TY - JOUR
T1 - Metabolomics of Dietary Acid Load and Incident Chronic Kidney Disease
AU - Tariq, Anam
AU - Chen, Jingsha
AU - Yu, Bing
AU - Boerwinkle, Eric
AU - Coresh, Josef
AU - Grams, Morgan E.
AU - Rebholz, Casey M.
N1 - Funding Information:
Support: The ARIC study has been funded by the National Heart, Lung, and Blood Institute (NHLBI), United States, National Institutes of Health (NIH), United States, Department of Health and Human Services, United States (HHSN262801700001I, HHSN262801700002I, HHSN262801700003I, HHSN262801700004I, HHSN262801700005I). Funding support for “Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium” was provided by the NIH through the American Recovery and Reinvestment Act of 2009 (ARRA) ( 5RC2HL102419 ). Metabolomics measurements were sponsored by the National Human Genome Research Institute, United States (3U01HG004402-02S1). Funding for laboratory testing and biospecimen collection at ARIC Visit 6 was supported by grant R01DK089174 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), United States of the National Institutes of Health (NIH). C.M.R. was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) ( K01 DK107782, R03 DK128386 ) and the NHLBI, United States (R21 HL143089, R56 HL153178). M.E.G. was supported by the NIDDK ( K08 DK092287 ). A.T. was supported by the NIDDK, United States of the NIH under award number T32DK007732 .
Funding Information:
Support: The ARIC study has been funded by the National Heart, Lung, and Blood Institute (NHLBI), United States, National Institutes of Health (NIH), United States, Department of Health and Human Services, United States (HHSN262801700001I, HHSN262801700002I, HHSN262801700003I, HHSN262801700004I, HHSN262801700005I). Funding support for “Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium” was provided by the NIH through the American Recovery and Reinvestment Act of 2009 (ARRA) (5RC2HL102419). Metabolomics measurements were sponsored by the National Human Genome Research Institute, United States (3U01HG004402-02S1). Funding for laboratory testing and biospecimen collection at ARIC Visit 6 was supported by grant R01DK089174 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), United States of the National Institutes of Health (NIH). C.M.R. was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (K01 DK107782, R03 DK128386) and the NHLBI, United States (R21 HL143089, R56 HL153178). M.E.G. was supported by the NIDDK (K08 DK092287). A.T. was supported by the NIDDK, United States of the NIH under award number T32DK007732.
Publisher Copyright:
© 2021 National Kidney Foundation, Inc.
PY - 2022/5
Y1 - 2022/5
N2 - Objective: Blood biomarkers of dietary intake are more objective than self-reported dietary intake. Metabolites associated with dietary acid load were previously identified in 2 chronic kidney disease (CKD) populations. We aimed to extend these findings to a general population, replicating their association with dietary acid load, and investigating whether the individual biomarkers were prospectively associated with incident CKD. Methods: Among 15,792 participants in the Atherosclerosis Risk in Communities cohort followed up from 1987 to 1989 (baseline) to 2019, we evaluated 3,844 black and white men and women with dietary and metabolomic data in cross-sectional and prospective analyses. We hypothesized that a higher dietary acid load (using equations for potential renal acid load and net endogenous acid production) was associated with lower serum levels of 12 previously identified metabolites: indolepropionylglycine, indolepropionate, N-methylproline, N-δ-acetylornithine, threonate, oxalate, chiro-inositol, methyl glucopyranoside, stachydrine, catechol sulfate, hippurate, and tartronate. In addition, we hypothesized that lower serum levels of these 12 metabolites were associated with higher risk of incident CKD. Results: Eleven out of 12 metabolites were significantly inversely associated with dietary acid load, after adjusting for demographics, socioeconomic status, health behaviors, health status, and estimated glomerular filtration rate: indolepropionylglycine, indolepropionate, N-methylproline, threonate, oxalate, chiro-inositol, catechol sulfate, hippurate, methyl glucopyranoside (α + β), stachydrine, and tartronate. N-methylproline was inversely associated with incident CKD (hazard ratio: 0.95, 95% confidence interval: 0.91, 0.99, P =.01). The metabolomic biomarkers of dietary acid load significantly improved prediction of elevated dietary acid load estimated using dietary data, beyond covariates (difference in C statistics: 0.021-0.077, P ≤ 1.08 × 10−3). Conclusion: Inverse associations between candidate biomarkers of dietary acid load were replicated in a general population. N-methylproline, representative of citrus fruit consumption, is a promising marker of dietary acid load and could represent an important pathway between dietary acid load and CKD.
AB - Objective: Blood biomarkers of dietary intake are more objective than self-reported dietary intake. Metabolites associated with dietary acid load were previously identified in 2 chronic kidney disease (CKD) populations. We aimed to extend these findings to a general population, replicating their association with dietary acid load, and investigating whether the individual biomarkers were prospectively associated with incident CKD. Methods: Among 15,792 participants in the Atherosclerosis Risk in Communities cohort followed up from 1987 to 1989 (baseline) to 2019, we evaluated 3,844 black and white men and women with dietary and metabolomic data in cross-sectional and prospective analyses. We hypothesized that a higher dietary acid load (using equations for potential renal acid load and net endogenous acid production) was associated with lower serum levels of 12 previously identified metabolites: indolepropionylglycine, indolepropionate, N-methylproline, N-δ-acetylornithine, threonate, oxalate, chiro-inositol, methyl glucopyranoside, stachydrine, catechol sulfate, hippurate, and tartronate. In addition, we hypothesized that lower serum levels of these 12 metabolites were associated with higher risk of incident CKD. Results: Eleven out of 12 metabolites were significantly inversely associated with dietary acid load, after adjusting for demographics, socioeconomic status, health behaviors, health status, and estimated glomerular filtration rate: indolepropionylglycine, indolepropionate, N-methylproline, threonate, oxalate, chiro-inositol, catechol sulfate, hippurate, methyl glucopyranoside (α + β), stachydrine, and tartronate. N-methylproline was inversely associated with incident CKD (hazard ratio: 0.95, 95% confidence interval: 0.91, 0.99, P =.01). The metabolomic biomarkers of dietary acid load significantly improved prediction of elevated dietary acid load estimated using dietary data, beyond covariates (difference in C statistics: 0.021-0.077, P ≤ 1.08 × 10−3). Conclusion: Inverse associations between candidate biomarkers of dietary acid load were replicated in a general population. N-methylproline, representative of citrus fruit consumption, is a promising marker of dietary acid load and could represent an important pathway between dietary acid load and CKD.
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U2 - 10.1053/j.jrn.2021.05.005
DO - 10.1053/j.jrn.2021.05.005
M3 - Article
C2 - 34294549
AN - SCOPUS:85111032332
SN - 1051-2276
VL - 32
SP - 292
EP - 300
JO - Journal of Renal Nutrition
JF - Journal of Renal Nutrition
IS - 3
ER -