Multi-omics and AI integration in autoimmune kidney diseases: from molecular signatures to precision immunotherapy

Autoimmune-mediated kidney diseases arise when alterations in the immune system (through circulating autoantibodies, immune complexes, or aberrant immune responses) drive glomerular inflammation, causing progressive kidney damage and potential end-stage kidney disease. These include renal manifestations of systemic autoimmune diseases such as lupus nephritis, ANCA-associated vasculitis, anti-GBM disease, and mixed cryoglobulinemia, as well as renal-limited conditions such as IgA nephropathy, membranous nephropathy, C3 glomerulopathy (C3GN), primary FSGS, and minimal change disease.Diagnosis typically relies on kidney biopsy, although some conditions, such as membranous nephropathy, have highly specific autoantibodies that may enable non-invasive diagnosis. Current clinical markers such as proteinuria remain imperfect predictors of disease activity and treatment response, while standard therapies largely depend on toxic, non-specific immunosuppressive regimens with suboptimal response rates and significant side effects. There remains a clear and urgent need for novel diagnostic and therapeutic approaches with direct patient care impact.The convergence of high-dimensional molecular profiling and computational analysis is fundamentally reshaping our understanding of immune dysregulation in glomerular disease. Single-cell transcriptomics, spatial proteomics, and metabolomics are revealing the cellular and molecular architecture of these conditions with unprecedented resolution, enabling mechanistic discoveries, robust biomarker identification, and the definition of novel therapeutic targets. By bridging basic science and clinical translation, multi-omics approaches offer a powerful framework for patient stratification and precision immunotherapy.Complementing these molecular advances, artificial intelligence is emerging as a transformative force in renal immunopathology. AI-driven analysis of biopsy histology, integrated with autoantibody profiles and flow cytometry data, is accelerating immune phenotyping and enabling machine learning-based prediction of immunosuppression response.Central to both paradigms is a renewed focus on the cellular players driving glomerular pathology. The roles of Tfh, Th17, and Treg cells, alongside innate effectors such as macrophages and NK cells, and their crosstalk with resident renal cells, are increasingly recognised as critical determinants of disease initiation and progression.This Research Topic welcomes translational and interdisciplinary contributions addressing nephroimmunology, diagnostic and therapeutic limitations across the spectrum of autoimmune-mediated kidney diseases. We invite articles on the following themes (but not limited to):- Immune mechanisms underlying lupus nephritis, ANCA-associated vasculitis, anti-GBM disease, mixed cryoglobulinemia, IgA nephropathy, membranous nephropathy, C3GN, primary FSGS, and minimal change disease- Diagnostic markers: from tissue biomarkers (biopsy) to circulating non-invasive biomarkers and autoantibodies their relation to immune dysregulation in autoimmune kidney disorders- Single-cell and spatial multi-omics profiling of glomerular immune pathology- AI-based analysis of renal biopsy images and histopathological pattern recognition related to immunological features- Integration of omics, flow cytometry, and autoantibody data for immune phenotyping- Crosstalk between T/B cell subsets, innate immune cells, and renal resident cells- Immunotherapies and novel treatments across autoimmune-mediated kidney diseases- Translational studies linking immune molecular signatures to patient outcomes for precision medicineAccepted article formats include original research articles, FAIR² data articles, reviews, methods papers, and data-driven perspectives. COI note: Dr. MAPV has received honoraria for participation in advisory boards from Novartis, Sobi and CSL Vifor. Received speaker honoraria and fees for educational activities from Boehringer Ingelheim, AstraZeneca and Bayer. These activities are unrelated to the editorial responsibilities associated with this Research Topic and have not influenced the preparation of the proposal or the editorial process. Topic editors: Dawn Caster, David Powell, Miguel Angel Pérez Valdivia Source: https://www.frontiersin.org/research-topics/80043/multi-omics-and-ai-integration-in-autoimmune-kidney-diseases-from-molecular-signatures-to-precision-immunotherapy