Gender-based analysis of cortical thickness and structural connectivity in Parkinson's disease

A multi-site study on sex differences in cortical thickness in non-demented Parkinson's disease

Clinical, cognitive, and atrophy characteristics depending on sex have been previously reported in Parkinson's disease (PD). However, though sex differences in cortical gray matter measures in early drug naïve patients have been described, little is known about differences in cortical thickness (CTh) as the disease advances. Our multi-site sample comprised 211 non-demented PD patients (64.45% males; mean age 65.58 ± 8.44 years old; mean disease duration 6.42 ± 5.11 years) and 86 healthy controls (50% males; mean age 65.49 ± 9.33 years old) with available T1-weighted 3 T MRI data from four international research centers. Sex differences in regional mean CTh estimations were analyzed using generalized linear models. The relation of CTh in regions showing sex differences with age, disease duration, and age of onset was examined through multiple linear regression. PD males showed thinner cortex than PD females in six frontal (bilateral caudal middle frontal, bilateral superior frontal, left precentral and right pars orbitalis), three parietal (bilateral inferior parietal and left supramarginal), and one limbic region (right posterior cingulate). In PD males, lower CTh values in nine out of ten regions were associated with longer disease duration and older age, whereas in PD females, lower CTh was associated with older age but with longer disease duration only in one region. Overall, male patients show a more widespread pattern of reduced CTh compared with female patients. Disease duration seems more relevant to explain reduced CTh in male patients, suggesting worse prognostic over time. Further studies should explore sex-specific cortical atrophy trajectories using large longitudinal multi-site data.

Differences in brain aging between sexes in Parkinson's disease

Parkinson's disease (PD) is linked to faster brain aging. Male sex is associated with higher prevalence, severe symptoms, and a faster progression rate in PD. There remains a significant gap in understanding the function of sex in the process of brain aging in PD. The structural T1-weighted MRI-driven brain-predicted age difference (i.e., Brain-PAD: the actual age subtracted from the brain-predicted age) was computed in a group of 373 people with PD (mean age ± SD: 61.37 ± 9.81, age range: 33-85, 34% female) from the Parkinson's Progression Marker Initiative database using a robust brain-age estimation framework that was trained on 949 healthy subjects. Linear regression models were used to investigate the association between Brain-PAD and clinical variables in PD, stratified by sex. Males with Parkinson's disease (PD-M) exhibited a significantly higher mean Brain-PAD than their female counterparts (PD-F) (t(256) = 2.50, p = 0.012). In the propensity score-matched PD-M group (PD-M*), Brain-PAD was found to be associated with a decline in general cognition, a worse degree of sleep behavior disorder, reduced visuospatial acuity, and caudate atrophy. Conversely, no significant links were observed between these factors and Brain-PAD in the PD-F group. Having 'older' looking brains in PD-M than PD-F supports the idea that sex plays a vital function in PD, such that the PD mechanism may be different in males and females. This study has the potential to broaden our understanding of dissimilarities in brain aging between sexes in the context of PD.

Brain connectivity for subtypes of parkinson's disease using structural MRI

Objective. Delineating Parkinson's disease (PD) into distinct subtypes is a major challenge. Most studies use clinical symptoms to label PD subtypes while our work uses an imaging-based data-mining approach to subtype PD. Our study comprises two major objectives - firstly, subtyping Parkinson's patients based on grey matter information from structural magnetic resonance imaging scans of human brains; secondly, comparative structural brain connectivity analysis of PD subtypes derived from the former step.Approach. Source-based-morphometry decomposition was performed on 131 Parkinson's patients and 78 healthy controls from PPMI dataset, to derive at components (regions) with significance in disease and high effect size. The loading coefficients of significant components were thresholded for arriving at subtypes. Further, regional grey matter maps of subtype-specific subjects were separately parcellated and employed for construction of subtype-specific association matrices using Pearson correlation. These association matrices were binarized using sparsity threshold and leveraged for structural brain connectivity analysis using network metrics.Main results. Two distinct Parkinson's subtypes (namely A and B) were detected employing loadings of two components satisfying the selection criteria, and a third subtype (AB) was detected, common to these two components. Subtype A subjects were highly weighted in inferior, middle and superior frontal gyri while subtype B subjects in inferior, middle and superior temporal gyri. Network metrics analyses through permutation test revealed significant inter-subtype differences (p < 0.05) in clustering coefficient, local efficiency, participation coefficient and betweenness centrality. Moreover, hubs were obtained using betweenness centrality and mean network degree.Significance. MRI-based data-driven subtypes show frontal and temporal lobes playing a key role in PD. Graph theory-driven brain network analyses could untangle subtype-specific differences in structural brain connections showing differential network architecture. Replication of these initial results in other Parkinson's datasets may be explored in future. Clinical Relevance- Investigating structural brain connections in Parkinson's disease may provide subtype-specific treatment.

Gender discrepancies and differences in motor and non-motor symptoms, cognition, and psychological outcomes in the treatment of Parkinson's disease with subthalamic deep brain stimulation

Available data suggest that there may be gender differences in the effect of STN-DBS in the treatment of Parkinson's disease (PD). The aim of this study was to review data on gender discrepancies and gender differences in clinical outcomes in PD patients treated with deep brain stimulation of the subthalamic nucleus (STN-DBS). Included were original studies that specifically examined gender discrepancies or gender differences in PD patients with STN-DBS. Men receive more DBS than women, for various indications. The decision-making process for DBS in women compared to men is more influenced by personal preferences and external factors. Motor symptoms improve in both genders, but bradykinesia improves more in men. The postoperative reduction of the levodopa equivalent daily dose seems to be more pronounced in men. Men show more cognitive deterioration and less improvement than women after STN-DBS. Women show more depressive symptoms before surgery, but they improve similarly to men. Men show more improvement in impulsivity and less decrease in impulsive behaviour symptoms than women. Anxiety and personality traits remain unchanged in both genders. Voice quality improves more in men and deteriorates less often than in women. Men gain fat-free mass and fat mass, but women only gain fat mass. Regarding sexual function the evidence is inconsistent. More urinary symptoms improve in women than in men. Pain and restless leg syndrome seems to improve more in men. Regarding quality of life, the evidence seems to be inconsistent, and activities of daily living seems to improve in both genders. Better prospective controlled studies, focusing directly on gender differences in PD patients treated with STN-DBS, are needed to better explain gender differences in STN-DBS for PD.

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.

Increased palmitoylation improves estrogen receptor alpha-dependent hippocampal synaptic deficits in a mouse model of synucleinopathy

Parkinson's disease (PD) is characterized by conversion of soluble α-synuclein (αS) into intraneuronal aggregates and degeneration of neurons and neuronal processes. Indications that women with early-stage PD display milder neurodegenerative features suggest that female sex partially protects against αS pathology. We previously reported that female sex and estradiol improved αS homeostasis and PD-like phenotypes in E46K-amplified (3K) αS mice. Here, we aimed to further dissect mechanisms that drive this sex dimorphism early in disease. We observed that synaptic abnormalities were delayed in females and improved by estradiol, mediated by local estrogen receptor alpha (ERα). Aberrant ERα distribution in 3K compared to wild-type mice was paired with its decreased palmitoylation. Treatment with ML348, a de-palmitoylation inhibitor, increased ERα availability and soluble αS homeostasis, ameliorating synaptic plasticity and cognitive and motor phenotypes. Our finding that sex differences in early-disease αS-induced synaptic impairment in 3KL mice are in part mediated by palmitoylated ERα may have functional and pathogenic implications for clinical PD.

Association of coffee consumption and striatal volume in patients with Parkinson's disease and healthy controls

BACKGROUND

Mounting studies have demonstrated that coffee consumption significantly reduces the risk of developing Parkinson's disease (PD). However, there have been few investigations about the role of chronic coffee consumption in nigrostriatal structural neurodegeneration in PD. We aimed to investigate whether chronic coffee consumption is associated with the change in striatal volume in PD.

METHODS

In this study, 130 de novo patients with PD and 69 healthy controls were enrolled from the Parkinson's Progression Markers Initiative cohort. Patients with PD and healthy controls were, respectively, divided into three subgroups, including current, ever, and never coffee consumers. Then, striatal volume was compared across the three subgroups. Correlation analyses were performed to assess the relationship between cups consumed per day and striatal volume. Furthermore, we included the factors that may have influenced nigrostriatal dopaminergic neurons in multiple linear regression analyses to identify significant contributing factors to striatal volume in each investigated striatal region.

RESULTS

Current coffee consumers had decreased striatal volume compared with ever consumers in controls but not patients with PD. Furthermore, the correlation analyses revealed that cups per day were negatively correlated with striatal volume in current consumers of patients with PD and controls. In addition, multiple linear regression analyses showed that current coffee consumption remained as an independent predictor of a decrease in striatal volume in controls.

CONCLUSIONS

Our study showed that chronic coffee consumption was negatively correlated with striatal volume. In addition, our study showed that chronic coffee consumption was associated with the change in striatal volume in current-rather than ever coffee consumers, which suggests that the chronic effects of caffeine on striatal morphology may fade and even compensate after quitting coffee. Our study provides evidence for the effect of chronic coffee consumption on striatal volume in human brain in vivo.

Unique Brain Network Identification Number for Parkinson's and Healthy Individuals Using Structural MRI

We propose a novel algorithm called Unique Brain Network Identification Number (UBNIN) for encoding the brain networks of individual subjects. To realize this objective, we employed structural MRI on 180 Parkinson's disease (PD) patients and 70 healthy controls (HC) from the National Institute of Mental Health and Neurosciences, India. We parcellated each subject's brain volume and constructed an individual adjacency matrix using the correlation between the gray matter volumes of every pair of regions. The unique code is derived from values representing connections for every node (i), weighted by a factor of 2-(i-1). The numerical representation (UBNIN) was observed to be distinct for each individual brain network, which may also be applied to other neuroimaging modalities. UBNIN ranges observed for PD were 15,360 to 17,768,936,615,460,608, and HC ranges were 12,288 to 17,733,751,438,064,640. This model may be implemented as a neural signature of a person's unique brain connectivity, thereby making it useful for brainprinting applications. Additionally, we segregated the above datasets into five age cohorts: A: ≤32 years (n1 = 4, n2 = 5), B: 33-42 years (n1 = 18, n2 = 14), C: 43-52 years (n1 = 42, n2 = 23), D: 53-62 years (n1 = 69, n2 = 22), and E: ≥63 years (n1 = 46, n2 = 6), where n1 and n2 are the number of individuals in PD and HC, respectively, to study the variation in network topology over age. Sparsity was adopted as the threshold estimate to binarize each age-based correlation matrix. Connectivity metrics were obtained using Brain Connectivity toolbox (Version 2019-03-03)-based MATLAB (R2020a) functions. For each age cohort, a decreasing trend was observed in the mean clustering coefficient with increasing sparsity. Significantly different clustering coefficients were noted in PD between age-cohort B and C (sparsity: 0.63, 0.66), C and E (sparsity: 0.66, 0.69), and in HC between E and B (sparsity: 0.75 and above 0.81), E and C (sparsity above 0.78), E and D (sparsity above 0.84), and C and D (sparsity: 0.9). Our findings suggest network connectivity patterns change with age, indicating network disruption may be due to the underlying neuropathology. Varying clustering coefficients for different cohorts indicate that information transfer between neighboring nodes changes with age. This provides evidence of age-related brain shrinkage and network degeneration. We also discuss limitations and provide an open-access link to software codes and a help file for the entire study.

Sex and gender differences in Alzheimer's disease, Parkinson's disease, and Amyotrophic Lateral Sclerosis: a narrative review

Neurodegenerative diseases (NDs), including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS), exhibit high phenotypic variability and they are very common in the general population. These diseases are associated with poor prognosis and a significant burden on patients and their caregivers. Although increasing evidence suggests that biological sex is an important factor for the development and phenotypical expression of some NDs, the role of sex and gender in the diagnosis and prognosis of NDs has been poorly explored. Current knowledge relating to sex- and gender-related differences in the epidemiology, clinical features, biomarkers, and treatment of AD, PD, and ALS will be summarized in this narrative review. The cumulative evidence hitherto collected suggests that sex and gender are factors to be considered in explaining the heterogeneity of these NDs. Clarifying the role of sex and gender in AD, PD, and ALS is a key topic in precision medicine, which will facilitate sex-specific prevention and treatment strategies to be implemented in the near future.

Age and sex differentially shape brain networks in Parkinson's disease

AIMS

Age and sex are important individual factors modifying the clinical symptoms of patients with Parkinson's disease (PD). Our goal is to evaluate the effects of age and sex on brain networks and clinical manifestations of PD patients.

METHODS

Parkinson's disease participants (n = 198) receiving functional magnetic resonance imaging from Parkinson's Progression Markers Initiative database were investigated. Participants were classified into lower quartile group (age rank: 0%~25%), interquartile group (age rank: 26%~75%), and upper quartile group (age rank: 76%~100%) according to their age quartiles to examine how age shapes brain network topology. The differences of brain network topological properties between male and female participants were also investigated.

RESULTS

Parkinson's disease patients in the upper quartile age group exhibited disrupted network topology of white matter networks and impaired integrity of white matter fibers compared to lower quartile age group. In contrast, sex preferentially shaped the small-world topology of gray matter covariance network. Differential network metrics mediated the effects of age and sex on cognitive function of PD patients.

CONCLUSION

Age and sex have diverse effects on brain structural networks and cognitive function of PD patients, highlighting their roles in the clinical management of PD.

Sex Differences in Brain Structure in de novo Parkinson's Disease: A Cross-Sectional and Longitudinal Neuroimaging Study

BACKGROUND

Parkinson's disease (PD) varies in occurrence, presentation, and severity between males and females. However, the sex effects on the patterns of brain structure, cross-sectionally and longitudinally, are still unclear.

OBJECTIVE

We aimed to compare sex differences in brain features cross-sectionally and longitudinally using grey matter volume (GMV) and cortical thickness in a large sample of newly diagnosed drug-naive PD patients.

METHODS

Cognitive assessments and structural MR images of 262 PD patients (171 males) and 113 healthy controls (68 males) were selected from the Parkinson's Progression Markers Initiative. Of these, 97 PD patients (66 males) completed 12- and 24-month follow-up examinations. After regressing out the expected effects of age and sex, brain maps of GMV and cortical thickness were compared using two-sample t tests cross-sectionally and were compared using repeated measurement analyses of variance longitudinally.

RESULTS

At baseline, male PD patients exhibited a greater extent of brain atrophy and cortical thickness reduction than females, which mainly occurred in the cerebellum, frontal lobe, parietal lobe, and temporal lobe. At follow-up, female and male PD patients showed similar dynamics of disease progression, as both groups declined over time while the females maintained the advantage. The cortical thickness of the right precentral gyrus at baseline was negatively associated with the longitudinal changes of motor function in male PD patients.

CONCLUSION

The current findings might demonstrate sex effect in neuroanatomy during the course of PD, provide new insights into the neurodegenerative process, and facilitate the development of more effective sex-specific therapeutic strategies.

Gender differences in diagnostic tools, medication, time to medication, and nonmotor symptoms in Parkinsonian patients

BACKGROUND

Swedish National Quality Registers (NQRs) play an important role in collecting large amounts of diagnosis-specific data, symptoms, and treatments. The subset of data, Parkinson's Registry, has been in use for more than 20 years and represents all counties and hospitals in Sweden where neurological care is provided.

OBJECTIVE

To study the differences between genders regarding diagnostic tools, pharmacological interventions, and self-reported symptoms in patients with symptoms originating from basal ganglia disease, either idiopathic or secondary Parkinsonism (PD).

METHODS

PD-diagnosed patients from a mix of urban and rural locations were chosen from the NQR and sorted by gender. Self-reported, first-experienced PD-related symptoms defined the debut point of PD.

RESULTS

In all, data from 1,217 patients were analyzed: 502 (41%) females/715 (59%) males. A total of 493 imaging investigations were performed, where of 239 (48% females/52% males) had a CT scan performed, 120 (24% females/29% males) had a dopamine transporter scans, and 134 (23% females/26% males) had a magnetic resonance imaging performed (Fisher's exact test, P = 0.19). The average time in years from symptom onset to start of first treatment, and from first to second added treatment was 2;7/2;9 (females) and 5;1/5;2 (males). Nonmotor symptoms were more prominent among males, especially in memory and gastrointestinal domains, including drooling and obstipation. Significantly more sexual problems were reported from males; 26% versus 7% (Fisher's exact test, P < 0.0001).

CONCLUSIONS

Differences between genders were identified in this study. Sexual problems and cognitive decline were more frequent among males. More advanced diagnostic imaging techniques were performed among males. The time point for a second added medication was earlier for males than females.

Sparsity Dependent Metrics Depict Alteration of Brain Network Connectivity in Parkinson's Disease

To date, regional brain atrophy unfolded using neuroimaging methods is observed to be the signature of Parkinson's disease (PD). In addition, graph theory-based studies are proving altered structural connectivity in PD. This motivated us to employ regional grey matter volume of PD patients (N=70) for comparative network analysis with an equal number of age- and gender-matched healthy controls (HC). In the current study, normalized grey matter maps obtained from structural magnetic resonance imaging (sMRI) were parcellated into 56 ROI (regions of interest) for construction of symmetric matrix using partial correlation between every pair of regional grey matter volumes. Sparsity thresholding was used to binarize the matrices and MATLAB functions from brain connectivity toolbox were employed to obtain the connectivity metrics. We observed PD with a significantly lower clustering coefficient as well as local efficiency at higher sparsities (above 0.9 and 0.84, respectively) with p<0.05. The right fusiform gyrus was found to be the conserved hub, besides disruption of four hubs and regeneration of five other hubs. Lower clustering coefficient and local efficiency were indicative of reduced local integration and information processing, respectively. Hence, we suggest that global clustering coefficient and local efficiency could have a pivotal role in evaluating network topology. Thereby, our findings confirmed impairment of normal structural brain network topology reflecting disconnectivity mechanisms in PD. Clinical Relevance - Analyzing structural brain connectivity in Parkinson's disease might provide the researchers and clinicians with a signature pattern of the disease to discriminate patients from normal controls.

Combining Neuroimaging and Omics Datasets for Disease Classification Using Graph Neural Networks

Both neuroimaging and genomics datasets are often gathered for the detection of neurodegenerative diseases. Huge dimensionalities of neuroimaging data as well as omics data pose tremendous challenge for methods integrating multiple modalities. There are few existing solutions that can combine both multi-modal imaging and multi-omics datasets to derive neurological insights. We propose a deep neural network architecture that combines both structural and functional connectome data with multi-omics data for disease classification. A graph convolution layer is used to model functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data simultaneously to learn compact representations of the connectome. A separate set of graph convolution layers are then used to model multi-omics datasets, expressed in the form of population graphs, and combine them with latent representations of the connectome. An attention mechanism is used to fuse these outputs and provide insights on which omics data contributed most to the model's classification decision. We demonstrate our methods for Parkinson's disease (PD) classification by using datasets from the Parkinson's Progression Markers Initiative (PPMI). PD has been shown to be associated with changes in the human connectome and it is also known to be influenced by genetic factors. We combine DTI and fMRI data with multi-omics data from RNA Expression, Single Nucleotide Polymorphism (SNP), DNA Methylation and non-coding RNA experiments. A Matthew Correlation Coefficient of greater than 0.8 over many combinations of multi-modal imaging data and multi-omics data was achieved with our proposed architecture. To address the paucity of paired multi-modal imaging data and the problem of imbalanced data in the PPMI dataset, we compared the use of oversampling against using CycleGAN on structural and functional connectomes to generate missing imaging modalities. Furthermore, we performed ablation studies that offer insights into the importance of each imaging and omics modality for the prediction of PD. Analysis of the generated attention matrices revealed that DNA Methylation and SNP data were the most important omics modalities out of all the omics datasets considered. Our work motivates further research into imaging genetics and the creation of more multi-modal imaging and multi-omics datasets to study PD and other complex neurodegenerative diseases.

Sex Differences in Brain and Cognition in de novo Parkinson's Disease

Background and Objective: Brain atrophy and cognitive impairment in neurodegenerative diseases are influenced by sex. We aimed to investigate sex differences in brain atrophy and cognition in de novo Parkinson's disease (PD) patients. Methods: Clinical, neuropsychological and T1-weighted MRI data from 205 PD patients (127 males: 78 females) and 69 healthy controls (40 males: 29 females) were obtained from the PPMI dataset. Results: PD males had a greater motor and rapid eye movement sleep behavior disorder symptomatology than PD females. They also showed cortical thinning in postcentral and precentral regions, greater global cortical and subcortical atrophy and smaller volumes in thalamus, caudate, putamen, pallidum, hippocampus, and brainstem, compared with PD females. Healthy controls only showed reduced hippocampal volume in males compared to females. PD males performed worse than PD females in global cognition, immediate verbal recall, and mental processing speed. In both groups males performed worse than females in semantic verbal fluency and delayed verbal recall; as well as females performed worse than males in visuospatial function. Conclusions: Sex effect in brain and cognition is already evident in de novo PD not explained by age per se, being a relevant factor to consider in clinical and translational research in PD.

Sex differences in brain atrophy and cognitive impairment in Parkinson's disease patients with and without probable rapid eye movement sleep behavior disorder

Background

The presence of rapid eye movement sleep behavior disorder (RBD) contributes to increase cognitive impairment and brain atrophy in Parkinson’s disease (PD), but the impact of sex is unclear. We aimed to investigate sex differences in cognition and brain atrophy in PD patients with and without probable RBD (pRBD).

Methods

Magnetic resonance imaging and cognition data were obtained for 274 participants from the Parkinson's Progression Marker Initiative database: 79 PD with pRBD (PD-pRBD; male/female, 54/25), 126 PD without pRBD (PD-non pRBD; male/female, 73/53), and 69 healthy controls (male/female, 40/29). FreeSurfer was used to obtain volumetric and cortical thickness data.

Results

Males showed greater global cortical and subcortical gray matter atrophy than females in the PD-pRBD group. Significant group-by-sex interactions were found in the pallidum. Structures showing a within-group sex effect in the deep gray matter differed, with significant volume reductions for males in one structure in in PD-non pRBD (brainstem), and three in PD-pRBD (caudate, pallidum and brainstem). Significant group-by-sex interactions were found in Montreal Cognitive Assessment (MoCA) and Symbol Digits Modalities Test (SDMT). Males performed worse than females in MoCA, phonemic fluency and SDMT in the PD-pRBD group.

Conclusion

Male sex is related to increased cognitive impairment and subcortical atrophy in de novo PD-pRBD. Accordingly, we suggest that sex differences are relevant and should be considered in future clinical and translational research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10728-x.

Sex effects on brain structure in de novo Parkinson's disease: a multimodal neuroimaging study

Parkinson's disease varies in severity and age of onset. One source of this variability is sex. Males are twice as likely as females to develop Parkinson's disease, and tend to have more severe symptoms and greater speed of progression. However, to date, there is little information in large cohorts on sex differences in the patterns of neurodegeneration. Here we used MRI and clinical information from the Parkinson Progression Markers Initiative to measure structural brain differences between sexes in Parkinson's disease after regressing out the expected effect of age and sex. We derived atrophy maps from deformation-based morphometry of T1-weighted MRI and connectivity from diffusion-weighted MRI in de novo Parkinson's disease patients (149 males: 83 females) with comparable clinical severity, and healthy control participants (78 males: 39 females). Overall, even though the two patient groups were matched for disease duration and severity, males demonstrated generally greater brain atrophy and disrupted connectivity. Males with Parkinson's disease had significantly greater tissue loss than females in 11 cortical regions including bilateral frontal and left insular lobe, right postcentral gyrus, left inferior temporal and cingulate gyrus and left thalamus, while females had greater atrophy in six cortical regions, including regions in the left frontal lobe, right parietal lobe, left insular gyrus and right occipital cortex. Local efficiency of white matter connectivity showed greater disruption in males in multiple regions such as basal ganglia, hippocampus, amygdala and thalamus. These findings support the idea that development of Parkinson's disease may involve different pathological mechanisms and yield distinct prognosis in males and females, which may have implications for research into neuroprotection, and stratification for clinical trials.

Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis

Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.

Classification of PPMI MRI scans with voxel-based morphometry and machine learning to assist in the diagnosis of Parkinson's disease

BACKGROUND AND OBJECTIVES

Qualitative and quantitative analyses of Magnetic Resonance Imaging (MRI) scans are carried out to study and understand Parkinson's Disease, the second most common neurodegenerative disorder in people at their 60's. Some quantitative analyses are based on the application of voxel-based morphometry (VBM) on magnetic resonance images to determine the regions of interest, within gray matter, where there is a loss of the nerve cells that generate dopamine. This loss of dopamine is indicative of Parkinson's disease. The purpose of this research is the introduction of a new method to classify the 3-D magnetic resonance scans of an individual, as an assisting tool for diagnosis of Parkinson's disease by using the largest MRI dataset (Parkinson's Progression Markers Initiative) from a population of patients with Parkinson's disease and control individuals. A contribution is that separate studies are conducted for men and women since gender plays a significant role within Neurobiology, which is demonstrated by the fact that men are more prone to Parkinson's disease than women are.

METHODS

Previous to classification, VBM is conducted on magnetic resonance images to detect the regions where features are extracted by using first- and second-order statistics methods. Furthermore, the number of features is considerably reduced by using feature selection techniques. Seven classifiers are used and we are conducting separate experiments for men and women.

RESULTS

The best detection performance achieved in men is 99.01% of accuracy, 99.35% of sensitivity, 100% of specificity, and 100% of precision. The best detection performance achieved in women is 96.97% of accuracy, 100% of sensitivity, 96.15% of specificity, and 97.22% of precision. During classification of magnetic resonance images, the corresponding computational complexity is reduced since few features are selected.

CONCLUSIONS

The proposed method provides high performance as an assisting tool in the diagnosis of Parkinson's disease, by conducting separate experiments in men and women. While previous works have focused their analysis to the striatum region of the brain (the largest nuclear complex of the basal ganglia), the proposed approach is based on analysis over the whole brain by looking for decreases of tissue thickness, with the consequence of finding other regions of interest such as the cortex.

Brain White-Matter Degeneration Due to Aging and Parkinson Disease as Revealed by Double Diffusion Encoding

Microstructure imaging by means of multidimensional diffusion encoding is increasingly applied in clinical research, with expectations that it yields a parameter that better correlates with clinical disability than current methods based on single diffusion encoding. Under the assumption that diffusion within a voxel can be well described by a collection of diffusion tensors, several parameters of this diffusion tensor distribution can be derived, including mean size, variance of sizes, orientational dispersion, and microscopic anisotropy. The information provided by multidimensional diffusion encoding also enables us to decompose the sources of the conventional fractional anisotropy and mean kurtosis. In this study, we explored the utility of the diffusion tensor distribution approach for characterizing white-matter degeneration in aging and in Parkinson disease by using double diffusion encoding. Data from 23 healthy older subjects and 27 patients with Parkinson disease were analyzed. Advanced age was associated with greater mean size and size variances, as well as smaller microscopic anisotropy. By analyzing the parameters underlying diffusion kurtosis, we found that the reductions of kurtosis in aging and Parkinson disease reported in the literature are likely driven by the reduction in microscopic anisotropy. Furthermore, microscopic anisotropy correlated with the severity of motor impairment in the patients with Parkinson disease. The present results support the use of multidimensional diffusion encoding in clinical studies and are encouraging for its future clinical implementation.

Cortical thickness in Parkinson disease: A coordinate-based meta-analysis

BACKGROUND

A growing number of studies have used surface-based morphometry (SBM) analyses to investigate gray matter cortical thickness (CTh) abnormalities in Parkinson disease (PD). However, the results across studies are inconsistent and have not been systematically reviewed. A clear picture of CTh alterations in PD remains lacked. Coordinate-based meta-analysis (CBMA) is a powerful tool to quantitatively integrate the results of individual voxel-based neuroimaging studies to identify the functional or structural neural substrates of particular neuropsychiatric disorders. Recently, CBMA has been updated for integrating SBM studies.

METHODS

The online databases PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), WanFang, and SinoMed were comprehensively searched without language limitations from the database inception to February 2, 2020. We will include all SBM studies that compared regional CTh between patients with idiopathic PD and healthy control subjects at the whole-cortex level using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI). In addition to the main CBMA, we will conduct several supplementary analyses to test the robustness of the results, such as jackknife analyses, subgroup analyses, heterogeneity analyses, publication bias analyses, and meta-regression analyses.

RESULTS

This CBMA will offer the latest evidence of CTh alterations in PD.

CONCLUSIONS

Consistent and robust evidence of CTh alterations will feature brain morphometry of PD and may facilitate biomarker development.

PROSPERO REGISTRATION NUMBER

CRD42020148775.

Sex differences in movement disorders

In a range of neurological conditions, including movement disorders, sex-related differences are emerging not only in brain anatomy and function, but also in pathogenesis, clinical features and response to treatment. In Parkinson disease (PD), for example, oestrogens can influence the severity of motor symptoms, whereas elevation of androgens can exacerbate tic disorders. Nevertheless, the real impact of sex differences in movement disorders remains under-recognized. In this article, we provide an up-to-date review of sex-related differences in PD and the most common hyperkinetic movement disorders, namely, essential tremor, dystonia, Huntington disease and other chorea syndromes, and Tourette syndrome and other chronic tic disorders. We highlight the most relevant clinical aspects of movement disorders that differ between men and women. Increased recognition of these differences and their impact on patient care could aid the development of tailored approaches to the management of movement disorders and enable the optimization of preclinical research and clinical studies.

Brain Atrophy and Reorganization of Structural Network in Parkinson's Disease With Hemiparkinsonism

Hemiparkinsonism duration in patients with Parkinson's disease (PD) is a key time window to study early pathology of PD. We aimed to comprehensively explore the alterations of deformation and structural network in PD patients with hemiparkinsonism, which could potentially disclose the early biomarker for PD. Thirty-one PD patients with hemiparkinsonism and 37 age- and gender- matched normal controls were included in the present study. First of all, we normalized the left hemisphere of structural images as the contralateral side to the affected limbs. Deformation-based morphometry (DBM) was conducted to evaluate the brain atrophy and/or enlargement. structural networks were constructed by thresholding gray matter volume correlation matrices of 116 regions and analyzed using graph theoretical approaches (e.g., small-worldness, global, and nodal measures). Significantly decreased deformation values were observed in the temporoparietal regions like bilateral middle temporal gyri, ipsilateral precuneus and contralateral Rolandic operculum extending to supramarginal and postcentral gyri. Lower deformation values in contralateral middle temporal gyrus were negatively correlated with higher motor impairment which was dominated by akinesia/rigidity. Moreover, nodal reorganization of structural network mainly located in frontal, temporal, subcortex and cerebellum was bilaterally explored in PD patients with hemiparkinsonism. Increased nodal properties could be commonly observed in frontal lobes. Disruption of subcortex including basal ganglia and amygdala was detected by nodal local efficiency and nodal clustering coefficient. Twelve hubs, mainly from paralimbic-limbic and heteromodal networks, were disrupted and, alternatively, 14 hubs, most of which were located in frontal lobes, were additionally detected in PD patients with hemiparkinsonism. In conclusion, during hemiparkinsonism period, mild brain atrophy in the temporoparietal regions and widespread reorganization of structural network, e.g., enhanced frontal function and disruption of basal ganglia nodes, occurred in both hemispheres. With our data, we can also argue that MTG contralateral to the affected limbs (expressing clinically verified brain atrophy) might be a potential living biomarker to monitor disease progression. Therefore, the combination of DBM and structural network analyses can provide a comprehensive and sensitive evaluation for potential pathogenesis of early PD patients with hemiparkinsonism.

Altered structural brain changes and neurocognitive performance in pediatric HIV

Pediatric HIV patients often suffer with neurodevelopmental delay and subsequently cognitive impairment. While tissue injury in cortical and subcortical regions in the brain of adult HIV patients has been well reported there is sparse knowledge about these changes in perinatally HIV infected pediatric patients. We analyzed cortical thickness, subcortical volume, structural connectivity, and neurocognitive functions in pediatric HIV patients and compared with those of pediatric healthy controls. With informed consent, 34 perinatally infected pediatric HIV patients and 32 age and gender matched pediatric healthy controls underwent neurocognitive assessment and brain magnetic resonance imaging (MRI) on a 3 T clinical scanner. Altered cortical thickness, subcortical volumes, and abnormal neuropsychological test scores were observed in pediatric HIV patients. The structural network connectivity analysis depicted lower connection strengths, lower clustering coefficients, and higher path length in pediatric HIV patients than healthy controls. The network betweenness and network hubs in cortico-limbic regions were distorted in pediatric HIV patients. The findings suggest that altered cortical and subcortical structures and regional brain connectivity in pediatric HIV patients may contribute to deficits in their neurocognitive functions. Further, longitudinal studies are required for better understanding of the effect of HIV pathogenesis on brain structural changes throughout the brain development process under standard ART treatment.

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Structural brain MRI and cognitive assessments were performed in pediatric HIV.

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Pediatric HIV showed altered cortical thickness and subcortical volumes.

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Disrupted structural connectivity was observed in pediatric HIV.

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Altered brain structures and connectivity contribute to deficits in neurocognition.