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Updated: Jun 19, 2026

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
Published on: December 15, 2023
A multi-organ metabolomics atlas reveals molecular dysregulations in Alzheimer's disease mouse models
Simone Zuffa1, Celeste Allaband2, Vincent Charron-Lamoureux1
1Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA; Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA.
Abstract:
The etiology of Alzheimer's disease (AD) remains unclear but is likely driven by gene-environment interactions. We present a multi-organ untargeted metabolomics atlas (n = 2,271) paired with metagenomics data (n = 666) from two AD transgenic mouse models (3xTg and 5xFAD) under colonized and germ-free conditions. Systems-level analyses revealed clusters of dysregulated molecules across tissues, including carnitines, bile acids, B vitamins, neurotransmitters, and N-acyl lipids. Metabolic shifts were associated with the depletion of Akkermansia muciniphila and enrichment of Mucispirillum schaedleri in the 3xTg model. We identify previously unexplored carnitines linked to microbial metabolism of phenylalanine. Using tissueMASST-a mass spectrometry search tool we developed to translate animal-model findings into a human clinical context-we trace phenylacetyl-carnitine in human plasma and serum samples (n = 1,470) from independent cohorts, revealing associations with aging, cognitive impairment, and diminished memory performance. This public resource and associated tools will aid future research in AD etiology.
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