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CSF tau and tau/A?42 predict cognitive decline in Parkinson's disease.

ABSTRACT: A substantial proportion of patients with Parkinson's disease (PD) have concomitant cognitive dysfunction. Identification of biomarker profiles that predict which PD patients have a greater likelihood for progression of cognitive symptoms is pressingly needed for future treatment and prevention approaches.Subjects were drawn from the Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) study, a large clinical trial that enrolled initially untreated PD patients. For the current study, Phase One encompassed trial baseline until just prior to levodopa administration (n = 403), and Phase Two spanned the initiation of levodopa treatment until the end of cognitive follow-up (n = 305). Correlations and linear mixed models were performed to determine cross-sectional and longitudinal associations between baseline amyloid ?1-42 (A?42), total tau (t-tau), and phosphorylated tau (p-tau) in cerebrospinal fluid (CSF) and measures of memory and executive function. Analyses also considered APOE genotype and tremor- vs. rigidity-dominant phenotype.No association was found between baseline CSF biomarkers and cognitive test performance during Phase One. However, once levodopa treatment was initiated, higher p-tau and p-tau/A?42 predicted subsequent decline on cognitive tasks involving both memory and executive functions. The interactions between biomarkers and cognition decline did not appear to be influenced by levodopa dosage, APOE genotype or motor phenotype.The current study has, for the first time, demonstrated the possible involvement of tau species, whose gene (MAPT) has been consistently linked to the risk of PD by genome-wide association studies, in the progression of cognitive symptoms in PD.

SUBMITTER: Liu C

PROVIDER: S-EPMC4603566 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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CSF tau and tau/Aβ42 predict cognitive decline in Parkinson's disease.

Liu Changqin C Cholerton Brenna B Shi Min M Ginghina Carmen C Cain Kevin C KC Auinger Peggy P Zhang Jing J

Parkinsonism & related disorders 20150105 3

<h4>Introduction</h4>A substantial proportion of patients with Parkinson's disease (PD) have concomitant cognitive dysfunction. Identification of biomarker profiles that predict which PD patients have a greater likelihood for progression of cognitive symptoms is pressingly needed for future treatment and prevention approaches.<h4>Methods</h4>Subjects were drawn from the Deprenyl and Tocopherol Antioxidative Therapy of Parkinsonism (DATATOP) study, a large clinical trial that enrolled initially u ...[more]

PMID: 25596881

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Project description:BackgroundDelirium and dementia share symptoms of cognitive dysfunctions, and mechanisms of neuroinflammation appear involved in both conditions. Triggering receptor expressed on myeloid cells 2 (TREM2) is linked to dementia and neurodegenerative disease. It encodes expression of an innate immune receptor in the brain expressed by microglia. The level of the soluble fragment of TREM2 (sTREM2) is reported to increase in the cerebrospinal fluid (CSF) already in prodromal and asymptomatic Alzheimer's disease.MethodsWe analyzed the level of CSF sTREM2 in relation to delirium and dementia. The study included patients with or without pre-existing dementia who underwent acute hip fracture surgery (n = 120), and some of the patients developed delirium (n = 65). A medical delirium cohort (n = 26) was also examined. ELISA was used to determine the level of sTREM2 in CSF.ResultsDelirium was associated with a higher level of CSF sTREM2 only among those without pre-existing dementia (p = 0.046, n = 15, n = 44), particularly among patients developing delirium after CSF sampling (p = 0.02, n = 7, n = 44). Between patients with dementia, there was no group difference, but the CSF sTREM2 level increased with waiting time for surgery (rS = 0.39, p = 0.002, n = 60) and correlated well with the CSF Alzheimer's disease biomarkers, Aβ42, and t-tau/p-tau (rS = 0.40, p = 0.002, rS = 0.46, p < 0.001/ rS = 0.49, p < 0.001, n = 60). Among patients with dementia, the level of Aβ38 and Aβ40 also correlated positively with sTREM2 in CSF (Aβ38MSDrS = 0.44, p = 0.001; Aβ40MSDrS = 0.48, p < 0.001; Aβ42MSDrS = 0.43, p < 0.001, n = 60).ConclusionThe findings reinforce the involvement of neuroinflammation in delirium, yet with separate responses in patients with or without pre-existing dementia. Our findings support the concept of primed microglia in neurodegenerative disease and central immune activation after a peripheral trauma in such patients. A CSF biomarker panel of neuroinflammation might be valuable to prevent delirium by identifying patients at risk.

Project description:Tau pathology, neuroinflammation, and neurodegeneration are key aspects of Alzheimer's disease. Understanding whether these features predict cognitive decline, alone or in combination, is crucial to develop new prognostic measures and enhanced stratification for clinical trials. Here, we studied how baseline assessments of in vivo tau pathology (measured by 18F-AV-1451 PET), neuroinflammation (measured by 11C-PK11195 PET) and brain atrophy (derived from structural MRI) predicted longitudinal cognitive changes in patients with Alzheimer's disease pathology. Twenty-six patients (n = 12 with clinically probable Alzheimer's dementia and n = 14 with amyloid-positive mild cognitive impairment) and 29 healthy control subjects underwent baseline assessment with 18F-AV-1451 PET, 11C-PK11195 PET, and structural MRI. Cognition was examined annually over the subsequent 3 years using the revised Addenbrooke's Cognitive Examination. Regional grey matter volumes, and regional binding of 18F-AV-1451 and 11C-PK11195 were derived from 15 temporo-parietal regions characteristically affected by Alzheimer's disease pathology. A principal component analysis was used on each imaging modality separately, to identify the main spatial distributions of pathology. A latent growth curve model was applied across the whole sample on longitudinal cognitive scores to estimate the rate of annual decline in each participant. We regressed the individuals' estimated rate of cognitive decline on the neuroimaging components and examined univariable predictive models with single-modality predictors, and a multi-modality predictive model, to identify the independent and combined prognostic value of the different neuroimaging markers. Principal component analysis identified a single component for the grey matter atrophy, while two components were found for each PET ligand: one weighted to the anterior temporal lobe, and another weighted to posterior temporo-parietal regions. Across the whole-sample, the single-modality models indicated significant correlations between the rate of cognitive decline and the first component of each imaging modality. In patients, both stepwise backward elimination and Bayesian model selection revealed an optimal predictive model that included both components of 18F-AV-1451 and the first (i.e. anterior temporal) component for 11C-PK11195. However, the MRI-derived atrophy component and demographic variables were excluded from the optimal predictive model of cognitive decline. We conclude that temporo-parietal tau pathology and anterior temporal neuroinflammation predict cognitive decline in patients with symptomatic Alzheimer's disease pathology. This indicates the added value of PET biomarkers in predicting cognitive decline in Alzheimer's disease, over and above MRI measures of brain atrophy and demographic data. Our findings also support the strategy for targeting tau and neuroinflammation in disease-modifying therapy against Alzheimer's disease.

Project description:PurposeBiomarkers used for predicting longitudinal cognitive change in Alzheimer's disease (AD) continuum are still elusive. Tau pathology, neuroinflammation, and neurodegeneration are the leading candidate predictors. We aimed to determine these three aspects of biomarkers in cerebrospinal fluid (CSF) and plasma to predict longitudinal cognition status using Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort.Patients and methodsA total of 430 subjects including, 96 cognitive normal (CN) with amyloid β (Aβ)-negative, 54 CN with Aβ-positive, 195 mild cognitive impairment (MCI) with Aβ-positive, and 85 AD with amyloid-positive (Aβ-positive are identified by CSF Aβ42/Aβ40 < 0.138). Aβ burden was evaluated by CSF and plasma Aβ42/Aβ40 ratio; tau pathology was evaluated by CSF and plasma phosphorylated-tau (p-tau181); microglial activation was measured by CSF soluble TREM2 (sTREM2) and progranulin (PGRN); neurodegeneration was measured by CSF and plasma t-tau and structural magnetic resonance imaging (MRI); cognition was examined annually over the subsequent 8 years using the Alzheimer's Disease Assessment Scale Cognition 13-item scale (ADAS13) and Mini-Mental State Exam (MMSE). Linear mixed-effects models (LME) were applied to assess the correlation between biomarkers and longitudinal cognition decline, as well as their effect size on the prediction of longitudinal cognitive decline.ResultsBaseline CSF Aβ42/Aβ40 ratio was decreased in MCI and AD compared to CN, while CSF p-tau181 and t-tau increased. Baseline CSF sTREM2 and PGRN did not show any differences in MCI and AD compared to CN. Baseline brain volumes (including the hippocampal, entorhinal, middle temporal lobe, and whole-brain) decreased in MCI and AD groups. For the longitudinal study, there were significant interaction effects of CSF p-tau181 × time, plasma p-tau181 × time, CSF sTREM2 × time, and brain volumes × time, indicating CSF, and plasma p-tau181, CSF sTREM2, and brain volumes could predict longitudinal cognition deterioration rate. CSF sTREM2, CSF, and plasma p-tau181 had similar medium prediction effects, while brain volumes showed stronger effects in predicting cognition decline.ConclusionOur study reported that baseline CSF sTREM2, CSF, and plasma p-tau181, as well as structural MRI, could predict longitudinal cognitive decline in subjects with positive AD pathology. Plasma p-tau181 can be used as a relatively noninvasive reliable biomarker for AD longitudinal cognition decline prediction.

Project description:ImportancePhase 3 trials of successful antiamyloid therapies in Alzheimer disease (AD) have demonstrated improved clinical efficacy in people with less severe disease. Plasma biomarkers will be essential for efficient screening of participants in future primary prevention clinical trials testing antiamyloid therapies in cognitively unimpaired (CU) individuals with initially low brain β-amyloid (Aβ) levels who are at high risk of accumulating Aβ.ObjectiveTo investigate if combining plasma biomarkers could be useful in predicting subsequent development of Aβ pathology in CU individuals with subthreshold brain Aβ levels (defined as Aβ levels <40 Centiloids) at baseline.Design, setting, and participantsThis was a longitudinal study including Swedish BioFINDER-2 (enrollment 2017-2022) and replication in 2 independent cohorts, the Knight Alzheimer Disease Research Center (Knight ADRC; enrollment 1988 and 2019) and Swedish BioFINDER-1 (enrollment 2009-2015). Included for analysis was a convenience sample of CU individuals with baseline plasma phosphorylated tau 217 (p-tau217) and Aβ42/40 assessments and Aβ assessments with positron emission tomography (Aβ-PET) or cerebrospinal fluid (CSF) Aβ42/40. Data were analyzed between April 2023 and May 2024.ExposuresBaseline plasma levels of Aβ42/40, p-tau217, the ratio of p-tau217 to nonphosphorylated tau (%p-tau217), p-tau231, and glial fibrillary acidic protein (GFAP).Main outcomes and measuresCross-sectional and longitudinal PET and CSF measures of brain Aβ pathology.ResultsThis study included 495 (BioFINDER-2), 283 (Knight ADRC), and 205 (BioFINDER-1) CU participants. In BioFINDER-2, the mean (SD) age was 65.7 (14.4) with 261 females (52.7%). When detecting abnormal CSF Aβ-status, a combination of plasma %p-tau217 and Aβ42/40 showed better performance (area under the curve = 0.949; 95% CI, 0.929-0.970; P <.02) than individual biomarkers. In CU participants with subthreshold baseline Aβ-PET, baseline plasma %p-tau217 and Aβ42/40 levels were significantly associated with baseline Aβ-PET (n = 384) and increases in Aβ-PET over time (n = 224). Associations of plasma %p-tau217 and Aβ42/40 and their interaction with baseline Aβ-PET (%p-tau217: β = 2.77; 95% CI, 1.84-3.70; Aβ42/40: β = -1.64; 95% CI, -2.53 to -0.75; %p-tau217 × Aβ42/40: β = -2.14; 95% CI, -2.79 to -1.49; P < .001) and longitudinal Aβ-PET (%p-tau217: β = 0.67; 95% CI, 0.48-0.87; Aβ42/40: β = -0.33; 95% CI, -0.51 to -0.15; %p-tau217 × Aβ42/40: β = -0.31; 95% CI, -0.44 to -0.18; P < .001) were also significant in the models combining the 2 baseline biomarkers as predictors. Similarly, baseline plasma p-tau217 and Aβ42/40 were independently associated with longitudinal Aβ-PET in Knight ADRC (%p-tau217: β = 0.71; 95% CI, 0.26-1.16; P = .002; Aβ42/40: β = -0.74; 95% CI, -1.26 to -0.22; P = .006) and longitudinal CSF Aβ42/40 in BioFINDER-1 (p-tau217: β = -0.0003; 95% CI, -0.0004 to -0.0001; P = .01; Aβ42/40: β = 0.0004; 95% CI, 0.0002-0.0006; P < .001) in CU participants with subthreshold Aβ levels at baseline. Plasma p-tau231 and GFAP did not provide any clear independent value.Conclusions and relevanceResults of this cohort study suggest that combining plasma p-tau217and Aβ42/40 levels could be useful for predicting development of Aβ pathology in people with early stages of subthreshold Aβ accumulation. These biomarkers might thus facilitate screening of participants for future primary prevention trials.

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CSF tau and tau/A?42 predict cognitive decline in Parkinson's disease.

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CSF tau and tau/Aβ42 predict cognitive decline in Parkinson's disease.

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