Abstract
Microbiota plays an important role in immunoglobulin A (IgA) nephropathy (IgAN); however, the pathogenesis, early diagnosis, and treatment of IgAN remain unclear. The aim of the present study was to develop a preliminary model based on saliva‑specific microbes and clinical indicators to facilitate the early diagnosis of IgAN and obtain insights into its treatment. The microbial profile of the saliva of 28 IgAN patients and 25 healthy control subjects was investigated using high‑throughput sequencing and bioinformatics analyses of the V4 region in microbial 16S rRNA genes. IgAN patients and healthy subjects did not differ significantly in α‑diversity indices (Chao1 and Shannon index) or phylum composition. At the genus level, however, Granulicatella was significantly less abundant in healthy individuals than in IgAN patients, while Prevotella and Veillonella were significantly more abundant in the healthy subjects than in IgAN patients (P<0.05 and P<0.01, respectively). Correlation analysis between biochemical indicators and operational taxonomic units (OTUs) revealed that the glomerular filtration rate was positively correlated with OTU86 and OTU287 at P<0.05, positively correlated with OTU165 at P<0.001, and negatively correlated with OTU455 at P<0.05. The serum creatinine index was negatively correlated with OTU287 at P<0.05 and negatively correlated with OTU165 at P<0.001. The pathological changes were positively correlated with OTU255 at P<0.05, OTU200 at P<0.01, and OTU455 and OTU75 at P<0.001, and negatively correlated with OTU86, OTU287, and OTU788 at P<0.05 and with OTU165 at P<0.01. The differences between Chinese IgAN patients and healthy subjects in terms of OTUs and biochemical indicators were analyzed and a mathematical model to facilitate the clinical diagnosis of IgAN was established.