PloS one · 2026
Integrated multi-omics reveals dysbiosis in hemodialysis patients: A multi-center study.
СтатьяМногоцентровое исследованиеНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
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Zhang Xinyue, Yu Dan, Cui Yupeng, Chi Yanqing, Yan Zhenyu, Song Yang, Hou Liping, Qin Jin, Zhang Jingjing, Wang Yuanyuan, Wei Wei, Di Hailing
Аннотация
INTRODUCTION: The gut microbiome-metabolome interplay in hemodialysis (HD) patients remains poorly characterized. Using multi-omics approaches, we compared HD patients with healthy controls (HC) to identify microbial signatures, metabolic perturbations, and their integrated correlations.
METHODS: This case-control study included 192 participants (96 HD-HC pairs under identical dietary and living conditions). The gut microbiota composition was analyzed using 16S ribosomal RNA gene sequencing, and fecal metabolomes were analyzed using ultra-high-performance liquid chromatography and high-resolution mass spectrometry (UPLC-HRMS). A multi-omics analysis was conducted utilizing Spearman correlation analysis, Mantel test analysis, and differential functional pathway analysis.
RESULTS: We observed significant differences in gut microbiota composition between the HD and HC groups, such as Ruminococcus and Bifidobacterium. Comparative analysis revealed 497 significantly altered metabolites in the HD group versus HC, primarily associated with amino acid, vitamin, lipid, purine, and pyrimidine metabolisms. ROC analysis identified 4-pyridoxic acid, nudifloramide, imidazoleacetic acid, ascorbic acid, and tocopheronic acid as potential diagnostic biomarkers (AUC > 0.8, p < 0.01). Integrated multi-omics analysis revealed correlations between Ruminococcus and metabolites such as Docosapentoic acid (DPA), 13 - EPAHAAB (EPA), and tryptamine, with shared differential pathways in bile secretion, caffeine metabolism, gastric acid secretion, and vitamin B6 metabolism.
CONCLUSION: Hemodialysis patients exhibited significant alterations in gut microbiota composition and metabolic profiles (amino acid, vitamin, and lipid metabolism) compared with healthy controls, with demonstrated microbiome-metabolome interactions and shared functional pathways. The potential diagnostic and therapeutic value of these differential features warrants further exploration and external validation.
METHODS: This case-control study included 192 participants (96 HD-HC pairs under identical dietary and living conditions). The gut microbiota composition was analyzed using 16S ribosomal RNA gene sequencing, and fecal metabolomes were analyzed using ultra-high-performance liquid chromatography and high-resolution mass spectrometry (UPLC-HRMS). A multi-omics analysis was conducted utilizing Spearman correlation analysis, Mantel test analysis, and differential functional pathway analysis.
RESULTS: We observed significant differences in gut microbiota composition between the HD and HC groups, such as Ruminococcus and Bifidobacterium. Comparative analysis revealed 497 significantly altered metabolites in the HD group versus HC, primarily associated with amino acid, vitamin, lipid, purine, and pyrimidine metabolisms. ROC analysis identified 4-pyridoxic acid, nudifloramide, imidazoleacetic acid, ascorbic acid, and tocopheronic acid as potential diagnostic biomarkers (AUC > 0.8, p < 0.01). Integrated multi-omics analysis revealed correlations between Ruminococcus and metabolites such as Docosapentoic acid (DPA), 13 - EPAHAAB (EPA), and tryptamine, with shared differential pathways in bile secretion, caffeine metabolism, gastric acid secretion, and vitamin B6 metabolism.
CONCLUSION: Hemodialysis patients exhibited significant alterations in gut microbiota composition and metabolic profiles (amino acid, vitamin, and lipid metabolism) compared with healthy controls, with demonstrated microbiome-metabolome interactions and shared functional pathways. The potential diagnostic and therapeutic value of these differential features warrants further exploration and external validation.