Hierarchical cluster analysis of multimodal imaging data identifies brain atrophy and cognitive patterns in Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) is a heterogeneous condition. Cluster analysis based on cortical thickness has been used to define distinct patterns of brain atrophy in PD. However, the potential of other neuroimaging modalities, such as white matter (WM) fractional anisotropy (FA), which has also been demonstrated to be altered in PD, has not been investigated. OBJECTIVE: We aim to characterize PD subtypes using a multimodal clustering approach based on cortical and subcortical gray matter (GM) volumes and FA measures. METHODS: We included T1-weighted and diffusion-weighted MRI data from 62 PD patients and 33 healthy controls. We extracted mean GM volumes from 48 cortical and 17 subcortical regions using FSL-VBM, and the mean FA from 20 WM tracts using Tract-Based Spatial Statistics (TBSS). Hierarchical cluster analysis was performed with the PD sample using Ward's linkage method. Whole-brain voxel-wise intergroup comparisons of VBM and TBSS data were also performed using FSL. Neuropsychological and demographic statistical analyses were conducted using IBM SPSS Statistics 25.0. RESULTS: We identified three PD subtypes, with prominent differences in GM patterns and little WM involvement. One group (n = 15) with widespread cortical and subcortical GM volume and WM FA reductions and pronounced cognitive deficits; a second group (n = 21) with only cortical atrophy limited to frontal and temporal regions and more specific neuropsychological impairment, and a third group (n = 26) without detectable atrophy or cognition impairment. CONCLUSION: Multimodal MRI data allows classifying PD patients into groups according to GM and WM patterns, which in turn are associated with the cognitive profile.

Disruption of posterior brain functional connectivity and its relation to cognitive impairment in idiopathic REM sleep behavior disorder.

BACKGROUND: Resting-state functional MRI has been proposed as a new biomarker of prodromal neurodegenerative disorders, but it has been poorly investigated in the idiopathic form of rapid-eye-movement sleep behavior disorder (IRBD), a clinical harbinger of subsequent synucleinopathy. Particularly, a complex-network approach has not been tested to study brain functional connectivity in IRBD patients. OBJECTIVES: The aim of the current work is to characterize resting-state functional connectivity in IRBD patients using a complex-network approach and to determine its possible relation to cognitive impairment. METHOD: Twenty patients with IRBD and 27 matched healthy controls (HC) underwent resting-state functional MRI with a 3T scanner and a comprehensive neuropsychological battery. The functional connectome was studied using threshold-free network-based statistics. Global and local network parameters were calculated based on graph theory and compared between groups. Head motion, age and sex were introduced as covariates in all analyses. RESULTS: IRBD patients showed reduced cortico-cortical functional connectivity strength in comparison with HC in edges located in posterior regions (p <0.05, FWE corrected). This regional pattern was also shown in an independent analysis comprising posterior areas where a decreased connectivity in 51 edges was found, whereas no significant results were detected when an anterior network was considered (p <0.05, FWE corrected). In the posterior network, the left superior parietal lobule had reduced centrality in IRBD. Functional connectivity strength between left inferior temporal lobe and right superior parietal lobule positively correlated with mental processing speed in IRBD (r = .633; p = .003). No significant correlations were found in the HC group. CONCLUSION: Our findings support the presence of disrupted posterior functional brain connectivity of IRBD patients similar to that found in synucleinopathies. Moreover, connectivity reductions in IRBD were associated with lower performance in mental processing speed domain.

Comparing the accuracy and neuroanatomical correlates of the UPSIT-40 and the Sniffin' Sticks test in REM sleep behavior disorder.

BACKGROUND: Olfactory impairment increases the risk of developing neurodegenerative diseases in patients with idiopathic REM sleep behavior disorder (IRBD). Knowing the test properties of distinct olfactory measures could contribute to their selection for clinical or research purposes. OBJECTIVE: To compare the accuracy in distinguishing IRBD patients from controls with the University of Pennsylvania Smell Identification Test (UPSIT-40) and Sniffin' Sticks Extended test, and to assess the gray-matter volume correlates of these tests. METHOD: Twenty-one patients with IRBD and 27 healthy controls were assessed using both olfactory tests. Independent logistic regressions were computed with diagnosis as a dependent variable and olfactory measures as predictive variables. Receiver operating characteristic curves were computed for each olfactory subtest. Diagnostic accuracy for IRBD was calculated according to the resulting optimal cut-off score. Structural MRI data, acquired with a 3T scanner, were analyzed with voxel-based morphometry. RESULTS: Patients differed from controls in all olfactory measures. The Sniffin-Identification correctly classified 89.1% of cases; the UPSIT-40, 85.4%; the Sniffin-Discrimination, 82.6%; the Sniffin-Total, 81.8%; and the Sniffin-Threshold, 77.3%. Respective AUROC, optimal cut-off, sensitivity, and specificity for each test were: 0.902, ≤26, 85.7%, and 85.2% for the UPSIT-40; 0.884, ≤29, 89.5%, and 76.0% for the Sniffin-Total; 0.922, ≤11, 90.5%, and 88.0% for the Sniffin-Identification; 0.739, ≤4, 73.7%, and 76.0% for the Sniffin-Threshold; and 0.838, ≤11, 85.7%, and 76.0% for the Sniffin-Discrimination. UPSIT-40 scores correlated with gray-matter volumes in orbitofrontal regions in anosmic patients. CONCLUSIONS: UPSIT-40 and Sniffin' Identification showed similar discrimination accuracy, but only the UPSIT-40 showed structural correlates (p ≤ .05 FDR-corrected).

Diagnostic Accuracy, Item Analysis and Age Effects of the UPSIT Spanish Version in Parkinson's Disease.

OBJECTIVE: The University of Pennsylvania Smell Identification Test (UPSIT) is the most commonly used test to detect olfactory impairment in Parkinson's disease (PD), but the cut-off score for clinical purposes is often difficult to establish because of age and sex effects. The current work aims to study the sensitivity and specificity of the UPSIT Spanish version and its accuracy in discriminating PD patients at different age groups from healthy controls (HC), and to perform an item analysis. METHOD: Ninety-seven non-demented PD patients and 65 HC were assessed with the UPSIT Spanish version. Sensitivity, specificity, and diagnostic accuracy for PD were calculated. Multiple regression analysis was used to define predictors of UPSIT scores. RESULTS: Using the normative cut-off score for anosmia (≤18), the UPSIT showed a sensitivity of 54.6% with a specificity of 100.0% for PD. We found that, using the UPSIT cut-off score of ≤25, sensitivity was 81.4% and specificity 84.6% (area under the receiver operating characteristic curve = 0.908). Diagnosis and age were good predictors of UPSIT scores (B = -10.948; p < .001; B = -0.203; p < .001). When optimal cut-off scores were considered according to age ranges (≤60, 61-70, and ≥71), sensitivity and specificity values were >80.0% for all age groups. CONCLUSIONS: In the Spanish UPSIT version, sensitivity and specificity are improved when specific cut-off scores for different age groups are computed.

Cortical thinning correlates of changes in visuospatial and visuoperceptual performance in Parkinson's disease: A 4-year follow-up.

BACKGROUND: Growing evidence highlights the relevance of posterior cortically-based cognitive deficits in Parkinson's disease (PD) as possible biomarkers of the evolution to dementia. Cross-sectional correlational studies have established a relationship between the degree of atrophy in posterior brain regions and visuospatial and visuoperceptual (VS/VP) impairment. The aim of this study is to address the progressive cortical thinning correlates of VS/VP performance in PD. METHODS: Forty-four PD patients and 20 matched healthy subjects were included in this study and followed for 4 years. Tests used to assess VS/VP functions included were: Benton's Judgement of Line Orientation (JLOT), Facial Recognition (FRT), and Visual Form Discrimination (VFDT) Tests; Symbol Digit Modalities Test (SDMT); and the Pentagon Copying Test (PCT). Structural magnetic resonance imaging data and FreeSurfer were used to evaluate cortical thinning evolution. RESULTS: PD patients with normal cognition (PD-NC) and PD patients with mild cognitive impairment (PD-MCI) differed significantly in the progression of cortical thinning in posterior regions. In PD-MCI patients, the change in VS/VP functions assessed by PCT, JLOT, FRT, and SMDT correlated with the symmetrized percent change of cortical thinning of occipital, parietal, and temporal regions. In PD-NC patients, we also observed a correlation between changes in FRT and thinning in parieto-occipital regions. CONCLUSION: In this study, we establish the neuroanatomical substrate of progressive changes in VS/VP performance in PD patients with and without MCI. In agreement with cross-sectional data, VS/VP changes over time are related to cortical thinning in posterior regions.

Structural MRI correlates of the MMSE and pentagon copying test in Parkinson's disease.

BACKGROUND: Cognitive impairment in Parkinson's disease (PD) is common and recent studies have focused on addressing the most suitable screening tool for its assessment. MMSE is commonly used in clinical practice and longitudinal studies found a relationship between the MMSE pentagon copying item and progression to dementia, but its neuroanatomical correlates have been poorly investigated. The aim of this study is to investigate the MRI structural correlates of the global MMSE and the pentagon item scores in PD patients in the absence of dementia. METHODS: We selected a sample of 92 PD patients and 36 controls. MMSE was used as a global measure of cognitive status, and the pentagon copying test as a measure of visuospatial performance. FreeSurfer software was used to assess intergroup differences in cortical thickness (CTh) and global atrophy measures, as well as their relationship with cognitive performance. RESULTS: Compared to controls, patients showed significant differences in measures of global atrophy, which correlated with performance on MMSE and the pentagon item. Regional differences in CTh were seen between PD patients and controls bilaterally in the temporo-parietal-occipital region. Patients with impaired performance compared with those of normal performance also showed CTh reductions in these regions. CONCLUSION: Our results suggest MMSE and the pentagon item reflect brain changes which at a regional level involve mainly posterior regions. Correlates of the pentagon item were seen in the same regions where PD patients exhibited significant thinning, and involved more areas and bigger cluster sizes than the correlates of MMSE global scores.

Structural correlates of facial emotion recognition deficits in Parkinson's disease patients.

The ability to recognize facial emotion expressions, especially negative ones, is described to be impaired in Parkinson's disease (PD) patients. Previous neuroimaging work evaluating the neural substrate of facial emotion recognition (FER) in healthy and pathological subjects has mostly focused on functional changes. This study was designed to evaluate gray matter (GM) and white matter (WM) correlates of FER in a large sample of PD. Thirty-nine PD patients and 23 healthy controls (HC) were tested with the Ekman 60 test for FER and with magnetic resonance imaging. Effects of associated depressive symptoms were taken into account. In accordance with previous studies, PD patients performed significantly worse in recognizing sadness, anger and disgust. In PD patients, voxel-based morphometry analysis revealed areas of positive correlation between individual emotion recognition and GM volume: in the right orbitofrontal cortex, amygdala and postcentral gyrus and sadness identification; in the right occipital fusiform gyrus, ventral striatum and subgenual cortex and anger identification, and in the anterior cingulate cortex (ACC) and disgust identification. WM analysis through diffusion tensor imaging revealed significant positive correlations between fractional anisotropy levels in the frontal portion of the right inferior fronto-occipital fasciculus and the performance in the identification of sadness. These findings shed light on the structural neural bases of the deficits presented by PD patients in this skill.