Urate and Homocysteine: Predicting Motor and Cognitive Changes in Newly Diagnosed Parkinson's Disease.
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ABSTRACT:
SUBMITTER: Sleeman I
PROVIDER: S-EPMC6597987 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionAnxiety and mild cognitive impairment (MCI) are prevalent non-motor manifestations of Parkinson's disease (PD). While few studies have demonstrated a possible link between cognitive dysfunction and anxiety in PD, to our knowledge, no studies have directly examined the association between them. This study investigated the association between anxiety and cognitive deficits in newly diagnosed PD patients.MethodsPatients with newly diagnosed PD (N = 185) were recruited from community and outpatient clinics. Anxiety was assessed using the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) clinician rated anxiety item, which has previously been validated against a standardized criteria for the diagnosis of anxiety disorders in PD. Participants scoring ≥2 were classified as anxious. A threshold of 1 SD below normative values (obtained from controls) was used to define cognitive impairment. Impairments in specific cognitive domains were identified as being >1 SD below controls in ≥1 test per domain.ResultsAfter controlling for age, education and motor severity, patients with anxiety were three times more likely to have cognitive impairment compared to those without anxiety (OR = 3.0, 95% CI = 1.2-7.3, p < 0.05). Patients with anxiety were more than twice as likely to be classified as having cognitive impairment due to impairment in the memory domain compared with PD without anxiety (OR = 2.3, 95% CI = 1.0-5.1, p < 0.05), whilst no associations were found between anxiety and performance on other cognitive domains.ConclusionThis study shows an association between anxiety and cognitive impairment (specifically memory impairment). Examining the neural basis of this association warrants future research in this developing field.
| S-EPMC5338650 | biostudies-literature
Project description:Background: Subjective cognitive complaints (SCCs) and mild cognitive impairment (MCI) are common among patients with Parkinson's disease (PD). However, the relationship between SCCs and MCI is not well understood. Herein, we aimed to investigate whether there are any differences in the prevalence and risk factors of SCCs between early PD patients with and without MCI. Methods: Overall, 108 newly diagnosed, untreated PD patients underwent comprehensive neuropsychological assessments. PD patients with mild cognitive impairment (PD-MCI) were diagnosed according to the MCI level II criteria. Furthermore, SCCs were measured with the Cognitive Complaints Interview (CCI). Logistic regression analysis, after adjusting for confounding variable, was performed in order to investigate risk factors of SCCs in PD-MCI patients and PD patients with normal cognition (PD-NC). Results: Furthermore, 42 (42.3%) participants reported SCCs and 53 (53.5%) participants were diagnosed with PD-MCI. The prevalence of SCCs in PD-MCI and PD-NC participants was 30.3% and 12.1%, respectively. Logistic regression analyses revealed that the presence of SCCs in PD-MCI group was significantly associated with Non-Motor Symptoms Questionnaire (NMSQ) score (OR = 1.340, 95%CI = 1.115-1.610, p = 0.002), while the presence of SCCs in PD-NC group was significantly associated with time of Stroop Color-Word Test card C (OR = 1.050, 95%CI = 1.009-1.119, p = 0.016). Conclusion: SCCs are frequent among patients with early PD. The prevalence and risk factor of SCCs are distinct in PD with and without MCI. These findings suggest that SCCs in early PD with different cognitive status appear to have different pathogenicity.
| S-EPMC8651703 | biostudies-literature
Project description:ObjectiveWe recently demonstrated that 998 features derived from a simple 7-minute smartphone test could distinguish between controls, people with Parkinson's and people with idiopathic Rapid Eye Movement sleep behavior disorder, with mean sensitivity/specificity values of 84.6-91.9%. Here, we investigate whether the same smartphone features can be used to predict future clinically relevant outcomes in early Parkinson's.MethodsA total of 237 participants with Parkinson's (mean (SD) disease duration 3.5 (2.2) years) in the Oxford Discovery cohort performed smartphone tests in clinic and at home. Each test assessed voice, balance, gait, reaction time, dexterity, rest, and postural tremor. In addition, standard motor, cognitive and functional assessments and questionnaires were administered in clinic. Machine learning algorithms were trained to predict the onset of clinical outcomes provided at the next 18-month follow-up visit using baseline smartphone recordings alone. The accuracy of model predictions was assessed using 10-fold and subject-wise cross validation schemes.ResultsBaseline smartphone tests predicted the new onset of falls, freezing, postural instability, cognitive impairment, and functional impairment at 18 months. For all outcome predictions AUC values were greater than 0.90 for 10-fold cross validation using all smartphone features. Using only the 30 most salient features, AUC values greater than 0.75 were obtained.InterpretationWe demonstrate the ability to predict key future clinical outcomes using a simple smartphone test. This work has the potential to introduce individualized predictions to routine care, helping to target interventions to those most likely to benefit, with the aim of improving their outcome.
| S-EPMC6689691 | biostudies-literature
Project description:Mild cognitive impairment in Parkinson's disease is associated with progression to dementia (Parkinson's disease dementia) in a majority of patients. Determining structural imaging biomarkers associated with prodromal Parkinson's disease dementia may allow for the earlier identification of those at risk, and allow for targeted disease modifying therapies. One hundred and five non-demented subjects with newly diagnosed idiopathic Parkinson's disease and 37 healthy matched controls had serial 3 T structural magnetic resonance imaging scans with clinical and neuropsychological assessments at baseline, which were repeated after 18 months. The Movement Disorder Society Task Force criteria were used to classify the Parkinson's disease subjects into Parkinson's disease with mild cognitive impairment (n = 39) and Parkinson's disease with no cognitive impairment (n = 66). Freesurfer image processing software was used to measure cortical thickness and subcortical volumes at baseline and follow-up. We compared regional percentage change of cortical thinning and subcortical atrophy over 18 months. At baseline, cases with Parkinson's disease with mild cognitive impairment demonstrated widespread cortical thinning relative to controls and atrophy of the nucleus accumbens compared to both controls and subjects with Parkinson's disease with no cognitive impairment. Regional cortical thickness at baseline was correlated with global cognition in the combined Parkinson's disease cohort. Over 18 months, patients with Parkinson's disease with mild cognitive impairment demonstrated more severe cortical thinning in frontal and temporo-parietal cortices, including hippocampal atrophy, relative to those with Parkinson's disease and no cognitive impairment and healthy controls, whereas subjects with Parkinson's disease and no cognitive impairment showed more severe frontal cortical thinning compared to healthy controls. At baseline, Parkinson's disease with no cognitive impairment converters showed bilateral temporal cortex thinning relative to the Parkinson's disease with no cognitive impairment stable subjects. Although loss of both cortical and subcortical volume occurs in non-demented Parkinson's disease, our longitudinal analyses revealed that Parkinson's disease with mild cognitive impairment shows more extensive atrophy and greater percentage of cortical thinning compared to Parkinson's disease with no cognitive impairment. In particular, an extension of cortical thinning in the temporo-parietal regions in addition to frontal atrophy could be a biomarker in therapeutic studies of mild cognitive impairment in Parkinson's disease for progression towards dementia.
| S-EPMC4671477 | biostudies-literature
Project description:BackgroundStudies attempting to elucidate an association between homocysteine and symptom progression in Parkinson's disease (PD) have had largely discrepant findings. This study aimed to investigate elevated serum homocysteine levels and symptom progression in a cohort of PD patients.MethodsSerum homocysteine, folate, and vitamin B12 levels were measured in 205 people with PD and 78 age-matched healthy controls. People with Parkinson's disease underwent a battery of clinical assessments to evaluate symptom severity, including motor (MDS-UPDRS) and cognitive (ACE-R) assessments. Multivariate generalised linear models were created, controlling for confounding variables, and were used to determine whether serum markers are associated with various symptom outcome measures.ResultsPeople with Parkinson's disease displayed significantly elevated homocysteine levels (p < 0.001), but not folate or vitamin B12 levels, when compared to healthy controls. A significant positive correlation between homocysteine and MDS-UPDRS III score was identified in males with Parkinson's disease (r s = 0.319, p < 0.001), but not in females, whereas a significant negative correlation between homocysteine levels and total ACE-R score was observed in females with Parkinson's disease (r s = -0.449, p < 0.001), but not in males. Multivariate general linear models confirmed that homocysteine was significantly predictive of MDS-UPDRS III score in male patients (p=0.004) and predictive of total ACE-R score in female patients (p=0.021).ConclusionElevated serum homocysteine levels are associated with a greater motor impairment in males with Parkinson's disease and poorer cognitive performance in females with Parkinson's disease. Our gender-specific findings may help to explain previous discrepancies in the literature surrounding the utility of homocysteine as a biomarker in PD.
| S-EPMC6560330 | biostudies-literature
Project description:BackgroundCognitive impairment is a common non-motor symptom in patients with Parkinson's disease (PD). Mild cognitive impairment (MCI) is also prevalent in nondemented PD patients, even in newly diagnosed PD patients. The possible impacts of MCI on brain function activities for PD patients need more investigation, and the potential of emerging technologies for detecting underlying pathophysiology of cognitive signs in PD can be further improved.MethodForty-seven newly diagnosed drug-naïve PD patients (28 PD-MCI patients and 19 PD patients with cognitively unimpaired (PD-CU)) and 28 healthy controls (HCs) underwent resting-state functional MRI. The connectivity patterns of specific networks were investigated through the independent component analysis among PD-MCI, PD-CU and HCs groups.ResultsThe independent component analysis revealed significantly decreased functional connectivity (FC) of the default mode network, visual network and sensorimotor network in the PD-MCI subgroup compared with the HC group. Furthermore, FC of the default mode network was positively correlated with memory scores from the brief visuospatial memory test-revised, and FC of the visual network was positively correlated with visuospatial scores from the clock copying test in the PD-MCI group. In all patients with PD, FC of the sensorimotor network negatively correlated with motor severity scores from the Unified PD Rating Scale (UPDRS) part III. On the other hand, the potential damage was more likely to occur in FC between the sensorimotor network and limbic network, and between the ventral attention network and visual network in all PD patients.ConclusionsNewly diagnosed drug-naïve PD-MCI patients showed characteristic damage of FC within the default mode network, visual network and sensorimotor network, and all PD patients presented impaired FC between the sensorimotor network and limbic network, and FC between the ventral attention network and visual network. These network-wide functional aberrations may underline the pathophysiology of PD.
| S-EPMC8386092 | biostudies-literature
Project description:IntroductionSeveral treatment guidelines for Parkinson's disease (PD) had been proposed in recent decades. The aim of current study was to investigate the initial medication utilized in newly diagnosed PD subjects in Taiwan during an eleven-year period.MethodsA total of 7,550 patients with newly diagnosed Parkinsonism were retrospectively enrolled from the National Health Insurance Research Database of Taiwan from 2000 to 2010. After excluding patients at risk of secondary or atypical Parkinsonism, those never receiving medication or having incomplete data, 1,645 subjects were included. The participants were then divided into four treating regimen groups, namely levodopa (LD) only group, dopamine agonist (DA) only group, LD+DA group, and No-LD, No-DA group. The demographic data and medication retention rate were compared across the four treatment groups.ResultsLD only and No-LD, No-DA regimens were the main initial choice of PD treatment in Taiwan. LD containing drugs were more often prescribed to the elderly population than the other two treatment regimens, while No-LD, No-DA medication was the major initial choice for younger patients. DA only regimen occupied only 3-4% of the initial PD prescriptions and was given predominantly by neurologists. Over the eleven-year period, there is a trend for the middle-aged population to receive medication containing LD as initial treatment. The one year retention rate of anti-Parkinsonism medication was around 30-50% in our population. Age, polypharmacy, change of one-year daily levodopa equivalent dosage and newly onset of dementia, stroke and psychiatric diseases all affect drug compliance in PD patients.ConclusionsThis is the first long-term study to explore initial pharmacotherapies in an Asian PD population. We hope to provide evidence for adjusting government policies and public education of physicians and PD patients in the future.
| S-EPMC4164642 | biostudies-literature
Project description:Olfactory dysfunction is a robust and early sign for Parkinson's disease (PD). Previous studies have revealed its association with dementia and related neural changes in PD. Yet, how olfactory dysfunction affects white matter (WM) microstructure in newly diagnosed and untreated PD remains unclear. Here we comprehensively examined WM features using unbiased whole-brain analyses. 88 newly diagnosed PD patients without dementia (70 with hyposmia and 18 without hyposmia) and 33 healthy controls underwent clinical assessment and diffusion tensor imaging (DTI) scanning. Tract-based special statistics (TBSS), graph-theoretic methods and network-based statistics (NBS) were used to compare regional and network-related WM features between groups. TBSS analysis did not show any differences in fractional anisotropy and mean diffusivity between groups. Compared with controls, PD patients without hyposmia showed a significant decrease in global efficiency, whilst PD patients with hyposmia exhibited significantly reduced global and local efficiency and additionally a disrupted connection between the right medial orbitofrontal cortex and left rectus and had poorer frontal-related cognitive functioning. These results demonstrate that hyposmia-related WM changes in early PD only occur at the network level. The confined disconnectivity between the bilateral olfactory circuitry may serve as a biomarker for olfactory dysfunction in early PD.
| S-EPMC5624890 | biostudies-literature
Project description:BackgroundParkinson's disease is associated with an increased incidence of cognitive impairment and dementia. Predicting who is at risk of cognitive decline early in the disease course has implications for clinical prognosis and for stratification of participants in clinical trials. We assessed the use of clinical information and biomarkers as predictive factors for cognitive decline in patients with newly diagnosed Parkinson's disease.MethodsThe Parkinson's Progression Markers Initiative (PPMI) study is a cohort study in patients with newly diagnosed Parkinson's disease. We evaluated cognitive performance (Montreal Cognitive Assessment [MoCA] scores), demographic and clinical data, APOE status, and biomarkers (CSF and dopamine transporter [DAT] imaging results). Using change in MoCA scores over 2 years, MoCA scores at 2 years' follow-up, and a diagnosis of cognitive impairment (combined mild cognitive impairment or dementia) at 2 years as outcome measures, we assessed the predictive values of baseline clinical variables and separate or combined additions of APOE status, DAT imaging, and CSF biomarkers. We did univariate and multivariate linear analyses with MoCA change scores between baseline and 2 years, and with MoCA scores at 2 years as dependent variables, using backwards linear regression analysis. Additionally, we constructed a prediction model for diagnosis of cognitive impairment using logistic regression analysis.Findings390 patients with Parkinson's disease recruited between July 1, 2010, and May 31, 2013, and for whom data on MoCA scores at baseline and 2 years were available. In multivariate analyses, baseline age, University of Pennsylvania Smell Inventory Test (UPSIT) scores, CSF amyloid - (Aβ42) to t-tau ratio, and APOE status were associated with change in MoCA scores over time. Baseline age, MoCA and UPSIT scores, and CSF Aβ42 to t-tau ratio were associated with MoCA score at 2 years (using a backwards p-removal threshold of 0·1). Accuracy of prediction of cognitive impairment using age alone (area under the curve 0·68, 95% CI 0·60-0·76) significantly improved by addition of clinical scores (UPSIT, Rapid Eye Movement Sleep Behaviour Disorder Screening Questionnaire [RBDSQ], Geriatric Depression Scale, and Movement Disorder Society Unified Parkinson's Disease Rating Scale motor scores; 0·76, 0·68-0·83), CSF variables (0·74, 0·68-0·81), or DAT imaging results (0·76, 0·68-0·83). In combination, the five variables showing the most significant associations with cognitive impairment (age, UPSIT, RBDSQ, CSF Aβ42, and caudate uptake on DAT imaging) allowed prediction of cognitive impairment at 2 years (0·80, 0·74-0·87; p=0·0003 compared to age alone).InterpretationIn newly diagnosed Parkinson's disease, the occurrence of cognitive impairment at 2 year follow-up can be predicted with good accuracy using a model combining information on age, non-motor assessments, DAT imaging, and CSF biomarkers.FundingNone.
| S-EPMC5377592 | biostudies-literature
Project description:ObjectiveThe objective of this study was to develop valid prognostic models to predict mortality, dependency, and "death or dependency" for use in newly diagnosed Parkinson's disease (PD).MethodsThe models were developed in the Parkinsonism Incidence in North-East Scotland study (UK, 198 patients) and validated in the ParkWest study (Norway, 192 patients), cohorts that attempted to identify and follow-up all new PD cases in the study area. Dependency was defined using the Schwab & England scale. We selected variables measured at time of diagnosis to include in the models. Internal validation and external validation were performed by calculating C-statistics (discrimination) and plotting observed versus predicted risk in quantiles of predicted risk (calibration).ResultsOlder age, male sex, increased severity of axial features, and Charlson comorbidity index were independent prognostic factors in the mortality model. Increasing age, higher smoking history, increased severity of axial features, and lower MMSE score were independent predictors in the models of dependency and "death or dependency." Each model had very good internal calibration and very good or good discrimination (internal and external C-statistics for the models were 0.73-0.75 and 0.68-0.78, respectively). Although each model clearly separated patients into groups according to risk, they tended to overestimate risk in ParkWest. The models were recalibrated to the baseline risk in the ParkWest study and then calibrated well in this cohort.ConclusionsWe have developed prognostic models for predicting medium-term risk of important clinical outcomes in newly diagnosed PD. These models have validity for use for stratification of randomization, confounder adjustment, and case-mix correction, but they are inadequate for individualized prognostication. © 2017. The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
| S-EPMC5813201 | biostudies-literature