Abstract: TH-PO076
Urine Proteomic Signatures of Kidney Function Decline after Hospitalization
Session Information
- AKI: Clinical, Outcomes, and Trials - Epidemiology and Pathophysiology
October 24, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Acute Kidney Injury
- 102 AKI: Clinical, Outcomes, and Trials
Authors
- Wen, Yumeng, Genentech Inc, South San Francisco, California, United States
- Menez, Steven, Johns Hopkins Medicine, Baltimore, Maryland, United States
- Thiessen Philbrook, Heather, Johns Hopkins Medicine, Baltimore, Maryland, United States
- Moledina, Dennis G., Yale University School of Medicine, New Haven, Connecticut, United States
- Bhatraju, Pavan K., University of Washington School of Medicine, Seattle, Washington, United States
- Coca, Steven G., Icahn School of Medicine at Mount Sinai, New York, New York, United States
- Chinchilli, Vernon M., Penn State College of Medicine, Hershey, Pennsylvania, United States
- Go, Alan S., Kaiser Permanente, Oakland, California, United States
- Siew, Edward D., Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Kimmel, Paul L., National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States
- Ikizler, Talat Alp, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Hsu, Chi-yuan, University of California San Francisco School of Medicine, San Francisco, California, United States
- Himmelfarb, Jonathan, University of Washington School of Medicine, Seattle, Washington, United States
- Cantley, Lloyd G., Yale University School of Medicine, New Haven, Connecticut, United States
- Parikh, Chirag R., Johns Hopkins Medicine, Baltimore, Maryland, United States
Group or Team Name
- Kidney Precision Medicine Project (KPMP).
Background
Urine proteomics may identify proteins specifically excreted by the kidney that provide mechanistic insights into future adverse kidney outcomes.
Methods
In 174 patients (48% with acute kidney injury [AKI]) from the Assessment, Serial Evaluation, and Subsequent Sequelae in AKI (ASSESS-AKI) cohort, we used Olink to profile 2783 urine proteins in samples from 3 months after index hospitalization. We used linear mixed-effects models to identify proteins associated with estimated glomerular filtration rate (eGFR) decline after 4.8 years (median) follow-up. We used weighted correlation network analysis to determine proteins’ cellular enrichment in the kidney transcriptome (single-cell/nucleus RNA sequencing, spatial transcriptomics) in 20 patients with diverse causes of AKI who received research kidney biopsy from the Kidney Precision Medicine Project.
Results
The ASSESS-AKI patients had median (IQR) age of 67 (59-75) years and median (IQR) eGFR of 65 (41-85) ml/min/1.73m2 at 3 months post-discharge. We identified 387 and 10 proteins associated with faster and slower eGFR decline, respectively (Fig. 1A), including 283 expressed by kidney cells and 114 not expressed. The expression formed 3 clusters enriched in the proximal tubule (Module 1 [M1], Fig.1B), degenerative tubule and myeloid cells (M2), and stromal cells (M3), and correlated with histopathological features of AKI, such as tubular injury, interstitial inflammation, and fibrosis (Fig.1C).
Conclusion
By integrating the urine proteome and kidney transcriptome, we identified degenerative tubular injury, inflammation, and fibrosis as pathways associated with eGFR decline in recently hospitalized patients.
Funding
- NIDDK Support