How will artificial intelligence and bioinformatics change our understanding of IgA Nephropathy in the next decade?
Seminars in Immunopathology, vol. 43, pp. 739–752
Abstract
IgA nephropathy (IgAN) is the most common glomerulonephritis. It is characterized by the deposition of immune complexes containing immunoglobulin A (IgA) in the kidney's glomeruli, triggering an inflammatory process. In many patients, the disease has a progressive course, eventually leading to end-stage kidney disease. The current understanding of IgAN's pathophysiology is incomplete, with the involvement of several potential players, including the mucosal immune system, the complement system, and the microbiome. Dissecting this complex pathophysiology requires an integrated analysis across molecular, cellular, and organ scales. Such data can be obtained by employing emerging technologies, including single-cell sequencing, next-generation sequencing, proteomics, and complex imaging approaches. These techniques generate complex "big data," requiring advanced computational methods for their analyses and interpretation. Here, we introduce such methods, focusing on the broad areas of bioinformatics and artificial intelligence and discuss how they can advance our understanding of IgAN and ultimately improve patient care. The close integration of advanced experimental and computational technologies with medical and clinical expertise is essential to improve our understanding of human diseases. We argue that IgAN is a paradigmatic disease to demonstrate the value of such a multidisciplinary approach.
Authors 4
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Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
University Hospital RWTH Aachen, Institute of Pathology, Aachen, Germany
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Heidelberg University · University Hospital Heidelberg
Affiliation as printed
Faculty of Medicine, Heidelberg University, Heidelberg, Germany
Institute for Computational Biomedicine, Heidelberg University Hospital, Bioquant, Heidelberg, Germany
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Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
Department of Nephrology and Immunology, University Hospital RWTH Aachen, Aachen, Germany. pboor@ukaachen.de
University Hospital RWTH Aachen, Institute of Pathology, Aachen, Germany. pboor@ukaachen.de
University Hospital RWTH Aachen, Institute of Pathology, Aachen, Germany
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Julio Sáez-Rodríguez corresponding Aachen Faculty of Medicine Joint Research Centre for Computational Biomedicine (JRC-COMBINE)
Heidelberg University · University Hospital Heidelberg · European Molecular Biology Laboratory · European Molecular Biology Laboratory · RWTH Aachen University
Affiliation as printed
Faculty of Medicine, Heidelberg University, Heidelberg, Germany. julio.saez@uni-heidelberg.de
Faculty of Medicine, Joint Research Centre for Computational Biomedicine (JRC-COMBINE), 52074, RWTH Aachen University, Aachen, Germany. julio.saez@uni-heidelberg.de
Institute for Computational Biomedicine, Heidelberg University Hospital, Bioquant, Heidelberg, Germany. julio.saez@uni-heidelberg.de
Molecular Medicine Partnership Unit, European Molecular Biology Laboratory and Heidelberg University, Heidelberg, Germany. julio.saez@uni-heidelberg.de
Faculty of Medicine, Heidelberg University, Heidelberg, Germany
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