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Original research
Use of plasma biomarkers for AT(N) classification of neurodegenerative dementias

Abstract

Objectives All categories included in the AT(N) classification can now be measured in plasma. However, their agreement with cerebrospinal fluid (CSF) markers is not fully established. A blood signature to generate the AT(N) classification would facilitate early diagnosis of patients with Alzheimer’s disease (AD) through an easy and minimally invasive approach.

Methods We measured Aβ, pTau181 and neurofilament light (NfL) in 150 plasma samples of the Sant Pau Initiative on Neurodegeneration cohort including patients with mild cognitive impairment, AD dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal participants. We classified participants in the AT(N) categories according to CSF biomarkers and studied the diagnostic value of plasma biomarkers within each category individually and in combination.

Results The plasma Aβ composite, pTau181 and NfL yielded areas under the curve (AUC) of 0.75, 0.78 and 0.88 to discriminate positive and negative participants in their respective A, T and N categories. The combination of all three markers did not outperform pTau181 alone (AUC=0.81) to discriminate A+T+ from A–T– participants. There was a moderate correlation between plasma Aβ composite and CSF Aβ1–42/Aβ1–40 (Rho=−0.5, p<0.001) and between plasma pTau181 and CSF pTau181 in the entire cohort (Rho=0.51, p<0.001). NfL levels in plasma showed high correlation with those in CSF (Rho=0.78, p<0.001).

Conclusions Plasma biomarkers are useful to detect the AT(N) categories, and their use can differentiate patients with pathophysiological evidence of AD. A blood AT(N) signature may facilitate early diagnosis and follow-up of patients with AD through an easy and minimally invasive approach.

  • csf
  • amyloid

Data availability statement

Raw anonymised data and code for statistical analysis are available upon reasonable request. All requests should be sent to the corresponding author detailing the study hypothesis and statistical analysis plan. The steering committee of this study will decide whether data/code sharing is appropriate based on the novelty and scientific rigor of the proposal. All applicants will be asked to sign a data access agreement.

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