Jacqueline Rick

Impaired olfaction and other prodromal features in the Parkinson At-Risk Syndrome Study.

To test the association between impaired olfaction and other prodromal features of PD in the Parkinson At‐Risk Syndrome Study. The onset of olfactory dysfunction in PD typically precedes motor features, suggesting that olfactory testing could be used as a screening test. A combined strategy that uses other prodromal nonmotor features, along with olfactory testing, may be more efficient than hyposmia alone for detecting the risk of PD. Individuals with no neurological diagnosis completed a mail survey, including the 40‐item University of Pennsylvania Smell Identification Test, and questions on prodromal features of PD. The frequency of reported nonmotor features was compared across individuals with and without hyposmia. A total of 4,999 subjects completed and returned the survey and smell test. Of these, 669 were at or below the 15th percentile based on age and gender, indicating hyposmia. Hyposmics were significantly more likely to endorse nonmotor features, including anxiety and depression, constipation, and rapid eye movement sleep behavior disorder symptoms, and to report changes in motor function. Twenty‐six percent of subjects with combinations of four or more nonmotor features were hyposmic, compared to 12% for those reporting three or fewer nonmotor features (P < 0.0001). Hyposmia is associated with other nonmotor features of PD in undiagnosed individuals. Further assessment of hyposmic subjects using more specific markers for degeneration, such as dopamine transporter imaging, will evaluate whether combining hyposmia and other nonmotor features is useful in assessing the risk of future neurodegeneration.

Diagnosis of Parkinson's disease on the basis of clinical and genetic classification: a population-based modelling study

BACKGROUND Accurate diagnosis and early detection of complex diseases, such as Parkinsons disease, has the potential to be of great benefit for researchers and clinical practice. We aimed to create a non-invasive, accurate classification model for the diagnosis of Parkinsons disease, which could serve as a basis for future disease prediction studies in longitudinal cohorts. METHODS We developed a model for disease classification using data from the Parkinsons Progression Marker Initiative (PPMI) study for 367 patients with Parkinsons disease and phenotypically typical imaging data and 165 controls without neurological disease. Olfactory function, genetic risk, family history of Parkinsons disease, age, and gender were algorithmically selected by stepwise logistic regression as significant contributors to our classifying model. We then tested the model with data from 825 patients with Parkinsons disease and 261 controls from five independent cohorts with varying recruitment strategies and designs: the Parkinsons Disease Biomarkers Program (PDBP), the Parkinsons Associated Risk Study (PARS), 23andMe, the Longitudinal and Biomarker Study in PD (LABS-PD), and the Morris K Udall Parkinsons Disease Research Center of Excellence cohort (Penn-Udall). Additionally, we used our model to investigate patients who had imaging scans without evidence of dopaminergic deficit (SWEDD). FINDINGS In the population from PPMI, our initial model correctly distinguished patients with Parkinsons disease from controls at an area under the curve (AUC) of 0·923 (95% CI 0·900-0·946) with high sensitivity (0·834, 95% CI 0·711-0·883) and specificity (0·903, 95% CI 0·824-0·946) at its optimum AUC threshold (0·655). All Hosmer-Lemeshow simulations suggested that when parsed into random subgroups, the subgroup data matched that of the overall cohort. External validation showed good classification of Parkinsons disease, with AUCs of 0·894 (95% CI 0·867-0·921) in the PDBP cohort, 0·998 (0·992-1·000) in PARS, 0·955 (no 95% CI available) in 23andMe, 0·929 (0·896-0·962) in LABS-PD, and 0·939 (0·891-0·986) in the Penn-Udall cohort. Four of 17 SWEDD participants who our model classified as having Parkinsons disease converted to Parkinsons disease within 1 year, whereas only one of 38 SWEDD participants who were not classified as having Parkinsons disease underwent conversion (test of proportions, p=0·003). INTERPRETATION Our model provides a potential new approach to distinguish participants with Parkinsons disease from controls. If the model can also identify individuals with prodromal or preclinical Parkinsons disease in prospective cohorts, it could facilitate identification of biomarkers and interventions. FUNDING National Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J Fox Foundation.

Longitudinal study of normal cognition in Parkinson disease.

Objective: To report the rates and predictors of progression from normal cognition to either mild cognitive impairment (MCI) or dementia using standardized neuropsychological methods. Methods: A prospective cohort of patients diagnosed with Parkinson disease (PD) and baseline normal cognition was assessed for cognitive decline, performance, and function for a minimum of 2 years, and up to 6. A panel of movement disorders experts classified patients as having normal cognition, MCI, or dementia, with 55/68 (80.9%) of eligible patients seen at year 6. Kaplan-Meier curves and Cox proportional hazard models were used to examine cognitive decline and its predictors. Results: We enrolled 141 patients, who averaged 68.8 years of age, 63% men, who had PD on average for 5 years. The cumulative incidence of cognitive impairment was 8.5% at year 1, increasing to 47.4% by year 6. All incident MCI cases had progressed to dementia by year 5. In a multivariate analysis, predictors of future decline were male sex (p = 0.02), higher Unified Parkinsons Disease Rating Scale motor score (p ≤ 0.001), and worse global cognitive score (p < 0.001). Conclusions: Approximately half of patients with PD with normal cognition at baseline develop cognitive impairment within 6 years and all new MCI cases progress to dementia within 5 years. Our results show that the transition from normal cognition to cognitive impairment, including dementia, occurs frequently and quickly. Certain clinical and cognitive variables may be useful in predicting progression to cognitive impairment in PD.

Cognition following bilateral deep brain stimulation surgery of the subthalamic nucleus for Parkinson's disease.

Parkinsons disease (PD) is a neurodegenerative disorder characterized by significant motor dysfunction and various non‐motor disturbances, including cognitive alterations. Deep brain stimulation (DBS) is an increasingly utilized therapeutic option for patients with PD that yields remarkable success in alleviating disabling motor symptoms. DBS has additionally been associated with changes in cognition, yet the evidence is not consistent across studies. The following review sought to provide a clearer understanding of the various cognitive sequelae of bilateral subthalamic nucleus (STN) DBS while taking into account corresponding neuroanatomy and potential confounding variables.

Conversion Between Mini-Mental State Examination, Montreal Cognitive Assessment, and Dementia Rating Scale-2 Scores in Parkinson’s Disease

Cognitive impairment is one of the earliest, most common, and most disabling non‐motor symptoms in Parkinsons disease (PD). Thus, routine screening of global cognitive abilities is important for the optimal management of PD patients. Few global cognitive screening instruments have been developed for or validated in PD patients. The Mini‐Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Dementia Rating Scale‐2 (DRS‐2) have been used extensively for cognitive screening in both clinical and research settings. Determining how to convert the scores between instruments would facilitate the longitudinal assessment of cognition in clinical settings and the comparison and synthesis of cognitive data in multicenter and longitudinal cohort studies. The primary aim of this study was to apply a simple and reliable algorithm for the conversion of MoCA to MMSE scores in PD patients. A secondary aim was to apply this algorithm for the conversion of DRS‐2 to both MMSE and MoCA scores. The cognitive performance of a convenience sample of 360 patients with idiopathic PD was assessed by at least two of these cognitive screening instruments. We then developed conversion scores between the MMSE, MoCA, and DRS‐2 using equipercentile equating and log‐linear smoothing. The conversion score tables reported here enable direct and easy comparison of three routinely used cognitive screening assessments in PD patients.

Caregiver report of apathy predicts dementia in Parkinson's disease.

INTRODUCTION Apathy is a common, troublesome symptom in Parkinsons disease (PD). However, little is known about its relationship with long-term cognition. We sought to determine if a caregiver-reported apathy measure predicts the development of PD dementia. METHODS Non-demented PD patients were recruited as part of a longitudinal study of cognition. Demographics, medications, Dementia Rating Scale-2, Unified Parkinsons Disease Rating Scale, Geriatric Depression Scale and the Neuropsychiatric Inventory-Questionnaire (NPI-Q) ratings were obtained. Apathy was defined as an NPI-Q apathy score ≥1. Participants were evaluated annually with cognitive and functional assessments until the end of the study period or a physician consensus diagnosis of dementia was assigned. Cox proportional hazard models were used to assess the effects of baseline apathy on dementia development while controlling for other clinical and demographic factors. RESULTS Of 132 PD patients 12.1% (N = 16) scored in the apathetic range at baseline. A total of 19.6% (N = 26) individuals developed dementia over the course of the study, 8 of whom (30.8% of future dementia patients) had baseline apathy. In bivariate analyses baseline apathy, older age, and worse cognitive, motor, and depressive symptom scores predicted the development of dementia. In a multivariate analysis the predictive effects of baseline apathy were still significant (HR = 3.56; 95% CI = 1.09-11.62; p = 0.04). CONCLUSIONS A simple, caregiver-reported measure of apathy is an independent predictor of progression to dementia in PD. This highlights the importance of apathy as a clinical characteristic of PD and could prove useful for the prediction of future dementia.

Defining and validating a short form Montreal Cognitive Assessment (s-MoCA) for use in neurodegenerative disease

Introduction Screening for cognitive deficits is essential in neurodegenerative disease. Screening tests, such as the Montreal Cognitive Assessment (MoCA), are easily administered, correlate with neuropsychological performance and demonstrate diagnostic utility. Yet, administration time is too long for many clinical settings. Methods Item response theory and computerised adaptive testing simulation were employed to establish an abbreviated MoCA in 1850 well-characterised community-dwelling individuals with and without neurodegenerative disease. Results 8 MoCA items with high item discrimination and appropriate difficulty were identified for use in a short form (s-MoCA). The s-MoCA was highly correlated with the original MoCA, showed robust diagnostic classification and cross-validation procedures substantiated these items. Discussion Early detection of cognitive impairment is an important clinical and public health concern, but administration of screening measures is limited by time constraints in demanding clinical settings. Here, we provide as-MoCA that is valid across neurological disorders and can be administered in approximately 5 min.

An Alzheimer’s Disease-Derived Biomarker Signature Identifies Parkinson’s Disease Patients with Dementia

Biomarkers from multiple modalities have been shown to correlate with cognition in Parkinson’s disease (PD) and in Alzheimer’s disease (AD). However, the relationships of these markers with each other, and the use of multiple markers in concert to predict an outcome of interest, are areas that are much less explored. Our objectives in this study were (1) to evaluate relationships among 17 biomarkers previously reported to associate with cognition in PD or AD and (2) to test performance of a five-biomarker classifier trained to recognize AD in identifying PD with dementia (PDD). To do this, we evaluated a cross-sectional cohort of PD patients (n = 75) across a spectrum of cognitive abilities. All PD participants had 17 baseline biomarkers from clinical, genetic, biochemical, and imaging modalities measured, and correlations among biomarkers were assessed by Spearman’s rho and by hierarchical clustering. We found that internal correlation among all 17 candidate biomarkers was modest, showing a maximum pairwise correlation coefficient of 0.51. However, a five-marker subset panel derived from AD (CSF total tau, CSF phosphorylated tau, CSF amyloid beta 42, APOE genotype, and SPARE-AD imaging score) discriminated cognitively normal PD patients vs. PDD patients with 80% accuracy, when employed in a classifier originally trained to recognize AD. Thus, an AD-derived biomarker signature may identify PDD patients with moderately high accuracy, suggesting mechanisms shared with AD in some PDD patients. Based on five measures readily obtained during life, this AD-derived signature may prove useful in identifying PDD patients most likely to respond to AD-based crossover therapies.

Lower plasma apolipoprotein A1 levels are found in Parkinson's disease and associate with apolipoprotein A1 genotype

The discovery of novel plasma‐based biomarkers could lead to new approaches in the treatment of Parkinsons disease (PD). Here, we explore the role of plasma apolipoprotein A1 (ApoA1) as a risk marker for PD and evaluate the influence of APOA1 promoter variation on plasma ApoA1 levels. Plasma ApoA1 and the single‐nucleotide polymorphism, rs670, were assayed in a discovery cohort (cohort 1) of 301 PD patients, 80 normal controls (NCs), and 165 subjects with other neurodegenerative diseases, as well as a cohort (cohort 2) of 158 PD patients from a second clinical site. Additionally, rs670 was genotyped in a third cohort of 1,494 PD and 925 NC subjects from both clinical sites. Compared to both normal and disease controls, PD patients have lower plasma ApoA1 (P < 0.001 for both comparisons). Moreover, in PD patients, plasma ApoA1 levels are correlated with genotype at the APOA1 promoter polymorphism, rs670. Specifically, lower plasma ApoA1 levels were found in rs670 major allele (G) homozygotes in both cohort 1 (P = 0.009) and in a replication cohort (cohort 2; n = 158 PD patients; P = 0.024). Finally, evaluating rs670 genotype frequencies in 1,930 PD cases versus 997 NCs, the rs670 GG genotype shows a trend toward association (odds ratio: 1.1; P = 0.10) with PD. Our results are compatible with a model whereby circulating ApoA1 levels may be useful in risk‐stratifying subjects for the development of PD, with higher ApoA1 levels suggesting relative protection. Future studies evaluating modulation of ApoA1 as a novel therapeutic strategy in PD are warranted.

The Penn Parkinson's Daily Activities Questionnaire-15: Psychometric properties of a brief assessment of cognitive instrumental activities of daily living in Parkinson's disease *

INTRODUCTION To describe the psychometric properties of the Penn Parkinsons Daily Activities Questionnaire-15 (PDAQ-15), a 15-item measure of cognitive instrumental activities of daily living for Parkinsons disease (PD) patients derived from the original 50-item PDAQ. METHODS PDAQ-15 items were chosen by expert consensus. Knowledgeable informants of PD participants (n = 161) completed the PDAQ-15. Knowledgeable informants were defined as an individual having regular contact with the PD participant. PD participants were assigned a diagnosis of normal cognition, mild cognitive impairment, or dementia based on expert consensus. RESULTS PDAQ-15 scores correlated strongly with global cognition (Dementia Rating Scale-2, r = 0.71, p < 0.001) and a performance-based functional measure (Direct Assessment of Functional Status, r = 0.83; p < 0.001). PDAQ-15 scores accurately discriminated between non-demented PD participants (normal cognition/mild cognitive impairment) and PD with dementia (ROC curve area = 0.91), participants with and without any cognitive impairment (normal cognition versus mild cognitive impairment/dementia, ROC curve area = 0.85) and between participants with mild cognitive impairment and dementia (ROC curve area = 0.84). CONCLUSIONS The PDAQ-15 shows good discriminant validity across cognitive stages, correlates highly with global cognitive performance, and appears suitable to assess daily cognitive functioning in PD.