Abstract: TH-PO920
Metabolomics Analysis of Urinary Biomarkers That Correlate with Kidney Injury in Diabetic African American Men
Session Information
- Diabetic Kidney Disease: Biomarkers, Pathogenesis
November 07, 2019 | Location: Exhibit Hall, Walter E. Washington Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 602 Diabetic Kidney Disease: Clinical
Authors
- Newman, Heather A., North Carolina A&T State University, Greensboro, North Carolina, United States
- Ongeri, Elimelda Moige, North Carolina A&T State University, Greensboro, North Carolina, United States
- Harrison, Scott H., North Carolina A&T State University, Greensboro, North Carolina, United States
- Jegede, Olugbemiga E., Cone Health, Greensboro, North Carolina, United States
- Newman, Robert H., North Carolina A&T State University, Greensboro, North Carolina, United States
Background
African Americans (AA) are disproportionately burdened by diabetes and diabetic kidney disease (DKD). However, little is known about the cellular and molecular mechanisms underlying the onset and progression of DKD in this population. This is due, in part, to the fact that AAs are often underrepresented in biomedical research. We recently reported undiagnosed kidney injury in a significant proportion of diabetic AA men served by a community clinic in Greensboro, NC. The goal of the current study was to determine the association between specific metabolites and kidney injury in this population.
Methods
We used Biocrates Absolute IDQ p400 kits together with high-resolution liquid chromatography-mass spectrometry to analyze fasting urine samples from three groups of AA men; 1) diabetics with DKD (n=10), 2) diabetics but no diagnosed DKD (DM; n=55), and 3) age-matched non-diabetic controls (ND; n=15). Patients in the DM group were further stratified based on their urinary albumin-to-creatinine ratios (UACR) into normo- (UACR<30 mg/g; n=28), micro- (30 mg/g<UACR < 300 mg/g; n=20); and macroalbuminuria (UACR>300 mg/g; n=7). The concentrations of metabolites were normalized to the urinary creatinine levels, and compared through linear mixed models.
Results
The differentiating metabolites included glycerides, cholesterol esters, sphingolipids, glycerophospholipids, biogenic amines and amino acids. The levels of several metabolites correlated with UACR. These include the Pro and the Arg derivative, citrulline, and three biogenic amines (kynurenine, 4-hydroxyproline, and a-aminoadipic acid). 87 urine metabolites exhibited levels above the limit of detection of the assay.
Conclusion
The current data suggest that key metabolic pathways are altered in diabetes and DKD for this population. For instance, proline is a precursor during the biosynthesis of both 4-hydroxyproline and citrulline. Likewise, citrulline is also involved in nitric oxide production, consistent with our previous observation that inflammation markers correlated with severity of DKD in this population. Together, the metabolic biomarkers offer insights into the cellular and metabolic pathways that are dysregulated during the development of DKD in this population.
Funding
- NIDDK Support