Reduced fronto-striatal volume in attention-deficit/hyperactivity disorder in two cohorts across the lifespan

Renata Basso Cupertino, Sourena Soheili-Nezhad, Eugenio Horacio Grevet, Cibele Edom Bandeira, Felipe Almeida Picon, Maria Eduarda de Araujo Tavares, Jilly Naaijen, Daan van Rooij, Sophie Akkermans, Eduardo Schneider Vitola, Marcel P. Zwiers, Diego Luiz Rovaris, Pieter J. Hoekstra, Vitor Breda, Jaap Oosterlaan, Catharina A. Hartman, Christian F. Beckmann, Jan K. Buitelaar, Barbara Franke, Claiton Henrique Dotto BauEmma Sprooten

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)

Abstract

Attention-Deficit/Hyperactivity Disorder (ADHD) has been associated with altered brain anatomy in neuroimaging studies. However, small and heterogeneous study samples, and the use of region-of-interest and tissue-specific analyses have limited the consistency and replicability of these effects. We used a data-driven multivariate approach to investigate neuroanatomical features associated with ADHD in two independent cohorts: the Dutch NeuroIMAGE cohort (n = 890, 17.2 years) and the Brazilian IMpACT cohort (n = 180, 44.2 years). Using independent component analysis of whole-brain morphometry images, 375 neuroanatomical components were assessed for association with ADHD. In both discovery (corrected-p = 0.0085) and replication (p = 0.032) cohorts, ADHD was associated with reduced volume in frontal lobes, striatum, and their interconnecting white-matter. Current results provide further evidence for the role of the fronto-striatal circuit in ADHD in children, and for the first time show its relevance to ADHD in adults. The fact that the cohorts are from different continents and comprise different age ranges highlights the robustness of the findings.

Original languageEnglish
Article number102403
Pages (from-to)1-9
Number of pages9
JournalNeuroImage: Clinical
Volume28
Early online date28 Aug 2020
DOIs
Publication statusPublished - 2020

Keywords

  • ADHD
  • Fronto-striatal
  • Independent component analysis
  • Tensor-based morphometry
  • White matter

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