Summary of Study ST002087
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 PR001326. The data can be accessed directly via it's Project DOI: 10.21228/M89T2Q 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 | ST002087 |
Study Title | Profiling metabolites and lipoproteins in COMETA, an Italian cohort of COVID-19 patients |
Study Type | NMR-based metabolomics |
Study Summary | 1H NMR spectra of EDTA-plasma from 246 COVID-19-positive subjects in the acute phase of infection were compared to those of 94 COVID-19-recovered subjects. The two cohorts are largely different (discrimination accuracy > 93%) due to a pool of 16 metabolites and 74 lipoprotein parameters significantly up- or down-regulated in the patients and within the healthy range in the recovered subjects. In 28 post-acute COVID-19-positive patients, the metabolites levels are reverted back to normality whereas the lipoprotein parameters are still altered. Therefore, the metabolite biomarkers might be used as the timeliest sign of the individual response to treatment or spontaneous healing. |
Institute | University of Florence |
Department | Department of Chemistry |
Laboratory | metabolomics |
Last Name | Ghini |
First Name | Veronica |
Address | via Luigi Sacconi |
ghini@cerm.unifi.it | |
Phone | +390554574266 |
Submit Date | 2022-02-17 |
Num Groups | 3 |
Total Subjects | 368 |
Num Males | 201 |
Num Females | 167 |
Raw Data Available | Yes |
Raw Data File Type(s) | fid |
Analysis Type Detail | NMR |
Release Date | 2022-03-16 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR001326 |
Project DOI: | doi: 10.21228/M89T2Q |
Project Title: | Profiling metabolites and lipoproteins in COMETA, an Italian cohort of COVID-19 patients |
Project Type: | NMR-based metabolomics |
Project Summary: | 1H NMR spectra of EDTA-plasma from 246 COVID-19-positive subjects in the acute phase of infection were compared to those of 95 COVID-19-recovered subjects. The two cohorts are largely different (discrimination accuracy > 93%) due to a pool of 16 metabolites and 74 lipoprotein parameters significantly up- or down-regulated in the patients and within the healthy range in the recovered subjects. In 28 post-acute COVID-19-positive patients, the metabolites levels are reverted back to normality whereas the lipoprotein parameters are still altered. Therefore, the metabolite biomarkers might be used as the timeliest sign of the individual response to treatment or spontaneous healing. |
Institute: | University of Florence |
Department: | Department of Chemistry |
Laboratory: | Metabolomics |
Last Name: | Ghini |
First Name: | Veronica |
Address: | via Luigi Sacconi 6 |
Email: | ghini@cerm.unifi.it |
Phone: | +390554574266 |
Funding Source: | COMETA project, funded by the Tuscany Region,Italy |
Subject:
Subject ID: | SU002171 |
Subject Type: | Human |
Subject Species: | Homo sapiens |
Taxonomy ID: | 9606 |
Gender: | Male and female |
Human Inclusion Criteria: | hospedalized COVID-19 patients |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
mb_sample_id | local_sample_id | Grade of severity | Group |
---|---|---|---|
SA198471 | 21 | Asymptomatic | COVID-19>21days |
SA198472 | 24 | Asymptomatic | COVID-19>21days |
SA198473 | 17 | Asymptomatic | COVID-19>21days |
SA198474 | 266 | Asymptomatic | COVID-19>21days |
SA198475 | 99 | Asymptomatic | COVID-19>21days |
SA198476 | 10 | Asymptomatic | COVID-19>21days |
SA198477 | 15 | Asymptomatic | COVID-19>21days |
SA198478 | 12 | Asymptomatic | COVID-19>21days |
SA198479 | 13 | Asymptomatic | COVID-19>21days |
SA198436 | 361 | Asymptomatic | COVID-19<21days |
SA198437 | 365 | Asymptomatic | COVID-19<21days |
SA198438 | 399 | Asymptomatic | COVID-19<21days |
SA198439 | 360 | Asymptomatic | COVID-19<21days |
SA198440 | 358 | Asymptomatic | COVID-19<21days |
SA198441 | 347 | Asymptomatic | COVID-19<21days |
SA198442 | 350 | Asymptomatic | COVID-19<21days |
SA198443 | 408 | Asymptomatic | COVID-19<21days |
SA198444 | 476 | Asymptomatic | COVID-19<21days |
SA198445 | 485 | Asymptomatic | COVID-19<21days |
SA198446 | 491 | Asymptomatic | COVID-19<21days |
SA198447 | 6 | Asymptomatic | COVID-19<21days |
SA198448 | 483 | Asymptomatic | COVID-19<21days |
SA198449 | 482 | Asymptomatic | COVID-19<21days |
SA198450 | 335 | Asymptomatic | COVID-19<21days |
SA198451 | 479 | Asymptomatic | COVID-19<21days |
SA198452 | 475 | Asymptomatic | COVID-19<21days |
SA198453 | 338 | Asymptomatic | COVID-19<21days |
SA198454 | 111 | Asymptomatic | COVID-19<21days |
SA198455 | 112 | Asymptomatic | COVID-19<21days |
SA198456 | 113 | Asymptomatic | COVID-19<21days |
SA198457 | 20 | Asymptomatic | COVID-19<21days |
SA198458 | 19 | Asymptomatic | COVID-19<21days |
SA198459 | 7 | Asymptomatic | COVID-19<21days |
SA198460 | 9 | Asymptomatic | COVID-19<21days |
SA198461 | 205 | Asymptomatic | COVID-19<21days |
SA198462 | 133 | Asymptomatic | COVID-19<21days |
SA198463 | 283 | Asymptomatic | COVID-19<21days |
SA198464 | 324 | Asymptomatic | COVID-19<21days |
SA198465 | 333 | Asymptomatic | COVID-19<21days |
SA198466 | 223 | Asymptomatic | COVID-19<21days |
SA198467 | 263 | Asymptomatic | COVID-19<21days |
SA198468 | 254 | Asymptomatic | COVID-19<21days |
SA198469 | 231 | Asymptomatic | COVID-19<21days |
SA198470 | 245 | Asymptomatic | COVID-19<21days |
SA198480 | 27 | Asymptomatic | Post-COVID-19 |
SA198481 | 50 | Asymptomatic | Post-COVID-20 |
SA198482 | 66 | Asymptomatic | Post-COVID-21 |
SA198483 | 84 | Asymptomatic | Post-COVID-22 |
SA198484 | 90 | Asymptomatic | Post-COVID-23 |
SA198485 | 123 | Asymptomatic | Post-COVID-24 |
SA198486 | 185 | Asymptomatic | Post-COVID-26 |
SA198487 | 186 | Asymptomatic | Post-COVID-27 |
SA198488 | 187 | Asymptomatic | Post-COVID-28 |
SA198489 | 192 | Asymptomatic | Post-COVID-29 |
SA198490 | 346 | Asymptomatic | Post-COVID-30 |
SA198491 | 382 | Asymptomatic | Post-COVID-31 |
SA198576 | 22 | Mild | COVID-19>21days |
SA198577 | 25 | Mild | COVID-19>21days |
SA198578 | 18 | Mild | COVID-19>21days |
SA198579 | 14 | Mild | COVID-19>21days |
SA198580 | 41 | Mild | COVID-19>21days |
SA198581 | 63 | Mild | COVID-19>21days |
SA198582 | 97 | Mild | COVID-19>21days |
SA198583 | 64 | Mild | COVID-19>21days |
SA198584 | 395 | Mild | COVID-19>21days |
SA198585 | 96 | Mild | COVID-19>21days |
SA198492 | 416 | Mild | COVID-19<21days |
SA198493 | 415 | Mild | COVID-19<21days |
SA198494 | 421 | Mild | COVID-19<21days |
SA198495 | 422 | Mild | COVID-19<21days |
SA198496 | 433 | Mild | COVID-19<21days |
SA198497 | 426 | Mild | COVID-19<21days |
SA198498 | 412 | Mild | COVID-19<21days |
SA198499 | 410 | Mild | COVID-19<21days |
SA198500 | 398 | Mild | COVID-19<21days |
SA198501 | 394 | Mild | COVID-19<21days |
SA198502 | 402 | Mild | COVID-19<21days |
SA198503 | 405 | Mild | COVID-19<21days |
SA198504 | 393 | Mild | COVID-19<21days |
SA198505 | 407 | Mild | COVID-19<21days |
SA198506 | 435 | Mild | COVID-19<21days |
SA198507 | 464 | Mild | COVID-19<21days |
SA198508 | 468 | Mild | COVID-19<21days |
SA198509 | 467 | Mild | COVID-19<21days |
SA198510 | 469 | Mild | COVID-19<21days |
SA198511 | 473 | Mild | COVID-19<21days |
SA198512 | 391 | Mild | COVID-19<21days |
SA198513 | 480 | Mild | COVID-19<21days |
SA198514 | 461 | Mild | COVID-19<21days |
SA198515 | 454 | Mild | COVID-19<21days |
SA198516 | 440 | Mild | COVID-19<21days |
SA198517 | 439 | Mild | COVID-19<21days |
SA198518 | 441 | Mild | COVID-19<21days |
SA198519 | 448 | Mild | COVID-19<21days |
SA198520 | 453 | Mild | COVID-19<21days |
SA198521 | 438 | Mild | COVID-19<21days |
SA198522 | 428 | Mild | COVID-19<21days |
SA198523 | 234 | Mild | COVID-19<21days |
SA198524 | 239 | Mild | COVID-19<21days |
SA198525 | 232 | Mild | COVID-19<21days |
Collection:
Collection ID: | CO002164 |
Collection Summary: | The analysed were done on EDTA-plasma. All the samples were collected, processed and stored following the ISO standards (ISO 23118:2021), designed for high quality biological samples for metabolomic analysis |
Sample Type: | Blood (plasma) |
Storage Conditions: | -80℃ |
Treatment:
Treatment ID: | TR002183 |
Treatment Summary: | not applicable |
Sample Preparation:
Sampleprep ID: | SP002177 |
Sampleprep Summary: | Frozen EDTA-plasma samples were thawed at room temperature and shaken before use. A total of 350 μL of sodium phosphate buffer (70 mM Na2HPO4; 20% (v/v) 2H2O; 6.1 mM NaN3, 4.6 mM sodium trimethylsilyl [2,2,3,3−2H4] propionate (TMSP), pH 7.4) was added to 350 μL of each serum sample; the mixture was homogenized by vortexing for 30 s. A total of 600 μL of each mixture was transferred into a 5.00 mm NMR tube (Bruker BioSpin) for the analysis. |
Analysis:
Analysis ID: | AN003405 |
Laboratory Name: | Metabolomics |
Analysis Type: | NMR |
Num Factors: | 102 |
Num Metabolites: | 139 |
Units: | uM |
NMR:
NMR ID: | NM000231 |
Analysis ID: | AN003405 |
Instrument Name: | Bruker 600MHZ |
Instrument Type: | FT-NMR |
NMR Experiment Type: | 1D-1H |
Spectrometer Frequency: | 600 MHz |
NMR Probe: | 5 mm PATXI 1H−13C−15N and 2H-decoupling probe |
NMR Tube Size: | 5 mm |
Pulse Sequence: | noesygp1d |
Water Suppression: | water peak suppression |
Dummy Scans: | 4 |
Acquisition Time: | 2.7 s |
Relaxation Delay: | 4 s |
Spectral Width: | 18,028 Hz |
Num Data Points Acquired: | 98000 |
Line Broadening: | 0.3 |
Baseline Correction Method: | automatic baseline correction |
Chemical Shift Ref Std: | doublet at 5.24 ppm |
Binned Increment: | 0.2 ppm |
Binned Data Excluded Range: | 4.5-5.5 ppm |