Blood-based metabolic signatures in Alzheimer's disease

TL;DR

This study identifies blood-based metabolic signatures associated with Alzheimer's disease, revealing potential early biomarkers and differences in metabolic networks based on APOE genotype, which could inform diagnosis and understanding of disease pathways.

Contribution

The paper introduces a comprehensive analysis of blood metabolites in AD, highlighting specific biomarkers and network differences related to APOE genotype, advancing biomarker discovery and disease pathway insights.

Findings

26 metabolites differentially expressed in AD

Metabolite signatures improved classification accuracy from 74% to 79%

Distinct metabolic network structures based on APOE genotype

Abstract

Introduction: Identification of blood-based metabolic changes might provide early and easy-to-obtain biomarkers. Methods: We included 127 AD patients and 121 controls with CSF-biomarker-confirmed diagnosis (cut-off tau/A$\beta_{42}$: 0.52). Mass spectrometry platforms determined the concentrations of 53 amine, 22 organic acid, 120 lipid, and 40 oxidative stress compounds. Multiple signatures were assessed: differential expression (nested linear models), classification (logistic regression), and regulatory (network extraction). Results: Twenty-six metabolites were differentially expressed. Metabolites improved the classification performance of clinical variables from 74% to 79%. Network models identified 5 hubs of metabolic dysregulation: Tyrosine, glycylglycine, glutamine, lysophosphatic acid C18:2 and platelet activating factor C16:0. The metabolite network for APOE $\epsilon$4 negative AD patients was less cohesive compared to the network for APOE $\epsilon$4 positive AD patients. Discussion: Multiple signatures point to various promising peripheral markers for further validation. The network differences in AD patients according to APOE genotype may reflect different pathways to AD.