Identification of neurobehavioural symptom groups based on shared brain mechanisms

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • King's College London (KCL)
  • Max Planck Institute of Psychiatry
  • Université de Rennes 1
  • Radboud University Nijmegen
  • Universität Heidelberg
  • Trinity College Dublin
  • Universität Hamburg
  • Stanford University
  • University of Montreal
  • Universität Mannheim
  • Commissariat à l’énergie atomique et aux énergies alternatives (CEA)
  • University of Vermont
  • University of Nottingham
  • Charité – Universitätsmedizin Berlin
  • Physikalisch-Technische Bundesanstalt
  • Université Paris-Saclay
  • Assistance publique – Hôpitaux de Paris
  • Tampere University Hospital
  • Georg-August-Universität Göttingen
  • National Institutes of Health (NIH)
  • University of Oslo
  • Diakonhjemmet Hospital
  • Karolinska Institutet
  • INSERM - Institut national de la santé et de la recherche médicale
  • University College London
  • University of Cambridge
  • Leibniz-Institut für Neurobiologie
  • Fudan University
  • Berliner Institut für Gesundheitsforschung in der Charité

Abstract

Most psychopathological disorders develop in adolescence. The biological basis for this development is poorly understood. To enhance diagnostic characterization and develop improved targeted interventions, it is critical to identify behavioural symptom groups that share neural substrates. We ran analyses to find relationships between behavioural symptoms and neuroimaging measures of brain structure and function in adolescence. We found two symptom groups, consisting of anxiety/depression and executive dysfunction symptoms, respectively, that correlated with distinct sets of brain regions and inter-regional connections, measured by structural and functional neuroimaging modalities. We found that the neural correlates of these symptom groups were present before behavioural symptoms had developed. These neural correlates showed case–control differences in corresponding psychiatric disorders, depression and attention deficit hyperactivity disorder in independent clinical samples. By characterizing behavioural symptom groups based on shared neural mechanisms, our results provide a framework for developing a classification system for psychiatric illness that is based on quantitative neurobehavioural measures.

Details

OriginalspracheEnglisch
Seiten (von - bis)1306-1318
Seitenumfang13
FachzeitschriftNature human behaviour
Jahrgang3
Ausgabenummer12
PublikationsstatusVeröffentlicht - 1 Dez. 2019
Peer-Review-StatusJa

Externe IDs

PubMed 31591521
ORCID /0000-0001-5398-5569/work/161890732