Reduced Gray Matter Volume and Risk of Falls in Parkinson's Disease with Dementia Patients: A Voxel-Based Morphometry Study

Brain activity in different brain areas of patients with diabetic vitreous hemorrhage according to voxel-based morphometry

AIM

To elucidate the neuropathological mechanisms underlying diabetic vitreous hemorrhage (DVH) and its correlation with clinical characteristics.

METHODS

Twenty-one individuals with DVH (male/female 12/9; mean age 52.29±11.66y) were selected, alongside 21 appropriately matched controls with diabetes mellitus (DM). Voxel-based morphometry (VBM) techniques were employed to identify aberrant functional regions in the brain. Receiver operating characteristic (ROC) curves were utilized for classification based on the average VBM values of the two groups, and Pearson correlation analysis was conducted to assess the relationship between average VBM values in distinct brain regions and clinical manifestations.

RESULTS

Relative to the DM controls, DVH patients exhibited reduced VBM values in the right superior temporal pole, the right superior temporal gyrus, the right medial orbital frontal gyrus, and the left superior frontal gyrus. Furthermore, ROC curve analysis of these four brain regions in DVH patients demonstrated a high degree of accuracy, as indicated by the area under the curve. The average VBM value in each of these regions exhibited a negative correlation with both the duration of DVH and the score on the Hospital Anxiety and Depression Scale (HADS).

CONCLUSION

Pathological alterations in four distinct brain regions are observed in patients with DVH, potentially reflecting neuropathological changes associated with this condition.

Gray Matter Atrophy in a 6-OHDA-induced Model of Parkinson's Disease

INTRODUCTION

Magnetic resonance imaging (MRI) based brain morphometric changes in unilateral 6-hydroxydopamine (6-OHDA) induced Parkinson's disease (PD) model can be elucidated using voxel-based morphometry (VBM), study of alterations in gray matter volume and Machine Learning (ML) based analyses.

METHODS

We investigated gray matter atrophy in 6-OHDA induced PD model as compared to sham control using statistical and ML based analysis. VBM and atlas-based volumetric analysis was carried out at regional level. Support vector machine (SVM)-based algorithms wherein features (volume) extracted from (a) each of the 150 brain regions (b) statistically significant features (only) and (c) volumes of each cluster identified after application of VBM (VBM_Vol) were used for training the decision model. The lesion of the 6-OHDA model was validated by estimating the net contralateral rotational behaviour by the injection of apomorphine drug and motor impairment was assessed by rotarod and open field test.

RESULTS AND DISCUSSION

In PD, gray matter volume (GMV) atrophy was noted in bilateral cortical and subcortical brain regions, especially in the internal capsule, substantia nigra, midbrain, primary motor cortex and basal ganglia-thalamocortical circuits in comparison with sham control. Behavioural results revealed an impairment in motor performance. SVM analysis showed 100% classification accuracy, sensitivity and specificity at both 3 and 7 weeks using VBM_Vol.

CONCLUSION

Unilateral 6-OHDA induced GMV changes in both hemispheres at 7th week may be associated with progression of the disease in the PD model. SVM based approaches provide an increased classification accuracy to elucidate GMV atrophy.

Risk factors for falls in Parkinson's disease: a cross-sectional observational and Mendelian randomization study

Background

Patients with Parkinson's disease (PD) exhibit a heightened risk of falls and related fractures compared to the general population. This study aims to assess the clinical characteristics associated with falls in the patient with PD and to gain further insight into these factors through Mendelian randomization analysis.

Methods

From January 2013 to December 2023, we included 591 patients diagnosed with Parkinson's disease at Shenzhen Baoan People's Hospital. Using univariate and multivariate logistic regression analyses, we identified clinical variables associated with falls. We constructed a nomogram based on these variables and evaluated the predictive efficacy of the model. Additionally, we employed summary statistics from genome-wide association studies to conduct two-sample Mendelian randomization (MR) analyses on key variables influencing falls.

Results

Compared to the control group, we identified osteoporosis, motor dysfunction, higher Hoehn and Yahr scale as significant risk factors for falls in PD patients. Conversely, treatment with levodopa and a higher level of education exhibited a protective effect against the risk of falling. MR analysis further confirmed a causal relationship between osteoporosis, education level and falls in PD patients.

Conclusion

Osteoporosis and educational attainment are correlated with falls in Parkinson's disease.

Association between ABO genotypes and risk of dementia and neuroimaging markers: roles of sex and APOE status

Background

Whether the relationships between ABO blood genotypes (AA, AO, BB, BO, AB, and OO) and dementia are modified by gender and APOE status has been unclear.

Methods

We used data from the UK Biobank, a population-based cohort study of 487,425 individuals. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CI) between ABO genotypes and risk of dementia. Multivariable linear regression models were used to estimate the relationship between ABO genotypes and MRI-based brain indices.

Results

Overall, 487,425 participants were included at baseline. After 34 million person-years follow up, 7,548 patients developed all-cause dementia. Before stratifying by sex and APOE status, compared to OO genotype, BB genotype was associated with increased risk of all-cause dementia (1.36, 1.03-1.80) and other types dementia (1.65, 1.20-2.28). After stratifying by sex, only in males, BB genotype was associated with higher risk of all-cause dementia (1.44, 1.02-2.09) and other types of dementia (1.95, 1.30-2.93). AB genotype in males was also associated with increased AD (1.34, 1.04-1.72). After further stratifying by APOE e4 status, BB genotype with two APOE e4 alleles showed even stronger association with all-cause dementia 4.29 (1.57, 11.72) and other types dementia (5.49, 1.70-17.69) in males. Also in males, AA genotype with one APOE e4 was associated with increased risks of all-cause dementia (1.27, 1.04-1.55), AD (1.45, 1.09-1.94) and other types dementia (1.40, 1.08-1.81). Linear regression models showed that in both sexes with APOE e4, AA genotype was associated with reduced total grey matter volume.

Conclusion

Sex and APOE e4 carrier status modified the association between ABO genotypes and risk of dementia. In males, BB genotype was consistently associated with increased risk of dementia, especially in those with two APOE e4 alleles. Also, in males with one APOE e4, AA genotype might be linked to higher risk of dementia.

Voxel-based morphometry of grey matter structures in Parkinson's Disease with wearing-off

Our study aimed to investigate the grey matter (GM) changes using voxel-based morphometry (VBM) in Parkinson's disease (PD) patients with wearing-off (WO). 3D-T1-weighted imaging was performed on 48 PD patients without wearing-off (PD-nWO), 39 PD patients with wearing-off (PD-WO) and 47 age and sex-matched healthy controls (HCs). 3D structural images were analyzed by VBM procedure with Statistical Parametric Mapping (SPM12) to detect grey matter volume. Widespread areas of grey matter changes were found in patients among three groups (in bilateral frontal, temporal lobes, lingual gyrus, inferior occipital gyrus, right precuneus, right superior parietal gyrus and right cerebellum). Grey matter reductions were found in frontal lobe (right middle frontal gyrus, superior frontal gyrus and precentral gyrus), right parietal lobe (precuneus, superior parietal gyrus, postcentral gyrus), right temporal lobe (superior temporal gyrus, middle temporal gyrus), bilateral lingual gyrus and inferior occipital gyrus in PD-WO group compared with the PD-nWO group. Our results suggesting that wearing-off may be associated with grey matter atrophy in the cortical areas. These findings may aid in a better understanding of the brain degeneration process in PD with wearing-off.

Gray matter, white matter and cerebrospinal fluid abnormalities in Parkinson's disease: A voxel-based morphometry study

BACKGROUND

Parkinson's disease (PD) is a chronic neurodegenerative disorder characterized by bradykinesia, tremor, and rigidity among other symptoms. With a 70% cumulative prevalence of dementia in PD, cognitive impairment and neuropsychiatric symptoms are frequent.

MATERIALS AND METHODS

In this study, we looked at anatomical brain differences between groups of patients and controls. A total of 138 people with PD were compared to 64 age-matched healthy people using voxel-based morphometry (VBM). VBM is a fully automated technique that allows for the identification of regional differences in gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) allowing for an objective comparison of brains of different groups of people. We used statistical parametric mapping for image processing and statistical analysis.

RESULTS

In comparison to controls, PD patients had lower GM volumes in the left middle cingulate, left lingual gyrus, right calcarine and left fusiform gyrus, also PD patients indicated lower WM volumes in the right middle cingulate, left lingual gyrus, right calcarine, and left inferior occipital gyrus. Moreover, PD patients group demonstrated higher CSF in the left caudate compared to the controls.

CONCLUSION

Physical fragility and cognitive impairments in PD may be detected more easily if anatomical abnormalities to the cingulate gyrus, occipital lobe and the level of CSF in the caudate are identified. Thus, our findings shed light on the role of the brain in PD and may aid in a better understanding of the events that occur in PD patients.