Does the Montreal Cognitive Assessment (MoCA) identify cognitive impairment profiles in Parkinson’s disease? An exploratory study

Cognitive impairment (CI) is a common nonmotor complication of Parkinson's disease (PD), and is associated with significant disability for patients and burden for caregivers. Similar to motor symptoms, the characteristics of CI in PD can be quite variable, both in terms of what cognitive domains are impaired, and the timing of onset and rate of progression. This review will examine the profile of cognitive domain impairments observed in PD, with a focus on early CI (without dementia). We will also discuss possible relationships between specific cognitive domain impairments in PD and pathological processes such as Lewy-related pathology and Alzheimer's disease. It is our hypothesis that the specific characteristics of CI observed in individual PD patients provide clues to the underlying pathological processes, and that understanding the biological basis of this clinical phenomenon will assist in directing disease-specific treatments. Given the high lifetime risk for CI in PD, it is imperative that we improve our understanding and treatments for this common and disabling problem in PD.

Objective: To establish the diagnostic accuracy of the Montreal Cognitive Assessment (MoCA) when screening externally validated cognition in Parkinson disease (PD), by comparison with a PD-focused test (Scales for Outcomes in Parkinson disease–Cognition [SCOPA-COG]) and the standardized Mini-Mental State Examination (S-MMSE) as benchmarks. Methods: A convenience sample of 114 patients with idiopathic PD and 47 healthy controls was examined in a movement disorders center. The 21 patients with dementia (PD-D) were diagnosed using Movement Disorders Society criteria, externally validated by detailed independent functional and neuropsychological tests. The 21 patients with mild cognitive impairment (PD-MCI) scored 1.5 SD or more below normative data in at least 2 measures in 1 of 4 cognitive domains. Other patients had normal cognition (PD-N). Results: Primary outcomes using receiver operating characteristic (ROC) curve analyses showed that all 3 mental status tests produced excellent discrimination of PD-D from patients without dementia (area under the curve [AUC], 87%–91%) and PD-MCI from PD-N patients (AUC, 78%–90%), but the MoCA was generally better suited across both assessments. The optimal MoCA screening cutoffs were Conclusions: The MoCA is a suitably accurate, brief test when screening all levels of cognition in PD.

Background: Cognitive impairment is prevalent in Parkinson's disease (PD), affecting 15–20% of patients at diagnosis. α-synuclein expression and genetic polymorphisms of Apolipoprotein E (ApoE) have been associated with the presence of cognitive impairment in PD although data have been inconsistent.Objectives: To determine the prevalence of cognitive impairment in patients with PD using Montreal Cognitive Assessment (MoCA), Comprehensive Trail Making Test (CTMT) and Parkinson's disease-cognitive rating scale (PDCRS), and its association with plasma α-synuclein and ApoE genetic polymorphisms.Methods: This was across-sectional study involving 46 PD patients. Patients were evaluated using Montreal cognitive assessment test (MoCA), and detailed neuropsychological tests. The Parkinson's disease cognitive rating scale (PDCRS) was used for cognitive function and comprehensive trail making test (CTMT) for executive function. Blood was drawn for plasma α-synuclein measurements and ApoE genetic analysis. ApoE polymorphism was detected using MutaGELAPoE from ImmunDiagnostik. Plasma α-synuclein was detected using the ELISA Technique (USCN Life Science Inc.) according to the standard protocol.Results: Based on MoCA, 26 (56.5%) patients had mild cognitive impairment (PD-MCI) and 20 (43.5%) had normal cognition (PD-NC). Based on the PDCRS, 18 (39.1%) had normal cognition (PDCRS-NC), 17 (37%) had mild cognitive impairment (PDCRS-MCI), and 11 (23.9%) had dementia (PDCRS-PDD). In the PDCRS-MCI group, 5 (25%) patients were from PD-NC group and all PDCRS-PDD patients were from PD-MCI group. CTMT scores were significantly different between patients with MCI and normal cognition on MoCA (p = 0.003). Twenty one patients (72.4%) with executive dysfunction were from the PD-MCI group; 17 (77.3%) with severe executive dysfunction and 4 (57.1%) had mild to moderate executive dysfunction. There were no differences in the plasma α-synuclein concentration between the presence or types of cognitive impairment based on MoCA, PDCRS, and CTMT. TheApoEe4 allele carrier frequency was significantly higher in patients with executive dysfunction (p = 0.014).Conclusion: MCI was prevalent in our PD population. PDCRS appeared to be more discriminatory in detecting MCI and PDD than MoCA. Plasma α-synuclein level was not associated with presence nor type of cognitive impairment, but the ApoEe4 allele carrier status was significantly associated with executive dysfunction in PD.

Cognitive impairment (CI) is recognized as a debilitating complication of Parkinson's disease (PD). This study was designed to develop a diagnostic classification model by integrating substantia nigra hyperechogenicity (SNH) and inflammationassociated biomarkers to evaluate its diagnostic performance in distinguishing PD CI stages. Between January, 2023 and May, 2024, 184 patients with PD who underwent transcranial sonography were prospectively enrolled. Based on Montreal Cognitive Assessment (MoCA) scores, participants were categorized into three groups: cognitive impairment (PD-CI, MoCA <26), mild cognitive impairment (PD-MCI, MoCA 22-25), and dementia (PD-dementia, MoCA ≤21). Ultrasound features and inflammationassociated biomarkers were screened with univariate analyses. Multivariate logistic regression was used to identify independent diagnostic factors, and receiver operating characteristic (ROC) curve analysis was used to assess model discrimination. Multivariate regression analysis indicated that age <50 years and more years of education were significantly associated factors for CI (OR = 0.170, p = 0.0350; OR = 0.8780, p = 0.0020, respectively), whereas Unified Parkinson's Disease Rating Scale Part III (UPDRSIII) score (OR = 1.024, p = 0.0270), SNH (OR = 2.550, p = 0.0030), elevated C-reactive protein (CRP) (OR = 2.038, p = 0.0350), and elevated homocysteine (Hcy) (OR = 2.830, p = 0.0020) were independent risk factors. The area uinder the curves (AUCs) for the combined SNH+CRP+Hcy model in predicting PD-CI, PD-MCI, and PD-dementia were 0.783, 0.729, and 0.823, respectively; these values were significantly superior to those for single or dual marker combinations (p < 0.05), with the strongest performance for distinguishing PD-dementia. An SNH and inflammationassociated biomarkerbased model was developed for predicting the stage of cognitive impairment in PD. Clinical targets for individualized intervention can be provided, and clinical risk stratification and care pathways can be optimized. Furthermore, the model supports the iron deposition-neuroinflammation-CI pathway hypothesis, providing a mechanistic rationale for ultrasoundbased PD-CI diagnosis.

Little is known about the impact of the dopamine system on development of cognitive impairment (CI) in Parkinson disease (PD). We used data from a multi-site, international, prospective cohort study to explore the impact of dopamine system-related biomarkers on CI in PD. PD participants were assessed annually from disease onset out to 7 years, and CI determined by applying cut-offs to four measures: (1) Montreal Cognitive Assessment; (2) detailed neuropsychological test battery; (3) Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) cognition score; and (4) site investigator diagnosis of CI (mild cognitive impairment or dementia). The dopamine system was assessed by serial Iodine-123 Ioflupane dopamine transporter (DAT) imaging, genotyping, and levodopa equivalent daily dose (LEDD) recorded at each assessment. Multivariate longitudinal analyses, with adjustment for multiple comparisons, determined the association between dopamine system-related biomarkers and CI, including persistent impairment. Demographic and clinical variables associated with CI were higher age, male sex, lower education, non-White race, higher depression and anxiety scores and higher MDS-UPDRS motor score. For the dopamine system, lower baseline mean striatum dopamine transporter values (P range 0.003-0.005) and higher LEDD over time (P range <0.001-0.01) were significantly associated with increased risk for CI. Our results provide preliminary evidence that alterations in the dopamine system predict development of clinically-relevant, cognitive impairment in Parkinson's disease. If replicated and determined to be causative, they demonstrate that the dopamine system is instrumental to cognitive health status throughout the disease course. Parkinson's Progression Markers Initiative is registered with ClinicalTrials.gov (NCT01141023).

The early diagnosis of mild cognitive impairment (PD-MCI) in Parkinson's disease (PD) is essential as it increases the future risk for PD dementia (PDD). Recently, a novel weighting algorithm for the Montreal Cognitive Assessment (MoCA) subtests has been reported, to best discriminate between those with and without cognitive impairment in PD. The aim of our study was to validate this scoring algorithm in a large sample of non-demented PD patients, hypothesizing that the weighted MoCA would have a higher diagnostic accuracy for PD-MCI than the original MoCA. In 202 non-demented PD patients, we evaluated cognitive status, clinical and demographic data, as well as the MoCA with a weighted and unweighted score. Receiver operating characteristic (ROC) curve analysis was used to evaluate discriminative ability of the MoCA. Group comparisons and ROC analysis were performed for PD-MCI classifications with a cut-off ≤ 1, 1.5, and 2 standard deviation (SD) below appropriate norms. PD-MCI patients scored lower on the weighted than the original MoCA version (p < 0.001) compared to PD patients with normal cognitive function. Areas under the curve only differed significantly for the 2 SD cut-off, leading to an increased sensitivity of the weighted MoCA score (72.9% vs. 70.5%) and specificity compared to the original version (79.0% vs. 65.4%). Our results indicate better discriminant power for the weighted MoCA compared to the original for more advanced stages of PD-MCI (2 SD cut-off). Future studies are needed to evaluate the predictive value of the weighted MoCA for PDD.

The impact of Parkinson’s disease (PD) dementia is substantial and has major functional and socioeconomic consequences. Early prediction of future cognitive impairment would help target future interventions. The Montreal Cognitive Assessment (MoCA), the Mini-Mental State Examination (MMSE), and fluency tests were administered to 486 patients with PD within 3.5 years of diagnosis, and the results were compared with those from 141 controls correcting for age, sex, and educational years. Eighteen-month longitudinal assessments were performed in 155 patients with PD. The proportion of patients classified with normal cognition, mild cognitive impairment (MCI), and dementia varied considerably, depending on the MoCA and MMSE thresholds used. With the MoCA total score at screening threshold, 47.7%, 40.5%, and 11.7% of patients with PD were classified with normal cognition, MCI, and dementia, respectively; by comparison, 78.7% and 21.3% of controls had normal cognition and MCI, respectively. Cognitive impairment was predicted by lower education, increased age, male sex, and quantitative motor and non-motor (smell, depression, and anxiety) measures. Longitudinal data from 155 patients with PD over 18 months showed significant reductions in MoCA scores, but not in MMSE scores, with 21.3% of patients moving from normal cognition to MCI and 4.5% moving from MCI to dementia, although 13.5% moved from MCI to normal; however, none of the patients with dementia changed their classification. The MoCA may be more sensitive than the MMSE in detecting early baseline and longitudinal cognitive impairment in PD, because it identified 25.8% of those who experienced significant cognitive decline over 18 months. Cognitive decline was associated with worse motor and non-motor features, suggesting that this reflects a faster progressive phenotype.

Background/Objectives: Cognitive impairment (CI) in Parkinson's disease (PD) is a major burden and significantly affects patients' quality of life. Previous studies found that older age at onset and presence of the akinetic-rigid (AR) subtype are associated with an increased likelihood of CI in PD. The present study aimed to assess factors that are related to the development of CI in PD. Methods: Eighty-three PD patients were consecutively recruited. Demographic information, clinical details, Montreal cognitive assessment (MoCA), Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), walking speed, and instrumental activity of daily living (IADL) were assessed. Resting motor threshold (rMT), was also assessed for subgroup of patients with versus without cognitive impairment. Results: According to the MoCA cut-off score of 26, 45 had PD without CI (PD-NCI) (54.22%) and 38 cases (45.78%) had PD with CI (PD-CI). The age and age at onset were significantly older in the PD-CI group (p = 0.006 and 0.018, respectively). The patients were reclassified into AR and tremor-dominant (TR) phenotype. PD-CI patients were more likely to have the AR (81.6%). Walking speed, MDS-UPDRS score, and IADL scores were significantly worse in PD-CI than in PD-NCI. Stepwise linear regression analysis of risk factors associated CI revealed that higher MDS-UPDRS scores, later age of onset, and higher rMT values were considered risk factors for developing CI. Conclusions: Higher UPDRS score, later age of onset, and higher rMT values were considered as risk factors associated CI in PD patients and provide valuable insights for further investigation and potential clinical considerations.

Which figure copy test is more sensitive for cognitive impairment in Parkinson's disease: Wire cube or interlocking pentagons?

Recognition of early cognitive impairment in Parkinsons disease (PD) is important since it represents a risk factor for developing Parkinson's disease dementia and psychosis. The Mini- Mental State Examination (MMSE) remains the most commonly used screening instrument for global cognition, even though it has not been specifically validated for use in PD subjects. More recently, the Montreal Cognitive Assessment (MoCA) test has been recommended as a better screening tool in PD. Most of these studies have been done in countries with a highly-educated population. The objective of the study is to compare the performance between the MMSE and the MoCA to screen for mild cognitive impairment in subjects with Parkinson's disease and a low education background. The MMSE and MoCA were applied to 128 subjects using a cut-off score of 26 points for cognitive impairment. Fifty-five percent were classified with cognitive impairment according to the MoCA. Forty-one percent of subjects with a normal MMSE were classified with cognitive impairment by MoCA. Results from our analysis could be directly applied to other populations with a high proportion of poorly educated subjects.

Cognitive impairment (CI) is common in Parkinson's disease (PD) and an important cause of disability. Screening facilitates early detection of CI and has implications for management. Preclinical disability is when patients have functional limitations but maintain independence through compensatory measures. The objective of this study was to investigate the relationship between scores on the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) with levels of PD severity and disability. PD patients (n = 2,234) in a large observational study were stratified by disease severity, based on Total Unified Parkinson's Disease Rating Scale (Total UPDRS) and Hoehn and Yahr (HY) stage. Using MMSE (n = 1,184) or MoCA (n = 1,050) and basic (ADL) and instrumental activities of daily living (IADL) scales for disability, linear regression analysis examined associations between cognitive status and disability. Cognition and disability were highly correlated, with the strongest correlation between IADL and MoCA. Only 16.0% of mean MMSE scores were below threshold for CI (28) and only in advanced PD (Total UPDRS 60+, HY≥3). MoCA scores fell below CI threshold (26) in 66.2% of the sample and earlier in disease (Total UPDRS 30+, HY≥2), corresponding with impairments in ADLs. In a large clinical dataset, a small fraction of MMSE scores fell below cutoff for CI, reinforcing that MMSE is an insensitive screening tool in PD. MoCA scores indicated CI earlier in disease and coincided with disability. This study shows that MoCA, but not MMSE is sensitive to the emergence of early cognitive impairment in PD and correlates with the concomitant onset of disability.

Aim: Parkinson’s disease (PD) is a progressive neurodegenerative disorder marked by dopaminergic neuron loss, leading to motor and non-motor symptoms. Cognitive impairment in PD (PD-CI), ranging from mild cognitive deficits to dementia, significantly reduces quality of life and increases caregiver burden. This study aims to identify predictors of PD-CI, potentially supporting early interventions. Methods: This one-year prospective observational study included 80 idiopathic PD patients recruited from Al-Azhar University Hospitals. Inclusion followed the Movement Disorder Society (MDS) Clinical Diagnostic Criteria for PD, with evaluations conducted at baseline, 3, 6, and 12 months. Patients underwent clinical assessments [Unified Parkinson’s Disease Rating Scale, Part III (UPDRS-III), Hoehn and Yahr (H-Y), Beck Depression Inventory (BDI), and Hamilton Anxiety Rating Scale (HAM-A)], cognitive evaluations [Brief International Cognitive Assessment for MS (BICAMS) and Montreal Cognitive Assessment (MoCA)], magnetic resonance imaging (MRI), and laboratory testing. Exclusion criteria included conditions such as cerebellar abnormalities, early dementia diagnoses, and other Parkinsonism causes. Results: Cognitive impairment was observed in 41.25% of patients. Those with cognitive impairment were older, had a longer disease duration, and exhibited higher fasting blood glucose (FBS) levels and lower thyroid-stimulating hormone (TSH) levels compared to patients without cognitive impairment (p &lt; 0.05). Brain atrophy was detected in 4 (5%) patients in a subset of patients with PD, which was particularly pronounced in regions associated with cognitive function, such as the hippocampus and frontal lobe. Higher H-Y, UPDRS-III, and BDI scores correlated with cognitive decline, while lower MoCA and Symbol Digit Modalities Test (SDMT) scores predicted impairment (p &lt; 0.05). Conclusions: Cognitive impairment in PD is associated with advanced age, longer disease duration, metabolic factors, and structural brain changes. These findings suggest the potential for a predictive model to identify early cognitive decline in PD, enabling timely intervention and improved patient outcomes.

Objective To investigate the risk factors of Parkinson＇s disease（PD）with mild cognitive impairment and mode of cerebral glucose metabolism. Methods One hundred and one non-dementia PD patients were assessed with Montreal Cognitive Assessment（MoCA）and divided into the PD with mild cognitive impairment （PD-MCI）group and the PD non-cognitive impairment（PD-NC）group. The demographic details, clinical features,Unified Pakinson＇s Disease Rating Scale（UPDRS）, Hohen-Yahr rank and Hamilton Depression Scale（HAMD）were compared between the two groups. Patients in Hohen-Yahr stage 1 underwent positron emission tomography（PET）with 18F-fluorodeoxyglucose（18F-FDG）to show glucose metabolism. Results Seventy-seven（74. 3%）PD patients had mild cognitive impairment PD-MCI group had higher score in UPDRS 1st（mentation ,behavior and mood）,2nd （activity of daily living）and 3rd（motor examination）subscale（2.48 ± 1.51,10. 71 ± 4. 88,22.31 ± 12.70）than PD-NC group（1.65 ± 1.29,8.15 ±2. 20,15.92 ±7.56,P 〈0.05）respectively. The FDG metabolism ratio of frontal cortex,parietal cortex and occipital cortex decreased more significantly in PD-MCI than in PD-NC（P 〈 0.05）.Conclusions The risk factors of mild cognitive impairment in PD include moter dysfunction, clinical stage and depression. The metabolic dysfunction of cortex may be the mechanism of mild cognitive impairment in PD. Key words: Parkinson＇s disease; Cognitive impairment; Positron emission tomography

BackgroundInsulin resistance (IR) is proved be involved in the pathophysiology of Parkinson’s disease (PD). As an effective surrogate marker of IR, the correlation between the triglyceride-glucose (TyG) index and PD remains unclear. This cross-sectional study aimed to explore the association between the TyG index and cognitive impairment in PD (PDCI).MethodsPatients with sporadic PD were consecutively enrolled between May 2022 and October 2023. The cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA). The Spearman correlation analysis was used to evaluate the correlation between TyG index and MoCA score, Unified-Parkinson Disease Rating Scale (UPDRS) III and peripheral blood oxidative stress markers, respectively. Logistic regression analysis was performed to explore the correlation between TyG and PDCI and dementia in PD (PDD).ResultsA total of 78 patients were enrolled, of whom 50 (64.1%) were diagnosed with PDCI [26 with mild cognitive impairment (MCI) and 24 with PDD]. The TyG index in patients with dementia and MCI were higher than those with normal cognition (9.32 ± 0.43 vs. 8.90 ± 0.47 vs. 8.51 ± 0.46, P < 0.001). The Spearman correlation analysis demonstrated that TyG was negatively correlated with MoCA (r = −0.704, P < 0.001) and superoxide dismutase (r = −0.244, P = 0.031), but positively correlated with UPDRS III (r = 0.246, P = 0.030). Multivariate logistic regression analysis showed that TyG was independently associated with PDCI regardless of whether it was used as a continuous variable (OR = 6.177, 95% CI = 1.590–24.000) or a tertile variable (OR = 5.478, 95% CI = 1.030–29.132). This association persisted after excluding patients with diabetes. The receiver operating characteristic (ROC) analysis suggested that the area under the curve (AUC) of TyG for predicting PDCI was 0.805 (95% CI = 0.707–0.903, P < 0.001).ConclusionElevated TyG levels were associated with an increased likelihood of PDCI in patients with PD.

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.