Summary of Study ST002552
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 PR001644. The data can be accessed directly via it's Project DOI: 10.21228/M86F07 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 | ST002552 |
| Study Title | Biomarker discovery in galactosemia: Metabolomics with UPLC/HRMS in dried blood spots |
| Study Type | Newborn screening |
| Study Summary | Galactosemia (GAL) is an autosomal recessive genetic disorder characterized by galactose metabolism disturbances. GAL develops non-preventable life-threatening complications even with a reduced content of galactose and lactose patient’s diet. Thus, the underlying pathophysiology of long-term complications in GAL remains poorly understood. The current study used a metabolomics approach using ultra-performance liquid chromatography coupled with high-resolution mass spectrometry to investigate the metabolomic changes in the dried blood spots of 15 patients with GAL and 39 healthy individuals. Compared to the control group, 2,819 metabolites underwent significant changes in patients with GAL. In all, 480 human endogenous metabolites were identified, of which 209 and 271 were upregulated and downregulated, respectively. PA (8:0/LTE4) and ganglioside GT1c (d18:0/20:0) metabolites showed the most significant difference between GAL and the healthy group, with an area under the curve of 1 and 0.995, respectively. Additionally, our findings showed novel potential biomarkers for GAL, such as 17-alpha-estradiol-3-glucuronide and 16-alpha-hydroxy DHEA 3-sulfatediphosphate. In conclusion, this metabolomics study deepened the understanding of the pathophysiology of GAL and presented metabolites that might serve as potential prognostic biomarkers to monitor the progression or support the clinical diagnosis of GAL. |
| Institute | King Saud University |
| Last Name | AlMalki |
| First Name | Reem |
| Address | King Fahad road, Riyadh, KSA, 00000, Saudi Arabia |
| 439203044@student.ksu.edu.sa | |
| Phone | +966534045397 |
| Submit Date | 2023-03-28 |
| Num Groups | 2 |
| Publications | Yes |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Waters) |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-04-24 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN004202 | AN004203 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | Reversed phase | Reversed phase |
| Chromatography system | Waters Acquity | Waters Acquity |
| Column | Waters Acquity UPLC XSelect HSS C18 (100 × 2.1mm, 2.5um) | Waters Acquity UPLC XSelect HSS C18 (100 × 2.1mm, 2.5um) |
| MS Type | ESI | ESI |
| MS instrument type | QTOF | QTOF |
| MS instrument name | Waters Xevo-G2-S | Waters Xevo-G2-S |
| Ion Mode | POSITIVE | NEGATIVE |
| Units | peak area | peak area |
MS:
| MS ID: | MS003949 |
| Analysis ID: | AN004202 |
| Instrument Name: | Waters Xevo-G2-S |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The DIA data were collected with a Masslynx™ V4.1 workstation in continuum mode (Waters Inc., Milford, MA, USA). The raw MS data were processed following a standard pipeline using the Progenesis QI v.3.0 software. |
| Ion Mode: | POSITIVE |
| MS ID: | MS003950 |
| Analysis ID: | AN004203 |
| Instrument Name: | Waters Xevo-G2-S |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The DIA data were collected with a Masslynx™ V4.1 workstation in continuum mode (Waters Inc., Milford, MA, USA). The raw MS data were processed following a standard pipeline using the Progenesis QI v.3.0 software. |
| Ion Mode: | NEGATIVE |
