Altered Intra- and Inter-Network Connectivity in Drug-Naïve Patients With Early Parkinson's Disease.

Abstract

The aim of our study was to investigate differences in whole brain connectivity at different levels between drug-naïve individuals with early Parkinson's disease (PD) and healthy controls (HCs). Resting-state functional magnetic resonance imaging data were collected from 47 patients with early-stage, drug-naïve PD and 50 HCs. Functional brain connectivity was analyzed at the integrity, network, and edge levels; UPDRS-III, MMSE, MOCA, HAMA, and HAMD scores, reflecting the symptoms of PD, were collected for further regression analysis. Compared with age-matched HCs, reduced functional connectivity were mainly observed in the visual (VSN), somatomotor (SMN), limbic (LBN), and deep gray matter networks (DGN) at integrity level [p < 0.05, false discovery rate (FDR) corrected]. Intra-network analysis indicated decreased functional connectivity in DGN, SMN, LBN, and ventral attention networks (VAN). Inter-network analysis indicated reduced functional connectivity in nine pairs of resting-state networks. At the edge level, the LBN was the center of abnormal functional connectivity (p < 0.05, FDR corrected). MOCA score was associated with the intra-network functional connectivity strength (FC) of the DGN, and inter-network FC of the DGN-VAN. HAMA and HAMD scores were associated with the FC of the SMN and DGN, and either the LBN or VAN, respectively. We demonstrated variations in whole brain connections of drug-naïve patients with early PD. Major changes involved the SMN, DGN, LBN, and VSN, which may be relevant to symptoms of early PD. Additionally, our results support PD as a disconnection syndrome.

• Authors: Weiqi Zeng, Wenliang Fan, Xiangchuang Kong, Xiaoming Liu, Ling Liu, Ziqin Cao, Xiaoqian Zhang, Xiaoman Yang, Chi Cheng, Yi Wu, Yu Xu, Xuebing Cao, Yan Xu
• Journal: Frontiers in aging neuroscience (Front Aging Neurosci) Vol. 14 Pg. 783634 ( 2022) ISSN: 1663-4365 [Print] Switzerland
• PMID: 35237144 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Zeng, Fan, Kong, Liu, Liu, Cao, Zhang, Yang, Cheng, Wu, Xu, Cao and Xu.