Abnormal intra- and inter-network functional connectivity of brain networks in early-onset Parkinson's disease and late-onset Parkinson's disease

Front Aging Neurosci. 2023 Mar 24:15:1132723. doi: 10.3389/fnagi.2023.1132723. eCollection 2023.

Abstract

Objective: The purpose of this study is to look into the altered functional connectivity of brain networks in Early-Onset Parkinson's Disease (EOPD) and Late-Onset Parkinson's Disease (LOPD), as well as their relationship to clinical symptoms.

Methods: A total of 50 patients with Parkinson' disease (28 EOPD and 22 LOPD) and 49 healthy controls (25 Young Controls and 24 Old Controls) were admitted to our study. Employing independent component analysis, we constructed the brain networks of EOPD and Young Controls, LOPD and Old Controls, respectively, and obtained the functional connectivity alterations in brain networks.

Results: Cerebellar network (CN), Sensorimotor Network (SMN), Executive Control Network (ECN), and Default Mode Network (DMN) were selected as networks of interest. Compared with their corresponding health controls, EOPD showed increased functional connectivity within the SMN and ECN and no abnormalities of inter-network functional connectivity were found, LOPD demonstrated increased functional connectivity within the ECN while decreased functional connectivity within the CN. Furthermore, in LOPD, functional connectivity between the SMN and DMN was increased. The functional connectivity of the post-central gyrus within the SMN in EOPD was inversely correlated with the Unified Parkinson's Disease Rating Scale Part III scores. Age, age of onset, and MMSE scores are significantly different between EOPD and LOPD (p < 0.05).

Conclusion: There is abnormal functional connectivity of networks in EOPD and LOPD, which could be the manifestation of the associated pathological damage or compensation.

Keywords: MMSE; UPDRS-III; brain network; early-onset Parkinson’s disease; independent component analysis; late-onset Parkinson’s disease.

Grants and funding

This study was supported by the grants from Chinese National Science and Technology Pillar Program (No. 2022YFC2009900/2022YFC2009904), the Natural Science Foundation of Hunan Province (Nos. 2022JJ30818 and 2021JJ40860), the Science and Technology Innovation Program of Hunan Province (2021SK53502), and the Natural Science Foundation of Changsha City (No. kq2202416).