Summary of Study ST001642
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 PR001050. The data can be accessed directly via it's Project DOI: 10.21228/M8ZX18 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Study ID | ST001642 |
| Study Title | Lipidomics in high-risk subjects for the identification of integrated biomarker signatures of type 1 diabetes |
| Study Summary | We present the lipidome of plasma collected from high-risk type 1 diabetes subjects. The methyl tert-butyl ether (MTBE) method was used for lipid extraction, followed by high performance liquid chromatography (HPLC) tandem mass spectrometry (LC-MS/MS) using a Q Exactive Orbitrap mass spectrometer and an Accela 600 HPLC. Lipid species were identified and quantified by analyzing the raw files in LipidSearch 4.2. Further analysis was conducted using Graphpad Prism and Ingenuity Pathway Analysis (IPA). |
| Institute | University of Miami |
| Last Name | Bhattacharya |
| First Name | Sanjoy |
| Address | 1638 NW 10th Avenue, Room 706-A, Miami, FL 33136 |
| sbhattacharya@med.miami.edu | |
| Phone | 305-482-4103 |
| Submit Date | 2021-01-06 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2021-01-25 |
| Release Version | 1 |
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Project:
| Project ID: | PR001050 |
| Project DOI: | doi: 10.21228/M8ZX18 |
| Project Title: | Parallel multi-omics in high-risk subjects for the identification of integrated biomarker signatures of 4 type 1 diabetes |
| Project Summary: | Biomarkers are of paramount importance for early disease detection and are particularly valuable in type 1 diabetes (T1D) to prevent significant β cell loss before the onset of clinical symptoms. Thus far, single-omics studies have failed to identify such T1D biomarkers. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics. Blood from human subjects at high risk for T1D (and healthy controls; n=4 each) were subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to the controls. |
| Institute: | University of Miami |
| Last Name: | Bhattacharya |
| First Name: | Sanjoy |
| Address: | 1638 NW 10th Avenue, Room 706-A, Miami, FL 33136 |
| Email: | sbhattacharya@med.miami.edu |
| Phone: | 305-482-4103 |
