Gut frailty in chronic heart failure: clinical determinants and distinct microbial signatures

Figure 1. ASVs distribution, sequencing depth validation, and alpha diversity of the gut microbiota. (A) Venn diagram illustrating the number of shared and unique operational taxonomic units between the non-gut frailty and gut frailty groups. The overlapping region represents taxa common to both groups, while non-overlapping regions represent group-specific taxa. (B) Rarefaction curves based on the Observed Species index. The curves approach a plateau with increasing sequencing depth, indicating that the sampling depth was sufficient to capture the majority of microbial diversity in the samples. (C–F) Comparison of alpha diversity indices between the non-gut frailty and gut frailty groups. Box plots depict the (C) Ace index, (D) Shannon index, (E) Chao1 index, and (F) Observed ASV. The gut frailty group exhibited significantly lower alpha diversity across these metrics compared to the non-gut frailty group. Statistical significance is indicated by asterisks (****, P < 0.0001).

Figure 2. Beta diversity and taxonomic composition analysis of the gut microbiota. (A) Principal Coordinate Analysis (PCoA) plot based on Bray-Curtis distances, visualizing the distinct separation of microbial community structures between the non-gut frailty and gut frailty groups. The variation explained by the first two coordinates is PCoA1 (26.59%) and PCoA2 (9.43%). An Adonis test confirmed significant differences between the groups (R2 = 0.111, P = 0.001). (B) Relative abundance of dominant bacterial taxa at the Phylum level. (C) Relative abundance of bacterial taxa at the Genus level. (D) Analysis of Similarity using Bray-Curtis ranks, confirming significant dissimilarity between the groups (R = 0.2766, P = 0.0011) compared to intra-group distances. (E) Top 35 Genera were ranked by total quantitative abundance across all samples. The heatmap displays the Z-score standardized relative abundance, with annotations indicating statistically significant differences calculated by Metastats between the non-gut frailty and gut frailty groups. Hypothesis testing was performed to obtain p-values, which were corrected to q-values to assess statistical significance. (F) Similarity Percentage…

Figure 3. Identification of characteristic taxa and predicted functional pathways of the gut microbiota. (A,B) Linear discriminant analysis Effect Size (LEfSe) analysis identifying differentially abundant taxa biomarkers between the non-gut frailty and gut frailty groups. (A) Histogram of Linear Discriminant Analysis scores. Taxa enriched in the gut frailty group are shown with positive scores, while taxa enriched in the non-gut frailty group are shown with negative scores. (B) Cladogram illustrating the phylogenetic relationship and taxonomic hierarchy of the identified differential taxa, from phylum to species levels. (C) Prediction of functional potential using PICRUSt2 analysis. The extended error bar plot displays significantly different KEGG pathways at Level 3 between the two groups. Statistical significance was determined using a T-test, showing the mean proportion and 95% confidence intervals of the difference. (D) Heatmap of predicted functional profiles based on KEGG pathways, visualizing the differential enrichment of functional categories across the groups. (E) Differential abundance analysis of metabolic pathways performed using the metagenomeSeq method. The bar plot…