Abstract: FR-PO880
Serum and Urine Metabolites and Kidney Function in an Older Community-Based Population
Session Information
- Geriatric Nephrology
November 03, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Geriatric Nephrology
- 1300 Geriatric Nephrology
Authors
- Yeo, Wan-Jin, NYU Langone Health, New York, New York, United States
- Surapaneni, Aditya L., NYU Langone Health, New York, New York, United States
- Chen, Jingsha, Johns Hopkins University Department of Epidemiology, Baltimore, Maryland, United States
- Sekula, Peggy, Institute of Genetic Epidemiology, University of Freiburg, Freiburg, Germany
- Kottgen, Anna, Johns Hopkins University Department of Epidemiology, Baltimore, United States
- Yu, Bing, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, United States
- Rebholz, Casey, Johns Hopkins University Department of Epidemiology, Baltimore, Maryland, United States
- Coresh, Josef, Johns Hopkins University Department of Epidemiology, Baltimore, Maryland, United States
- Grams, Morgan, NYU Langone Health, New York, New York, United States
- Waikar, Sushrut S., Boston University School of Medicine, Boston, Massachusetts, United States
- Rhee, Eugene P., Massachusetts General Hospital Division of Nephrology, Boston, Massachusetts, United States
- Schmidt, Insa Marie, Boston University School of Medicine, Boston, Massachusetts, United States
- Schlosser, Pascal, Johns Hopkins University Department of Epidemiology, Baltimore, United States
Background
Metabolites represent a cellular read-out of ongoing processes underlying states of health and disease.
Methods
We evaluated cross-sectional and longitudinal associations between 1254 serum and 1398 urine metabolites (untargeted, Metabolon HD4, 713 present in both biofluids) and kidney function in 1613 participants of the Atherosclerosis Risk in Communities (ARIC) Study (visit 5; mean age 76 years, 56.1% women, mean eGFR and urine albumin-to-creatinine levels (ACR) of 62 mL/min/1.73m2 and 4 mg/g, respectively). All analyses were comprehensively adjusted including for baseline eGFR and ACR.
Results
In cross-sectional analysis, 674 serum and 542 urine metabolites were associated with eGFR (p<4E-5), including 245 in both biofluids. Fewer metabolites (75 serum and 92 urine metabolites, including 7 shared across both biofluids) were associated with ACR. Five metabolites, including 2 unnamed metabolites, were significantly associated with both eGFR and albuminuria (Table 1). In longitudinal analysis, higher levels of N2,N2-dimethylguanosine and X-25422 were associated with greater risk of eGFR decline (defined as 40% decrease over a mean follow-up of 6.6 years) and increase in albuminuria (defined as doubling of UACR levels) in both serum and urine (p<0.05). Next, we estimated the relative fractional excretion (rFE) of metabolites shared in both biofluids (713). The rFE of 482 metabolites had negative associations with eGFR, whereas 5 metabolites had positive associations (p<7E-5). The most negative associations with eGFR were for 5-methylthioribose and 5-oxoproline and the most positive was for gamma-glutamylglutamine. Thirty-eight rFE of metabolites were associated with eGFR decline (p<0.05), including guanine, S-methylcysteine sulfoxide, and hypoxanthine which were protective for eGFR decline, but none met Bonferroni significance (p<5E-5).
Conclusion
In summary, untargeted metabolomic profiling can identify metabolites of interest in kidney disease. Notably, the metabolomic coverage was markedly increased by the inclusion of both matrices.
Table 1: Metabolites associated with both eGFR and albuminuria.
Funding
- NIDDK Support