Introduction ANCA-associated vasculitis with glomerulonephritis (AAV-GN) is classically considered pauci-immune, yet complement activation is a central pathogenic mechanism. Whether intrarenal complement-related transcriptional programs are reflected by conventional serum or immunofluorescence markers, and whether they are clinically informative, remains unclear. Methods In 369 AAV-GN patients from two independent retrospective cohorts, complement was assessed across circulating, histopathological, and transcriptomic layers (serum C3/C4, glomerular C1q/C3 deposition, targeted kidney transcriptomics). Predefined classical and alternative pathway–related expression scores were derived from intrarenal gene expression. Associations with severity and outcomes were evaluated using multivariable Cox models. Public spatial transcriptomic datasets provided validation and localization. Results Below-normal serum C3/C4 levels were uncommon. Low serum C3, but not C4, was associated with more severe kidney involvement, kidney failure (adjusted HR 2.0 [1.1–3.7]) and mortality (adjusted HR 2.3 [1.3–4.0]). Glomerular C3 (47%) and C1q (11%) deposition both identified more severe pathology and adverse outcomes. Compared with controls, AAV-GN kidneys showed increased complement-related expression involving classical pathway components, proximal alternative pathway genes, C3 , C5AR1 , and regulatory transcripts, only weakly concordant with serum or deposition markers. Low alternative pathway–related expression was independently associated with better kidney (adjusted HR 0.3 [0.1–0.7]) and overall (adjusted HR 0.4 [0.2–0.9]) survival. Spatial transcriptomics validated these signatures and suggested contributions from both immune and resident kidney compartments. Conclusion AAV-GN displays a reproducible intrarenal complement-related transcriptional program, only weakly captured by serum levels or routine immunofluorescence, associated with renal severity and outcomes. These findings support prospective studies integrating tissue complement transcriptomics for stratification and therapeutic hypothesis generation.
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Brilland et al. (2026) studied this question.
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