Abstract
Introduction
Chronic kidney disease (CKD) is a major public health challenge given its high global prevalence and associated risks of cardiovascular disease and progression to end stage renal disease. Although it is known that numerous metabolic changes occur in CKD patients, identifying novel metabolite associations with kidney function may enhance our understanding of the physiologic pathways relating to CKD.
Objectives
The objective of this study was to elucidate novel metabolite associations with kidney function among participants of two community-based cohorts with carefully ascertained metabolomics, kidney function, and covariate data.
Methods
Untargeted ultrahigh-performance liquid chromatography–tandem mass spectrometry was used to detect and quantify blood metabolites. We used multivariate adjusted linear regression to examine associations between single metabolites and creatinine-based estimated glomerular filtration rate (eGFRcr) among 1243 Bogalusa Heart Study (BHS) participants (median eGFRcr: 94.4, 5th–95th percentile: 66.0–119.6 mL/min/1.73 m2). Replication, determined by statistical significance and consistent effect direction, was tested using gold standard measured glomerular filtration rate (mGFR) among 260 Multi-Ethnic Study of Atherosclerosis (MESA) participants (median mGFR: 72.0, 5th–95th percentile: 43.5–105.0 mL/min/1.73 m2). All analyses used Bonferroni-corrected alpha thresholds.
Results
Fifty-one novel metabolite associations with kidney function were identified, including 12 from previously unrelated sub-pathways: N6-carboxymethyllysine, gulonate, quinolinate, gamma-CEHC-glucuronide, retinol, methylmalonate, 3-hydroxy-3-methylglutarate, 3-aminoisobutyrate, N-methylpipecolate, hydroquinone sulfate, and glycine conjugates of C10H12O2 and C10H14O2(1). Significant metabolites were generally inversely associated with kidney function and smaller in mass-to-charge ratio than non-significant metabolites.
Conclusion
The 51 novel metabolites identified may serve as early, clinically relevant, kidney function biomarkers.
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Data availability
The metabolomic data sets generated and analyzed during this study are available as supplementary data.
Abbreviations
- AGE:
-
Advanced glycation end-product
- BAIBA:
-
Β-aminoisobutyric acid
- BCAA:
-
Branched-chain amino acids
- BHS:
-
Bogalusa Heart Study
- BMI:
-
Body mass index
- CEHC:
-
Carboxyethyl hydroxychroman
- CKD:
-
Chronic kidney disease
- CML:
-
N6-carboxymethyllysine
- CVD:
-
Cardiovascular disease
- eGFR:
-
Estimated glomerular filtration rate
- eGFRcr:
-
Creatinine based eGFR
- GFR:
-
Glomerular filtration rate
- MESA:
-
Multi-Ethnic Study of Atherosclerosis
- mGFR:
-
Measured glomerular filtration rate
- MMA:
-
Methylmalonate
- SD:
-
Standard deviation
- UPLC–MS/MS:
-
Ultrahigh performance liquid chromatography–tandem mass spectrometry
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Acknowledgements
This study was funded by the National Institute on Aging of the NIH under award numbers R01AG041200 and R21AG051914. Research reported in this publication was partially supported by the National Institute of General Medical Sciences of the NIH under award number P20GM109036. We are grateful for the contribution of all staff members who were involved in conducting BHS and MESA. We extend our gratitude to the participants of BHS (many of whom have diligently participated since they were children) and MESA.
Funding
This study was funded by the National Institute on Aging of the NIH under Award Numbers R01AG041200 and R21AG051914. Research reported in this publication was partially supported by the National Institute of General Medical Sciences of the NIH under Award Number P20GM109036.
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JLN, TNK, JH, SL, LB, HH, AHA, and WC designed the study; JLN, CL, XG, MS, ACR, and XM analyzed the data; JMK contributed to the logistics and optimization of the untargeted metabolomics; CMR, JC, ASL, LAI, and MS performed replication of the study results; JLN made the figures; JLN and TNK drafted and revised the manuscript; all authors read and approved the final article.
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JLN, TNK, JH, SL, LB, HH, AHA, WC, CL, XG, MS, ACR, XM, CMR, JC, ASL, LAI, and MS declare that they have no conflict of interest. JMK is employed by Metabolon, Inc. He contributed to the logistics, optimization, and interpretation of the untargeted metabolomics. Metabolon, Inc. was not involved in the study design, statistical analysis, or interpretation of the results.
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Nierenberg, J.L., He, J., Li, C. et al. Novel associations between blood metabolites and kidney function among Bogalusa Heart Study and Multi-Ethnic Study of Atherosclerosis participants. Metabolomics 15, 149 (2019). https://doi.org/10.1007/s11306-019-1613-3
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DOI: https://doi.org/10.1007/s11306-019-1613-3