Microstructural network alterations of olfactory dysfunction in newly diagnosed Parkinson's disease

Global Alterations of Whole Brain Structural Connectome in Parkinson's Disease: A Meta-analysis

Recent graph-theoretical studies of Parkinson's disease (PD) have examined alterations in the global properties of the brain structural connectome; however, reported alterations are not consistent. The present study aimed to identify the most robust global metric alterations in PD via a meta-analysis. A comprehensive literature search was conducted for all available diffusion MRI structural connectome studies that compared global graph metrics between PD patients and healthy controls (HC). Hedges' g effect sizes were calculated for each study and then pooled using a random-effects model in Comprehensive Meta-Analysis software, and the effects of potential moderator variables were tested. A total of 22 studies met the inclusion criteria for review. Of these, 16 studies reporting 10 global graph metrics (916 PD patients; 560 HC) were included in the meta-analysis. In the structural connectome of PD patients compared with HC, we found a significant decrease in clustering coefficient (g = -0.357, P = 0.005) and global efficiency (g = -0.359, P < 0.001), and a significant increase in characteristic path length (g = 0.250, P = 0.006). Dopaminergic medication, sex and age of patients were potential moderators of global brain network changes in PD. These findings provide evidence of decreased global segregation and integration of the structural connectome in PD, indicating a shift from a balanced small-world network to 'weaker small-worldization', which may provide useful markers of the pathophysiological mechanisms underlying PD.

Cerebellar Microstructural Abnormalities in Parkinson's Disease: a Systematic Review of Diffusion Tensor Imaging Studies

Diffusion tensor imaging (DTI) is now having a strong momentum in research to evaluate the neural fibers of the CNS. This technique can study white matter (WM) microstructure in neurodegenerative disorders, including Parkinson's disease (PD). Previous neuroimaging studies have suggested cerebellar involvement in the pathogenesis of PD, and these cerebellum alterations can correlate with PD symptoms and stages. Using the PRISMA 2020 framework, PubMed and EMBASE were searched to retrieve relevant articles. Our search revealed 472 articles. After screening titles and abstracts, and full-text review, and implementing the inclusion criteria, 68 papers were selected for synthesis. Reviewing the selected studies revealed that the patterns of reduction in cerebellum WM integrity, assessed by fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity measures can differ symptoms and stages of PD. Cerebellar diffusion tensor imaging (DTI) changes in PD patients with "postural instability and gait difficulty" are significantly different from "tremor dominant" PD patients. Freezing of the gate is strongly related to cerebellar involvement depicted by DTI. The "reduced cognition," "visual disturbances," "sleep disorders," "depression," and "olfactory dysfunction" are not related to cerebellum microstructural changes on DTI, while "impulsive-compulsive behavior" can be linked to cerebellar WM alteration. Finally, higher PD stages and longer disease duration are associated with cerebellum white matter alteration depicted by DTI. Depiction of cerebellar white matter involvement in PD is feasible by DTI. There is an association with disease duration and severity and several clinical presentations with DTI findings. This clinical-imaging association may eventually improve disease management.

Alteration in Asymmetry of White Matter Network of Parkinson’s Disease

Parkinson’s disease (PD) is manifest clinically by an asymmetrical presentation of motor dysfunction. A large number of previous neuroimaging research studies have stated the alteration in the hemispheric asymmetry of morphological features in PD disease. Diffusion Magnetic Resonance Imaging (MRI), which is noninvasive, has been widely used to quantify the white matter network in the human brain of both healthy subjects and patients. Besides, graph theory analysis is widely used to quantify the topological architecture of the human brain network. Lately, researchers have discovered that the topological architecture of the white matter network significantly differs in PD compared with healthy controls (HC). Nevertheless, the asymmetry of the topological architecture of the white matter network for PD patients remains unclear. To clarify this, the diffusion-weighted images and tractography technique were used to reconstruct the hemispherical white matter networks for 22 bilateral PD patients and 18 HC subjects. Network-based statistical analysis and graph theory analysis approaches were employed to estimate the asymmetry at both the connectivity level and the hemispheric topological level for PD patients. We found that the PD group showed atypically right-higher-than-left asymmetry in hemispheric brain global and local efficiencies. The detected right-higher-than-left asymmetry was driven by the atypically topological changes in the left hemispheric brain in the PD group. Findings from these studies might provide new insights into the asymmetric features of hemispheric disconnectivity and emphasize that the topological asymmetry of the hemispheric brain could be used as a biomarker to identify PD individuals.

Disrupted morphological grey matter networks in early-stage Parkinson's disease

While previous structural-covariance studies have an advanced understanding of brain alterations in Parkinson's disease (PD), brain–behavior relationships have not been examined at the individual level. This study investigated the topological organization of grey matter (GM) networks, their relation to disease severity, and their potential imaging diagnostic value in PD. Fifty-four early-stage PD patients and 54 healthy controls (HC) underwent structural T1-weighted magnetic resonance imaging. GM networks were constructed by estimating interregional similarity in the distributions of regional GM volume using the Kullback–Leibler divergence measure. Results were analyzed using graph theory and network-based statistics (NBS), and the relationship to disease severity was assessed. Exploratory support vector machine analyses were conducted to discriminate PD patients from HC and different motor subtypes. Compared with HC, GM networks in PD showed a higher clustering coefficient (P = 0.014) and local efficiency (P = 0.014). Locally, nodal centralities in PD were lower in postcentral gyrus and temporal-occipital regions, and higher in right superior frontal gyrus and left putamen. NBS analysis revealed decreased morphological connections in the sensorimotor and default mode networks and increased connections in the salience and frontoparietal networks in PD. Connection matrices and graph-based metrics allowed single-subject classification of PD and HC with significant accuracy of 73.1 and 72.7%, respectively, while graph-based metrics allowed single-subject classification of tremor-dominant and akinetic–rigid motor subtypes with significant accuracy of 67.0%. The topological organization of GM networks was disrupted in early-stage PD in a way that suggests greater segregation of information processing. There is potential for application to early imaging diagnosis.

Global and Regional Changes in Perivascular Space in Idiopathic and Familial Parkinson's Disease

BACKGROUND

The glymphatic system, including the perivascular space (PVS), plays a critical role in brain homeostasis. Although mounting evidence from Alzheimer's disease has supported the potential role of PVS in neurodegenerative disorders, its contribution in Parkinson's disease (PD) has not been fully elucidated. Although idiopathic (IPD) and familial PD (FPD) share similar pathophysiology in terms of protein aggregation, the differential impact of PVS on PD subtypes remains unknown. Our objective was to examine the differences in PVS volume fraction in IPD and FPD compared to healthy controls (HCs) and nonmanifest carriers (NMCs).

METHODS

A total of 470 individuals were analyzed from the Parkinson's Progression Markers Initiative database, including (1) IPD (n = 179), (2) FPD (LRRK2 [leucine-rich repeat kinase 2], glucocerebrosidase, or α-synuclein) (n = 67), (3) NMC (n = 101), and (4) HCs (n = 84). Total PVS volume fraction (%) was compared using parcellation and quantitation within greater white matter volume at global and regional levels in all cortical and subcortical white matter.

RESULTS

There was a significant increase in global and regional PVS volume fraction in PD versus non-PD, particularly in FPD versus NMC and LRRK2 FPD versus NMC. Regionally, FPD and NMC differed in the medial orbitofrontal region, as did LRRK2 FPD versus NMC. Non-PD and PD differed in the medial orbitofrontal region and the banks of the superior temporal regions. IPD and FPD differed in the cuneus and lateral occipital regions.

CONCLUSIONS

Our findings support the role of PVS in PD and highlight a potentially significant contribution of PVS to the pathophysiology of FPD, particularly LRRK2. © 2021 International Parkinson and Movement Disorder Society.

Diffusion Tensor Imaging in Parkinson's Disease and Parkinsonian Syndrome: A Systematic Review

Diffusion tensor imaging (DTI) allows measuring fractional anisotropy and similar microstructural indices of the brain white matter. Lower than normal fractional anisotropy as well as higher than normal diffusivity is associated with loss of microstructural integrity and neurodegeneration. Previous DTI studies in Parkinson's disease (PD) have demonstrated abnormal fractional anisotropy in multiple white matter regions, particularly in the dopaminergic nuclei and dopaminergic pathways. However, DTI is not considered a diagnostic marker for the earliest Parkinson's disease since anisotropic alterations present a temporally divergent pattern during the earliest Parkinson's course. This article reviews a majority of clinically employed DTI studies in PD, and it aims to prove the utilities of DTI as a marker of diagnosing PD, correlating clinical symptomatology, tracking disease progression, and treatment effects. To address the challenge of DTI being a diagnostic marker for early PD, this article also provides a comparison of the results from a longitudinal, early stage, multicenter clinical cohort of Parkinson's research with previous publications. This review provides evidences of DTI as a promising marker for monitoring PD progression and classifying atypical PD types, and it also interprets the possible pathophysiologic processes under the complex pattern of fractional anisotropic changes in the first few years of PD. Recent technical advantages, limitations, and further research strategies of clinical DTI in PD are additionally discussed.

Clinically relevant connectivity features define three subtypes of Parkinson's disease patients

Parkinson's disease (PD) is characterized by complex clinical symptoms, including classic motor and nonmotor disturbances. Patients with PD vary in clinical manifestations and prognosis, which point to the existence of subtypes. This study aimed to find the fiber connectivity correlations with several crucial clinical symptoms and identify PD subtypes using unsupervised clustering analysis. One hundred and thirty-four PD patients and 77 normal controls were enrolled. Canonical correlation analysis (CCA) was performed to define the clinically relevant connectivity features, which were then used in the hierarchical clustering analysis to identify the distinct subtypes of PD patients. Multimodal neuroimaging analyses were further used to explore the neurophysiological basis of these subtypes. The methodology was validated in an independent data set. CCA revealed two significant clinically relevant patterns (motor-related pattern and depression-related pattern; r = .94, p < .001 and r = .926, p = .001, respectively) among PD patients, and hierarchical clustering analysis identified three neurophysiological subtypes ("mild" subtype, "severe depression-dominant" subtype and "severe motor-dominant" subtype). Multimodal neuroimaging analyses suggested that the patients in the "severe depression-dominant" subtype exhibited widespread disruptions both in function and structure, while the other two subtypes exhibited relatively mild abnormalities in brain function. In the independent validation, three similar subtypes were identified. In conclusion, we revealed heterogeneous subtypes of PD patients according to their distinct clinically relevant connectivity features. Importantly, depression symptoms have a considerable impact on brain damage in patients with PD.

Olfactory Dysfunction in Familial and Sporadic Parkinson's Disease

This minireview discusses our current understanding of the olfactory dysfunction that is frequently observed in sporadic and familial forms of Parkinson's disease and parkinsonian syndromes. We review the salient characteristics of olfactory dysfunction in these conditions, discussing its prevalence and characteristics, how neuronal processes and circuits are altered in Parkinson's disease, and what is assessed by clinically used measures of olfactory function. We highlight how studies of monogenic Parkinson's disease and investigations in ethnically diverse populations have contributed to understanding the mechanisms underlying olfactory dysfunction. Furthermore, we discuss how imaging and system-level approaches have been used to understand the pathogenesis of olfactory dysfunction. We discuss the challenging, remaining gaps in understanding the basis of olfactory dysfunction in neurodegeneration. We propose that insights could be obtained by following longitudinal cohorts with familial forms of Parkinson's disease using a combination of approaches: a multifaceted longitudinal assessment of olfactory function during disease progression is essential to identify not only how dysfunction arises, but also to address its relationship to motor and non-motor Parkinson's disease symptoms. An assessment of cohorts having monogenic forms of Parkinson's disease, available within the Genetic Epidemiology of Parkinson's Disease (GEoPD), as well as other international consortia, will have heuristic value in addressing the complexity of olfactory dysfunction in the context of the neurodegenerative process. This will inform our understanding of Parkinson's disease as a multisystem disorder and facilitate the more effective use of olfactory dysfunction assessment in identifying prodromal Parkinson's disease and understanding disease progression.

Clinical Features of Parkinson's Disease: The Evolution of Critical Symptoms

Parkinson’s disease (PD) is a multi-attribute neurodegenerative disorder combining motor and nonmotor symptoms without well-defined diagnostic clinical markers. The presence of primary motor features (bradykinesia, rest tremor, rigidity and loss of postural reflexes) are the most characteristic signs of PD that are also utilized to identify patients in current clinical practice. The successful implementation of levodopa treatment revealed that nonmotor features are the main contributors of patient disability in PD, and their occurrence might be earlier than motor symptoms during disease progression. Targeted detection of prodromal PD symptoms can open up new possibilities in the identification of PD patients and provide potential patient populations for developing novel neuroprotective therapies. In this review, the evolution of critical features in PD diagnosis is described with special attention to nonmotor symptoms and their possible detection.

Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review

Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest–based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.

Perturbation of in vivo Neural Activity Following α-Synuclein Seeding in the Olfactory Bulb

BACKGROUND

Parkinson's disease (PD) neuropathology is characterized by intraneuronal protein aggregates composed of misfolded α-Synuclein (α-Syn), as well as degeneration of substantia nigra dopamine neurons. Deficits in olfactory perception and aggregation of α-Syn in the olfactory bulb (OB) are observed during early stages of PD, and have been associated with the PD prodrome, before onset of the classic motor deficits. α-Syn fibrils injected into the OB of mice cause progressive propagation of α-Syn pathology throughout the olfactory system and are coupled to olfactory perceptual deficits.

OBJECTIVE

We hypothesized that accumulation of pathogenic α-Syn in the OB impairs neural activity in the olfactory system.

METHODS

To address this, we monitored spontaneous and odor-evoked local field potential dynamics in awake wild type mice simultaneously in the OB and piriform cortex (PCX) one, two, and three months following injection of pathogenic preformed α-Syn fibrils in the OB.

RESULTS

We detected α-Syn pathology in both the OB and PCX. We also observed that α-Syn fibril injections influenced odor-evoked activity in the OB. In particular, α-Syn fibril-injected mice displayed aberrantly high odor-evoked power in the beta spectral range. A similar change in activity was not detected in the PCX, despite high levels of α-Syn pathology.

CONCLUSION

Together, this work provides evidence that synucleinopathy impacts in vivo neural activity in the olfactory system at the network-level.

Contribution of the GABAergic System to Non-Motor Manifestations in Premotor and Early Stages of Parkinson's Disease

Non-motor symptoms are common in Parkinson’s disease (PD) and they represent a major source of disease burden. Several non-motor manifestations, such as rapid eye movement sleep behavior disorder, olfactory loss, gastrointestinal abnormalities, visual alterations, cognitive and mood disorders, are known to precede the onset of motor signs. Nonetheless, the mechanisms mediating these alterations are poorly understood and probably involve several neurotransmitter systems. The dysregulation of GABAergic system has received little attention in PD, although the spectrum of non-motor symptoms might be linked to this pathway. This Mini Review aims to provide up-to-date information about the involvement of the GABAergic system for explaining non-motor manifestations in early stages of PD. Therefore, special attention is paid to the clinical data derived from patients with isolated REM sleep behavior disorder or drug-naïve patients with PD, as they represent prodromal and early stages of the disease, respectively. This, in combination with animal studies, might help us to understand how the disturbance of the GABAergic system is related to non-motor manifestations of PD.

Open questions on the nature of Parkinson's disease: from triggers to spreading pathology

Parkinson's disease (PD) is a movement disorder identified more than 200 years ago; today it is defined by specific motor symptoms that together receive the name of parkinsonism. PD diagnosis is reached with the full parkinsonian syndrome, but in recent years, a series of non-motor symptoms have arisen as intrinsic components of PD. These non-motor symptoms are variable, creating a widely heterogenous disease presentation. Some non-motor symptoms appear in late disease stages and are explained as the natural progression of PD pathology into other brain centres, including the frontal cortex. Other symptoms can appear a decade or earlier preceding PD diagnosis, particularly hyposmia (loss of smell) and constipation. These early symptoms and the accompanying protein pathology have stimulated a lively conversation about the origin and nature of PD and other related conditions: some authors propose that PD starts in the olfactory mucosa and the gut due to direct exposure to toxins or pathogens. This pathology then travels by anatomically interconnected networks to the midbrain to cause motor symptoms and the cortex to cause late complications. Other models propose that PD develops in multiple independent foci that do not require pathology spread. We will review these hypotheses in the context of recent developments regarding the spread of amyloids and propose a mixed model where a multifocal origin explains the variable presentation of PD, while cell-to-cell spread explains stereotypical disease progression.