Summary of Study ST002829

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 PR001771. The data can be accessed directly via it's Project DOI: 10.21228/M8SM6H This work is supported by NIH grant, U2C- DK119886.

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Study IDST002829
Study TitleNucleotide, phospholipid, and kynurenine metabolites are robustly associated with COVID-19 severity and time of plasma sample collection in a prospective cohort study
Study SummaryIntroduction: A deep understanding of the molecular underpinnings of disease severity and progression in large human studies is necessary to develop metabolism-related preventive strategies of severe disease outcomes, particularly in viral pandemics like that of COVID-19. The use of samples collected before disease diagnosis, however, is limited and thus metabolites and metabolic pathways that predispose to severe disease are not well understood. Further, current studies are limited in sample size, number of metabolites evaluated, and/or do not adjust for comorbidities. Methods: We generated comprehensive plasma metabolomic profiles in more than 600 patients from the Longitudinal EMR and Omics COVID-19 Cohort (LEOCC). Samples were collected before (n = 441), during (n = 86), and after (n = 82) COVID-19 diagnosis. Regression models were used to determine (1) metabolites associated with predisposition to and/or persistent effects of COVID-19 severity within each time of sample collection, using logistic regression and (2) metabolites associated with time of sample collection, using linear regression, to better understand transient or lingering metabolic alterations over the disease course. All models were controlled for demographic (age, sex, race, ethnicity), risk (smoking status, BMI), and comorbidities (Charlson Index). Metabolites with an FDR-adjusted p-value < 0.05 were considered significant. Results: Of the 1,546 metabolites measured, 506 were associated with disease severity or time of sample collection. Among these, sphingolipids and phospholipids were negatively associated with severity and exhibited lingering elevations after disease, while modified nucleotides were positively associated with severity and had lingering decreases after disease. Cytidine and uridine metabolites, which were positively and negatively associated with COVID-19 severity, respectively, were transiently elevated in active disease, reflecting particular importance of pyrimidine metabolism in active COVID-19. Conclusions: We identified novel metabolites reflecting predisposition to severe disease and changes to global metabolism from before to during and after COVID-19 diagnosis. This is the first large metabolomics study using COVID-19 plasma samples before, during, and/or after disease. This study lays the groundwork for identifying putative clinical biomarkers and identifying preventative strategies for severe disease outcomes.
Institute
National Institutes of Health
DepartmentDivision of Preclinical Innovation - National Center for Advancing Translational Sciences
LaboratoryInformatics Core - Division of Preclinical Innovation
Last NameChatelaine
First NameHaley
Address9800 Medical Center Drive
Emailhaley.chatelaine@nih.gov
Phone952-738-2061
Submit Date2023-08-24
Num Groups4
Total Subjects609
Num Males232
Num Females377
Analysis Type DetailOther
Release Date2023-09-19
Release Version1
Haley Chatelaine Haley Chatelaine
https://dx.doi.org/10.21228/M8SM6H
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:

Project:

Project ID:PR001771
Project DOI:doi: 10.21228/M8SM6H
Project Title:Nucleotide, phospholipid, and kynurenine metabolites are robustly associated with COVID-19 severity and time of plasma sample collection in a prospective cohort study
Project Summary:Introduction: A deep understanding of the molecular underpinnings of disease severity and progression in large human studies is necessary to develop metabolism-related preventive strategies of severe disease outcomes, particularly in viral pandemics like that of COVID-19. The use of samples collected before disease diagnosis, however, is limited and thus metabolites and metabolic pathways that predispose to severe disease are not well understood. Further, current studies are limited in sample size, number of metabolites evaluated, and/or do not adjust for comorbidities. Methods: We generated comprehensive plasma metabolomic profiles in more than 600 patients from the Longitudinal EMR and Omics COVID-19 Cohort (LEOCC). Samples were collected before (n = 441), during (n = 86), and after (n = 82) COVID-19 diagnosis. Regression models were used to determine (1) metabolites associated with predisposition to and/or persistent effects of COVID-19 severity within each time of sample collection, using logistic regression and (2) metabolites associated with time of sample collection, using linear regression, to better understand transient or lingering metabolic alterations over the disease course. All models were controlled for demographic (age, sex, race, ethnicity), risk (smoking status, BMI), and comorbidities (Charlson Index). Metabolites with an FDR-adjusted p-value < 0.05 were considered significant. Results: Of the 1,546 metabolites measured, 506 were associated with disease severity or time of sample collection. Among these, sphingolipids and phospholipids were negatively associated with severity and exhibited lingering elevations after disease, while modified nucleotides were positively associated with severity and had lingering decreases after disease. Cytidine and uridine metabolites, which were positively and negatively associated with COVID-19 severity, respectively, were transiently elevated in active disease, reflecting particular importance of pyrimidine metabolism in active COVID-19. Conclusions: We identified novel metabolites reflecting predisposition to severe disease and changes to global metabolism from before to during and after COVID-19 diagnosis. This is the first large metabolomics study using COVID-19 plasma samples before, during, and/or after disease. This study lays the groundwork for identifying putative clinical biomarkers and identifying preventative strategies for severe disease outcomes.
Institute:National Institutes of Health
Department:Division of Preclinical Innovation - National Center for Advancing Translational Sciences
Laboratory:Informatics Core
Last Name:Chatelaine
First Name:Haley
Address:9800 Medical Center Drive
Email:haley.chatelaine@nih.gov
Phone:952-738-2061

Subject:

Subject ID:SU002938
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606
Age Or Age Range:35 - 69
Gender:Male and female
Human Race:Black, White, Other
Human Ethnicity:Hispanic, Non-Hispanic
Human Smoking Status:Yes or No
Human Inclusion Criteria:positive COVID-19 diagnosis and plasma sample available

Factors:

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

mb_sample_id local_sample_id Sex Severity_Scale Race Ethnicity hasSmokingBeforeCOVID-19 Time
SA305873NATS-00851Female 0 Black Non-Hispanic 0 during COVID-19
SA305874NATS-01145Female 0 Black Non-Hispanic 0 during COVID-19
SA305875NATS-00824Female 0 Black Non-Hispanic 0 post-COVID-19
SA305876NATS-00504Female 0 Black Non-Hispanic 0 post-COVID-19
SA305877NATS-00345Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305878NATS-00285Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305879NATS-00680Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305880NATS-00720Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305881NATS-00338Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305882NATS-00297Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305883NATS-00755Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305884NATS-00331Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305885NATS-00315Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305886NATS-00470Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305887NATS-00436Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305888NATS-00666Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305889NATS-00443Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305890NATS-00494Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305891NATS-00262Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305892NATS-00576Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305893NATS-00425Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305894NATS-00613Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305895NATS-00658Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305896NATS-00410Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305897NATS-00603Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305898NATS-00400Female 0 Black Non-Hispanic 0 pre-COVID-19
SA305899NATS-00298Female 0 Black Non-Hispanic 1 pre-COVID-19
SA305900NATS-00779Female 0 Black Non-Hispanic 1 pre-COVID-19
SA305901NATS-00307Female 0 Black Non-Hispanic 1 pre-COVID-19
SA305902NATS-00669Female 0 Black Non-Hispanic 1 pre-COVID-19
SA305903NATS-00901Female 0 Other Hispanic 0 during COVID-19
SA305904NATS-00292Female 0 Other Hispanic 0 post-COVID-19
SA305905NATS-01074Female 0 Other Hispanic 0 post-COVID-19
SA305906NATS-00562Female 0 Other Hispanic 0 pre-COVID-19
SA305907NATS-00741Female 0 Other Hispanic 0 pre-COVID-19
SA305908NATS-00566Female 0 Other Hispanic 0 pre-COVID-19
SA305909NATS-00567Female 0 Other Hispanic 0 pre-COVID-19
SA305910NATS-00596Female 0 Other Hispanic 0 pre-COVID-19
SA305911NATS-00439Female 0 Other Hispanic 0 pre-COVID-19
SA305912NATS-00558Female 0 Other Hispanic 0 pre-COVID-19
SA305913NATS-00559Female 0 Other Hispanic 0 pre-COVID-19
SA305914NATS-00595Female 0 Other Hispanic 0 pre-COVID-19
SA305915NATS-00557Female 0 Other Hispanic 0 pre-COVID-19
SA305916NATS-00569Female 0 Other Hispanic 0 pre-COVID-19
SA305917NATS-00587Female 0 Other Hispanic 0 pre-COVID-19
SA305918NATS-00590Female 0 Other Hispanic 0 pre-COVID-19
SA305919NATS-00591Female 0 Other Hispanic 0 pre-COVID-19
SA305920NATS-00585Female 0 Other Hispanic 0 pre-COVID-19
SA305921NATS-00580Female 0 Other Hispanic 0 pre-COVID-19
SA305922NATS-00549Female 0 Other Hispanic 0 pre-COVID-19
SA305923NATS-00571Female 0 Other Hispanic 0 pre-COVID-19
SA305924NATS-00579Female 0 Other Hispanic 0 pre-COVID-19
SA305925NATS-00278Female 0 Other Hispanic 0 pre-COVID-19
SA305926NATS-00442Female 0 Other Hispanic 0 pre-COVID-19
SA305927NATS-00508Female 0 Other Hispanic 0 pre-COVID-19
SA305928NATS-00629Female 0 Other Hispanic 0 pre-COVID-19
SA305929NATS-00620Female 0 Other Hispanic 0 pre-COVID-19
SA305930NATS-00498Female 0 Other Hispanic 0 pre-COVID-19
SA305931NATS-00652Female 0 Other Hispanic 0 pre-COVID-19
SA305932NATS-00479Female 0 Other Hispanic 0 pre-COVID-19
SA305933NATS-00490Female 0 Other Hispanic 0 pre-COVID-19
SA305934NATS-00492Female 0 Other Hispanic 0 pre-COVID-19
SA305935NATS-00548Female 0 Other Hispanic 0 pre-COVID-19
SA305936NATS-00598Female 0 Other Hispanic 0 pre-COVID-19
SA305937NATS-00446Female 0 Other Hispanic 0 pre-COVID-19
SA305938NATS-00283Female 0 Other Hispanic 0 pre-COVID-19
SA305939NATS-00528Female 0 Other Hispanic 0 pre-COVID-19
SA305940NATS-00593Female 0 Other Hispanic 0 pre-COVID-19
SA305941NATS-00514Female 0 Other Hispanic 0 pre-COVID-19
SA305942NATS-00527Female 0 Other Hispanic 0 pre-COVID-19
SA305943NATS-00404Female 0 Other Hispanic 0 pre-COVID-19
SA305944NATS-00518Female 0 Other Hispanic 0 pre-COVID-19
SA305945NATS-01183Female 0 Other Hispanic 1 during COVID-19
SA305946NATS-00512Female 0 Other Hispanic 1 pre-COVID-19
SA305947NATS-00350Female 0 Other Hispanic 1 pre-COVID-19
SA305948NATS-01088Female 0 Other Non-Hispanic 0 post-COVID-19
SA305949NATS-01120Female 0 Other Non-Hispanic 0 post-COVID-19
SA305950NATS-00380Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305951NATS-00600Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305952NATS-00511Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305953NATS-00510Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305954NATS-00493Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305955NATS-00453Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305956NATS-00597Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305957NATS-00631Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305958NATS-00568Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305959NATS-00519Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305960NATS-00403Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305961NATS-00450Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305962NATS-00582Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305963NATS-00376Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305964NATS-00355Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305965NATS-00279Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305966NATS-00686Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305967NATS-01065Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305968NATS-00366Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305969NATS-00766Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305970NATS-00761Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305971NATS-00759Female 0 Other Non-Hispanic 0 pre-COVID-19
SA305972NATS-00291Female 0 Other Non-Hispanic 1 pre-COVID-19
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Collection:

Collection ID:CO002931
Collection Summary:The Mass General Brigham (MGB) Biobank contains ~100,000 banked plasma, serum, and DNA samples from >100,000 consented patients. Electronic Medical Record (EMR) data and lifestyle, environment, and family history surveys can also be linked to the banked samples. The Longitudinal EMR and Omics COVID-19 Cohort (LEOCC) consists of a subset of individuals with prospective plasma samples from the MGB Biobank. Patients with a positive COVID-19 diagnosis (defined as a COVID-19 positive infection control flag, COVID-19 presumed infection control flag, or SARS-CoV-2 RNA positive test result) and available plasma samples prior to COVID-19 (up to October 27, 2020) were included. No additional exclusion criteria were applied. Clinical data relevant to COVID-19 infection, including clinical measures, disease diagnoses, and COVID-19 severity were also extracted from EMR data for use in statistical models. This study was approved by the Brigham and Women’s Institutional Review Board (IRB: 2014P001109). A total of 940 plasma samples from 661 individuals were collected from consented patients and were stored at –80 C. These samples are categorized by the time point of collection relative to a positive COVID-19 diagnosis, including 474 pre-COVID-19 samples (date of collection < date of diagnosis), 282 during COVID-19 samples (collected within 28 days of diagnosis), and 182 post-COVID-19 samples (collected more than 28 days after COVID-19 diagnosis). For patients with multiple during and/or post-COVID-19 samples, only the sample collected at the date closest to diagnosis was retained for during-COVID-19, and only the sample collected at the date furthest from diagnosis was retained for post-COVID-19. Patients without BMI data were also excluded from the sample sets, yielding a total of n = 441 pre-COVID-19, n = 86 during COVID-19, and n = 82 post-COVID-19 samples used for analysis.
Sample Type:Blood (plasma)

Treatment:

Treatment ID:TR002947
Treatment Summary:The COVID-19 severity level was determined according to WHO guidelines (16) as 0 = ambulatory mild disease (no hospitalization), 1 = hospitalized moderate disease (hospitalized without ventilation), 2 = hospitalized severe disease (hospitalized with ventilation), or 3 = death. Further demographic, risk factor, and comorbidity covariables were defined before COVID-19 diagnosis for all patients as follows: age is the numerical patient age; race is categorical (black, other, white); ethnicity (Hispanic/non-Hispanic), sex (female/male), and smoking (yes/no) are binary; BMI is the numerical median body mass index (BMI) for each patient; and comorbidity level is a binary “mild” or “severe” factor based on a Charlson index < 5 or ≥ 5, respectively.

Sample Preparation:

Sampleprep ID:SP002944
Sampleprep Summary:Plasma samples were sent to Metabolon for comprehensive metabolomic profiling of polar and nonpolar metabolite classes in plasma extracts. Samples were extracted and prepared according to methods published previously (19).

Combined analysis:

Analysis ID AN004619 AN004620 AN004621 AN004622
Analysis type MS MS MS MS
Chromatography type Reversed phase Reversed phase Reversed phase HILIC
Chromatography system Waters Acquity Waters Acquity Waters Acquity Waters Acquity
Column Waters ACQUITY UPLC BEH C18 (100 x 2.1mm,1.7um) Waters ACQUITY UPLC BEH C18 (100 x 2.1mm,1.7um) Waters ACQUITY UPLC BEH C18 (100 x 2.1mm,1.7um) Waters Acquity BEH Amide (150 x 2.1mm, 1.7um)
MS Type ESI ESI ESI ESI
MS instrument type Orbitrap Orbitrap Orbitrap Orbitrap
MS instrument name Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap
Ion Mode POSITIVE POSITIVE NEGATIVE NEGATIVE
Units log transformed data log transformed data log transformed data log transformed data

Chromatography:

Chromatography ID:CH003475
Chromatography Summary:Low pH polar (LC/MS Pos early)
Instrument Name:Waters Acquity
Column Name:Waters ACQUITY UPLC BEH C18 (100 x 2.1mm,1.7um)
Column Temperature:-
Flow Gradient:-
Flow Rate:-
Solvent A:-
Solvent B:-
Chromatography Type:Reversed phase
  
Chromatography ID:CH003476
Chromatography Summary:Low pH Lipophilic (LC/MS Pos late)
Instrument Name:Waters Acquity
Column Name:Waters ACQUITY UPLC BEH C18 (100 x 2.1mm,1.7um)
Column Temperature:-
Flow Gradient:-
Flow Rate:-
Solvent A:-
Solvent B:-
Chromatography Type:Reversed phase
  
Chromatography ID:CH003477
Chromatography Summary:High pH (LC/MS Neg)
Instrument Name:Waters Acquity
Column Name:Waters ACQUITY UPLC BEH C18 (100 x 2.1mm,1.7um)
Column Temperature:-
Flow Gradient:-
Flow Rate:-
Solvent A:-
Solvent B:-
Chromatography Type:Reversed phase
  
Chromatography ID:CH003478
Chromatography Summary:HILIC (LC/MS Polar Neg)
Instrument Name:Waters Acquity
Column Name:Waters Acquity BEH Amide (150 x 2.1mm, 1.7um)
Column Temperature:-
Flow Gradient:-
Flow Rate:-
Solvent A:-
Solvent B:-
Chromatography Type:HILIC

MS:

MS ID:MS004365
Analysis ID:AN004619
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Metabolon (LC/MS Pos early)
Ion Mode:POSITIVE
Analysis Protocol File:Metabolon_Data_Filtering_and_Normalization_LEOCC.pdf
  
MS ID:MS004366
Analysis ID:AN004620
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Metabolon (LC/MS Pos late)
Ion Mode:POSITIVE
Analysis Protocol File:Metabolon_Data_Filtering_and_Normalization_LEOCC.pdf
  
MS ID:MS004367
Analysis ID:AN004621
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Metabolon (LC/MS Neg)
Ion Mode:NEGATIVE
Analysis Protocol File:Metabolon_Data_Filtering_and_Normalization_LEOCC.pdf
  
MS ID:MS004368
Analysis ID:AN004622
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Metabolon (LC/MS Polar)
Ion Mode:NEGATIVE
Analysis Protocol File:Metabolon_Data_Filtering_and_Normalization_LEOCC.pdf
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