Summary of Study ST001849

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 PR001166. The data can be accessed directly via it's Project DOI: 10.21228/M80981 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	ST001849
Study Title	Longitudinal Metabolomics of Human Plasma Reveals Robust Prognostic Markers of COVID-19 Disease Severity (part I)
Study Summary	There is an urgent need to identify which COVID-19 patients will develop life-threatening illness so that medical resources can be optimally allocated and rapid treatment can be administered early in the disease course, when clinical management is most effective. To aid in the prognostic classification of disease severity, we perform untargeted metabolomics on plasma from 339 patients, with samples collected at six longitudinal time points. Using the temporal metabolic profiles and machine learning, we build a predictive model of disease severity. We discover that a panel of metabolites measured at the time of study entry successfully determine disease severity. Through analysis of longitudinal samples, we confirm that the majority of these markers are directly related to disease progression and that their levels are restored to baseline upon disease recovery. Finally, we validate that these metabolites are also altered in a hamster model of COVID-19. Our results indicate that metabolic changes associated with COVID-19 severity can be effectively used to stratify patients and inform resource allocation during the pandemic.
Institute	Washington University in St. Louis
Department	Chemistry
Laboratory	Patti
Last Name	Patti
First Name	Gary
Address	McMillen Chemistry Laboratory Washington University 1 Brookings Dr @ Throop Drive Rm 102 St. Louis, MO 63130-4899
Email	gjpattij@wustl.edu
Phone	314-935-3512
Submit Date	2021-01-29
Num Groups	3
Total Subjects	339
Num Males	184
Num Females	155
Raw Data Available	Yes
Raw Data File Type(s)	mzML
Analysis Type Detail	LC-MS
Release Date	2021-06-30
Release Version	1

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Sample Preparation:

Sampleprep ID:	SP001932
Sampleprep Summary:	Participant plasma, which had been stored at -80°C upon collection, was thawed on ice. A 50 µL aliquot was transferred onto the solid-phase-extraction (SPE)-system CAPTIVA-EMR Lipid 96-wellplate (Agilent Technologies) before addition of 250 µL of acetonitrile containing 1% formic acid (v/v) and 10 µM internal standard (consisting of uniformly 13C and 15N labeled amino acids from Cambridge Isotope Laboratories, Inc). The samples were mixed for 1 min at 360 rpm on an orbital shaker at room temperature prior to a 10 min incubation period at 4°C. Afterwards, 200 µL 80% acetonitrile in water (v/v) were added to the samples. The samples were mixed on an orbital shaker (360 rpm) for an additional 10 min at room temperature. The samples were then eluted into a 96-deepwell collection plate by centrifugation (10 min, 57 x g, 4°C followed by 2 min, 1000 x g, 4°C). Polar eluates were stored at -80°C until the day of LC/MS analysis. The SPE-plates were then washed twice with 500 µL 80% acetonitrile in water (v/v). Lipids still bound to the SPE-material were then released into a second elution plate, in two elution steps applying 2x 500 µL 1:1 methyl tert-butyl ether:methanol (v/v) onto the SPE cartridge and centrifuging for 2 min at 1000 g and 4°C. The combined eluates were dried under a stream of nitrogen (Biotage SPE Dry Evaporation System) at room temperature and reconstituted with 100 µL 1:1 2-propanol:methanol (v/v) prior to LC/MS analysis.
Processing Storage Conditions:	Described in summary
Extract Storage:	Described in summary