41 research outputs found
Cerebrospinal fluid biomarkers in parkinsonian conditions: an update and future directions
Parkinsonian diseases comprise a heterogeneous group of neurodegenerative disorders, which show significant clinical and pathological overlap. Accurate diagnosis still largely relies on clinical acumen; pathological diagnosis remains the gold standard. There is an urgent need for biomarkers to diagnose parkinsonian disorders, particularly in the early stages when diagnosis is most difficult. In this review, several of the most promising cerebrospinal fluid candidate markers will be discussed. Their strengths and limitations will be considered together with future developments in the field
Cerebrospinal fluid in the differential diagnosis of Alzheimer's disease: clinical utility of an extended panel of biomarkers in a specialist cognitive clinic.
BACKGROUND: Cerebrospinal fluid (CSF) biomarkers are increasingly being used to support a diagnosis of Alzheimer's disease (AD). Their clinical utility for differentiating AD from non-AD neurodegenerative dementias, such as dementia with Lewy bodies (DLB) or frontotemporal dementia (FTD), is less well established. We aimed to determine the diagnostic utility of an extended panel of CSF biomarkers to differentiate AD from a range of other neurodegenerative dementias. METHODS: We used immunoassays to measure conventional CSF markers of amyloid and tau pathology (amyloid beta (Aβ)1-42, total tau (T-tau), and phosphorylated tau (P-tau)) as well as amyloid processing (AβX-38, AβX-40, AβX-42, soluble amyloid precursor protein (sAPP)α, and sAPPβ), large fibre axonal degeneration (neurofilament light chain (NFL)), and neuroinflammation (YKL-40) in 245 patients with a variety of dementias and 30 controls. Patients fulfilled consensus criteria for AD (n = 156), DLB (n = 20), behavioural variant frontotemporal dementia (bvFTD; n = 45), progressive non-fluent aphasia (PNFA; n = 17), and semantic dementia (SD; n = 7); approximately 10% were pathology/genetically confirmed (n = 26). Global tests based on generalised least squares regression were used to determine differences between groups. Non-parametric receiver operating characteristic (ROC) curves and area under the curve (AUC) analyses were used to quantify how well each biomarker discriminated AD from each of the other diagnostic groups (or combinations of groups). CSF cut-points for the major biomarkers found to have diagnostic utility were validated using an independent cohort which included causes of AD (n = 104), DLB (n = 5), bvFTD (n = 12), PNFA (n = 3), SD (n = 9), and controls (n = 10). RESULTS: There were significant global differences in Aβ1-42, T-tau, T-tau/Aβ1-42 ratio, P-tau-181, NFL, AβX-42, AβX-42/X-40 ratio, APPα, and APPβ between groups. At a fixed sensitivity of 85%, AβX-42/X-40 could differentiate AD from controls, bvFTD, and SD with specificities of 93%, 85%, and 100%, respectively; for T-tau/Aβ1-42 these specificities were 83%, 70%, and 86%. AβX-42/X-40 had similar or higher specificity than Aβ1-42. No biomarker or ratio could differentiate AD from DLB or PNFA with specificity > 50%. Similar sensitivities and specificities were found in the independent validation cohort for differentiating AD and other dementias and in a pathology/genetically confirmed sub-cohort. CONCLUSIONS: CSF AβX-42/X-40 and T-tau/Aβ1-42 ratios have utility in distinguishing AD from controls, bvFTD, and SD. None of the biomarkers tested had good specificity at distinguishing AD from DLB or PNFA
Musical tasks targeting preserved and impaired functions in two dementias.
Studies of musical abilities in dementia have for the most part been rather general assessments of abilities, for instance, assessing retention of music learned premorbidly. Here, we studied patients with dementias with contrasting cognitive profiles to explore specific aspects of music cognition under challenge. Patients suffered from Alzheimer's disease (AD), in which a primary impairment is in forming new declarative memories, or Lewy body disease (PD/LBD), a type of parkinsonism in which executive impairments are prominent. In the AD patients, we examined musical imagery. Behavioral and neural evidence confirms involvement of perceptual networks in imagery, and these are relatively spared in early stages of the illness. Thus, we expected patients to have relatively intact imagery in a mental pitch comparison task. For the LBD patients, we tested whether executive dysfunction would extend to music. We probed inhibitory skills by asking for a speeded pitch or timbre judgment when the irrelevant dimension was held constant or also changed. Preliminary results show that AD patients score similarly to controls in the imagery tasks, but PD/LBD patients are impaired relative to controls in suppressing some irrelevant musical dimensions, particularly when the required judgment varies from trial to trial
Identification of novel CSF biomarkers for neurodegeneration and their validation by a high-throughput multiplexed targeted proteomic assay
Increased CSF neurogranin concentration is specific to Alzheimer disease
OBJECTIVE: To assess the specificity of the dendritic protein neurogranin (Ng) in CSF from patients with a broad range of neurodegenerative diseases including a variety of dementias, tauopathies, and synucleinopathies. METHOD: An optimized immunoassay was used to analyze CSF Ng in a retrospective cohort of 331 participants with different neurodegenerative diseases, including healthy controls (n = 19), biomarker-proven Alzheimer disease (AD) (n = 100), genetic AD (n = 2), behavioral variant frontotemporal dementia (n = 20), speech variant frontotemporal dementia (n = 21), Lewy body dementia (n = 13), Parkinson disease (n = 31), progressive supranuclear palsy (n = 46), multiple system atrophy (n = 29), as well as a heterogeneous group with non-neurodegenerative cognitive impairment (n = 50). CSF Ng concentrations and correlations of CSF Ng with total tau, phosphorylated tau, and β-amyloid 42 concentrations, Mini-Mental State Examination score, and disease duration in the different groups were investigated. RESULTS: Median CSF Ng concentration was higher in patients with AD compared to both controls (p < 0.001) and all other disease groups (all p < 0.001) except speech variant frontotemporal dementia. There were no significant differences in CSF Ng concentrations between any other neurodegenerative groups and controls. In addition, we found strong correlations between Ng and total tau (p < 0.001) and phosphorylated tau (p < 0.001). CONCLUSIONS: These results confirm an increase in CSF Ng concentration in patients with AD as previously reported and show that this is specific to AD and not seen in a range of other neurodegenerative diseases
Value of cerebrospinal fluid α-synuclein species as biomarker in Parkinson's diagnosis and prognosis
Since diagnosis of Parkinson's disease (PD) is mostly based on clinical criteria, it is almost impossible to formulate an early diagnosis, as well as a timely differential diagnosis versus other parkinsonisms. A great effort in searching reliable biomarkers both for early diagnosis and prognosis in PD is currently ongoing. Cerebrospinal fluid has been widely investigated as potential source for such biomarkers, with particular emphasis on α-synuclein (α-syn) species. We reviewed all the clinical studies carried out so far on cerebrospinal fluid quantification of α-syn species in PD. Current evidence supports the value of total and oligomeric α-syn in PD diagnosis and in the differential diagnosis of PD and other parkinsonisms. Conversely, the role of α-syn species in PD prognosis remains unsatisfactory
Perceptual decision-making in patients with Parkinson's disease
Impulsive choice and poor information sampling have been found to be key behavioural mechanisms linked to impulse control disorders (ICDs) in Parkinson’s disease (PD). Perceptual decision-making is intimately related to information sampling. Therefore, we wanted to determine whether dopaminergic medication or ICDs influence perceptual decision-making in PD. All participants performed two tasks. One was a simple reaction time task, where subjects needed to respond as quickly as possible. The second was a perceptual decision-making task, in which participants had to estimate whether a stimulus contained either more red or more blue pixels. We tested three groups of patients, one treated with levodopa monotherapy, one additionally treated with dopamine agonists, and a third group had ICDs. Results were compared to healthy controls. We found that all patients made more errors than controls. Further, patients with ICDs responded fastest on the reaction time task and also in incorrect trials on the perceptual decision-making task. Similarly, patients with dopamine agonists responded faster than those on levodopa monotherapy and controls. Our results demonstrate that all patients have deficits in perceptual decision-making. However, patients treated with dopamine agonists closely resembled patients with ICDs
A panel of nine cerebrospinal fluid biomarkers may identify patients with atypical parkinsonian syndromes
BackgroundPatients presenting with parkinsonian syndromes share many clinical features, which can make diagnosis difficult. This is important as atypical parkinsonian syndromes (APSs) such as progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and corticobasal syndrome (CBS) carry a poor prognosis, compared with patients with Parkinson's disease (PD). In addition, there is overlap between APS and dementia diseases, such as Alzheimer's disease (AD) and frontotemporal dementia (FTD).ObjectiveTo use a panel of cerebrospinal fluid (CSF) biomarkers to differentiate patients with APS from PD and dementia.MethodsA prospective cohort of 160 patients and 30 control participants were recruited from a single specialist centre. Patients were clinically diagnosed according to current consensus criteria. CSF samples were obtained from patients with clinical diagnoses of PD (n=31), PSP (n=33), CBS (n=14), MSA (n=31), AD (n=26) and FTD (n=16). Healthy, elderly participants (n=30) were included as controls. Total τ (t-τ), phosphorylated τ (p-τ), β-amyloid 1–42 (Aβ42), neurofilament light chain (NFL), α-synuclein (α-syn), amyloid precursor protein soluble metabolites α and β (soluble amyloid precursor protein (sAPP)α, sAPPβ) and two neuroinflammatory markers (monocyte chemoattractant protein-1 and YKL-40) were measured in CSF. A reverse stepwise regression analysis and the false discovery rate procedure were used.ResultsCSF NFL (p<0.001), sAPPα (p<0.001) and a-syn (p=0.003) independently predicted diagnosis of PD versus APS. Together, these nine biomarkers could differentiate patients with PD from APS with an area under the curve of 0.95 and subtypes of APS from one another. There was good discriminatory power between parkinsonian groups, dementia disorders and healthy controls.ConclusionsA panel of nine CSF biomarkers was able to differentiate APS from patients with PD and dementia. This may have important clinical utility in improving diagnostic accuracy, allowing better prognostication and earlier access to potential disease-modifying therapies.</jats:sec
A novel approach in combination of 3D gait analysis data for aiding clinical decision-making in patients with Parkinson’s disease
The most common methods used by neurologist to evaluate Parkinson’s Disease (PD) patients are rating scales, that are affected by subjective and non-repeatable observations. Since several research studies have revealed that walking is a sensitive indicator for the progression of PD. In this paper, we propose an innovative set of features derived from three-dimensional Gait Analysis in order to classify motor signs of motor impairment in PD and differentiate PD patients from healthy subjects or patients suffering from other neurological diseases. We consider kinematic data from Gait Analysis as Gait Variables Score (GVS), Gait Profile Score (GPS) and spatio-temporal data for all enrolled patients. We then carry out experiments evaluating the extracted features using an Artificial Neural Network (ANN) classifier. The obtained results are promising with the best classifier score accuracy equal to 95.05%
