Brain-Behavior Networks Unravelling Robust Brain-Behavior Links of Depressive Symptoms Through Granular Network Models: Understanding Heterogeneity and Clinical Implications

Importance Major depressive disorder (MDD) is highly heterogeneous and prevalent globally, with diverse neurobiological underpinnings. Understanding the interplay between psychopathological symptoms and biological factors is critical for elucidating its etiology and persistence. Objective We aimed to evaluate the utility of using symptom-brain networks to parse the heterogeneity of depressive symptomatology in a large adolescent sample. Design, Setting, Participants We used data from the third wave of the IMAGEN study, a multi-center panel cohort study involving 1,317 adolescents (52.49% female, mean±SD age=18.5±0.72). Main outcomes and measures Two network models were estimated: one including an overall depression severity sum score based on the Adolescent Depression Rating Scale (ADRS), and one incorporating individual ADRS symptom/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 symptom scores revealed associations between cortical thickness measures and specific symptoms, 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). Conclusions and Relevance This study showcases the utility of network models at parsing heterogeneity in depression, linking individual symptoms with specific neural substrates. We discuss the clinical relevance and implications of this approach and outline the next steps to integrate neurobiological and cognitive markers to further unravel MDD’s phenotypic heterogeneity. Question What is the utility of estimating brain-symptom network models of depression? Finding We found no brain-symptom associations when estimating a network with an overall depression severity score. A network estimated on the level of individual depression symptoms showed specific symptom – neural substrate connections (e.g., thinning of insula – cognitive dysfunction). Lower cortical thickness in several regions (insula, mOFC, cingulate) was associated with more specific depression symptoms. Meaning Network models integrating individual symptoms and specific neural markers may provide a promising avenue for understanding the phenotypic heterogeneity of depression. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study received funding through the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology)and IMAGEN associated funding sources. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The IMAGEN project obtained written informed consent from all participants and their legal guardians. The IMAGEN study was approved by local ethics research committees at each research site: King's College London, University of Nottingham, Trinity College Dublin, University of Heidelberg, Technische Universitaet Dresden, Commissariata l'Energie Atomique et aux Energies Alternatives and University Medical Center. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data for this study are available from the IMAGEN study. Restrictions apply to the availability of these data, which were used under license for this study.