A Pragmatic, Data-Driven Method to Determine Cutoffs for CSF Biomarkers of Alzheimer Disease Based on Validation Against PET Imaging

Abstract

Objective:To elaborate a new algorithm to establish a standardized method to define cuff-offs for CSF biomarkers of Alzheimer’s disease (AD) by validating the algorithm against CSF classification derived from PET imaging.Methods:Low and high levels of CSF phosphorylated tau were first identified to establish optimal cut-offs for CSF amyloid-β peptide (Aβ) biomarkers. These Aβ cut-offs were then used to determine cut-offs for CSF tau and phosphorylated tau markers. We compared this algorithm to a reference method, based on tau and amyloid PET imaging status (ADNI study), and then applied the algorithm to 10 large clinical cohorts of patients.Results:A total of 6,922 subjects with CSF biomarkers data were included (mean (SD) age: 70.6 (8.5) years, 51.0% women). In the ADNI study population (n=497), the agreement between classification based on our algorithm and one based on amyloid/tau PET imaging was high with Cohen’s kappa coefficient between 0.87 and 0.99. Applying the algorithm to 10 large cohorts of patients (n=6,425), the proportion of persons with AD ranged from 25.9% to 43.5%.Discussion:The proposed novel, pragmatic method to determine CSF biomarkers cut-offs for AD does not require assessment of other biomarkers or assumptions concerning the clinical diagnosis of patients. Use of this standardized algorithm is likely to reduce heterogeneity in AD classification.

A data‐driven approach to complement the A/T/(N) classification system using CSF biomarkers

“…Moreover, clustering techniques like the one applied in this work would not require determining the cut‐off points using traditional methods. This fact avoids the need for a comparison with a healthy control group (which could be in preclinical stages and develop AD in the following years) or using amyloid PET (which also requires cut‐off points) as standard 17,22–24 . Moreover, it considers the mentioned interaction between biomarkers.…”

“…This fact avoids the need for a comparison with a healthy control group (which could be in preclinical stages and develop AD in the following years) or using amyloid PET (which also requires cut‐off points) as standard. 17 , 22 , 23 , 24 Moreover, it considers the mentioned interaction between biomarkers. Thus, clustering techniques could be useful to obtain valid groups for different cohorts, reducing the variability across centers and the limitations of using cut‐off points from other populations 25 , 26 , 27 and with a similar computational cost to the AT(N) system.…”

Impact of amyloid and tau positivity on longitudinal brain atrophy in cognitively normal individuals

“…CSF concentrations of Aβ42 and p-tau181 were measured with the Elecsys immunoassays using the cobas e601 analyzer (Roche Diagnostics GmbH, Mannheim, Germany) [ 15 , 16 ]. In the present study, the cutoff values for CSF concentrations of Aβ42 and p-tau181 were defined as 981 pg/mL based on 18F-florbetapir PET and 24.3 pg/mL based on 18F-flortaucipir PET, respectively [ 17 ]; namely, participants with Aβ42 < 981 pg/mL were classified as amyloid positive (A +). Participants with p-tau181 > 24.3 pg/mL were classified as tau positive (T +).…”

The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022

“…A method to standardize the procedure for cutpoint determination in different cohorts was developed that relies on CSF p-tau181 levels to determine the cut-point values for CSF Aβ42 and CSF Aβ40. 42 The method was validated against Aβ and tau PET and tested across 11 cohorts including ADNI and may make selection of different data sets, AdataViewer, aims to increase the findability and interoperability of cohort data sets, saving time and effort for researchers in the field. 45 It allows researchers to access metadata from 20 cohort studies including ADNI, to select cohorts that contain their variables of interest, and to apply for data access (Figure S3 in supporting information).…”

“…Determination of Aβ and tau status from CSF biomarkers is also complicated by variability in assay methods that precludes the use of universal cut‐points. A method to standardize the procedure for cut‐point determination in different cohorts was developed that relies on CSF p‐tau181 levels to determine the cut‐point values for CSF Aβ42 and CSF Aβ40 42 . The method was validated against Aβ and tau PET and tested across 11 cohorts including ADNI and may make selection of cut‐points across cohorts a more transparent process.…”