Dong Yijun, Yan Ge, Zhang Yiding, Zhou Yukun, Shang Jin
Department of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
School of Medicine, Zhengzhou University, Zhengzhou, China.
Ren Fail. 2025 Dec;47(1):2514184. doi: 10.1080/0886022X.2025.2514184. Epub 2025 Jul 9.
Immunoglobulin A nephropathy (IgAN) is characterized by the deposition of glycosylation-deficient IgA1 in the glomeruli and has been linked to the gut-kidney axis. This study aimed to determine if baseline differences in gut microbiota could predict therapeutic responses in IgAN patients. We analyzed fecal microbiomes of 55 biopsy-confirmed IgAN patients and followed them for over 6 months. Patients were classified as responders ( = 39) or nonresponders ( = 16) based on remission status. Fecal microbiomes were profiled using 16S rRNA sequencing, revealing significant microbiota differences. Nonresponders had increased and , with notable enrichment of opportunistic bacteria like and . A predictive classifier based on 24 amplicon sequence variants, with and as key contributors, showed high accuracy in identifying nonresponders (AUC 0.9103, < 0.0001). These findings highlight the role of microbial dysbiosis in IgAN progression and treatment response, suggesting that gut microbiota analysis could guide personalized therapy for IgAN. Future studies with larger cohorts are needed to validate these results and explore microbiome-based treatments.
免疫球蛋白A肾病(IgAN)的特征是肾小球中糖基化缺陷型IgA1的沉积,并且与肠-肾轴有关。本研究旨在确定肠道微生物群的基线差异是否可以预测IgAN患者的治疗反应。我们分析了55例经活检确诊的IgAN患者的粪便微生物群,并对他们进行了6个月以上的随访。根据缓解状态,患者被分为反应者(n = 39)或无反应者(n = 16)。使用16S rRNA测序对粪便微生物群进行分析,发现微生物群存在显著差异。无反应者的[具体细菌名称1]和[具体细菌名称2]增加,[具体机会致病菌名称1]和[具体机会致病菌名称2]等机会性细菌显著富集。基于24个扩增子序列变异构建的预测分类器,以[具体细菌名称1]和[具体细菌名称2]为主要贡献因素,在识别无反应者方面显示出高准确性(AUC 0.9103,P < 0.0001)。这些发现突出了微生物失调在IgAN进展和治疗反应中的作用,表明肠道微生物群分析可以指导IgAN的个性化治疗。需要更大队列的未来研究来验证这些结果并探索基于微生物群的治疗方法。