Exploring the Relevance between Gut Microbiota-Metabolites Profile and Chronic Kidney Disease with Distinct Pathogenic Factor Original paper

What was studied?

The study Exploring the Relevance Between Gut Microbiota–Metabolites Profile and Chronic Kidney Disease with Distinct Pathogenic Factor investigated how gut dysbiosis and metabolite alterations relate to chronic kidney disease (CKD) progression. This research specifically explored how the gut microbiota–metabolite axis functions as a potential CKD biomarker, using patients with hypertensive CKD, diabetic CKD, and CKD without comorbidity. The authors used long-read 16S rRNA sequencing and untargeted LC-MS/MS metabolomics to identify microbial and metabolic signatures capable of distinguishing CKD phenotypes. By integrating operational taxonomic units (OTUs), fecal metabolite patterns, and species–metabolite associations, the study assessed the predictive utility of these signatures for CKD with distinct pathogenic factors. This work emphasizes the complex interplay between gut ecology and kidney function, highlighting microbe–metabolite networks that may underlie early detection of CKD.

Who was studied?

The cohort included 165 total participants: 60 healthy individuals and 105 CKD patients divided into diabetic CKD (n=39), hypertensive CKD (n=26), and non-comorbid CKD (n=40). All participants were recruited from Taipei Medical University–affiliated medical centers. Groups were matched on age and sex, and all CKD patients met guideline-based diagnostic criteria. Fecal samples were collected under standardized conditions, and participants underwent laboratory evaluation for glucose, HbA1c, creatinine, and eGFR. Diabetic CKD cases exhibited significantly elevated fasting glucose, HbA1c, and creatinine compared to hypertensive and non-comorbid CKD groups. Long-read sequencing quality metrics were consistent across participants, ensuring comparability of microbial and metabolomic data.

Most important findings

Microbiome analyses revealed marked α- and β-diversity shifts across CKD groups, especially in diabetic and non-comorbid CKD. Species enriched in CKD included Escherichia marmotae, Fusobacterium mortiferum, Streptococcus pasteurianus, Bacteroides stercoris, and Lactobacillus mucosae. Healthy participants showed higher levels of Mitsuokella jalaludinii, Megasphaera indica, Selenomonas ruminantium, and Anaerostipes hadrus. Visualizations demonstrate clear group clustering in PCoA plots and LDA bar charts, highlighting disease-specific dysbiosis. Metabolomics identified 41 discriminative metabolites, many involved in fatty acid, amino acid, and xenobiotic metabolism. Notably, stearic acid, L-proline, amiloride, and 3,4-dimethoxyphenylethylamine were elevated in diabetic CKD, while arachidic acid, L-phenylalanine, and N-acetylputrescine were enriched in non-comorbid CKD. Heatmaps show distinct metabolite clusters separating CKD subtypes from healthy individuals.
Species–metabolite associations were highly specific:

Key implications

The study demonstrates that CKD etiology is reflected in distinct gut microbial and metabolomic patterns. Microbiome signatures may aid early detection, stratification, and personalized intervention. The work supports the potential of species–metabolite networks as high-resolution biomarkers, outperforming microbiome-only or metabolite-only approaches. Such signatures could guide therapies targeting dysbiosis, dietary modulation, or metabolite-related pathways. It also reinforces the mechanistic role of microbial metabolites—such as uremic toxins, fatty acids, and amino acid derivatives—in CKD progression. Future longitudinal studies are required to validate causality and integrate findings into clinical practice.

Citation

Chen T-H, Cheng C-Y, Huang C-K, Ho Y-H, Lin J-C. Exploring the relevance between gut microbiota–metabolites profile and chronic kidney disease with distinct pathogenic factor. Microbiology Spectrum. 2023;11(1):e02805-22