Impaired white matter microstructure associated with severe depressive symptoms in patients with PD

"Advanced" Parkinson's disease: A review

There is no consensus driven definition of "advanced" Parkinson's disease (APD) currently. APD has been described in terms of emergence of specific clinical features and clinical milestones of the disease e.g., motor fluctuations, time to increasing falls, emergence of cognitive decline, etc. The pathological burden of disease has been used to characterize various stages of the disease. Imaging markers have been associated with various motor and nonmotor symptoms of advancing disease. In this review, we present an overview of clinical, pathologic, and imaging markers of APD. We also propose a model of disease definition involving longitudinal assessments of these markers as well as quality of life metrics to better understand and predict disease progression in those with Parkinson's disease.

Alterations in cortical volume and complexity in Parkinson's disease with depression

AIMS

The aim of this study is to investigate differences in gray matter volume and cortical complexity between Parkinson's disease with depression (PDD) patients and Parkinson's disease without depression (PDND) patients.

METHODS

A total of 41 PDND patients, 36 PDD patients, and 38 healthy controls (HC) were recruited and analyzed by Voxel-based morphometry (VBM) and surface-based morphometry (SBM). Differences in gray matter volume and cortical complexity were compared using the one-way analysis of variance (ANOVA) and correlated with the Hamilton Depression Scale-17 (HAMD-17) scores.

RESULTS

PDD patients exhibited significant cortical atrophy in various regions, including bilateral medial parietal-occipital-temporal lobes, right dorsolateral temporal lobes, bilateral parahippocampal gyrus, and bilateral hippocampus, compared to HC and PDND groups. A negative correlation between the GMV of left precuneus and HAMD-17 scores in the PDD group tended to be significant (r = -0.318, p = 0.059). Decreased gyrification index was observed in the bilateral insular and dorsolateral temporal cortex. However, there were no significant differences found in fractal dimension and sulcal depth.

CONCLUSION

Our research shows extensive cortical structural changes in the insular cortex, parietal-occipital-temporal lobes, and hippocampal regions in PDD. This provides a morphological perspective for understanding the pathophysiological mechanism underlying depression in Parkinson's disease.

Disrupted topologic efficiency of brain functional connectome in de novo Parkinson's disease with depression

Growing evidence supports that depression in Parkinson's disease (PD) depends on disruptions in specific neural networks rather than regional dysfunction. According to the resting-state functional magnetic resonance imaging data, the study attempted to decipher the alterations in the topological properties of brain networks in de novo depression in PD (DPD). The study also explored the neural network basis for depressive symptoms in PD. We recruited 20 DPD, 37 non-depressed PD and 41 healthy controls (HC). The Graph theory and network-based statistical methods helped analyse the topological properties of brain functional networks and anomalous subnetworks across these groups. The relationship between altered properties and depression severity was also investigated. DPD revealed significantly reduced nodal efficiency in the left superior temporal gyrus. Additionally, DPD decreased five hubs, primarily located in the temporal-occipital cortex, and increased seven hubs, mainly distributed in the limbic cortico-basal ganglia circuit. The betweenness centrality of the left Medio Ventral Occipital Cortex was positively associated with depressive scores in DPD. In contrast to HC, DPD had a multi-connected subnetwork with significantly lower connectivity, primarily distributed in the visual, somatomotor, dorsal attention and default networks. Regional topological disruptions in the temporal-occipital region are critical in the DPD neurological mechanism. It might suggest a potential network biomarker among newly diagnosed DPD patients.

Cortical gyrification pattern of depression in Parkinson's disease: a neuroimaging marker for disease severity?

Background

Although the study of the neuroanatomical correlates of depression in Parkinson's Disease (PD) is gaining increasing interest, up to now the cortical gyrification pattern of PD-related depression has not been reported. This study was conducted to investigate the local gyrification index (LGI) in PD patients with depression, and its associations with the severity of depression.

Methods

LGI values, as measured using FreeSurfer software, were compared between 59 depressed PD (dPD), 27 non-depressed PD (ndPD) patients and 43 healthy controls. The values were also compared between ndPD and mild-depressed PD (mi-dPD), moderate-depressed PD (mo-dPD) and severe-depressed PD (se-dPD) patients as sub-group analyses. Furthermore, we evaluated the correlation between LGI values and depressive symptom scores within dPD group.

Results

Compared to ndPD, the dPD patients exhibited decreased LGI in the left parietal, the right superior-frontal, posterior cingulate and paracentral regions, and the LGI values within these areas negatively correlated with the severity of depression. Specially, reduced gyrification was observed in mo-dPD and involving a larger region in se-dPD, but not in mi-dPD group.

Conclusion

The present study demonstrated that cortical gyrification is decreased within specific brain regions among PD patients with versus without depression, and those changes were associated with the severity of depression. Our findings suggested that cortical gyrification might be a potential neuroimaging marker for the severity of depression in patients with PD.

Neural functional network of early Parkinson's disease based on independent component analysis

This work explored neural network changes in early Parkinson's disease: Resting-state functional magnetic resonance imaging was used to investigate functional alterations in different stages of Parkinson's disease (PD). Ninety-five PD patients (50 early/mild and 45 early/moderate) and 37 healthy controls (HCs) were included. Independent component analysis revealed significant differences in intra-network connectivity, specifically in the default mode network (DMN) and right frontoparietal network (RFPN), in both PD groups compared to HCs. Inter-network connectivity analysis showed reduced connectivity between the executive control network (ECN) and DMN, as well as ECN-left frontoparietal network (LFPN), in early/mild PD. Early/moderate PD exhibited decreased connectivity in ECN-LFPN, ECN-RFPN, ECN-DMN, and DMN-auditory network, along with increased connectivity in LFPN-cerebellar network. Correlations were found between ECN-DMN and ECN-LFPN connections with UPDRS-III scores in early/mild PD. These findings suggest that PD progression involves dysfunction in multiple intra- and inter-networks, particularly implicating the ECN, and a wider range of abnormal functional networks may mark the progression of the disease.

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.

Cingulum and Uncinate Fasciculus Microstructural Abnormalities in Parkinson's Disease: A Systematic Review of Diffusion Tensor Imaging Studies

Diffusion tensor imaging (DTI) is gaining traction in neuroscience research as a tool for evaluating neural fibers. The technique can be used to assess white matter (WM) microstructure in neurodegenerative disorders, including Parkinson disease (PD). There is evidence that the uncinate fasciculus and the cingulum bundle are involved in the pathogenesis of PD. These fasciculus and bundle alterations correlate with the symptoms and stages of PD. PRISMA 2022 was used to search PubMed and Scopus for relevant articles. Our search revealed 759 articles. Following screening of titles and abstracts, a full-text review, and implementing the inclusion criteria, 62 papers were selected for synthesis. According to the review of selected studies, WM integrity in the uncinate fasciculus and cingulum bundles can vary according to symptoms and stages of Parkinson disease. This article provides structural insight into the heterogeneous PD subtypes according to their cingulate bundle and uncinate fasciculus changes. It also examines if there is any correlation between these brain structures' structural changes with cognitive impairment or depression scales like Geriatric Depression Scale-Short (GDS). The results showed significantly lower fractional anisotropy values in the cingulum bundle compared to healthy controls as well as significant correlations between FA and GDS scores for both left and right uncinate fasciculus regions suggesting that structural damage from disease progression may be linked to cognitive impairments seen in advanced PD patients. This review help in developing more targeted treatments for different types of Parkinson's disease, as well as providing a better understanding of how cognitive impairments may be related to these structural changes. Additionally, using DTI scans can provide clinicians with valuable information about white matter tracts which is useful for diagnosing and monitoring disease progression over time.

Pathomechanisms of depression in progressive supranuclear palsy

Depression is one of the most frequent neuropsychiatric symptoms in progressive supranuclear palsy (PSP), a four-repeat tauopathy and most common atypical parkinsonian disorder, but its pathophysiology and pathogenesis are poorly understood. Pubmed/Medline was systematically analyzed until January 2023, with focus on the prevalence, major clinical features, neuroimaging findings and treatment options of depression in PSP. The average prevalence of depression in PSP is around 50%; it does usually not correlate with most other clinical parameters. Depression is associated with multi-regional patterns of morphometric gray matter variations, e.g., reduced thickness of temporo-parieto-occipital cortices, and altered functional orbitofrontal and medial frontal circuits with disturbances of mood-related brain networks. Unfortunately, no specific neuropathological data about depression in PSP are available. Antidepressive and electroconvulsive therapies are effective in improving symptoms; the efficacy of transcranial stimulation needs further confirmation. Depression in PSP is a common symptom, related to multi-regional patterns of cerebral disturbances and complex pathogenic mechanisms that deserve further elucidation as a basis for adequate treatment to improve the quality of life in this fatal disease.

Pathomechanisms of depression in multiple system atrophy

Multiple system atrophy (MSA) is a rapidly progressing neurodegenerative disorder of uncertain etiology that is characterized by various combinations of Parkinsonism, autonomic, cerebellar and motor dysfunctions, with poor prognosis. Little is known about modifiable factors, such as depression, that has negative effects on quality of life in MSA. Depression, with an estimated prevalence of about 43%, is among the most common neuropsychiatric disorders in MSA similar to other atypical Parkinsonian disorders, the frequency of which is associated with increased disease progression, disease severity and autonomic dysfunctions. Depression in MSA, like in Parkinson disease, has been related to a variety of pathogenic mechanisms associated with the underlying neurodegenerative process, such as involvement of serotonergic neuron groups in the brainstem, prefrontal cortical dysfunctions, and altered functional fronto-temporal-thalamic connectivities with disturbances of mood related and other essential resting-state brain networks. The pathophysiology and pathogenesis of depression in MSA, as in other degenerative movement disorders, are complex and deserve further elucidation as a basis for adequate treatment to improve the quality of life in this fatal disease.

Exploring the relationship between brain white matter change and higher degree of invisible hand tremor with computer technology

BACKGROUND: At present, the clinical diagnosis of white matter change (WMC) patients depends on cranial magnetic resonance imaging (MRI) technology. This diagnostic method is costly and does not allow for large-scale screening, leading to delays in the patient’s condition due to inability to receive timely diagnosis. OBJECTIVE: To evaluate whether the burden of WMC is associated with the degree of invisible hand tremor in humans. METHODS: Previous studies have shown that tremor is associated with WMC, however, tremor does not always have imaging of WMC. Therefore, to confirm that the appearance of WMC causes tremor, which are sometimes invisible to the naked eye, we achieved an optical-based computer-aided diagnostic device by detecting the invisible hand tremor, and we proposed a calculation method of WMC volume by using the characteristics of MRI images. RESULTS: Statistical analysis results further clarified the relationship between WMC and tremor, and our devices are validated for the detection of tremors with WMC. CONCLUSIONS: The burden of WMC volume is positive factor for degree of invisible hand tremor in the participants without visible hand tremor. Detection technology provides a more convenient and low-cost evaluating method before MRI for tremor diseases.

Identifying Depression in Parkinson's Disease by Using Combined Diffusion Tensor Imaging and Support Vector Machine

Objective

To investigate white matter microstructural alterations in Parkinson's disease (PD) patients with depression using the whole-brain diffusion tensor imaging (DTI) method and to explore the DTI–based machine learning model in identifying depressed PD (dPD).

Methods

The DTI data were collected from 37 patients with dPD and 35 patients with non-depressed PD (ndPD), and 25 healthy control (HC) subjects were collected as the reference. An atlas-based analysis method was used to compare fractional anisotropy (FA) and mean diffusivity (MD) among the three groups. A support vector machine (SVM) was trained to examine the probability of discriminating between dPD and ndPD.

Results

As compared with ndPD, dPD group exhibited significantly decreased FA in the bilateral corticospinal tract, right cingulum (cingulate gyrus), left cingulum hippocampus, bilateral inferior longitudinal fasciculus, and bilateral superior longitudinal fasciculus, and increased MD in the right cingulum (cingulate gyrus) and left superior longitudinal fasciculus-temporal part. For discriminating between dPD and ndPD, the SVM model with DTI features exhibited an accuracy of 0.70 in the training set [area under the receiver operating characteristic curve (ROC) was 0.78] and an accuracy of 0.73 in the test set (area under the ROC was 0.71).

Conclusion

Depression in PD is associated with white matter microstructural alterations. The SVM machine learning model based on DTI parameters could be valuable for the individualized diagnosis of dPD.

Altered regional brain white matter in dry eye patients: a brain imaging study

This study aimed to investigate the regional changes of brain white matter (WM) in DE patients using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). A total of 25 dry eye patients (PAT) and 25 healthy controls (HC) were recruited. All subjects underwent DTI and NODDI, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), isotropic volume fraction (FISO), intra-cellular volume fraction (FICVF), and orientation dispersion index (ODI) were obtained respectively. Then complete Hospital Anxiety and Depression Scale (HADS), anxiety score (AS) or depression scores (DS) were obtained. Receiver operating characteristic (ROC) curve analysis was used to evaluate the reliability of DTI and NODDI in distinguishing the two groups. DTI revealed that PAT had lower FA in both the left superior longitudinal fasciculus (LSLF) and the corpus callosum (CC), and higher MD in the LSLF, the right posterior limb of the internal capsule and the right posterior thalamic radiation. PAT had significant AD changes in regions including the genu of the CC, the right posterior limb of internal capsule, and the right splenium of the CC. From NODDI, PAT showed increased ODI in the LSLF and increased FISO in the right splenium of the CC. FICVF showed a significant decrease in the LSLF while increased in the left anterior corona radiata and the CC. Furthermore, the average values of MD and FICVF were significantly correlated with DS and AS. Hence the results of this study suggest that there are regional changes in WM in DE patients which may contribute to further understanding of the pathological mechanism of DE.

The pathobiological basis of depression in Parkinson disease: challenges and outlooks

Depression, with an estimated prevalence of about 40% is a most common neuropsychiatric disorder in Parkinson disease (PD), with a negative impact on quality of life, cognitive impairment and functional disability, yet the underlying neurobiology is poorly understood. Depression in PD (DPD), one of its most common non-motor symptoms, can precede the onset of motor symptoms but can occur at any stage of the disease. Although its diagnosis is based on standard criteria, due to overlap with other symptoms related to PD or to side effects of treatment, depression is frequently underdiagnosed and undertreated. DPD has been related to a variety of pathogenic mechanisms associated with the underlying neurodegenerative process, in particular dysfunction of neurotransmitter systems (dopaminergic, serotonergic and noradrenergic), as well as to disturbances of cortico-limbic, striato-thalamic-prefrontal, mediotemporal-limbic networks, with disruption in the topological organization of functional mood-related, motor and other essential brain network connections due to alterations in the blood-oxygen-level-dependent (BOLD) fluctuations in multiple brain areas. Other hypothetic mechanisms involve neuroinflammation, neuroimmune dysregulation, stress hormones, neurotrophic, toxic or metabolic factors. The pathophysiology and pathogenesis of DPD are multifactorial and complex, and its interactions with genetic factors, age-related changes, cognitive disposition and other co-morbidities awaits further elucidation.