Cerebrospinal fluid proteomics in patients with Alzheimer’s disease reveals five molecular subtypes with distinct genetic risk profiles

Journal Article (2024)
Author(s)

Betty M. Tijms (Vrije Universiteit Amsterdam, Amsterdam UMC)

Ellen M. Vromen (Vrije Universiteit Amsterdam, Amsterdam UMC)

Olav Mjaavatten (University of Bergen and Bjerknes Centre for Climate Research)

Henne Holstege (Amsterdam UMC, Vrije Universiteit Amsterdam)

Lianne M. Reus (University of California, Amsterdam UMC, Vrije Universiteit Amsterdam)

Sven van der Lee (Vrije Universiteit Amsterdam, Amsterdam UMC)

Kirsten E.J. Wesenhagen (Vrije Universiteit Amsterdam, Amsterdam UMC)

Luigi Lorenzini (Amsterdam UMC, Vrije Universiteit Amsterdam)

Niccoló Tesi (Vrije Universiteit Amsterdam, TU Delft - Pattern Recognition and Bioinformatics)

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Research Group
Pattern Recognition and Bioinformatics
DOI related publication
https://doi.org/10.1038/s43587-023-00550-7
More Info
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Publication Year
2024
Language
English
Research Group
Pattern Recognition and Bioinformatics
Journal title
Nature Aging
Issue number
1
Volume number
4
Pages (from-to)
33-47
Downloads counter
445
Collections
Institutional Repository
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Abstract

Alzheimer’s disease (AD) is heterogenous at the molecular level. Understanding this heterogeneity is critical for AD drug development. Here we define AD molecular subtypes using mass spectrometry proteomics in cerebrospinal fluid, based on 1,058 proteins, with different levels in individuals with AD (n = 419) compared to controls (n = 187). These AD subtypes had alterations in protein levels that were associated with distinct molecular processes: subtype 1 was characterized by proteins related to neuronal hyperplasticity; subtype 2 by innate immune activation; subtype 3 by RNA dysregulation; subtype 4 by choroid plexus dysfunction; and subtype 5 by blood–brain barrier impairment. Each subtype was related to specific AD genetic risk variants, for example, subtype 1 was enriched with TREM2 R47H. Subtypes also differed in clinical outcomes, survival times and anatomical patterns of brain atrophy. These results indicate molecular heterogeneity in AD and highlight the need for personalized medicine.

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