Related Experiment Video
Updated: Jul 12, 2026

Biomarker Identification for Gender Specificity of Alzheimer's Disease Based on the Glial Transcriptome Profiles
Published on: May 20, 2024
Region-specific Transcriptomic Signatures in Alzheimer's Disease: A Meta-analysis of Vulnerable Brain Regions Reveals
Khojaste Rahimi Jaberi1, Shayan Khalili Alashti2, Sedighe Hooshmandi3
1Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.
Background:
Alzheimer's disease (AD) is characterized by progressive neurodegeneration in regionally vulnerable brain areas, yet molecular insights into early pathogenic mechanisms remain limited.
Methods:
We conducted a meta-analysis of transcriptomic datasets from brain regions affected in early-to-moderate AD - including entorhinal cortex, CA1 hippocampus, angular gyrus, and frontal cortex synaptoneurosomes - using data from seven mRNA and one microRNA (miRNA) microarray studies (GSE16759, GSE110226, GSE37264, GSE26972, GSE36980, GSE37263, GSE39420, and GSE157239). Preprocessing included background correction, log2 transformation, quantile normalization, and batch correction via ComBat. Differentially expressed features were defined as false discovery rate <0.05 and | logFC| ≥ 1.23 (genes) or ≥ 2 (miRNAs).
Results:
We identified 172 differentially expressed genes (122 upregulated and 50 downregulated) and 82 significant miRNAs. Hub genes included Inositol-trisphosphate 3-kinase B (ITPKB), Synaptotagmin 1, Dystrobrevin alpha (DTNA), X Inactive Specific Transcript, and Regulator of G protein signaling 4 (RGS4). Functional enrichment highlighted calcium signaling, synaptic failure, and neuroinflammation. Notably, hsa-miR-30d-5p was predicted to target both ITPKB and DTNA, suggesting a regulatory axis linking miRNA dysregulation to calcium dyshomeostasis. Receiver operating characteristic analysis revealed that only RGS4 showed moderate discriminative capacity (area under the curve [AUC] =0.70), while other hub genes (e.g., ITPKB, AUC = 0.40) exhibited below-chance performance, underscoring the limitations of single-gene classifiers in postmortem tissue.
Conclusion:
This study provides mechanistic hypotheses - rather than diagnostic biomarkers - by uncovering region-specific, miRNA-mediated regulatory networks in AD-affected brain tissues. Future validation in accessible biofluids is essential before clinical translation.
More Related Videos
04:41Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
Published on: January 9, 2020
09:47DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
Published on: December 15, 2023
Related Concept Videos
Alzheimer Disease ll: Pathophysiology
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...
Alzheimer Disease l: Introduction
MicroRNAs