Summary of Study ST001950
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 PR001237. The data can be accessed directly via it's Project DOI: 10.21228/M8TB0S This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
Study ID | ST001950 |
Study Title | Lipidome Alterations Following Mild Traumatic Brain Injury. |
Study Type | Untargeted Lipidomics |
Study Summary | Traumatic brain injury (TBI) poses a major health challenge, with tens of millions of new cases reported globally every year. Brain damage resulting from TBI can vary significantly due to factors including injury severity, diffusivity, modality, time delay relative to impact, and exposure to repeated injury events. Untargeted lipidomic analysis of Sprague-Dawley rat serum within 24 hours of mild single and repeat controlled cortical impact (CCI) injury events led to the discovery of biomarker candidates of TBI. Lipid biomarkers have a unique potential to serve as objective molecular measures of the body’s response to injury as their alteration in brain tissue can be more freely observed than for larger protein markers. Animal serum was analyzed via ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) in positive and negative ion modes. Known lipid species were identified through matching to in-house tandem MS databases. Machine learning and feature selection approaches were used to construct lipid panels capable of distinguishing serum from injured and uninjured animals across a range of injury severities and timepoints within the first day of injury. The best multivariate lipid panels had over 90% cross-validated sensitivity, selectivity, and accuracy and consisted of species from nine different lipid classes. These mapped onto sphingolipid signaling, autophagy, necroptosis and glycerophospholipid metabolism pathways, with FDR corrected p-values better than 0.05. |
Institute | Georgia Institute of Technology |
Department | Chemistry and Biochemistry |
Laboratory | Facundo Fernández |
Last Name | Gier |
First Name | Eric |
Address | 311 Ferst Drive, Atlanta, GA, 30318, USA |
egier3@gatech.edu | |
Phone | 2246221699 |
Submit Date | 2021-10-24 |
Num Groups | 6 |
Total Subjects | 32 |
Num Males | 14 |
Num Females | 18 |
Study Comments | LC-MS |
Raw Data Available | Yes |
Raw Data File Type(s) | mzML |
Analysis Type Detail | LC-MS |
Release Date | 2022-02-07 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR001237 |
Project DOI: | doi: 10.21228/M8TB0S |
Project Title: | Lipidome Alterations Following Mild Traumatic Brain Injury. |
Project Summary: | Traumatic brain injury (TBI) poses a major health challenge, with tens of millions of new cases reported globally every year. Brain damage resulting from TBI can vary significantly due to factors including injury severity, diffusivity, modality, time delay relative to impact, and exposure to repeated injury events. Untargeted lipidomic analysis of Sprague-Dawley rat serum within 24 hours of mild single and repeat controlled cortical impact (CCI) injury events led to the discovery of biomarker candidates of TBI. Lipid biomarkers have a unique potential to serve as objective molecular measures of the body’s response to injury as their alteration in brain tissue can be more freely observed than for larger protein markers. Animal serum was analyzed via ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) in positive and negative ion modes. Known lipid species were identified through matching to in-house tandem MS databases. Machine learning and feature selection approaches were used to construct lipid panels capable of distinguishing serum from injured and uninjured animals across a range of injury severities and timepoints within the first day of injury. The best multivariate lipid panels had over 90% cross-validated sensitivity, selectivity, and accuracy and consisted of species from nine different lipid classes. These mapped onto sphingolipid signaling, autophagy, necroptosis and glycerophospholipid metabolism pathways, with FDR corrected p-values better than 0.05. |
Institute: | Georgia Institute of Technology |
Department: | Chemistry and Biochemistry |
Laboratory: | Facundo Fernández |
Last Name: | Gier |
First Name: | Eric |
Address: | 311 Ferst Dr. Atlanta, GA, 30318, USA |
Email: | ericgier4@gmail.com |
Phone: | 2246221699 |