Cognitive Decline In Parkinson's Disease Research Articles

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.

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.

Validation of the Italian version of the Parkinson’s Disease- Cognitive Functional Rating Scale

A key distinguishing factor between mild cognitive impairment (MCI) and dementia in Parkinson’s disease (PD) lies in the notable decrease in functioning due to cognitive impairment. The Parkinson’s Disease-Cognitive Functional Rating Scale (PD-CRFS) was developed to assess functional limitations caused by cognitive impairment, while reducing the influence of motor impairment. The aim of this multicenter study was to (i) validate the Italian version of the PD-CFRS in PD, (ii) determine optimal cut-off scores for detecting MCI and dementia in PD, (iii) compare its performances with the most established functional assessment tool (IADL). Six hundred and sixty nine PD participants were recruited from 4 Italian Movement Disorders centers (Venice, Milan, Gravedona, and Salerno). They underwent Level-II cognitive evaluation, which resulted in 282 PD-NC, 310 PD-MCI, and 77 PDD. The PD-CFRS’s psychometric and clinimetric properties, applicability, and responsiveness were analyzed. The PD-CFRS showed high acceptability. Floor and ceiling effects were acceptable. It also displayed strong internal consistency (Cronbach’s α = 0.738), and test–retest reliability (ICC = .854). The PD-CFRS demonstrated higher coefficient of variation to detect dysfunction in PD-MCI patients in comparison to the IADL scale (PD-CFRS 96% vs IADL 22.5%). Convergent validity with the IADL was r = − 0.638 and − 0.527 in males and females, respectively. PD-CFRS total score negatively correlated with global cognition (MoCA corrected score r = − 0.61; p < 0.001). A cut-off score > 6.5 identified PDD with a sensitivity of 90% and specificity of 88% (AUC = .959). A cut-off value of > 1 detected PD-MCI with a sensitivity of 68% and specificity of 69% (AUC = .695). The Italian version of the PD-CFRS demonstrated to be an easy, valid and reliable tool that properly captures functional impairment due to cognitive decline in PD. It also proved to be particularly effective in the advanced stages of PD, and would be a useful support for the diagnosis of PD-MCI and PDD.

Proxy-analysis of the genetics of cognitive decline in Parkinson’s disease through polygenic scores

Cognitive decline is common in Parkinson’s disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e–13), cognitive performance (p = 1.46e–12), educational attainment (p = 8.52e–10), and reasoning (p = 3.58e–5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant’s cognitive reserve for cognitive outcome in PD.

Predicting the occurrence of mild cognitive impairment in Parkinson's disease using structural MRI data.

Mild cognitive impairment (MCI) is a common symptom observed in individuals with Parkinson's disease (PD) and a main risk factor for progressing to dementia. Our objective was to identify early anatomical brain changes that precede the transition from healthy cognition to MCI in PD. Structural T1-weighted magnetic resonance imaging data of PD patients with healthy cognition at baseline were downloaded from the Parkinson's Progression Markers Initiative database. Patients were divided into two groups based on the annual cognitive assessments over a 5-year time span: (i) PD patients with unstable healthy cognition who developed MCI over a 5-year follow-up (PD-UHC, n = 52), and (ii) PD patients who maintained stable healthy cognitive function over the same period (PD-SHC, n = 52). These 52 PD-SHC were selected among 192 PD-SHC patients using propensity score matching method to have similar demographic and clinical characteristics with PD-UHC at baseline. Seventy-five percent of these were used to train a support vector machine (SVM) algorithm to distinguish between the PD-UHC and PD-SHC groups, and tested on the remaining 25% of individuals. Shapley Additive Explanations (SHAP) feature analysis was utilized to identify the most informative brain regions in SVM classifier. The average accuracy of classifying PD-UHC vs. PD-SHC was 80.76%, with 82.05% sensitivity and 79.48% specificity using 10-fold cross-validation. The performance was similar in the hold-out test sets with all accuracy, sensitivity, and specificity at 76.92%. SHAP analysis showed that the most influential brain regions in the prediction model were located in the frontal, occipital, and cerebellar regions as well as midbrain. Our machine learning-based analysis yielded promising results in identifying PD individuals who are at risk of cognitive decline from the earliest disease stage and revealed the brain regions which may be linked to the prospective cognitive decline in PD before clinical symptoms emerge.

Relationship between plasma NFL and disease progression in Parkinson's disease: a prospective cohort study.

We aimed to examine the longitudinal change of plasma neurofilament light chain (NFL) level and explore its diagnostic and prognostic implications in Parkinson's disease (PD). A total of 184 patients with early PD who completed 5-year annually repeated clinical assessments were included. Plasma NFL at baseline, 1year, and 2year were examined, which were quantified using the ultrasensitive Simoa technology. At baseline, blood from 86 sex- and age-matched healthy controls (HC) were obtained for comparison. Plasma NFL in PD patients at baseline was significantly higher than those in HC (P = 0.046), and significantly increased after 2years (P = 0.046). Receiver operating characteristic curve indicated that a plasma NFL cut-off value of 10.79pg/mL resulted in 39.7% sensitivity and 84.0% specificity, with an area under the curve of 0.635, to distinguish PD from HC (P < 0.001). Linear mixed-effect models indicated that baseline plasma NFL (> 9.24pg/mL) correlated with a greater increase in the Unified Parkinson's Disease Rating Scale III (estimate = 0.651, P = 0.001) and Hoehn & Yahr stage (estimate = 0.072, P < 0.001), and also correlated with a greater decrease in the Montreal Cognitive Assessment (estimate = -0.387, P < 0.001) during follow-up visits. Plasma NFL exhibits a tendency to increase with disease progression, and elevated baseline plasma NFL can serve as a predictor for accelerated motor deterioration and cognitive decline in PD. However, plasma NFL does not have high accuracy to distinguish individuals with early-stage PD from HC.

Current level of knowledge about Parkinson’s disease cognitive impairment: review

Background: Parkinson’s disease (PD) affects more than 1% of the population aged over 65 years and manifests with both motor symptoms – bradykinesia, rest tremor, rigidity, and non-motor symptoms. Cognitive impairment and dementia are recognized non-motor symptoms that can significantly affect the quality of life of both the patient and caregivers and are a risk factor for institutionalization in nursing homes and a risk factor for early mortality. Cognitive impairment is frequent in Parkinson’s disease (PD) that can develop even before the diagnosis of Parkinson’s disease based on its motor features. Conclusions: There are several clinical, molecular, and imaging factors that constitute risk factors for the development of Parkinson’s disease dementia, in which basal cholinergic and prefrontal dopaminergic systems are involved. Histological changes are Lewy-body, Alzheimer, but also vascular pathology. Clinically can be distinguished subjective cognitive decline, mild cognitive impairment and, subsequently, Parkinson’s disease dementia. There are no remedies with a proven effect to prevent the occurrence of cognitive decline in PD. The only approved drug for already developed D-PD is the cholinesterase inhibitor – donepezil. Non-pharmacological interventions are thought to be beneficial. A multidisciplinary approach to cognitive impairment is recommended, with specific pharmaceutical treatment of the cognitive disorder and comorbidities, and appropriate rehabilitation.

1 Basal Forebrain Free Water Fraction is Associated with Cortical Cholinergic Levels in Idiopathic Parkinson’s Disease

Objective:Cognitive dysfunction is a common non-motor symptom of Parkinson’s disease (PD). Cognitive decline in PD is likely associated with dysfunction in the cholinergic system, which is affected by synuclein pathology early in the disease course. Recent studies have shown an association between reduced integrity of the basal forebrain (BF), which provides cholinergic innervation to most of cortex, and diminished cognitive functioning in PD. Specifically, those with PD and reduced cholinergic innervation also have higher rates of cognitive impairment. However, no study has directly investigated the relationship between basal forebrain integrity and cortical cholinergic levels. In the present study, we examined this relationship through measures of basal forebrain microstructural integrity and cholinergic nerve terminal density in cortical and subcortical gray matter.Participants and Methods:Participants included 92 non-demented individuals with idiopathic PD (M:F=64:28; Age=67.0±7.1 yrs) who underwent structural MRI, diffusion MRI, and [18F] fluoroethoxybenzovesamicol (FEOBV) cholinergic PET imaging. We used a basal forebrain and region of interest defined by AssemblyNet, which uses ensembles of pretrained convolutional neural networks to create a full brain segmentation. Bilateral putamen from this atlas was also included as a control region. We measured microstructural integrity using free water fraction (FWF), a diffusion MRI-derived metric of extracellular water that associates with cellular density and neuroinflammation. For PET data, we computed the distribution volume ratio (DVR) by regions as defined by FreeSurfer. A factor analysis of DVR in all 88 FreeSurfer ROIs resulted in seven clusters of ROIs covering 1) widespread bilateral cortical regions (PC1); 2) subcortical and limbic regions (PC2); 3) bilateral cingulate regions (PC3); 4) left frontal regions (PC4); 5) right frontal and temporal regions (PC5); 6) cerebellum (PC6); and 7) bilateral entorhinal cortex and left temporal cortex (PC7). We performed seven separate regression analyses per ROI (controlling for age and disease duration) to evaluate the association between BF FWF and cholinergic levels in these regions. To determine if these ROIs showed unique associations with BF FWF, we then entered ROIs with a significant association with BF FWF as independent variables in a stepwise regression with forward selection with BF FWF as the dependent variable.Results:BF FWF was significantly and negatively associated with cholinergic levels in PC1 (AR2=.042, ß=-0.208, p=.04), PC3 (AR2=.044, ß=-0.206, p=.03), PC4 (AR2=.056, ß=-0.239, p=.02), and PC7 (ß=-0.215, p=.04). BF FWF trended towards a negative association with cholinergic levels in PC5 (AR2=.045, ß=-0.168, p=.09) and PC6 (ß=-0.188, p=.09). Putamen FWF did not significantly associate with any of the ROIs. In the follow-up stepwise regression, only PC4 contributed significantly to the overall model (AR2=.061, ß=-0.261, p=.02).Conclusions:Basal forebrain FWF was inversely related to cholinergic levels in regions that are directly innervated by the basal forebrain (e.g., cingulate cortex, left frontal cortex, and bilateral entorhinal cortex). Future research should directly investigate the relationship between basal forebrain integrity, cortical cholinergic levels, and cognition. Separating the basal forebrain into specific nuclei would also be beneficial, as different nuclei may have differing associations with specific hemispheric cholinergic pathways and cognition.

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).

A fixel-based analysis of white matter reductions early detects Parkinson disease with mild cognitive impairment

BackgroundWhite matter (WM) tract alterations are early signs of cognitive impairment in Parkinson disease (PD) patients. Fixel-based analysis (FBA) has advantages over traditional diffusion tensor imaging in managing complex and crossing fibers. We used FBA to measure fiber-specific changes in patients with PD mild cognitive impairment (PD-MCI) and PD normal cognition (PD-NC). MethodsSeventy-one patients with PD without dementia were included: 39 PD-MCI and 32 PD-NC. All underwent diffusion-weighted imaging, clinical examinations, and tests to evaluate their cognitive function globally and in five cognitive domains. FBA was used to investigate fiber-tract alterations and compare PD-MCI with PD-NC subjects. Correlations with each cognitive test were analyzed. ResultsPatients with PD-MCI were significantly older (P = 0.044), had a higher male-to-female ratio (P = 0.006) and total Unified Parkinson's Disease Rating Scale score (P = 0.001). All fixel-based metrics were significantly reduced within the body of the corpus callosum and superior corona radiata in PD-MCI patients (family-wise error-corrected P value < 0.05) compared with PD-NC patients. The cingulum, superior longitudinal fasciculi, and thalamocortical circuit exhibited predominantly fiber-bundle cross-section (FC) changes. In regression analysis, reduced FC values in cerebellar circuits were associated with poor motor function in PD-MCI patients and poor picture-naming ability in PD-NC patients. ConclusionsPD-MCI patients have significant WM alterations compared with PD-NC patients. FBA revealed these changes in various bundle tracts, helping us to better understand specific WM changes that are functionally implicated in PD cognitive decline. FBA is potentially useful in detecting early cognitive decline in PD.

Original research: initial development of a pragmatic tool to estimate cognitive decline risk focusing on potentially modifiable factors in Parkinson’s disease

IntroductionCognitive decline is common in Parkinson’s disease (PD). Calculating personalized risk of cognitive decline in PD would allow for appropriate counseling, early intervention with available treatments, and inclusion in disease-modifying trials.MethodsData were from the Parkinson’s Progression Markers Initiative de novo cohort. Baseline scores were calculated for Lifestyle for Brain Health (LIBRA) and the Montreal Parkinson Risk of Dementia Scale (MoPaRDS) per prior literature and preliminary Parkinson’s disease Risk Estimator for Decline In Cognition Tool (pPREDICT) by attributing a point for fourteen posited risk factors. Baseline and 5-year follow-up composite cognitive scores (CCSs) were calculated from a neuropsychological battery and used to define cognitive decliners (PD-decline) versus maintainers (PD-maintain).ResultsThe PD-decline group (n = 44) had higher LIBRA (6.76 ± 0.57, p &amp;lt; 0.05), MoPaRDS (2.45 ± 1.41, p &amp;lt; 0.05) and pPREDICT (4.52 ± 1.66, p &amp;lt; 0.05) scores compared to the PD-maintain group (n = 263; LIBRA 4.98 ± 0.20, MoPaRDS 1.68 ± 1.16, pPREDICT 3.38 ± 1.69). Area-under-the-curve (AUC) for LIBRA was 0.64 (95% confidence interval [CI], 0.55–0.73), MoPaRDS was 0.66 (95% CI, 0.58–0.75) and for pPREDICT was 0.68 (95% CI, 0.61–0.76). In linear regression analyses, LIBRA (p &amp;lt; 0.05), MoPaRDS (p &amp;lt; 0.05) and pPREDICT (p &amp;lt; 0.05) predicted change in CCS. Only age stratified by sex (p &amp;lt; 0.05) contributed significantly to the model for LIBRA. Age and presence of hallucinations (p &amp;lt; 0.05) contributed significantly to the model for MoPaRDS. Male sex, older age, excessive daytime sleepiness, and moderate–severe motor symptoms (all p &amp;lt; 0.05) contributed significantly to the model for pPREDICT.ConclusionAlthough MoPaRDS is a PD-specific tool for predicting cognitive decline relying on only clinical features, it does not focus on potentially modifiable risk factors. LIBRA does focus on potentially modifiable risk factors and is associated with prediction of all-cause dementia in some populations, but pPREDICT potentially demonstrates improved performance in cognitive decline risk calculation in individuals with PD and may identify actionable risk factors. As pPREDICT incorporates multiple potentially modifiable risk factors that can be obtained easily in the clinical setting, it is a first step in developing an easily assessable tool for a personalized approach to reduce dementia risk in people with PD.

An interpretable multiparametric radiomics model of basal ganglia to predict dementia conversion in Parkinson’s disease

Cognitive impairment in Parkinson’s disease (PD) severely affects patients’ prognosis, and early detection of patients at high risk of dementia conversion is important for establishing treatment strategies. We aimed to investigate whether multiparametric MRI radiomics from basal ganglia can improve the prediction of dementia development in PD when integrated with clinical profiles. In this retrospective study, 262 patients with newly diagnosed PD (June 2008–July 2017, follow-up >5 years) were included. MRI radiomic features (n = 1284) were extracted from bilateral caudate and putamen. Two models were developed to predict dementia development: (1) a clinical model—age, disease duration, and cognitive composite scores, and (2) a combined clinical and radiomics model. The area under the receiver operating characteristic curve (AUC) were calculated for each model. The models’ interpretabilities were studied. Among total 262 PD patients (mean age, 68 years ± 8 [standard deviation]; 134 men), 51 (30.4%), and 24 (25.5%) patients developed dementia within 5 years of PD diagnosis in the training (n = 168) and test sets (n = 94), respectively. The combined model achieved superior predictive performance compared to the clinical model in training (AUCs 0.928 vs. 0.894, P = 0.284) and test set (AUCs 0.889 vs. 0.722, P = 0.016). The cognitive composite scores of the frontal/executive function domain contributed most to predicting dementia. Radiomics derived from the caudate were also highly associated with cognitive decline. Multiparametric MRI radiomics may have an incremental prognostic value when integrated with clinical profiles to predict future cognitive decline in PD.

Investigating cortico-striatal beta oscillations in Parkinson's disease cognitive decline.

This scientific commentary refers to ‘Corticostriatal beta oscillation changes associated with cognitive function in Parkinson’s disease’ by Paulo et al. (https://doi.org/10.1093/brain/awad206).

Basal Forebrain Atrophy, Cortical Thinning, and Amyloid-β Status in Parkinson's disease-Related Cognitive Decline.

Degeneration of the cortically-projecting cholinergic basal forebrain (cBF) is a well-established pathologic correlate of cognitive decline in Parkinson's disease (PD). In Alzheimer's disease (AD) the effect of cBF degeneration on cognitive decline was found to be mediated by parallel atrophy of denervated cortical areas. To examine whether the association between cBF degeneration and cognitive decline in PD is mediated by parallel atrophy of cortical areas and whether these associations depend on the presence of comorbid AD pathology. We studied 162 de novo PD patients who underwent serial 3 T magnetic resonance imaging scanning (follow-up: 2.33 ± 1.46 years) within the Parkinson's Progression Markers Initiative. cBF volume and regional cortical thickness were automatically calculated using established procedures. Individual slopes of structural brain changes and cognitive decline were estimated using linear-mixed models. Associations between longitudinal cBF degeneration, regional cortical thinning, and cognitive decline were assessed using regression analyses and mediation effects were assessed using nonparametric bootstrap. Complementary analyses assessed the effect of amyloid-β biomarker positivity on these associations. After controlling for global brain atrophy, longitudinal cBF degeneration was highly correlated with faster cortical thinning (PFDR  < 0.05), and thinning in cBF-associated cortical areas mediated the association between cBF degeneration and cognitive decline (rcBF-MoCA  = 0.30, P < 0.001). Interestingly, both longitudinal cBF degeneration and its association with cortical thinning were largely independent of amyloid-β status. cBF degeneration in PD is linked to parallel thinning of cortical target areas, which mediate the effect on cognitive decline. These associations are independent of amyloid-β status, indicating that they reflect proper features of PD pathophysiology. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Associations of Alzheimer's-related plasma biomarkers with cognitive decline in Parkinson's disease.

Parkinson's disease (PD) is associated with cognitive decline through multiple mechanisms, including Alzheimer's disease (AD) pathology and cortical Lewy body involvement. However, its underlying mechanisms remain unclear. Recently, AD-related plasma biomarkers have emerged as potential tools for predicting abnormal pathological protein accumulation. We aimed to investigate the association between AD-related plasma biomarkers and cognitive decline in PD patients. Plasma biomarkers were measured in 70 PD patients (49 with nondemented Parkinson's disease (PDND) and 21 with Parkinson's disease dementia (PDD)) and 38 healthy controls (HCs) using a single-molecule array. The study evaluated (1) the correlation between plasma biomarkers and clinical parameters, (2) receiver operating characteristic curves and areas under the curve to evaluate the discrimination capacity of plasma biomarkers among groups, and (3) a generalized linear model to analyze associations with Addenbrooke's Cognitive Examination-Revised and Montreal Cognitive Assessment-Japanese version scores. Plasma glial fibrillary acidic protein significantly correlated with cognitive function tests, including all subdomains, with a notable increase in the PDD group compared with the HC and PDND groups, while plasma neurofilament light chain captured both cognitive decline and disease severity in the PDND and PDD groups. Plasma beta-amyloid 42/40 and pholphorylated-tau181 indicated AD pathology in the PDD group, but plasma beta-amyloid 42/40 was increased in the PDND group compared with HCs and decreased in the PDD group compared with the PDND group. AD-related plasma biomarkers may predict cognitive decline in PD and uncover underlying mechanisms suggesting astrocytic pathologies related to cognitive decline in PD.

Third ventricular width by transcranial sonography is associated with cognitive impairment in Parkinson's disease.

One-fourth of Parkinson's disease (PD) patients suffer from cognitive impairment. However, few neuroimaging markers have been identified regarding cognitive impairment in PD. This study aimed to explore the association between third ventricular width by transcranial sonography (TCS) and cognitive decline in PD. Participants with PD were recruited from one medical center in China. Third ventricular width was assessed by TCS, and cognitive function was analyzed by the Mini-Mental State Examination (MMSE). Receiver operating characteristic (ROC) analysis and Cox model analysis were utilized to determine the diagnostic and predictive accuracy of third ventricular width by TCS for cognitive decline in PD patients. A total of 174 PD patients were recruited. Third ventricular width was negatively correlated with MMSE scores. ROC analysis suggested that the optimal cutoff point for third ventricular width in screening for cognitive impairment in PD was 4.75 mm (sensitivity 62.7%; specificity 75.6%). After 21.5 (18.0, 26.0) months of follow-up in PD patients without cognitive impairment, it was found that those with a third ventricular width greater than 4.75 mm exhibited a 7.975 times higher risk of developing cognitive impairment [hazard ratio = 7.975, 95% CI 1.609, 39.532, p = 0.011] compared with patients with a third ventricular width less than 4.75 mm. Third ventricular width based on TCS emerged as an independent predictor of developing cognitive impairment in PD patients.

Original research: longitudinal evaluation of cognitively demanding daily function using performance-based functional assessment highlights heterogeneous trajectories in cognitive and functional abilities in people with Parkinson's disease.

Longitudinal assessment of functional abilities in Parkinson's disease (PD) is needed to determine the efficacy of cognitive interventions in providing meaningful improvements in daily life. Additionally, subtle changes in instrumental activities of daily living may precede a clinical diagnosis of dementia and could aid earlier detection of and intervention for cognitive decline. The primary goal was to validate the longitudinal application of the University of California San Diego Performance-Based Skills Assessment (UPSA). An exploratory secondary goal was to determine whether UPSA may identify individuals at higher risk of cognitive decline in PD. Seventy participants with PD completed the UPSA with at least one follow-up visit. Linear mixed effects modeling was used to identify associations between baseline UPSA score and cognitive composite score (CCS) over time. Descriptive analysis of four heterogeneous cognitive and functional trajectory groups and individual case examples was performed. Baseline UPSA score predicted CCS at each timepoint for functionally impaired and unimpaired groups (p < 0.01) but did not predict the rate change in CCS over time (p = 0.83). Participants displayed heterogenous trajectories in both UPSA and CCS during the follow-up period. Most participants maintained both cognitive and functional performance (n = 54), though some displayed cognitive and functional decline (n = 4), cognitive decline with functional maintenance (n = 4), and functional decline with cognitive maintenance (n = 8). The UPSA is a valid measure of cognitive functional abilities over time in PD. Given the heterogeneity of functional and cognitive trajectories, this performance-based assessment did not predict cognitive decline with this relatively short follow-up. Further work is needed to understand longitudinal functional assessments in PD-associated cognitive impairment.