Related Experiment Video
Updated: Jul 16, 2026

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
Published on: December 15, 2023
An Exploratory Six-Probe Blood RNA Signature for Predicting 12-Month Cognitive Decline Along the Alzheimer's Disease
Asif Hassan Syed1, Sultan Alhayyani2
1Department of Computer Science, Faculty of Computing and Information Technology at Rabigh, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Abstract:
Background/Objectives: Predicting how fast a patient with Alzheimer's disease will decline over the next year remains a challenge. Existing blood transcriptomic studies have not established whether probe selection is reproducible, whether the signal is transcriptional or reflects immune cell shifts, or whether they generalise across platforms. Methods: We applied five steps to 96 ADNI-GO whole-blood microarray samples (Affymetrix HG-U219; 12-month MMSE change): PyImpetus Markov Blanket selection, Elastic Net with leave-one-out cross-validation (LOOCV), SHAP attribution, MCP-counter cell-type deconvolution, and cross-platform mapping into AddNeuroMed (GSE63060, n = 329, Illumina). Feature selection preceded cross-validation without constituting data leakage. Results: The same six probes emerged across four independent runs (Jaccard J = 0.214, p = 0.03): AQP7, RPS5, CHD2, SNX5, ASS1, and an uncharacterised chr12q15 transcript. The panel achieved LOOCV MAE = 1.388 and R2 = 0.247, outperforming the full-probe baseline by 14.9%. All probes survived immune cell correction with signs intact. SNX5 replicated in AddNeuroMed (r = -0.170, p = 0.002). Conclusions: The exploratory six-probe blood RNA panel predicts 12-month cognitive decline (LOOCV R2 = 0.247) with transcriptional origin confirmed by cell-type deconvolution and cross-platform evidence for SNX5. External testing in ADNI-2 (n = 91, R2 = -0.222) showed that generalisation depends on visit-timepoint matching, indicating clinical utility cannot yet be claimed and defining conditions for prospective validation. Code and a research prototype tool are publicly available.
More Related Videos
09:38Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
Published on: November 14, 2017
12:18A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Related Concept Videos
Alzheimer Disease l: Introduction
Alzheimer's Disease: Overview
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ and tau...