Untargeted saliva metabolomics by liquid chromatography—Mass spectrometry reveals markers of COVID-19 severity

The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:PloS one 2022-09, Vol.17 (9), p.e0274967-e0274967
Hauptverfasser: Frampas, Cecile F, Longman, Katie, Spick, Matt, Lewis, Holly-May, Costa, Catia D. S, Stewart, Alex, Dunn-Walters, Deborah, Greener, Danni, Evetts, George, Skene, Debra J, Trivedi, Drupad, Pitt, Andy, Hollywood, Katherine, Barran, Perdita, Bailey, Melanie J
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page e0274967
container_issue 9
container_start_page e0274967
container_title PloS one
container_volume 17
creator Frampas, Cecile F
Longman, Katie
Spick, Matt
Lewis, Holly-May
Costa, Catia D. S
Stewart, Alex
Dunn-Walters, Deborah
Greener, Danni
Evetts, George
Skene, Debra J
Trivedi, Drupad
Pitt, Andy
Hollywood, Katherine
Barran, Perdita
Bailey, Melanie J
description The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether markers can be found in different biofluids-are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum. Saliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing, and COVID-19 severity was classified using clinical descriptors (respiratory rate, peripheral oxygen saturation score and C-reactive protein levels). Metabolites were extracted and analysed using high resolution liquid chromatography-mass spectrometry, and the resulting peak area matrix was analysed using multivariate techniques. Positive percent agreement of 1.00 between a partial least squares-discriminant analysis metabolomics model employing a panel of 6 features (5 of which were amino acids, one that could be identified by formula only) and the clinical diagnosis of COVID-19 severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, leading to an area under receiver operating characteristics curve of 1.00 for the panel of features identified. In this exploratory work, we found that saliva metabolomics and in particular amino acids can be capable of separating high severity COVID-19 patients from low severity COVID-19 patients. This expands the atlas of COVID-19 metabolic dysregulation and could in future offer the basis of a quick and non-invasive means of sampling patients, intended to supplement existing clinical tests, with the goal of offering timely treatment to patients with potentially poor outcomes.
doi_str_mv 10.1371/journal.pone.0274967
format Article
fullrecord <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2716914089</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A719015834</galeid><doaj_id>oai_doaj_org_article_2a21482b62e947d7a81fae8bf52d1f93</doaj_id><sourcerecordid>A719015834</sourcerecordid><originalsourceid>FETCH-LOGICAL-c669t-6b7a9d4fcfc3054faf8f2b42e7318fc4663bdaf4e99656712e799780152c68153</originalsourceid><addsrcrecordid>eNqNk9-L1DAQx4soeJ7-B4IFQfRh1yZNk-ZFONZfCycL6t1rSNNJN2fb9JJ0cd_8I_wL_UvM3la5yj1IHhIyn_lmZjKTJE9RtkQ5Q6-v7Oh62S4H28Myw4xwyu4lJ4jneEFxlt-_dX6YPPL-KsuKvKT0JBku-iBdAwHq1MvW7GTaQZCVbW1nlE-rfdqa69HUqdo628lgGyeH7f7Xj5-fpPepH0CFaIDg9qmDHcjWp51038D51Op0tblcv10gnvpocybsHycPdGTgybSfJhfv331dfVycbz6sV2fnC0UpDwtaMclropVWeVYQLXWpcUUwsByVWhFK86qWmgDntKAMRQPnrMxQgRUtUZGfJs-OukNrvZgq5AVmiHJEspJHYn0kaiuvxOBMDHsvrDTi5sK6RkgXjGpBYIkRKXFFMXDCaiZLpCWUlS5wjTTPo9ab6bWx6qBW0Acn25no3NKbrWjsTnDCyxh3FHg5CTh7PYIPojNeQdvKHux4EzejZU7YIbPn_6B3ZzdRjYwJmF7b-K46iIozhngsVFSL1PIOKq4a4vfHdtIm3s8cXs0cIhPge2jk6L1Yf_n8_-zmcs6-uMVuYxuFrbftGIzt_RwkR1A5670D_bfIKBOHafhTDXGYBjFNQ_4b3rT-yQ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2716914089</pqid></control><display><type>article</type><title>Untargeted saliva metabolomics by liquid chromatography—Mass spectrometry reveals markers of COVID-19 severity</title><source>Public Library of Science (PLoS) Journals Open Access</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Frampas, Cecile F ; Longman, Katie ; Spick, Matt ; Lewis, Holly-May ; Costa, Catia D. S ; Stewart, Alex ; Dunn-Walters, Deborah ; Greener, Danni ; Evetts, George ; Skene, Debra J ; Trivedi, Drupad ; Pitt, Andy ; Hollywood, Katherine ; Barran, Perdita ; Bailey, Melanie J</creator><creatorcontrib>Frampas, Cecile F ; Longman, Katie ; Spick, Matt ; Lewis, Holly-May ; Costa, Catia D. S ; Stewart, Alex ; Dunn-Walters, Deborah ; Greener, Danni ; Evetts, George ; Skene, Debra J ; Trivedi, Drupad ; Pitt, Andy ; Hollywood, Katherine ; Barran, Perdita ; Bailey, Melanie J</creatorcontrib><description>The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether markers can be found in different biofluids-are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum. Saliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing, and COVID-19 severity was classified using clinical descriptors (respiratory rate, peripheral oxygen saturation score and C-reactive protein levels). Metabolites were extracted and analysed using high resolution liquid chromatography-mass spectrometry, and the resulting peak area matrix was analysed using multivariate techniques. Positive percent agreement of 1.00 between a partial least squares-discriminant analysis metabolomics model employing a panel of 6 features (5 of which were amino acids, one that could be identified by formula only) and the clinical diagnosis of COVID-19 severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, leading to an area under receiver operating characteristics curve of 1.00 for the panel of features identified. In this exploratory work, we found that saliva metabolomics and in particular amino acids can be capable of separating high severity COVID-19 patients from low severity COVID-19 patients. This expands the atlas of COVID-19 metabolic dysregulation and could in future offer the basis of a quick and non-invasive means of sampling patients, intended to supplement existing clinical tests, with the goal of offering timely treatment to patients with potentially poor outcomes.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0274967</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Agreements ; Amino acids ; Biological markers ; Biology and Life Sciences ; Biomarkers ; C-reactive protein ; Chromatography ; Consent ; Coronaviruses ; COVID-19 ; COVID-19 vaccines ; Diagnosis ; Discriminant analysis ; Global health ; Identification and classification ; Infections ; Liquid chromatography ; Markers ; Mass spectrometry ; Mass spectroscopy ; Medical research ; Medicine and Health Sciences ; Metabolism ; Metabolites ; Metabolomics ; Methods ; Oxygen ; Oxygen content ; Pandemics ; Patients ; Physical Sciences ; Polymerase chain reaction ; Public health ; Research and Analysis Methods ; Respiration ; Respiratory rate ; Saliva ; Salivary glands ; Sampling ; Scientific imaging ; secretions ; Severe acute respiratory syndrome coronavirus 2 ; Spectroscopy ; Testing ; Vaccines</subject><ispartof>PloS one, 2022-09, Vol.17 (9), p.e0274967-e0274967</ispartof><rights>COPYRIGHT 2022 Public Library of Science</rights><rights>2022 Frampas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 Frampas et al 2022 Frampas et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c669t-6b7a9d4fcfc3054faf8f2b42e7318fc4663bdaf4e99656712e799780152c68153</citedby><cites>FETCH-LOGICAL-c669t-6b7a9d4fcfc3054faf8f2b42e7318fc4663bdaf4e99656712e799780152c68153</cites><orcidid>0000-0002-9417-6511 ; 0000-0001-8202-6180</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498978/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498978/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids></links><search><creatorcontrib>Frampas, Cecile F</creatorcontrib><creatorcontrib>Longman, Katie</creatorcontrib><creatorcontrib>Spick, Matt</creatorcontrib><creatorcontrib>Lewis, Holly-May</creatorcontrib><creatorcontrib>Costa, Catia D. S</creatorcontrib><creatorcontrib>Stewart, Alex</creatorcontrib><creatorcontrib>Dunn-Walters, Deborah</creatorcontrib><creatorcontrib>Greener, Danni</creatorcontrib><creatorcontrib>Evetts, George</creatorcontrib><creatorcontrib>Skene, Debra J</creatorcontrib><creatorcontrib>Trivedi, Drupad</creatorcontrib><creatorcontrib>Pitt, Andy</creatorcontrib><creatorcontrib>Hollywood, Katherine</creatorcontrib><creatorcontrib>Barran, Perdita</creatorcontrib><creatorcontrib>Bailey, Melanie J</creatorcontrib><title>Untargeted saliva metabolomics by liquid chromatography—Mass spectrometry reveals markers of COVID-19 severity</title><title>PloS one</title><description>The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether markers can be found in different biofluids-are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum. Saliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing, and COVID-19 severity was classified using clinical descriptors (respiratory rate, peripheral oxygen saturation score and C-reactive protein levels). Metabolites were extracted and analysed using high resolution liquid chromatography-mass spectrometry, and the resulting peak area matrix was analysed using multivariate techniques. Positive percent agreement of 1.00 between a partial least squares-discriminant analysis metabolomics model employing a panel of 6 features (5 of which were amino acids, one that could be identified by formula only) and the clinical diagnosis of COVID-19 severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, leading to an area under receiver operating characteristics curve of 1.00 for the panel of features identified. In this exploratory work, we found that saliva metabolomics and in particular amino acids can be capable of separating high severity COVID-19 patients from low severity COVID-19 patients. This expands the atlas of COVID-19 metabolic dysregulation and could in future offer the basis of a quick and non-invasive means of sampling patients, intended to supplement existing clinical tests, with the goal of offering timely treatment to patients with potentially poor outcomes.</description><subject>Agreements</subject><subject>Amino acids</subject><subject>Biological markers</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers</subject><subject>C-reactive protein</subject><subject>Chromatography</subject><subject>Consent</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 vaccines</subject><subject>Diagnosis</subject><subject>Discriminant analysis</subject><subject>Global health</subject><subject>Identification and classification</subject><subject>Infections</subject><subject>Liquid chromatography</subject><subject>Markers</subject><subject>Mass spectrometry</subject><subject>Mass spectroscopy</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Metabolomics</subject><subject>Methods</subject><subject>Oxygen</subject><subject>Oxygen content</subject><subject>Pandemics</subject><subject>Patients</subject><subject>Physical Sciences</subject><subject>Polymerase chain reaction</subject><subject>Public health</subject><subject>Research and Analysis Methods</subject><subject>Respiration</subject><subject>Respiratory rate</subject><subject>Saliva</subject><subject>Salivary glands</subject><subject>Sampling</subject><subject>Scientific imaging</subject><subject>secretions</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>Spectroscopy</subject><subject>Testing</subject><subject>Vaccines</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNk9-L1DAQx4soeJ7-B4IFQfRh1yZNk-ZFONZfCycL6t1rSNNJN2fb9JJ0cd_8I_wL_UvM3la5yj1IHhIyn_lmZjKTJE9RtkQ5Q6-v7Oh62S4H28Myw4xwyu4lJ4jneEFxlt-_dX6YPPL-KsuKvKT0JBku-iBdAwHq1MvW7GTaQZCVbW1nlE-rfdqa69HUqdo628lgGyeH7f7Xj5-fpPepH0CFaIDg9qmDHcjWp51038D51Op0tblcv10gnvpocybsHycPdGTgybSfJhfv331dfVycbz6sV2fnC0UpDwtaMclropVWeVYQLXWpcUUwsByVWhFK86qWmgDntKAMRQPnrMxQgRUtUZGfJs-OukNrvZgq5AVmiHJEspJHYn0kaiuvxOBMDHsvrDTi5sK6RkgXjGpBYIkRKXFFMXDCaiZLpCWUlS5wjTTPo9ab6bWx6qBW0Acn25no3NKbrWjsTnDCyxh3FHg5CTh7PYIPojNeQdvKHux4EzejZU7YIbPn_6B3ZzdRjYwJmF7b-K46iIozhngsVFSL1PIOKq4a4vfHdtIm3s8cXs0cIhPge2jk6L1Yf_n8_-zmcs6-uMVuYxuFrbftGIzt_RwkR1A5670D_bfIKBOHafhTDXGYBjFNQ_4b3rT-yQ</recordid><startdate>20220922</startdate><enddate>20220922</enddate><creator>Frampas, Cecile F</creator><creator>Longman, Katie</creator><creator>Spick, Matt</creator><creator>Lewis, Holly-May</creator><creator>Costa, Catia D. S</creator><creator>Stewart, Alex</creator><creator>Dunn-Walters, Deborah</creator><creator>Greener, Danni</creator><creator>Evetts, George</creator><creator>Skene, Debra J</creator><creator>Trivedi, Drupad</creator><creator>Pitt, Andy</creator><creator>Hollywood, Katherine</creator><creator>Barran, Perdita</creator><creator>Bailey, Melanie J</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>COVID</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-9417-6511</orcidid><orcidid>https://orcid.org/0000-0001-8202-6180</orcidid></search><sort><creationdate>20220922</creationdate><title>Untargeted saliva metabolomics by liquid chromatography—Mass spectrometry reveals markers of COVID-19 severity</title><author>Frampas, Cecile F ; Longman, Katie ; Spick, Matt ; Lewis, Holly-May ; Costa, Catia D. S ; Stewart, Alex ; Dunn-Walters, Deborah ; Greener, Danni ; Evetts, George ; Skene, Debra J ; Trivedi, Drupad ; Pitt, Andy ; Hollywood, Katherine ; Barran, Perdita ; Bailey, Melanie J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c669t-6b7a9d4fcfc3054faf8f2b42e7318fc4663bdaf4e99656712e799780152c68153</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Agreements</topic><topic>Amino acids</topic><topic>Biological markers</topic><topic>Biology and Life Sciences</topic><topic>Biomarkers</topic><topic>C-reactive protein</topic><topic>Chromatography</topic><topic>Consent</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>COVID-19 vaccines</topic><topic>Diagnosis</topic><topic>Discriminant analysis</topic><topic>Global health</topic><topic>Identification and classification</topic><topic>Infections</topic><topic>Liquid chromatography</topic><topic>Markers</topic><topic>Mass spectrometry</topic><topic>Mass spectroscopy</topic><topic>Medical research</topic><topic>Medicine and Health Sciences</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Metabolomics</topic><topic>Methods</topic><topic>Oxygen</topic><topic>Oxygen content</topic><topic>Pandemics</topic><topic>Patients</topic><topic>Physical Sciences</topic><topic>Polymerase chain reaction</topic><topic>Public health</topic><topic>Research and Analysis Methods</topic><topic>Respiration</topic><topic>Respiratory rate</topic><topic>Saliva</topic><topic>Salivary glands</topic><topic>Sampling</topic><topic>Scientific imaging</topic><topic>secretions</topic><topic>Severe acute respiratory syndrome coronavirus 2</topic><topic>Spectroscopy</topic><topic>Testing</topic><topic>Vaccines</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Frampas, Cecile F</creatorcontrib><creatorcontrib>Longman, Katie</creatorcontrib><creatorcontrib>Spick, Matt</creatorcontrib><creatorcontrib>Lewis, Holly-May</creatorcontrib><creatorcontrib>Costa, Catia D. S</creatorcontrib><creatorcontrib>Stewart, Alex</creatorcontrib><creatorcontrib>Dunn-Walters, Deborah</creatorcontrib><creatorcontrib>Greener, Danni</creatorcontrib><creatorcontrib>Evetts, George</creatorcontrib><creatorcontrib>Skene, Debra J</creatorcontrib><creatorcontrib>Trivedi, Drupad</creatorcontrib><creatorcontrib>Pitt, Andy</creatorcontrib><creatorcontrib>Hollywood, Katherine</creatorcontrib><creatorcontrib>Barran, Perdita</creatorcontrib><creatorcontrib>Bailey, Melanie J</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Frampas, Cecile F</au><au>Longman, Katie</au><au>Spick, Matt</au><au>Lewis, Holly-May</au><au>Costa, Catia D. S</au><au>Stewart, Alex</au><au>Dunn-Walters, Deborah</au><au>Greener, Danni</au><au>Evetts, George</au><au>Skene, Debra J</au><au>Trivedi, Drupad</au><au>Pitt, Andy</au><au>Hollywood, Katherine</au><au>Barran, Perdita</au><au>Bailey, Melanie J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Untargeted saliva metabolomics by liquid chromatography—Mass spectrometry reveals markers of COVID-19 severity</atitle><jtitle>PloS one</jtitle><date>2022-09-22</date><risdate>2022</risdate><volume>17</volume><issue>9</issue><spage>e0274967</spage><epage>e0274967</epage><pages>e0274967-e0274967</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether markers can be found in different biofluids-are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum. Saliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing, and COVID-19 severity was classified using clinical descriptors (respiratory rate, peripheral oxygen saturation score and C-reactive protein levels). Metabolites were extracted and analysed using high resolution liquid chromatography-mass spectrometry, and the resulting peak area matrix was analysed using multivariate techniques. Positive percent agreement of 1.00 between a partial least squares-discriminant analysis metabolomics model employing a panel of 6 features (5 of which were amino acids, one that could be identified by formula only) and the clinical diagnosis of COVID-19 severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, leading to an area under receiver operating characteristics curve of 1.00 for the panel of features identified. In this exploratory work, we found that saliva metabolomics and in particular amino acids can be capable of separating high severity COVID-19 patients from low severity COVID-19 patients. This expands the atlas of COVID-19 metabolic dysregulation and could in future offer the basis of a quick and non-invasive means of sampling patients, intended to supplement existing clinical tests, with the goal of offering timely treatment to patients with potentially poor outcomes.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><doi>10.1371/journal.pone.0274967</doi><tpages>e0274967</tpages><orcidid>https://orcid.org/0000-0002-9417-6511</orcidid><orcidid>https://orcid.org/0000-0001-8202-6180</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1932-6203
ispartof PloS one, 2022-09, Vol.17 (9), p.e0274967-e0274967
issn 1932-6203
1932-6203
language eng
recordid cdi_plos_journals_2716914089
source Public Library of Science (PLoS) Journals Open Access; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry
subjects Agreements
Amino acids
Biological markers
Biology and Life Sciences
Biomarkers
C-reactive protein
Chromatography
Consent
Coronaviruses
COVID-19
COVID-19 vaccines
Diagnosis
Discriminant analysis
Global health
Identification and classification
Infections
Liquid chromatography
Markers
Mass spectrometry
Mass spectroscopy
Medical research
Medicine and Health Sciences
Metabolism
Metabolites
Metabolomics
Methods
Oxygen
Oxygen content
Pandemics
Patients
Physical Sciences
Polymerase chain reaction
Public health
Research and Analysis Methods
Respiration
Respiratory rate
Saliva
Salivary glands
Sampling
Scientific imaging
secretions
Severe acute respiratory syndrome coronavirus 2
Spectroscopy
Testing
Vaccines
title Untargeted saliva metabolomics by liquid chromatography—Mass spectrometry reveals markers of COVID-19 severity
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T05%3A25%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Untargeted%20saliva%20metabolomics%20by%20liquid%20chromatography%E2%80%94Mass%20spectrometry%20reveals%20markers%20of%20COVID-19%20severity&rft.jtitle=PloS%20one&rft.au=Frampas,%20Cecile%20F&rft.date=2022-09-22&rft.volume=17&rft.issue=9&rft.spage=e0274967&rft.epage=e0274967&rft.pages=e0274967-e0274967&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0274967&rft_dat=%3Cgale_plos_%3EA719015834%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2716914089&rft_id=info:pmid/&rft_galeid=A719015834&rft_doaj_id=oai_doaj_org_article_2a21482b62e947d7a81fae8bf52d1f93&rfr_iscdi=true