Decline In Parkinson's Disease Research Articles

Peripheral biomarkers of Parkinson’s disease and its correlation with clinical symptoms: a case-control study

BackgroundInflammation significantly impacts Parkinson’s disease (PD), yet the intricate relationship between inflammatory markers and PD remains elusive.ObjectiveTo identify the peripheral biomarkers of PD and its correlation with the motor and non-motor symptoms of PD.Methods79 PD patients and 65 controls were included in this study. Clinical information and the serum levels of IL-8, IL-27, IL-33, β-NGF, AgRP, and TRAILR2 in the participants were collected. Appropriate scales were used to assess the symptoms of PD. For the factors with significant differences in the two groups, multivariable logistic regression was used to determine its relationship with PD. Moreover, spearman correlation was conducted to explore the correlation between the factors and PD related symptoms. The IL-27 level was compared between the cognitively healthy PD group and the mild cognitive impairment in PD (PD-MCI). The serum level of TRAILR2 was positively correlated with age and was not associated with other clinical characteristics related to PD.ResultsCompared to controls, the serum levels of IL-27(P = 0.013) were increased whereas the levels of TRAILR2(P = 0.008) were decreased in PD patients. IL-8, IL-33, β-NGF, and AgRP showed no significant differences between the two groups. After controlling for the other variables, IL-27 was considered as an independent risk factor for PD in the multivariable logistic regression model. The receiver operating characteristic (ROC) curve for diagnosing PD with IL-27 yielded an area under the curve (AUC) of 0.621. Additionally, IL-27 level in PD patients was positively correlated with age, the disease duration, LEDD and negatively correlated with the MoCA scores. However, no significant difference was found in IL-27 levels between cognitively healthy PD and PD-MCI groups.ConclusionElevated serum IL-27 was a risk factor for PD and positively correlated with the cognitive decline in PD.

Mitochondrial Dysfunction in Parkinson's Disease: A Contribution to Cognitive Impairment?

Among the non-motor symptoms associated with Parkinson's disease (PD), cognitive impairment is one of the most common and disabling. It can occur either early or late during the disease, and it is heterogeneous in terms of its clinical manifestations, such as Subjective Cognitive Dysfunction (SCD), Mild Cognitive Impairment (MCI), and Parkinson's Disease Dementia (PDD). The aim of the present review is to delve deeper into the molecular mechanisms underlying cognitive decline in PD. This is extremely important to delineate the guidelines for the differential diagnosis and prognosis of the dysfunction, to identify the molecular and neuronal mechanisms involved, and to plan therapeutic strategies that can halt cognitive impairment progression. Specifically, the present review will discuss the pathogenetic mechanisms involved in the progression of cognitive impairment in PD, with attention to mitochondria and their contribution to synaptic dysfunction and neuronal deterioration in the brain regions responsible for non-motor manifestations of the disease.

Temporal ordering of cognitive impairment in Parkinson's disease patients based on disease progression models

IntroductionIdentifying Parkinson's disease (PD) patients at risk of cognitive decline is crucial for enhancing clinical interventions. While several models predicting cognitive decline in PD exist, a new machine learning framework called disease progression models (DPMs) offers a data-driven approach to understand disease evolution. MethodsWe enrolled 423 PD patients and 196 healthy controls from the Parkinson's Progression Markers Initiative (PPMI). Our study encompassed a range of biomarkers, including motor, neurocognitive, and neuroimaging evaluations at baseline and annually. A methodology was employed to select optimal combinations of biomarkers for constructing DPMs with superior predictive capabilities for both diagnosing and estimating conversion times toward cognitive decline. ResultsAt baseline, the approach showed excellent performance in identifying individuals at high risk of cognitive decline within the first five years. Furthermore, the proposed timeline from cognitive impairment to dementia was also used to explore clinical events such as the onset of cognitive impairment, the development of dementia or amyloid pathology. The presence of amyloid pathology did not alter the progression of cognitive impairment among PD patients. ConclusionsNeuropsychological measures and certain biomarkers, including cerebrospinal fluid (CSF) amyloid beta 42 (Aβ42) and dopamine transporter deficits, can be used to predict cognitive decline and estimate a timeline from cognitive impairment to dementia, with amyloid pathology preceding the onset of dementia in many cases. Our DPMs suggested that the profiles of CSF Aβ42 and phosphorylated tau in PD patients may differ from those in aging patients and those with Alzheimer's disease.

Cholinergic Basal Forebrain Integrity and Cognition in Parkinson's Disease: A Reappraisal of Magnetic Resonance Imaging Evidence.

Cognitive impairment is a well-recognized and debilitating symptom of Parkinson's disease (PD). Degradation in the cortical cholinergic system is thought to be a key contributor. Both postmortem and in vivo cholinergic positron emission tomography (PET) studies have provided valuable evidence of cholinergic system changes in PD, which are pronounced in PD dementia (PDD). A growing body of literature has employed magnetic resonance imaging (MRI), a noninvasive, more cost-effective alternative to PET, to examine cholinergic system structural changes in PD. This review provides a comprehensive discussion of the methodologies and findings of studies that have focused on the relationship between cholinergic basal forebrain (cBF) integrity, based on T1- and diffusion-weighted MRI, and cognitive function in PD. Nucleus basalis of Meynert (Ch4) volume has been consistently reduced in cognitively impaired PD samples and has shown potential utility as a prognostic indicator for future cognitive decline. However, the extent of structural changes in Ch4, especially in early stages of cognitive decline in PD, remains unclear. In addition, evidence for structural change in anterior cBF regions in PD has not been well established. This review underscores the importance of continued cross-sectional and longitudinal research to elucidate the role of cholinergic dysfunction in the cognitive manifestations of PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The angiotensin (1–7) glycopeptide PNA5 improves cognition in a chronic progressive mouse model of Parkinson's disease through modulation of neuroinflammation

Cognitive decline in Parkinson's Disease (PD) is a prevalent and undertreated aspect of disease. Currently, no therapeutics adequately improve this aspect of disease. It has been previously shown that MAS receptor agonism via the glycosylated Angiotensin (1–7) peptide, PNA5, effectively reduces cognitive decline in models of vascular contributions to cognitive impairment and dementia (VCID). PNA5 has a brain/plasma ratio of 0.255 indicating good brain penetration. The goal of the present study was to determine if (1) systemic administration of PNA5 rescued cognitive decline in a mouse model of PD, and (2) if improvements in cognitive status could be correlated with changes to histopathological or blood plasma-based changes. Mice over-expressing human, wild-type α-synuclein (αSyn) under the Thy1 promoter (Thy1-αSyn mice, “line 61”) were used as a model of PD with cognitive decline. Thy1-αSyn mice were treated with a systemic dose of PNA5, or saline (1 mg/kg/day) beginning at 4 months of age and underwent behavioral testing at 6 months, compared to WT. Subsequently, mice brains were analyzed for changes to brain pathology, and blood plasma was examined with a Multiplex Immunoassay for peripheral cytokine changes. Treatment with PNA5 reversed cognitive dysfunction measured by Novel Object Recognition and spontaneous alteration in a Y-maze in Thy1-αSyn mice. PNA5 treatment was specific to cognitive deficits, as fine-motor disturbances were unchanged. Enhanced cognition was associated with decreases in hippocampal inflammation and reductions in circulating levels of Macrophage Induced Protein (MIP-1β). Additionally, neuronal loss was blunted within the CA3 hippocampal region of PNA5-treated αsyn mice. These data reveal that PNA5 treatment reduces cognitive dysfunction in a mouse model of PD. These changes are associated with decreased MIP-1β levels in plasma identifying a candidate biomarker for target engagement. Thus, PNA5 treatment could potentially fill the therapeutic gap for cognitive decline in PD.

Mapping brain morphology to cognitive deficits: a study on PD-CRS scores in Parkinson's disease with mild cognitive impairment.

The Parkinson's Disease-Cognitive Rating Scale (PD-CRS) is a widely used tool for detecting mild cognitive impairment (MCI) in Parkinson's Disease (PD) patients, however, the neuroanatomical underpinnings of this test's outcomes require clarification. This study aims to: (a) investigate cortical volume (CVol) and cortical thickness (CTh) disparities between PD patients exhibiting mild cognitive impairment (PD-MCI) and those with preserved cognitive abilities (PD-IC); and (b) identify the structural correlates in magnetic resonance imaging (MRI) of overall PD-CRS performance, including its subtest scores, within a non-demented PD cohort. This study involved 51 PD patients with Hoehn & Yahr stages I-II, categorized into two groups: PD-IC (n = 36) and PD-MCI (n = 15). Cognitive screening evaluations utilized the PD-CRS and the Montreal Cognitive Assessment (MoCA). PD-MCI classification adhered to the Movement Disorder Society Task Force criteria, incorporating extensive neuropsychological assessments. The interrelation between brain morphology and cognitive performance was determined using FreeSurfer. Vertex-wise analysis of the entire brain demonstrated a notable reduction in CVol within a 2,934 mm2 cluster, encompassing parietal and temporal regions, in the PD-MCI group relative to the PD-IC group. Lower PD-CRS total scores correlated with decreased CVol in the middle frontal, superior temporal, inferior parietal, and cingulate cortices. The PD-CRS subtests for Sustained Attention and Clock Drawing were associated with cortical thinning in distinct regions: the Clock Drawing subtest correlated with changes in the parietal lobe, insula, and superior temporal cortex morphology; while the PD-CRS frontal-subcortical scores presented positive correlations with CTh in the transverse temporal, medial orbitofrontal, superior temporal, precuneus, fusiform, and supramarginal regions. Additionally, PD-CRS subtests for Semantic and Alternating verbal fluency were linked to CTh changes in orbitofrontal, temporal, fusiform, insula, and precentral regions. PD-CRS performance mirrors neuroanatomical changes across extensive fronto-temporo-parietal areas, covering both lateral and medial cortical surfaces, in PD patients without dementia. The observed changes in CVol and CTh associated with this cognitive screening tool suggest their potential as surrogate markers for cognitive decline in PD. These findings warrant further exploration and validation in multicenter studies involving independent patient cohorts.

Prediction of Cognitive Heterogeneity in Parkinson's Disease: A 4-Year Longitudinal Study Using Clinical, Neuroimaging, Biological and Electrophysiological Biomarkers.

Cognitive impairment in Parkinson's disease (PD) can show a very heterogeneous trajectory among patients. Here, we explored the mechanisms involved in the expression and prediction of different cognitive phenotypes over 4 years. In 2 independent cohorts (total n = 475), we performed a cluster analysis to identify trajectories of cognitive progression. Baseline and longitudinal level II neuropsychological assessments were conducted, and baseline structural magnetic resonance imaging, resting electroencephalogram and neurofilament light chain plasma quantification were carried out. Linear mixed-effects models were used to study longitudinal changes. Risk of mild cognitive impairment and dementia were estimated using multivariable hazard regression. Spectral power density from the electroencephalogram at baseline and source localization were computed. Two cognitive trajectories were identified. Cluster 1 presented stability (PD-Stable) over time, whereas cluster 2 showed progressive cognitive decline (PD-Progressors). The PD-Progressors group showed an increased risk for evolving to PD mild cognitive impairment (HR 2.09; 95% CI 1.11-3.95) and a marked risk for dementia (HR 4.87; 95% CI 1.34-17.76), associated with progressive worsening in posterior-cortical-dependent cognitive processes. Both clusters showed equivalent clinical and sociodemographic characteristics, structural magnetic resonance imaging, and neurofilament light chain levels at baseline. Conversely, the PD-Progressors group showed a fronto-temporo-occipital and parietal slow-wave power density increase, that was in turn related to worsening at 2 and 4 years of follow-up in different cognitive measures. In the absence of differences in baseline cognitive function and typical markers of neurodegeneration, the further development of an aggressive cognitive decline in PD is associated with increased slow-wave power density and with a different profile of worsening in several posterior-cortical-dependent tasks. ANN NEUROL 2024;96:981-993.

The Parkinson's Disease Composite of Executive Functioning: A Measure for Detecting Cognitive Decline in Clinical Trials.

Executive functioning is one of the first domains to be impaired in Parkinson disease (PD), and the majority of patients with PD eventually develop dementia. Thus, developing a cognitive endpoint measure specifically assessing executive functioning is critical for PD clinical trials. The objective of this study was to develop a cognitive composite measure that is sensitive to decline in executive functioning for use in PD clinical trials. We used cross-sectional and longitudinal follow-up data from PD participants enrolled in the PD Cognitive Genetics Consortium, a multicenter setting focused on PD. All PD participants with Trail Making Test, Digit Symbol, Letter-Number Sequencing, Semantic Fluency, and Phonemic Fluency neuropsychological data collected from March 2010 to February 2020 were included. Baseline executive functioning data were used to create the Parkinson's Disease Composite of Executive Functioning (PaCEF) through confirmatory factor analysis. We examined the changes in the PaCEF over time, how well baseline PaCEF predicts time to cognitive progression, and the required sample size estimates for PD clinical trials. PaCEF results were compared with the Montreal Cognitive Assessment (MoCA), individual tests forming the PaCEF, and tests of visuospatial, language, and memory functioning. A total of 841 participants (251 no cognitive impairment [NCI], 480 mild cognitive impairment [MCI], and 110 dementia) with baseline data were included, of which the mean (SD) age was 67.1 (8.9) years and 270 were women (32%). Five hundred forty five PD participants had longitudinal neuropsychological data spanning 9 years (mean [SD] 4.5 [2.2] years) and were included in analyses examining cognitive decline. A 1-factor model of executive functioning with excellent fit (comparative fit index = 0.993, Tucker-Lewis index = 0.989, and root mean square error of approximation = 0.044) was used to calculate the PaCEF. The average annual change in PaCEF ranged from 0.246 points per year for PD-NCI participants who remained cognitively unimpaired to -0.821 points per year for PD-MCI participants who progressed to dementia. For PD-MCI, baseline PaCEF, but not baseline MoCA, significantly predicted time to dementia. Sample size estimates were 69%-73% smaller for PD-NCI trials and 16%-19% smaller for PD-MCI trials when using the PaCEF rather than MoCA as the endpoint. The PaCEF is a sensitive measure of executive functioning decline in PD and will be especially beneficial for PD clinical trials.

Genetic background of cognitive decline in Parkinson's disease

Parkinson's disease (PD) is a complex disorder that is influenced by multiple genetic risk factors. There is a significant heterogeneity in PD presentation, both pathologically and clinically. Some of the most common and important symptoms affecting the patient are cognitive impairment and dementia. However, the genetic and biological basis underlying the differences in cognitive profiles, including the development of dementia in PD, is not yet well understood. Understanding the role of genes in cognitive outcomes is crucial for effective patient counseling and treatment. Research on familial PD has discovered more than 20 genes that can cause the disease. The identified genes responsible for familial cases of PD are LRRK2, PARK7, PINK1, PRKN, or SNCA gene, although there may be other genes that also contribute. Additionally, some of these genes may also play a role in cases that were previously thought to be sporadic. Currently, numerous well-described genes increase the risk of cognitive decline in PD, each with varying levels of penetrance. The aim of this review is to identify the relevant genetic factors that contribute to differences in cognition. We discuss the genes that may affect cognition and the challenges in establishing a clear genetic diagnostic and prognostic assessment. This article aims to demonstrate the complexity of the genetic background of cognition in PD and to present the different types of genotype changes that can impact cognition through various neurobiological mechanisms.

Machine learning for predicting cognitive decline within five years in Parkinson's disease: Comparing cognitive assessment scales with DAT SPECT and clinical biomarkers.

Parkinson's disease (PD) is an age-related neurodegenerative condition characterized mostly by motor symptoms. Although a wide range of non-motor symptoms (NMS) are frequently experienced by PD patients. One of the important and common NMS is cognitive impairment, which is measured using different cognitive scales. Monitoring cognitive impairment and its decline in PD is essential for patient care and management. In this study, our goal is to identify the most effective cognitive scale in predicting cognitive decline over a 5-year timeframe initializing clinical biomarkers and DAT SPECT. Machine Learning has previously shown superior performance in image and clinical data classification and detection. In this study, we propose to use machine learning with different types of data, such as DAT SPECT and clinical biomarkers, to predict PD-CD based on various cognitive scales. We collected 330 DAT SPECT images and their clinical data in baseline, years 2,3,4, and 5 from Parkinson's Progression Markers Initiative (PPMI). We then designed a 3D Autoencoder to extract deep radiomic features (DF) from DAT SPECT images, and we then concatenated it with 17 clinical features (CF) to predict cognitive decline based on Montreal Cognitive Assessment (MoCA) and The Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS-I). The utilization of MoCA as a cognitive decline scale yielded better performance in various years compared to MDS-UPDRS-I. In year 4, the application of the deep radiomic feature resulted in the highest achievement, with a cross-validation AUC of 89.28, utilizing the gradient boosting classifier. For the MDS-UPDRS-I scale, the highest achievement was obtained by utilizing the deep radiomic feature, resulting in a cross-validation AUC of 81.34 with the random forest classifier. The study findings indicate that the MoCA scale may be a more effective predictor of cognitive decline within 5 years compared to MDS-UPDRS-I. Furthermore, deep radiomic features had better performance compared to sole clinical biomarkers or clinical and deep radiomic combined. These results suggest that using the MoCA score and deep radiomic features extracted from DAT SPECT could be a promising approach for identifying individuals at risk for cognitive decline in four years. Future research is needed to validate these findings and explore their utility in clinical practice.

Diffusion Tensor Imaging-Along the Perivascular-Space Index Is Associated with Disease Progression in Parkinson's Disease.

The glymphatic clearance pathway is a waste clearance system that allows for removal of soluble proteins such as amyloid β (Aβ) from the brain. Higher Aβ levels are associated with cognitive dysfunction in Parkinson's disease (PD). Diffusion tensor imaging-along the perivascular space (DTI-ALPS) is an imaging measure proposed to indirectly measure glymphatic function. Evaluate differences in DTI-ALPS-index between PD and healthy controls (HC) and characterize relationships between this proposed measure of glymphatic clearance, cognition, and disease severity in PD. PD (n = 32) and HC (n = 23) participants underwent brain imaging to assess DTI-ALPS. PD participants were classified as PD-normal cognition (PD-NC; n = 20) or PD-mild cognitive impairment (PD-MCI; n = 12) based on a Level II comprehensive cognitive assessment. A subgroup of PD participants (n = 21) returned for annual assessments for up to 4 years after baseline. Longitudinal outcomes included changes in performance on the comprehensive cognitive assessment and changes in the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). PD participants had lower DTI-ALPS-index compared to HC. PD participants classified as PD-MCI had significantly lower DTI-ALPS-index compared to PD-NC. Lower DTI-ALPS-index at baseline was associated with longitudinal cognitive decline and worse longitudinal disease severity. Glymphatic clearance, as measured with DTI-ALPS, has potential to serve as a marker of longitudinal disease progression. Interventions targeting glymphatic function should be explored for potential to slow cognitive decline in PD. © 2024 International Parkinson and Movement Disorder Society.

Assessment tools for cognitive performance in Parkinson's disease and its genetic contributors.

We have shown that genetic factors associating with motor progression of Parkinson's disease (PD), but their roles in cognitive function is poorly understood. One reason is that while cognitive performance in PD can be evaluated by various cognitive scales, there is no definitive guide indicating which tool performs better. Data were obtained from the Parkinson's Progression Markers Initiative, where cognitive performance was assessed using five cognitive screening tools, including Symbol Digit Modalities Test (SDMT), Montreal Cognitive Assessment, Benton Judgment of Line Orientation, Modified Semantic Fluency Test, and Letter Number Sequencing Test, at baseline and subsequent annual follow-up visit for 5 years. Genetic data including ApoE and other PD risk genetic information were also obtained. We used SPSS-receiver operating characteristic and ANOVA repeated measures to evaluate which cognitive assessment is the best reflecting cognitive performance in PD at early stage and over time. Logistic regression analyses were used to determine the genetic associations with the rapidity of cognitive decline in PD. SDMT performed better in detecting mild cognitive impairment at baseline (AUC = 0.763), and SDMT was the only tool showing a steady cognitive decline during longitudinal observation. Multigenetic factors significantly associated with cognitive impairment at early stage of the disease (AUC = 0.950) with IP6K2 rs12497850 more evident, and a significantly faster decline (AUC = 0.831) within 5 years after motor onset, particularly in those carrying FGF20 rs591323. SDMT is a preferable cognitive assessment tool for PD and genetic factors synergistically contribute to the cognitive dysfunction in PD.

GWAS Identifies DPP6 as Risk Gene of Cognitive Decline in Parkinson's Disease.

Cognitive decline is among the most common non-motor symptoms in Parkinson's disease (PD), while its physiological mechanisms remain poorly understood. Genetic factors constituted a fundamental determinant in the heterogeneity of cognitive decline among PD patients. However, the underlying genetic background was still less studied. To explore the genetic determinants contributing to cognitive decline in PD, we performed genome-wide survival analysis using a Cox proportional hazards model in a longitudinal cohort of 450 Chinese patients with PD, and further explored the functional effect of the target variant. Additionally, we built a clinical-genetic model by incorporating clinical characteristics and polygenic risk score (PRS) to predict cognitive decline in PD. The cohort was followed up for an average of 5.25 (SE = 2.46) years, with 95 incidents of cognitive impairment. We identified significant association between locus rs75819919 (DPP6) and accelerated cognitive decline (p = 8.63E-09, beta = 1.74, SE = 0.30). Dual-luciferase reporter assay suggested this locus might be involved in the regulation of DPP6 expression. Using data set from the UK Biobank, we identified rs75819919 was associated with cognitive performance in the general population. Incorporation of PRS increased the model's predictability, achieving an average AUC of 75.6% through fivefold cross-validation in 1000 iterations. These findings improve the current understanding of the genetic etiology of cognitive impairment in PD, and provide a novel target DPP6 to explore therapeutic options. Our results also demonstrate the potential to develop clinical-genetic model to identify patients susceptible to cognitive impairment and thus provide personalized clinical guidance.

Early-phase amyloid PET reproduces metabolic signatures of cognitive decline in Parkinson's disease.

Recent work suggests that amyloid beta (Aβ) positron emission tomography (PET) tracer uptake shortly after injection ("early phase") reflects brain metabolism and perfusion. We assessed this modality in a predominantly amyloid-negative neurodegenerative condition, Parkinson's disease (PD), and hypothesized that early-phase 18F-florbetaben (eFBB) uptake would reproduce characteristic hypometabolism and hypoperfusion patterns associated with cognitive decline in PD. One hundred fifteen PD patients across the spectrum of cognitive impairment underwent dual-phase Aβ PET, structural and arterial spin labeling (ASL) magnetic resonance imaging (MRI), and neuropsychological assessments. Multiple linear regression models compared eFBB uptake to cognitive performance and ASL MRI perfusion. Reduced eFBB uptake was associated with cognitive performance in brain regions previously linked to hypometabolism-associated cognitive decline in PD, independent of amyloid status. Furthermore, eFBB uptake correlated with cerebral perfusion across widespread regions. EFBB uptake is a potential surrogate measure for cerebral perfusion/metabolism. A dual-phase PET imaging approach may serve as a clinical tool for assessing cognitive impairment. Images taken at amyloid beta (Aβ) positron emission tomography tracer injection may reflect brain perfusion and metabolism.Parkinson's disease (PD) is a predominantly amyloid-negative condition.Early-phase florbetaben (eFBB) in PD was associated with cognitive performance.eFBB uptake reflects hypometabolism-related cognitive decline in PD.eFBB correlated with arterial spin labeling magnetic resonance imaging measured cerebral perfusion.eFBB distinguished dementia from normal cognition and mild cognitive impairment.Findings were independent of late-phase Aβ burden.Thus, eFBB may serve as a surrogate measure for brain metabolism/perfusion.

Nonlinear Relationship Between Homocysteine and Mild Cognitive Impairment in Early Parkinson's Disease: A Cross-Sectional Study.

Cognitive impairment, a prevalent non-motor symptom in advanced Parkinson's disease (PD), has been associated with hyperhomocysteinemia, an important risk factor for PD progression and cognitive decline in PD. However, evidence regarding the association between homocysteine (Hcy) and cognitive function during early PD remains insufficient. Therefore, this study aims to examine the correlation between Hcy levels and cognitive function in the early stage of PD. The study included 218 individuals in the early stages of PD who were consecutively admitted to the Suining Central Hospital Neurology Department. All the individuals completed the Parkinson's Disease Cognitive Rating Scale (PD-CDR). The Unified Parkinson's Disease Rating Scale part III (UPDRS-III) was employed for measuring the severity of motor symptoms, while the Hoehn-Yahr scale was used to measure the clinical symptom stage. Fasting venous blood samples were also drawn to measure the Hcy concentration, red blood cell folate, and vitamin B12. In this cross-sectional study, 47 (21.5%) patients with PD showed cognitive dysfunction. The serum Hcy levels were significantly higher in the cognitive impairment PD (PDCI) group compared with the cognitive normal PD group (P<0.001). The Generalized Additive Model (GAM) analysis revealed a nonlinear relationship between Hcy and the risk of PDCI. Multiple logistic regression analyses demonstrated a positive relationship between elevated Hcy and the risk of PDCI in the fully adjusted model ([OR]:3.1, 95% CI, 1.1-8.5, P=0.028). Segmented linear regression analysis showed that when Hcy levels were above 17.7 umol/l, the risk of PDCI increased by 1.6 times for every 1 unit elevated in Hcy (95% CI:1.1-2.2, P=0.008). This study revealed a nonlinear positive correlation between the risk of PDCI and elevated serum Hcy levels in early PD patients, suggesting hyperhomocysteinemia as one of the treatable factors for cognitive impairment in the early stages of PD.

Hippocampal resting-state connectivity is associated with posterior-cortical cognitive impairment in Parkinson's disease.

Frontal and posterior-cortical cognitive subtypes in Parkinson's disease (PD) present with executive/attention and memory/visuospatial deficits, respectively. As the posterior-cortical subtype is predicted to progress rapidly toward dementia, the present study aimed to explore biological markers of this group using resting-state functional magnetic resonance imaging (rs-fMRI). K-means cluster analysis delineated subtypes (cognitively intact, frontal, posterior-cortical, and globally impaired) among 85 people with PD. A subset of PD participants (N=42) and 20 healthy controls (HCs) underwent rs-fMRI. Connectivity of bilateral hippocampi with regions of interest was compared between posterior-cortical, cognitively intact, and HC participants using seed-based analysis, controlling for age. Exploratory correlations were performed between areas of interest from the group analysis and a series of cognitive tests. The posterior-cortical subtype (N=19) showed weaker connectivity between the left hippocampus and right anterior temporal fusiform cortex compared to the cognitively intact (N=11) group, p-false discovery rate (FDR)=.01, and weaker connectivity between bilateral hippocampi and most fusiform regions compared to HCs (N=20). No differences were found between HCs and cognitively intact PD. Exploratory analyses revealed strongest associations between connectivity of the right anterior temporal fusiform cortex and left hippocampus with category fluency (p-FDR=.01). Results suggest that weakened connectivity between the hippocampus and fusiform region is a unique characteristic of posterior-cortical cognitive deficits in PD. Further exploration of hippocampal and fusiform functional integrity as a marker of cognitive decline in PD is warranted.

Evaluation of ATNPD Framework and Biofluid Markers to Predict Cognitive Decline in Early Parkinson Disease.

In Parkinson disease (PD), Alzheimer disease (AD) copathology is common and clinically relevant. However, the longitudinal progression of AD CSF biomarkers-β-amyloid 1-42 (Aβ42), phosphorylated tau 181 (p-tau181), and total tau (t-tau)-in PD is poorly understood and may be distinct from clinical AD. Moreover, it is unclear whether CSF p-tau181 and serum neurofilament light (NfL) have added prognostic utility in PD, when combined with CSF Aβ42. First, we describe longitudinal trajectories of biofluid markers in PD. Second, we modified the AD β-amyloid/tau/neurodegeneration (ATN) framework for application in PD (ATNPD) using CSF Aβ42 (A), p-tau181 (T), and serum NfL (N) and tested ATNPD prediction of longitudinal cognitive decline in PD. Participants were selected from the Parkinson's Progression Markers Initiative cohort, clinically diagnosed with sporadic PD or as controls, and followed up annually for 5 years. Linear mixed-effects models (LMEMs) tested the interaction of diagnosis with longitudinal trajectories of analytes (log transformed, false discovery rate [FDR] corrected). In patients with PD, LMEMs tested how baseline ATNPD status (AD [A+T+N±] vs not) predicted clinical outcomes, including Montreal Cognitive Assessment (MoCA; rank transformed, FDR corrected). Participants were 364 patients with PD and 168 controls, with comparable baseline mean (±SD) age (patients with PD = 62 ± 10 years; controls = 61 ± 11 years]; Mann-Whitney Wilcoxon: p = 0.4) and sex distribution (patients with PD = 231 male individuals [63%]; controls = 107 male individuals [64%]; χ2: p = 1). Patients with PD had overall lower CSF p-tau181 (β = -0.16, 95% CI -0.23 to -0.092, p = 2.2e-05) and t-tau than controls (β = -0.13, 95% CI -0.19 to -0.065, p = 4e-04), but not Aβ42 (p = 0.061) or NfL (p = 0.32). Over time, patients with PD had greater increases in serum NfL than controls (β = 0.035, 95% CI 0.022 to 0.048, p = 9.8e-07); slopes of patients with PD did not differ from those of controls for CSF Aβ42 (p = 0.18), p-tau181 (p = 1), or t-tau (p = 0.96). Using ATNPD, PD classified as A+T+N± (n = 32; 9%) had worse cognitive decline on global MoCA (β = -73, 95% CI -110 to -37, p = 0.00077) than all other ATNPD statuses including A+ alone (A+T-N-; n = 75; 21%). In patients with early PD, CSF p-tau181 and t-tau were low compared with those in controls and did not increase over 5 years of follow-up. Our study shows that classification using modified ATNPD (incorporating CSF Aβ42, CSF p-tau181, and serum NfL) can identify biologically relevant subgroups of PD to improve prediction of cognitive decline in early PD.

Longitudinal brain changes in Parkinson's disease with severe olfactory deficit

IntroductionOlfactory dysfunction and REM sleep behavior disorder (RBD) are associated with distinct cognitive trajectories in the course of Parkinson's disease (PD). The underlying neurobiology for this relationship remains unclear but may involve distinct patterns of neurodegeneration. This study aimed to examine longitudinal cortical atrophy and thinning in early-stage PD with severe olfactory deficit (anosmia) without and with concurrent probable RBD. MethodsLongitudinal MRI data over four years of 134 de novo PD and 49 healthy controls (HC) from the Parkinson Progression Marker Initiative (PPMI) cohort were analyzed using a linear mixed-effects model. Patients were categorized into those with anosmia by the University of Pennsylvania Smell Identification Test (UPSIT) score ≤ 18 (AO+) and those without (UPSIT score > 18, AO-). The AO+ group was further subdivided into AO+ with probable RBD (AO+RBD+) and without (AO+RBD-) for subanalysis. ResultsCompared to subjects without baseline anosmia, the AO+ group exhibited greater longitudinal declines in both volume and thickness in the bilateral parahippocampal gyri and right transverse temporal gyrus. Patients with concurrent anosmia and RBD showed more extensive longitudinal declines in cortical volume and thickness, involving additional brain regions including the bilateral precuneus, left inferior temporal gyrus, right paracentral gyrus, and right precentral gyrus. ConclusionsThe atrophy/thinning patterns in early-stage PD with severe olfactory dysfunction include regions that are critical for cognitive function and could provide a structural basis for previously reported associations between severe olfactory deficit and cognitive decline in PD. Concurrent RBD might enhance the dynamics of cortical changes.

Radionuclide Imaging of the Neuroanatomical and Neurochemical Substrate of Cognitive Decline in Parkinson's Disease.

Cognitive impairment is a frequent manifestation of Parkinson's disease (PD), resulting in decrease in patients' quality of life and increased societal and economic burden. However, cognitive decline in PD is highly heterogenous and the mechanisms are poorly understood. Radionuclide imaging techniques like positron emission tomography (PET) and single photon emission computed tomography (SPECT) have been used to investigate the neurochemical and neuroanatomical substrate of cognitive decline in PD. These techniques allow the assessment of different neurotransmitter systems, changes in brain glucose metabolism, proteinopathy, and neuroinflammation in vivo in PD patients. Here, we review current radionuclide imaging research on cognitive deficit in PD with a focus on predicting accelerating cognitive decline. This research could assist in the development of prognostic biomarkers for patient stratification and have utility in the development of ameliorative or disease-modifying therapies targeting cognitive deficit in PD.

High-frequency multimodal training with a focus on Tai Chi in people with Parkinson's disease: a pilot study.

Cognitive decline is an important and common complication in patients with Parkinson's disease (PD) since it significantly reduces the quality of life. A breakthrough in treating and preventing cognitive decline in PD remains to be achieved. This study aimed to evaluate the effectiveness of high-frequency and intensive multimodal training in improving motor and cognitive function. Twenty-eight patients diagnosed with idiopathic PD completed a comprehensive neuropsychological test battery and were neurologically examined. The patients of the intervention group (n = 15) underwent 2 weekly sessions of Tai Chi therapy over 4 weeks and participated in an individually tailored training program consisting of two modules (smartphone-based speech training and cognitive training). A matched control group consisted of n = 13 patients with PD who received computer-assisted cognitive training. The data were analyzed with repeated-measures ANOVA. Four weeks of high-frequency training showed significant effects on verbal and figural episodic memory and visuospatial function in the intervention groupCompared to the control group, the cognitive performance of the intervention group improved significantly in visuospatial function and figural episodic memory. A significant improvement was also shown in the intervention group in the Tinetti Mobility Test and the Epworth Sleepiness Scale. The significant effects in the Tinetti mobility test remained after the 6 months follow-up. After the intervention, the patients reported high motivation and satisfaction with the multimodal training. In patients with PD, a multimodal training program not only improves gait and stability but may also contribute to improving cognition. ClinicalTrials.gov Identifier: NCT04103255; https://register.clinicaltrials.gov/prs/app/action/LoginUser?ts=1&cx=-jg9qo4.