Integrative Bulk and Single-Cell Transcriptome Analyses Reveal Mitochondrial Metabolism-Related Biomarkers in IgA Nephropathy with Experimental Validation

整合的批量和单细胞转录组分析揭示了IgA肾病中与线粒体代谢相关的生物标志物,并通过实验验证了这些标志物

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Abstract

BACKGROUND: Abnormalities in mitochondrial metabolism have been linked to renal disease; however, the precise mechanism underlying its involvement in immunoglobulin A nephropathy (IgAN) remains incompletely elucidated. The objective of this study was to ascertain the impact of biomarkers associated with mitochondrial metabolism on IgAN. METHODS: The data related to IgAN were obtained from public databases. The mitochondrial metabolism-related biomarkers in IgAN were identified through various bioinformatics approaches, including machine learning algorithms and expression validation. Subsequently, enrichment analysis and immune microenvironment analysis were conducted to explore biomarkers' potential mechanisms in IgAN. Additionally, single-cell RNA sequencing (scRNA-seq) analysis was performed to identify key cell types and clarify the expression dynamics of biomarkers. The expression levels of the biomarkers were validated via reverse transcription quantitative PCR (RT-qPCR). RESULTS: CYP27B1 and PCK1 were identified as biomarkers for IgAN. Notably, CYP27B1 and PCK1 were commonly enriched in the pathways of "fatty acid metabolism" and "oxidative phosphorylation". Moreover, CYP27B1 displayed the highest positive correlation with neutrophils, whereas PCK1 exhibited the highest negative correlation with activated NK cells. Besides, scRNA-seq analysis identified proximal tubular cells (PTCs) as the key cell type. The expression of CYP27B1 remained unchanged throughout PTCs' differentiation, while the expression of PCK1 gradually increased initially and then decreased in the middle to later stages. Moreover, RT-qPCR analysis revealed a significant reduction in the expression levels of CYP27B1 and PCK1 in the IgAN group (P < 0.001), aligning with the predictions obtained from the database. CONCLUSION: This study integrated bulk and scRNA-seq analyses to pinpoint CYP27B1 and PCK1 as biomarkers, with PTCs identified as key cells, providing novel diagnostic approaches for IgAN.

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