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Related Experiment Video

Updated: Oct 10, 2025

Visualization of Amyloid β Deposits in the Human Brain with Matrix-assisted Laser Desorption/Ionization Imaging Mass Spectrometry

Visualization of Amyloid β Deposits in the Human Brain with Matrix-assisted Laser Desorption/Ionization Imaging Mass Spectrometry

Published on: March 7, 2019

Soluble amyloid-beta isoforms predict downstream Alzheimer's disease pathology.

Guilherme Povala^1,2, Bruna Bellaver¹, Marco Antônio De Bastiani¹

¹Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.

Cell & Bioscience

|December 13, 2021

Summary

Soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) can predict tau pathology and neurodegeneration in cognitively unimpaired individuals. Machine learning models achieved high accuracy, identifying key biological processes for further Alzheimer's disease research.

Keywords:

Alzheimer’s disease Amyloid-beta Machine learning Neurodegeneration Proteomics Tau pathology

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Last Updated: Oct 10, 2025

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Area of Science:

Neuroscience
Biochemistry
Computational Biology

Background:

Soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are early indicators of Alzheimer's disease (AD).
Predictive value of Aβ isoforms for downstream tau pathology (T+) and neurodegeneration (N+) in cognitively unimpaired (CU) individuals remains unclear.

Purpose of the Study:

To investigate if combined soluble Aβ isoforms can predict T+ and N+ positivity in CU individuals.
To explore biological processes altered in individuals with predicted T+ and N+ using proteomics.

Main Methods:

Machine learning (ML) models were trained using CSF Aβ_1-38, Aβ_1-40, and Aβ_1-42 measurements from 318 CU individuals.
2046 predictive ML models were built using nested cross-validation.
Proteomics data analyzed for functional enrichment of differentially expressed proteins (DEPs) in misclassified individuals.

Main Results:

Aβ isoforms accurately predicted T+ (AUC=0.929) and N+ (AUC=0.936).
Proteomics identified 17 DEPs in misclassified individuals.
Enrichment analysis revealed altered myelinization, glucose metabolism, amino acid biosynthesis, and cell adhesion pathways.

Conclusions:

Refined ML analysis demonstrates high predictive accuracy of Aβ isoforms for T+ and N+.
CSF proteomics identified potential biomarkers for improving T+ and N+ prediction in early AD stages.