Baseline Characteristics of the Study Subjects
In this cross-sectional study, 52 IgAN patients and 25 HCs were enrolled according to the specified inclusion and exclusion criteria (see Materials and Methods). The basic information for IgAN patients and HCs is shown in Table 1. Systolic blood pressure, diastolic blood pressure, and serum levels of creatinine, e-GFR, BUN, urine protein, and red blood cell numbers in urine were significantly higher in IgAN patients than in HCs (P < 0.05).
Composition of Gut Microbiota
Analysis of Pan and Core genomes and rarefaction curves at the genus level indicated that the data in our study were large enough and valid (Fig. 1). We evaluated alpha and beta diversity to compare community richness and diversity between the gut microbiota of IgAN patients and HCs. Although alpha diversity analysis showed no significant differences in taxon richness and evenness, there was a clear separation in the composition of gut microbiota between the IgAN patients and HCs (Ace, P = 0.073; Chao, P = 0.077; Sobs, P = 0.088) (Table 2). These results suggested that bacterial community diversity was altered between the two groups.
Beta diversity analysis also demonstrated that the overall structure of the intestinal microbiomes differed significantly between IgAN patients and HCs (P = 0.005; Fig. 2A), which was further confirmed by Venn diagram analysis (Fig. 2a). Overall, 437 genera were detected at a 97% sequence homology cutoff for the 16S rRNA gene. Of these genera, 287 were shared between IgAN patients and HCs, 18 were specific for the HCs, and 132 were unique to IgAN patients. Overall, the gut microbiome composition of IgAN patients differed from that of HCs.
Specific Differences from Phylum to Genus Levels in IgAN Patients and HCs
To further explore the differences in microflora between IgAN patients and HCs, we used the LEfSe algorithm. The results indicated that 3 phyla, 3 classes, 3 orders, 5 families, and 12 genera were enriched in IgAN patients, while 2 phyla, 2 classes, 5 orders, 7 families, and 28 genera were enriched in HCs (LDA score >2.0, P < 0.05) (Fig. 3a). At the phylum level, the relative abundance of Bacteroidetes was higher in IgAN patients while that of Firmicutes was higher in HCs. At the genus level, the relative abundance of Bacteroides was higher in IgAN patients, whereas that of Subdoligranulum was higher in HCs. A cladogram was then generated to directly visualize and compare the phylogenetic distribution from the phylum to genus level between the two groups, with the results demonstrating that significant differences existed at each taxonomic level analyzed (P < 0.05; Fig. 3b).
At the phylum level, a Wilcoxon rank-sum test indicated that the proportions of Bacteroidetes and Fusobacteria were markedly higher in IgAN patients than in HCs (P < 0.05; Fig. 4a). Additionally, IgAN patients had a higher proportion of Proteobacteria, although the difference was not significant (P = 0.066). Conversely, the proportions of Firmicutes, Actinobacteria, and Tenericutes were significantly higher in the fecal microbiota of HCs (P < 0.05). A genus-level comparison between HCs and IgAN patients demonstrated that the abundances of Bacteroides, Escherichia–Shigella, and Lachnoclostridium were significantly increased in IgAN patients when compared with those of HCs (P < 0.05; Fig. 4b). However, IgAN patients also presented a significant reduction in the proportions of Blautia, Subdoligranulum, Prevotella 9, genus_Eubacterium hallii, and Bifidobacterium (P < 0.05). The community bar plot analysis also showed differences in composition at the genus level (Fig. 4c), although the differences were not significant.
Relationship between Gut Microbiota and Clinical Characteristics
IgAN patients were divided into subgroups based on the levels of proteinuria and hematuria to evaluate whether intestinal microbes were related to the severity of IgAN. As most patients enrolled in our study were at early stages of chronic kidney disease (CKD 1 and CKD 2 stages), subgroup analysis based on the eGFR level was discontinued. As shown in Table 3, patients with a higher urine RBC count (≥10/HP) count presented a higher abundance of Escherichia–Shigella (P = 0.016) and a lower abundance of Bifidobacterium spp. (P = 0.055) than patients with a urine RBC count <10/HP. Patients with different levels of urine protein had significantly different abundances of Subdoligranulum spp. (P < 0.05). Moreover, the abundance of Escherichia–Shigella was marginally higher, while that of members of the Bifidobacterium genus was lower (P = 0.06), in patients with proteinuria ≥1 g/24 h (P = 0.075).
Because immune reactions and inflammation have a role in IgAN pathogenesis, serum concentrations of immune and inflammatory factors, such as Gd-IgA1, LBP, sCD14, ICAM-1, and CRP, were measured along with routine laboratory indexes. We found that serum levels of Gd-IgA1, LBP, sCD14, and ICAM-1, and CRP levels were significantly increased in IgAN patients when compared with those of HCs (Fig. 5).
Spearman’s correlation analysis was performed only in the IgAN group to investigate the relationship between bacteria and inflammation indexes in the disease state. The genus Prevotella 7 was negatively correlated with Gd-IgA1, LBP, sCD14, and ICAM-1 (r = −0.356, P = 0.014; r = −0.322, P = 0.014; r = −0.321, P = 0.028; r = −0.311, P = 0.033, respectively). Meanwhile, Bifidobacterium spp. had a marked inverse relationship with LBP and Gd-IgA1 (r = −0.301, P = 0.040; r = −0.266, P = 0.070, respectively). Additionally, Escherichia–Shigella was negatively correlated with Prevotella 7 spp. (r = −0.305, P = 0.037), indicating that there was also interaction among microbiota, as shown in Table 4. Combined with previous results, it was reasonable to draw a conclusion that the gut microbiota might be associated with inflammatory state in IgAN.