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Multivariate prediction of dementia in Parkinson's disease.

ABSTRACT: Cognitive impairment in Parkinson's disease (PD) is pervasive with potentially devastating effects. Identification of those at risk for cognitive decline is vital to identify and implement appropriate interventions. Robust multivariate approaches, including fixed-effect, mixed-effect, and multitask learning models, were used to study associations between biological, clinical, and cognitive factors and for predicting cognitive status longitudinally in a well-characterized prevalent PD cohort (n = 827). Age, disease duration, sex, and GBA status were the primary biological factors associated with cognitive status and progression to dementia. Specific cognitive tests were better predictors of subsequent cognitive status for cognitively unimpaired and dementia groups. However, these models could not accurately predict future mild cognitive impairment (PD-MCI). Data collected from a large PD cohort thus revealed the primary biological and cognitive factors associated with dementia, and provide clinicians with data to aid in the identification of risk for dementia. Sex differences and their potential relationship to genetic status are also discussed.

SUBMITTER: Phongpreecha T

PROVIDER: S-EPMC7447766 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Multivariate prediction of dementia in Parkinson's disease.

Phongpreecha Thanaphong T Cholerton Brenna B Mata Ignacio F IF Zabetian Cyrus P CP Poston Kathleen L KL Aghaeepour Nima N Tian Lu L Quinn Joseph F JF Chung Kathryn A KA Hiller Amie L AL Hu Shu-Ching SC Edwards Karen L KL Montine Thomas J TJ

NPJ Parkinson's disease 20200825

Cognitive impairment in Parkinson's disease (PD) is pervasive with potentially devastating effects. Identification of those at risk for cognitive decline is vital to identify and implement appropriate interventions. Robust multivariate approaches, including fixed-effect, mixed-effect, and multitask learning models, were used to study associations between biological, clinical, and cognitive factors and for predicting cognitive status longitudinally in a well-characterized prevalent PD cohort (<i> ...[more]

PMID: 32885039

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Project description:Parkinson's disease dementia is neuropathologically characterized by aggregates of α-synuclein (Lewy bodies) in limbic and neocortical areas of the brain with additional involvement of Alzheimer's disease-type pathology. Whilst immune activation is well-described in Parkinson's disease (PD), how it links to protein aggregation and its role in PD dementia has not been explored. We hypothesized that neuroinflammatory processes are a critical contributor to the pathology of PDD. To address this hypothesis, we examined 7 brain regions at postmortem from 17 PD patients with no dementia (PDND), 11 patients with PD dementia (PDD), and 14 age and sex-matched neurologically healthy controls. Digital quantification after immunohistochemical staining showed a significant increase in the severity of α-synuclein pathology in the hippocampus, entorhinal and occipitotemporal cortex of PDD compared to PDND cases. In contrast, there was no difference in either tau or amyloid-β pathology between the groups in any of the examined regions. Importantly, we found an increase in activated microglia in the amygdala of demented PD brains compared to controls which correlated significantly with the extent of α-synuclein pathology in this region. Significant infiltration of CD4+ T lymphocytes into the brain parenchyma was commonly observed in PDND and PDD cases compared to controls, in both the substantia nigra and the amygdala. Amongst PDND/PDD cases, CD4+ T cell counts in the amygdala correlated with activated microglia, α-synuclein and tau pathology. Upregulation of the pro-inflammatory cytokine interleukin 1β was also evident in the substantia nigra as well as the frontal cortex in PDND/PDD versus controls with a concomitant upregulation in Toll-like receptor 4 (TLR4) in these regions, as well as the amygdala. The evidence presented in this study show an increased immune response in limbic and cortical brain regions, including increased microglial activation, infiltration of T lymphocytes, upregulation of pro-inflammatory cytokines and TLR gene expression, which has not been previously reported in the postmortem PDD brain.

Project description:As the differential diagnosis of dementias based on established clinical criteria is often difficult, biomarkers for applicable diagnostic testing are currently under intensive investigation. Amyloid plaques deposited in the brain of patients suffering from Alzheimer's disease, dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) mainly consist of carboxy-terminally elongated forms of amyloid-beta (Abeta) peptides, such as Abeta1-42. Absolute Abeta1-42 levels in CSF have shown diagnostic value for the diagnosis of Alzheimer's disease, but the discrimination among Alzheimer's disease, DLB and PDD was poor. A recently established quantitative urea-based Abeta-sodium-dodecylsulphate-polyacrylamide-gel-electrophoresis with Western immunoblot (Abeta-SDS-PAGE/immunoblot) revealed a highly conserved Abeta peptide pattern of the carboxy-terminally truncated Abeta peptides 1-37, 1-38, 1-39 in addition to 1-40 and 1-42 in human CSF. We used the Abeta-SDS-PAGE/immunoblot to investigate the CSF of 23 patients with Alzheimer's disease, 21 with DLB, 21 with PDD and 23 non-demented disease controls (NDC) for disease-specific alterations of the Abeta peptide patterns in its absolute and relative quantities. The diagnostic groups were matched for age and severity of dementia. The present study is the first attempt to evaluate the meaning of Abeta peptide patterns in CSF for differential diagnosis of the three neurodegenerative diseases--Alzheimer's disease, DLB and PDD. The Abeta peptide patterns displayed disease-specific variations and the ratio of the differentially altered Abeta1-42 to the Abeta1-37 levels subsequently discriminated all diagnostic groups from each other at a highly significant level, except DLB from PDD. Additionally, a novel peptide with Abeta-like immunoreactivity was observed constantly in the CSF of all 88 investigated patients. The pronounced percentage increase of this peptide in DLB allowed a highly significant discrimination from PDD. Using a cut-off point of 0.954%, this marker yielded a diagnostic sensitivity and specificity of 81 and 71%, respectively. From several lines of indication, we consider this peptide to represent an oxidized alpha-helical form of Abeta1-40 (Abeta1-40*). The increased abundance of Abeta1-40* probably reflects a disease-specific alteration of the Abeta1-40 metabolism in DLB. We conclude that Abeta peptide patterns reflect disease-specific pathophysiological pathways of different dementia syndromes as distinct neurochemical phenotypes. Although Abeta peptide patterns failed to fulfil the requirements for a sole biomarker, their combined evaluation with other biomarkers is promising in neurochemical dementia diagnosis. It is noteworthy that DLB and PDD exhibit distinct clinical temporal courses, despite their similar neuropathological appearance. Their distinct molecular phenotypes support the view of different pathophysiological pathways for each of these neurodegenerative diseases.

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Dataset Information

Multivariate prediction of dementia in Parkinson's disease.

Publications

Multivariate prediction of dementia in Parkinson's disease.

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