COMPARATIVE ANALYSIS OF ALZHEIMER'S DISEASES: IDENTIFICATION OF HUBS TO FORECAST DIAGNOSIS THROUGH COMPREHENSIVE DATA MINING

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Ahmad Hayat
Muhammad Afzal
Shazia Anwer Bukhari
Muhammad Ahmad Majeed
Abdullah Sethar
Nabila Farah
Atiqa Saleem
Ayesha Hassan
Syed Sabir Ali Shah
Tamseel Saleem
Akbar Ali

Keywords

Neurodegeneration, Transcriptomics, Hub genes, Alzheimer’s, Parkinson’s, Bioinformatics

Abstract

Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common neurodegenerative disorders, often sharing overlapping molecular mechanisms. This study seeks to identify common differentially expressed genes (DEGs) and hub genes between AD and PD using gene expression data from publicly available datasets. We analyzed the GSE122063 dataset for AD and GSE20141 dataset for PD, both sourced from the Gene Expression Omnibus (GEO). After preprocessing, normalization, and differential expression analysis, common DEGs were identified and a protein-protein interaction (PPI) network was constructed using the STRING database. Hub genes were determined using the cytoHubba plugin in Cytoscape based on various centrality measures. The key findings of this study reveal shared pathways involving cellular stress response, neuroinflammation, and synaptic dysfunction. Significant hub genes, including APP, SNCA, MAPT, and TP53, may represent novel therapeutic targets for both AD and PD. These results contribute to understanding the shared molecular landscape between these neurodegenerative disorders and open new avenues for the development of therapeutic interventions.

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