Abstract: TH-PO993
Metabolome Biomarkers of CKD Progression in SPRINT Participants
Session Information
- CKD: Epidemiology, Risk Factors, and Prevention - 1
October 24, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2301 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Ozekin, Yunus, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- You, Zhiying, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Nowak, Kristen L., University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Gitomer, Berenice Y., University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Jovanovich, Anna, Bozeman Health, Bozeman, Montana, United States
- Chonchol, Michel, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
Background
Understanding circulating metabolome patterns in relation to kidney disease progression may facilitate the identification of novel biomarkers and development of targeted interventions for CKD progression.
Methods
Untargeted metabolomics of baseline plasma samples from 700 Systolic Blood Pressure Interventional Trial (SPRINT) participants with CKD was performed using UPLC-MS/MS. Bioinformatic analysis was performed using the MetaboAnalyst 6.0 workflow. The association between 35 metabolites and the primary kidney outcome in SPRINT (≥50% decrease in eGFR or development of ESKD requiring dialysis or kidney transplantation) was assessed using Cox proportional hazards models.
Results
Baseline characteristics are summarized in Table 1. There were 1686 metabolites with standardized measurements at baseline. 234 compounds were upregulated and 27 were downregulated (p<0.05, abs(fold change) >1.5) (Fig. 1). The associations of the top 35 metabolites with the CKD composite outcome in SPRINT are shown in Fig. 2.
Conclusion
Among patients with CKD, novel metabolites derived from untargeted metabolomic profiling were independently associated with kidney disease progression outcomes.
Baseline Characteristics of Study Patients
| Characteristic | Standard Treatment n=342 | Intensive Treatment n=358 |
| Age | 73.46 +/- 9.06 | 74.03 +/- 9.53 |
| Female sex-no. (%) | 141 (39.39) | 135 (39.47) |
| eGFR | 45.14 +/- 9.82 | 45.23 +/- 9.76 |
| Body mass index | 29.35 +/- 6.82 | 29.12 +/- 6.27 |
| Composite Renal Outcome-no. (%) | 13 (3.63) | 10 (2.92) |
Funding
- Veterans Affairs Support