Abstract: SA-OR042
Metabolomics of CKD Progression in CRIC and AASK
Session Information
- Biomarkers in CKD
November 09, 2019 | Location: 152, Walter E. Washington Convention Center
Abstract Time: 05:18 PM - 05:30 PM
Category: CKD (Non-Dialysis)
- 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Rhee, Eugene P., Massachusetts General Hospital, Newton, Massachusetts, United States
- Zheng, Zihe, University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Grams, Morgan, Johns Hopkins University, Baltimore, Maryland, United States
- Xie, Dawei, University of Pennsylvania School of Medicine Center for Clinical Epidemiology and Biostatistics, Philadelphia, Pennsylvania, United States
- Waikar, Sushrut S., Harvard Medical School, Boston, Massachusetts, United States
- Rebholz, Casey, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States
- Denburg, Michelle, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
- Kimmel, Paul L., National Institute of Diabetes and Digestive Kidney Diseases (NIDDK), Bethesda, Maryland, United States
- Coresh, Josef, Welch Center for Prevention, Epidemiology & Clinical Research, Baltimore, Maryland, United States
- Feldman, Harold I., University of Pennsylvania, Philadelphia, Pennsylvania, United States
Group or Team Name
- CKD Biomarkers Consortium
Background
Non-targeted metabolomics is a promising tool for the identification of novel markers of CKD progression, with the goal to improve CKD diagnosis, prognosis, and therapy.
Methods
We examined the association between blood metabolites and CKD progression, defined as subsequent development of ESRD or eGFR halving. Discovery analysis was performed with the Broad Institute platform in 1800 randomly selected participants of the CRIC study. We fit Cox proportional hazards models, adjusting for age, gender, center, race/ethnicity/APOL1, CVD, smoking, alcohol, physical activity, SBP, diabetes, BMI, UPCR, and eGFR. Statistical significance was determined at a FDR <5%. For replication, we examined data generated with the Metabolon platform for 962 participants of the AASK study, adjusting for age, sex, study arm, smoking, CVD, BMI, SBP, UPCR, and mGFR.
Results
In CRIC, >160 of 547 metabolites were associated with the composite of ESRD or eGFR halving in unadjusted analysis, but only 9 metabolites remained significant following full adjustment (Fig). This attenuation in associations was driven by adjustment for eGFR. A subset of 7 of these metabolite were also measured in AASK, 3 of which were associated with CKD progression (Table): pseudouridine, 4-acetamidobutanoate, and guanidinoacetate.
Conclusion
In this large metabolomics study of CKD progression, 3 metabolites significantly associated with ESRD or eGFR halving, with discovery and replication performed in independent cohorts using different metabolomics platforms. More work is required to explore clinical utility and biologic implications.
| Metabolite | Pathway | CRIC HR | P | AASK HR | P |
| allantoin | purine | 1.43 | 4.4x10-6 | 1.00 | 0.99 |
| pseudouridine | pyrimidine | 2.90 | 7.5x10-6 | 1.86 | 3.1x10-9 |
| 4-acetamidobutanoate | polyamine | 1.88 | 8.4x10-6 | 1.26 | 0.0088 |
| myristoleate | fatty acid | 0.70 | 4.5x10-5 | 0.94 | 0.37 |
| trimethylbenzene | xenobiotic | 0.56 | 2.6x10-4 | ||
| triacylglycerol 49:3 | triglyceride | 0.69 | 1.6x10-4 | ||
| N6-acetyllysine | amino acid | 2.09 | 2.8x10-4 | 1.07 | 0.33 |
| tryptophan | amino acid | 0.54 | 6.4x10-4 | 0.89 | 0.081 |
| guanidinoacetate | creatine | 0.63 | 6.8x10-4 | 0.75 | 1.2x10-5 |
Funding
- NIDDK Support