Clinical Characteristics of all Participants
We recruited 44 patients with IgAN, 40 patients with MN, and 30 healthy controls. All the patients were newly diagnosed with the conditions using kidney biopsy. The clinical characteristics of the participants are shown in Table 1. Age, gender, and BMI were matched between the patients and healthy controls. As expected, serum creatinine level was higher in patients with IgAN than in healthy controls, while the serum levels of total protein and albumin were significantly lower in patients with MN than in healthy controls (Table 1). The median proteinuria of patients with IgAN was 776mg/24h, whereas that of patients with MN was 3,623mg/24h. About 72.5% of patients with MN presented with positivity of serum anti-PLA2R antibodies. According to the Oxford classification of IgAN, there was modest glomerulonephritis with mild tubulointerstitial injury. Approximately 35(87.5%) patients presented with stage Ⅱ MN (Table 2).
Richness and Diversity of the Gut Microbiota
In total, 6,337,125 usable raw reads were obtained from 114 stool samples. After quality filtering and assembly of overlapping paired-end reads, 5,674,350 high-quality reads were generated and 698 operational taxonomic units (OTUs) were obtained based on a 97% homology cutoff. The average number of sequences per sample was 49,775±16,071(range 25,248-142,345). The values of Good’s coverage of all libraries were above 99%. The species accumulation curve showed that the estimated OTU richness already approached saturation at this sequencing depth, suggesting that a vast majority of diversity had been detected (Figure 1A). A Venn diagram showed that 541 of the total 698 OTUs were shared among the three groups, while 31 were unique for IgAN, and 16 were specific for MN (Figure 1B). No significant differences in community richness (estimated by chao and ACE indices) and diversity(measured by Shannon and Simpson indices) were observed between IgAN and the healthy control(Supplemental Table 3, Supplemental Fig. 1A, B, C, D).Similar trends for community richness and diversity were observed between IgAN and MN, consistent with the trends observed between MN and healthy control(Supplemental Table 3; Supplemental Fig. 1A, B, C, D).
Taxonomy-based comparisons of gut microbiota at the phylum and genus levels
At the phylum level, the gut microbiota of the three groups was dominated by Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria, which on average accounted for up to 98% of the relative abundance (Figure 2A). Bacterial genera Bacteroides, Faecalibacterium, Prevotella, and Lachnospiraceae_incertae_sedis, each accounting for up to 5% of the sequences on average, were the dominant populations (Figure 2B). The faecal microbial composition of all samples at the phylum and genus levels is shown in the Supplemental Figure 2A, B.
IgA Nephropathy versus Healthy Controls
Firmicutes was the most predominant phylum, contributing 47.5% and 50.7% of the gut microbiota in patients with IgAN and healthy controls, respectively. Compared to that in the healthy controls, Proteobacteria and Candidate_division_TM7were overrepresented (8.37% vs. 3.41% and 0.026% vs. 0.013%, respectively), while Fusobacteria and Synergistetes were significantly underrepresented in patients with IgAN (0.25% vs. 0.29% and 0.013% vs. 0.018%, respectively, all P<0.05, Figure 2C, Supplemental Table 4). At the genus level, we observed that Escherichia-Shigella and Defluviitaleaceae_incertae_sedis were enriched in IgAN(5.67% vs. 1.04% and 0.17% vs. 0.12%, respectively), while five genera, namely, Roseburia, Lachnospiraceae_unclassified, Clostridium_sensu_stricto_1, Haemophilus, and Fusobacterium were enriched in the healthy control(3.52% vs. 4.28%, 0.39% vs. 0.72%, 0.12% vs. 1.02%, 0.03% vs. 0.22%, and 0.25% vs. 0.29%, respectively, all P<0.05, Figure 2D, Supplemental Table 5).
Membranous Nephropathy versus Healthy Controls
Firmicutes was the dominant phylum in both MN and HC, contributing 47.2% and 50.7% of the gut microbiota, respectively. At the phylum level, the abundance of Proteobacteria increased (9.86% vs. 3.41%), whereas that of Synergistetes decreased in patients with MN compared to that in the healthy controls (0.008% vs. 0.018%, all P<0.05, Figure 2E, Supplemental Table 4). At the genus level, the abundance of five genera, namely, Escherichia-Shigella, Streptococcus, Enterobacteriaceae_unclassified, Peptostreptococcaceae_incertae_sedis, and Enterococcus increased(6.24% vs. 1.04%, 0.61% vs. 0.29%, 1.01% vs. 0.11%, 0.18% vs. 0.10%, and 0.045% vs. 0.007%), whereas the abundance of four genera, namely, Lachnospira, Lachnospiraceae_unclassified, Clostridium_sensu_stricto_1, and Veillonella decreased in patients with MN compared to that in the healthy controls (0.63% vs. 1.83%, 0.43% vs. 0.72%, 0.28% vs. 1.02%, and 0.28% vs. 0.42%, all P<0.05, Figure 2F, Supplemental Table 5).
IgA Nephropathy versus Membranous Nephropathy
Next, we investigated how microbial populations vary between disease cohorts, although no significant differences were observed at the phylum level between IgAN and MN. Compared to that in MN, the abundance of genera Megasphaera and Bilophila increased (1.23% vs. 0.17% and 0.23% vs. 0.09%), whereas those of Veillonella, Klebsiella, Haemophilus, Enterococcus, and Streptococcus decreased in patients with IgAN(0.25% vs. 0.28%, 0.33% vs. 0.91%, 0.03% vs. 0.43, 0.006% vs. 0.04%,and 0.17% vs. 1.01%, all P<0.05, Figure 2G,Supplemental Table 5).
Identification of Key OTUs
To identify key phylotypes distinguishing different groups, OTUs with a median relative abundance larger than 0.01% were analyzed using a Random Forest model. Compared to that in the healthy control, we identified 15 OTUs specific for IgAN, among which six OTUs assigned to Bifidobacterium, Paraprevotella, Parabacteroides, Roseburia, and Defluviitaleaceae_incertae_sedis were enriched, while nine OTUs assigned to Lachnospiraceae_unclassified, Haemophilus, Clostridium_sensu_stricto_1, Bacteroides, Ruminococcaceae_incertae_sedis, Megamonas, Faecalibacterium, and Roseburia were depleted in IgAN. Furthermore, we identified 15 OTUs specific for MN, among which seven OTUs assigned to Bacteroides, Escherichia-Shigella, Streptococcus, and Lachnospiraceae_incertae_sedis were enriched, while eight OTUs assigned to Bacteroides, Lachnospiraceae_unclassified, Clostridium_sensu_stricto_1, Lachnospira, Lachnospiraceae_incertae_sedis, Ruminococcaceae_incertae_sedis, Subdoligranulum, and Ruminococcus were depleted in MN. Furthermore, we found 12 OTUs as key variables between patients with IgAN and MN, among which three OTUs assigned to Flavonifractor, Veillonella and Ruminococcaceae_incertae_sedis were enriched in IgAN, while nine OTUs assigned to Veillonella, Haemophilus, Gemella, Lactobacillus, Bacteroides, Klebsiella, Actinomyces and Streptococcus were enriched in MN(Figure 3A,B,C).
Differentiation of patients Based on Gut Microbiota Profiles
PCoA based on unweighted UniFrac distances revealed that the microbial composition of IgAN deviated from those of the healthy controls (P=0.007, Figure 4A). The patients with MN and healthy control samples also separated when subjected to PCoA (P=0.018, Figure 4B). Conversely, a symmetrical distribution was observed between IgAN and MN when subjected to PCoA based on unweighted UniFrac distances (P=0.633, Supplemental Figure 3). To identify the specific taxa between groups, we analyzed faecal microbiota using LEfSe. A cladogram presented the gut microbial structures and the major differences in taxa between patients with IgAN and healthy controls (Supplemental Figure 4A, B). We also compared the faecal microbiota to identify the specific taxa between patients with MN and healthy controls (Supplemental Figure 4C, D); results showed gut microbial dysbiosis in patients with IgAN and MN. Further, the cladogram of microbial structure obtained after comparison of the faecal microbiota between disease cohorts showed the maximum differences in taxa (Supplemental Figure 4E, F).
Spearman correlation test in patients with IgAN and MN
Pairwise comparisons of clinical factors were shown, with a color gradient denoting Spearman’s correlation coefficients. The clinical factors were mainly focused on the risk factors for kidney prognosis. In IgAN group, significant positive correlation existed between the genera Klebsiella and Enterobacteriaceae_unclassified(ρ=0.82, Figure 5A). In addition, the genus Prevotella showed positive correlation, while Klebsiella, Citrobacter, and Fusobacterium showed negative correlations with serum albumin (ALB) level. Positive correlations existed between Bilophila and Crescents in the Oxford classification of IgAN (Figure 5A, Supplemental Table 6). Correspondingly, in the MN group, significant positive correlations existed in the genera: Alistipes and Ruminococcaceae_uncultured(ρ=0.82), Anaerotruncus and Christensenellaceae_uncultured(ρ=0.87), Citrobacter and Enterobacteriaceae_unclassified(ρ=0.81, Figure 5B). Negative correlation existed between Escherichia-Shigella and proteinuria, Bacteroides and Klebsiella showed positive correlation with the MN stage, while Akkermansia showed negative correlation with IgG4 deposition in the subepithelia, as observed using immunofluorescence (Figure 5B, Supplemental Table 7).