Verbal Memory in Parkinson's Disease: A Combined DTI and fMRI Study

Neurocognitive correlates of semantic memory navigation in Parkinson's disease

Cognitive studies on Parkinson's disease (PD) reveal abnormal semantic processing. Most research, however, fails to indicate which conceptual properties are most affected and capture patients' neurocognitive profiles. Here, we asked persons with PD, healthy controls, and individuals with behavioral variant frontotemporal dementia (bvFTD, as a disease control group) to read concepts (e.g., 'sun') and list their features (e.g., hot). Responses were analyzed in terms of ten word properties (including concreteness, imageability, and semantic variability), used for group-level comparisons, subject-level classification, and brain-behavior correlations. PD (but not bvFTD) patients produced more concrete and imageable words than controls, both patterns being associated with overall cognitive status. PD and bvFTD patients showed reduced semantic variability, an anomaly which predicted semantic inhibition outcomes. Word-property patterns robustly classified PD (but not bvFTD) patients and correlated with disease-specific hypoconnectivity along the sensorimotor and salience networks. Fine-grained semantic assessments, then, can reveal distinct neurocognitive signatures of PD.

Study of the relationship between onset lateralization and hemispheric white matter asymmetry in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is characterized by a lateralized onset, but its cause and mechanism are still unclear.

METHODS

Obtaining diffusion tensor imaging (DTI) data from the Parkinson's Progression Markers Initiative (PPMI). Tract-based spatial statistics analysis and region-of-interest-based analysis were performed to evaluate the white matter (WM) asymmetry using original DTI parameters, Z Score normalized parameters, or the asymmetry index (AI). Hierarchical cluster analysis and least absolute shrinkage and selection operator regression were performed to construct predictive models for predicting the PD onset side. DTI data from The Second Affiliated Hospital of Chongqing Medical University were obtained for external validation of the prediction model.

RESULTS

118 PD patients and 69 healthy controls (HC) from PPMI were included. Right-onset PD patients presented more asymmetric areas than left-onset PD patients. The inferior cerebellar peduncle (ICP), superior cerebellar peduncle (SCP), external capsule (EC), cingulate gyrus (CG), superior fronto-occipital fasciculus (SFO), uncinate fasciculus (UNC), and tapetum (TAP) showed significant asymmetry in left-onset and right-onset PD patients. An onset-side-specific pattern of WM alterations exists in PD patients, and a prediction model was constructed. The predicting models based on AI and ΔZ Score presented favorable efficacy in predicting PD onset side by external validation in 26 PD patients and 16 HCs from our hospital.

CONCLUSIONS

Right-onset PD patients may have more severe WM damage than left-onset PD patients. WM asymmetry in ICP, SCP, EC, CG, SFO, UNC, and TAP may predict PD onset side. Imbalances in the WM network may underlie the mechanism of lateralized onset in PD.

MAPT rs17649553 T allele is associated with better verbal memory and higher small-world properties in Parkinson's disease

Currently, over 90 genetic loci have been found to be associated with Parkinson's disease (PD) in genome-wide association studies, nevertheless, the effects of these genetic variants on the clinical features and brain structure of PD patients are largely unknown. This study investigated the effects of microtubule-associated protein tau (MAPT) rs17649553 (C>T), a genetic variant associated with reduced PD risk, on the clinical manifestations and brain networks of PD patients. We found MAPT rs17649553 T allele was associated with better verbal memory in PD patients. In addition, MAPT rs17649553 significantly shaped the topology of gray matter covariance network and white matter network. Both the network metrics in gray matter covariance network and white matter network were correlated with verbal memory, however, the mediation analysis showed that it was the small-world properties in white matter network that mediated the effects of MAPT rs17649553 on verbal memory. These results suggest that MAPT rs17649553 T allele is associated with higher small-world properties in structural network and better verbal memory in PD.

Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study

Introduction

Parkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD.

Objective

In this study, structural connectivity and white matter networks were analyzed by diffusion MRI and graph theory in a cohort of patients with PD and a cohort of healthy controls (HC) obtained from the Parkinson's Progression Markers Initiative (PPMI) database in a cross-sectional analysis. Furthermore, we investigated longitudinal changes in the PD cohort over 36 months.

Result

Compared with the control group, participants with PD showed lower structural connectivity in several brain areas, including the corpus callosum, fornix, and uncinate fasciculus, which were also confirmed by a large effect-size. Additionally, altered connectivity between baseline and after 36 months was found in different network paths inside the white matter with a medium effect-size. Network analysis showed trends toward lower network density in PD compared with HC at baseline and after 36 months, though not significant after correction. Significant differences were observed in nodal degree and strength in several nodes.

Conclusion

In conclusion, altered structural and network metrics in several brain regions, such as corpus callosum, fornix, and cingulum were found in PD, compared to HC. We also report altered connectivity in the PD group after 36 months, reflecting the impact of both PD pathology and aging processes. These results indicate that structural and network metrics might yield insight into network reorganization that occurs in PD.

Machine learning-based prediction of cognitive outcomes in de novo Parkinson's disease

Cognitive impairment is a debilitating symptom in Parkinson's disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson's Progression Markers Initiative (PPMI). Annual cognitive assessments over an 8-year time span were used to define two cognitive outcomes of (i) cognitive impairment, and (ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.

A Comparative Study of Diffusion Fiber Reconstruction Models for Pyramidal Tract Branches

Currently, comparative studies evaluating the quantification accuracy of pyramidal tracts (PT) and PT branches that were tracked based on four mainstream diffusion models are deficient. The present study aims to evaluate four mainstream models using the high-quality Human Connectome Project (HCP) dataset. Diffusion tensor imaging (DTI), diffusion spectral imaging (DSI), generalized Q-space sampling imaging (GQI), and Q-ball imaging (QBI) were used to construct the PT and PT branches in 50 healthy volunteers from the HCP. False and true PT fibers were identified based on anatomic information. One-way repeated measure analysis of variance and post hoc paired-sample t-test were performed to identify the best PT and PT branch quantification model. The number, percentage, and density of true fibers of PT obtained based on GQI and QBI were significantly larger than those based on DTI and DSI (all p < 0.0005, Bonferroni corrected), whereas false fibers yielded the opposite results (all p < 0.0005, Bonferroni corrected). More trunk branches (PT_trunk) were present in the four diffusion models compared with the upper limb (PT_Ulimb), lower limb (PT_Llimb), and cranial (PT_cranial) branches. In addition, significantly more true fibers were obtained in PT_trunk, PT_Ulimb, and PT_Llimb based on the GQI and QBI compared with DTI and DSI (all p < 0.0005, Bonferroni corrected). Finally, GQI-based group probabilistic maps showed that the four PT branches exhibited relatively unique spatial distributions. Therefore, the GQI and QBI represent better diffusion models for the PT and PT branches. The group probabilistic maps of PT branches have been shared with the public to facilitate more precise studies on the plasticity of and the damage to the motor pathway.

Imaging Cognitive Impairment and Impulse Control Disorders in Parkinson's Disease

Dementia and mild forms of cognitive impairment as well as neuropsychiatric symptoms (i. e., impulse control disorders) are frequent and disabling non-motor symptoms of Parkinson's disease (PD). The identification of changes in neuroimaging studies for the early diagnosis and monitoring of the cognitive and neuropsychiatric symptoms associated with Parkinson's disease, as well as their pathophysiological understanding, are critical for the development of an optimal therapeutic approach. In the current literature review, we present an update on the latest structural and functional neuroimaging findings, including high magnetic field resonance and radionuclide imaging, assessing cognitive dysfunction and impulse control disorders in PD.

Application of Functional Magnetic Resonance Imaging in the Diagnosis of Parkinson's Disease: A Histogram Analysis

This study aimed to investigate the value of amplitude of low-frequency fluctuation (ALFF)-based histogram analysis in the diagnosis of Parkinson's disease (PD) and to investigate the regions of the most important discriminative features and their contribution to classification discrimination. Patients with PD (n = 59) and healthy controls (HCs; n = 41) were identified and divided into a primary set (80 cases, including 48 patients with PD and 32 HCs) and a validation set (20 cases, including 11 patients with PD and nine HCs). The Automated Anatomical Labeling (AAL) 116 atlas was used to extract the histogram features of the regions of interest in the brain. Machine learning methods were used in the primary set for data dimensionality reduction, feature selection, model construction, and model performance evaluation. The model performance was further validated in the validation set. After feature data dimension reduction and feature selection, 23 of a total of 1,276 features were entered in the model. The brain regions of the selected features included the frontal, temporal, parietal, occipital, and limbic lobes, as well as the cerebellum and the thalamus. In the primary set, the area under the curve (AUC) of the model was 0.974, the sensitivity was 93.8%, the specificity was 90.6%, and the accuracy was 93.8%. In the validation set, the AUC, sensitivity, specificity, and accuracy were 0.980, 90.9%, 88.9%, and 90.0%, respectively. ALFF-based histogram analysis can be used to classify patients with PD and HCs and to effectively identify abnormal brain function regions in PD patients.

Correlation between alpha activity and neuropsychometric tests in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disease that leads to memory impairment and executive and visuospatial dysfunction as the disease progresses. Alpha activity on EEG has been related to cognition in previous studies. We aimed to investigate the correlation between alpha activity and neuropsychometric tests (NPTs) in PD patients. Fifty-five idiopathic PD patients and 20 healthy controls were included. The Standardized Mini-Mental Test (SMMT), Verbal Learning Memory Test (VLMT), Wechsler Memory Scale (WMS), Stroop Color-Word Test, Categorical Verbal Fluency Test (CVFT), Benton's Face Recognition Test (BFR), and Benton Line Judgment Orientation Test (BLOT) were administered to all participants. Patients were separated into four groups according to NPT results: healthy controls (HC); PD patients with normal cognition (PDNC); PD patients with MCI (PDMCI); and PD patients with dementia (PDD). Analysis of the EEG data showed that HC had the highest alpha activity, and PDD had the lowest. High SMMT scores were correlated with high alpha activity at posterior electrode locations in all PD groups. VLMT and WMS test scores were associated with alpha activity at the parietal sites in PDMCI. VLMT, WMS, and CVFT test scores were correlated with alpha activity at parietooccipital sites in PDD. Verbal and visuospatial memory dysfunction related to low alpha activity was evident in both PDMCI and PDD, whereas executive dysfunction was more strongly associated with low alpha activity in PDD. Analysis of alpha activity could help clinicians predict the progression of cognitive dysfunction in PD patients.

Amnestic mild cognitive impairment in Parkinson's disease: White matter structural changes and mechanisms

Mild cognitive impairment (MCI) is a heterogeneous cognitive disorder that is often comorbid with Parkinson's diseases (PD). The amnestic subtype of PD-MCI (PD-aMCI) has a higher risk to develop dementia. However, there is a lack of studies on the white matter (WM) structural changes of PD-aMCI. We characterized the WM structural changes of PD-aMCI (n = 17) with cognitively normal PD (PD-CN, n = 19) and normal controls (n = 20), using voxel-based and tract-based spatial statistics (TBSS) analyses on fractional anisotropy (FA) axial diffusivity (AD), and radial diffusivity (RD). By excluding and then including the motor performance as a covariate in the comparison analysis between PD-aMCI and PD-CN, we attempted to discern the influences of two neuropathological mechanisms on the WM structural changes of PD-aMCI. The correlation analyses between memory and voxel-based WM measures in all PD patients were also performed (n = 36). The results showed that PD-aMCI had smaller FA values than PD-CN in the diffuse WM areas, and PD-CN had higher AD and RD values than normal controls in the right caudate. Most FA difference between PD-aMCI and PD-CN could be weakened by the motor adjustment. The FA differences between PD-aMCI and PD-CN were largely spatially overlapped with the memory-correlated FA values. Our findings demonstrated that the WM structural differences between PD-aMCI and PD-CN were mainly memory-related, and the influence of motor adjustment might indicate a common mechanism underlying both motor and memory impairment in PD-aMCI, possibly reflecting a predominant influence of dopaminergic neuropathology.

Safety and preliminary efficacy of intranasal insulin for cognitive impairment in Parkinson disease and multiple system atrophy: A double-blinded placebo-controlled pilot study

Parkinson disease (PD) is associated with cognitive impairment. We aimed to determine the effects of intranasal insulin (INI) on cognition and motor performance in PD. This was a proof of concept, randomized, double-blinded, placebo-controlled trial evaluating the effects of 40 international units (IU) of insulin or saline once daily for four weeks on cognitive and functional performance. Of 16 subjects enrolled, eight in the INI group and six in the placebo group completed verbal fluency (FAS), Unified Parkinson Disease Scale (UPDRS), and modified Hoehn and Yahr scale (HY, PD severity) at baseline and post-treatment and were included in the analyses. After treatment, the INI group had a better total FAS score (p = 0.02) (41 ± 8.2 vs. 30.8 ± 7.1, mean ±SD, p = 0.02) compared to the placebo group. The INI group also had improved HY (p = 0.04) and UPDRS-Motor (Part III) (p = 0.02) scores when compared to baseline. One INI treated patient with multiple system atrophy (MSA) remained stable and did not show disease progression. The placebo group had no change. INI administration was well tolerated and there were no hypoglycemic episodes or serious study related adverse events or medications interactions. INI is safe in PD and MSA patients and may provide clinically relevant functional improvement. Larger studies are warranted to determine the INI effect in treatment of cognitive and motor impairment in Parkinson disease.

Trial Registration: ClinicalTrial.gov NCT02064166.

Functional MRI in Parkinson's Disease Cognitive Impairment

Functional magnetic resonance imaging (fMRI) has been used to study the neural bases of cognitive deficits in Parkinson's disease for several years. Traditionally, task-based fMRI has been applied to study specific cognitive functions, providing information on disease-related alterations and regarding the physiological bases of normal cognition, the dopaminergic system, and the frontostriatal circuits. More recently, functional connectivity techniques using resting-state fMRI data have been developed. Unconstrained by specific cognitive tasks, these techniques allow assessing whole-brain patterns of connectivity believed to be useful proxies for the underlying functional architecture of the brain. These methods have shown that different types of Parkinson's disease-related cognitive deficits are associated with patterns of altered connectivity within and between resting-state intrinsic connectivity networks. Although methodological standardization and the vulnerability of fMRI techniques to artifacts mandate further technical refinement, early studies provide encouraging results regarding the potential of fMRI-derived parameters for the ultimate goal of individual-subject classification.

Dilated Virchow-Robin space and Parkinson's disease: A case report of combined MRI and diffusion tensor imaging

In this manuscript we report the case of a 69-year-old female patient, who suffers from Parkinson's disease (PD) with a dilated Virchow-Robin space (dVRS) on the left anterior perforated substance. During a magnetic resonance imaging examination, the presence of a dVRS was discovered on the left anterior perforated substance. Subsequently, the patient has been subjected to further investigation of magnetic resonance imaging and diffusion tensor imaging (DTI). The DTI data of our PD patient showed increased peak frequency of left fractional anisotropy and decreases in the distribution of Mean Diffusivity(MD) with changes in the fiber density compared to the normal contralateral tract. We hypothesize that the DTI changes are due to dVRS. In the text a review of the recent literature on the presence of dVRSs, located in mono and bilateral seat, in patients with PD is reported, explaining its possible implications on disease progression, cognitive decline, and worsening of symptoms.

Microstructural Changes in Patients With Parkinson's Disease Comorbid With REM Sleep Behaviour Disorder and Depressive Symptoms

The diagnosis of Parkinson's disease (PD) is currently anchored on clinical motor symptoms, which appear more than 20 years after initiation of the neurotoxicity. Extra-nigral involvement in the onset of PD with probable nonmotor manifestations before the development of motor signs, lead us to the preclinical (asymptomatic) or prodromal stages of the disease (various nonmotor or subtle motor signs). REM sleep behavior disorder (RBD) and depression are established prodromal clinical markers of PD and predict worse motor and cognitive outcomes. Nevertheless, taken by themselves, these markers are not yet claimed to be practical in identifying high-risk individuals. Combining promising markers may be helpful in a reliable diagnosis of early PD. Therefore, we aimed to detect neural correlates of RBD and depression in 93 treatment-naïve and non-demented early PD by means of diffusion MRI connectometry. Comparing four groups of PD patients with or without comorbid RBD and/or depressive symptoms with each other and with 31 healthy controls, we found that these two non-motor symptoms are associated with lower connectivity in several white matter tracts including the cerebellar peduncles, corpus callosum and long association fibers such as cingulum, fornix, and inferior longitudinal fasciculus. For the first time, we were able to detect the involvement of short association fibers (U-fibers) in PD neurodegenerative process. Longitudinal studies on larger sample groups are needed to further investigate the reported associations.

Increased brain connectivity and activation after cognitive rehabilitation in Parkinson's disease: a randomized controlled trial

Cognitive rehabilitation programs have demonstrated efficacy in improving cognitive functions in Parkinson's disease (PD), but little is known about cerebral changes associated with an integrative cognitive rehabilitation in PD. To assess structural and functional cerebral changes in PD patients, after attending a three-month integrative cognitive rehabilitation program (REHACOP). Forty-four PD patients were randomly divided into REHACOP group (cognitive rehabilitation) and a control group (occupational therapy). T1-weighted, diffusion weighted and functional magnetic resonance images (fMRI) during resting-state and during a memory paradigm (with learning and recognition tasks) were acquired at pre-treatment and post-treatment. Cerebral changes were assessed with repeated measures ANOVA 2 × 2 for group x time interaction. During resting-state fMRI, the REHACOP group showed significantly increased brain connectivity between the left inferior temporal lobe and the bilateral dorsolateral prefrontal cortex compared to the control group. Moreover, during the recognition fMRI task, the REHACOP group showed significantly increased brain activation in the left middle temporal area compared to the control group. During the learning fMRI task, the REHACOP group showed increased brain activation in the left inferior frontal lobe at post-treatment compared to pre-treatment. No significant structural changes were found between pre- and post-treatment. Finally, the REHACOP group showed significant and positive correlations between the brain connectivity and activation and the cognitive performance at post-treatment. This randomized controlled trial suggests that an integrative cognitive rehabilitation program can produce significant functional cerebral changes in PD patients and adds evidence to the efficacy of cognitive rehabilitation programs in the therapeutic approach for PD.

Does apolipoprotein A1 predict microstructural changes in subgenual cingulum in early Parkinson?

Higher plasma cholesterol levels are associated with lower Parkinson's disease (PD) risk. Apolipoprotein A-1 (ApoA-1) is a surface marker of brain HDL-like particles associated with the time of PD onset. Clinical correlates of serum Apolipoprotein A1 levels with structural brain connectivity in PD-related disorders remains unclear. Here, we applied a novel diffusion-weighted imaging approach [Diffusion Magnetic Resonance Imaging (MRI) Connectometry] to explore the association between ApoA-1 and structural brain connectivity in PD. Participants involved in this research were recruited from Parkinson's Progression Markers Initiative (PPMI). Diffusion MRI connectometry was conducted using a multiple regression against apoA-1 for 36 patients with DTI measurements available in the baseline visit. Fiber results of the connectometry were then reconstructed for each patient, and diffusion parameters were extracted and regressed against apoA-1 levels. Connectometry results revealed the subgenual cingulum to be associated with ApoA-1, with different FDR yields. This result was further supported by significant negative correlation of Quantitative Anisotropic (QA) of left subgenual cingulum (Pearson's coefficient = -0.398, p = 0.020) and Generalized Fractional Anisotropic (GFA) of right subgenual cingulum (Pearson's coefficient -0.457, p = 0.007) with plasma apoA-1 levels, in a multiple regression model with age and sex. The subgenual cingulum encompasses fibers from the anterior cingulate cortex and anterior thalamus. These structures are involved in PD-associated psychosis and executive cognitive decline. We demonstrated for the first time that apoA-1, as a blood marker, can predict microstructural changes in white matter regions in PD patients with undisturbed cognition and mild motor disability.