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Updated: Aug 21, 2026

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
Published on: December 15, 2023
Associations of proteomic and epigenetic aging clocks with Alzheimer's disease phenotypes: An exploratory analysis
Cindy David Sarmento1, Gabin Drouard1, Toni T Saari1
1Institute for Molecular Medicine Finland (FIMM) HiLIFE University of Helsinki Helsinki Finland.
Introduction:
Proteomic aging clocks detect disease-related systemic and organ-specific changes and are easily accessible by minimally invasive blood draws. However, their potential in Alzheimer's disease (AD) assessment remains unestablished.
Methods:
We investigated associations of proteomic and epigenetic clocks with AD-related blood-based biomarkers and cognitive tests. Omics were generated from blood samples of 153 cognitively unimpaired individuals (average age 62 years); blood biomarkers and cognition were measured approximately nine years after.
Results:
Proteomic clocks explained up to 23% of variance in cognitive and biomarker measures not explained by epigenetics. Accelerated systemic and brain-specific proteomic aging were linked to poorer cognition and higher levels of plasma neurofilament light chain. Exploratory interaction analyses suggested weaker proteomic aging-cognition associations in individuals with higher genetic liability for diabetes.
Discussion:
Our study illustrates the potential of plasma proteomic clocks in detecting AD-related phenotypes. However, co-morbidities possibly constitute confounding factors, compromising the performance of proteomic aging models.
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