Towards finding the linkage between metabolic and age-related disorders using semantic gene data network analysis

Area of Science:

• Biochemistry and Molecular Biology
• Computational Biology and Bioinformatics
• Genetics and Genomics

Background:

• Metabolic disorders (MD) disrupt essential biochemical reactions involving carbohydrates, proteins, and lipids.
• These disruptions affect numerous inter-dependent metabolic pathways crucial for cellular function.
• The molecular connections between MD and age-related diseases (ARD) warrant investigation.

Purpose of the Study:

• To identify common pathways shared between metabolic disorders and age-related diseases.
• To construct and analyze protein-protein interaction (PPI) networks for MD and ARD.
• To propose a model hypothesis for the molecular mechanisms linking MD and ARD.

Main Methods:

• Creation of protein-protein interaction (PPI) networks using publicly available data for MD and ARD.
• Network analysis to identify common pathways and associated proteins/genes.
• Isolation and analysis of genes within common pathways for co-localization and shared domains.

Main Results:

• Identification of known MD-associated proteins within the constructed networks.
• Prediction of potential ARD-related genes and products involved in shared pathways.
• Isolation of genes from common pathways for further molecular analysis.

Conclusions:

• A model hypothesis was proposed based on linked interaction networks between MD and ARD.
• The study provides insights into the molecular mechanisms underlying diseases.
• Findings contribute to understanding disease relationships and potential therapeutic targets.