|
Abstract
Aim: Metabolic syndrome
(MetS) is a clustering of risk factors that increases susceptibility to type
2 diabetes and cardiovascular disease. This study aimed to perform a
comprehensive bioinformatic analysis of genomic data to elucidate molecular
pathways underlying MetS.
Methodology: GWAS data from
previous MetS studies were analyzed using TargetScan, miRTarBase, Reactome
Pathways, KEGG, protein–protein interaction (PPI) networks, and Gene Ontology
(GO) mapping. Integration of these datasets identified key miRNAs, metabolic
pathways, biological processes, and molecular activities associated with
MetS.
Results: hsa-miR-126 was
markedly enriched and strongly correlated with MetS. Pathway analysis
highlighted cholesterol metabolism (p <0.05) and plasma lipoprotein
remodeling (p <0.05) as significant contributors. GO analysis revealed
triglyceride homeostasis (p <0.05) and very-low-density lipoprotein
particle remodeling (p <0.05) as a key biological processes. Metabolomic
analysis established strong links between triacylglycerol and glycerol
metabolism. Lipid transport and metabolism emerged as central to MetS pathogenesis,
with notable enrichments for high-density lipoprotein particles (p <0.05)
and phosphatidylcholine-sterol O-acyltransferase activator activity (p
<0.05).
Interpretation: This comprehensive
analysis indicates that dysregulation of lipid metabolism is a major pathway
in MetS, with specific miRNAs functioning as critical regulatory molecules.
These insights suggest potential therapeutic strategies targeting
miRNA-mediated regulation of lipid metabolism.
Key
words:
Cholesterol homeostasis, Lipid metabolism, Lipoprotein remodeling, Metabolic
syndrome, miRNA regulation
|