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

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) <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.

Disease-Associated Multimolecular Signature in the Urine of Patients with Lyme Disease Detected Using Raman Spectroscopy and Chemometrics.

A urine-based screening technique for Lyme disease (LD) was developed in this research. The screen is based on Raman spectroscopy, iterative smoothing-splines with root error adjustment (ISREA) spectral baselining, and chemometric analysis using Rametrix software. Raman spectra of urine from 30 patients with positive serologic tests (including the US Centers for Disease Control [CDC] two-tier standard) for LD were compared against subsets of our database of urine spectra from 235 healthy human volunteers, 362 end-stage kidney disease (ESKD) patients, and 17 patients with active or remissive bladder cancer (BCA). We found statistical differences (p < 0.001) between urine scans of healthy volunteers and LD-positive patients. We also found a unique LD molecular signature in urine involving 112 Raman shifts (31 major Raman shifts) with significant differences from urine of healthy individuals. We were able to distinguish the LD molecular signature as statistically different (p < 0.001) from the molecular signatures of ESKD and BCA. When comparing LD-positive patients against healthy volunteers, the Rametrix-based urine screen performed with 86.7% for overall accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), respectively. When considering patients with ESKD and BCA in the LD-negative group, these values were 88.7% (accuracy), 83.3% (sensitivity), 91.0% (specificity), 80.7% (PPV), and 92.4% (NPV). Additional advantages to the Raman-based urine screen include that it is rapid (minutes per analysis), is minimally invasive, requires no chemical labeling, uses a low-profile, off-the-shelf spectrometer, and is inexpensive relative to other available LD tests.