Parafoveal thinning of inner retina is associated with visual dysfunction in Lewy body diseases

Background Retinal optical coherence tomography findings in Lewy body diseases and their implications for visual outcomes remain controversial. We investigated whether region-specific thickness analysis of retinal layers could improve the detection of macular atrophy and unravel its association with visual disability in Parkinson's disease. Methods Patients with idiopathic Parkinson's disease (n = 63), dementia with Lewy bodies (n = 8), and E46K mutation carriers in the alpha-synuclein gene (E46K-SNCA) (n = 4) and 34 controls underwent Spectralis optical coherence tomography macular scans and a comprehensive battery of visual function and cognition tests. We computed mean retinal layer thicknesses of both eyes within 1-, 2-, 3-, and 6-mm diameter macular discs and in concentric parafoveal (1- to 2-mm, 2- to 3-mm, 1- to 3-mm) and perifoveal (3- to 6-mm) rings. Group differences in imaging parameters and their relationship with visual outcomes were analyzed. A multivariate logistic model was developed to predict visual impairment from optical coherence tomography measurements in Parkinson's disease, and cutoff values were determined with receiver operating characteristic analysis. Results When compared with controls, patients with dementia with Lewy bodies had significant thinning of the ganglion cell-inner plexiform layer complex within the central 3-mm disc mainly because of differences in 1- to 3-mm parafoveal thickness. This parameter was strongly correlated in patients, but not in controls, with low contrast visual acuity and visual cognition outcomes (P < .05, False Discovery Rate), achieving 88% of accuracy in predicting visual impairment in Parkinson's disease. Conclusion Our findings support that parafoveal thinning of ganglion cell-inner plexiform complex is a sensitive and clinically relevant imaging biomarker for Lewy body diseases, specifically for Parkinson's disease. (c) 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.This study was partially cofunded by the Michael J. Fox Foundation (2014 Rapid Response Innovation Awards; Grant 10189), by the Carlos III Health Institute through Projects PI14/00679 and PI16/00005, and Juan Rodes Grant JR15/00008 (I.G.) (cofunded by the European Regional Development Fund/European Social Fund "Investing in Your Future"), and by the Department of Health of the Basque Government through Project 201611100

Parameters from site classification to harmonize MRI clinical studies: Application to a multi-site Parkinson's disease dataset

Multi-site MRI datasets are crucial for big data research. However, neuroimaging studies must face the batch effect. Here, we propose an approach that uses the predictive probabilities provided by Gaussian processes (GPs) to harmonize clinical-based studies. A multi-site dataset of 216 Parkinson's disease (PD) patients and 87 healthy subjects (HS) was used. We performed a site GP classification using MRI data. The outcomes estimated from this classification, redefined like Weighted HARMonization PArameters (WHARMPA), were used as regressors in two different clinical studies: A PD versus HS machine learning classification using GP, and a VBM comparison (FWE-p < .05, k = 100). Same studies were also conducted using conventional Boolean site covariates, and without information about site belonging. The results from site GP classification provided high scores, balanced accuracy (BAC) was 98.39% for grey matter images. PD versus HS classification performed better when the WHARMPA were used to harmonize (BAC = 78.60%; AUC = 0.90) than when using the Boolean site information (BAC = 56.31%; AUC = 0.71) and without it (BAC = 57.22%; AUC = 0.73). The VBM analysis harmonized using WHARMPA provided larger and more statistically robust clusters in regions previously reported in PD than when the Boolean site covariates or no corrections were added to the model. In conclusion, WHARMPA might encode global site-effects quantitatively and allow the harmonization of data. This method is user-friendly and provides a powerful solution, without complex implementations, to clean the analyses by removing variability associated with the differences between sites

Retinal thickness predicts the risk of cognitive decline in Parkinson's disease

Objective: To analyze longitudinal changes of retinal thickness and their predictive value as biomarkers of disease progression in idiopathic Parkinson’s disease (iPD). Methods: Patients with Lewy body diseases (LBDs) were enrolled and prospectively evaluated at 3 years, including patients with iPD (n=42), dementia with Lewy bodies (DLB, n=4), E46K-SNCA mutation carriers (n=4) and controls (n=17). All participants underwent Spectralis retinal optical coherence tomography and Montreal Cognitive Assessment (MoCA), and Unified Parkinson’s Disease Rating Scale (UPDRS) score was obtained in patients. Macular ganglion-inner plexiform layer complex (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) thickness reduction rates were estimated with linear mixed models. Risk ratios were calculated to evaluate the association between baseline GCIPL and pRNFL thickness and the risk of subsequent cognitive and motor worsening, using clinically meaningful cut-offs. Results: GCIPL thickness in the parafoveal region (1- to 3-mm ring) presented the largest reduction rate. The annualized atrophy rate was 0.63 µm in iPD patients and 0.23 µm in controls (p<0.0001). iPD patients with lower parafoveal GCIPL and pRNFL thickness at baseline presented an increased risk of cognitive decline at 3 years (RR 3.49, 95% CI 1.10 – 11.1, p=0.03 and RR 3.28, 95% CI 1.03 – 10.45, p=0.045, respectively). We did not identify significant associations between retinal thickness and motor deterioration. Interpretation: Our results provide evidence of the potential use of OCT-measured parafoveal GCIPL thickness to monitor neurodegeneration and to predict the risk of cognitive worsening over time in iPD

A Neuropsychological Rehabilitation Program for Cognitive Impairment in Psychiatric and Neurological Conditions: A Review That Supports Its Efficacy

Neuropsychological rehabilitation has been the focus of much scientific research over the past decades due to its efficacy in different pathologies. Advances in the neuropsychology field have led to improvements and changes in neuropsychological interventions, which in turn have given rise to different approaches and rehabilitation programs. REHACOP is an integrative neuropsychological rehabilitation program designed by specialist neuropsychologists. With an integrated bottom-up and top-down approach, REHACOP includes neurocognition, social cognition, and daily living tasks hierarchically organized on an increasing level of difficulty. Task arrangement is addressed to maximize improvements and transfer effects into participant’s daily living. To date, REHACOP has been implemented on different clinical samples such as patients with schizophrenia, multiple sclerosis (MS), and Parkinson’s disease (PD). This manuscript presents the efficacy data of REHACOP across these three populations and discusses it in the context of the available literature. Overall, the magnitude of improvements obtained by means of REHACOP ranged from medium to high across samples. These changes were not restricted to specific neurocognitive domains since participants attending the REHACOP program also showed changes in social cognition and daily functioning variables by means of both direct and transfer effects. Results regarding REHACOP’s efficacy in psychiatric and neurological conditions have contributed to expanding the existing evidence about the use of structured neuropsychological rehabilitation. In addition, the results obtained after its implementation highlighted the need and importance of designing and implementing integrative neuropsychological rehabilitation programs that are focused not only on cognition per se but also on participants’ performance in daily living

Brain Degeneration in Synucleinopathies Based on Analysis of Cognition and Other Nonmotor Features: A Multimodal Imaging Study

Background: We aimed to characterize subtypes of synucleinopathies using a clustering approach based on cognitive and other nonmotor data and to explore structural and functional magnetic resonance imaging (MRI) brain differences between identified clusters. Methods: Sixty-two patients (n = 6 E46K-SNCA, n = 8 dementia with Lewy bodies (DLB) and n = 48 idiopathic Parkinson’s disease (PD)) and 37 normal controls underwent nonmotor evaluation with extensive cognitive assessment. Hierarchical cluster analysis (HCA) was performed on patients’ samples based on nonmotor variables. T1, diffusion-weighted, and resting-state functional MRI data were acquired. Whole-brain comparisons were performed. Results: HCA revealed two subtypes, the mild subtype (n = 29) and the severe subtype (n = 33). The mild subtype patients were slightly impaired in some nonmotor domains (fatigue, depression, olfaction, and orthostatic hypotension) with no detectable cognitive impairment; the severe subtype patients (PD patients, all DLB, and the symptomatic E46K-SNCA carriers) were severely impaired in motor and nonmotor domains with marked cognitive, visual and bradykinesia alterations. Multimodal MRI analyses suggested that the severe subtype exhibits widespread brain alterations in both structure and function, whereas the mild subtype shows relatively mild disruptions in occipital brain structure and function. Conclusions: These findings support the potential value of incorporating an extensive nonmotor evaluation to characterize specific clinical patterns and brain degeneration patterns of synucleinopathies

Autonomic dysfunction is associated with neuropsychological impairment in Lewy body disease

Objective: This study aimed to analyze the association of autonomic dysfunction with cognition, depression, apathy, and fatigue in Lewy body disease (LBD). Methods: We included 61 patients [49 with idiopathic Parkinson’s disease, 7 with dementia with Lewy bodies, and 5 E46K-SNCA mutation carriers] and 22 healthy controls. All participants underwent a comprehensive battery of neuropsychological and clinical measures, autonomic symptom assessment with the SCOPA-AUT, analysis of non-invasive hemodynamic parameters during deep breathing, the Valsalva maneuver, and a 20-min tilt test, and electrochemical skin conductance measurement at rest (Sudoscan). Student’s t tests were used to assess group differences, and bivariate correlations and stepwise linear regressions to explore associations between autonomic function, cognition, depression, apathy, and fatigue. Results: Compared to controls, patients who had significant impairment (p < 0.05) in cognition, higher depression, apathy, and fatigue, more autonomic symptoms and objective autonomic dysfunction, reduced deep breathing heart rate variability [expiratory-to-inspiratory (E/I) ratio], prolonged pressure recovery time, and lower blood pressure in Valsalva late phase II and phase IV, while 24.1% had orthostatic hypotension in the tilt test. Autonomic parameters significantly correlated with cognitive and neuropsychiatric outcomes, systolic blood pressure during the Valsalva maneuver predicting apathy and depression. The E/I ratio was the main predictor of cognitive performance (17.6% for verbal fluency to 32.8% for visual memory). Conclusion: Cardiovascular autonomic dysfunction is associated with cognitive and neuropsychiatric impairment in LBD, heart rate variability during deep breathing and systolic blood pressure changes during the Valsalva procedure are the main predictors of neuropsychological performance and depression/apathy symptoms, respectively

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

Abstract 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