School of Medicine, South China University of Technology, Guangzhou, China.
Department of Nephrology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Microbiol Spectr. 2023 Jun 15;11(3):e0520222. doi: 10.1128/spectrum.05202-22. Epub 2023 May 25.
IgA nephropathy (IgAN) is reportedly associated with microbial dysbiosis. However, the microbiome dysregulation of IgAN patients across multiple niches remains unclear. To gain a systematic understanding of microbial dysbiosis, we conducted large-scale 16S rRNA gene sequencing in IgAN patients and healthy volunteers across 1,732 oral, pharynx, gut, and urine samples. We observed a niche-specific increase of several opportunistic pathogens, including and in the oral and pharynx, whereas some beneficial commensals decreased in IgAN patients. Similar alterations were also observed in the early versus advanced stage of chronic kidney disease (CKD) progression. Moreover, , and in the oral and pharynx were positively associated with creatinine and urea, indicating renal lesions. Random forest classifiers were developed by using the microbial abundance to predict IgAN, achieving an optimal accuracy of 0.879 in the discovery phase and 0.780 in the validation phase. This study provides microbial profiles of IgAN across multiple niches and underlines the potential of these biomarkers as promising, noninvasive tools with which to differentiate IgAN patients for clinical applications.
IgA 肾病（IgAN）据报道与微生物失调有关。然而，IgAN 患者在多个生态位的微生物失调仍然不清楚。为了系统地了解微生物失调，我们对 IgAN 患者和健康志愿者的 1732 个口腔、咽、肠道和尿液样本进行了大规模的 16S rRNA 基因测序。我们观察到几种机会性病原体在口腔和咽中的生态位特异性增加，包括 和 ，而一些有益的共生菌在 IgAN 患者中减少。在慢性肾脏病（CKD）进展的早期和晚期阶段也观察到了类似的变化。此外，口腔和咽中的 和 与肌酐和尿素呈正相关，表明存在肾脏损伤。通过使用微生物丰度来开发随机森林分类器来预测 IgAN，在发现阶段的最佳准确性为 0.879，在验证阶段的最佳准确性为 0.780。本研究提供了 IgAN 在多个生态位的微生物特征，并强调了这些生物标志物作为有前途的非侵入性工具的潜力，可用于临床应用中区分 IgAN 患者。
