Summary of Study ST003039
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 PR001891. The data can be accessed directly via it's Project DOI: 10.21228/M88X46 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.
Study ID | ST003039 |
Study Title | A Non-Targeted Metabolomics Comparative Study on Plasma of Pfizer and Sinopharm COVID- 19 Vaccinated individuals, Assessed by (TIMS-QTOF) Mass Spectrometry. |
Study Summary | COVID-19 is a contagious globally threatening infectious disease that accounted for an ongoing pandemic that manifested in multi-organs diseases and failures. The current study aimed to investigate the effectiveness of the Pfizer and Sinopharm vaccines in relation to metabolomic alterations and their association with immune pathways. The study employed a cross-sectional design and utilized an untargeted metabolomics-based approach. Plasma samples were collected from three groups: non- vaccinated participants, Sinopharm vaccinated participants, and Pfizer vaccinated participants. Comparative metabolomic analysis was performed using TIMS-QTOF, and a one-way ANOVA test was conducted using MetaboAnalyst Software. Out of the 105 detected metabolites, 72 showed statistically significant alterations (p<0.05) among the different groups. Several metabolites, including neopterin, pyridoxal, and syringic acid, were highly altered in individuals vaccinated with Pfizer. On the other hand, sphinganine, neopterin, and sphingosine were impacted in individuals vaccinated with Sinopharm. These metabolites could potentially serve as biomarkers for vaccine efficacy. Furthermore, both Pfizer and Sinopharm vaccinations were found to affect sphingolipid metabolism pathways and histidine metabolism pathways when compared to the control group. The Sinopharm group exhibited altered lysine degradation compared to the control group. When comparing the enriched pathways of the Pfizer and Sinopharm groups, purine metabolism was found to be affected. Additionally, perturbations in tryptophan metabolism and vitamin B6 metabolism were observed when comparing the Pfizer group with both the control and Sinopharm groups. These findings highlight the importance of metabolomics in assessing vaccine effectiveness and identifying potential biomarkers. |
Institute | Sharjah Institute for Medical Research |
Last Name | Facility |
First Name | Core |
Address | M32, SIMR, College of Pharmacy, Health Sciences, University of Sharjah, Sharjah, UAE, Sharjah, 000, United Arab Emirates |
tims-tof@sharjah.ac.ae | |
Phone | +971 6 5057656 |
Submit Date | 2024-01-02 |
Raw Data Available | Yes |
Raw Data File Type(s) | d |
Analysis Type Detail | LC-MS |
Release Date | 2024-01-31 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR001891 |
Project DOI: | doi: 10.21228/M88X46 |
Project Title: | A Non-Targeted Metabolomics Comparative Study on Plasma of Pfizer and Sinopharm COVID- 19 Vaccinated individuals, Assessed by (TIMS-QTOF) Mass Spectrometry. |
Project Summary: | COVID-19 is a contagious globally threatening infectious disease that accounted for an ongoing pandemic that manifested in multi-organs diseases and failures. The current study aimed to investigate the effectiveness of the Pfizer and Sinopharm vaccines in relation to metabolomic alterations and their association with immune pathways. The study employed a cross-sectional design and utilized an untargeted metabolomics-based approach. Plasma samples were collected from three groups: non- vaccinated participants, Sinopharm vaccinated participants, and Pfizer vaccinated participants. Comparative metabolomic analysis was performed using TIMS-QTOF, and a one-way ANOVA test was conducted using MetaboAnalyst Software. Out of the 105 detected metabolites, 72 showed statistically significant alterations (p<0.05) among the different groups. Several metabolites, including neopterin, pyridoxal, and syringic acid, were highly altered in individuals vaccinated with Pfizer. On the other hand, sphinganine, neopterin, and sphingosine were impacted in individuals vaccinated with Sinopharm. These metabolites could potentially serve as biomarkers for vaccine efficacy. Furthermore, both Pfizer and Sinopharm vaccinations were found to affect sphingolipid metabolism pathways and histidine metabolism pathways when compared to the control group. The Sinopharm group exhibited altered lysine degradation compared to the control group. When comparing the enriched pathways of the Pfizer and Sinopharm groups, purine metabolism was found to be affected. Additionally, perturbations in tryptophan metabolism and vitamin B6 metabolism were observed when comparing the Pfizer group with both the control and Sinopharm groups. These findings highlight the importance of metabolomics in assessing vaccine effectiveness and identifying potential biomarkers. |
Institute: | Sharjah Institute for Medical Research |
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: | SU003153 |
Subject Type: | Human |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Gender: | Male |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Treatment |
---|---|---|
SA329877 | Dual 123-8783 | Dual |
SA329878 | Dual 372-8784 | Dual |
SA329879 | Dual 573-8787 | Dual |
SA329880 | Dual 59-8782 | Dual |
SA329881 | Dual 414-8785 | Dual |
SA329882 | Dual 517-8786 | Dual |
SA329883 | Pfizer-50-8429 | Pfizer |
SA329884 | Pfizer-455-8538 | Pfizer |
SA329885 | Pfizer-500-8539 | Pfizer |
SA329886 | Pfizer-452-8537 | Pfizer |
SA329887 | Pfizer-441-8532 | Pfizer |
SA329888 | Pfizer-505-8540 | Pfizer |
SA329889 | Pfizer-445-8533 | Pfizer |
SA329890 | Pfizer-450-8535 | Pfizer |
SA329891 | Pfizer-451-8536 | Pfizer |
SA329892 | Pfizer-515-8544 | Pfizer |
SA329893 | Pfizer-520-8546 | Pfizer |
SA329894 | Pfizer-522-8547 | Pfizer |
SA329895 | Pfizer-524-8548 | Pfizer |
SA329896 | Pfizer-516-8545 | Pfizer |
SA329897 | Pfizer-438-8531 | Pfizer |
SA329898 | Pfizer-51-8430 | Pfizer |
SA329899 | Pfizer-512-8542 | Pfizer |
SA329900 | Pfizer-513-8543 | Pfizer |
SA329901 | Pfizer-509-8541 | Pfizer |
SA329902 | Pfizer-426-8525 | Pfizer |
SA329903 | Pfizer-381-8517 | Pfizer |
SA329904 | Pfizer-393-8518 | Pfizer |
SA329905 | Pfizer-397-8519 | Pfizer |
SA329906 | Pfizer-378-8516 | Pfizer |
SA329907 | Pfizer-377-8515 | Pfizer |
SA329908 | Pfizer-364-8512 | Pfizer |
SA329909 | Pfizer-371-8513 | Pfizer |
SA329910 | Pfizer-374-8514 | Pfizer |
SA329911 | Pfizer-400-8520 | Pfizer |
SA329912 | Pfizer-411-8521 | Pfizer |
SA329913 | Pfizer-429-8526 | Pfizer |
SA329914 | Pfizer-432-8528 | Pfizer |
SA329915 | Pfizer-436-8529 | Pfizer |
SA329916 | Pfizer-525-8549 | Pfizer |
SA329917 | Pfizer-424-8582 | Pfizer |
SA329918 | Pfizer-412-8522 | Pfizer |
SA329919 | Pfizer-415-8523 | Pfizer |
SA329920 | Pfizer-421-8524 | Pfizer |
SA329921 | Pfizer-437-8530 | Pfizer |
SA329922 | Pfizer-531-8552 | Pfizer |
SA329923 | Pfizer-568-8574 | Pfizer |
SA329924 | Pfizer-569-8575 | Pfizer |
SA329925 | Pfizer-571-8576 | Pfizer |
SA329926 | Pfizer-567-8573 | Pfizer |
SA329927 | Pfizer-566-8572 | Pfizer |
SA329928 | Pfizer-563-8569 | Pfizer |
SA329929 | Pfizer-564-8570 | Pfizer |
SA329930 | Pfizer-565-8571 | Pfizer |
SA329931 | Pfizer-572-8577 | Pfizer |
SA329932 | Pfizer-575-8578 | Pfizer |
SA329933 | Pfizer-65-8436 | Pfizer |
SA329934 | Pfizer-67-8437 | Pfizer |
SA329935 | Pfizer-72-8438 | Pfizer |
SA329936 | Pfizer-64-8435 | Pfizer |
SA329937 | Pfizer-58-8434 | Pfizer |
SA329938 | Pfizer-577-8579 | Pfizer |
SA329939 | Pfizer-578-8580 | Pfizer |
SA329940 | Pfizer-579-8581 | Pfizer |
SA329941 | Pfizer-562-8568 | Pfizer |
SA329942 | Pfizer-561-8567 | Pfizer |
SA329943 | Pfizer-542-8555 | Pfizer |
SA329944 | Pfizer-544-8556 | Pfizer |
SA329945 | Pfizer-545-8557 | Pfizer |
SA329946 | Pfizer-536-8554 | Pfizer |
SA329947 | Pfizer-534-8553 | Pfizer |
SA329948 | Pfizer-527-8551 | Pfizer |
SA329949 | Pfizer-53-8431 | Pfizer |
SA329950 | Pfizer-361-8511 | Pfizer |
SA329951 | Pfizer-546-8559 | Pfizer |
SA329952 | Pfizer-547-8560 | Pfizer |
SA329953 | Pfizer-555-8564 | Pfizer |
SA329954 | Pfizer-556-8565 | Pfizer |
SA329955 | Pfizer-560-8566 | Pfizer |
SA329956 | Pfizer-554-8563 | Pfizer |
SA329957 | Pfizer-55-8433 | Pfizer |
SA329958 | Pfizer-548-8561 | Pfizer |
SA329959 | Pfizer-549-8562 | Pfizer |
SA329960 | Pfizer-526-8550 | Pfizer |
SA329961 | Pfizer-446-8534 | Pfizer |
SA329962 | Pfizer-201-8457 | Pfizer |
SA329963 | Pfizer-202-8458 | Pfizer |
SA329964 | Pfizer-203-8459 | Pfizer |
SA329965 | Pfizer-205-8460 | Pfizer |
SA329966 | Pfizer-200-8456 | Pfizer |
SA329967 | Pfizer-20-8424 | Pfizer |
SA329968 | Pfizer-154-8454 | Pfizer |
SA329969 | Pfizer-155-8455 | Pfizer |
SA329970 | Pfizer-18-8423 | Pfizer |
SA329971 | Pfizer-209-8461 | Pfizer |
SA329972 | Pfizer-211-8462 | Pfizer |
SA329973 | Pfizer-220-8468 | Pfizer |
SA329974 | Pfizer-221-8469 | Pfizer |
SA329975 | Pfizer-222-8470 | Pfizer |
SA329976 | Pfizer-22-8425 | Pfizer |
Collection:
Collection ID: | CO003146 |
Collection Summary: | A total of 340 subjects (aged between 10-85 years) were enrolled from Al-Quds Medical Labs (AL-Zarqa, Jordan). Blood samples were collected from 77 healthy individuals (had not received any of the COVID- 19 vaccines), 107 individuals who received the Sinopharm vaccine, and 156 individuals who received the Pfizer vaccine. The samples were collected using heparinized tubes and were then subjected to centrifugation for five minutes to obtain plasma. The study received ethical approval from The Institutional Review Board at The University of Jordan (UHS-HERC-094-21032022), and all participants signed an informed consent before collecting the blood samples. Individuals who tested positive for COVID-19, had received booster doses, had received a third dose of COVID-19 vaccine, or had received a single dose of either Pfizer or Sinopharm vaccines were excluded from the study |
Sample Type: | Blood (plasma) |
Storage Conditions: | -80℃ |
Treatment:
Treatment ID: | TR003162 |
Treatment Summary: | Blood samples were collected from 77 healthy individuals (had not received any of the COVID- 19 vaccines), 107 individuals who received the Sinopharm vaccine, and 156 individuals who received the Pfizer vaccine |
Sample Preparation:
Sampleprep ID: | SP003159 |
Sampleprep Summary: | we used chloroform/methanol extraction protocol to increase the coverage of the extracted metabolites. At first, the samples (cells and buffer) were transferred into Eppendorf tubes then centrifuged at 14000 rpm for 5 min. Afterward, the buffer was discarded, and the cells were preserved. To each sample, 400 µL of the mixture containing one protease inhibitor tablet and 10 mL of lysis buffer was added. Following rest for 10 minutes, samples were transferred to 10 mL tubes, vortexed for 2–4 minutes, and sonicated with a COPLEY probe-sonicator (QSONICA SONICATOR, USA) for 30 seconds while utilizing a 30 % amplifier in an ice bath. The samples were then transferred to Eppendorf tubes and centrifuged for 5 minutes at 14000 rpm. The supernatant was then transferred to another Eppendorf, and 400 µL of methanol and 300 µL of chloroform were added. Following that, the samples were vortexed for 30 seconds and centrifuged for 5 minutes at 14000 rpm. After that, two metabolite-containing layers are obtained, after transferring the upper layer of each sample to glass vials, 400 µl of methanol was added, followed by vertexing and centrifugation. The remaining supernatant was transferred to the same glass vials used before for the drying step, with the remaining protein pellets being air-dried for proteomics. A dried metabolomics sample was resuspended in 200 µL (0.1% formic acid in water) and injected into HPLC to be analysed by Q-TOF MS.In summary, After dividing the samples into 100 µL portions in Eppendorf tubes, 300 µL of methanol from Wunstorfer Strasse, Seelze, Germany, was introduced. The tubes were subsequently vortexed and placed in an incubator at -20°C for two hours. Following incubation, the samples underwent another round of vortexing and were centrifuged for 15 minutes at 14000 rpm. The resulting supernatant was evaporated at 35 to 40 °C through speed vacuum evaporation. To assess the analysis's repeatability, a quality control (QC) sample was created by pooling the same volume of each sample (10µl). The extracted samples were then resuspended in 100 µL of Honeywell's LC-MS CHROMASOLV's 0.1% formic acid in Deionized Water (Wunstorfer Strasse, Seelze, Germany). Following that, 100 µL of the prepared sample was collected in an insert inside LC glass vials after filtration through a 0.45µm hydrophilic nylon syringe filter for LC-MS/MS analysis. |
Combined analysis:
Analysis ID | AN004986 |
---|---|
Analysis type | MS |
Chromatography type | Reversed phase |
Chromatography system | Bruker Elute |
Column | Hamilton Intensity Solo 2 C18 (100 x 2.1 mm, 1.8 um) |
MS Type | ESI |
MS instrument type | QTOF |
MS instrument name | Bruker timsTOF |
Ion Mode | POSITIVE |
Units | AU |
Chromatography:
Chromatography ID: | CH003766 |
Chromatography Summary: | Samples were chromatographically separated by inline reversed-phase chromatography using the Elute HPG 1300 pumps and Elute Autosampler (Bruker, Darmstadt, Germany) with solvent A 0.1% FA in HPLC grade water and solvent B 0.1% FA in ACN. A Hamilton Intensity Solo 2 C18 column (100 mm x 2.1 mm, 1.8µm beads) was maintained at 35C. For metabolomics, 10 µL was injected twice for each sample and eluted using a 30-minute gradient as follows: 1% ACN was held for 2 minutes, ramping to 99% ACN over 15 minutes, held at 99% ACN for 3 minutes before re-equilibrating to 1% ACN for 10 minutes. Flow rates were 250 µL/min for elution and 350 µL/min for re-equilibration. |
Instrument Name: | Bruker Elute |
Column Name: | Hamilton Intensity Solo 2 C18 (100 x 2.1 mm, 1.8 um) |
Column Temperature: | 35 |
Flow Gradient: | 1%B to 99%B in 15 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: | MS004726 |
Analysis ID: | AN004986 |
Instrument Name: | Bruker timsTOF |
Instrument Type: | QTOF |
MS Type: | ESI |
MS Comments: | The MS analysis was performed using a TimsTOF (Bruker, Darmstadt, Germany) with Apollo II electrospray ionization (ESI) source. The drying gas was set to flow at 10 L/min and the drying temperature to 220C and the nebulizer pressure to 2.2 bar. The capillary voltage was 4500 V and the end plate offset 500V. For metabolomics the scan range was 20-1300 m/z. The collision energy was set to 20 eV, the cycle time to 0.5 seconds with a relative minimum intensity threshold of 400 counts per thousand and target intensity of 20,000. Sodium formate was injected as an external calibrant in the first 0.3 minutes of each LC-MS/MS run. MetaboScape 4.0 software was used for metabolite processing and statistical analysis (Bruker Daltonics). The following parameters for molecular feature identification and "bucketing" were set in the T-ReX 2D/3D workflow: For peak detection, a minimum intensity threshold of 1,000 counts is required, as well as a minimum peak duration of 7 spectra, with feature quantification determine using peak area. The file masses were recalibrated based on the external calibrant injected between 0-0.3 min. |
Ion Mode: | POSITIVE |