Single-cell transcriptomic analysis reveals the T lymphocyte microenvironment and identifies HOPX as a hub gene in membranous nephropathy.

BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex deposition and progressive renal function impairment. Although studies have demonstrated that dysregulation of adaptive immunity, primarily T lymphocyte dysregulation, plays a significant role in its pathogenesis through heterogeneity, the understanding of immune cell subpopulations and key immune response genes during the pathological process of MN remains incomplete. METHODS: This study integrated single-cell RNA sequencing (scRNA-seq) data from GSE193512 with bulk RNA sequencing (bulk RNA-seq) data from GSE142025. Through differential expression analysis, high-dimensional weighted gene co-expression network analysis (hdWGCNA), pseudotime trajectory inference, and cell-cell communication analysis, the composition of the immune cell microenvironment and gene regulatory changes were systematically analyzed. Meanwhile, four machine learning algorithms were employed in combination to screen for hub genes. We collected clinical blood samples from 53 MN patients and healthy controls, and performed experimental validation via qRT-PCR and flow cytometry. RESULTS: The results indicated significant expansion of peripheral blood CD8-positive T cells and natural killer cells in PLA2R-positive patients, and the functional states of these cells were markedly altered in non-remission MN cases. In the scRNA-seq data, ten key module genes within T cells, including GNLY, NKG7, GZMB, KLRD1, HOPX, and ZEB2, were identified using the hdWGCNA algorithm and the combined screening of four machine learning algorithms. Multi-algorithm integration consistently identified HOPX as a core hub gene. HOPX expression was significantly upregulated in the peripheral blood of MN patients, and qRT-PCR and ROC curve analysis confirmed its diagnostic performance. Cell-cell communication analysis revealed that T cells and NK cells form an active interaction network through signaling pathways such as MIF and GZMA, suggesting a central role for these pathways in the immune response. CONCLUSION: In summary, this study presents a high-resolution single-cell sequencing-based immune cell landscape of MN and establishes HOPX as a potential novel diagnostic biomarker for the first time. It elucidates the crucial roles of lymphocyte dysfunction, metabolic remodeling, and immune exhaustion in disease progression. These findings not only deepen the understanding of the immunopathogenesis of MN but also provide important theoretical basis and candidate targets for developing targeted immunotherapeutic strategies.