Is either anosmia or constipation associated with cognitive dysfunction in Parkinson’s disease?

Objective To clarify the association of anosmia or constipation with cognitive dysfunction and disease severity in patients with Parkinson’s disease (PD). Methods Newly diagnosed patients with PD (less than 5 years) without a clinical diagnosis of dementia were included from February 2017 to August 2018. The subjects were further divided into subgroups based on whether anosmia occurred and the grade of constipation. The severity of PD motor symptoms was rated using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), and cognitive functions were evaluated by Montreal Cognitive Assessment (MoCA). Statistical analyses including t-tests, chi-square tests, multiple linear regression, and binary logistic regression were used to determine statistical significance. Results A total of 107 newly diagnosed PD patients were included in this study. The MoCA score was significantly lower in the anosmia group (p < 0.001). Constipation was associated with impaired olfaction in a post-hoc test. The correlation coefficient between MoCA and UPSIT score was 0.41 (p < 0.001). Total anosmia and age were associated with cognitive dysfunction (MoCA < 26) (odds ratio, 2.63, p = 0.003; 1.10, p < 0.001, respectively). The anosmia group had a higher MDS-UPDRS part 3 score with β coefficient of 7.30 (p = 0.02). Furthermore, grade 3 constipation was associated with a higher MDS-UPDRS total score with β coefficient of 14.88 (p = 0.02). Conclusions Anosmia but not constipation was associated with cognitive impairment in PD patients. Nevertheless, severe constipation was associated with impaired olfaction and PD disease severity. We suggest that the propagation of α-synuclein from the olfactory route is distinct from the enteric nervous system, but the intercommunication between these two routes is complex.

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Zonisamide Administration Improves Fatty Acid β-Oxidation in Parkinson’s Disease

Cells ◽

10.3390/cells8010014 ◽

2018 ◽

Vol 8 (1) ◽

pp. 14 ◽

Cited By ~ 2

Author(s):

Shin-Ichi Ueno ◽

Shinji Saiki ◽

Motoki Fujimaki ◽

Haruka Takeshige-Amano ◽

Taku Hatano ◽

...

Keyword(s):

Mass Spectrometry ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Disease Severity ◽

Rating Scale ◽

Statistical Significance ◽

Experimental Studies ◽

Time Of Flight ◽

Metabolome Analysis ◽

Flight Mass Spectrometry

Although many experimental studies have shown the favorable effects of zonisamide on mitochondria using models of Parkinson’s disease (PD), the influence of zonisamide on metabolism in PD patients remains unclear. To assess metabolic status under zonisamide treatment in PD, we performed a pilot study using a comprehensive metabolome analysis. Plasma samples were collected for at least one year from 30 patients with PD: 10 without zonisamide medication and 20 with zonisamide medication. We performed comprehensive metabolome analyses of plasma with capillary electrophoresis time-of-flight mass spectrometry and liquid chromatography time-of-flight mass spectrometry. We also measured disease severity using Hoehn and Yahr (H&Y) staging and the Unified Parkinson’s Disease Rating Scale (UPDRS) motor section, and analyzed blood chemistry. In PD with zonisamide treatment, 15 long-chain acylcarnitines (LCACs) tended to be increased, of which four (AC(12:0), AC(12:1)-1, AC(16:1), and AC(16:2)) showed statistical significance. Of these, two LCACs (AC(16:1) and AC(16:2)) were also identified by partial least squares analysis. There was no association of any LCAC with age, disease severity, levodopa daily dose, or levodopa equivalent dose. Because an upregulation of LCACs implies improvement of mitochondrial β-oxidation, zonisamide might be beneficial for mitochondrial β-oxidation, which is suppressed in PD.

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The Association of Olfactory Dysfunction With Depression, Cognition, and Disease Severity in Parkinson's Disease

Frontiers in Neurology ◽

10.3389/fneur.2021.779712 ◽

2021 ◽

Vol 12 ◽

Author(s):

Ting-Chun Fang ◽

Ming-Hong Chang ◽

Chun-Pai Yang ◽

Yi-Huei Chen ◽

Ching-Heng Lin

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Cognitive Impairment ◽

Disease Severity ◽

Rating Scale ◽

Statistical Significance ◽

Olfactory Dysfunction ◽

University Of Pennsylvania ◽

Disease Rating ◽

The University

Background: Non-motor subtypes of Parkinson's disease (PD) include the limbic, cognitive, and brainstem phenotype, which may have different pathological pathways with olfaction. In this work, we aim to clarify the association between olfactory dysfunction, depression, cognition, and disease severity in PD.Methods: A total of 105 PD subjects were included and divided into anosmia and non-anosmic groups, using the University of Pennsylvania Smell Identification Test (UPSIT). All patients were evaluated with the movement disorder society unified Parkinson's disease rating scale (MDS-UPDRS), the Beck depression inventory (BDI)-II, and the Montreal cognitive assessment (MoCA).Results: The BDI-II and UPSIT scores had a trend of reverse correlation without statistical significance (β-coefficient −0.12, p = 0.232). However, the odds ratio (OR) in anosmia was 2.74 (95% CI 1.01–7.46) for depression and 2.58 (95% CI 1.06–6.29) for cognitive impairment. For the MDS-UPDRS total and Part 3 score, the anosmia had a β-coefficient of 12.26 (95% CI 5.69–18.82) and 8.07 (95% CI 3.46–12.67), respectively. Neither depression nor cognitive impairment is associated with motor symptoms.Conclusion: More severe olfactory dysfunction in PD is associated with cognitive impairment and greater disease severity. Depression in PD may involve complex pathways, causing relatively weak association with olfactory dysfunction.

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Correlates of the discrepancy between objective and subjective cognitive functioning in non-demented patients with Parkinson’s disease

Journal of Neurology ◽

10.1007/s00415-021-10519-4 ◽

2021 ◽

Author(s):

Mattia Siciliano ◽

Lugi Trojano ◽

Rosa De Micco ◽

Valeria Sant’Elia ◽

Alfonso Giordano ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Linear Regression ◽

Cognitive Functioning ◽

Rating Scale ◽

Regression Analyses ◽

Chi Square ◽

Cognitive Measure ◽

Objective Evidence ◽

Cognitive Discrepancy

Abstract Background Subjective complaints of cognitive deficits are not necessarily consistent with objective evidence of cognitive impairment in Parkinson’s disease (PD). Here we examined the factors associated with the objective-subjective cognitive discrepancy. Methods We consecutively enrolled 90 non-demented patients with PD who completed the Parkinson’s Disease Cognitive Functional Rating Scale (subjective cognitive measure) and the Montreal Cognitive Assessment (MoCA; objective cognitive measure). The patients were classified as “Overestimators”, “Accurate estimators”, and “Underestimators” on the basis of the discrepancy between the objective vs. subjective cognitive measures. To identify the factors distinguishing these groups from each other, we used chi-square tests or one-way analyses of variance, completed by logistic and linear regression analyses. Results Forty-nine patients (54.45%) were classified as “Accurate estimators”, 29 (32.22%) as “Underestimators”, and 12 (13.33%) as “Overestimators”. Relative to the other groups, the “Underestimators” scored higher on the Fatigue Severity Scale (FSS), Beck Depression Inventory (BDI), and Parkinson Anxiety Scale (p < 0.01). Logistic regression confirmed that FSS and BDI scores distinguished the “Underestimators” group from the others (p < 0.05). Linear regression analyses also indicated that FSS and BDI scores positively related to objective-subjective cognitive discrepancy (p < 0.01). “Overestimators” scored lower than other groups on the MoCA’s total score and attention and working memory subscores (p < 0.01). Conclusion In more than 45% of consecutive non-demented patients with PD, we found a ‘mismatch’ between objective and subjective measures of cognitive functioning. Such discrepancy, which was related to the presence of fatigue and depressive symptoms and frontal executive impairments, should be carefully evaluated in clinical setting.

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Association between White Matter Lesions and Non-Motor Symptoms in Parkinson Disease

Neurodegenerative Diseases ◽

10.1159/000489311 ◽

2018 ◽

Vol 18 (2-3) ◽

pp. 127-132 ◽

Cited By ~ 3

Author(s):

Jeong-Yoon Lee ◽

Ji Sun Kim ◽

Wooyoung Jang ◽

Jinse Park ◽

Eungseok Oh ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

White Matter ◽

Parkinson Disease ◽

Cognitive Dysfunction ◽

Rating Scale ◽

White Matter Lesions ◽

Motor Dysfunction ◽

Motor Symptoms ◽

Non Motor Symptoms

Background: There are only few studies exploring the relationship between white matter lesions (WMLs) and non-motor symptoms in Parkinson disease (PD). This study aimed to investigate the association between WMLs and the severity of non-motor symptoms in PD. Methods: The severity of motor dysfunction, cognitive impairment, and non-motor symptoms was assessed by various scales in 105 PD patients. We used a visual semiquantitative rating scale and divided the subjects into four groups: no, mild, moderate, and severe WMLs. We compared the means of all scores between the four groups and analyzed the association between the severity of WMLs and the specific domain of non-motor symptoms. Results: The non-motor symptoms as assessed by the Non-Motor Symptoms Scale, Parkinson’s Disease Questionnaire (PDQ-39), Parkinson’s Disease Sleep Scale, Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Neuropsychiatric Inventory (NPI), and Parkinson Fatigue Scale (PFS) were significantly worse in the patients with moderate and severe WMLs than in those without WMLs. Compared with the no WML group, the scores for motor dysfunction were significantly higher in the mild, moderate, and severe WML groups. The scores for cognitive dysfunction were significantly higher in the patients with severe WMLs than in those without WMLs. The severity of WMLs showed linear associations with PFS, BDI, BAI, NPI, and PDQ-39 scores. The severity of WMLs also correlated linearly with scores for motor and cognitive dysfunction. Conclusions: Among the non-motor symptoms, fatigue, depression, anxiety, and quality of life were significantly affected by WMLs in PD. Confirmation of the possible role of WMLs in non-motor symptoms associated with PD in a prospective manner may be crucial not only for understanding non-motor symptoms but also for the development of treatment strategies.

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Stereopsis Deficits in Parkinson’s Disease and Their Clinical Implications

10.21203/rs.3.rs-106032/v1 ◽

2020 ◽

Author(s):

Fang Ba ◽

Tina T. Sang ◽

Jaleh Fatehi ◽

Wenjing He ◽

Emanuel Mostofi ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Disease Severity ◽

Rating Scale ◽

Disease Status ◽

Cognitive Status ◽

Control Group ◽

Motor Disorder ◽

Healthy Control ◽

Stereo Acuity

Abstract Background: Parkinson's disease (PD) is not exclusively a motor disorder. Among non-motor features, PD patients possess sensory visual dysfunctions. Stereopsis deficit can significantly impact patients' motor performance. However, it is not routinely tested, and its significance is under-investigated. Studying stereopsis using reliable 3D stimuli may help determine its implications in disease status in PD.The objective of the study is to investigate stereopsis abnormalities in PD with reliable and more physiological tools, and their correlation with indicators of PD severity. Methods: Twenty-four healthy control and 20 PD participants were first evaluated for visual acuity, visual field, contrast acuity, and stereoperception with 2D and Titmus stereotests, followed by the assessment with the 3D active shutter system. The correlation between stereopsis and disease severity, Unified Parkinson’s disease rating scale motor scores (UPDRS-III), levodopa equivalent daily dose (LEDD), course of disease and cognitive status were evaluated using univariate regression models. Results: Screening visual tests did not reveal any differences between PD and control group. With the 3D active shutter system, PD patients demonstrated significantly worse stereopsis (i.e p=0.002, 26 seconds of arc). There was a trend that UPDRS-III and LEDD negatively correlate with the stereo acuity, suggesting poorer stereoperception is related to disease severity. Preserved cognitive function correlated with more intact stereo acuity. Conclusion: With more reliable and physiological tools, PD patients exhibit poorer stereopsis. These deficits reflected PD motor and cognitive status. How stereopsis relates to gait, fall risks and navigation warrants more investigations in the future.

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CLOCK 3111T/C Variant Correlates with Motor Fluctuation and Sleep Disorders in Chinese Patients with Parkinson’s Disease

Parkinson s Disease ◽

10.1155/2018/4670380 ◽

2018 ◽

Vol 2018 ◽

pp. 1-6 ◽

Cited By ~ 2

Author(s):

Fan Lou ◽

Ming Li ◽

Xiaoguang Luo ◽

Yan Ren

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Sleep Disorders ◽

Sleep Disorder ◽

Rating Scale ◽

Clock Genes ◽

Motor Fluctuation ◽

Binary Logistic Regression ◽

Chinese Patients ◽

Binary Logistic Regression Analysis

Background. The clock genes controlling biological rhythm play an important role in the pathophysiology of aging. The purpose of this study was to determine whether there is an association between a variant of the circadian locomotor output cycles kaput (CLOCK) gene and circadian dysfunction of Parkinson’s disease (PD). Methods. Six hundred and forty-six cases of Parkinson’s disease from consecutive outpatients and inpatients ward from our hospital were included in this study. Kompetitive allele-specific PCR was used to determine the frequency distribution of genotypes and alleles. The examinations for the PD group were assessed in person in order to evaluate motor symptoms, cognitive function, sleep, and depression, including the Unified Parkinson’s Disease Rating Scale (UPDRS), Mini-Mental State Examination (MMSE), Pittsburgh Sleep Quality Index (PSQI), and 17-item Hamilton Rating Scale for Depression (HAMD-17). Results. Motor fluctuation (P<0.001) and sleep disorders (P=0.007) were significantly different between the two groups. These correlations persisted after adjusting for confounding risk factors by further binary logistic regression analysis, suggesting that the CLOCK 3111T/C variant was associated with motor fluctuation (OR = 1.080, P<0.001) and a subjective sleep disorder (OR = 1.130, P=0.037). Conclusion. The CLOCK 3111T/C variant can be an independent risk factor for motor fluctuation and sleep disorder in Parkinson’s disease.

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Muscle strength and executive function as complementary parameters for the assessment of impairment in Parkinson's disease

Arquivos de Neuro-Psiquiatria ◽

10.1590/0004-282x20130175 ◽

2013 ◽

Vol 71 (12) ◽

pp. 948-954

Author(s):

Dannyel Barbirato ◽

Alessandro Carvalho ◽

Narahyana Bom de Araujo ◽

Jose Vicente Martins ◽

Andrea Deslandes

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Executive Function ◽

Disease Severity ◽

Rating Scale ◽

Motor Impairment ◽

Cognitive Status ◽

Cognitive Capacity ◽

Response To Treatment ◽

The Relationship

Objective To evaluate the relationship between the quantitative results of functional and cognitive performance of patients with Parkinson's disease (PD) and disease severity; and to study the relationship between patients' functional and cognitive capacity and motor impairment (Unified Parkinson's Disease Rating Scale - UPDRS III). Method Twenty-nine subjects clinically diagnosed with PD were classified into three groups according to disease severity using the modified Hoehn and Yahr Scale (H&Y). They were submitted to functional (Senior Fitness Test) and neuropsychological tests. Stepwise regression analysis showed a significant association between H&Y and upper limb strength (r 2 =0.30; p=0.005) and executive function (r 2 =0.37; p=0.004). In relation to UPDRS III, there was a significant association between lower limb strength (r 2 =0.27; p=0.010) and global cognitive status (r 2 =0.24; p=0.024). Conclusion The implementation of simple tests of functional capacity associated with neuropsychological testing can help to assess disease severity and motor impairment, and can be used to monitor the response to treatment in PD.

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Quantitative analysis of cerebrovascular characteristics of Parkinson’s disease treated with acupuncture based on magnetic resonance angiography

Brain Science Advances ◽

10.26599/bsa.2021.9050015 ◽

2021 ◽

Vol 7 (2) ◽

pp. 141-154

Author(s):

Yuan Yang ◽

Le He ◽

Suhua Miao ◽

Rongsong Zhou ◽

Yuqi Zhang ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Blood Flow ◽

Magnetic Resonance ◽

Magnetic Resonance Angiography ◽

Rating Scale ◽

Statistical Significance ◽

Motor Symptoms ◽

Before And After ◽

Underlying Mechanisms

Background: Acupuncture has become an important alternative clinical treatment for Parkinson’s disease (PD), but its efficacy and the underlying mechanisms remain debatable. Using a newly developed magnetic resonance angiography (MRA) method that has higher sensitivity for smaller and distal vessels and a novel tool that can trace vessels and extract vascular features, the immediate effects of acupuncture on intracranial vessels and blood flow in patients with PD as well as correlations with clinical outcomes were quantitatively evaluated. Methods: Fifteen PD patients received acupuncture at the Dazhui and Fengchi acupoint positions. MRA was performed before and after 30 min of treatment. The cerebral blood flow (CBF) and the length, volume, diameter, and signal intensity of the intracranial internal carotid artery (ICA) and middle cerebral artery (MCA) were measured. The Unified Parkinson’s Disease Rating Scale part III (UPDRS-III) and Visual Analogue Scale (VAS) were used to evaluate the motor symptoms and the subjective feelings of discomfort. Results: Acupuncture significantly reduced UPDRS-III and VAS scores. No significant changes were noted in the overall CBF before and after treatment. However, there was a significant extension effect on the length of the intracranial ICA and MCA and the distal MCA, and a significant increase in the number of branches of the MCA was found. Although acupuncture tended to increase the total volume of the intracranial ICA and the volume of the MCA, no statistical significance was reached. The total intensity was not altered, but the intensity and diameter of the M1 segment were significantly increased, whereas the intensity of the MCA was decreased. A positive correlation between M1 intensity changes and UPDRS-III changes was found. Conclusions: Angiographic evaluation suggested that acupuncture had a significant effect on intracranial blood vessels, which is one possible mechanism for acupuncture improving the motor symptoms of PD.

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Predicting Longitudinal Disease Severity for Individuals with Parkinson’s Disease using Functional MRI and Machine Learning Prognostic Models

10.1101/2020.04.20.050971 ◽

2020 ◽

Author(s):

Kevin P. Nguyen ◽

Vyom Raval ◽

Alex Treacher ◽

Cooper Mellema ◽

Frank Yu ◽

...

Keyword(s):

Machine Learning ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Disease Severity ◽

Clinical Decision Making ◽

Rating Scale ◽

Neurodegenerative Disorder ◽

Clinical Severity ◽

Predictive Values ◽

Updrs Score

AbstractParkinson’s disease is the second most common neurodegenerative disorder and is characterized by the loss of ability to control voluntary movements. Predictive biomarkers of progression in Parkinson’s Disease are urgently needed to expedite the development of neuroprotective treatments and facilitate discussions about disease prognosis between clinicians and patients. Resting-state functional magnetic resonance imaging (rs-fMRI) shows promise in predicting progression, with derived measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF), having been previously been associated with current disease severity. In this work, ReHo and fALFF features from 82 Parkinson’s Disease subjects are used to train machine learning predictors of baseline clinical severity and progression at 1 year, 2 years, and 4 years follow-up as measured by the Movement Disorder Society Unified Depression Rating Scale (MDS-UPDRS) score. This is the first time that rs-fMRI and machine learning have been combined to predict future disease progression. The machine learning models explain up to 30.4% (R2 = 0.304) of the variance in baseline MDS-UPDRS scores, 55.8% (R2 = 0.558) of the variance in year 1 scores, and 47.1% (R2 = 0.471) of the variance in year 2 scores with high statistical significance (p < 0.0001). For distinguishing high- and low-progression individuals (MDS-UPDRS score above or below the median), the models achieve positive predictive values of up to 71% and negative predictive values of up to 84%. The models learn patterns of ReHo and fALFF measures that predict better and worse prognoses. Higher ReHo and fALFF in regions of the default motor network predicted lower current severity and lower future progression. The rs-fMRI features in the temporal lobe, limbic system, and motor cortex were also identified as predictors. These results present a potential neuroimaging biomarker that accurately predicts progression, which may be useful as a clinical decision-making tool and in future trials of neuroprotective treatments.

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