Exploring the gut mycobiome: differential composition and clinical associations in hypertension, chronic kidney disease, and their comorbidity

Abstract

Background: Hypertension (HTN) and chronic kidney disease (CKD) pose significant global health challenges and often coexist, amplifying cardiovascular risks. Recent attention has turned to the gut mycobiome as a potential factor in their pathophysiology. Our study sought to examine the gut fungal profile in individuals with HTN, CKD, and the concurrent HTN+CKD condition, investigating its connections with serum cytokines, renal function, and blood pressure.

Methods and materials: We investigated three distinct participant groups: a cohort of 50 healthy controls (HC), 50 individuals diagnosed with HTN-only, and 50 participants suffering from both HTN and CKD (HTN+CKD). To facilitate our research, we gathered fecal and blood samples and conducted a comprehensive analysis of serum cytokines. Moreover, fungal DNA extraction was conducted with meticulous care, followed by sequencing of the Internal Transcribed Spacer (ITS) region.

Results: HTN+CKD patients displayed distinctive fungal composition with increased richness and diversity compared to controls. In contrast, HTN-only patients exhibited minimal fungal differences. Specific fungal genera were notably altered in HTN+CKD patients, characterized by increased Apiotrichum and Saccharomyces levels and reduced Candida abundance. Our correlation analyses revealed significant associations between fungal genera and serum cytokines. Moreover, certain fungal taxa, such as Apiotrichum and Saccharomyces, exhibited positive correlations with renal function, while others, including Septoria, Nakaseomyces, and Saccharomyces, were linked to blood pressure, particularly diastolic pressure.

Conclusion: Gut mycobiome dysbiosis in individuals with comorbid HTN and CKD differs significantly from that observed in HTN-only and healthy controls. The interactions between serum cytokines, renal function, and blood pressure emphasize the potential impact of the fungal microbiome on these conditions. Additional research is required to clarify the underlying mechanisms and identify therapeutic opportunities associated with mycobiome dysbiosis in HTN and CKD.

Keywords: chronic kidney disease; cytokine; gut mycobiome; hypertension; renal function.

Figure 1

Mycobiome Composition, Diversity, Phylum and Genus Profiles, and Inter-Group Comparisons. (A-C) Principal Coordinate Analysis (PCoA) based on Bray-Curtis distances at the Operational Taxonomic Unit (OTU) level, illustrating the microbial community comparisons among healthy controls (HC), hypertension (HTN-only), and hypertension with chronic kidney disease (HTN+CKD) groups, among HTN+CKD female and HTN+CKD male, and among HTN+CKD eld and HTN+CKD non-eld. A 95% confidence ellipse is plotted for each group. Permutational multivariate analysis of variance (PERMANOVA) was applied for statistical comparisons between the groups, with P-values adjusted using the Benjamini and Hochberg false discovery rate (FDR) correction. (D) Assessment of fungal richness and diversity using Chao 1, Shannon, and Simpson indices at the OTU level. Wilcoxon rank-sum tests were employed, and P-values were adjusted for multiple comparisons using the Benjamini and Hochberg FDR correction. (E, F) Fungal taxonomic profiles at the phylum and genus levels, with representation limited to the top 15 most abundant genera. (G) Comparative analysis of fungal genera across the HC, HTN-only, and HTN+CKD groups. Wilcoxon rank-sum tests were employed, and P-values were adjusted for multiple comparisons using the Benjamini and Hochberg FDR correction. *, FDR < 0.05; **, FDR<0.01 CKD, chronic kidney disease; HC, healthy controls; HTN, hypertension.

Figure 2

Comparative analysis of serum cytokines across the HC, HTN-only, and HTN+CKD groups. Student’s t test and ANOVA were used on normalized continuous variables and Wilcoxon rank-sum test on non-normal continuous variables. The P-value was adjusted for multiple comparisons using the Benjamini–Hochberg (BH) false discovery rate (FDR). *, P/FDR < 0.05; **, P/FDR<0.01; ***P/FDR<0.001. CKD, chronic kidney disease; HC, healthy controls; HTN, hypertension.

Figure 3

Gut mycobiome was associated with participants’ serum cytokines. (A) The heatmap depicted the association between the fungal genera and serum cytokines showing differed among the three groups of HC, HTN-only and HTN+CKD. Spearson correlation analysis was performed. The correlation of two variables with values of |r|>0.3 and P < 0.05 are displayed. *, P < 0.05; and **, P < 0.01. (B) Network analysis of the correlation between abnormal genera and discriminatory cytokines. Yellow line represents positive correlations and gray negative correlations. (C) Linear regression analysis was conducted to examine the relationship between abnormal genera and discriminatory cytokines.

Figure 4

Gut mycobiome was associated with participants’ eGFR/blood pressure, and cytokines. (A) The correlation analysis depicted the association between the fungal genera and eGFR/blood pressure showing differed in among the three groups of HC, HTN-only and HTN+CKD. Spearson correlation analysis was performed. Solid lines represent statistically significant correlations (P<0.05); dashed lines indicate no statistically significant correlations (P≥0.05). Red lines denote positive correlations, while blue lines indicate negative correlations. (B) Abnormal genera regulated BP and cytokines.