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01-04-2023 | Mood Disorders | Research

Co-alteration Network Architecture of Major Depressive Disorder: A Multi-modal Neuroimaging Assessment of Large-scale Disease Effects

Authors: Jodie P. Gray, Jordi Manuello, Aaron F. Alexander-Bloch, Cassandra Leonardo, Crystal Franklin, Ki Sueng Choi, Franco Cauda, Tommaso Costa, John Blangero, David C. Glahn, Helen S. Mayberg, Peter T. Fox

Published in: Neuroinformatics | Issue 2/2023

Abstract

Major depressive disorder (MDD) exhibits diverse symptomology and neuroimaging studies report widespread disruption of key brain areas. Numerous theories underpinning the network degeneration hypothesis (NDH) posit that neuropsychiatric diseases selectively target brain areas via meaningful network mechanisms rather than as indistinct disease effects. The present study tests the hypothesis that MDD is a network-based disorder, both structurally and functionally. Coordinate-based meta-analysis and Activation Likelihood Estimation (CBMA-ALE) were used to assess the convergence of findings from 92 previously published studies in depression. An extension of CBMA-ALE was then used to generate a node-and-edge network model representing the co-alteration of brain areas impacted by MDD. Standardized measures of graph theoretical network architecture were assessed. Co-alteration patterns among the meta-analytic MDD nodes were then tested in independent, clinical T1-weighted structural magnetic resonance imaging (MRI) and resting-state functional (rs-fMRI) data. Differences in co-alteration profiles between MDD patients and healthy controls, as well as between controls and clinical subgroups of MDD patients, were assessed. A 65-node 144-edge co-alteration network model was derived for MDD. Testing of co-alteration profiles in replication data using the MDD nodes provided distinction between MDD and healthy controls in structural data. However, co-alteration profiles were not distinguished between patients and controls in rs-fMRI data. Improved distinction between patients and healthy controls was observed in clinically homogenous MDD subgroups in T1 data. MDD abnormalities demonstrated both structural and functional network architecture, though only structural networks exhibited between-groups differences. Our findings suggest improved utility of structural co-alteration networks for ongoing biomarker development.

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Title: Co-alteration Network Architecture of Major Depressive Disorder: A Multi-modal Neuroimaging Assessment of Large-scale Disease Effects
Authors: Jodie P. Gray
Jordi Manuello
Aaron F. Alexander-Bloch
Cassandra Leonardo
Crystal Franklin
Ki Sueng Choi
Franco Cauda
Tommaso Costa
John Blangero
David C. Glahn
Helen S. Mayberg
Peter T. Fox
Publication date: 01-04-2023
Publisher: Springer US
Keywords: Mood Disorders
Affective Disorder
Published in: Neuroinformatics / Issue 2/2023
Print ISSN: 1539-2791
Electronic ISSN: 1559-0089
DOI: https://doi.org/10.1007/s12021-022-09614-2

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Co-alteration Network Architecture of Major Depressive Disorder: A Multi-modal Neuroimaging Assessment of Large-scale Disease Effects

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