Dataset Information

Serum metabolomic profiling and incident CKD among African Americans.

ABSTRACT: Novel biomarkers that more accurately reflect kidney function and predict future CKD are needed. The human metabolome is the product of multiple physiologic or pathophysiologic processes and may provide novel insight into disease etiology and progression. This study investigated whether estimated kidney function would be associated with multiple metabolites and whether selected metabolomic factors would be independent risk factors for incident CKD.In total, 1921 African Americans free of CKD with a median of 19.6 years follow-up among the Atherosclerosis Risk in Communities Study were included. A total of 204 serum metabolites quantified by untargeted gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry was analyzed by both linear regression for the cross-sectional associations with eGFR (specified by the Chronic Kidney Disease Epidemiology Collaboration equation) and Cox proportional hazards model for the longitudinal associations with incident CKD.Forty named and 34 unnamed metabolites were found to be associated with eGFR specified by the Chronic Kidney Disease Epidemiology Collaboration equation with creatine and 3-indoxyl sulfate showing the strongest positive (2.8 ml/min per 1.73 m(2) per +1 SD; 95% confidence interval, 2.1 to 3.5) and negative association (-14.2 ml/min per 1.73 m(2) per +1 SD; 95% confidence interval, -17.0 to -11.3), respectively. Two hundred four incident CKD events with a median follow-up time of 19.6 years were included in the survival analyses. Higher levels of 5-oxoproline (hazard ratio, 0.70; 95% confidence interval, 0.60 to 0.82) and 1,5-anhydroglucitol (hazard ratio, 0.68; 95% confidence interval, 0.58 to 0.80) were significantly related to lower risk of incident CKD, and the associations did not appreciably change when mutually adjusted.These data identify a large number of metabolites associated with kidney function as well as two metabolites that are candidate risk factors for CKD and may provide new insights into CKD biomarker identification.

SUBMITTER: Yu B

PROVIDER: S-EPMC4123405 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Serum metabolomic profiling and incident CKD among African Americans.

Yu Bing B Zheng Yan Y Nettleton Jennifer A JA Alexander Danny D Coresh Josef J Boerwinkle Eric E

Clinical journal of the American Society of Nephrology : CJASN 20140710 8

<h4>Background and objectives</h4>Novel biomarkers that more accurately reflect kidney function and predict future CKD are needed. The human metabolome is the product of multiple physiologic or pathophysiologic processes and may provide novel insight into disease etiology and progression. This study investigated whether estimated kidney function would be associated with multiple metabolites and whether selected metabolomic factors would be independent risk factors for incident CKD.<h4>Design, se ...[more]

PMID: 25011442

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Project description:BackgroundLow-normal potassium is a risk factor for diabetes and may account for some of the racial disparity in diabetes risk. Aldosterone affects serum potassium and is associated with insulin resistance.ObjectivesWe sought to confirm the association between potassium and incident diabetes in an African-American cohort, and to determine the effect of aldosterone on this association.DesignWe studied participants from the Jackson Heart Study, an African-American adult cohort, who were without diabetes at baseline. With the use of logistic regression, we characterized the associations of serum, dietary, and urinary potassium with incident diabetes. In addition, we evaluated aldosterone as a potential effect modifier of these associations.ResultsOf 2157 participants, 398 developed diabetes over 8 y. In a minimally adjusted model, serum potassium was a significant predictor of incident diabetes (OR: 0.83; 95% CI: 0.74, 0.92 per SD increment in serum potassium). In multivariable models, we found a significant interaction between serum potassium and aldosterone (P = 0.046). In stratified multivariable models, in those with normal aldosterone (<9 ng/dL, n = 1163), participants in the highest 2 potassium quartiles had significantly lower odds of incident diabetes than did those in the lowest potassium quartile [OR (95% CI): 0.61 (0.39, 0.97) and 0.54 (0.33, 0.90), respectively]. Among those with high-normal aldosterone (≥9 ng/dL, n = 202), we found no significant association between serum potassium and incident diabetes. In these stratified models, serum aldosterone was not a significant predictor of incident diabetes. We found no statistically significant associations between dietary or urinary potassium and incident diabetes.ConclusionsIn this African-American cohort, we found that aldosterone may modify the association between serum potassium and incident diabetes. In participants with normal aldosterone, high-normal serum potassium was associated with a lower risk of diabetes than was low-normal serum potassium. Additional studies are warranted to determine whether serum potassium is a modifiable risk factor that could be a target for diabetes prevention. This trial was registered at clinicaltrials.gov as NCT00415415.

Project description:BackgroundHigh diet quality is associated with a lower risk of chronic diseases. Metabolomics can be used to identify objective biomarkers of diet quality.ObjectivesWe used metabolomics to identify serum metabolites associated with 4 diet indices and the components within these indices in 2 samples from African Americans and European Americans.MethodsWe studied cross-sectional associations between known metabolites and Healthy Eating Index (HEI)-2015, Alternative Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension Trial (DASH) diet, alternate Mediterranean diet (aMED), and their components using untargeted metabolomics in 2 samples (n1 = 1,806, n2 = 2,056) of the Atherosclerosis Risk in Communities study (aged 45-64 y at baseline). Dietary intakes were assessed using an FFQ. We used multivariable linear regression models to examine associations between diet indices and serum metabolites in each sample, adjusting for participant characteristics. Metabolites significantly associated with diet indices were meta-analyzed across 2 samples. C-statistics were calculated to examine if these candidate biomarkers improved prediction of individuals in the highest compared with lowest quintile of diet scores beyond participant characteristics.ResultsSeventeen unique metabolites (HEI: n = 6; AHEI: n = 5; DASH: n = 14; aMED: n = 2) were significantly associated with higher diet scores after Bonferroni correction in sample 1 and sample 2. Six of 17 significant metabolites [glycerate, N-methylproline, stachydrine, threonate, pyridoxate, 3-(4-hydroxyphenyl)lactate)] were associated with ≥1 dietary pattern. Candidate biomarkers of HEI, AHEI, and DASH distinguished individuals with highest compared with lowest quintile of diet scores beyond participant characteristics in samples 1 and 2 (P value for difference in C-statistics <0.02 for all 3 diet indices). Candidate biomarkers of aMED did not improve C-statistics beyond participant characteristics (P value = 0.930).ConclusionsA considerable overlap of metabolites associated with HEI, AHEI, DASH, and aMED reflects the similar food components and similar metabolic pathways involved in the metabolism of healthy diets in African Americans and European Americans.

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Serum metabolomic profiling and incident CKD among African Americans.

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Serum metabolomic profiling and incident CKD among African Americans.

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