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Brain network structural connectome abnormalities among youth with attention-deficit/hyperactivity disorder at
1From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong).
Background:
Attention-deficit/hyperactivity disorder (ADHD) is highly prevalent among youth with or at familial risk for bipolar-I disorder (BD-I), and ADHD symptoms commonly precede and may increase the risk for BD-I; however, associated neuropathophysiological mechanisms are not known. In this cross-sectional study, we sought to investigate brain structural network topology among youth with ADHD, with and without familial risk of BD-I.
Methods:
We recruited 3 groups of psychostimulant-free youth (aged 10-18 yr), namely youth with ADHD and at least 1 biological parent or sibling with BD-I (high-risk group), youth with ADHD who did not have a first- or second-degree relative with a mood or psychotic disorder (low-risk group) and healthy controls. We used graph-based network analysis of structural magnetic resonance imaging data to investigate topological properties of brain networks. We also evaluated relationships between topological metrics and mood and ADHD symptom ratings.
Results:
A total of 149 youth were included in the analysis (49 healthy controls, 50 low-risk youth, 50 high-risk youth). Low-risk and high-risk ADHD groups exhibited similar differences from healthy controls, mainly in the default mode network and central executive network. We found topological alterations in the salience network of the high-risk group, relative to both low-risk and control groups. We found significant abnormalities in global network properties in the high-risk group only, compared with healthy controls. Among both low-risk and high-risk ADHD groups, nodal metrics in the right triangular inferior frontal gyrus correlated positively with ADHD total and hyperactivity/impulsivity subscale scores.
Limitations:
The cross-sectional design of this study could not determine the relevance of these findings to BD-I risk progression.
Conclusion:
Youth with ADHD, with and without familial risk for BD-I, exhibit common regional abnormalities in the brain connectome compared with healthy youth, whereas alterations in the salience network distinguish these groups and may represent a prodromal feature relevant to BD-I risk.
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