis of Covariance (MANCOVA) to compare gray matter volume (GMV) and structural covariance between the ADHD subgroups and typically developing children. We also analyzed correlations between structural covariance and clinical symptoms. The results showed significant GMV differences, particularly in the frontal cortex and basal ganglia, among ADHD subtypes and typically developing children. Compared to controls, children with ADHD combined presentation (ADHD-C) exhibited significantly larger GMV in the right precentral gyrus, right inferior frontal gyrus, right superior frontal gyrus, and left cingulate gyrus, while children with ADHD-predominantly inattentive (ADHD-I) exhibited larger GMV in the right cingulate gyrus. Within the ADHD subtypes, ADHD-C children displayed larger GMV in the left caudate nucleus compared to ADHD-I children. Structural covariance analysis highlighted the altered connectivity patterns, involving the striatum and regions within the default mode network. Correlation analysis indicated associations between altered brain structures and symptoms, cognitive abilities, and social functioning. Our findings suggested that specific brain regions are implicated in ADHD pathology and associated with clinical symptoms, paving ways for developing diagnostic markers and future interventions.
Persistent Identifierhttp://hdl.handle.net/10722/367631
ISSN
2023 Impact Factor: 3.5
2023 SCImago Journal Rankings: 1.381

 

DC FieldValueLanguage
dc.contributor.authorChen, Qiao Ru-
dc.contributor.authorWang, Yi-
dc.contributor.authorYang, Bin Rang-
dc.contributor.authorWang, Yu Feng-
dc.contributor.authorChan, Raymond C.K.-
dc.date.accessioned2025-12-19T07:58:12Z-
dc.date.available2025-12-19T07:58:12Z-
dc.date.issued2025-
dc.identifier.citationEuropean Archives of Psychiatry and Clinical Neuroscience, 2025, v. 275, n. 7, p. 1897-1911-
dc.identifier.issn0940-1334-
dc.identifier.urihttp://hdl.handle.net/10722/367631-
dc.description.abstractAttention deficit and hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by attention deficits, hyperactivity, and impulsivity. This study investigated brain structural differences in children with ADHD compared to typically developing children. Our sample included 199 ADHD children (114 ADHD-predominantly inattentive; 85 ADHD-combined presentation subtypes) and 94 typically developing controls. All participants completed clinical assessments and MRI scans. We conducted whole-brain voxel-based morphometry (VBM) analysis, structural covariance analysis, and clinical correlation. We used Analysis of Covariance (ANCOVA) and Multivariate Analysis of Covariance (MANCOVA) to compare gray matter volume (GMV) and structural covariance between the ADHD subgroups and typically developing children. We also analyzed correlations between structural covariance and clinical symptoms. The results showed significant GMV differences, particularly in the frontal cortex and basal ganglia, among ADHD subtypes and typically developing children. Compared to controls, children with ADHD combined presentation (ADHD-C) exhibited significantly larger GMV in the right precentral gyrus, right inferior frontal gyrus, right superior frontal gyrus, and left cingulate gyrus, while children with ADHD-predominantly inattentive (ADHD-I) exhibited larger GMV in the right cingulate gyrus. Within the ADHD subtypes, ADHD-C children displayed larger GMV in the left caudate nucleus compared to ADHD-I children. Structural covariance analysis highlighted the altered connectivity patterns, involving the striatum and regions within the default mode network. Correlation analysis indicated associations between altered brain structures and symptoms, cognitive abilities, and social functioning. Our findings suggested that specific brain regions are implicated in ADHD pathology and associated with clinical symptoms, paving ways for developing diagnostic markers and future interventions.-
dc.languageeng-
dc.relation.ispartofEuropean Archives of Psychiatry and Clinical Neuroscience-
dc.subjectADHD subtypes-
dc.subjectClinical symptoms-
dc.subjectGray matter volume-
dc.subjectMedication-naive-
dc.subjectNeuroimaging-
dc.subjectStructural covariance-
dc.subjectStructural MRI-
dc.titleAbnormalities of gray matter volume and structural covariance in children with attention-deficit/hyperactivity disorder subtypes: implications for clinical correlations-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s00406-025-02029-5-
dc.identifier.pmid40539998-
dc.identifier.scopuseid_2-s2.0-105008466409-
dc.identifier.volume275-
dc.identifier.issue7-
dc.identifier.spage1897-
dc.identifier.epage1911-
dc.identifier.eissn1433-8491-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats