Title:Identification of MicroRNA Drug Targets for Alzheimer's and Diabetes Mellitus Using Network Medicine
Volume: 22
Issue: 7
Author(s): Ricardo Castillo-Velazquez, Julio E. Castaneda-Delgado, Mariana H. Garcia-Hernandez, Bruno Rivas-Santiago, Sofia Ruiz-Hernandez, Eyra Liliana Ortiz-Perez, Juan C. Lopez-Alvarenga, Gildardo Rivera and Edgar E. Lara-Ramirez*
Affiliation:
- Laboratorio de Biotecnología Farmacéutica, Centro de Biotecnología
Genómica, Instituto Politécnico Nacional, Reynosa, Tamaulipas, México
Keywords:
Network medicine, Alzheimer's disease, diabetes mellitus, microRNAs, drug design, metabolic disorder.
Abstract:
Introduction: Type 2 diabetes mellitus (T2D) is a known risk factor for developing
Alzheimer’s disease (AD). Recent research shows that both diseases share complex and related
pathophysiological processes. Network medicine approaches can help to elucidate common dysregulated
processes among different diseases, such as AD and T2D. Thus, the aim of this work
was to determine differentially expressed genes (DEGs) in AD and T2D and to apply a network
medicine approach to identify the microRNAs (miRNAs) involved in the AD-T2D association.
Methods: Gene expression microarray data sets consisting of 384 control samples and 399 samples
belonging to AD and T2D disease were analyzed to obtain DEGs shared by both diseases; the
miRNAs associated with these DEGs were predicted using a network medicine approach. Finally,
potential small molecules targeting these potentially deregulated miRNAs were identified.
Results: AD and T2D shared a subset of 82 downregulated DEGs. These genes were significantly
associated (p < 0.01) with the ontology terms of chemical synaptic deregulation. DEGs were associated
with 12 miRNAs expressed in specific tissues for AD and T2D. Such miRNAs were also
primarily associated with the ontology terms related to synaptic deregulation and cancer, and
AKT signaling pathways. Steroid anti-inflammatory drugs, antineoplastics, and glucose metabolites
were predicted to be potential regulators of the 12 shared miRNAs.
Discussion: The network medicine approach integrating DEGs and miRNAs enabled the identification
of shared, potentially deregulated biological processes and pathways underlying the pathophysiology
of AD and T2D. These common molecular mechanisms were also linked to drugs currently
used in clinical practice, suggesting that this strategy may inform future drug repurposing efforts.
Nonetheless, further in-depth biological validation is required to confirm these findings.
Conclusion: Network medicine allowed identifying 12 miRNAs involved in the AD-T2D association,
and these could be drug targets for the design of new treatments; however, the identified miRNAs
need further experimental confirmation.
