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

Autor: John L. Robertson, Ryan S. Senger, Janine Talty, Pang Du, Amr Sayed-Issa, Maggie L. Avellar, Lacey T. Ngo, Mariana Gomez De La Espriella, Tasaduq N. Fazili, Jasmine Y. Jackson-Akers, Georgi Guruli, Giuseppe Orlando
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: PLoS ONE, Vol 17, Iss 7 (2022)
Druh dokumentu: article
ISSN: 1932-6203
Popis: We 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)
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