Investigating and validating the molecular mechanisms of lipid metabolism regulation in myasthenia gravis development based on single-cell, bulk transcriptomics, and RT-qPCR.
Abstract
Myasthenia gravis (MG) is a complex autoimmune neuromuscular disorder, and the role of lipid metabolism dysregulation in MG pathogenesis remains unclear. This study aimed to investigate the molecular mechanisms of lipid metabolism regulation in myasthenia gravis development by integrating single-cell and bulk transcriptomic data. This study analyzed bulk RNA sequencing data from the GSE85452 dataset (13 MG patients and 12 healthy controls) and single-cell RNA sequencing data from the GSE227835 dataset (10 MG patients and 10 healthy controls). Differential expression analysis was performed, and weighted gene co-expression network analysis (WGCNA) was conducted to identify disease-related modules. Key genes were screened through the intersection of differentially expressed genes (DEGs), WGCNA hub genes, and lipid metabolism-related genes. Functional enrichment analysis, protein‒protein interaction (PPI) network construction, immune infiltration analysis, and regulatory network analysis were performed. Single-cell analysis was used to characterize cellular heterogeneity and intercellular communication features. A nomogram prediction model was constructed and internally validated using leave-one-out cross-validation (LOOCV). Potential therapeutic compounds were identified through drug prediction and molecular docking analysis. Furthermore, key genes were validated by RT-qPCR in an independent cohort of 5 MG patients and 5 healthy controls. A total of 823 DEGs and 13…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 13 participants or records.
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