Identification of Circadian Rhythm-Associated Genes and Therapeutic Targets in Myopia with Dynamics Simulation: A Multiomics Study Using Machine Learning Algorithms and Mendelian Randomization

The prevalence of myopia is rising, with genetic and environmental factors playing key roles. Disruptions in circadian melatonin rhythms are also linked to refractive errors, though exact mechanisms remain unclear. Differential expression analysis on the GSE136701 dataset identified circadian-related genes. GSEA, GO, and KEGG analyses revealed key genes. To identify key genes, seven machine learning models were employed, and their performance was evaluated using ROC curve analysis. The correlation genes were further assessed. Concurrently, we performed a comprehensive analysis of immune infiltration and correlation pertaining to these pivotal genes. Additionally, potential target drugs were screened using the DSigDB database, and both protein-protein and molecular docking analyses were performed. To investigate the causal relationship between target genes and myopia, two-sample MR analysis was conducted. Finally, single-cell annotation and cell-cell communication analyses were carried out on the GSE235684 dataset. We preliminarily identified four circadian rhythm-related key genes: UTS2, BTBD9, S100A3, and LGALS9. We identified 8-Bromo-cAMP as the small molecule exhibiting the highest binding efficiency to BTBD9 and UTS2, with a docking binding energy of -37.5 kcal/mol for the BTBD9-UTS2 complex and -6.8 kcal/mol for the complex-small molecule interaction. The dynamics simulation analysis has further corroborated the dynamic stability of the UTS2-BTBD9 complex binding with 8-bromo-cAMP. Additionally, Mendelian randomization analysis revealed a significant association between UTS2 and myopia, with an inverse variance weighted (IVW) P value of 0.013 (OR 0.532, 95% CI 0.323-0.877).