Molecular Differences in Glomerular Compartment to Distinguish Immunoglobulin A Nephropathy and Lupus Nephritis

Background: Immunoglobulin A nephropathy (IgAN) and lupus nephritis (LN) are the most prevalent primary and secondary glomerular diseases, respectively, with several similarities in clinical presentations. Common pathogenic mechanisms in IgAN and LN have been well investigated by previous studies. However, the manifestation mechanism of these two independent diseases carrying distinct immunofluorescent pathological features is still unknown considering the similarities between them. Therefore, differences in pathogenic mechanisms between IgAN and LN were compared in this study. Methods: R packages were used for processing the glomerular gene expression datasets acquired from the Gene Expression Omnibus (GEO) database. Least Absolute Selection and Shrinkage Operator (LASSO) and multivariate logistic regression analysis were used to construct models predicting IgAN and LN. Cibersort was used to process the immune cell infiltration analysis. Immunochemistry was used to validate the findings by bioinformatics analysis. Results: In the predicting models based on differentially expressed genes (DEG) and weighted correlation network analysis (WGCNA), retinoic acid receptor gamma (RARG) and prolactin releasing hormone (PRLH) were independent risk factors for IgAN, and HECT domain and RCC1-like domain-containing protein 5 (HERC5) and interferon stimulated exonuclease gene 20 (ISG20) were independent risk factors for LN. Gene Ontology (GO) analysis revealed that DEGs mostly correlated to IgAN were enriched in ligandreceptor activity-induced cellular growth and development, while DEGs mostly correlated to LN were enriched in nucleic acid/ nucleotide binding-induced type I interferon-related activity and response to virus infection. Immune infiltration analysis showed CD4+ T-cells and M2 macrophage abundance in the glomerular compartment in IgAN and LN, respectively. Immunochemistry validated the predicting models for IgAN and LN and revealed different expression patterns of RARG, PRLH, HERC5, and ISG20. Conclusion: We investigated key differences in the pathogenesis between IgAN and LN and provided validated predicting models to distinguish IgAN and LN. RARG and PRLH, HERC5 and ISG20 might play an essential role in the formation of IgAN and LN, respectively.