Alterations in the molecular composition of COVID-19 patient urine, detected using Raman spectroscopic/computational analysis

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dc.contributor.authorRobertson, John L.en
dc.contributor.authorSenger, Ryan S.en
dc.contributor.authorTalty, Janineen
dc.contributor.authorDu, Pangen
dc.contributor.authorSayed-Issa, Amren
dc.contributor.authorAvellar, Maggie L.en
dc.contributor.authorNgo, Lacy T.en
dc.contributor.authorGomez de la Espriella, Marianaen
dc.contributor.authorFazili, Tasaduq N.en
dc.contributor.authorJackson-Akers, Jasmine Y.en
dc.contributor.authorGuruli, Georgien
dc.contributor.authorOrlando, Giuseppeen
dc.contributor.editorBussolati, Benedettaen
dc.date.accessioned2022-08-09T20:32:46Zen
dc.date.available2022-08-09T20:32:46Zen
dc.date.issued2022-07-01en
dc.date.updated2022-08-08T21:25:01Zen
dc.description.abstractWe developed and tested a method to detect COVID-19 disease, using urine specimens. The technology is based on Raman spectroscopy and computational analysis. It does not detect SARS-CoV-2 virus or viral components, but rather a urine ‘molecular fingerprint’, representing systemic metabolic, inflammatory, and immunologic reactions to infection. We analyzed voided urine specimens from 46 symptomatic COVID-19 patients with positive real time-polymerase chain reaction (RT-PCR) tests for infection or household contact with test-positive patients. We compared their urine Raman spectra with urine Raman spectra from healthy individuals (n = 185), peritoneal dialysis patients (n = 20), and patients with active bladder cancer (n = 17), collected between 2016–2018 (i.e., pre-COVID-19). We also compared all urine Raman spectra with urine specimens collected from healthy, fully vaccinated volunteers (n = 19) from July to September 2021. Disease severity (primarily respiratory) ranged among mild (n = 25), moderate (n = 14), and severe (n = 7). Seventy percent of patients sought evaluation within 14 days of onset. One severely affected patient was hospitalized, the remainder being managed with home/ambulatory care. Twenty patients had clinical pathology profiling. Seven of 20 patients had mildly elevated serum creatinine values (>0.9 mg/dl; range 0.9–1.34 mg/dl) and 6/7 of these patients also had estimated glomerular filtration rates (eGFR) <90 mL/min/1.73m2 (range 59–84 mL/min/1.73m2). We could not determine if any of these patients had antecedent clinical pathology abnormalities. Our technology (Raman Chemometric Urinalysis—Rametrix®) had an overall prediction accuracy of 97.6% for detecting complex, multimolecular fingerprints in urine associated with COVID-19 disease. The sensitivity of this model for detecting COVID-19 was 90.9%. The specificity was 98.8%, the positive predictive value was 93.0%, and the negative predictive value was 98.4%. In assessing severity, the method showed to be accurate in identifying symptoms as mild, moderate, or severe (random chance = 33%) based on the urine multimolecular fingerprint. Finally, a fingerprint of ‘Long COVID-19’ symptoms (defined as lasting longer than 30 days) was located in urine. Our methods were able to locate the presence of this fingerprint with 70.0% sensitivity and 98.7% specificity in leave-one-out cross-validation analysis. Further validation testing will include sampling more patients, examining correlations of disease severity and/or duration, and employing metabolomic analysis (Gas Chromatography–Mass Spectrometry [GC-MS], High Performance Liquid Chromatography [HPLC]) to identify individual components contributing to COVID-19 molecular fingerprints.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0270914en
dc.identifier.eissn1932-6203en
dc.identifier.issn1932-6203en
dc.identifier.orcidSenger, Ryan [0000-0002-2450-6693]en
dc.identifier.orcidRobertson, John [0000-0002-5499-9943]en
dc.identifier.orcidDu, Pang [0000-0003-1365-4831]en
dc.identifier.orcidGomez, Mariana [0000-0001-8963-9959]en
dc.identifier.otherPONE-D-21-38432 (PII)en
dc.identifier.pmid35849572en
dc.identifier.urihttp://hdl.handle.net/10919/111492en
dc.identifier.volume17en
dc.language.isoenen
dc.publisherPLOSen
dc.relation.urihttps://www.ncbi.nlm.nih.gov/pubmed/35849572en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectClinical Researchen
dc.subject4.2 Evaluation of markers and technologiesen
dc.subject4.1 Discovery and preclinical testing of markers and technologiesen
dc.subject4 Detection, screening and diagnosisen
dc.subject.meshHumansen
dc.subject.meshUrinalysisen
dc.subject.meshSpectrum Analysis, Ramanen
dc.subject.meshCOVID-19en
dc.subject.meshSARS-CoV-2en
dc.titleAlterations in the molecular composition of COVID-19 patient urine, detected using Raman spectroscopic/computational analysisen
dc.title.serialPLOS Oneen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dcterms.dateAccepted2022-06-17en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciencesen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciences/Biological Systems Engineeringen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/Statisticsen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/University Research Institutesen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciencesen
pubs.organisational-group/Virginia Tech/Engineering/Biomedical Engineering and Mechanicsen
pubs.organisational-group/Virginia Tech/Faculty of Health Sciencesen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Science/COS T&R Facultyen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciences/CALS T&R Facultyen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciences/Durelle Scotten
pubs.organisational-group/Virginia Tech/VT Carilion School of Medicineen
pubs.organisational-group/Virginia Tech/VT Carilion School of Medicine/Internal Medicineen
pubs.organisational-group/Virginia Tech/VT Carilion School of Medicine/Internal Medicine/Infectious Diseaseen

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