ArticleRenal failure2024
Gut and respiratory microbiota landscapes in IgA nephropathy: a cross-sectional study.
Article in Renal failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Probiotics in Autoimmune Disease: Strain-specific Mechanisms and Therapeutic Perspectives.Clinical reviews in allergy & immunology · 2026Review
- Organ cross-talk: molecular mechanisms, biological functions, and therapeutic interventions for diseases.Signal transduction and targeted therapy · 2026Review
- Gut-kidney axis in IgA nephropathy: mechanisms linking microbiota dysbiosis to immune dysregulation, Gd-IgA1 generation, and renal injury.Frontiers in immunology · 2026Review
- Gut microbiota dysbiosis and immune responses: insights from IgA nephropathy and inflammatory bowel disease.Frontiers in immunology · 2026Review
- Targeted release of budesonide modulates key gut microbial abnormalities in immunoglobulin A nephropathy.Frontiers in immunology · 2026Article
- The evolving understanding of systemic mechanisms in organ-specific IgA nephropathy: a focus on gut-kidney crosstalk.Theranostics · 2025Review
- Fecal microbiota transplantation is a promising therapy for kidney diseases.Frontiers in medicine · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIgA nephropathy (IgAN) is intimately linked to mucosal immune responses, with nasopharyngeal and intestinal lymphoid tissues being crucial for its abnormal mucosal immunity. The specific pathogenic bacteria in these sites associated with IgAN, however, remain elusive. Our study employs 16S rRNA sequencing and machine learning (ML) approaches to identify specific pathogenic bacteria in these locations and to investigate common pathogens that may exacerbate IgAN.
methodsIn this cross-sectional analysis, we collected pharyngeal swabs and stool specimens from IgAN patients and healthy controls. We applied 16SrRNA sequencing to identify differential microbial populations. ML algorithms were then used to classify IgAN based on these microbial differences. Spearman correlation analysis was employed to link key bacteria with clinical parameters.
resultsWe observed a reduced microbial diversity in IgAN patients compared to healthy controls. In the gut microbiota of IgAN patients, increases in
conclusionsThis study revealing that changes in flora structure could provide important pathological insights for identifying therapeutic targets, and ML could facilitate noninvasive diagnostic methods for IgAN.
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