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 Parkinsonʼs 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.
Summary Recent findings question our present understanding of Parkinson's disease and suggest that new research criteria for the diagnosis of Parkinson's disease are needed, similar to those recently ...defined in Alzheimer's disease. However, our ability to redefine Parkinson's disease is hampered by its complexity and heterogeneity in genetics, phenotypes, and underlying molecular mechanisms; the absence of biochemical markers or ability to image Parkinson's disease-specific histopathological changes; the long prodromal period during which non-motor manifestations might precede classic motor manifestations; and uncertainty about the status of disorders diagnosed clinically as Parkinson's disease but without Lewy pathology. Although it is too early to confidently redefine Parkinson's disease, the time has come to establish a research framework that could lead to new diagnostic criteria. We propose the establishment of three tiers encompassing clinical features, pathological findings, and genetics or molecular mechanisms. Specific advances in each tier, bridged by neuroimaging and biochemical data, will eventually lead to a redefinition of Parkinson's disease.
Aim Several pathophysiological processes are involved in Parkinson's disease (PD) and could inform in vivo biomarkers. We assessed an established biomarker panel, validated in Alzheimer's Disease, in ...a PD cohort. Methods Longitudinal cerebrospinal fluid (CSF) samples from PPMI (252 PD, 115 healthy controls, HC) were analyzed at six timepoints (baseline, 6, 12, 24, 36, and 48 months follow-up) using Elecsys® electrochemiluminescence immunoassays to quantify neurofilament light chain (NfL), soluble TREM2 receptor (sTREM2), chitinase-3-like protein 1 (YKL40), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), S100, and total alpha-synuclein (alphaSyn). Results alphaSyn was significantly lower in PD (mean 103 pg/ml vs. HC: 127 pg/ml, p0.05) and none showed a significant difference longitudinally. We found significantly higher levels of all these markers between PD patients who developed cognitive decline during follow-up, except for alphaSyn and IL-6. Conclusion Except for alphaSyn, the additional biomarkers did not differentiate PD and HC, and none showed longitudinal differences, but most markers predict cognitive decline in PD during follow-up.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Phosphorylated α-synuclein (PS-129), a protein implicated in the pathogenesis of Parkinson's disease (PD), was identified by mass spectrometry in human cerebrospinal fluid (CSF). A highly sensitive ...and specific assay was established and used to measure PS-129 together with total α-synuclein in the CSF of patients with PD, other parkinsonian disorders such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), and healthy individuals (a total of ~600 samples). PS-129 CSF concentrations correlated weakly with PD severity and, when combined with total α-synuclein concentrations in CSF, contributed to distinguishing PD from MSA and PSP. Further rigorous validation in independent cohorts of patients, especially those where samples have been collected longitudinally, will determine whether the concentration of PS-129 in CSF will be useful for diagnosing PD and for monitoring PD severity and progression.
A recent controlled clinical trial suggested a role for amantadine as a treatment for pathological gambling in patients with Parkinson disease (PD). Analyzing data from a large cross‐sectional study ...of impulse control disorders (ICDs) in PD, amantadine use (n = 728), vs no amantadine use (n = 2,357), was positively associated with a diagnosis of any ICD (17.6% vs 12.4%, p < 0.001) and compulsive gambling specifically (7.4% vs 4.2%, p < 0.001). This amantadine association remained after controlling for covariates of amantadine use, including both dopamine agonist use and levodopa dosage. Further research, including larger clinical trials, is needed to assess the role of amantadine in the development and treatment of ICDs in PD. Ann Neurol 2010
Objective
Common variants near TMEM106B associate with risk of developing frontotemporal dementia (FTD). Emerging evidence suggests a role for TMEM106B in neurodegenerative processes beyond FTD. We ...evaluate the effect of TMEM106B genotype on cognitive decline across multiple neurogenerative diseases.
Methods
We longitudinally followed 870 subjects with diagnoses of Parkinson disease (PD; n = 179), FTD (n = 179), Alzheimer disease (AD; n = 300), memory‐predominant mild cognitive impairment (MCI; n = 75), or neurologically normal control subjects (NC; n = 137) at the University of Pennsylvania (UPenn). All participants had annual Mini‐Mental State Examination (MMSE; median follow‐up duration = 3.0 years) and were genotyped at TMEM106B index single nucleotide polymorphism rs1990622. Genotype effects on cognition were confirmed by extending analyses to additional cognitive instruments (Mattis Dementia Rating Scale‐2 DRS‐2 and Montreal Cognitive Assessment MoCA) and to an international validation cohort (Parkinson's Progression Markers Initiative PPMI, N = 371).
Results
The TMEM106B rs1990622T allele, linked to increased risk of FTD, associated with greater MMSE decline over time in PD subjects but not in AD or MCI subjects. For FTD subjects, rs1990622T associated with more rapid decrease in MMSE only under the minor‐allele, rs1990622C, dominant model. Among PD patients, rs1990622T carriers from the UPenn cohort demonstrated more rapid longitudinal decline in DRS‐2 scores. Finally, in the PPMI cohort, TMEM106B risk allele carriers demonstrated more rapid longitudinal decline in MoCA scores.
Interpretation
Irrespective of cognitive instrument or cohort assessed, TMEM106B acts as a genetic modifier for cognitive trajectory in PD. Our results implicate lysosomal dysfunction in the pathogenesis of cognitive decline in 2 different proteinopathies. ANN NEUROL 2019;85:801–811.
Now that wearable sensors have become more commonplace, it is possible to monitor individual healthcare-related activity outside the clinic, unleashing potential for early detection of events in ...diseases such as Parkinson’s disease (PD). However, the unsupervised and “open world” nature of this type of data collection make such applications difficult to develop. In this proof-of-concept study, we used inertial sensor data from Verily Study Watches worn by individuals for up to 23 h per day over several months to distinguish between seven subjects with PD and four without. Since motor-related PD symptoms such as bradykinesia and gait abnormalities typically present when a PD subject is walking, we initially used human activity recognition (HAR) techniques to identify walk-like activity in the unconstrained, unlabeled data. We then used these “walk-like” events to train one-dimensional convolutional neural networks (1D-CNNs) to determine the presence of PD. We report classification accuracies near 90% on single 5-s walk-like events and 100% accuracy when taking the majority vote over single-event classifications that span a duration of one day. Though based on a small cohort, this study shows the feasibility of leveraging unconstrained wearable sensor data to accurately detect the presence or absence of PD.
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