Summary of Study ST000398
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 PR000311. The data can be accessed directly via it's Project DOI: 10.21228/M8G020 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST000398 |
| Study Title | Metabolic profiling of maternal urine can aid clinical management of Gestational Diabetes Mellitus (GDM) |
| Study Type | Search for non-treated and treated GDM biomarkers in urine |
| Study Summary | NMR metabolomics study of maternal urine of 1) GDM women at the time of diagnosis and before treatment, to define the urine metabolic profile of untreated GDM, and of 2) GDM women treated using diet control alone or with the addition of insulin, to identify treatment-resistant and treatment-responsive metabolic pathways and, hence, evaluate treatment efficacy, and 3) GDM treatment prediction at the time of diagnosis, with the aim of finding potential predictive markers of future treatment requirements based on each individual metabotype. |
| Institute | University of Aveiro |
| Department | CICECO-Department of Chemistry |
| Last Name | Gil |
| First Name | Ana |
| Address | CICECO-Department of Chemistry, University of Aveiro |
| agil@ua.pt | |
| Phone | none |
| Submit Date | 2016-04-20 |
| Num Groups | 5 |
| Total Subjects | 98 |
| Analysis Type Detail | NMR |
| Release Date | 2016-06-18 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR000311 |
| Project DOI: | doi: 10.21228/M8G020 |
| Project Title: | Urine metabolomics for the study of Gestational Diabetes Mellitus |
| Project Summary: | A urine NMR metabolomics study using a variable selection methodology to reduce uninformative variability enables a metabolic signature of gestational diabetes mellitus (GDM) to be identified at the time of diagnosis. This signature comprises relevant changes in 12 NMR metabolites/resonances and qualitative variations in a number of additional metabolites. |
| Institute: | University of Aveiro |
| Department: | CICECO-Department of Chemistry |
| Last Name: | Gil |
| First Name: | Ana |
| Address: | CICECO-Department of Chemistry, University of Aveiro |
| Email: | agil@ua.pt |
| Phone: | none |
