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Abstract: TH-PO874

Patterns of Gut Microbiota and Metabolites in CKD: The CRIC Study

Session Information

Category: CKD (Non-Dialysis)

  • 2201 CKD (Non-Dialysis): Epidemiology‚ Risk Factors‚ and Prevention

Authors

  • Anderson, Amanda Hyre, Tulane University, New Orleans, Louisiana, United States
  • Baudier, Robin Leigh, Tulane University, New Orleans, Louisiana, United States
  • Daniel, Scott G., The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
  • Chau, Lillian, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Nessel, Lisa C., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Lash, James P., University of Illinois Chicago, Chicago, Illinois, United States
  • Frydrych, Anne, University of Illinois Chicago, Chicago, Illinois, United States
  • Feldman, Harold I., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Bittinger, Kyle, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
  • Kelly, Tanika, Tulane University, New Orleans, Louisiana, United States
  • He, Jiang, Tulane University, New Orleans, Louisiana, United States
  • Wu, Gary, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States

Group or Team Name

  • The CRIC Study
Background

The gut microbiome is altered in numerous disease conditions but its importance in the setting of moderate chronic kidney disease (CKD) remains to be elucidated.

Methods

Among 291 men and women with CKD (58% with diabetes; mean estimated glomerular filtration rate (eGFR): 56 mL/min/1.73m2; 56 repeat stool collections) enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study, shotgun metagenomic sequencing and targeted fecal metabolite assays were performed. For genera associations, 148 genera present in ≥5% of samples that comprised ≥0.01% of total reads were included.

Results

Beta diversity (Euclidean distance, Bray Curtis dissimilarity and unweighted Jaccard similarity index) was related to eGFR and its change over time using the Optimal Microbiome Regression-based Kernel Association Test (Figure 1; each P≤0.001). Nearly all fecal measures of amino acids, bile acids, short-chain fatty acids and urea were significantly associated with beta diversity at a false discovery rate (FDR) <0.05. eGFR was inversely correlated with alpha diversity (ACE: each P<0.001). Five genera including Lawsonella (phylum: Actinobacteria), Hymenobacter (phylum: Bacteroidetes), Neisseria and Halomonas (phylum: Proteobacteria), and Methanosphaera (phylum: Euryarchaeota), as well as caprioic acid levels were associated with eGFR by linear regression independent of age, sex, race, diabetes, and systolic blood pressure at an FDR <0.05. Twenty-six genera were independently associated with eGFR change prior to FDR adjustment. Various genera were independently associated with amino (Figure 2) and bile acids (not shown) at an FDR threshold of <0.05 by tobit regression.

Conclusion

These findings suggest possible pathways through which CKD may influence health.

Funding

  • NIDDK Support