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Clin J Am Soc Nephrol. 2019 Feb 7. pii: CJN.10010818. doi: 10.2215/CJN.10010818. [Epub ahead of print]

Serum Metabolomic Alterations Associated with Proteinuria in CKD.

Author information

1
Welch Center for Prevention, Epidemiology, and Clinical Research.
2
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
3
Division of General Internal Medicine, and.
4
Department of Medicine, Boston University School of Medicine, Boston, Massachusetts.
5
Department of Biostatistics, Epidemiology, and Informatics and.
6
Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
7
Division of Kidney Urologic and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland.
8
Renal Division, Brigham and Women's Hospital, Boston, Massachusetts.
9
Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
10
Research and Development, Metabolon, Inc., Morrisville, North Carolina; and.
11
Division of Nephrology, Tufts Medical Center, Boston, Massachusetts.
12
Welch Center for Prevention, Epidemiology, and Clinical Research, mgrams2@jhmi.edu.
13
Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland.

Abstract

BACKGROUND AND OBJECTIVES:

Data are scarce on blood metabolite associations with proteinuria, a strong risk factor for adverse kidney outcomes. We sought to investigate associations of proteinuria with serum metabolites identified using untargeted profiling in populations with CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:

Using stored serum samples from the African American Study of Kidney Disease and Hypertension (AASK; n=962) and the Modification of Diet in Renal Disease (MDRD) study (n=620), two rigorously conducted clinical trials with per-protocol measures of 24-hour proteinuria and GFR, we evaluated cross-sectional associations between urine protein-to-creatinine ratio and 637 known, nondrug metabolites, adjusting for key clinical covariables. Metabolites significantly associated with proteinuria were tested for associations with CKD progression.

RESULTS:

In the AASK and the MDRD study, respectively, the median urine protein-to-creatinine ratio was 80 (interquartile range [IQR], 28-359) and 188 (IQR, 54-894) mg/g, mean age was 56 and 52 years, 39% and 38% were women, 100% and 7% were black, and median measured GFR was 48 (IQR, 35-57) and 28 (IQR, 18-39) ml/min per 1.73 m2. Linear regression identified 66 serum metabolites associated with proteinuria in one or both studies after Bonferroni correction (P<7.8×10-5), 58 of which were statistically significant in a meta-analysis (P<7.8×10-4). The metabolites with the lowest P values (P<10-27) were 4-hydroxychlorthalonil and 1,5-anhydroglucitol; all six quantified metabolites in the phosphatidylethanolamine pathway were also significant. Of the 58 metabolites associated with proteinuria, four were associated with ESKD in both the AASK and the MDRD study.

CONCLUSIONS:

We identified 58 serum metabolites with cross-sectional associations with proteinuria, some of which were also associated with CKD progression.

KEYWORDS:

AASK (African American Study of Kidney Disease and Hypertension); Cross-Sectional Studies; Diet; Linear Models; Renal Insufficiency, Chronic; chronic kidney disease; creatinine; glomerular filtration rate; hypertension; metabolism; phosphatidylethanolamine; proteinuria; risk factors

PMID:
30733224
DOI:
10.2215/CJN.10010818

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