Summary of project PR000020
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000020. The data can be accessed directly via it's Project DOI: 10.21228/M8PP4H This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Project ID: | PR000020 |
| Project DOI: | doi: 10.21228/M8PP4H |
| Project Title: | Correlation of urine metabolomics profile with eGFR, ACR and dietary acid load in elderly and non-elderly patients with CKD |
| Project Type: | Metabolomics |
| Project Summary: | Abstract. Although urine is an easily obtained biological fluid that is useful for metabolomics analysis and holds promise for uncovering metabolic differences between normal and disease states, it is underutilized for biomarker discovery. Urine composition can reflect the state of different organs, however, kidney cells determine the final concentrations of urine metabolites. Therefore, specific aspects of kidney function likely correlate with a particular metabolic signature that reflects modulation of metabolic pathways involved in specific entities such as progression of chronic kidney disease (CKD). Beyond a decline in glomerular filtration rate (GFR) and proteinuria/albuminuria, there are limited markers of CKD available. Moreover, the serious limitations of serum creatinine and albuminuria as measures of kidney function are widely appreciated, limiting their reliability for ascribing risk for CKD progression, particularly at an early CKD stage; that most amenable for therapeutic intervention. There is a conspicuous gap between limited treatment options for CKD, our inability to predict those who will progress to kidney failure, and epidemiological data indicating that 26 million Americans, aged 20 years or older, have CKD at Stage 2 or higher. Since patients with CKD have an exceptionally high incidence of death from cardiovascular disease, detection of and early intervention in CKD, assumes great importance for the public health. There are no metabolomics profile data available from large population studies that have the power to correlate traditional markers of CKD with urine metabolomics data. The objective of this pilot proposal is to explore the feasibility of correlating the urine metabolomics profile from two existing large databases that provide measures of kidney function (defined by eGFR and albuminuria) and can be stratified according to age, gender, ethnicity, serum bicarbonate concentration, and dietary acid load. Our long-term goal is to establish an approach for a future large scale translational metabolomics project, that will define standards for urine sample collection and processing for metabolomics analysis, standardize procedures that normalize metabolite concentrations to account for variations in urine concentration, define specific sets of urine metabolites as markers of early stage CKD, and develop assays for these metabolites that are cost effective for clinical use in different patient populations. Ultimately we plan to use a systems biology approach for pathway analysis and validation, which may point to specific enzymes with potentially significant pathophysiological roles in the early stages and progression of CKD. A unique advantage of this proposal is the source of urine samples, namely two large studies: the African American Diabetes Heart Study (AADHS), and the Health, Aging, and Body Composition Study (H ABC) cohort of elderly adults. We are enthusiastic about the current proposal because of our preliminary analysis of the effect of dietary acid load on CKD progression in the DHS database, and kidney function (eGFR) in elderly subjects in the H ABC study. The analysis was prompted by recently published human studies, which demonstrate that high dietary acid load facilitate the progression of CKD. Western diet, which is high in protein, generates a high acid load, and provokes well-known renal adaptive metabolic pathways to increase acid excretion. How and when the adaptive response of the kidney to high acid load or metabolic acidosis becomes maladaptive is unknown. Our gene microarray analysis of kidney tissue in a mouse model of metabolic acidosis (knockout of the pH sensor GPR4) indicates that metabolic acidosis is associated with alterations of specific canonical pathways, which we anticipate will be reflected by modifications of broad sets of small metabolites in the urine. Our preliminary results obtained from patients in the European American cohort of the AADHS study revealed a significant correlation between serum bicarbonate (reflecting acid-base status) and the urine albumin to creatinine ratio (ACR), reflecting abnormal kidney function. The objective of this pilot proposal is to test the feasibility of correlating the urine metabolomics profile with the parameters reflecting dietary acid load and level of kidney function. Having assembled an outstanding team of investigators with background in kidney pathology, aging, and acid-base regulation with access to samples from two major studies with detailed and standardized characterization of phenotypes, we expect that this pilot analysis will provide sufficient support for the extension of these programs into R01 projects supported by NIDDK and NIA, and ultimately expand into a large scale translational metabolomics kidney project. |
| Institute: | Wake Forest University |
| Department: | Hypertension and Vascular Research Center |
| Laboratory: | Petrovic Laboratory |
| Last Name: | Petrovic |
| First Name: | Snezana |
| Address: | Wake Forest School of Medicine |
| Email: | snpetrov@wakehealth.edu |
| Phone: | 336-713-7213 |
| Funding Source: | NIH RTI RCMRC P&F study |
Summary of all studies in project PR000020
| Study ID | Study Title | Species | Institute | Analysis(* : Contains Untargted data) | Release Date | Version | Samples | Download(* : Contains raw data) |
|---|---|---|---|---|---|---|---|---|
| ST000021 (Availability TBA) | NMR based metabolomics of CKD | Homo sapiens | University of North Carolina | NMR | - | - | 108 | Not available |
| ST000132 (Availability TBA) | Metallomic Analysis of Chronic Kidney disease | Homo sapiens | University of North Carolina | MS | - | - | 99 | Not available |
