Identification of Renal Transcripts Associated with Kidney Function and Prognosis in ANCA-Associated Vasculitis

Key Points Large-scale kidney transcriptomics identifies a 12-gene signature, including CLU and C3 , predicting kidney failure in ANCA-associated vasculitis. This molecular signature outperformed Berden, renal risk score, and ANCA kidney risk score clinicopathologic classifications. ANCA-associated vasculitis with GN kidneys show broad immune dysregulation, notably in complement, TGF β , and immunometabolism pathways. Background ANCA-associated vasculitis with GN (AAV-GN) frequently progresses to kidney failure. However, tools for risk stratification of kidney outcomes remain limited. Existing approaches inadequately capture the molecular complexity underlying kidney injury, despite its potential value to tailor therapeutic management. We explored whether kidney transcriptomics could identify molecular signatures linked to kidney outcomes. Methods We included 199 patients with AAV-GN from two multicenter biobanks, and 23 controls. Kidney biopsies were profiled using NanoString nCounter to assess the expression of 750 immune-related genes. We conducted differential gene expression analysis, pathway enrichment analysis, and immune cell infiltration estimation to explore associations with kidney function and survival. A 12-gene prognostic signature was developed through least absolute shrinkage and selection operator–penalized Cox regression and compared with established histologic classifications (Berden classification, renal risk score, and ANCA kidney risk score) with robust internal validation. Results AAV-GN demonstrated extensive immune dysregulation with 150 differentially expressed genes versus controls, highlighting complement activation, immune cell recruitment and activation, TGF β signaling, and immunometabolism pathways. Immune cell infiltration was marked by increased macrophages, dendritic cells, neutrophils, and T-cell subsets, reflecting broad immune activation. Initial eGFR correlated with the expression of 319 genes. A 12-gene signature ( CLU , C3 , LTF , FLT1 , PLCG2 , FES , PRKCD , TXNIP , SLC7A5 , PTEN , NRBF2 , and NFATC1 ) was significantly more strongly associated with kidney survival than were established histologic classifications (adjusted P value < 0.0001). Both high expression and low expression of several immune pathways (especially lymphocyte trafficking) were associated with better outcomes compared with intermediate expression. Conclusions Transcriptomic analysis of kidney biopsies in AAV-GN identified 150 differentially expressed immune-related genes and led to the development of a 12-gene signature that correlated strongly with kidney survival, outperforming established histologic classifications.