Evidence map›Paper›PMID 41614741›Full record

ArticleCurrent issues in molecular biology2025

Comparative Multi-Omics Analysis Identifies Shared Transcriptomic Signatures and Therapeutic Targets in Alzheimer's, Parkinson's, and Huntington's Diseases.

Luai Ibrahim Alharbi, Elsayed Badr, Abdallah Donia, Eman Monir

Abstract read
In one paragraph

Article in Current issues in molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Luai Ibrahim AlharbiDepartment of Science and Artificial Intelligence, Faculty of Information Technology, Monash University, Clayton, VIC 3800, Australia.ORCID 0009-0003-1256-1614
Elsayed BadrDepartment of Information Systems, College of Information Technology, Misr University for Science and Technology (MUST), Giza P.O. Box 77, Egypt.ORCID 0000-0002-7666-1169
Abdallah DoniaDepartment of Scientific Computing, Faculty of Computer and Artificial Intelligence, Benha University, Benha 13518, Egypt.ORCID 0009-0006-7245-6260
Eman MonirDepartment of Scientific Computing, Faculty of Computer and Artificial Intelligence, Benha University, Benha 13518, Egypt.ORCID 0000-0002-3729-2778

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD) are major neurodegenerative disorders that share certain pathological features but differ in their genetic etiology and clinical presentation. Their potential molecular intersections remain incompletely understood. In this research, we conducted a comparative transcriptomic analysis using postmortem brain RNA-seq datasets from AD (GSE53697), PD (GSE68719), and HD (GSE64810) to identify shared and disease-specific transcriptional signatures. Differentially expressed genes (DEGs) were determined and functionally characterized through Gene Ontology (GO) enrichment. Protein-protein interaction (PPI) networks were generated using STRING and visualized in Cytoscape to identify central hub genes, followed by gene-disease and drug-interaction analyses to assess functional and therapeutic relevance. Ten DEGs were found to overlap among the three disorders, exhibiting variable directions of regulation across diseases. Enrichment analysis indicated convergence on immune- and inflammation-related biological processes. Key hub genes, including

Indexed as

Alzheimer’s diseasedifferential gene expressiongene ontologyHuntington’s diseaseneuroinflammationParkinson’s diseaseprotein–protein interaction networkRNA-seq

Identifiers

PMID41614741
PMCPMC12732164

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.