Cognitive Impairment In Parkinson's Disease Research Articles

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.

Duzhong Fang ameliorates cognitive impairment of Parkinsonian mice by suppressing neuronal apoptotic pathway.

Parkinson's disease (PD) is a complex multisystem neurodegenerative disease, and cognitive impairment is a common symptom in the trajectory of PD. Duzhong Fang (DZF) consists of Eucommia ulmoides, Dendrobium, Rehmanniae Radix, and Dried Ginger. Our previous study showed that DZF improves motor deficits in mice. However, whether DZF can ameliorate cognitive impairment in PD has not been reported. In this study, we established mice models of PD induced by rotenone and examined the effect of DZF on cognitive impairment in Parkinson's disease (PD-CI). The results confirmed that DZF treatment not only significantly improved the motor deficits in PD mice and decreased the loss of dopaminergic neurons, but also had significant effects in improving cognitive impairment. We further integrate serum metabolome and network pharmacology to explore the mechanisms by which DZF improves PD-CI. The results revealed that DZF can treat PD-CI by regulating sphingolipid metabolism to inhibit neuronal apoptotic pathway. In conclusion, preliminary studies confirmed that DZF contributes to the improvement of cognitive ability in PD, and our results provide a potential drug for the clinical treatment of PD and a theoretical foundation for DZF in clinical application.

Analysis of cognitive dysfunction in Parkinson's disease using voxel based morphometry and radiomics.

Cognitive impairment in Parkinson's disease (PD) is associated with changes in the brain anatomical structures. The objective of this study, is to identify the atrophy patterns based on the severity of cognitive decline and evaluate the disease progression. In this study, gray matter alterations are analysed in 135 PD subjects under 3 cognitive domains (91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D)) by comparing them with 58 Healthy Control (HC) subjects. Voxel Based Morphometry (VBM) is used to segment the gray matter regions in magnetic resonance images and analyse the atrophy patterns statistically. Significant patterns of gray matter variations observed in the middle temporal and medial frontal region differentiate between HC and PD subject groups based on the severity of cognitive decline. Abnormalities in gray matter is substantiated through radiomic features extracted from the significant gray matter clusters. Significant radiomic features of the clusters are able to differentiate between the HC and PD-D subjects with an accuracy of 81.82%. Higher atrophy levels identified in PD-D subjects compared to NC-PD and PD-MCI group enables early diagnosis and treatment procedures. The combined and comprehensive analysis of gray matter alterations through VBM and radiomic features gives better assessment of cognitive impairment in PD.

Misfolded protein deposits in Parkinson’s disease and Parkinson’s disease-related cognitive impairment, a [11C]PBB3 study

Parkinson’s disease (PD) is associated with aggregation of misfolded α-synuclein and other proteins, including tau. We designed a cross-sectional study to quantify the brain binding of [11C]PBB3 (a ligand known to bind to misfolded tau and possibly α-synuclein) as a proxy of misfolded protein aggregation in Parkinson’s disease (PD) subjects with and without cognitive impairment and healthy controls (HC). In this cross-sectional study, nineteen cognitively normal PD subjects (CN-PD), thirteen cognitively impaired PD subjects (CI-PD) and ten HC underwent [11C]PBB3 PET. A subset of the PD subjects also underwent PET imaging with [11C](+)DTBZ to assess dopaminergic denervation and [11C]PBR28 to assess neuroinflammation. Compared to HC, PD subjects showed higher [11C]PBB3 binding in the posterior putamen but not the substantia nigra. There was no relationship across subjects between [11C]PBB3 and [11C]PBR28 binding in nigrostriatal regions. [11C]PBB3 binding was increased in the anterior cingulate in CI-PD compared to CN-PD and HC, and there was an inverse correlation between cognitive scores and [11C]PBB3 binding in this region across all PD subjects. Our results support a primary role of abnormal protein deposition localized to the posterior putamen in PD. This suggests that striatal axonal terminals are preferentially involved in the pathophysiology of PD. Furthermore, our findings suggest that anterior cingulate pathology might represent a significant in vivo marker of cognitive impairment in PD, in agreement with previous neuropathological studies.

Cognitive function in different motor subtypes of Parkinson's disease: A systematic review protocol.

As the fastest-growing neurological disorder globally, a better understanding of Parkinson's disease (PD) is needed to improve patient outcomes and reduce the increasing economic and healthcare burden associated with the disease. Whilst classified as a movement disorder, this disease is highly heterogeneous, encompassing a broad range of both motor and non-motor symptoms (NMS). Cognitive impairment, presenting as either mild cognitive impairment or PD-dementia, is one of the most prevalent and disabling NMS. To better understand heterogeneity in PD, researchers have sought to identify subtypes of individuals who share similar symptom profiles. To date, this research has predominantly focused on motor subtyping, with many studies comparing these motor subtypes on non-motor outcomes, such as cognitive impairment. However, despite evidence of a motor-cognitive relationship in healthy aging, findings regarding the presence of a motor-cognitive relationship in PD are inconsistent. In our proposed systematic review, we will investigate motor subtyping studies that have evaluated the relationship between motor and cognitive function in PD. We aim to examine what is currently known about the relationship between motor and cognitive impairment in PD and evaluate the state of the field with respect to the subtyping methods and quality of cognitive assessment tools used. Systematic literature searches will be conducted in PubMed, PsycINFO, CINAHL, Scopus, and Web of Science. Results will be synthesized using meta-analysis and, where meta-analysis is not feasible, narrative synthesis. Despite the preponderance of motor subtyping research in PD, our study will be the first to systematically review evidence regarding the association between motor subtypes and cognitive impairment. Understanding the nature of the motor-cognitive relationship in PD may lead to important insights regarding shared underlying disease pathology, which would have significant implications for early diagnosis, prognosis, and treatment of cognitive impairment in PD.

A nomogram based on neuron-specific enolase and substantia nigra hyperechogenicity for identifying cognitive impairment in Parkinson's disease.

One in four individuals with Parkinson's disease (PD) experience cognitive impairment (CI). However, few practical models integrating clinical and neuroimaging biomarkers have been developed to address CI in PD. This study aimed to evaluate the correlation between circulating neuron-specific enolase (NSE) levels, substantia nigra hyperechogenicity (SNH), and cognitive function in PD and to develop a nomogram based on clinical and neuroimaging biomarkers for predicting CI in patients with PD. A total of 385 patients with PD who underwent transcranial sonography (TCS) from January 2021 to December 2022 at Beijing Tiantan Hospital, Capital Medical University, were recruited as the training cohort. For validation, 165 patients with PD treated from January 2023 to December 2023 were enrolled. Data for SNH, plasma NSE, and other clinical measures were collected, and cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Logistic regression analysis was employed to select potential risk factors and establish a nomogram. The receiver operating characteristic curve and calibration curve were generated to evaluate the performance of the nomogram. Patients with PD exhibiting CI displayed advanced age, elevated Unified PD Rating Scale-III (UPDRS-III) score, an increased percentage of SNH, higher levels of plasma NSE and homocysteine (Hcy), a larger SNH area, and lower education levels compared to PD patients without CI. Gender [odds ratio (OR) =0.561, 95% confidence interval (CI): 0.330-0.954, P=0.03], age (OR =1.039; 95% CI: 1.011-1.066; P=0.005), education level (OR =0.892; 95% CI: 0.842-0.954; P<0.001), UPDRS-III scores (OR =1.026; 95% CI: 1.009-1.043; P=0.003), plasma NSE concentration (OR =1.562; 95% CI: 1.374-1.776; P<0.001), and SNH (OR =0.545; 95% CI: 0.330-0.902; P=0.02) were independent predictors of CI in patients with PD. A nomogram developed using these six factors yielded a moderate discrimination performance with an area under the curve (AUC) of 0.823 (95% CI 0.781-0.864; P<0.001). The calibration curve demonstrated acceptable agreement between predicted outcomes and actual values. Validation further confirmed the reliability of the nomogram, with an AUC of 0.864 (95% CI: 0.805-0.922; P<0.001). The level of NSE in plasma and the SNH assessed by TCS are associated with CI in patients with PD. The proposed nomogram has the potential to facilitate the detection of cognitive decline in individuals with PD.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease.

This study aimed to investigate whether spontaneous brain activity can be used as a prospective indicator to identify cognitive impairment in patients with Parkinson's disease (PD). Resting-state functional magnetic resonance imaging (RS-fMRI) was performed on PD patients. The cognitive level of patients was assessed by the Montreal Cognitive Assessment (MoCA) scale. The fractional amplitude of low-frequency fluctuation (fALFF) was applied to measure the strength of spontaneous brain activity. Correlation analysis and between-group comparisons of fMRI data were conducted using Rest 1.8. By overlaying cognitively characterized brain regions and defining regions of interest (ROIs) based on their spatial distribution for subsequent cognitive stratification studies. A total of 58 PD patients were enrolled in this study. They were divided into three groups: normal cognition (NC) group (27 patients, average MoCA was 27.96), mild cognitive impairment (MCI) group (21 patients, average MoCA was 23.52), and severe cognitive impairment (SCI) group (10 patients, average MoCA was 17.3). It is noteworthy to mention that those within the SCI group exhibited the most advanced chronological age, with an average of 74.4 years, whereas the MCI group displayed a higher prevalence of male participants at 85.7%. It was found hippocampal regions were a stable representative brain region of cognition according to the correlation analysis between the fALFF of the whole brain and cognition, and the comparison of fALFF between different cognitive groups. The parahippocampal gyrus was the only region with statistically significant differences in fALFF among the three cognitive groups, and it was also the only brain region to identify MCI from NC, with an AUC of 0.673. The paracentral lobule, postcentral gyrus was the region that identified SCI from NC, with an AUC of 0.941. The midbrain, hippocampus, and parahippocampa gyrus was the region that identified SCI from MCI, with an AUC of 0.926. The parahippocampal gyrus was the potential brain region for recognizing cognitive impairment in PD, specifically for identifying MCI. Thus, the fALFF of parahippocampal gyrus is expected to contribute to future study as a multimodal fingerprint for early warning.

Oral Microbiota and Porphyromonas gingivalis Kgp Genotypes Altered in Parkinson's Disease with Mild Cognitive Impairment.

Cognitive impairment (CI) is a common complication of the non-motor symptoms in Parkinson's disease (PD), including PD with mild cognitive impairment (PD-MCI) and PD dementia. Recent studies reported the oral dysbiosis in PD and CI, respectively. Porphyromonas gingivalis (P. gingivalis), a pathogen of oral dysbiosis, plays an important role in PD, whose lysine-gingipain (Kgp) could lead to AD-type pathologies. No previous study investigated the composition of oral microbiota and role of P. gingivalis in PD-MCI. This study aimed to investigate the differences of oral microbiota composition, P. gingivalis copy number, and Kgp genotypes among PD-MCI, PD with normal cognition (PD-NC) and periodontal status-matched control (PC) groups. The oral bacteria composition, the copy number of P. gingivalis, and the Kgp genotypes in gingival crevicular fluid from PD-MCI, PD-NC, and PC were analyzed using 16S ribosomal RNA sequencing, quantitative real-time PCR, and MseI restriction. We found that the structures of oral microbiota in PD-MCI group were significantly different compared to that in PD-NC and PC group. The relative abundances of Prevotella, Lactobacillus, Megasphaera, Atopobium, and Howardella were negatively correlated with cognitive score. Moreover, there was a significant difference of Kgp genotypes among the three groups. The predominant Kgp genotypes of P. gingivalis in the PD-MCI group were primarily Kgp II, whereas in the PD-NC group, it was mainly Kgp I. The Kgp II correlated with lower MMSE and MoCA scores, which suggested that Kgp genotypes II is related to cognitive impairment in PD.

Social cognition in Parkinson's disease and functional movement disorders.

Functional movement disorders (FMD) can overlap with Parkinson's disease (PD), and distinguishing between the two clinical conditions can be complex. Framing social cognition (theory of mind) (TOM) disorder, attention deficit, and psychodynamic features of FMD and PD may improve diagnosis. Subjects with FMD and PD and healthy controls (HC) were administered tasks assessing TOM abilities and attention. The psychodynamic hypothesis of conversion disorder was explored by a questionnaire assessing dissociative symptoms. A comprehensive battery of neuropsychological tasks was also administered to FMD and PD. Although both FMD and PD scored lower than HC on all TOM tests, significant correlations between TOM and neuropsychological tasks were found only in PD but not in FMD. Only PD showed a reduction in attentional control. Dissociative symptoms occurred only in FMD. Cognitive-affective disturbances are real in FMD, whereas they are largely dependent on cognitive impairment in PD. Attentional control is preserved in FMD compared to PD, consistent with the hypothesis that overload of voluntary attentional orientation may be at the basis of the onset of functional motor symptoms. On a psychodynamic level, the confirmation of dissociative symptoms in FMD supports the conversion disorder hypothesis. FMD and PD can be distinguished on an affective and cognitive level. At the same time, however, the objective difficulty often encountered in distinguishing between the two pathologies draws attention to how blurred the boundary between 'organic' and 'functional' can be.

Serum level of YWHAG as a diagnostic marker of cognitive impairment in Parkinson's disease patients.

Identifying reliable biomarkers for early detection and prediction of cognitive impairment in Parkinson's disease (PD) is crucial for optimal patient care. This study set out to investigate the potential of YWHAG as a diagnostic biomarker for cognitive impairment in PD. We enrolled a total of 331 PD patients and selected 241 patients that met the criteria for cognitive impairment analysis. The patients were classified into three groups: PD-NC: PD patients with normal cognition, PD-MCI: PD patients with mild cognitive impairment, and PD-D: PD patients with dementia. ELISA was employed to assess YWHAG expression, as well as the neurofilament light chain (NfL). Additionally, cognitive impairment was evaluated using MoCA scores. Correlation analysis and receiver operating curve analysis (ROC) were performed to clarify the relationship between YWHAG expression and cognitive impairment. Our findings revealed a significant upregulation of YWHAG expression in both the PD-MCI and PD-D groups compared to the PD-NC group. This observation aligned with the elevated expression of NfL in the PD-MCI and PD-D groups. YWHAG and NfL expression levels displayed negative correlations with MoCA scores and positive associations with age. Furthermore, ROC curve analysis demonstrated the diagnostic efficacy of YWHAG expression in distinguishing individuals with PD-NC, PD-MCI, and PD-D. Our findings indicate that YWHAG could serve as a promising biomarker for cognitive impairment in PD. The upregulation of YWHAG expression in PD-MCI and PD-D groups, its association with cognitive impairment, and its correlations with MoCA scores and NfL levels support its potential clinical utility.

Correlation and underlying brain mechanisms between rapid eye movement sleep behavior disorder and executive functions in Parkinson's disease: an fNIRS study.

Rapid eye movement sleep behavior disorder (RBD) affects 30%-40% of patients with Parkinson's disease (PD) and has been linked to a higher risk of cognitive impairment, especially executive dysfunction. The aim of this study was to investigate the brain activation patterns in PD patients with RBD (PD-RBD+) compared to those without RBD (PD-RBD-) and healthy controls (HCs), and to analyze the correlation between changes in cerebral cortex activity and the severity of RBD. We recruited 50 PD patients, including 30 PD-RBD+, 20 PD-RBD-, and 20 HCs. We used functional near infrared spectroscopy during a verbal fluency task (VFT-fNIRS) and clinical neuropsychological assessment to explore the correlation between PD-RBD+ and executive function and changes in neural activity. The VFT-fNIRS analysis revealed a significant reduction in activation among PD-RBD+ patients across multiple channels when compared to both the PD-RBD- and HC groups. Specifically, PD-RBD+ patients exhibited diminished activation in the bilateral dorsolateral prefrontal cortex (DLPFC) and the right ventrolateral prefrontal cortex (VLPFC) relative to their PD-RBD- counterparts. Furthermore, compared to the HC group, PD-RBD+ patients displayed reduced activation specifically in the right DLPFC. Significantly, a noteworthy negative correlation was identified between the average change in oxygenated hemoglobin concentration (ΔHbO2) in the right DLPFC of PD-RBD+ patients and the severity of their RBD. Our study offers compelling evidence that RBD exacerbates cognitive impairment in PD, manifested as executive dysfunction, primarily attributed to reduced prefrontal activation. These aberrations in brain activation may potentially correlate with the severity of RBD.

Structural and microstructural predictors of cognitive decline in deep brain stimulation of subthalamic nucleus in Parkinson’s disease

Background and objectivesThe intricate relationship between deep brain stimulation (DBS) in Parkinson’s disease (PD) and cognitive impairment has lately garnered substantial attention. The presented study evaluated pre-DBS structural and microstructural cerebral patterns as possible predictors of future cognitive decline in PD DBS patients. MethodsPre-DBS MRI data in 72 PD patients were combined with neuropsychological examinations and follow-up for an average of 2.3 years after DBS implantation procedure using a screening cognitive test validated for diagnosis of mild cognitive impairment in PD in a Czech population – Dementia Rating Scale 2. ResultsPD patients who would exhibit post-DBS cognitive decline were found to have, already at the pre-DBS stage, significantly lower cortical thickness and lower microstructural complexity than cognitively stable PD patients. Differences in the regions directly related to cognition as bilateral parietal, insular and cingulate cortices, but also occipital and sensorimotor cortex were detected. Furthermore, hippocampi, putamina, cerebellum and upper brainstem were implicated as well, all despite the absence of pre-DBS differences in cognitive performance and in the position of DBS leads or stimulation parameters between the two groups. ConclusionsOur findings indicate that the cognitive decline in the presented PD cohort was not attributable primarily to DBS of the subthalamic nucleus but was associated with a clinically silent structural and microstructural predisposition to future cognitive deterioration present already before the DBS system implantation.

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks.

Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.

Structural changes in the retina and serum HMGB1 levels are associated with decreased cognitive function in patients with Parkinson's disease

BackgroundCognitive impairment is a serious nonmotor symptom in patients with Parkinson's disease (PD). Currently, there are few studies investigating the relationship of serum markers and retinal structural changes with cognitive function in PD. ObjectiveTo investigate the relationship between retinal structural changes, serum high mobility group box-1 (HMGB1) levels and cognitive function and motor symptoms in PD patients. MethodsEighty-nine participants, including 47 PD patients and 42 healthy subjects, were enrolled. PD patients were divided into Parkinson's disease with normal cognitive (PD-NC), Parkinson's disease with mild cognitive impairment (PD-MCI), and Parkinson's disease with dementia (PDD) groups. The motor and nonmotor symptoms of PD patients were evaluated with clinical scale. Serum HMGB1 levels were detected by enzyme-linked immunosorbent assay (ELISA), and ganglion cell-inner plexiform layer complex (GCIPL) thickness changes in the macula were quantitatively analyzed by swept source optical coherence tomography (SS-OCT) in all patients. ResultsCompared with the control group, the macular GCIPL (t = −2.308, P = 0.023) was thinner and serum HMGB1 (z = −2.285, P = 0.022) was increased in PD patients. Macular GCIPL thickness in patients with PD-MCI and PDD were significantly lower than that in PD-NC patients, but there were no significant difference between the PD-MCI and PDD groups. Serum HMGB1 levels in patients with PD-MCI and PDD were significantly higher than those in PD-NC patients, and serum HMGB1 levels in PDD patients were higher than those in PD-MCI patients. Correlation analysis showed that serum HMGB1 levels in PD patients were positively correlated with disease duration, HY stage, UPDRS-I score, UPDRS-III score, and UPDRS total score and negatively correlated with MOCA score. Macular GCIPL thickness was negatively correlated with HY stage and positively correlated with MOCA score, and macular GCIPL thickness was negatively correlated with serum HMGB1 level. Logistic regression analysis showed that elevated serum HMGB1 level, thinner macular GCIPL thickness, and higher HY stage were independent risk factors for Parkinson's disease with cognitive impairment (PD-CI). The areas under the receiver operating characteristic curve (AUC) for the serum HMGB1 level and macular GCIPL thickness-based diagnosis of PD-MCI, PDD and PD-CI based on in patients with PD were 0.786 and 0.825, 0.915 and 0.856, 0.852 and 0.841, respectively. The AUC for the diagnosis of PD-MCI, PDD and PD-CI with serum HMGB1 level and GCIPL thickness combined were 0.869, 0.967 and 0.916, respectively. ConclusionThe macular GCIPL thickness and serum HMGB1 level are potential markers of cognitive impairment in PD patients, and their combination can significantly improve the accuracy of the diagnosis of cognitive impairment in PD.

Pathological correlates of cognitive decline in Parkinson’s disease: from molecules to neural networks

Parkinson’s disease (PD) is a progressive neurodegenerative disorder resulting from the death of dopaminergic neurons in the substantia nigra and the appearance of protein aggregates in neuronal cell bodies composed predominantly of alpha-synuclein, known as Lewy bodies. PD is now recognized as a multisystem disorder characterized by severe motor impairment and various non-motor symptoms. Cognitive decline is one of the most common and worrisome non-motor symptoms. Moderate cognitive impairment (CI), diagnosed already in the early stages of PD, usually leads to deep dementia. The main types of CI observed in PD include executive dysfunction, attention, and memory disfunction, visuospatial decline, and verbal deficits. According to the literature, the following mechanisms play a significant role in the development of cognitive dysfunctions in PD: (1) changes in the conformational structure of synaptic proteins; (2) disruption of synaptic transmission; (3) neuroinflammation (pathological activation of neuroglia); (4) mitochondrial dysfunction and oxidative stress; (5) metabolic conditions; (6) functional remodeling of the neural networks. The listed molecular and synaptic changes in the brain can lead to the death of dopamine-synthesizing cells of the substantia nigra and dysfunction of other mediator systems, as well as partial cellular atrophy in the neocortex and subcortical nuclei. As a result, the functioning of neural networks involved in the transmission of information related to the regulation of motor activity and cognitive functions is disrupted. Elucidation of the causes of changes occurring in PD and the search for methods to eliminate them will help create new approaches in the treatment of this disease. The aim of the review is to analyze the pathological processes in the brain that underlie the onset of cognitive impairment in PD. The review analyzes the data obtained both from studies on patients with PD and animal (rodents and primates) models of this disease used for the evaluation of the mechanisms underlying etiology and the development of PD in humans.

REM Sleep Behavior Disorder and Cognitive Functions in Parkinson’s Patients: A Systematic Review

Sleep disorders, such as REM sleep behavior disorder (RBD) and excessive daytime sleepiness, are among the most common non-motor symptoms in subjects with Parkinson’s disease (PD). Sleep disorders have a major negative impact on the quality of life of patients and their caregivers. In addition, REM sleep behavior disorder is an important risk factor for cognitive impairment in PD. This systematic review was conducted on studies investigating the influence of RBD on cognitive performance in PD subjects. We searched the PubMed and Scopus databases, screened the references of the studies included, and reviewed articles for additional citations. From the first 244 publications, we included only 11 studies that met the search criteria. The results showed that sleep disorders in PD were associated with impaired executive functions, visual-constructive abilities, reduced attention, and episodic verbal memory, and could predict the possible risk of developing dementia.

Metaproteogenomic analysis of saliva samples from Parkinson’s disease patients with cognitive impairment

Cognitive impairment (CI) is very common in patients with Parkinson’s Disease (PD) and progressively develops on a spectrum from mild cognitive impairment (PD-MCI) to full dementia (PDD). Identification of PD patients at risk of developing cognitive decline, therefore, is unmet need in the clinic to manage the disease. Previous studies reported that oral microbiota of PD patients was altered even at early stages and poor oral hygiene is associated with dementia. However, data from single modalities are often unable to explain complex chronic diseases in the brain and cannot reliably predict the risk of disease progression. Here, we performed integrative metaproteogenomic characterization of salivary microbiota and tested the hypothesis that biological molecules of saliva and saliva microbiota dynamically shift in association with the progression of cognitive decline and harbor discriminatory key signatures across the spectrum of CI in PD. We recruited a cohort of 115 participants in a multi-center study and employed multi-omics factor analysis (MOFA) to integrate amplicon sequencing and metaproteomic analysis to identify signature taxa and proteins in saliva. Our baseline analyses revealed contrasting interplay between the genus Neisseria and Lactobacillus and Ligilactobacillus genera across the spectrum of CI. The group specific signature profiles enabled us to identify bacterial genera and protein groups associated with CI stages in PD. Our study describes compositional dynamics of saliva across the spectrum of CI in PD and paves the way for developing non-invasive biomarker strategies to predict the risk of CI progression in PD.

Proprioceptive and olfactory deficits in individuals with Parkinson disease and mild cognitive impairment.

Individuals with neurodegenerative diseases such as Parkinson disease (PD) and Alzheimer's (AD) disease often present with perceptual impairments at an early clinical stage. Therefore, early identification and quantification of these impairments could facilitate diagnosis and early intervention. This study aimed to compare proprioceptive and olfactory sensitivities in individuals diagnosed with PD and mild cognitive impairment (MCI). Proprioception in the forearm and olfactory function were measured in neurotypical older adults, individuals with PD, and individuals with MCI. Position and passive motion senses were assessed using a passive motion apparatus. The traditional Chinese version of the University of Pennsylvania smell identification test (UPSIT-TC) and the smell threshold test (STT) were used to identify and discriminate smell, respectively. Position sense threshold between the groups differed significantly (p < 0.001), with the PD (p < 0.001) and MCI (p = 0.004) groups showing significantly higher than the control group. The control group had significantly higher mean UPSIT-TC scores than the PD (p < 0.001) and MCI (p = 0.006) groups. The control group had a significantly lower mean STT threshold than the PD and MCI groups (p < 0.001 and p = 0.008, respectively). UPSIT-TC scores significantly correlated with disease progression in PD (r = -0.50, p = 0.008) and MCI (r = 0.44, p = 0.04). Proprioceptive and olfactory sensitivities were reduced in individuals with PD and MCI, and these deficits were related to disease severity. These findings support previous findings indicating that perceptual loss may be a potential biomarker for diagnosing and monitoring disease progression in individuals with neurodegenerative diseases.

24 Functional Distinctions in Metabolic Network Patterns in Parkinson's Disease

Objective:Cognitive decline is a common non-motor feature of Parkinson's disease (PD). However, the underlying mechanisms of cognitive impairment in PD require further elucidation. FDG PET imaging data analyses have revealed distinct brain metabolic patterns associated with the cognitive features of PD. The PD cognition-related pattern (PDCP) and default mode network (DMN) are two overlapping, but topographically distinct, networks that may serve as biomarkers of cognitive decline in PD. Decreased activity of the resting-state DMN and increased expression of the PDCP are associated with cognitive impairment in PD. Studies have consistently demonstrated the association between neuropsychological memory test performance and PDCP expression. Thus, we examined whether memory performance could offer additional value in predicting PDCP expression in PD patients. We hypothesized that DMN and memory performance would predict greater variance in PDCP expression than the DMN alone.Participants and Methods:Participants included 48 PD patients ages 46-80 (mean (SD) Age: 61.9 (8.1), Education: 15.0 (2.8), IQ: 112.5 (14.9), DRS total: 136.7 (5.8)). All participants completed the FDG PET and neuropsychological evaluation 8-12 hours after their last dose of Levodopa. Neuropsychological memory testing included the California Verbal Learning Test (CVLT) z score of sum of learning trials. PDCP and DMN values were z scores generated from normal controls in previous studies. Data were analyzed using linear regression analyses.Results:A hierarchical regression was performed to predict PDCP as a function of DMN and CVLT learning performance. Variables were entered in two separate blocks. The first block included DMN as a predictor, and the overall regression was significant (R2 = 0.55, F(1, 39)= 47.0, p &lt; 0.001). As hypothesized, DMN significantly predicted PCDP expression (β= -0.74, p &lt; 0.001). The second block of the regression included CVLT learning memory performance. Both DMN and CVLT performance explained a significant amount of variance in PDCP (R2 change = 0.05, F(2, 39)= 27.6, p &lt; 0.001). CVLT performance significantly predicted PDCP (β= -0.22, p =0.048). The final model accounted for 60.0% of the variance in PDCP.Conclusions:Disruptions in functional connectivity within brain networks have become increasingly recognized as mechanisms responsible for cognitive impairment in patients. As demonstrated in previous studies, our results indicated that DMN loss is a strong predictor of PDCP expression, likely due to the networks' overlapping spatial regions. However, we found that the addition of memory performance to the model could explain a small amount of variance (5%) over and above DMN expression. Overall, the current findings demonstrate a functional (i.e., learning) distinction between population-specific (PDCP) and more general brain networks (DMN).

EEG-Based Parkinson's Disease Recognition Via Attention-based Sparse Graph Convolutional Neural Network.

Parkinson's disease (PD) is a complicated neurological ailment that affects both the physical and mental wellness of elderly individuals which makes it problematic to diagnose in its initial stages. Electroencephalogram (EEG) promises to be an efficient and cost-effective method for promptly detecting cognitive impairment in PD. Nevertheless, prevailing diagnostic practices utilizing EEG features have failed to examine the functional connectivity among EEG channels and the response of associated brain areas causing an unsatisfactory level of precision. Here, we construct an attention-based sparse graph convolutional neural network (ASGCNN) for diagnosing PD. Our ASGCNN model uses a graph structure to represent channel relationships, the attention mechanism for selecting channels, and the L1 norm to capture channel sparsity. We conduct extensive experiments on the publicly available PD auditory oddball dataset, which consists of 24 PD patients (under ON/OFF drug status) and 24 matched controls, to validate the effectiveness of our method. Our results show that the proposed method provides better results compared to the publicly available baselines. The achieved scores for Recall, Precision, F1-score, Accuracy and Kappa measures are 90.36%, 88.43%, 88.41%, 87.67%, and 75.24%, respectively. Our study reveals that the frontal and temporal lobes show significant differences between PD patients and healthy individuals. In addition, EEG features extracted by ASGCNN demonstrate significant asymmetry in the frontal lobe among PD patients. These findings can offer a basis for the establishment of a clinical system for intelligent diagnosis of PD by using auditory cognitive impairment features.