High-order network degree revealed shared and distinct features among adult schizophrenia, bipolar disorder and ADHD
Dingjie Wu1, Zhao Chang2, Yaozu Wang1
1School of Aerospace Engineering, Xi'an Jiaotong University, Xi'an, China; State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi'an, China.
Abstract:
Schizophrenia (SCHZ), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD) share clinical symptoms and risk genes, but the shared and distinct neural dynamic mechanisms at adults remain inadequately understood. Degree is a fundamental and important graph measure in network neuroscience, and we here used eigenmodes to extend the degree to hierarchical levels and compared the resting-state brain networks of three disorders and healthy controls (HC) at adults (age: 21-50 years old). First, compared to HC, SCHZ and BD patients exhibited substantially overlapped abnormalities in brain networks, wherein BD patients displayed more significant alterations. In contrast, ADHD patients exhibited few alterations. Second, compared to the graph theory measure, hierarchical degree better predicted the clinical symptoms of three disorders, and distinguished them from HC. Furthermore, three disorders shared associations of brain network abnormalities with dopamine receptors/transporters. Finally, the alterations in SCHZ and BD patients were associated with cellular localization and transport, as well as abnormal social behavior and communication, while ADHD patients were associated with energy production and transport. These findings provided a deep understanding of the shared and distinct neuropathology of three disorders and facilitated a more precise differentiation for them.
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