Bi-omics of gut microbiota and urine metabolomics in predicting kidney function decline
Description
Chronic kidney disease (CKD) imposes a significant financial burden on healthcare systems, exacerbated by delays in diagnosis and the risk of progression to end-stage renal disease. Although renal function typically declines gradually with age, the mechanisms driving rapid deterioration in certain CKD cases is poorly understood. While prior studies have linked CKD-associated changes in gut microbiota to systemic inflammation, disrupted metabolism, and comorbidities, the specific microbial and metabolic alterations underlie CKD progression have not been fully elucidated. This study recruited 84 CKD patients and categorized into case and control groups based on their estimated glomerular filtration rate (eGFR) decrease more than 5 mL/min/1.73 m² per year. Urine samples and fecal samples were collected for analyzing metabolites and gut microbiome composition. Our findings revealed significant alterations in carbohydrate and amino acid metabolism pathways. Furthermore, 3-hexenedioic acid in urine metabolites, Phocaeicola vulgatus ATCC 8482, Pusillibacter, and Pusillibacter faecalis in fecal samples could be used to effectively differentiate the cases and controls, with an area under the receiver operating characteristic curve (AUC) of 0.983. These markers could potentially serve as early indicators in CKD progression, and enabling earlier diagnosis and intervention through restore gut microbiota balance in CKD patients.