Mass Spectrometry With Data-Independent Acquisition for the Identification of Target Antigens in Membranous Nephropathy

Abstract

Rationale & objective: In recent years, the strategy of using laser capture microdissection and mass spectrometry (LCM/MS) has expanded the landscape of antigens associated with membranous nephropathy (MN). Specific associations with phenotypes, diseases, and sometimes reversible triggers led to an antigen-based classification of MN, informing precision medicine and highlighting the potential value of routine use of proteomics in classifying MN. This study reproduces and further improves the original LCM/MS for antigen detection in MN.

Study design: Retrospective cohort study using residual material from kidney biopsies.

Setting & participants: We applied LCM/MS to kidney biopsy specimens from 64 individuals, including 31 healthy controls; 5 with M-type phospholipase A₂ receptor (PLA₂R)-associated MN; 23 with PLA₂R-negative MN; and 5 individuals with other glomerular diseases.

Predictor: Proteomic analysis of microdissected glomeruli.

Outcome: Protein abundance and C3 fragments in PLA₂R-MN specimens versus controls; identification of target antigens in PLA₂R-negative MN.

Analytical approach: The technique of LCM/MS was expanded by integrating a data-independent acquisition (DIA) approach to enable the identification and quantification of peptides of varying abundance.

Results: We observed significant enrichment in PLA₂R, IgG4, and complement proteins, providing molecular evidence for complement activation in glomeruli from patients with PLA₂R-MN. Compared with conventional data-dependent acquisition (DDA), DIA increased the number of glomerular proteins (∼3,800 vs ∼1,200) identified in healthy glomeruli, allowed the detection of all known antigens except NELL1 in normal glomeruli, and increased the detection rate of antigens from 46% to 83% in PLA₂R-negative MN.

Limitations: Retrospective design; sample size; no identification of novel antigens.

Conclusions: An integrative approach combining LCM/MS and DIA enabled identification of more target antigens than LCM/MS with DDA, potentially informing our understanding of disease mechanisms in MN.

Plain-language summary: Membranous nephropathy is an autoimmune kidney disease characterized by circulating autoantibodies that recognize antigens in podocytes or in the glomerular basement membrane. To date, more than 10 different antigens have been identified, with specific associations with various etiologies and potential impact on management. In this study, proteomic analyses were implemented on glomeruli microdissected from kidney biopsies in patients with membranous nephropathy and appropriate controls. The original technique of proteomic analysis developed by Sethi and coworkers was expanded by applying a specific and more sensitive mass spectrometry method (data-independent acquisition) combined with bioinformatics analysis. We showed that this approach is a powerful tool to detect target antigens, and it may provide insights into disease mechanisms, with the potential to inform clinical diagnosis and classification of membranous nephropathy.

Keywords: Autoimmunity; computational analysis; kidney disease; membranous nephropathy; proteomics.