Unraveling robust brain-behavior links of depressive complaints through granular network models for understanding heterogeneity

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • René Freichel - , University of Amsterdam (Author)
  • Agatha Lenartowicz - , University of California at Los Angeles (Author)
  • Linda Douw - , Amsterdam University Medical Centers (UMC) (Author)
  • Johann D. Kruschwitz - , Charité – Universitätsmedizin Berlin (Author)
  • Tobias Banaschewski - , Heidelberg University  (Author)
  • Gareth J. Barker - , King's College London (KCL) (Author)
  • Arun L.W. Bokde - , Trinity College Dublin (Author)
  • Sylvane Desrivières - , King's College London (KCL) (Author)
  • Herta Flor - , Heidelberg University , University of Mannheim (Author)
  • Antoine Grigis - , Université Paris-Saclay (Author)
  • Hugh Garavan - , University of Vermont (Author)
  • Andreas Heinz - , Charité – Universitätsmedizin Berlin (Author)
  • Rüdiger Brühl - , Physikalisch-Technische Bundesanstalt (Author)
  • Jean Luc Martinot - , École normale supérieure Paris-Saclay (Author)
  • Marie Laure Paillère Martinot - , École normale supérieure Paris-Saclay, Sorbonne Université (Author)
  • Eric Artiges - , École normale supérieure Paris-Saclay, EPS Barthélémy Durand (Author)
  • Frauke Nees - , Heidelberg University , Kiel University (Author)
  • Dimitri Papadopoulos Orfanos - , Université Paris-Saclay (Author)
  • Tomáš Paus - , University of Toronto, University of Montreal (Author)
  • Luise Poustka - , Heidelberg University  (Author)
  • Nathalie Holz - , Heidelberg University  (Author)
  • Christian Baeuchl - , Department of Psychiatry and Psychotherapy (Author)
  • Michael N. Smolka - , Department of Psychiatry and Psychotherapy (Author)
  • Nilakshi Vaidya - , Charité – Universitätsmedizin Berlin (Author)
  • Robert Whelan - , Trinity College Dublin (Author)
  • Vincent Frouin - , Université Paris-Saclay (Author)
  • Gunter Schumann - , Charité – Universitätsmedizin Berlin, Fudan University (Author)
  • Henrik Walter - , Charité – Universitätsmedizin Berlin (Author)
  • Tessa F. Blanken - , University of Amsterdam (Author)

Abstract

Background: Depressive symptoms are highly prevalent, present in heterogeneous symptom patterns, and share diverse neurobiological underpinnings. Understanding the links between psychopathological symptoms and biological factors is critical in elucidating its etiology and persistence. We aimed to evaluate the utility of using symptom-brain network models to parse the heterogeneity of depressive complaints in a large adolescent sample. Methods: We used data from the third wave of the IMAGEN study, a multi-center panel cohort study involving 1317 adolescents (52.49 % female, mean ± SD age = 18.5 ± 0.7). Two network models were estimated: one including an overall depressive symptom severity sum score based on the Adolescent Depression Rating Scale (ADRS), and one incorporating individual ADRS item scores. Both networks included measures of cortical thickness in several regions (insula, cingulate, mOFC, fusiform gyrus) and hippocampal volume derived from neuroimaging. Results: The network based on individual item scores revealed associations between cortical thickness measures and specific depressive complaints, obscured when using an aggregate depression severity score. Notably, the insula's cortical thickness showed negative associations with cognitive dysfunction (partial cor. = −0.15); the cingulate's cortical thickness showed negative associations with feelings of worthlessness (partial cor. = −0.10), and mOFC was negatively associated with anhedonia (partial cor. = −0.05). Limitations: This cross-sectional study relied on the self-reported assessment of depression complaints and used a non-clinical sample with predominantly healthy participants (19 % with depression or sub-threshold depression). Conclusions: This study showcases the utility of network models in parsing heterogeneity in depressive complaints, linking individual complaints to specific neural substrates. We outline the next steps to integrate neurobiological and cognitive markers to unravel MDD's phenotypic heterogeneity.

Details

Original languageEnglish
Pages (from-to)140-144
Number of pages5
JournalJournal of Affective Disorders
Volume359
Publication statusPublished - 15 Aug 2024
Peer-reviewedYes

External IDs

PubMed 38754596
ORCID /0000-0001-5398-5569/work/161890736
ORCID /0000-0001-5615-3645/work/175742221

Keywords

Keywords

  • Depression symptoms, Heterogeneity, Network analysis, Neural markers, Humans, Male, Depression/physiopathology, Young Adult, Magnetic Resonance Imaging, Brain/diagnostic imaging, Psychiatric Status Rating Scales, Cerebral Cortex/diagnostic imaging, Gyrus Cinguli/diagnostic imaging, Hippocampus/diagnostic imaging, Adolescent, Female, Cohort Studies