Deciphering molecular atlas of Alzheimer’s disease: A comprehensive bioinformatic analysis of gene expression and protein interaction networks

Alzheimer’s disease (AD) represents a formidable challenge in the realm of neurodegenerative research due to its complex pathology. Despite tremendous scientific endeavors, the intricate molecular underpinnings of AD remain incompletely understood, necessitating a multidimensional approach to decipher its complexity. In this study, we analyzed differential gene expression, gene ontology (GO) enrichment, and protein–protein interaction (PPI) networks using advanced bioinformatics tools to dissect the molecular landscape of AD. Initially, our research identified 732 differentially expressed genes (DEGs), which provided a comprehensive view of the genetic disruptions associated with AD. The results of subsequent GO enrichment analyses revealed that DEGs were enriched in several critical biological processes, predominantly including translation, neuroinflammation, and synaptic functionality, underscoring the multifaceted nature of AD pathology. The PPI network analysis further unveiled the central role of ribosomal proteins, such as RPL12, RPL15, RPL18, RPL19, RPL27, RPL35, RPL36, RPS16, RPS19, and RPS9, establishing a novel link between protein synthesis disruptions and the molecular mechanisms of AD. These results not only deepen the understanding of molecular mechanisms underlying AD but also illuminate potential therapeutic pathways and biomarkers for AD. Overall, our comprehensive bioinformatics exploration unraveled the complex molecular mechanisms that govern AD pathogenesis and highlighted promising new targets for the diagnosis and treatment of AD, creating a foundational framework for future research on AD.

Authors

Publication Details

Journal
Brain & Heart
Published
2024-08-29
DOI
https://doi.org/10.36922/bh.2906
Citations
2
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.47
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article

Deciphering molecular atlas of Alzheimer’s disease: A comprehensive bioinformatic analysis of gene expression and protein interaction networks

Shan Luo, Kohji Fukunaga, Yifei Wang
2 citations
Brain & Heart
Bioinformatics and Genomic Networks
0.47
article

Deciphering molecular atlas of Alzheimer’s disease: A comprehensive bioinformatic analysis of gene expression and protein interaction networks

Shan Luo, Kohji Fukunaga, Yifei Wang
article en
2 citations

Abstract

Alzheimer’s disease (AD) represents a formidable challenge in the realm of neurodegenerative research due to its complex pathology. Despite tremendous scientific endeavors, the intricate molecular underpinnings of AD remain incompletely understood, necessitating a multidimensional approach to decipher its complexity. In this study, we analyzed differential gene expression, gene ontology (GO) enrichment, and protein–protein interaction (PPI) networks using advanced bioinformatics tools to dissect the molecular landscape of AD. Initially, our research identified 732 differentially expressed genes (DEGs), which provided a comprehensive view of the genetic disruptions associated with AD. The results of subsequent GO enrichment analyses revealed that DEGs were enriched in several critical biological processes, predominantly including translation, neuroinflammation, and synaptic functionality, underscoring the multifaceted nature of AD pathology. The PPI network analysis further unveiled the central role of ribosomal proteins, such as RPL12, RPL15, RPL18, RPL19, RPL27, RPL35, RPL36, RPS16, RPS19, and RPS9, establishing a novel link between protein synthesis disruptions and the molecular mechanisms of AD. These results not only deepen the understanding of molecular mechanisms underlying AD but also illuminate potential therapeutic pathways and biomarkers for AD. Overall, our comprehensive bioinformatics exploration unraveled the complex molecular mechanisms that govern AD pathogenesis and highlighted promising new targets for the diagnosis and treatment of AD, creating a foundational framework for future research on AD.

Brain & HeartVol. 2(4)
Openalex Percentile: Top 35%
Bioinformatics and Genomic Networks
0.47
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