mRNA profiling in immune mediated necrotizing myopathy

Background: The therapeutic regimen of immune-mediated necrotizing myopathy (IMNM), a category of immune-related myopathies featuring progressive proximal muscle weakness and extremely high level of serum creatine kinase, remains a formidable barrier for clinicians. The proposed study intended to investigate new diagnostic biomarkers based on high-throughput sequencing data of IMNM and generate novel IMNM management strategies by bioinformatics technology. Methods: Eighteen IMNM patients were synthesized in a local sequencing cohort (high-throughput sequencing data) with Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression analysis to pinpoint robust IMNM-related differentially expressed genes (DEGs). The definitive feature genes were categorized by employing the protein-protein interaction (PPI) network, Least Absolute Shrinkage Selection Operator (LASSO), and support vector machine recursive feature elimination (SVM-RFE), and their sample discriminatory utility was appraised by obtaining the area under the curve (AUC) of the receiver operating curve (ROC) curve. The expression difference of key genes was verified by quantitative real-time polymerase chain reaction (qRT-PCR). Enrichment analysis of predefined gene sets disclosed the hidden functions of diagnostic DEGs. The 28 immune cell abundance patterns in the IMNM cohort were measured using single-sample gene set enrichment analysis (ssGSEA). Results: We recognized 193 genes that were aberrantly upregulated in the IMNM population and were firmly affiliated with immune-inflammatory responses, regulation of skeletal and cardiac muscle contraction and lipidprotein metabolism. LTK, MYBPH, and MYL4 were authenticated as diagnostic markers for IMNM (all AUC = 1.00), and functional enrichment analysis highlighted that these genes were notably integrated with immune-inflammatory response, autophagy-lysosome pathway and myofiber differentiation and regeneration. Ultimately, ssGSEA revealed a pronounced immune cell infiltrative microenvironment in the IMNM population. The results revealed the most significant relationship among CD4 T cells, CD8 T cells, macrophages, natural killer cells, T helper cells, Th17 cells and dendritic cells. Conclusion: LTK, MYBPH, and MYL4 might be served as diagnostic molecules for IMNM and possibly yield innovative insights into the mechanisms of progression and therapeutic options for IMNM in the future.