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. 2025 Jun 9;28(7):112856.
doi: 10.1016/j.isci.2025.112856. eCollection 2025 Jul 18.

Disturbance of gut microbiota in diabetes related macroangiopathy: Evidence from the gut bacteriome and mycobiome

Xiaoling Gou  1 , Yuqing Chen  2 , Yi Zong  1 , Xuemei Huang  1 , Yihong Shen  1 , Lijie Wang  1 , Yifan Liu  2 , Yuchi He  2 , Jialong Jia  2 , Xiyu Zhang  2 , Sihan Peng  2 , Xianhua Zhou  1 , Ya Liu  2 , Jing Zhang  1 , Gang Fan  1
Affiliations

Disturbance of gut microbiota in diabetes related macroangiopathy: Evidence from the gut bacteriome and mycobiome

Xiaoling Gou et al. iScience. .

Abstract

Diabetes related macroangiopathy (DMA) is a major complication of type 2 diabetes (T2D), impacting both morbidity and mortality. This study characterized the gut bacteriome and mycobiome in 179 adults, including 58 with DMA, 71 with T2D, and 50 healthy controls. The gut microbiome of DMA subjects exhibited reduced alpha diversity, and a distinct microbial composition compared with healthy control. Two bacterial families, six bacterial genera, and four bacterial species exhibited significant differences between DMA and T2D subjects. Additionally, in the mycobiome group, Xylariales was significantly decreased in DMA subjects compared with T2D subjects. Disruptions in transkingdom interactions between gut bacteria and fungi supported microbiota dysbiosis in DMA. A diagnostic model combining bacterial and fungal markers achieved an AUC of 94.20%. This work deepens our understanding of the microbial landscape associated with macroangiopathy in diabetes and highlights potential microbial targets for diagnostics and therapeutic intervention.

Keywords: Biological sciences; Microbiome.

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Conflict of interest statement

The authors declare no competing interest.

Figures

None
Graphical abstract
Figure 1
Figure 1
Alterations of the gut bacteria in DMA compared with T2D and healthy controls (A–C) Differences between the 3 groups in bacteria richness based on the (A) Chao1 index and bacteria diversity based on the (B) Shannon and (C) Simpson indices at the contig level. For the box plots, the boxes extend from the first to the third quartile (25th to 75th percentiles), with the center line indicating the median. (D) CPCoA analysis based on Bray-Curtis distance between DMA, T2D and healthy controls. p < 0.05 was considered statistically significant. ∗p < 0.05, ∗∗p < 0.01 and ∗∗∗p < 0.001.
Figure 2
Figure 2
Differential bacterial genera in DMA compared with T2D and healthy controls (A) Stacked bar chart showing bacterial composition at the genus level. (B) Differential bacterial genera in DMA compared with healthy T2D and controls were determined by MaAsLin2 analysis and adjusted for confounders, including age, sex, BMI, SBP, and DBP. p < 0.05 was considered statistically significant. ∗p < 0.05, ∗∗p < 0.01 and ∗∗∗p < 0.001. For the box plots, the boxes extend from the first to the third quartile (25th to 75th percentiles), with the center line indicating the median.
Figure 3
Figure 3
Alterations of the gut fungi in DMA compared with T2D and healthy controls (A–C) Differences between the 3 groups in fungi richness based on the (A) Chao1 index and fungi diversity based on the (B) Shannon and (C) Simpson indices at the contig level. For the boxplots, the boxes extend from the first to the third quartile (25th to 75th percentiles), with the center line indicating the median. (D) CPCoA analysis based on Bray-Curtis distance between DMA and T2D compared with healthy controls. p < 0.05 was considered statistically significant. ∗p < 0.05, ∗∗p < 0.01 and ∗∗∗p < 0.001.
Figure 4
Figure 4
Differential fungal genera in DMA compared with T2D and healthy controls (A) Stacked bar chart showing fungal composition at the genus level. (B) Differential fungal genera in DMA compared with healthy T2D and controls were determined by MaAsLin2 analysis and adjusted for confounders, including age, sex, BMI, SBP, and DBP. q < 0.05 was considered statistically significant. ∗q < 0.05, ∗∗q < 0.01 and ∗∗∗q < 0.001. For the boxplots, the boxes extend from the first to the third quartile (25th to 75th percentiles), with the center line indicating the median.
Figure 5
Figure 5
Alterations of transkingdom correlations between the gut bacteriome and mycobiome in DMA compared with T2D and healthy controls Heatmap shows color-coded Spearman’s correlations of the most abundant 10 bacteria genus with the most abundant 10 fungal genus. Red color indicates positive correlation and blue color indicates negative correlation. Significant correlations are displayed with an asterisk. ∗p < 0.05, ∗∗p < 0.01 and ∗∗∗p < 0.001.
Figure 6
Figure 6
The combination of gut bacteriome and mycobiome has good potential in diagnosing between DMA, T2D, and healthy controls based on the Random Forest model (A–C) The important features for (A) bacteriome (top 20), (B) mycobiome (top 20), and (C) combined bacteriome and mycobiome (top 20). The color of the bars corresponds to differential abundance between groups. (D) The ROC curve analysis for each of the three models based on macro-average, including their AUC values.
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