Identifying Hub Genes and miRNAs in Alzheimer's Disease

Table of Contents

Key Findings on Differentially Expressed Genes in Alzheimer’s Disease

Recent bioinformatics analyses have unveiled a plethora of differentially expressed genes (DEGs) in Alzheimer’s Disease. In a study utilizing the GSE138260 dataset, a total of 612 DEGs were identified, comprising 388 upregulated and 224 downregulated genes (Gascón et al., 2024). The upregulated genes predominantly relate to sensory perception, while the downregulated genes are implicated in the regulation and modulation of synaptic processes.

Gene Classification Number of Genes Associated Functions
Upregulated DEGs 388 Sensory perception
Downregulated DEGs 224 Synaptic modulation

The identification of these DEGs is crucial, as they provide insights into the molecular mechanisms underlying AD pathology, particularly in synaptic dysfunction and neurodegeneration, which are hallmarks of Alzheimer’s Disease.

Functional Pathways and Enrichment Analysis of Hub Genes

Further analysis revealed that the identified DEGs are involved in significant biological pathways, including:

  1. Sensory Perception of Chemical Stimulus: This pathway was enriched among upregulated DEGs, indicating a potential alteration in sensory processing in Alzheimer’s patients.
  2. Regulation of Synaptic Transmission: Downregulated genes linked to synaptic processes suggest disruptions in neurotransmission, which could contribute to cognitive decline.

Moreover, protein-protein interaction (PPI) network analysis has pinpointed 20 hub genes, key players in these pathways, which include:

  • CD2
  • CDC25A
  • S100A7

These genes are instrumental in various biological functions that may be impacted in Alzheimer’s pathology. The integration of these findings through bioinformatics tools emphasizes the potential for identifying novel therapeutic targets.

Protein-Protein Interaction Networks and Their Implications

The construction of PPI networks using STRING database tools and Cytoscape software has illuminated critical interactions between identified hub genes. For instance, the hub genes S100A7 and SPRR2G emerged as key players in neuroinflammatory responses and synaptic alterations associated with AD. The following table summarizes the hub genes and their potential implications in Alzheimer’s:

Hub Gene Function Implications in AD
CD2 Immune response Possible role in Aβ deposition and tau pathology
CDC25A Cell cycle regulation Neuronal protection against Aβ-induced cytotoxicity
S100A7 Calcium-binding protein Modulates Aβ levels and neuroinflammation

These interactions not only provide insights into the molecular landscape of Alzheimer’s but also highlight potential intervention points for therapeutic development.

Role of miRNAs in Alzheimer’s Disease: Targeting Hub Genes

The analysis extended to the role of miRNAs in regulating the expression of the identified hub genes. A total of 1767 miRNAs were found to target these hub genes, among which several, such as hsa-miR-106a-5p and hsa-miR-34a-5p, have gained attention due to their relevance in AD pathology.

miRNA Target Hub Genes Role in Alzheimer’s Disease
hsa-miR-106a-5p CD2, CDC25A Reduces VEGFA levels, potentially impacting neuroprotection
hsa-miR-34a-5p S100A7 Inhibits synaptic plasticity, linked to cognitive decline

These findings underscore the potential for miRNAs as biomarkers and therapeutic targets, offering new avenues for intervention in AD.

Proposed Therapeutic Strategies Based on Bioinformatics Insights

The identification of hub genes and their regulatory miRNAs opens up several therapeutic strategies:

  1. Gene Therapy: Targeting specific hub genes using gene editing technologies like CRISPR/Cas9 could restore normal function to disrupted pathways.
  2. miRNA Mimics/Inhibitors: Developing compounds that mimic the action of beneficial miRNAs or inhibit the harmful ones may modulate disease progression.
  3. Small Molecule Drugs: Targeting the pathways associated with the identified DEGs may provide symptomatic relief or modify disease progression.

These strategies, informed by comprehensive bioinformatics analyses, represent a promising frontier in Alzheimer’s research and treatment.

FAQ

What is Alzheimer’s Disease?

Alzheimer’s Disease is a neurodegenerative disorder characterized by progressive cognitive decline, memory impairment, and changes in behavior. It is the most common cause of dementia among older adults.

How are hub genes identified in Alzheimer’s Disease?

Hub genes are identified through bioinformatics analyses of gene expression datasets, such as the GSE138260 dataset. By analyzing differentially expressed genes and their interactions in protein-protein interaction networks, researchers can pinpoint key hub genes that play critical roles in disease mechanisms.

What role do miRNAs play in Alzheimer’s Disease?

miRNAs are small non-coding RNAs that regulate gene expression. In Alzheimer’s Disease, specific miRNAs can target hub genes that are involved in the disease’s pathology, potentially serving as biomarkers for diagnosis or targets for therapeutic interventions.

What are some potential therapeutic strategies for Alzheimer’s Disease based on this research?

Potential therapeutic strategies include gene therapy targeting hub genes, developing miRNA mimics or inhibitors, and creating small molecule drugs that modulate the pathways associated with the identified DEGs.

References

  1. Gascón, E., Calvo, A. C., Molina, N., Zaragoza, P., Osta, R. (2024). Identifying Hub Genes and miRNAs Associated with Alzheimer’s Disease: A Bioinformatics Pathway to Novel Therapeutic Strategies. Biomolecules. Retrieved from https://doi.org/10.3390/biom14121641

  2. Yang, S., Yuan, Z., Cheng, G. (2025). Effects of aerobic exercise on cognitive function and quality of life in patients with Alzheimer’s disease: a systematic review and meta-analysis. BMJ Open. Retrieved from https://doi.org/10.1136/bmjopen-2024-090623

  3. Hadi, Z., Mahmud, M., Seemungal, B. M. (2025). Balance recovery and its link to vestibular agnosia in traumatic brain injury: a longitudinal behavioural and neuro-imaging study. Journal of Neurology. Retrieved from https://doi.org/10.1007/s00415-024-12876-2

  4. Ge, Y., Yin, J., Chen, C. (2024). An EEG-based framework for automated discrimination of conversion to Alzheimer’s disease in patients with amnestic mild cognitive impairment: an 18-month longitudinal study. Frontiers in Aging Neuroscience. Retrieved from https://doi.org/10.3389/fnagi.2024.1470836

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Marinda earned her Bachelor’s degree in Nursing from the University of Michigan. She writes about patient care, wellness, and preventive health for several health blogs. Marinda enjoys gardening, reading, and spending time with her family.