Aberrant morphological brain networks in first-episode, treatment-naive adolescents with major depressive disorder

Author:

Qiu Xiaofan1,Li Junle1,Pan Fen2,Yang Yuping1,Zhou Weihua2,Chen Jinkai2,Wei Ning2,Lu Shaojia2,Weng Xuchu1,Huang Manli2,Wang Jinhui1

Affiliation:

1. South China Normal University

2. First Affiliated Hospital Zhejiang University

Abstract

Abstract Previous studies have shown that major depressive disorder (MDD) is associated with disrupted topological organizations of large-scale brain networks. However, the disruptions and their clinical and cognitive relevance are not well established for morphological brain networks in adolescent MDD. In this study, twenty-five first-episode, treatment-naive adolescents with MDD and nineteen healthy controls underwent T1-weighted MRI and a battery of neuropsychological tests. Individual morphological brain networks were constructed separately based on 4 morphological features, whose topological organizations were quantified by graph-based approaches. Permutation testing and partial correlation were used to examine between-group differences and clinical and cognitive relevance of the differences, respectively. Finally, support vector machine was used to classify the patients from controls. Compared with the controls, the patients exhibited topological alterations mainly in cortical thickness-based networks characterized by higher nodal centralities in parietal (left PriMary Sensory Cortex) but lower centralities in temporal (left ParaBelt Complex, right Perirhinal Ectorhinal Cortex, right Area PHT and right Ventral Visual Complex) regions. Moreover, decreased nodal centralities of some temporal regions were correlated with cognitive dysfunction and course of illness of the patients. These results were largely reproducible for binary and weighted network analyses. Finally, topological properties of the cortical thickness-based networks were able to distinguish the patients from controls with 87.6% accuracy. In short, adolescent MDD is associated with abnormal local organizations of morphological brain networks, which provide potential biomarkers for diagnosing and monitoring the disease.

Publisher

Research Square Platform LLC

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