Summary of Study ST002811

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 PR001758. The data can be accessed directly via it's Project DOI: 10.21228/M8GB0P 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.

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Study IDST002811
Study TitleMetabolomics panel associated with cystic fibrosis-related diabetes towards biomarker discovery
Study SummaryBackground: The most prevalent comorbidity among cystic fibrosis (CF) patients is cystic fibrosis-related diabetes (CFRD). CFRD has been linked to one of the worse clinical outcomes and higher mortality. Improved clinical results have been related to earlier diagnosis and treatment of CFRD. Therefore, the present study aimed to investigate the metabolome of human serum of patients with CFRD. This might aid in identifying novel biomarkers linked with the pathophysiology of CFRD and its diagnosis. Methods: The liquid chromatography–high-resolution mass spectrometry (LC–HRMS) metabolomics approach was utilized for serum samples from patients with CF (n= 36) and healthy control (n=36). Among the CF group, nine patients were with CFRD and 27 were non-CFRD (nCFRD). Results: A total of 2328 metabolites were significantly altered in CF compared to the healthy control. Among those, 799 significantly dysregulated metabolites were identified between CFRD and nCFRD. Arachidonic acid (AA), ascorbate, and aldarate metabolism were the most common metabolic pathways dysregulated in CF. L-homocysteic acid (L-HCA) levels were significantly reduced in CF and CFRD compared to control and nCFRD, respectively. In addition, gamma-glutamylglycine and L-5-hydroxytryptophan (5-HTP) had the highest discrimination between CFRD and nCFRD with AUC (0.716 and 0.683, respectively). Conclusions: These biomarkers might serve as diagnostic biomarkers and aid in understanding potential metabolic changes linked to CF and CFRD.
Institute
King Faisal Specialist Hospital and Research Centre (KFSHRC)
Last NameAl Mogren
First NameMaha
AddressZahrawi Street, Al Maather, Riyadh 11211, Saudi Arabia
Emailmmogren@kfshrc.edu.sa
Phone966541205332
Submit Date2023-08-10
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2024-08-05
Release Version1
Maha Al Mogren Maha Al Mogren
https://dx.doi.org/10.21228/M8GB0P
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001758
Project DOI:doi: 10.21228/M8GB0P
Project Title:Metabolomics panel associated with cystic fibrosis-related diabetes towards biomarker discovery
Project Summary:Background: The most prevalent comorbidity among cystic fibrosis (CF) patients is cystic fibrosis-related diabetes (CFRD). CFRD has been linked to one of the worse clinical outcomes and higher mortality. Improved clinical results have been related to earlier diagnosis and treatment of CFRD. Therefore, the present study aimed to investigate the metabolome of human serum of patients with CFRD. This might aid in identifying novel biomarkers linked with the pathophysiology of CFRD and its diagnosis. Methods: The liquid chromatography–high-resolution mass spectrometry (LC–HRMS) metabolomics approach was utilized for serum samples from patients with CF (n= 36) and healthy control (n=36). Among the CF group, nine patients were with CFRD and 27 were non-CFRD (nCFRD). Results: A total of 2328 metabolites were significantly altered in CF compared to the healthy control. Among those, 799 significantly dysregulated metabolites were identified between CFRD and nCFRD. Arachidonic acid (AA), ascorbate, and aldarate metabolism were the most common metabolic pathways dysregulated in CF. L-homocysteic acid (L-HCA) levels were significantly reduced in CF and CFRD compared to control and nCFRD, respectively. In addition, gamma-glutamylglycine and L-5-hydroxytryptophan (5-HTP) had the highest discrimination between CFRD and nCFRD with AUC (0.716 and 0.683, respectively). Conclusions: These biomarkers might serve as diagnostic biomarkers and aid in understanding potential metabolic changes linked to CF and CFRD.
Institute:King Faisal Specialist Hospital and Research Centre (KFSHRC)
Last Name:Al Mogren
First Name:Maha
Address:Zahrawi Street, Al Maather, Riyadh 11211, Saudi Arabia
Email:mmogren@kfshrc.edu.sa
Phone:966541205332

Subject:

Subject ID:SU002919
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
SA301664Ctrl25Control
SA301665Ctrl26Control
SA301666Ctrl28Control
SA301667Ctrl24Control
SA301668Ctrl23Control
SA301669Ctrl21Control
SA301670Ctrl22Control
SA301671Ctrl29Control
SA301672Ctrl31Control
SA301673Ctrl35Control
SA301674Ctrl36Control
SA301675Ctrl1Control
SA301676Ctrl34Control
SA301677Ctrl33Control
SA301678Ctrl20Control
SA301679Ctrl32Control
SA301680Ctrl30Control
SA301681Ctrl27Control
SA301682Ctrl7Control
SA301683Ctrl8Control
SA301684Ctrl9Control
SA301685Ctrl6Control
SA301686Ctrl5Control
SA301687Ctrl2Control
SA301688Ctrl19Control
SA301689Ctrl4Control
SA301690Ctrl10Control
SA301691Ctrl3Control
SA301692Ctrl16Control
SA301693Ctrl18Control
SA301694Ctrl11Control
SA301695Ctrl15Control
SA301696Ctrl17Control
SA301697Ctrl14Control
SA301698Ctrl12Control
SA301699Ctrl13Control
SA301700CF30Patient
SA301701CF33Patient
SA301702CF31Patient
SA301703CF28Patient
SA301704CF34Patient
SA301705CF26Patient
SA301706CF27Patient
SA301707CF29Patient
SA301708CF39Patient
SA301709CF41Patient
SA301710CF42Patient
SA301711CF25Patient
SA301712CF40Patient
SA301713CF38Patient
SA301714CF36Patient
SA301715CF37Patient
SA301716CF35Patient
SA301717CF1Patient
SA301718CF7Patient
SA301719CF8Patient
SA301720CF9Patient
SA301721CF6Patient
SA301722CF5Patient
SA301723CF2Patient
SA301724CF3Patient
SA301725CF4Patient
SA301726CF10Patient
SA301727CF11Patient
SA301728CF18Patient
SA301729CF19Patient
SA301730CF20Patient
SA301731CF17Patient
SA301732CF14Patient
SA301733CF12Patient
SA301734CF13Patient
SA301735CF21Patient
Showing results 1 to 72 of 72

Collection:

Collection ID:CO002912
Collection Summary:CF patients (n=36) and age- and gender-matched healthy controls (n=36) were enrolled in this study. Among 36 patients with CF, nine patients had CFRD. The institutional review board at King Faisal Specialist Hospital and Research Center (KFSHRC) approved this study (RAC# 2160 031). The exclusion criteria were patients who participated in other clinical studies in the last 30 days and were unable or unwilling to provide informed consent. The samples were collected as previously described [17]. In brief, blood samples were taken from adult CF patients who visited the adult CF-Pulmonology clinic at the King Faisal Specialist Hospital and Research Center (KFSHRC) in Riyadh, Saudi Arabia. The samples were centrifugated to separate the serum and frozen at −80 ◦C for further analysis.
Collection Protocol Filename:CF_Sample Collection
Sample Type:Blood (plasma)

Treatment:

Treatment ID:TR002928
Treatment Summary:None

Sample Preparation:

Sampleprep ID:SP002925
Sampleprep Summary:A standard procedure was used for metabolite extraction [18]. Briefly, metabolites were extracted from plasma samples by adding an extraction solvent of ACN: MeOH (1:1) followed by vortexing at 600 rpm, 4 °C for 1 hour in Thermomixer (Eppendorf, Germany). The samples were then centrifugated at 16000 rpm for 10 min at 4°C. Subsequently, the supernatant was dried using SpeedVac (Christ, Germany) and resuspended in 100 ul of 50% A: B mobile phase before LC/MS analysis. (A: 0.1% Formic acid in dH2O, B: 0.1% FA in 50% ACN: MeOH). Pooled QC was prepared from all samples to check the instrument performance.
Sampleprep Protocol Filename:Metabolites extraction

Combined analysis:

Analysis ID AN004572 AN004573
Analysis type MS MS
Chromatography type Reversed phase Reversed phase
Chromatography system Waters Acquity UPLC Waters Acquity UPLC
Column Waters XSelect HSS C18 (100 × 2.1mm,2.5um) Waters 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:CH003437
Chromatography Summary:Untargeted metabolomics analyses were performed using LCMS as previously reported [19]. Waters Acquity UPLC system coupled with a Xevo G2-S QTOF mass spectrometer equipped with an electrospray ionization source (ESI) was used. The samples were separated by ACQUITY UPLC and eluted through XSelect (100×2.1mm 2.5 mm) column (Waters Ltd., Elstree, UK). The composition of mobile phase solvent A was 0.1% formic acid in dH2O, and solvent B was 0.1% formic acid in 50% ACN: MeOH. The flow rate was at 0.300 µL/min. The gradient started with 95- 5% A for 16 minutes, followed by 4 min of 5% - 95% A, 1 min of 5-95% A, then 2 min of 95- 5% A. The total run time was 23 minutes with an injection volume of 5 μL. MS spectra were acquired under positive and negative electrospray ionization modes (ESI+, ESI−). MS conditions were as follows: the source and desolvation temperatures were set at 150°C and 500°C (ESI+) or 140 (ESI−), respectively. The capillary voltage was 3.20 kV (ESI+) or 3 kV (ESI−), the cone voltage was 40 V, the desolvation gas flow was 800.0 L/h, cone gas flow was 50 L/h. The collision energies of low and high functions were set off at 10 V and 50 V, respectively, in MSE mode. Data were collected in continuum mode with a MasslynxTM V4.1 workstation (Waters Inc., Milford, MA, USA).
Methods Filename:LC
MS Metabolomics
Instrument Name:Waters Acquity UPLC
Column Name:Waters 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, 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:MS004318
Analysis ID:AN004572
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
Analysis Protocol File:LC
MS Metabolomics
  
MS ID:MS004319
Analysis ID:AN004573
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
Analysis Protocol File:LC
MS Metabolomics
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