CSF proteome profiling across the Alzheimer’s disease spectrum reflects the multifactorial nature of the disease and identifies specific biomarker panels

Marta del Campo, Carel F. W. Peeters, Erik C. B. Johnson, Lisa Vermunt, Yanaika S. Hok-A-Hin, Mirrelijn van Nee, Alice Chen-Plotkin, David J. Irwin, William T. Hu, James J. Lah, Nicholas T. Seyfried, Eric B. Dammer, Gonzalo Herradon, Lieke H. Meeter, John van Swieten, Daniel Alcolea, Alberto Lleó, Allan I. Levey, Afina W. Lemstra, Yolande A. L. PijnenburgPieter J. Visser, Betty M. Tijms, Wiesje M. van der Flier, Charlotte E. Teunissen

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Scopus)

Abstract

Development of disease-modifying therapies against Alzheimer’s disease (AD) requires biomarkers reflecting the diverse pathological pathways specific for AD. We measured 665 proteins in 797 cerebrospinal fluid (CSF) samples from patients with mild cognitive impairment with abnormal amyloid (MCI(Aβ+): n = 50), AD-dementia (n = 230), non-AD dementias (n = 322) and cognitively unimpaired controls (n = 195) using proximity ligation-based immunoassays. Here we identified >100 CSF proteins dysregulated in MCI(Aβ+) or AD compared to controls or non-AD dementias. Proteins dysregulated in MCI(Aβ+) were primarily related to protein catabolism, energy metabolism and oxidative stress, whereas those specifically dysregulated in AD dementia were related to cell remodeling, vascular function and immune system. Classification modeling unveiled biomarker panels discriminating clinical groups with high accuracies (area under the curve (AUC): 0.85–0.99), which were translated into custom multiplex assays and validated in external and independent cohorts (AUC: 0.8–0.99). Overall, this study provides novel pathophysiological leads delineating the multifactorial nature of AD and potential biomarker tools for diagnostic settings or clinical trials.
Original languageEnglish
Pages (from-to)1040-1053
Number of pages14
JournalNature Aging
Volume2
Issue number11
Early online date2022
DOIs
Publication statusPublished - 1 Nov 2022

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