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Hajebrahimi F, Budak M, Saricaoglu M, Temel Z, Demir TK, Hanoglu L, Yildirim S, Bayraktaroglu Z. Functional neural networks stratify Parkinson's disease patients across the spectrum of cognitive impairment. Brain Behav 2024; 14:e3395. [PMID: 38376051 PMCID: PMC10808882 DOI: 10.1002/brb3.3395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 11/23/2023] [Accepted: 12/26/2023] [Indexed: 02/21/2024] Open
Abstract
INTRODUCTION Cognitive impairment (CI) is a significant non-motor symptoms in Parkinson's disease (PD) that often precedes the emergence of motor symptoms by several years. Patients with PD hypothetically progress from stages without CI (PD-normal cognition [NC]) to stages with Mild CI (PD-MCI) and PD dementia (PDD). CI symptoms in PD are linked to different brain regions and neural pathways, in addition to being the result of dysfunctional subcortical regions. However, it is still unknown how functional dysregulation correlates to progression during the CI. Neuroimaging techniques hold promise in discriminating CI stages of PD and further contribute to the biomarker formation of CI in PD. In this study, we explore disparities in the clinical assessments and resting-state functional connectivity (FC) among three CI stages of PD. METHODS We enrolled 88 patients with PD and 26 healthy controls (HC) for a cross sectional clinical study and performed intra- and inter-network FC analysis in conjunction with comprehensive clinical cognitive assessment. RESULTS Our findings underscore the significance of several neural networks, namely, the default mode network (DMN), frontoparietal network (FPN), dorsal attention network, and visual network (VN) and their inter-intra-network FC in differentiating between PD-MCI and PDD. Additionally, our results showed the importance of sensory motor network, VN, DMN, and salience network (SN) in the discriminating PD-NC from PDD. Finally, in comparison to HC, we found DMN, FPN, VN, and SN as pivotal networks for further differential diagnosis of CI stages of PD. CONCLUSION We propose that resting-state networks (RSN) can be a discriminating factor in distinguishing the CI stages of PD and progressing from PD-NC to MCI or PDD. The integration of clinical and neuroimaging data may enhance the early detection of PD in clinical settings and potentially prevent the disease from advancing to more severe stages.
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Affiliation(s)
- Farzin Hajebrahimi
- Functional Imaging and Cognitive‐Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Department of Physical Therapy and Rehabilitation, School of Health SciencesIstanbul Medipol UniversityIstanbulTurkey
- Department of Health Informatics, Rutgers University, School of Health ProfessionsRutgers Biomedical and Health SciencesNewarkNew JerseyUSA
| | - Miray Budak
- Functional Imaging and Cognitive‐Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Department of Ergotherapy, School of Health SciencesIstanbul Medipol UniversityIstanbulTurkey
- Center for Molecular and Behavioral NeuroscienceRutgers University‐NewarkNewarkNew JerseyUSA
| | - Mevhibe Saricaoglu
- Functional Imaging and Cognitive‐Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Program of Electroneurophysiology, Vocational SchoolIstanbul Medipol UniversityIstanbulTurkey
| | - Zeynep Temel
- Department of PsychologyFatih Sultan Mehmet Vakif UniversityIstanbulTurkey
| | - Tugce Kahraman Demir
- Program of Electroneurophysiology, Vocational SchoolBiruni UniversityIstanbulTurkey
| | - Lutfu Hanoglu
- Department of Neurology, School of MedicineIstanbul Medipol UniversityIstanbulTurkey
- Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
| | - Suleyman Yildirim
- Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Department of Medical Microbiology, International School of MedicineIstanbul Medipol UniversityIstanbulTurkey
| | - Zubeyir Bayraktaroglu
- Functional Imaging and Cognitive‐Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Department of Physiology, International School of MedicineIstanbul Medipol UniversityIstanbulTurkey
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Jahanshahi A, Ghareaghaji N, Hassanpour S, Vafadar A, Mousavi S, Khezerloo D. Cortical gray matter and cerebral white matter atrophy and asymmetry in Parkinson's disease patients with normal cognitive precede. Int J Neurosci 2023:1-6. [PMID: 38085250 DOI: 10.1080/00207454.2023.2294260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 12/08/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Parkinson's disease is the second most common neurodegenerative disorder with complex and distributed motor and non-motor symptoms. In this study, cortical gray matter (GM) and cerebral white matter (WM) overall atrophy, and asymmetry of atrophy are investigated in PD with normal cognitive function. METHOD Forty-eight male Parkinson's disease(PD) patients with normal cognitive precede (PD-NC), and thirty matched healthy control (HC) subjects were selected from the Parkinson's Progression Markers Initiative (PPMI) database. Brain structures volumes were extracted using Freesurfer software based on subject 3 tesla MRI images. The normalized volume of cortical GM and cerebral WM were compared in two study groups, and then the asymmetry index (AI) of GM and WM atrophy was also assessed in two groups. Statistical analysis was constructed using a t-test with p < 0.05 of significance. RESULTS No significant difference was observed in the volume of cortical GM and cerebral WM in the two study groups. The cortical GM asymmetry index in the PD-NC group was significantly (p = 0.01) higher than the HC group, however, no difference was observed for the cerebral WM asymmetry index. CONCLUSION Atrophy in cortical GM and WM was not observed between the PD-NC and the HC group, however, the asymmetry index in GM was significant between the two group. It seems that the brain's bilateral balance has ruptured in PD. Cortical GM asymmetry in PD-NC can be considered a potent biomarker and should be investigated more in the future. In future studies, construction of a longitudinal study on this issue could be useful.
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Affiliation(s)
- Amirreza Jahanshahi
- Department of Radiology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Nahideh Ghareaghaji
- Department of Radiology, Faculty of Allied Medical Sciences, Tabriz University of Medical Science, Tabriz, Iran
| | - Samaneh Hassanpour
- Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Ali Vafadar
- Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Saeid Mousavi
- Department of Statistics and Epidemiology, Faculty of Health Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Davood Khezerloo
- Department of Radiology, Faculty of Allied Medical Sciences, Tabriz University of Medical Science, Tabriz, Iran
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Yue JH, Zhang QH, Yang X, Wang P, Sun XC, Yan SY, Li A, Zhao WW, Cao DN, Wang Y, Wei ZY, Li XL, Zhu LW, Yang G, Mah JZ. Magnetic resonance imaging of white matter in Alzheimer's disease: a global bibliometric analysis from 1990 to 2022. Front Neurosci 2023; 17:1163809. [PMID: 37304017 PMCID: PMC10248146 DOI: 10.3389/fnins.2023.1163809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Accepted: 04/26/2023] [Indexed: 06/13/2023] Open
Abstract
Background Alzheimer's disease (AD) is a common, progressive, irreversible, and fatal neurodegenerative disorder with rapidly increasing worldwide incidence. Although much research on magnetic resonance imaging (MRI) of the white matter (WM) in AD has been published, no bibliometric analysis study has investigated this issue. Thus, this study aimed to provide an overview of the current status, hotspots, and trends in MRI of WM in AD. Methods We searched for records related to MRI studies of WM in AD from 1990 to 2022 in the Web of Science Core Collection (WOSCC) database. CiteSpace (version 5.1.R8) and VOSviewer (version 1.6.19) software were used for bibliometric analyses. Results A total of 2,199 articles were obtained from this study. From 1990 to 2022, the number of published articles showed exponential growth of y = 4.1374e0.1294x, with an average of 17.9 articles per year. The top country and institutions were the United States and the University of California Davis, accounting for 44.52 and 5.32% of the total studies, respectively. The most productive journal was Neurology, and the most co-cited journal was Lancet Neurology. Decarli C was the most productive author. The current research frontier trend focuses on the association between small vessel disease and AD, the clinical application and exploration of diffusion MRI, and related markers. Conclusion This study provides an in-depth overview of publications on MRI of WM in AD, identifying the current research status, hotspots, and frontier trends in the field.
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Affiliation(s)
- Jin-huan Yue
- Department of Tuina, Acupuncture and Moxibustion, Shenzhen Jiuwei Chinese Medicine Clinic, Shenzhen, China
| | - Qin-hong Zhang
- Department of Tuina, Acupuncture and Moxibustion, Shenzhen Jiuwei Chinese Medicine Clinic, Shenzhen, China
| | - Xu Yang
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Peng Wang
- Department of Oncology, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xu-Chen Sun
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Shi-Yan Yan
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China
| | - Ang Li
- Sanofifi-Aventis China Investment Co., Ltd, Beijing, China
| | | | - Dan-Na Cao
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Yang Wang
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ze-Yi Wei
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xiao-Ling Li
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Lu-Wen Zhu
- Department of Rehabilitation, Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
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Morphological basis of Parkinson disease-associated cognitive impairment: an update. J Neural Transm (Vienna) 2022; 129:977-999. [PMID: 35726096 DOI: 10.1007/s00702-022-02522-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 05/25/2022] [Indexed: 12/15/2022]
Abstract
Cognitive impairment is one of the most salient non-motor symptoms of Parkinson disease (PD) that poses a significant burden on the patients and carers as well as being a risk factor for early mortality. People with PD show a wide spectrum of cognitive dysfunctions ranging from subjective cognitive decline and mild cognitive impairment (MCI) to frank dementia. The mean frequency of PD with MCI (PD-MCI) is 25.8% and the pooled dementia frequency is 26.3% increasing up to 83% 20 years after diagnosis. A better understanding of the underlying pathological processes will aid in directing disease-specific treatment. Modern neuroimaging studies revealed considerable changes in gray and white matter in PD patients with cognitive impairment, cortical atrophy, hypometabolism, dopamine/cholinergic or other neurotransmitter dysfunction and increased amyloid burden, but multiple mechanism are likely involved. Combined analysis of imaging and fluid markers is the most promising method for identifying PD-MCI and Parkinson disease dementia (PDD). Morphological substrates are a combination of Lewy- and Alzheimer-associated and other concomitant pathologies with aggregation of α-synuclein, amyloid, tau and other pathological proteins in cortical and subcortical regions causing destruction of essential neuronal networks. Significant pathological heterogeneity within PD-MCI reflects deficits in various cognitive domains. This review highlights the essential neuroimaging data and neuropathological changes in PD with cognitive impairment, the amount and topographical distribution of pathological protein aggregates and their pathophysiological relevance. Large-scale clinicopathological correlative studies are warranted to further elucidate the exact neuropathological correlates of cognitive impairment in PD and related synucleinopathies as a basis for early diagnosis and future disease-modifying therapies.
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