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Deciphering molecular bridges: Unveiling the interplay between metabolic syndrome and Alzheimer's disease through a systems biology approach and drug repurposing.
Azizan, Zahra; Zali, Hakimeh; Mirmotalebisohi, Seyed Amir; Bazrgar, Maryam; Ahmadiani, Abolhassan.
Afiliação
  • Azizan Z; School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Zali H; Department of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Mirmotalebisohi SA; Student Research Committee, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Bazrgar M; Cellular and Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Ahmadiani A; Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
PLoS One ; 19(5): e0304410, 2024.
Article em En | MEDLINE | ID: mdl-38809924
ABSTRACT
The association between Alzheimer's disease and metabolic disorders as significant risk factors is widely acknowledged. However, the intricate molecular mechanism intertwining these conditions remains elusive. To address this knowledge gap, we conducted a thorough investigation using a bioinformatics method to illuminate the molecular connections and pathways that provide novel perspectives on these disorders' pathological and clinical features. Microarray datasets (GSE5281, GSE122063) from the Gene Expression Omnibus (GEO) database facilitated the way to identify genes with differential expression in Alzheimer's disease (141 genes). Leveraging CoreMine, CTD, and Gene Card databases, we extracted genes associated with metabolic conditions, including hypertension, non-alcoholic fatty liver disease, and diabetes. Subsequent analysis uncovered overlapping genes implicated in metabolic conditions and Alzheimer's disease, revealing shared molecular links. We utilized String and HIPPIE databases to visualize these shared genes' protein-protein interactions (PPI) and constructed a PPI network using Cytoscape and MCODE plugin. SPP1, CD44, IGF1, and FLT1 were identified as crucial molecules in the main cluster of Alzheimer's disease and metabolic syndrome. Enrichment analysis by the DAVID dataset was employed and highlighted the SPP1 as a novel target, with its receptor CD44 playing a significant role in the inflammatory cascade and disruption of insulin signaling, contributing to the neurodegenerative aspects of Alzheimer's disease. ECM-receptor interactions, focal adhesion, and the PI3K/Akt pathways may all mediate these effects. Additionally, we investigated potential medications by repurposing the molecular links using the DGIdb database, revealing Tacrolimus and Calcitonin as promising candidates, particularly since they possess binding sites on the SPP1 molecule. In conclusion, our study unveils crucial molecular bridges between metabolic syndrome and AD, providing insights into their pathophysiology for therapeutic interventions.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome Metabólica / Biologia de Sistemas / Reposicionamento de Medicamentos / Doença de Alzheimer / Mapas de Interação de Proteínas Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Irã

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Síndrome Metabólica / Biologia de Sistemas / Reposicionamento de Medicamentos / Doença de Alzheimer / Mapas de Interação de Proteínas Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Irã