Changes of brain gray matter structure in Parkinson's disease patients with dementia

Multimodal magnetic resonance scans of patients with mild cognitive impairment

The advancement of neuroimaging technology offers a pivotal reference for the early detection of mild cognitive impairment (MCI), a significant area of focus in contemporary cognitive function research. Structural MRI scans present visual and quantitative manifestations of alterations in brain tissue, whereas functional MRI scans depict the metabolic and functional state of brain tissues from diverse perspectives. As various magnetic resonance techniques possess both strengths and constraints, this review examines the methodologies and outcomes of multimodal magnetic resonance technology in MCI diagnosis, laying the groundwork for subsequent diagnostic and therapeutic interventions for MCI.

Structural connectivity from DTI to predict mild cognitive impairment in de novo Parkinson's disease

BACKGROUND

Early detection of Parkinson's disease (PD) patients at high risk for mild cognitive impairment (MCI) can help with timely intervention. White matter structural connectivity is considered an early and sensitive indicator of neurodegenerative disease.

OBJECTIVES

To investigate whether baseline white matter structural connectivity features from diffusion tensor imaging (DTI) of de novo PD patients can help predict PD-MCI conversion at an individual level using machine learning methods.

METHODS

We included 90 de novo PD patients who underwent DTI and 3D T1-weighted imaging. Elastic net-based feature consensus ranking (ENFCR) was used with 1000 random training sets to select clinical and structural connectivity features. Linear discrimination analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN) and naïve Bayes (NB) classifiers were trained based on features selected more than 500 times. The area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN) and specificity (SPE) were used to evaluate model performance.

RESULTS

A total of 57 PD patients were classified as PD-MCI nonconverters, and 33 PD patients were classified as PD-MCI converters. The models trained with clinical data showed moderate performance (AUC range: 0.62-0.68; ACC range: 0.63-0.77; SEN range: 0.45-0.66; SPE range: 0.64-0.84). Models trained with structural connectivity (AUC range, 0.81-0.84; ACC range, 0.75-0.86; SEN range, 0.77-0.91; SPE range, 0.71-0.88) performed similar to models that were trained with both clinical and structural connectivity data (AUC range, 0.81-0.85; ACC range, 0.74-0.85; SEN range, 0.79-0.91; SPE range, 0.70-0.89).

CONCLUSIONS

Baseline white matter structural connectivity from DTI is helpful in predicting future MCI conversion in de novo PD patients.

Crosstalk between neurological, cardiovascular, and lifestyle disorders: insulin and lipoproteins in the lead role

Insulin resistance and impaired lipoprotein metabolism contribute to a plethora of metabolic and cardiovascular disorders. These alterations have been extensively linked with poor lifestyle choices, such as consumption of a high-fat diet, smoking, stress, and a redundant lifestyle. Moreover, these are also known to increase the co-morbidity of diseases like Type 2 diabetes mellitus and atherosclerosis. Under normal physiological conditions, insulin and lipoproteins exert a neuroprotective role in the central nervous system. However, the tripping of balance between the periphery and center may alter the normal functioning of the brain and lead to neurological disorders such as Alzheimer's disease, Parkinson's disease, stroke, depression, and multiple sclerosis. These neurological disorders are further characterized by certain behavioral and molecular changes that show consistent overlap with alteration in insulin and lipoprotein signaling pathways. Therefore, targeting these two mechanisms not only reveals a way to manage the co-morbidities associated with the circle of the metabolic, central nervous system, and cardiovascular disorders but also exclusively work as a disease-modifying therapy for neurological disorders. In this review, we summarize the role of insulin resistance and lipoproteins in the progression of various neurological conditions and discuss the therapeutic options currently in the clinical pipeline targeting these two mechanisms; in addition, challenges faced in designing these therapeutic approaches have also been touched upon briefly.

Morphological analysis of subcortical structures for assessment of cognitive dysfunction in Parkinson's disease using multi-atlas based segmentation

Cognitive impairment in Parkinson's Disease (PD) is the most prevalent non-motor symptom that requires analysis of anatomical associations to cognitive decline in PD. The objective of this study is to analyse the morphological variations of the subcortical structures to assess cognitive dysfunction in PD. In this study, T1 MR images of 58 Healthy Control (HC) and 135 PD subjects categorised as 91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D) subjects, based on cognitive scores are utilised. The 132 anatomical regions are segmented using spatially localized multi-atlas model and volumetric analysis is carried out. The morphological alterations through textural features are captured to differentiate among the HC and PD subjects under different cognitive domains. The volumetric differences in the segmented subcortical structures of accumbens, amygdala, caudate, putamen and thalamus are able to predict cognitive impairment in PD. The volumetric distribution of the subcortical structures in PD-MCI subjects exhibit an overlap with the HC group due to lack of spatial specificity in their atrophy levels. The 3D GLCM features extracted from the significant subcortical structures could discriminate HC, NC-PD, PD-MCI and PD-D subjects with better classification accuracies. The disease related atrophy levels of the subcortical structures captured through morphological analysis provide sensitive evaluation of cognitive impairment in PD.

Structural Covariance Network Disruption and Functional Compensation in Parkinson's Disease

Purpose: To investigate the structural covariance network disruption in Parkinson’s disease (PD), and explore the functional alterations of disrupted structural covariance network.

Methods: A cohort of 100 PD patients and 70 healthy participants underwent structural and functional magnetic resonance scanning. Independent component analysis (ICA) was applied separately to both deformation-based morphometry (DBM) maps and functional maps with the same calculating parameters (both decomposed into 20 independent components (ICs) and computed 20 times the Infomax algorithm in ICASSO). Disrupted structural covariance network in PD patients was identified, and then, we performed goodness of fit analysis to obtain the functional network that showed the highest spatial overlap with it. We investigated the relationship between structural covariance network and functional network alterations. Finally, to further understand the structural and functional alterations over time, we performed a longitudinal subgroup analysis (51 patients were followed up for 2 years) with the same procedures.

Results: In a cross-sectional analysis, PD patients showed decreased structural covariance between anterior and posterior cingulate subnetworks. The functional components showed best overlap with anterior and posterior cingulate structural subnetworks were selected as anterior and posterior cingulate functional subnetworks. The functional connectivity between them was significantly increased [assessed by Functional Network Connectivity (FNC) toolbox]; and the increased functional connectivity was negatively correlated with cingulate structural covariance network integrity. Longitudinal subgroup analysis showed cingulate structural covariance network disruption was worse at follow-up, while the functional connectivity between anterior and posterior cingulate network was increased at baseline and decreased at follow-up.

Conclusion: This study indicated that the cingulate structural covariance network displayed a high susceptibility in PD patients. This study indicated that the cingulate structural covariance network displayed a high susceptibility in PD patients. Considering that disrupted structural covariance network coexisted with enhanced/remained functional activity during disease development, enhanced functional activity underlying the disrupted cingulate structural covariance network might represent a temporal compensation for maintaining clinical performance.

Assessing gray matter volume in patients with idiopathic rapid eye movement sleep behavior disorder

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is often a precursor to neurodegenerative disease. However, voxel-based morphological studies evaluating structural abnormalities in the brains of iRBD patients are relatively rare. This study aimed to explore cerebral structural alterations using magnetic resonance imaging and to determine their association with clinical parameters in iRBD patients. Brain structural T1-weighted MRI scans were acquired from 19 polysomnogram-confirmed iRBD patients (male:female 16:3; mean age 66.6 ± 7.0 years) and 20 age-matched healthy controls (male:female 5:15; mean age 63.7 ± 5.9 years). Gray matter volume (GMV) data were analyzed based on Statistical Parametric Mapping 8, using a voxel-based morphometry method and two-sample t-test and multiple regression analysis. Compared with controls, iRBD patients had increased GMV in the middle temporal gyrus and cerebellar posterior lobe, but decreased GMV in the Rolandic operculum, postcentral gyrus, insular lobe, cingulate gyrus, precuneus, rectus gyrus, and superior frontal gyrus. iRBD duration was positively correlated with GMV in the precuneus, cuneus, superior parietal gyrus, postcentral gyrus, posterior cingulate gyrus, hippocampus, lingual gyrus, middle occipital gyrus, middle temporal gyrus, and cerebellum posterior lobe. Furthermore, phasic chin electromyographic activity was positively correlated with GMV in the hippocampus, precuneus, fusiform gyrus, precentral gyrus, superior frontal gyrus, cuneus, inferior parietal lobule, angular gyrus, superior parietal gyrus, paracentral lobule, and cerebellar posterior lobe. There were no significant negative correlations of brain GMV with disease duration or electromyographic activity in iRBD patients. These findings expand the spectrum of known gray matter modifications in iRBD patients and provide evidence of a correlation between brain dysfunction and clinical manifestations in such patients. The protocol was approved by the Ethics Committee of Huashan Hospital (approval No. KY2013-336) on January 6, 2014. This trial was registered in the ISRCTN registry (ISRCTN18238599).

Biomarkers for Parkinson's Disease: Recent Advancement

As a multi-factorial degenerative disease, Parkinson's disease (PD) leads to tremor, gait rigidity, and hypokinesia, thus hampering normal living. As this disease is usually detected in the later stages when neurons have degenerated completely, cure is on hold, ultimately leading to death due to the lack of early diagnostic techniques. Thus, biomarkers are required to detect the disease in the early stages when prevention is possible. Various biomarkers providing early diagnosis of the disease include those of imaging, cerebrospinal fluid, oxidative stress, neuroprotection, and inflammation. Also, biomarkers, alone or in combination, are used in the diagnosis and evolution of PD. This review encompasses various biomarkers available for PD and discusses recent advances in their development.

A seed-based cross-modal comparison of brain connectivity measures

Human neuroimaging methods have provided a number of means by which the connectivity structure of the human brain can be inferred. For instance, correlations in blood-oxygen-level-dependent (BOLD) signal time series are commonly used to make inferences about "functional connectivity." Correlations across samples in structural morphometric measures, such as voxel-based morphometry (VBM) or cortical thickness (CT), have also been used to estimate connectivity, putatively through mutually trophic effects on connected brain areas. In this study, we have compared seed-based connectivity estimates obtained from four common correlational approaches: resting-state functional connectivity (RS-fMRI), meta-analytic connectivity modeling (MACM), VBM correlations, and CT correlations. We found that the two functional approaches (RS-fMRI and MACM) had the best agreement. While the two structural approaches (CT and VBM) had better-than-random convergence, they were no more similar to each other than to the functional approaches. The degree of correspondence between modalities varied considerably across seed regions, and also depended on the threshold applied to the connectivity distribution. These results demonstrate some degrees of similarity between connectivity inferred from structural and functional covariances, particularly for the most robust functionally connected regions (e.g., the default mode network). However, they also caution that these measures likely capture very different aspects of brain structure and function.

Synergistic stress exacerbation in hippocampal neurons: Evidence favoring the dual-hit hypothesis of neurodegeneration

The dual-hit hypothesis of neurodegeneration states that severe stress sensitizes vulnerable cells to subsequent challenges so that the two hits are synergistic in their toxic effects. Although the hippocampus is vulnerable to a number of neurodegenerative disorders, there are no models of synergistic cell death in hippocampal neurons in response to combined proteotoxic and oxidative stressors, the two major characteristics of these diseases. Therefore, a relatively high-throughput dual-hit model of stress synergy was developed in primary hippocampal neurons. In order to increase the rigor of the study and strengthen the interpretations, three independent, unbiased viability assays were employed at multiple timepoints. Stress synergy was elicited when hippocampal neurons were treated with the proteasome inhibitor MG132 followed by exposure to the oxidative toxicant paraquat, but only after 48 h. MG132 and paraquat only elicited additive effects 24 h after the final hit and even loss of heat shock protein 70 activity and glutathione did not promote stress synergy at this early timepoint. Dual hits of MG132 elicited modest glutathione loss and slightly synergistic toxic effects 48 h after the second hit, but only at some concentrations and only according to two viability assays (metabolic fitness and cytoskeletal integrity). The thiol N-acetyl cysteine protected hippocampal neurons against dual MG132/MG132 hits but not dual MG132/paraquat hits. These findings support the view that proteotoxic and oxidative stress propel and propagate each other in hippocampal neurons, leading to synergistically toxic effects, but not as the default response and only after a delay. The neuronal stress synergy observed here lies in contrast to astrocytic responses to dual hits, because astrocytes that survive severe proteotoxic stress resist additional cell loss following second hits. In conclusion, a new model of hippocampal vulnerability was developed for the testing of therapies, because neuroprotective treatments that are effective against severe, synergistic stress are more likely to succeed in the clinic. © 2016 Wiley Periodicals, Inc.

Neuroanatomical changes in Parkinson's disease in relation to cognition: An update

The pathophysiological changes underlying impairment of cognition in Parkinson's disease (PD) are complex and not fully understood till date. Hence, understanding the structural changes responsible for cognitive decline in PD is essential for early diagnosis and to offer effective treatment. In this review, we discuss the neuroanatomical changes in major brain structures responsible for cognition in PD. We have included the key findings of various studies to provide up-to-date information for better understanding of pathophysiology of PD, which will help researchers and clinicians in planning and developing new treatment methods for the benefit of PD patients.

Central pathways causing fatigue in neuro-inflammatory and autoimmune illnesses

BACKGROUND

The genesis of severe fatigue and disability in people following acute pathogen invasion involves the activation of Toll-like receptors followed by the upregulation of proinflammatory cytokines and the activation of microglia and astrocytes. Many patients suffering from neuroinflammatory and autoimmune diseases, such as multiple sclerosis, Parkinson's disease and systemic lupus erythematosus, also commonly suffer from severe disabling fatigue. Such patients also present with chronic peripheral immune activation and systemic inflammation in the guise of elevated proinflammtory cytokines, oxidative stress and activated Toll-like receptors. This is also true of many patients presenting with severe, apparently idiopathic, fatigue accompanied by profound levels of physical and cognitive disability often afforded the non-specific diagnosis of chronic fatigue syndrome.

DISCUSSION

Multiple lines of evidence demonstrate a positive association between the degree of peripheral immune activation, inflammation and oxidative stress, gray matter atrophy, glucose hypometabolism and cerebral hypoperfusion in illness, such as multiple sclerosis, Parkinson's disease and chronic fatigue syndrome. Most, if not all, of these abnormalities can be explained by a reduction in the numbers and function of astrocytes secondary to peripheral immune activation and inflammation. This is also true of the widespread mitochondrial dysfunction seen in otherwise normal tissue in neuroinflammatory, neurodegenerative and autoimmune diseases and in many patients with disabling, apparently idiopathic, fatigue. Given the strong association between peripheral immune activation and neuroinflammation with the genesis of fatigue the latter group of patients should be examined using FLAIR magnetic resonance imaging (MRI) and tested for the presence of peripheral immune activation.

SUMMARY

It is concluded that peripheral inflammation and immune activation, together with the subsequent activation of glial cells and mitochondrial damage, likely account for the severe levels of intractable fatigue and disability seen in many patients with neuroimmune and autoimmune diseases.This would also appear to be the case for many patients afforded a diagnosis of Chronic Fatigue Syndrome.