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.

Show all samples  |  Perform analysis on untargeted data  
Download mwTab file (text)   |  Download mwTab file(JSON)   |  Download data files (Contains raw data)
Study IDST002552
Study TitleBiomarker discovery in galactosemia: Metabolomics with UPLC/HRMS in dried blood spots
Study TypeNewborn screening
Study SummaryGalactosemia (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 NameAlMalki
First NameReem
AddressKing Fahad road, Riyadh, KSA, 00000, Saudi Arabia
Email439203044@student.ksu.edu.sa
Phone+966534045397
Submit Date2023-03-28
Num Groups2
PublicationsYes
Raw Data AvailableYes
Raw Data File Type(s)raw(Waters)
Analysis Type DetailLC-MS
Release Date2023-04-24
Release Version1
Reem AlMalki Reem AlMalki
https://dx.doi.org/10.21228/M86F07
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001644
Project DOI:doi: 10.21228/M86F07
Project Title:Biomarker discovery in galactosemia: Metabolomics with UPLC/HRMS in dried blood spots
Project Type:newborn screening
Project 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
Department:Metabolomics
Laboratory:Metabolomics
Last Name:AlMalki
First Name:Reem
Address:King Fahad road, Riyadh, KSA, 00000, Saudi Arabia
Email:439203044@student.ksu.edu.sa
Phone:+966534045397

Subject:

Subject ID:SU002652
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Gender:Male and female
Species Group:Mammals

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Factor
SA256253GALT_NR23_21752092Ctrl
SA256254GALT_NR22_21799695Ctrl
SA256255GALT_NR24_21799792Ctrl
SA256256GALT_NR25_21757006Ctrl
SA256257GALT_NR26_21799932Ctrl
SA256258GALT_NR21_21756964Ctrl
SA256259GALT_NR19_21756645Ctrl
SA256260GALT_NR16_21794987Ctrl
SA256261GALT_NR15_21798906Ctrl
SA256262GALT_NR17_21798924Ctrl
SA256263GALT_NR18_21756973Ctrl
SA256264GALT_NR28_21799871Ctrl
SA256265GALT_NR20_21798933Ctrl
SA256266GALT_NR29_21798155Ctrl
SA256267GALT_NR37_21798960Ctrl
SA256268GALT_NR36_21799941Ctrl
SA256269GALT_NR38_21783126Ctrl
SA256270GALT_NR39_21799677Ctrl
SA256271GALT_NR40_21798479Ctrl
SA256272GALT_NR35_21799853Ctrl
SA256273GALT_NR34_21799978Ctrl
SA256274GALT_NR30_21799710Ctrl
SA256275GALT_NR31_21756654Ctrl
SA256276GALT_NR32_21799969Ctrl
SA256277GALT_NR33_21798474Ctrl
SA256278GALT_NR14_21756609Ctrl
SA256279GALT_NR13_21756636Ctrl
SA256280GALT_NR5_21756742Ctrl
SA256281GALT_NR6_21799686Ctrl
SA256282GALT_NR3_21799729Ctrl
SA256283GALT_NR2_21799835Ctrl
SA256284GALT_NR1_21799701Ctrl
SA256285GALT_NR7_21798410Ctrl
SA256286GALT_NR4_21752056Ctrl
SA256287GALT_NR11_21798863Ctrl
SA256288GALT_NR8_21756982Ctrl
SA256289GALT_NR10_21756779Ctrl
SA256290GALT_NR12_21798942Ctrl
SA256291GALT_NR9_21756292Ctrl
SA256292GALT_AB8_21112212Patient
SA256293GALT_AB9_21775172Patient
SA256294GALT_AB6_21770900Patient
SA256295GALT_AB3_21745506Patient
SA256296GALT_AB2_21780341Patient
SA256297GALT_AB12_21780943Patient
SA256298GALT_AB4_21100457Patient
SA256299GALT_AB19_21744172Patient
SA256300GALT_AB18_21012310Patient
SA256301GALT_AB1_20587853Patient
SA256302GALT_AB17_20758512Patient
SA256303GALT_AB16_20428037Patient
SA256304GALT_AB14_21799507Patient
SA256305GALT_AB15_21745524Patient
SA256306GALT_AB13_21769782Patient
Showing results 1 to 54 of 54

Collection:

Collection ID:CO002645
Collection Summary:Fifty-four DBS samples were collected from genetically and biochemically confirmed GAL (n = 15) patients at King Faisal Specialist Hospital and Research center (KFSHRC) and healthy controls (n = 39).
Collection Protocol Filename:Characteristics of the study population and metabolites extraction
Sample Type:Blood (plasma)

Treatment:

Treatment ID:TR002664
Treatment Summary:no treatment use

Sample Preparation:

Sampleprep ID:SP002658
Sampleprep Summary:Metabolites extraction The polar metabolites were extracted from DBS samples using our developed standard protocol (Jacob et al., 2018). Five 3 mm size DBS disks were used for metabolite extraction using methanol, acetonitrile, and water (40:40:20%) for protein precipitation. The mixture was mixed at 25°C and 600 rpm for 2 hours in a thermomixer (Eppendorf, Germany). Pooled QC samples were prepared using aliquots from the study samples. Afterward, the supernatants were transferred to another set of tubes, evaporated in SpeedVacc (Christ, City, Germany), and stored at −80°C until LCMS analysis.
Sampleprep Protocol Filename:Metabolites extraction
Processing Storage Conditions:-20℃
Extract Storage:Room temperature

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

Chromatography:

Chromatography ID:CH003114
Methods Filename:UPLCHRMS
Instrument Name:Waters Acquity
Column Name:Waters Acquity UPLC XSelect HSS C18 (100 × 2.1mm, 2.5um)
Column Temperature:55
Flow Gradient:0–16 min 95%–5% A, 16–19 min 5% A, 19–20 min 5%–95% A, and 20–22 min, 95%– 95% A
Flow Rate:300 μl/min.
Solvent A:100% water; 0.1% formic acid
Solvent B:50% methanol/50% acetonitrile; 0.1% formic acid
Chromatography Type:Reversed phase

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
  logo