Summary of Study ST002553

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 PR001645. The data can be accessed directly via it's Project DOI: 10.21228/M82M7C 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 IDST002553
Study TitleExploring the Impact of Oral Arabic Gum Consumption on Sphingolipid Metabolism and human metabolites in Chronic Kidney Disease: A Mass Spectrometry Analysis
Study TypeLC/MS/MS
Study SummaryGlobally, the incidence of chronic kidney disease is increasing, raising serious concerns about its impact on public health. It also poses significant difficulty in finding novel early diagnostics, understanding biochemical pathways, monitoring patients, and prognosis. Any metabolite found in a biofluid, or tissue may act as a driver, signal, or both in the emergence or spread of the disease. As a result, metabolomics is a very useful strategy in this therapeutic setting. Broad metabolite coverage is essential since it strives to offer a representative image of a biological system. An untargeted metabolomics-based method was used in this cross-sectional study to identify metabolomic changes and their relationship to pathways in the Arabic gum patient group and control participants. Plasma samples were collected from 88 participants who met the inclusion criteria, of whom 43 control patients were treated with a placebo and 45 intervention patients were treated with Arabic gum. Highly sensitive ultra-high-performance liquid chromatography with electrospray ionization and quadrupole time-of-flight mass spectrometry was used to analyze the plasma samples (UHPLC-ESI-QTOF-MS). We investigated the effect of Arabic gum on individual metabolites using a two-tailed independent student t-test. The results showed that 31 out of 92 identified metabolites were found to be statistically significant (p < 0.05). L-Leucine and 5'-Methylthioadenosine were the significantly increased metabolites in the Arabic gum group. Conversely, triethylamine, D-limonene, 4-methylphenylacetic acid, and sphingosine levels were significantly lower in the Arabic gum group compared to the control. Arabic gum primarily affected multiple metabolic pathways, including glycine and serine, arginine and proline, valine, leucine, and isoleucine degradation, phenylalanine and tyrosine, urea cycle, and sphingolipid. The results from this study provide insights into the potential diagnostic significance of different metabolites in chronic kidney disease and their impact on specific metabolic pathways. However, further research involving larger cohorts is necessary to validate the observed metabolite changes following Arabic gum intake and their diagnostic value for chronic kidney disease.
Institute
Sharjah Institute for Medical Research
DepartmentSharjah Institute for Medical Research
LaboratoryBiomarker Discovery Group
Last NameFacility
First NameCore
AddressM32, SIMR, College of Pharmacy, Health Sciences, University of Sharjah, Sharjah, UAE, Sharjah, 000, United Arab Emirates
Emailtims-tof@sharjah.ac.ae
Phone+971 6 5057656
Submit Date2023-04-09
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2023-10-10
Release Version1
Core Facility Core Facility
https://dx.doi.org/10.21228/M82M7C
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001645
Project DOI:doi: 10.21228/M82M7C
Project Title:Exploring the Impact of Oral Arabic Gum Consumption on Sphingolipid Metabolism and human metabolites in Chronic Kidney Disease: A Mass Spectrometry Analysis
Project Type:LC-MS/MS
Project Summary:Globally, the incidence of chronic kidney disease is increasing, raising serious concerns about its impact on public health. It also poses significant difficulty in finding novel early diagnostics, understanding biochemical pathways, monitoring patients, and prognosis. Any metabolite found in a biofluid, or tissue may act as a driver, signal, or both in the emergence or spread of the disease. As a result, metabolomics is a very useful strategy in this therapeutic setting. Broad metabolite coverage is essential since it strives to offer a representative image of a biological system. An untargeted metabolomics-based method was used in this cross-sectional study to identify metabolomic changes and their relationship to pathways in the Arabic gum patient group and control participants. Plasma samples were collected from 88 participants who met the inclusion criteria, of whom 43 control patients were treated with a placebo and 45 intervention patients were treated with Arabic gum. Highly sensitive ultra-high-performance liquid chromatography with electrospray ionization and quadrupole time-of-flight mass spectrometry was used to analyze the plasma samples (UHPLC-ESI-QTOF-MS). We investigated the effect of Arabic gum on individual metabolites using a two-tailed independent student t-test. The results showed that 31 out of 92 identified metabolites were found to be statistically significant (p < 0.05). L-Leucine and 5'-Methylthioadenosine were the significantly increased metabolites in the Arabic gum group. Conversely, triethylamine, D-limonene, 4-methylphenylacetic acid, and sphingosine levels were significantly lower in the Arabic gum group compared to the control. Arabic gum primarily affected multiple metabolic pathways, including glycine and serine, arginine and proline, valine, leucine, and isoleucine degradation, phenylalanine and tyrosine, urea cycle, and sphingolipid. The results from this study provide insights into the potential diagnostic significance of different metabolites in chronic kidney disease and their impact on specific metabolic pathways. However, further research involving larger cohorts is necessary to validate the observed metabolite changes following Arabic gum intake and their diagnostic value for chronic kidney disease.
Institute:Sharjah Institute for Medical Research
Department:Sharjah Institute for Medical Research
Laboratory:Biomarker Discovery Group
Last Name:Facility
First Name:Core
Address:M32, SIMR, College of Pharmacy, Health Sciences, University of Sharjah, Sharjah, UAE, Sharjah, 000, United Arab Emirates
Email:tims-tof@sharjah.ac.ae
Phone:+971 6 5057656

Subject:

Subject ID:SU002653
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606

Factors:

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

mb_sample_id local_sample_id Treatment
SA256307Arabic Gum-T16-02-6719Arabic gum
SA256308Arabic Gum-T17-01-6720Arabic gum
SA256309Arabic Gum-T18-01-6723Arabic gum
SA256310Arabic Gum-T16-01-6718Arabic gum
SA256311Arabic Gum-T17-02-6721Arabic gum
SA256312Arabic Gum-T15-02-6717Arabic gum
SA256313Arabic Gum-T14-01-6714Arabic gum
SA256314Arabic Gum-T14-02-6715Arabic gum
SA256315Arabic Gum-T15-01-6716Arabic gum
SA256316Arabic Gum-T18-02-6724Arabic gum
SA256317Arabic Gum-T19-02-6726Arabic gum
SA256318Arabic Gum-T22-01-6731Arabic gum
SA256319Arabic Gum-T22-02-6732Arabic gum
SA256320Arabic Gum-T23-01-6733Arabic gum
SA256321Arabic Gum-T23-02-6734Arabic gum
SA256322Arabic Gum-T21-02-6730Arabic gum
SA256323Arabic Gum-T21-01-6729Arabic gum
SA256324Arabic Gum-T13-02-6713Arabic gum
SA256325Arabic Gum-T20-01-6727Arabic gum
SA256326Arabic Gum-T20-02-6728Arabic gum
SA256327Arabic Gum-T19-01-6725Arabic gum
SA256328Arabic Gum-T12-02-6711Arabic gum
SA256329Arabic Gum-T05-02-6696Arabic gum
SA256330Arabic Gum-T06-01-6697Arabic gum
SA256331Arabic Gum-T06-02-6698Arabic gum
SA256332Arabic Gum-T07-01-6699Arabic gum
SA256333Arabic Gum-T05-01-6695Arabic gum
SA256334Arabic Gum-T04-02-6694Arabic gum
SA256335Arabic Gum-T03-01-6691Arabic gum
SA256336Arabic Gum-T03-02-6692Arabic gum
SA256337Arabic Gum-T04-01-6693Arabic gum
SA256338Arabic Gum-T07-02-6700Arabic gum
SA256339Arabic Gum-T08-01-6702Arabic gum
SA256340Arabic Gum-T11-01-6708Arabic gum
SA256341Arabic Gum-T11-02-6709Arabic gum
SA256342Arabic Gum-T12-01-6710Arabic gum
SA256343Arabic Gum-T24-01-6735Arabic gum
SA256344Arabic Gum-T10-02-6707Arabic gum
SA256345Arabic Gum-T10-01-6706Arabic gum
SA256346Arabic Gum-T08-02-6703Arabic gum
SA256347Arabic Gum-T09-01-6704Arabic gum
SA256348Arabic Gum-T09-02-6705Arabic gum
SA256349Arabic Gum-T13-01-6712Arabic gum
SA256350Arabic Gum-T25-01-6737Arabic gum
SA256351Arabic Gum-T38-02-6769Arabic gum
SA256352Arabic Gum-T39-01-6770Arabic gum
SA256353Arabic Gum-T39-02-6771Arabic gum
SA256354Arabic Gum-T40-01-6772Arabic gum
SA256355Arabic Gum-T38-01-6768Arabic gum
SA256356Arabic Gum-T37-02-6766Arabic gum
SA256357Arabic Gum-T36-01-6763Arabic gum
SA256358Arabic Gum-T36-02-6764Arabic gum
SA256359Arabic Gum-T37-01-6765Arabic gum
SA256360Arabic Gum-T40-02-6773Arabic gum
SA256361Arabic Gum-T41-01-6774Arabic gum
SA256362Arabic Gum-T44-01-6780Arabic gum
SA256363Arabic Gum-T44-02-6781Arabic gum
SA256364Arabic Gum-T45-01-6782Arabic gum
SA256365Arabic Gum-T45-02-6783Arabic gum
SA256366Arabic Gum-T43-02-6779Arabic gum
SA256367Arabic Gum-T43-01-6778Arabic gum
SA256368Arabic Gum-T41-02-6775Arabic gum
SA256369Arabic Gum-T42-01-6776Arabic gum
SA256370Arabic Gum-T42-02-6777Arabic gum
SA256371Arabic Gum-T35-02-6762Arabic gum
SA256372Arabic Gum-T35-01-6761Arabic gum
SA256373Arabic Gum-T27-02-6742Arabic gum
SA256374Arabic Gum-T28-01-6744Arabic gum
SA256375Arabic Gum-T28-02-6745Arabic gum
SA256376Arabic Gum-T29-01-6749Arabic gum
SA256377Arabic Gum-T27-01-6741Arabic gum
SA256378Arabic Gum-T26-02-6740Arabic gum
SA256379Arabic Gum-T02-02-6690Arabic gum
SA256380Arabic Gum-T25-02-6738Arabic gum
SA256381Arabic Gum-T26-01-6739Arabic gum
SA256382Arabic Gum-T29-02-6750Arabic gum
SA256383Arabic Gum-T30-01-6751Arabic gum
SA256384Arabic Gum-T33-01-6757Arabic gum
SA256385Arabic Gum-T33-02-6758Arabic gum
SA256386Arabic Gum-T34-01-6759Arabic gum
SA256387Arabic Gum-T34-02-6760Arabic gum
SA256388Arabic Gum-T32-02-6756Arabic gum
SA256389Arabic Gum-T32-01-6755Arabic gum
SA256390Arabic Gum-T30-02-6752Arabic gum
SA256391Arabic Gum-T31-01-6753Arabic gum
SA256392Arabic Gum-T31-02-6754Arabic gum
SA256393Arabic Gum-T24-02-6736Arabic gum
SA256394Arabic Gum-T02-01-6689Arabic gum
SA256395Arabic Gum-T01-01-6687Arabic gum
SA256396Arabic Gum-T01-02-6688Arabic gum
SA256397Arabic Gum-C15-01-6626Control
SA256398Arabic Gum-C15-02-6627Control
SA256399Arabic Gum-C16-02-6629Control
SA256400Arabic Gum-C14-02-6625Control
SA256401Arabic Gum-C16-01-6628Control
SA256402Arabic Gum-C13-02-6623Control
SA256403Arabic Gum-C12-02-6621Control
SA256404Arabic Gum-C13-01-6622Control
SA256405Arabic Gum-C17-01-6630Control
SA256406Arabic Gum-C14-01-6624Control
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Collection:

Collection ID:CO002646
Collection Summary:The patients’ samples were collected from Jordan University Hospital, and the metabolomics study was conducted at the Research Institute of Medical & Health Sciences (RIMHS?) of the University of Sharjah. The study included two groups: a control group of 43 patients and an intervention group of 45 patients with stable CKD stages III-V not on dialysis and aged between 18 and 90 years. Exclusion criteria included pregnancy and treatment with complementary and alternative medicine (CAM) other than Arabic gum. Informed consent was obtained prior to the study, and approval was obtained from Jordan University Hospital's Research Ethics Committee. The study was conducted in accordance with the Helsinki Declaration principles, and participants were fully informed about the study prior to signing the consent forms.
Sample Type:Blood (serum)

Treatment:

Treatment ID:TR002665
Treatment Summary:For intervention group, Arabic gum in the form of powder twice daily was given, at the dose patients are taking usually over the counter (40 grams of GA in the form of instantly soluble granules to be dissolved in a glass of water or juice and drink it daily for the assigned study period. While for the control group, a placebo was given in the same shape and taste and same frequency. Participants in both groups underwent a 24-hour urine collection for creatinine, protein, and volume at baseline and every three months. eGFR was calculated using the CKD-epi equation [add ref], and lab tests, including serum creatinine, electrolytes, uric acid, serum albumin, phosphate, calcium, PTH, Complete Blood Count (CBC), fasting lipid profile, and urinalysis, were performed at baseline and at 3-month intervals for a year. The objectives of the study were to assess the impact of the intervention on various parameters, including a reduction in the eGFR and the rate of the decline, a decrease in proteinuria, changes in uric acid, electrolytes, calcium, phosphate, vitamin D, and PTH levels, effects on edema, body weight, blood pressure, and anemia parameters.

Sample Preparation:

Sampleprep ID:SP002659
Sampleprep Summary:300 µL of methanol (Wunstorfer Strasse, Seelze, Germany) was added after the samples were divided into 100 µL Eppendorf tubes, which were then vortexed and incubated at –20 °C for 2 hours. The samples were then vortexed and centrifuged for 15 minutes at 14,000 rpm. The supernatant was then evaporated at 35–40 °C using a speed vacuum evaporator. To assess the analysis's reproducibility, a quality control (QC) sample was created by combining the same volume of each sample. The extract samples were then resuspended in 250 L of Honeywell's LC-MS CHROMASOLV's 0.1% formic acid in Deionized Water (Wunstorfer Strasse, Seelze, Germany). After that, the supernatant was filtered for LC-MS/MS analysis through a hydrophilic nylon syringe filter with a 0.45 m pore size. 100 L of the prepared sample was then gathered in an insert inside LC glass vials.

Combined analysis:

Analysis ID AN004204
Analysis type MS
Chromatography type Reversed phase
Chromatography system Bruker timsTOF
Column Bruker Intensity Solo 2 C18 (100 mm × 2.1 mm , 1.8 μm)
MS Type ESI
MS instrument type QTOF
MS instrument name Bruker timsTOF
Ion Mode POSITIVE
Units AU

Chromatography:

Chromatography ID:CH003115
Instrument Name:Bruker timsTOF
Column Name:Bruker Intensity Solo 2 C18 (100 mm × 2.1 mm , 1.8 μm)
Column Temperature:35
Flow Gradient:The gradient program was: 0–2 min, 99% A: 1% B; 2–17 min, 99–1% A: 1–99% B; 17–20 min, 99% B: 1% A. The flow rate was fixed at 0.25 mL/min. Subsequently, 20–20.1 min 99% B to 99% A; 20.1–28.5 min, 99% A: 1% B at 0.35 mL/min flow rate; 28.5–30 min; 99% A: 1% B at 0.25 mL/min.
Flow Rate:250 uL/min
Solvent A:100% water; 0.1% formic acid
Solvent B:100% acetonitrile; 0.1% formic acid
Chromatography Type:Reversed phase

MS:

MS ID:MS003951
Analysis ID:AN004204
Instrument Name:Bruker timsTOF
Instrument Type:QTOF
MS Type:ESI
MS Comments:The LC-MS/MS analysis was performed using an ultra-high-performance liquid chromatography system (UHPLC) (Bruker Daltonik GmbH, Bremen, Germany) connected to a quadrupole time-of-flight mass spectrometer (QTOF). An electrospray ionization (ESI) source, a solvent delivery systems pump (HPG 1300), an autosampler, and a thermostat column compartment were all included in the system. The computer operating system was Windows 10 Enterprise 2016 LTSB. Bruker Compass HyStar 5.0 SR1 Patch1 (5.0.37.1), Compass 4.1 for otofSeries, and otof Control Version 6.2 software were used for data management. Mobile phases A (water with 0.1% formic acid) and B (acetonitrile with 0.1% formic acid) were employed. The gradient program was: 0–2 min, 99% A: 1% B; 2–17 min, 99–1% A: 1–99% B; 17–20 min, 99% B: 1% A. The flow rate. Subsequently, 20–20.1 min 99% B to 99% A; 20.1–28.5 min, 99% A: 1% B at 0.35 mL/min flow rate; 28.5–30 min; 99% A: 1% B at 0.25 mL/min. A 10 μL aliquot of the sample was injected, and the separation was performed on a Hamilton® Intensity Solo 2 C18 column (100 mm × 2.1 mm × 1.8 μm) at a column oven temperature set at 35 °C. For each injection, the ESI source circumstances were as follows: The capillary voltage was adjusted to 4500 V; the drying gas flow rate was 10.0 L/min at a temperature of 220 °C; and the nebulizer pressure was 2.2 bar. The collision energy stepping for the MS2 acquisition varied between 100 and 250% fixed at 20 eV and an end plate offset of 500 V. [35]. For the external calibration step, sodium formate was utilized as a calibrant. For the calibrant sodium formate, the auto MS scan segment of the acquisition lasted from 0 to 0.3 minutes, and the auto MS/MS segment, which included fragmentation, lasted from 0.3 to 30 minutes. The acquisition in both segments was performed using the positive mode at 12 Hz. The automatic in-run mass scan range was from 20 to 1300 m/z, the width of the precursor ion was ±0.5, the number of precursors was 3, the cycle time was 0.5 s, and the threshold was 400 cts. Active exclusion was excluded after 3 spectra and released after 0.2 min. The data was processed using MetaboScape® 4.0 software (Bruker Daltonics, Billerica, MA, USA) (37). The following were the T-ReX 2D/3D workflow bucketing parameters for the processed data: intensity threshold of 1000; peak length of 7 spectra; and using peak area for quantifying the feature. Mass spectra were calibrated in 0-0.3 minutes using features from at least 48 to 187 samples. However, the auto MS/MS scan was carried out using the average method. The retention time and mass ranges for the scan were 0.3 to 25 minutes and 50 to 1000 m/z, respectively. By using LC-QTOF to analyze every sample in duplicate, 88 samples from both groups undergoing examination were combined to create a data set with 3487 characteristics. Based on the mapping of the MS/MS spectra and retention time in the HMBD 4.0, an annotated database created to meet the demands of the metabolomics community, metabolites were identified. A total of 102 distinct metabolites were selected after MetaboScape® filtration (Supplementary Table S1). The peak intensities of each metabolite were used to quantify the data matrix. Only significant compounds recorded in the HMDB 4.0 with p < 0.05 were included in the metabolite datasets. The online website HMDB (https://hmdb.ca/metabolites/HMDB0059911) was used to filter the human metabolites or Arabic gum metabolites. Following HMDB filtration, 92 unique metabolites remained (Supplementary Table S2). The software MetaboAnalyst 5.0 (Mcgill University, Montreal, QC, Canada), a comprehensive platform for metabolomics data analysis, was used to import the metabolite datasets after exporting them as a CSV file [36]. To help classify the samples, the most discriminating features in the studied group were chosen using the sPLS-DA method in MetaboAnalyst. The rate of false positives was reduced, and multiple hypothesis testing was corrected using the false discovery rate (FDR) approach. The Arabic gum group's significantly altered metabolites were found using a two-tailed independent students t-test in comparison to the control group. As a result, a volcano plot was created to display the statistical significance and fold change for cellular metabolite dysregulation. The threshold for significance was p<0.05. Functional Enrichments were constructed using metaboanalyst (https://www.metaboanalyst.ca).
Ion Mode:POSITIVE
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