Dataset Information

Severe hyposmia and aberrant functional connectivity in cognitively normal Parkinson's disease.

ABSTRACT: Severe hyposmia is a risk factor of dementia in Parkinson's disease (PD), while the underlying functional connectivity (FC) and brain volume alterations in PD patients with severe hyposmia (PD-SH) are unclear.We examined voxel-based morphometric and resting state functional magnetic resonance imaging findings in 15 cognitively normal PD-SH, 15 cognitively normal patients with PD with no/mild hyposmia (PD-N/MH), and 15 healthy controls (HCs).Decreased gray matter volume (GMV) was observed in the bilateral cuneus, right associative visual area, precuneus, and some areas in anterior temporal lobes in PD-SH group compared to HCs. Both the PD-SH and PD-N/MH groups showed increased GMV in the bilateral posterior insula and its surrounding regions. A widespread significant decrease in amygdala FC beyond the decreased GMV areas and olfactory cortices were found in the PD-SH group compared with the HCs. Above all, decreased amygdala FC with the inferior parietal lobule, lingual gyrus, and fusiform gyrus was significantly correlated with both reduction of Addenbrooke's Cognitive Examination-Revised scores and severity of hyposmia in all participants. Canonical resting state networks exhibited decreased FC in the precuneus and left executive control networks but increased FC in the primary and high visual networks of patients with PD compared with HCs. Canonical network FC to other brain regions was enhanced in the executive control, salience, primary visual, and visuospatial networks of the PD-SH.PD-SH showed extensive decreased amygdala FC. Particularly, decreased FC between the amygdala and inferior parietal lobule, lingual gyrus, and fusiform gyrus were associated with the severity of hyposmia and cognitive performance. In contrast, relatively preserved canonical networks in combination with increased FC to brain regions outside of canonical networks may be related to compensatory mechanisms, and preservation of brain function.

SUBMITTER: Yoneyama N

PROVIDER: S-EPMC5755765 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Severe hyposmia and aberrant functional connectivity in cognitively normal Parkinson's disease.

Yoneyama Noritaka N Watanabe Hirohisa H Kawabata Kazuya K Bagarinao Epifanio E Hara Kazuhiro K Tsuboi Takashi T Tanaka Yasuhiro Y Ohdake Reiko R Imai Kazunori K Masuda Michihito M Hattori Tatsuya T Ito Mizuki M Atsuta Naoki N Nakamura Tomohiko T Hirayama Masaaki M Maesawa Satoshi S Katsuno Masahisa M Sobue Gen G

PloS one 20180105 1

<h4>Objective</h4>Severe hyposmia is a risk factor of dementia in Parkinson's disease (PD), while the underlying functional connectivity (FC) and brain volume alterations in PD patients with severe hyposmia (PD-SH) are unclear.<h4>Methods</h4>We examined voxel-based morphometric and resting state functional magnetic resonance imaging findings in 15 cognitively normal PD-SH, 15 cognitively normal patients with PD with no/mild hyposmia (PD-N/MH), and 15 healthy controls (HCs).<h4>Results</h4>Decre ...[more]

PMID: 29304050

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Project description:IntroductionThe current diagnosis of Parkinson's disease (PD) comorbidity with depression (DPD) largely depends on clinical evaluation. However, the modality may tend to lack precision in detecting PD with depression. A radiomic approach that combines functional connectivity and activity with clinical scores has the potential to achieve accurate and differential diagnosis between PD and DPD.MethodsIn this study, we aimed to employ the radiomic approach to extract large-scale features of functional connectivity and activity for differentiating among DPD, PD with no depression (NDPD), and healthy controls (HC). We extracted 6,557 features of five types from all subjects including clinical characteristics, resting-state functional connectivity (RSFC), amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC). Lasso, random forest, and support vector machine (SVM) were implemented for feature selection and dimension reduction based on the training sets, and the prediction performance for different methods in the testing sets was compared.ResultsThe results showed that nineteen features were selected for the group of DPD versus HC, 34 features were selected for the group of NDPD versus HC, and 17 features were retained for the group of DPD versus NDPD. In the testing sets, Lasso prediction achieved the accuracies of 0.95, 0.96, and 0.85 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively. Random forest achieved the accuracies of 0.90, 0.82, and 0.90 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively, while SVM yielded the accuracies of 1, 0.86 and 0.65 for distinguishing between DPD and HC, NDPD and HC, and DPD and NDPD, respectively.ConclusionsBy identifying aberrant functional connectivity and activity as potential biomarkers, the radiomic approach facilitates a deeper understanding and provides new insights into the pathophysiology of DPD to support the clinical diagnosis with high prediction accuracy.

Project description:Patients with Parkinson's disease (PD) frequently suffer from visual misperceptions and hallucinations, which are difficult to objectify and quantify. We aimed to develop an image recognition task to objectify misperceptions and to assess performance fluctuations in PD patients with and without self-reported hallucinations. Thirty-two non-demented patients with Parkinson's disease (16 with and 16 without self-reported visual hallucinations) and 25 age-matched healthy controls (HC) were tested. Participants performed a dynamic image recognition task with real and scrambled images. We assessed misperception scores and intra-individual variability in recognition times. To gain insight into possible neural mechanisms related to misperceptions and performance fluctuations we correlated resting state network connectivity to the behavioral outcomes in a subsample of Parkinson's disease patients (N?=?16). We found that PD patients with self-reported hallucinations (PD-VH) exhibited higher perceptual error rates, due to decreased perceptual sensitivity and not due to changed decision criteria. In addition, PD-VH patients exhibited higher intra-individual variability in recognition times than HC or PD-nonVH patients. Both, misperceptions and intra-individual variability were negatively correlated with resting state functional connectivity involving frontal and parietal brain regions, albeit in partly different subregions. Consistent with previous research suggesting that hallucinations arise from dysfunction in attentional networks, misperception scores correlated with reduced functional connectivity between the dorsal attention and salience network. Intra-individual variability correlated with decreased connectivity between somatomotor and right fronto-parietal networks. We conclude that our task can detect visual misperceptions that are more prevalent in PD-VH patients. In addition, fluctuating visual performance appear to be a signature of PD-VH patients, which might assist further studies of the underlying pathophysiological mechanisms and cognitive processes.

Dataset Information

Severe hyposmia and aberrant functional connectivity in cognitively normal Parkinson's disease.

Publications

Severe hyposmia and aberrant functional connectivity in cognitively normal Parkinson's disease.

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