The combined analysis of metabolomics and transcriptomics revealed the metabolic changes of kidney tissue in mice with IgA nephropathy

Abstract

Background: Immunoglobulin A nephropathy (IgAN) is a globally prevalent primary chronic glomerulopathy and a leading cause of end-stage renal disease. Despite its significance, the underlying mechanisms of IgAN remain poorly understood. This study aims to investigate these mechanisms by integrating metabolomics and transcriptomics approaches.

Methods: We established an IgAN mouse model and conducted pathological analysis using hematoxylin and eosin (HE) staining and immunofluorescent staining. Renal function was assessed by enzyme-linked immunosorbent assay (ELISA) and biochemical assays. Mass spectrometry-based metabolomics was employed to analyze differentially abundant metabolites (DAMs), while transcriptomics was employed to analyze differentially expressed genes (DEGs).

Results: An IgAN mouse model was successfully established. HE staining revealed abnormal proliferation of glomerular mesangial cells, while immunofluorescence staining indicated excessive deposition in the glomerular region. ELISA results showed that IgA levels were significantly elevated in the serum of IgAN mice. Biochemical tests showed that blood creatinine (CRE), blood urea nitrogen (BUN) and urine protein levels were significantly elevated in IgAN mice. Metabolomics and transcriptomics analyses identified 184 DAMs and 482 DEGs in the kidney tissues of normal and IgAN mice, respectively. Notably, combined analyses revealed that both DAMs and DEGs were enriched in 3 key pathways: bile secretion, pyruvate metabolism, and cholesterol metabolism.

Conclusion: In this article, we identified 3 critical pathways-bile secretion, pyruvate metabolism, and cholesterol metabolism-through a comprehensive analysis of metabolomics and transcriptomics. These pathways may play an important role in affecting metabolic changes in the renal tissue of IgAN mice and provide fresh insights into the pathogenesis of IgAN.

Keywords: IgAN; Metabolomics; Transcriptomics.