ReviewSeminars in immunopathology2021
How will artificial intelligence and bioinformatics change our understanding of IgA Nephropathy in the next decade?
Review in Seminars in immunopathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 27 citations in OpenAlex.
- Kidney Fibrosis In Vitro and In Vivo Models: Path Toward Physiologically Relevant Humanized Models.Advanced healthcare materials · 2025Review
- Operational greenhouse-gas emissions of deep learning in digital pathology: a modelling study.The Lancet. Digital health · 2024Article
- Evaluating Progression Risk in Patients With Immunoglobulin A Nephropathy.Kidney international reports · 2023Review
- Long-term follow-up of IgA nephropathy: clinicopathological features and predictors of outcomes.Clinical kidney journal · 2023Article
- Extending the landscape of omics technologies by pathomics.NPJ systems biology and applications · 2023Article
- Validation of two IgA nephropathy risk-prediction tools using a cohort with a long follow-up.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2023Article
- Next-Generation Morphometry for pathomics-data mining in histopathology.Nature communications · 2023Article
- Integration of artificial intelligence and multi-omics in kidney diseases.Fundamental research · 2023Review
- APOC1 exacerbates renal fibrosis through the activation of the NF-κB signaling pathway in IgAN.Frontiers in pharmacology · 2023Article
- Advances in proteomic profiling of pediatric kidney diseases.Pediatric nephrology (Berlin, Germany) · 2022Review
- Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects.Journal of clinical medicine · 2022Review
- Precision medicine for the treatment of glomerulonephritis: a bold goal but not yet a transformative achievement.Clinical kidney journal · 2022Review
- Review
- Common molecular mechanism and immune infiltration patterns of thoracic and abdominal aortic aneurysms.Frontiers in immunology · 2022Article
- IgA nephropathy: a perspective for 2021.Seminars in immunopathology · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.