| Cognitive dysfunction is a pretty common non-motor symptom of Parkinson’s disease, including mild cognitive impairment in Parkinson’s disease (PD-MCI) and Parkinson’s disease dementia (PDD), PD-MCI is an independent risk factor for PDD. The Movement Disorder Society (MDS) formalized diagnostic criteria for PD-MCI in January2012. Studies have shown that the prevalence of PD-MCI was18.9%-38.2%, even as high as52.8%in the non-demented PD. Annual progression rate from PD-MCI to dementia was6%-15%,62%of PD-MCI patients progress into PDD in four years. Patients with cognitive impairment in PD combined with severe motor symptoms resulted in a heavy social and economic burden. Therefore, early detection and timely intervention to delay the progression may be the most effective treatment for cognitive deficits in PD.There has been significant clinical heterogeneity in PD-MCI. It can initiate either at advanced or at the beginning of the PD diagnosis, involving a wide range of cognitive domains, including executive function, memory, attention, visuospatial ability, language fluency. Complex intrinsic pathophysiological changes may be associated with the formation of Lewy body, Alzheimer’s disease (AD)-like pathological changes and cerebral microvascular disease, accompanied by a variety of neurotransmitters participation and extensive neuronal degeneration. PD-MCI is an intermediate state between cognitively normal Parkinson’s disease (PDCN) and PDD, the study of which will help us to look insight into the characteristics and evolution of PD cognitive dysfunction.Although MDS has developed the PD-MCI diagnostic criteria, there are few systematic researches about it. Because of the diversity of assessment scale and diagnostic criteria adopted, the prevalence ranges from17.4%to38.2%and the clinical phenotype of the disease is also controversial. Some researchers believe that the single frontal/executive function impairment is the most common in PD-MCI. To the contrary, a multicenter study enrolling1346patients indicated that the most common clinical phenotype of PD-MCI is memory deficit in. Currently, there are only two studies showed that PD-MCI might be associated with older age, male, late onset, depression and severe motor symptoms, the correlation between vascular risk factors and PD-MCI has not been reported yet. And studies on these aspects are foreign publications, there is no research on Chinese PD population at present.At present, the diagnosis of PD-MCI, PDD and even PD is still in clinical diagnosis, lacking effective molecular biological and neuroimaging markers. And the study on pathogenesis of cognitive impairrment of PD is limited to autopsy of small samples, animal and cell experiments. With the development of imaging equipment and image processing techniques, the structural and functional brain imaging provides an important way in vitro to observe the brain shape, volume, density, structural integrity, metabolic changes and to analyze the cognitive activities. Previous semi-quantitative or quantitative analysis method is not only subjective and limited to small study areas, but also can not extract subtle structural changes and can not be compared with other similar studies. In the study of brain structure, a new analysis method based on voxelwas adopted to conduct automated quantitative analysis for gray matter, white matter and white matter fiber integrity of the whole brain in the statistical parametric mapping software (SPM). This method has been successfully applied in the the studies of neurodegenerative disease, headache, mental disease, and sleep disorder. Among the studies, researches on PDD are common, which found that PDD patients have widespread brain atrophy and white matter fiber changes.However, the study on the early-PD-MCI, especially the study on the entire brain white matter fiber has not been reported. Brain atrophy and white matter fiber lesions can be used as neuropathological markers of PD cognitive dysfunction, even in the early stage, as in other neurodegenerative diseases with dementia, such as AD. So here is my hypothesis:brain atrophy and/or white matter integrity lesions may bean important factor leading to PD-MCI.Our research group has developed a series of cognitive function assessment system for PD patients in China, which were applied to a number of neuroimaging and molecular biological studies,.many research results were published in international journals and conference communications and recoguzed by the domestic and international peers. In this study all non-demented PD patients were classified into cognitively normal Parkinson’s disease (PDCN) or PD-MCI considering global cognitive and four cognitive domains (executive function/planning skills, memory, attention and visual-spatial skill), according to the diagnostic criteria for PD-MCI (MDS), excluding dementia and severe depression. The objective of this study was to determine the prevalence, subtype, clinical characteristics and risk factors of mild cognitive impairment in Parkinson’s disease (PD-MCI).,which will contribute to a comprehensive understanding of the PD-MCI and provide theoretical basis for earlyintervention. Besides,we analyzed the changes of structural brain and white matter fiber in PD-MCI patients by combining VBM and DTI magnetic resonance imaging technology We aimedto explore the relevance between cognitive dysfunction and brain structure changes, to find potential pathological changes and the internal mechanism and tofind the characteristic imaging markers for the early identification and diagnosis of PD-MCI.Part I:Mild Impairment in Parkinson’s disease:Motor and Cognitive Characteristics, Risk FactorsObjective:The objective of this study was to determine the prevalence, subtype, clinical characteristics and risk factors of mild cognitive impairment in Parkinson’s disease (PD-MCI)Methods:We performed a retrospective study of234non-demented PD patients, who completed a standardized neurological assessment, including demographic and clinical information and a full neuropsychological battery. All non-demented PD patients were classified into cognitively normal Parkinson’s disease (PDCN) or PD-MCI considering global cognitive and four cognitive domains (executive function/planning skills, memory, attention and visual-spatial skill) according to the diagnostic criteria for PD-MCI (MDS), excluding dementia and severe depression. We further divided participants with MCI into four subtypes:amnestic single domain, amnestic multiple domain, nonamnestic single domain or nonamnestic multiple domain and analyzed the characteristics of the four subtypes. The risk factors for PD-MCI were examined using binary logistic regression.Results:(1) A total of45.3%of subjects (106) were classified as MCI. The MCI group had older age at assessment and at disease onset, shorter years of education and more severe motor symptoms than the cognitively normal group(P<0.05).(2) Single-domain impairment is the most common subtype of PD-MCI, Of which executive ability impairment was the most common (22.64%), followed by memory (20.75%), visual-spatial (6.6%) and attention impairment (2.83%). Regarding cognitive profiles,32.08%were classified as nonamnestic single domain MCI,20.75%as amnestic single-domain,36.79%as amnestic multiple domain, and10.38%as nonamnestic multiple-domain MCI.(3) Differences were not significant in the severity of motor symptoms among the four subtypes of PD-MCI. The education level may be associated with memory deficits, the decline of global cognition in amnestic multiple domain-MCI patients was more severe.(4)Regression analysis showed that advanced age, high score of UPDRS-Ⅲ and hyperhomocysteinemia were risk factors for PD-MCI and the high level of education was a protective factor, with lower risk of cognitive impairment in patients with a high level of education.Conclusions:MCI is common in patients with PD without dementia, affecting a range of cognitive domains, including memory, visual-spatial, and attention/executive abilities, of which single-domain impairment is the most common subtype. Differences were not significant in the severity of motor symptoms among the four subtypes of PD-MCI. MCI was associated with older age at assessment,lower levels of education, more severe motor symptoms, and vascular risk factors of hyperhomocysteinemia. Part II:A magnetic resonance imaging study of patients with Parkinson’s disease with mild cognitive impairment using voxel-based morphometryObjective:Voxel-based morphometry was used to examine the changes of gray and white matter in the brains of patients with mild cognitive impairment in Parkinson’s disease (PD-MCI) and to identify the specific regions responsible for cognitive dysfunction in PD.Methods:Patients were classified into PDCN (23) and PDMCI (21) groups according to the diagnostic criteria for PD-MCI (MDS), and21age-matched healthy control subjects recruited from an outpatient setting, who underwent3.0T MRI and neuropsychological assessment. The statistical MRI analyses were carried-out using SPM8(Wellcome Department of Imaging Neuroscience, London, UK) running under MatlabR2008a (Math Works, Natick, MA). A standard VBM analysis was used to assess the pattern of gray and white matter changes according to previously described methods. The preprocessing steps included normalization of the images to a template, segmentation into tissue classes, modulation and smoothing. The resulting smoothed and modulated images were used in the statistical analysis to assess gray matter volume and white matter density changes. Regional volume differences were determined using statistics at every voxel in the GM and WM from patients with PD-MCI and PDCN and healthy controls. In the PD patients, a correlation was also performed between local gray matter volume, white matter density and the score of MMSE and MoCA, two tests of global cognitive function.Results:(1) In a comparison between PDCN and control subjects, GM volume was significantly reduced in prefrontal, limbic system and middle temporal gyrus, WM density was significantly decreased in the basal ganglia and frontal areas.(2) PD-MCI showed grey matter atrophy in the frontal, limbic system, basal ganglia and cerebellum areas compared to control, WM density was significantly decreased in the frontal lobe and caudate nucleus.(3) PD-MCI patients had greater gray matter atrophy in the inferior/middle temporal gyrus and frontal lobe compared to PDCN, patients with PD-MCI exhibited decreasedWM density throughout the right inferior frontal gyrus, midbrain, and occipital lobe/lingual gyrus compared with PDCN.(4) Right cingulate and limbic of GM, frontal lobe, limbic and parahippocampal gyrus of WM were correlated with performance on the memory-based test of MMSE.(5) Regions related to non-memory-based MoCA scores were gray matter regions of the frontal lobe, basal ganglia, parahippocampal gyrus, occipital lobe and cerebellum, white matter regions of the frontal lobe, parietal lobe, precuneus, occipital lobe, cuneus, the insular cortex, limbic system and cerebellum.Conclusions:These findings show that mild cognitive impairment in Parkinson’s disease is associated with structural neocortical changes in the brain, such as the frontal lobe, limbic system, the medial temporal lobe and basal ganglia, and that cognitive impairment in patients with PD without dementia may be associated with structural changes in the brain. Memory deficits related to the limbic lobe atrophy, frontal lobe atrophy associated with executive dysfunction. The atrophy of the cerebral cortex and subcortical structures may coexist in brain of PD cognitive function disorders, the underlined mechanisms may be the Lewy body degeneration and AD-like pathological changes. VBM can find subtle changes in brain even in early phase of PD cognitive impairment, the atrophy of the brain structures may become neuroimaging markers for the early diagnosis of PD-MCI. Further studies with larger groups of patients are needed to confirm these findings. Part III:Voxel-based Analysis of Diffusion Tensor Imaging in the Brain of Patients with Mild Cognitive Impairment in Parkinson’s diseaseObjective:To assess the microstructural damage to cerebral white matter and its relationship with the cognitive dysfunction in patients with Parkinson’s disease (PD) through diffusion tensor imaging (DTI).Methods:Fifteen patients with PD-MCI,17patients with PDCN, and15age-matched healthy controls underwent diffusion tensor imaging with a3T MR imager. Voxel-based DTI procedure:we calculated fractional anisotropy with DTI studio software version2.40(www.mristudio.org). The statistical MRI analyses were carried-out using SPM8(Wellcome Department of Imaging Neuroscience, London, UK) running under MatlabR2008a (Math Works, Natick, MA). We performed voxel-based analysis of variance with SPM8to detect white matter integrity differences among3groups using fractional anisotropy values as the dependent variables. In the PD patients, a correlation was also performed between the fractional anisotropy values and the score of MMSE and MoCA, two tests of global cognitive function.Results:(1) FA was significantly lower in patients with PDCN than in healthy controls in both the right frontal and precentral gyrus.(2) In a comparison between PD-MCI and control subjects, FA was significantly reduced in the left superior temporal gyrus and inferior parietal lobule, followed by the thalamus, lentiform nucleus, insular, posterior cingulate gyrus, precuneus, occipital lobe and fusiform gyrus.(3) The PD-MCI group showed significant F A reduction in the right superior parietal lobule, precuneus and left middle occipital gyrus and cuneus, followed by the thalamus, posterior cingulated, inferior parietal gyrus, limbic, parahippocampal gyrus and superior temporal gyrus compared with PDND.(4) There was a positive correlation between FA values and the performance of MMSE and MoCA in PD patients. FA values in the right thalamus, cerebellum anterior lobe, culmen occipital lobe, limbic, parahippocampal gyrus and the left midbrain, thalamus and putamen showed significant correlations with the score of MMSE. Regions related to non-memory-based MoCA scores were the limbic lobe, parahippocampal gyrus, middle temporal gyrus, inferior parietal gyrus, precuneus, occipital lobe lingual gyrus, thalamus, cerebellum anterior lobe and basal ganglia.Conclusions:These findings show that mild cognitive impairment in Parkinson’s disease is associated with local white matter fiber integrity changes in the brain, such as superior parietal lobule, precuneus, middle occipital gyrus, cuneus and middle temporal gyrus; FA values in the periventricular cingulate, precuneus, cuneus and lingual gyrus showed significant correlations with the global cognitive function, these changes were associated with cholinergic fiber damage. Integrity of white matter fiber changes may accelerate PD cognitive dysfunction. Whole brain voxel-based analysis of DTI can reflect white matter changes fully and accurately, which contributes to the early diagnosis of cognitive impairment in PD... |
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