帕金森病认知障碍患者静息态功能连接的改变及其鉴别价值
Altered Resting-State Functional Connectivity in Parkinson’s Disease with Cognitive Impairment and Its Discriminative Value
DOI: 10.12677/acm.2026.1641283, PDF,   
作者: 楚晨曦, 刘时华, 朱啸薇, 陈 岩, 张 超, 钟 平:安徽医科大学附属宿州医院神经内科,安徽 宿州;曹 立*:安徽医科大学附属宿州医院神经内科,安徽 宿州;上海交通大学医学院附属第六人民医院神经内科,上海
关键词: 帕金森病认知障碍静息态功能磁共振成像功能连接神经影像学生物标志物Parkinson’s Disease Cognitive Impairment Resting-State fMRI Functional Connectivity Neuroimaging Biomarkers
摘要: 目的:帕金森病认知障碍(Parkinson’s Disease with Cognitive Impairment, PD-CI)严重影响患者生活质量,且缺乏客观诊断指标。本研究旨在探讨PD-CI患者静息态功能磁共振成像(Resting-state functional Magnetic Resonance Imaging, rs-fMRI)中功能连接(Functional Connectivity, FC)的异常模式,并评估其鉴别价值。方法:纳入23例PD-CI患者、20例PD认知正常(Parkinson’s Disease with Normal Cognition, PD-NC)患者及20名健康对照(Healthy Control, HC)。采集所有受试者的rs-fMRI数据,基于预定义感兴趣区(Region of Interest, ROI)进行全脑FC分析。比较组间FC差异,分析差异脑区FC值与蒙特利尔认知评估(Montreal Cognitive Assessment, MoCA)评分的相关性,并采用受试者工作特征(Receiver Operating Characteristic, ROC)曲线评估这些FC值对PD-CI的鉴别效能。结果:与PD-NC组相比,PD-CI患者在双侧颞中回及左侧楔叶表现为FC增强,而在右侧扣带回中部表现为FC减弱。相关性分析显示,左侧颞中回(r = −0.585, P < 0.0001)与左侧楔叶(r = −0.529, P = 0.0003)的FC值与MoCA评分呈显著负相关。ROC曲线分析表明,左侧颞中回的FC值对PD-CI具有最佳的鉴别能力,其曲线下面积(Area Under the Curve, AUC)为0.8739。结论:PD-CI患者存在以双侧颞中回连接增强为典型特征的功能网络重组,该特征与认知损伤密切相关。左侧颞中回的功能连接强度可作为鉴别PD-CI的高度潜力的神经影像学生物标志物。
Abstract: Objective: Cognitive impairment in Parkinson’s disease (PD-CI) significantly impacts patients’ quality of life, and objective diagnostic biomarkers are currently lacking. This study aimed to investigate the aberrant patterns of functional connectivity (FC) using resting-state functional magnetic resonance imaging (rs-fMRI) in PD-CI patients and to evaluate their potential for differential diagnosis. Methods: The study enrolled 23 PD-CI patients, 20 PD patients with normal cognition (PD-NC), and 20 healthy controls (HC). rs-fMRI data were acquired from all participants. Whole-brain FC analysis was performed based on predefined regions of interest (ROIs). Inter-group differences in FC were compared. Correlations between FC values in regions showing significant differences and Montreal Cognitive Assessment (MoCA) scores were analyzed. The receiver operating characteristic (ROC) curve was employed to assess the efficacy of these FC values in discriminating PD-CI. Results: Compared to the PD-NC group, PD-CI patients exhibited increased FC within the bilateral middle temporal gyri and the left cuneus, alongside decreased FC in the right mid-cingulate cortex. Correlation analysis revealed significant negative correlations between MoCA scores and FC values in the left middle temporal gyrus (r = −0.585, P < 0.0001) and the left cuneus (r = −0.529, P = 0.0003). ROC curve analysis demonstrated that the FC value of the left middle temporal gyrus had the best discriminatory power for PD-CI, with an area under the curve (AUC) of 0.8739. Conclusion: Patients with PD-CI display a reorganization of functional networks, characterized notably by enhanced connectivity within the bilateral middle temporal gyri, which is closely associated with cognitive deficits. The functional connectivity strength of the left middle temporal gyrus may serve as a highly promising neuroimaging biomarker for identifying PD-CI.
文章引用:楚晨曦, 刘时华, 朱啸薇, 陈岩, 张超, 钟平, 曹立. 帕金森病认知障碍患者静息态功能连接的改变及其鉴别价值[J]. 临床医学进展, 2026, 16(4): 580-590. https://doi.org/10.12677/acm.2026.1641283

参考文献

[1] Zhong, J., Guan, X., Zhong, X., Cao, F., Gu, Q., Guo, T., et al. (2019) Levodopa Imparts a Normalizing Effect on Default-Mode Network Connectivity in Non-Demented Parkinson’s Disease. Neuroscience Letters, 705, 159-166. [Google Scholar] [CrossRef] [PubMed]
[2] Weintraub, D., Aarsland, D., Biundo, R., Dobkin, R., Goldman, J. and Lewis, S. (2022) Management of Psychiatric and Cognitive Complications in Parkinson’s Disease. BMJ, 379, e068718. [Google Scholar] [CrossRef] [PubMed]
[3] Wallace, E.R., Segerstrom, S.C., van Horne, C.G., Schmitt, F.A. and Koehl, L.M. (2021) Meta-Analysis of Cognition in Parkinson’s Disease Mild Cognitive Impairment and Dementia Progression. Neuropsychology Review, 32, 149-160. [Google Scholar] [CrossRef] [PubMed]
[4] Gallagher, J., Gochanour, C., Caspell-Garcia, C., et al. (2024) Long-Term Dementia Risk in Parkinson Disease. Neurology, 103, e209699.
[5] Aarsland, D., Batzu, L., Halliday, G.M., Geurtsen, G.J., Ballard, C., Ray Chaudhuri, K., et al. (2021) Parkinson Disease-Associated Cognitive Impairment. Nature Reviews Disease Primers, 7, Article No. 47. [Google Scholar] [CrossRef] [PubMed]
[6] 孙维洋, 史晓航, 范玉, 等. 磁共振成像在帕金森病认知障碍中的研究进展[J]. 磁共振成像, 2023, 14(7): 134-138.
[7] Yan, C.G. and Zhang, Y.F. (2010) DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI. Frontiers in Systems Neuroscience, 4, Article 13.
[8] 罗树存, 罗泽斌, 罗旭东, 等. 广泛性焦虑障碍静息态功能磁共振脑功能的研究[J]. 临床放射学杂志, 2018, 37(9): 1427-1430.
[9] Gonzalez-Castillo, J., Kam, J.W.Y., Hoy, C.W. and Bandettini, P.A. (2021) How to Interpret Resting-State fMRI: Ask Your Participants. The Journal of Neuroscience, 41, 1130-1141. [Google Scholar] [CrossRef] [PubMed]
[10] Amboni, M., Tessitore, A., Esposito, F., Santangelo, G., Picillo, M., Vitale, C., et al. (2014) Resting-State Functional Connectivity Associated with Mild Cognitive Impairment in Parkinson’s Disease. Journal of Neurology, 262, 425-434. [Google Scholar] [CrossRef] [PubMed]
[11] Nomi, J.S., Farrant, K., Damaraju, E., Rachakonda, S., Calhoun, V.D. and Uddin, L.Q. (2016) Dynamic Functional Network Connectivity Reveals Unique and Overlapping Profiles of Insula Subdivisions. Human Brain Mapping, 37, 1770-1787. [Google Scholar] [CrossRef] [PubMed]
[12] Li, K., Su, W., Li, S., Jin, Y. and Chen, H. (2018) Resting State fMRI: A Valuable Tool for Studying Cognitive Dysfunction in Pd. Parkinsons Disease, 2018, Article ID: 6278649. [Google Scholar] [CrossRef] [PubMed]
[13] Postuma, R.B., Berg, D., Stern, M., Poewe, W., Olanow, C.W., Oertel, W., et al. (2015) MDS Clinical Diagnostic Criteria for Parkinson’s Disease. Movement Disorders, 30, 1591-1601. [Google Scholar] [CrossRef] [PubMed]
[14] Jastrzębowska, M.A., Marquis, R., Melie‐García, L., Lutti, A., Kherif, F., Herzog, M.H., et al. (2019) Dopaminergic Modulation of Motor Network Compensatory Mechanisms in Parkinson’s Disease. Human Brain Mapping, 40, 4397-4416. [Google Scholar] [CrossRef] [PubMed]
[15] Gardini, S., Venneri, A., Sambataro, F., Cuetos, F., et al. (2015) Increased Functional Connectivity in the Default Mode Network in Mild Cognitive Impairment: A Maladaptive Compensatory Mechanism Associated with Poor Semantic Memory Performance. Journal of Alzheimers Disease, 45, 457-470. [Google Scholar] [CrossRef] [PubMed]
[16] Das, S.R., Pluta, J., Mancuso, L., Kliot, D., Orozco, S., Dickerson, B.C., et al. (2012) Increased Functional Connectivity within Medial Temporal Lobe in Mild Cognitive Impairment. Hippocampus, 23, 1-6. [Google Scholar] [CrossRef] [PubMed]
[17] Piramide, N., De Micco, R., Siciliano, M., Silvestro, M. and Tessitore, A. (2024) Resting-State Functional MRI Approaches to Parkinsonisms and Related Dementia. Current Neurology and Neuroscience Reports, 24, 461-477. [Google Scholar] [CrossRef] [PubMed]
[18] Kicik, A., Bayram, A., Erdogdu, E., Kurt, E., Saridede, D.B., Cengiz, S., et al. (2025) Investigation of Symptom-Specific Functional Connectivity Patterns in Parkinson’s Disease. Neurological Sciences, 46, 4385-4396. [Google Scholar] [CrossRef] [PubMed]
[19] Hou, Y., Yang, J., Luo, C., Song, W., Ou, R., Liu, W., et al. (2016) Dysfunction of the Default Mode Network in Drug-Naïve Parkinson’s Disease with Mild Cognitive Impairments: A Resting-State fMRI Study. Frontiers in Aging Neuroscience, 8, Article 247. [Google Scholar] [CrossRef] [PubMed]
[20] Li, X., Pang, H., Bu, S., Zhao, M., Wang, J., Liu, Y., et al. (2024) Stage-Dependent Differential Impact of Network Communication on Cognitive Function across the Continuum of Cognitive Decline in Parkinson’s Disease. Neurobiology of Disease, 199, Article ID: 106578. [Google Scholar] [CrossRef] [PubMed]
[21] Guo, W., Jin, W., Li, N., Gao, J., Wang, J., Chang, Y., et al. (2021) Brain Activity Alterations in Patients with Parkinson’s Disease with Cognitive Impairment Based on Resting-State Functional MRI. Neuroscience Letters, 747, Article ID: 135672. [Google Scholar] [CrossRef] [PubMed]
[22] Owens-Walton, C., Jakabek, D., Power, B.D., Walterfang, M., Hall, S., van Westen, D., et al. (2021) Structural and Functional Neuroimaging Changes Associated with Cognitive Impairment and Dementia in Parkinson’s Disease. Psychiatry Research: Neuroimaging, 312, Article ID: 111273. [Google Scholar] [CrossRef] [PubMed]
[23] Maier, F., Greuel, A., Hoock, M., Kaur, R., Tahmasian, M., Schwartz, F., et al. (2021) Impaired Self-Awareness of Cognitive Deficits in Parkinson’s Disease Relates to Cingulate Cortex Dysfunction. Psychological Medicine, 53, 1244-1253. [Google Scholar] [CrossRef] [PubMed]
[24] Mograbi, D.C., Rodrigues, R., Bienemann, B. and Huntley, J. (2024) Brain Networks, Neurotransmitters and Psychedelics: Towards a Neurochemistry of Self-Awareness. Current Neurology and Neuroscience Reports, 24, 323-340. [Google Scholar] [CrossRef] [PubMed]
[25] Chung, S.J., Kim, Y.J., Jung, J.H., Lee, H.S., Ye, B.S., Sohn, Y.H., et al. (2022) Association between White Matter Connectivity and Early Dementia in Patients with Parkinson Disease. Neurology, 98, e1846-e1856. [Google Scholar] [CrossRef] [PubMed]
[26] Shang, S., Zhu, S., Wu, J., Xu, Y., Chen, L., Dou, W., et al. (2022) Topological Disruption of high‐order Functional Networks in Cognitively Preserved Parkinson’s Disease. CNS Neuroscience & Therapeutics, 29, 566-576. [Google Scholar] [CrossRef] [PubMed]
[27] Nishal, Z., Khan, S. and Kamran, B. (2025) Diagnostic Utility of Diffusion Tensor Imaging and Functional MRI in Early Neurodegeneration: A Systematic Review of Structural and Functional Brain Biomarkers. Cureus, 17, e89418. [Google Scholar] [CrossRef
[28] Hao, X., Xiao, X., Weng, L., Lin, Z., Xu, Q., Du, J., et al. (2025) Genetic Risk and Plasma Biomarkers of Dementia with Lewy Bodies in a Chinese Population. npj Parkinsons Disease, 11, Article No. 128. [Google Scholar] [CrossRef] [PubMed]
[29] Delva, A., Zatti, C., Pelletier, A., Montplaisir, J., Gagnon, J., Kollmorgen, G., et al. (2025) Plasma Markers of Astrocytic and Axonal Integrity in Idiopathic/Isolated REM Sleep Behavior Disorder (iRBD) as Predictors of Dementia with Lewy Bodies. Movement Disorders, 40, 2497-2503. [Google Scholar] [CrossRef
[30] Sasikumar, S. and Strafella, A.P. (2020) Imaging Mild Cognitive Impairment and Dementia in Parkinson’s Disease. Frontiers in Neurology, 11, Article 47. [Google Scholar] [CrossRef] [PubMed]
[31] Shafiei, G., Zeighami, Y., Clark, C.A., Coull, J.T., Nagano-Saito, A., Leyton, M., et al. (2018) Dopamine Signaling Modulates the Stability and Integration of Intrinsic Brain Networks. Cerebral Cortex, 29, 397-409. [Google Scholar] [CrossRef] [PubMed]
[32] Ay, U. and Gürvit, İ.H. (2022) Alterations in Large-Scale Intrinsic Connectivity Networks in the Parkinson’s Disease-Associated Cognitive Impairment Continuum: A Systematic Review. Archives of Neuropsychiatry, 59, S57-S66. [Google Scholar] [CrossRef] [PubMed]