Molecular Characterization
of Polycystic Ovary Syndrome: A Comprehensive Computational Genomics Approach
Kavya J., Molakala Pavan Kumar Reddy, Adiga Usha, Vasishta Sampara and Govardhan
T.
Res. J. Biotech.; Vol. 20(12); 138-147;
doi: https://doi.org/10.25303/2012rjbt1380147; (2025)
Abstract
Polycystic Ovary Syndrome (PCOS) represents a complex endocrine disorder characterized
by significant molecular heterogeneity. This comprehensive computational genomics
study investigated the molecular mechanisms underlying PCOS by analyzing the top
30 genes from the DisGeNET database. Advanced bioinformatics techniques were employed
to map genetic interactions across multiple molecular domains including biological
processes, cellular components and molecular functions.
The research revealed intricate genetic pathways significantly associated with PCOS
pathogenesis. Metabolomic analysis highlighted androstenedione and testosterone
as critical metabolites, suggesting complex hormonal regulatory mechanisms. Statistical
analysis of WikiPathways_2024_Human and HMDB_Metabolites databases uncovered multiple
statistically significant molecular interactions. The Kisspeptin Receptor System
and Primary Ovarian Insufficiency pathways emerged as particularly relevant, providing
insights into reproductive and metabolic disruptions characteristic of PCOS. Computational
modeling demonstrated the syndrome's multisystemic nature, challenging traditional
conceptualizations. The research provides a comprehensive molecular framework that
emphasizes PCOS as a dynamic, complex genetic condition with potential implications.
