Comprehensive Analysis of Uric Acid and Myasthenia Gravis: IGF1R as a Protective Factor and Potential Therapeutic Target

Abstract

Background: Previous studies have suggested that oxidative stress can significantly damage acetylcholine receptors (AChRs), which are implicated in the pathogenesis of myasthenia gravis (MG). Uric acid (UA), a scavenger of peroxynitrite and a natural antioxidant, plays a crucial role in eliminating free radicals in the bloodstream. However, the relationship between UA and MG, as well as the underlying mechanisms, remains insufficiently explored.

Methods: A meta-analysis was conducted to evaluate the clinical correlation between UA and MG. Subsequently, Mendelian randomization (MR) and bioinformatics analyses were employed to identify the key protein IGF1R. Public datasets, such as TCGA and GEO, along with patient data from our clinical center, were used for a comprehensive analysis of the relationship between IGF1R and UA in MG patients. Additionally, virtual screening and molecular docking were performed to identify small molecules that target IGF1R as potential therapeutic agents for MG.

Results: The meta-analysis revealed a significant association between low UA levels and MG (OR -48.46 [95% CI -63.26, -33.65], p < 0.00001). The two-sample MR analysis indicated a genetic relationship between UA and MG (p = 0.024; p = 0.036). The FUMA analysis and enrichment analysis identified IGF1R as a key protein likely involved in this relationship. Using the thymoma dataset from the TCGA database, we analyzed IGF1R expression in the MG and non-MG groups and found that IGF1R expression was lower in MG patients and was associated with a poor prognosis (p < 0.05). Single-cell RNA-seq data from the GEO database further supported the association between low IGF1R expression and MG, as well as the occurrence of crisis (p < 0.05). Additionally, data from MG patients treated at our center showed that IGF1R expression correlated with UA levels and that higher IGF1R expression was associated with milder clinical phenotypes (ocular phenotypes). Through a virtual screen and molecular docking of small molecules in the DrugBank database, we identified several potential small-molecule drugs that may target IGF1R to treat MG.

Conclusions: Our study revealed an association between low UA levels and MG and subsequently showed that low IGF1R expression is associated with the onset, severity, and poor prognosis of MG. We also explored the molecular mechanisms underlying the protective role of IGF1R in MG and identified potential drugs for treating MG.

Keywords: bioinformatics analysis; mendelian randomization; molecular docking; myasthenia gravis; type 1 insulin‐like growth factor receptor; uric acid.