Baseline plasma NfL, p‐tau217 and tau‐PET SUVr predict cognitive decline in non‐demented persons from a memory clinic

Abstract Background Plasma biomarkers have been increasingly studied in Alzheimer’s disease due to their potentially high accessibility, affordability, and low invasiveness. Recent studies have shown that baseline plasma levels are capable of predicting cognitive decline in cognitively unimpaired subjects (CU) and with mild cognitive impairment (MCI). Despite the fact that neuroimaging biomarkers are also strong predictors, it is still unclear how well they perform when compared to plasma biomarkers in predicting cognitive deterioration. Method Our goal was to evaluate how plasma (i.e., p‐tau181, p‐tau231, p‐tau217, GFAP, and NfL) and traditional neuroimaging biomarkers (i.e., amyloid‐PET centiloid, tau‐PET global‐SUVr, and hippocampal volume) are able to predict cognitive decline in non‐demented individuals. A total of 100 subjects were included in this study, namely 67 MCI and 33 CU from the Geneva Memory Center cohort. The study applied linear mixed‐effect regression models to evaluate how baseline biomarker levels predict cognitive decline. Moreover, sample sizes for future AD clinical trials were calculated for a subset of amyloid‐positive subjects based on how well each biomarker could predict the disease. Result Cognitive decline was only significantly predicted in the MCI subsample by baseline plasma NfL (β = ‐0.53, p = 0.02) p‐tau217 (β = ‐0.59, p = 0.009), and tau‐SUVR (β = ‐0.91, p = 0.002). Lastly, we have proven that the sample sizes for future treatment trials targeting AD can be reduced by up to 70% in individuals who exhibit both amyloid‐PET positivity by incorporating NfL as a requirement for inclusion. On the other hand, the inclusion of p‐tau217 might decrease amyloid‐positive sample sizes only by 10%. Conclusion Tau‐SUVR was the best predictor of cognitive decline in the MCI stage, followed by plasma p‐tau217, and NfL. However, when the goal is to identify at‐risk subjects for future AD clinical trials with amyloid‐PET positivity in the inclusion criteria, the NfL seems to be the most appropriate biomarker to evaluate. This implies a strong association between amyloid‐PET and p‐tau217, whereas NfL may be more appropriate to identify individuals at‐risk for developing cognitive decline.

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Journal
Alzheimer s & Dementia
Published
2024-12-01
DOI
https://doi.org/10.1002/alz.088816
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
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article

Baseline plasma NfL, p‐tau217 and tau‐PET SUVr predict cognitive decline in non‐demented persons from a memory clinic

Nicholas James Ashton, Frédéric Assal, Kaj Blennow, Augusto J. Mendes et al.
Alzheimer s & Dementia
Dementia and Cognitive Impairment Research
article

Baseline plasma NfL, p‐tau217 and tau‐PET SUVr predict cognitive decline in non‐demented persons from a memory clinic

Nicholas James Ashton, Frédéric Assal, Kaj Blennow, Augusto J. Mendes, Max Scheffler, Valentina Garibotto, Oskar Hansson, Giovanni Battista Frisoni, Aurélien Lathuilière, Federica Ribaldi, Henrik Zetterberg, Shorena Janelidze
article en

Abstract

Abstract Background Plasma biomarkers have been increasingly studied in Alzheimer’s disease due to their potentially high accessibility, affordability, and low invasiveness. Recent studies have shown that baseline plasma levels are capable of predicting cognitive decline in cognitively unimpaired subjects (CU) and with mild cognitive impairment (MCI). Despite the fact that neuroimaging biomarkers are also strong predictors, it is still unclear how well they perform when compared to plasma biomarkers in predicting cognitive deterioration. Method Our goal was to evaluate how plasma (i.e., p‐tau181, p‐tau231, p‐tau217, GFAP, and NfL) and traditional neuroimaging biomarkers (i.e., amyloid‐PET centiloid, tau‐PET global‐SUVr, and hippocampal volume) are able to predict cognitive decline in non‐demented individuals. A total of 100 subjects were included in this study, namely 67 MCI and 33 CU from the Geneva Memory Center cohort. The study applied linear mixed‐effect regression models to evaluate how baseline biomarker levels predict cognitive decline. Moreover, sample sizes for future AD clinical trials were calculated for a subset of amyloid‐positive subjects based on how well each biomarker could predict the disease. Result Cognitive decline was only significantly predicted in the MCI subsample by baseline plasma NfL (β = ‐0.53, p = 0.02) p‐tau217 (β = ‐0.59, p = 0.009), and tau‐SUVR (β = ‐0.91, p = 0.002). Lastly, we have proven that the sample sizes for future treatment trials targeting AD can be reduced by up to 70% in individuals who exhibit both amyloid‐PET positivity by incorporating NfL as a requirement for inclusion. On the other hand, the inclusion of p‐tau217 might decrease amyloid‐positive sample sizes only by 10%. Conclusion Tau‐SUVR was the best predictor of cognitive decline in the MCI stage, followed by plasma p‐tau217, and NfL. However, when the goal is to identify at‐risk subjects for future AD clinical trials with amyloid‐PET positivity in the inclusion criteria, the NfL seems to be the most appropriate biomarker to evaluate. This implies a strong association between amyloid‐PET and p‐tau217, whereas NfL may be more appropriate to identify individuals at‐risk for developing cognitive decline.

Alzheimer s & DementiaVol. 20(S2)
University of Geneva (CH), Lund University (SE), University Hospital of Geneva (CH), University of Gothenburg (SE)
Reduced inequalities
Openalex Percentile: Top 65%
Dementia and Cognitive Impairment Research
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