Dataset Information

Appropriateness of Applying Cerebrospinal Fluid Biomarker Cutoffs from Alzheimer's Disease to Parkinson's Disease.

ABSTRACT:

Background

While cutoffs for abnormal levels of the cerebrospinal fluid (CSF) biomarkers amyloid-β 1-42 (Aβ142), total tau (t-tau), phosphorylated tau (p-tau), and the ratios of t-tau/Aβ142 and p-tau/Aβ142, have been established in Alzheimer's disease (AD), biologically relevant cutoffs have not been studied extensively in Parkinson's disease (PD).

Objective

Assess the suitability and diagnostic accuracy of established AD-derived CSF biomarker cutoffs in the PD population.

Methods

Baseline and longitudinal data on CSF biomarkers, cognitive diagnoses, and PET amyloid imaging in 423 newly diagnosed patients with PD from the Parkinson's Progression Markers Initiative (PPMI) cohort were used to evaluate established AD biomarker cutoffs compared with optimal cutoffs derived from the PPMI cohort.

Results

Using PET amyloid imaging as the gold standard for AD pathology, the optimal cutoff of Aβ142 was higher than the AD cutoff, the optimal cutoffs of t-tau/Aβ142 and p-tau/Aβ142 were lower than the AD cutoffs, and their confidence intervals (CIs) did not overlap with the AD cutoffs. Optimal cutoffs for t-tau and p-tau to predict cognitive impairment were significantly lower than the AD cutoffs, and their CIs did not overlap with the AD cutoffs.

Conclusion

Optimal cutoffs for the PPMI cohort for Aβ142, t-tau/Aβ142, and p-tau/Aβ142 to predict amyloid-PET positivity and for t-tau and p-tau to predict cognitive impairment differ significantly from cutoffs derived from AD populations. The presence of additional pathologies such as alpha-synuclein in PD may lead to disease-specific CSF biomarker characteristics.

SUBMITTER: Weinshel S

PROVIDER: S-EPMC9934950 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Appropriateness of Applying Cerebrospinal Fluid Biomarker Cutoffs from Alzheimer's Disease to Parkinson's Disease.

Weinshel Sarah S Irwin David J DJ Zhang Panpan P Weintraub Daniel D Shaw Leslie M LM Siderowf Andrew A Xie Sharon X SX

Journal of Parkinson's disease 20220101 4

<h4>Background</h4>While cutoffs for abnormal levels of the cerebrospinal fluid (CSF) biomarkers amyloid-β 1-42 (Aβ142), total tau (t-tau), phosphorylated tau (p-tau), and the ratios of t-tau/Aβ142 and p-tau/Aβ142, have been established in Alzheimer's disease (AD), biologically relevant cutoffs have not been studied extensively in Parkinson's disease (PD).<h4>Objective</h4>Assess the suitability and diagnostic accuracy of established AD-derived CSF biomarker cutoffs in the PD population.<h4>Meth ...[more]

PMID: 35431261

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Project description:In a large multicentre sample of cognitively normal subjects, as a function of age, gender and APOE genotype, we studied the frequency of abnormal cerebrospinal fluid levels of Alzheimer's disease biomarkers including: total tau, phosphorylated tau and amyloid-β1-42. Fifteen cohorts from 12 different centres with either enzyme-linked immunosorbent assays or Luminex® measurements were selected for this study. Each centre sent nine new cerebrospinal fluid aliquots that were used to measure total tau, phosphorylated tau and amyloid-β1-42 in the Gothenburg laboratory. Seven centres showed a high correlation with the new Gothenburg measurements; therefore, 10 cohorts from these centres are included in the analyses here (1233 healthy control subjects, 40-84 years old). Amyloid-β amyloid status (negative or positive) and neurodegeneration status (negative or positive) was established based on the pathological cerebrospinal fluid Alzheimer's disease cut-off values for cerebrospinal fluid amyloid-β1-42 and total tau, respectively. While gender did not affect these biomarker values, APOE genotype modified the age-associated changes in cerebrospinal fluid biomarkers such that APOE ε4 carriers showed stronger age-related changes in cerebrospinal fluid phosphorylated tau, total tau and amyloid-β1-42 values and APOE ε2 carriers showed the opposite effect. At 40 years of age, 76% of the subjects were classified as amyloid negative, neurodegeneration negative and their frequency decreased to 32% at 85 years. The amyloid-positive neurodegeneration-negative group remained stable. The amyloid-negative neurodegeneration-positive group frequency increased slowly from 1% at 44 years to 16% at 85 years, but its frequency was not affected by APOE genotype. The amyloid-positive neurodegeneration-positive frequency increased from 1% at 53 years to 28% at 85 years. Abnormally low cerebrospinal fluid amyloid-β1-42 levels were already frequent in midlife and APOE genotype strongly affects the levels of cerebrospinal fluid amyloid-β1-42, phosphorylated tau and total tau across the lifespan without influencing the frequency of subjects with suspected non-amyloid pathology.

Project description:ObjectiveWe analyzed the longitudinal profile of Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in early Parkinson's disease (PD) compared with healthy controls (HCs) and tested baseline CSF biomarkers for prediction of clinical decline in PD.MethodsAmyloid-β 1 to 42 (Aβ42 ), total tau (t-tau) and phosphorylated tau (p-tau) at the threonine 181 position were measured using the high-precision Roche Elecsys electrochemiluminescence immunoassay in all available CSF samples from longitudinally studied patients with PD (n = 416) and HCs (n = 192) followed for up to 3 years in the Parkinson's Progression Markers Initiative (PPMI). Longitudinal CSF and clinical data were analyzed with linear-mixed effects models.ResultsWe found patients with PD had lower CSF t-tau (median = 157.7 pg/mL; range = 80.9-467.0); p-tau (median = 13.4 pg/mL; range = 8.0-40.1), and Aβ42 (median = 846.2 pg/mL; range = 238.8-3,707.0) than HCs at baseline (CSF t-tau median = 173.5 pg/mL; range = 82.0-580.8; p-tau median = 15.4 pg/mL; range = 8.1-73.6; and Aβ42 median = 926.5 pg/mL; range = 239.1-3,297.0; p < 0.05-0.001) and a moderate-to-strong correlation among these biomarkers in both patients with PD and HCs (Rho = 0.50-0.97; p < 0.001). Of the patients with PD, 31.5% had pathologically low levels of CSF Aβ42 at baseline and these patients with PD had lower p-tau levels (median = 10.8 pg/mL; range = 8.0-32.8) compared with 27.7% of HCs with pathologically low CSF Aβ42 (CSF p-tau median = 12.8 pg/mL; range 8.2-73.6; p < 0.03). In longitudinal CSF analysis, we found patients with PD had greater decline in CSF Aβ42 (mean difference = -41.83 pg/mL; p = 0.03) and CSF p-tau (mean difference = -0.38 pg/mL; p = 0.03) at year 3 compared with HCs. Baseline CSF Aβ42 values predicted small but measurable decline on cognitive, autonomic, and motor function in early PD.InterpretationOur data suggest baseline CSF AD biomarkers may have prognostic value in early PD and that the dynamic change of these markers, although modest over a 3-year period, suggest biomarker profiles in PD may deviate from healthy aging. ANN NEUROL 2020;88:574-587.

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Project description:Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aβ40lumi and Aβ42/Aβ40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aβ40lumi and t-tau/Aβ40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aβ40lumi, p-tau181/Aβ40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.

Project description:IntroductionThe relevance of the cerebrospinal fluid (CSF) biomarkers for the diagnosis of Alzheimer's disease (AD) and related disorders is clearly established. However, the question remains on how to use these data, which are often heterogeneous (not all biomarkers being pathologic). The objective of this study is to propose to physicians in memory clinics a biologic scale of probabilities that the patient with cognitive impairments has an Alzheimer's disease (AD) pathologic process.MethodsFor that purpose, we took advantage of the multicenter data of our Paris-North, Lille, and Montpellier (PLM) study, which has emerged through the initial sharing of information from these memory centers. Different models combining the CSF levels of amyloid-β 42, tau, and p-tau(181) were tested to generate categories of patients with very low (<10%), low (<25%), high (>75%), and very high predictive values (>90%) for positive AD. In total, 1,273 patients (646 AD and 627 non-AD) from six independent memory-clinic cohorts were included.ResultsA prediction model based on logistic regressions achieved a very good stratification of the population but had the disadvantages of needing mathematical optimization and being difficult to use in daily clinical practice. Remarkably, a simple and intuitive model based on the number (from zero to three) of three pathologic CSF biomarkers resulted in a very efficient predictive scale for AD in patients seen in memory clinics. The scale's overall predictive value for AD for the different categories were as follows: class 0, 9.6% (95% confidence interval (CI), 6.0% to 13.2%); class 1, 24.7% (95% CI, 18.0% to 31.3%); class 2, 77.2% (95% CI, 67.8% to 86.5%); and class 3, 94.2% (95% CI, 90.7% to 97.7%). In addition, with this scale, significantly more patients were correctly classified than with the logistic regression. Its superiority in model performance was validated by the computation of the net reclassification index (NRI). The model was also validated in an independent multicenter dataset of 408 patients (213 AD and 195 non-AD).ConclusionsIn conclusion, we defined a new scale that could be used to facilitate the interpretation and routine use of multivariate CSF data, as well as helping the stratification of patients in clinical research trials.

Dataset Information

Appropriateness of Applying Cerebrospinal Fluid Biomarker Cutoffs from Alzheimer's Disease to Parkinson's Disease.

Background

Objective

Methods

Results

Conclusion

Publications

Appropriateness of Applying Cerebrospinal Fluid Biomarker Cutoffs from Alzheimer's Disease to Parkinson's Disease.

Similar Datasets

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