Summary of Study ST002750

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 PR001713. The data can be accessed directly via it's Project DOI: 10.21228/M88X3T This work is supported by NIH grant, U2C- DK119886.

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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.

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Study IDST002750
Study TitleA Comprehensive Metabolomics Profile for Newborns with Maple syrup urine disease
Study TypeUntargeted LCMS
Study SummaryBackground: Maple syrup urine disease (MSUD) is a genetic inherited disorder caused by a defect in the branched-chain alpha-ketoacid dehydrogenase (BCKAD) complex function. This complex usually breaks down three amino acids: leucine, isoleucine, and valine. Therefore, abnormal activity in this process, can impact important bodily functions and lead to metabolic dysregulation related to the disease complications. A wide range of studied endogenous metabolites and dysregulated biomarkers and pathways provide a huge core support for the treatment and follow-up of newborn MSUD patients. Objectives: In this study, we aim to investigate MSUD’s distinctive profile in newborn MSUD patients using untargeted metabolomics to contribute to the growing knowledge surrounding MSUD and pathways involved for improving patient outcomes. Methods: In this study, untargeted metabolomics analyses via liquid chromatography–mass spectrometry was used to investigate metabolic changes in dry blood spot (DBS) of 22 MSUD newborns and 22 healthy newborns. Results: The metabolomics results revealed 1040 significantly dysregulated metabolites, where 303 and 737 were up- and down-regulated, respectively. 480 metabolites were annotated and 210 were identified as endogenous metabolites. The study identified potential biomarkers for MSUD such as L-Alloisoleucine and Methionine sulfoxide were upregulated in MSUD newborn compared to healthy newborns, while LysoPI was downregulated in MSUD newborns. In addition, the most affected pathways in MSUD Newborns were ascorbate and aldarate, Pentose and glucuronate interconversions and pyrimidine metabolism. Conclusion: Our results demonstrate metabolomics as a noninvasive strategy to understand the pathophysiology of the disease and is a promising tool to evaluate the potential biomarkers in the early diagnosis of newborn MSUD. Future studies are needed to correlate these dysregulated metabolites with defective mechanisms.
Institute
King Saud University
DepartmentBiochemistry
LaboratoryBiochemistry
Last NameAlotaibi
First NameAbeer
Address2808
Emailabeerotb12@gmail.com
Phone966551933703
Submit Date2023-05-29
Raw Data AvailableYes
Raw Data File Type(s)raw(Waters)
Analysis Type DetailLC-MS
Release Date2023-07-18
Release Version1
Abeer Alotaibi Abeer Alotaibi
https://dx.doi.org/10.21228/M88X3T
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001713
Project DOI:doi: 10.21228/M88X3T
Project Title:A Comprehensive Metabolomics Profile for Newborns with Maple syrup urine disease
Project Type:Untargeted LCMS
Project Summary:Investigation of MSUD’s distinctive profile in newborn MSUD patients using untargeted metabolomics
Institute:King Saud University
Department:Biochemistry
Laboratory:Biochemistry
Last Name:Alotaibi
First Name:Abeer
Address:2808
Email:abeerotb12@gmail.com
Phone:966551933703

Subject:

Subject ID:SU002857
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Age Or Age Range:</=14 days
Gender:Male and female
Human Inclusion Criteria:</=14 days, MSUD newborn DBS, Males and females
Human Exclusion Criteria:>14 days and any IEM's newborn other than MSUD, unknown gender

Factors:

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

mb_sample_id local_sample_id Sex Age_Days sample_type
SA28942118821169F 10 MSUD
SA28942221722019F 10 MSUD
SA28942321359910F 12 MSUD
SA28942421432000F 12 MSUD
SA28942520990701F 2 control
SA28942621323632F 3 MSUD
SA28942921756371F 5 control
SA28942721432578F 5 MSUD
SA28942821383148F 5 MSUD
SA28943021756797F 6 control
SA28943121903696F 6 control
SA28943221916609F 6 control
SA28943321915585F 6 control
SA28943421061334F 7 control
SA28943517943253F 8 MSUD
SA28943621309465F 8 MSUD
SA28943721916593F 9 control
SA28943821903669F 9 control
SA28944120882794M 10 control
SA28944220830861M 10 control
SA28943921439216M 10 MSUD
SA28944027192849M 10 MSUD
SA28944421751941M 11 control
SA28944317762490M 11 MSUD
SA28944521221237M 12 MSUD
SA28944621918555M 13 control
SA289447154124M 16 control
SA28944820990589M 3 MSUD
SA28944921288205M 3 MSUD
SA28945121051744M 4 control
SA28945021439094M 4 MSUD
SA28945321915628M 5 control
SA28945420972893M 5 control
SA28945521915503M 5 control
SA28945221917361M 5 MSUD
SA28945621483280M 6 MSUD
SA28945718725627M 6 MSUD
SA28945921812002M 7 control
SA28945820649047M 7 MSUD
SA28946017981165M 8 control
SA28946321798030M 9 control
SA28946419839244M 9 control
SA28946118097694M 9 MSUD
SA28946220741664M 9 MSUD
Showing results 1 to 44 of 44

Collection:

Collection ID:CO002850
Collection Summary:Forty-four DBS samples were collected form biochemically and genetically confirmed MSUD newborns (n=22) at King Faisal Specialist Hospital and Research Center (KFSHRC) and healthy controls (n=22). These healthy individuals were almost age-sex matched with MSUD's group (Female 53%). Samples from newborn patients and controls elder than 14 days were excluded from this study, as well as any IEM other than MSUD excluded.
Collection Protocol Filename:MSUD_biological_samples.docx
Sample Type:Dry Blood Spot
Storage Conditions:-80℃

Treatment:

Treatment ID:TR002866
Treatment Summary:No treatment used

Sample Preparation:

Sampleprep ID:SP002863
Sampleprep Summary:Briefly, one punch, a size 3.3 mm, DBS from MSUD newborn and healthy controls and were distributed in 96 V-shaped plate wells then immersed with 250 μL of Extraction solvent (Water: MeOH: ACN) [20:40:40%]. The samples were vortexed in thermomixer (Eppendrof, Germany) at 600 rpm, 25 ˚C, for 2hrs. The samples were spun down at 16.000 rpm, 4 ˚C, for 10 min. The supernatants were transferred into new 96 V-shaped plate and the punches discards, and then the samples were dried in a vacuum concentrator SpeedVac (Christ, City, Germany). Dry residue was re-dissolved in 100 μL of methanol/water with a ratio (1:1) earlier of LC-MS analysis.
Sampleprep Protocol Filename:Metabolites_extraction.docx
Extract Storage:Room temperature

Combined analysis:

Analysis ID AN004461 AN004462
Analysis type MS MS
Chromatography type Reversed phase Reversed phase
Chromatography system Waters Acquity UPLC Waters Acquity UPLC
Column Waters XSelect CSH C18 (100 x 2.1mm 2.5um) Waters XSelect CSH C18 (100 x 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:CH003349
Methods Filename:LC_MS_Metabolomics_MSUD.docx
Instrument Name:Waters Acquity UPLC
Column Name:Waters XSelect CSH C18 (100 x 2.1mm 2.5um)
Column Temperature:55
Flow Gradient:95–5% A [0–16 min], 5% A [16–19 min], 5–95% A [19–20 min], and 95–95% A [20–22 min].
Flow Rate:300 μL/min
Solvent A:0.1% formic acid: dH2O
Solvent B:0.1% formic acid: 50% MeOH and ACN
Chromatography Type:Reversed phase

MS:

MS ID:MS004208
Analysis ID:AN004461
Instrument Name:Waters Xevo-G2-S
Instrument Type:QTOF
MS Type:ESI
MS Comments:The DIA data were gathered with a Masslynx™ V4.1 Software (Waters Inc., Milford, MA, USA) in continuum mode. Quality control samples (QCs) were made with aliquots from all samples and introduced to the instrument after the randomization of each group, after 10 samples to validate the stability of the system (Aldubayan, Rodan, Berry, & Levy, 2017). Data and Statistical Analyses: The raw MS data were processed using a standard pipeline, beginning from an alignment depending on the mass to charge ratio (m/s) and the retention time (RT) of ion signals’, picking the best peak, followed by the filtering of signal depending on the quality of peak by utilizing the Progenesis QI (v.3.0) software (Waters Technologies, Milford, MA, USA). A multivariate statistics was applied by using MetaboAnalyst (v.5.0) (McGill University, Montreal, QB, Canada) (http://www.metaboanalyst.ca) (Pang et al., 2021). All the imported data-groups (compounds’ names also their raw abundances information) were Pareto scaled, log transformed and applied for creating partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models. The generated OPLS-DA model was measured through R2Y and Q2 values, that represents the fitness of the model and predictive ability, respectively (Worley & Powers, 2013). A univariate analysis was applied through Mass Profiler Professional (MPP) (v. 15.0) software (Agilent, Santa Clara, CA, USA). A volcano plot was applied to uncover significantly changed mass features based on a Moderated T-test, cut-off: no correction, p <0.05, FC 1.5. Heatmap analysis for altered features was performed using the Pearson distance measure according to the Pearson similarity test (Gu et al., 2020).
Ion Mode:POSITIVE
  
MS ID:MS004209
Analysis ID:AN004462
Instrument Name:Waters Xevo-G2-S
Instrument Type:QTOF
MS Type:ESI
MS Comments:Same as for POSITIVE mode
Ion Mode:NEGATIVE
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