Summary of Study ST002428

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 PR001562. The data can be accessed directly via it's Project DOI: 10.21228/M8SM54 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 IDST002428
Study TitleMass Spectrometry-based Proteomic and Metabolomic profiling of serum samples for discovery and validation of Tuberculosis diagnostic biomarker signature
Study SummaryTuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which is crucial the discovery of effective diagnostic biomarkers. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into 3 experimental groups – healthy controls (Controls), Latent TB infection (LTBI) and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between Controls and TB patients. The AUC, specificity and sensitivity, determined by ROC statistical analysis of the model composed by four of these proteins considering both proteomic sets, were 0.96; 93% and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes, were submitted to ROC analysis. An AUC=1 was determined with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling 1 protein and 4 metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature has correctly assigned the 12 controls and 12 patients used only for prediction (AUC=1, specificity=100% and sensitivity=100%). This multi-omics approach has revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.
Institute
ITQB NOVA
LaboratoryProteomics of Non-Model Organisms
Last NameGonçalves
First NameLuís
AddressAvenida Republica
Emaillgafeira@itqb.unl.pt
Phone214469464
Submit Date2022-10-04
Num Groups3
Raw Data AvailableYes
Raw Data File Type(s)mzML
Analysis Type DetailLC-MS
Release Date2023-01-20
Release Version1
Luís Gonçalves Luís Gonçalves
https://dx.doi.org/10.21228/M8SM54
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Project:

Project ID:PR001562
Project DOI:doi: 10.21228/M8SM54
Project Title:Mass Spectrometry-based Proteomic and Metabolomic profiling of serum samples for discovery and validation of Tuberculosis diagnostic biomarker signature
Project Type:Proteomic and metabolomic study
Project Summary:Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which is crucial the discovery of effective diagnostic biomarkers. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into 3 experimental groups – healthy controls (Controls), Latent TB infection (LTBI) and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between Controls and TB patients. The AUC, specificity and sensitivity, determined by ROC statistical analysis of the model composed by four of these proteins considering both proteomic sets, were 0.96; 93% and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes, were submitted to ROC analysis. An AUC=1 was determined with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling 1 protein and 4 metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature has correctly assigned the 12 controls and 12 patients used only for prediction (AUC=1, specificity=100% and sensitivity=100%). This multi-omics approach has revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.
Institute:ITQB NOVA
Laboratory:Proteomics of Non-Model Organisms
Last Name:Gonçalves
First Name:Luís
Address:Avenida Republica
Email:lgafeira@itqb.unl.pt
Phone:214469464

Subject:

Subject ID:SU002517
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Age Or Age Range:18-65
Gender:Male and female
Human Exclusion Criteria:HIV patients, respiratory infections beside TB, diabetes, chronic renal failure history and transplanted. individuals
Species Group:Mammals

Factors:

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

mb_sample_id local_sample_id Label
SA242795C47Controls
SA242796C46Controls
SA242797C45Controls
SA242798C49Controls
SA242799C51Controls
SA242800C4Controls
SA242801C53Controls
SA242802C40Controls
SA242803C38Controls
SA242804C8Controls
SA242805C7Controls
SA242806C5Controls
SA242807C9Controls
SA242808C16Controls
SA242809C37Controls
SA242810C31Controls
SA242811C25Controls
SA242812C21Controls
SA242813DE55LTBI
SA242814CE57LTBI
SA242815C28LTBI
SA242816CE55LTBI
SA242817C30LTBI
SA242818CE54LTBI
SA242819DE10TB
SA242820DE5TB
SA242821D58TB
SA242822D56TB
SA242823DE11TB
SA242824D59TB
SA242825DE51TB
SA242826D28TB
SA242827DE53TB
SA242828DE54TB
SA242829DE52TB
SA242830DE12TB
SA242831D11TB
SA242832D15TB
SA242833D16TB
SA242834D13TB
SA242835D12TB
SA242836D10TB
SA242837D19TB
SA242838D20TB
SA242839D25TB
SA242840D26TB
SA242841D23TB
SA242842D22TB
SA242843D21TB
SA242844D27TB
Showing results 1 to 50 of 50

Collection:

Collection ID:CO002510
Collection Summary:Peripheral blood samples were collected at the Vendas Novas and Almada-Seixal Pneumonologic Diagnostic Centers (CDP-). Briefly, around 7 mL of blood was collected in order to obtain 3 mL of serum. Whole blood samples were harvested using Clot Activator Tubes (Monovette Serum Gel Z – 7.5 mL, S-monovette, Sarstedt®). IGRA test (QuantiFERON®-TB Gold IT, ©QIAGEN) was used to confirm infection status in Control and Latent groups. These samples were transported at 4°C to the National Institute of Health Doctor Ricardo Jorge (INSA). Samples displaying hemolysis or with unidentified IGRA results were excluded from further analysis.
Sample Type:Blood (serum)

Treatment:

Treatment ID:TR002529
Treatment Summary:Blood was allowed to clot for three hours at 4°C after collection. The blood was then centrifuged at 1000 xg at 4°C for 30 min. Serum collected after centrifugation was passed through 0.2 μm filters (Sterile Acrodisc®, syringe filters with Supor membrane, 32 mm) to remove bacteria. Finally, an anti-protease cocktail (Protease Inhibitor Cocktail, ©SIGMA) was added to the filtered serum. The samples were transported from INSA to ITQB in a liquid nitrogen container and stored at −80°C.

Sample Preparation:

Sampleprep ID:SP002523
Sampleprep Summary:Serum samples (100 µL) were extracted with 300 µL of methanol overnight at 4°C. The morning after, the samples were centrifuged for 5 min at 16.000 ×g and 4°C. The supernatant was transferred to a new tube, evaporated in the speedvac, and the pellet was stored at −20°C until further analysis. Previous to LC-MS/MS analysis the pellets were resuspended in 99.16 µL of H2O 0.1%FA. The Internal Standard (IS) – 3-Nitro-L-tyrosine – was added to a final concentration of 42 µM. In addition, four pools of samples were used for metabolite identification.

Combined analysis:

Analysis ID AN003951 AN003952
Analysis type MS MS
Chromatography type Reversed phase Reversed phase
Chromatography system Dionex UltiMate 3000 UHPLC Dionex UltiMate 3000 UHPLC
Column Waters XBridge C18 (50 x 2.1mm, 3um) Waters XBridge C18 (50 x 2.1mm, 3um)
MS Type ESI ESI
MS instrument type Orbitrap Orbitrap
MS instrument name Thermo Q Exactive Focus Thermo Q Exactive Focus
Ion Mode POSITIVE NEGATIVE
Units ua au

Chromatography:

Chromatography ID:CH002925
Instrument Name:Dionex UltiMate 3000 UHPLC
Column Name:Waters XBridge C18 (50 x 2.1mm, 3um)
Chromatography Type:Reversed phase

MS:

MS ID:MS003686
Analysis ID:AN003951
Instrument Name:Thermo Q Exactive Focus
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Full-MS scan spectra were acquired in the m/z range 75 – 1125, at a resolution of 70,000 (full width at half maximum (FWHM) at m/z 200) and 1×106 automatic gain control (AGC). MS/MS scan spectra were acquired at 17,500 resolution (FWHM at m/z 200), with 1×105 AGC, maximum injection time of 100 ms and dynamic exclusion of 6 s. Raw data files were independently processed by Compound Discoverer™ 3.1 (ThermoFisher Scientific) software for metabolomics data analysis. The preferred database used for metabolite identification was mzCloud – since the "Search mzCloud '' node searches this database for matching fragmentation spectra (MS2) – followed by ChemSpider. For both databases the mass tolerance that the software used to search for matching mass peaks was set at 3 ppm. In the case of the mzCloud search the parameter "FT Fragment Mass Tolerance"was set to 5 ppm. The Human Metabolome Database (HMDB) was selected as the primary source for the ChemSpider search.
Ion Mode:POSITIVE
  
MS ID:MS003687
Analysis ID:AN003952
Instrument Name:Thermo Q Exactive Focus
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Full-MS scan spectra were acquired in the m/z range 75 – 1125, at a resolution of 70,000 (full width at half maximum (FWHM) at m/z 200) and 1×106 automatic gain control (AGC). MS/MS scan spectra were acquired at 17,500 resolution (FWHM at m/z 200), with 1×105 AGC, maximum injection time of 100 ms and dynamic exclusion of 6 s. Raw data files were independently processed by Compound Discoverer™ 3.1 (ThermoFisher Scientific) software for metabolomics data analysis. The preferred database used for metabolite identification was mzCloud – since the "Search mzCloud '' node searches this database for matching fragmentation spectra (MS2) – followed by ChemSpider. For both databases the mass tolerance that the software used to search for matching mass peaks was set at 3 ppm. In the case of the mzCloud search the parameter "FT Fragment Mass Tolerance"was set to 5 ppm. The Human Metabolome Database (HMDB) was selected as the primary source for the ChemSpider search.
Ion Mode:NEGATIVE
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