ArticleJournal of affective disorders2024
Unraveling robust brain-behavior links of depressive complaints through granular network models for understanding heterogeneity.
Article in Journal of affective disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Linking Affective Symptoms and Brain Morphology in Cocaine Use Disorder: An Integrated Network Approach.European addiction research · 2026Article
- Symptom-specific links between internalizing problems and functional connectivity in adolescents: a network analysis.European child & adolescent psychiatry · 2026Article
- Longitudinal associations between depressive symptoms and brain structure across late childhood and adolescence: A panel network analysis study.medRxiv : the preprint server for health sciences · 2026Article
- Symptom Network Analysis Tools for Applied Researchers With Cross-Sectional and Panel Data - A Brief Overview and Multiverse Analysis.Psychological reports · 2025Review
- A Network Approach to Understanding the Role of Executive Functioning and Alpha Oscillations in Inattention and Hyperactivity-Impulsivity Symptoms of ADHD.Journal of attention disorders · 2024Article
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Abstract
backgroundDepressive 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.
methodsWe 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.
resultsThe 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).
conclusionsThis 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.
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