Systems biology-driven analysis of obesity-associated genes with transcript mapping and post-translational...

Area of Science:

• Genetics
• Molecular Biology
• Bioinformatics

Background:

• Morbid obesity is influenced by genetic variations, but their protein-level functional consequences, especially post-translational modifications (PTMs), are not well understood.
• Genome-wide association studies have identified numerous obesity-related genetic loci, yet the role of PTMs and their interactions remains unclear.

Purpose of the Study:

• To investigate the functional impact of genetic variations on proteins involved in morbid obesity.
• To explore the role of post-translational modifications (PTMs) in obesity-related genetic pathways.
• To identify key regulatory protein hubs and potential therapeutic targets.

Main Methods:

• Computationally identified gene candidates and single nucleotide polymorphisms (SNPs) from dbSNP.
• Mapped mutations using SnpEff and correlated gene/transcript IDs with UniProtKB accessions.
• Integrated PTM data from multiple databases and constructed a protein-PTM-disease interaction network in Cytoscape.

Main Results:

• Retrieved 66 obesity-related genes with 3581 mutations, noting excess missense and frameshift variants in key genes like LEPR and MC4R.
• Identified ALMS1, POMC, and LEPR as major topological hubs in the interaction network.
• Network analysis revealed PTM hotspots (phosphoserine, N-glycosylation) where mutations converge, potentially disrupting receptor signaling and contributing to obesity.

Conclusions:

• Linked genetic mutations in morbid obesity to protein regulatory pathways affected by PTM alterations.
• Identified specific topological bottlenecks with high centrality as targets for precision medicine initiatives in obesity.