[Relationship Between Different Traditional Chinese Medicine Syndrome Types and Gut Microbiota in Patients With Type 2 Diabetes Mellitus]

Abstract

Objective: To observe the characteristics of gut microbiota in patients with type 2 diabetes mellitus (T2DM) with different traditional Chinese medicine (TCM) syndrome types, and to further explore the key microbial communities and functional differences affecting syndrome differentiation.

Methods: A total of 45 patients who visited the Department of Geriatrics, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine in 2023 were enrolled. These included 15 T2DM patients with qi-yin deficiency and blood stasis syndrome (Group A), 15 T2DM patients with qi-yin deficiency syndrome (Group B), and 15 non-diabetic patients from the same period (Group C). Fecal samples were collected, and 16S rRNA sequencing and analysis were performed.

Results: 1) A total of 1564 operational taxonomic units (OTUs) were obtained from the three groups of patients, with 224, 127, and 351 unique OTUs identified in Groups A, B and C, respectively. 2) Both α- and β-diversity analyses indicated differences among the gut microbiota of the three groups. For instance, in the α-diversity analysis, the Sobs index showed significant inter-group differences (P < 0.01). Group A (264.00 ± 88.84) was significantly higher than Group B (145.90 ± 87.0) (P < 0.01), while Group B was significantly lower than Group C (229.7 ± 112.4) (P < 0.05). In the β-diversity analysis, the principal coordinate analysis (PCoA) indicated a clear separation among groups (R = 0.1610, P < 0.01). The R values in the Anosim/Adonis analysis ranged from 0.144 to 0.196, and the R² values ranged from 0.067 to 0.083, all indicating differences in inter-group comparisons (P < 0.01). 3) At the phylum level, Firmicutes, Actinobacteriota, and Bacteroidota were predominant in all groups. Among them, Bacteroidota exhibited significant inter-group differences (P < 0.05), with its abundance in Group A being significantly higher than that in Group B (P < 0.01). 4) Analysis of differences in microbiota composition, combined with linear discriminant analysis effect size (LEfSe) and Random Forest analysis, revealed that, at the genus level, the microbiota biomarkers between Group A and Group B were Parabacteroides, Bacteroides, g__unclassified_f__Lachnospiraceae, Roseburia, and Aspergillus, those between Group B and Group C were Erysipelotrichaceae_UCG-003 and Ruminococcus, and those between Group A and Group C were Parabacteroides, Anaerotruncus, and Oscillibacter. The results were validated by receiver operating characteristic (ROC) curve analysis, which suggested that the microbiota biomarkers between Group A and Group B (AUC = 0.91; 95% CI, 0.80-1.00), Group B and Group C (AUC = 0.84; 95% CI, 0.69-0.99), Group A and Group C (AUC = 0.87; 95% CI, 0.75-0.99) had good diagnostic efficacy. 5) The study identified 116 major pathways with inter-group differences through Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. For example, the enrichment degree of ABC transporter pathway in Group A (2.58 ± 0.36) was significantly lower than those in Group B (2.90 ± 0.48) and Group C (3.11 ± 0.66) (P < 0.05). These pathways were associated with metabolism and environmental information processing. g.

Conclusion: The differences in the gut microbiota characteristics and functions among patients with specific TCM syndromes of T2DM may provide references for TCM syndrome differentiation and therapeutic mechanisms.

Keywords: 16S rRNA gene sequence; Gut microbiota; Type 2 diabetes mellitus.

图 1

Changes in the diversity of gut microbiota 肠道菌群多样性的改变 A, Venn diagram of OTUs. B, PCoA analysis plots, with each point representing a sample. The points of the same color are samples from the same group. Regarding the distance between two points, the closer two points are to each other, the smaller the difference in community composition between them. C, Anosim/Adonis test. D, Rarefaction curve, with the horizontal coordinates representing the amount of randomly selected sequencing data and the vertical coordinates representing the number of species observed (e.g., Sobs) or diversity indices (e.g., Shannon's index).

图 2

Differences in the composition of gut microbiota 肠道菌群的组成差异

图 3

Analysis of significantly different flora 显著差异菌群分析 A, LEfSe analysis of the composition of the gut microbiota from the phylum to the genus level (LDA > 2, P < 0.05). B-D, LDA discriminant bar graphs for two-by-two subgroups (LDA score ≥ 4, P < 0.05)

图 4

Assessment of the predictive power of gut microbiota biomarkers between two groups 两组间菌群标志物预测能力评估 A: Group A vs. Group B; B: Group B vs. Group C; C: Group C vs. Group A. ^* The data outside the parentheses are the optimal critical values of the microbiota marker diagnostic test between the two groups, and the values inside the parentheses are the specificity and sensitivity of these values, respectively.

图 5

KEGG functional abundance analysis at level 3 Level 3下的KEGG功能丰度分析

图 6

Test of pathway differences at level 3 Level 3下的通路差异检验 ^* P < 0.05, ^** P < 0.01, ^*** P < 0.001.