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.

Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19.

BACKGROUND: Acute kidney injury (AKI) is a common complication in patients hospitalized with COVID-19 and may require renal replacement therapy (RRT). Dipstick urinalysis is frequently obtained, but data regarding the prognostic value of hematuria and proteinuria for kidney outcomes is scarce. METHODS: Patients with positive severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) PCR, who had a urinalysis obtained on admission to one of 20 hospitals, were included. Nested models with degree of hematuria and proteinuria were used to predict AKI and RRT during admission. Presence of Chronic Kidney Disease (CKD) and baseline serum creatinine were added to test improvement in model fit. RESULTS: Of 5,980 individuals, 829 (13.9%) developed an AKI during admission, and 149 (18.0%) of those with AKI received RRT. Proteinuria and hematuria degrees significantly increased with AKI severity (P < 0.001 for both). Any degree of proteinuria and hematuria was associated with an increased risk of AKI and RRT. In predictive models for AKI, presence of CKD improved the area under the curve (AUC) (95% confidence interval) to 0.73 (0.71, 0.75), P < 0.001, and adding baseline creatinine improved the AUC to 0.85 (0.83, 0.86), P < 0.001, when compared to the base model AUC using only proteinuria and hematuria, AUC = 0.64 (0.62, 0.67). In RRT models, CKD status improved the AUC to 0.78 (0.75, 0.82), P < 0.001, and baseline creatinine improved the AUC to 0.84 (0.80, 0.88), P < 0.001, compared to the base model, AUC = 0.72 (0.68, 0.76). There was no significant improvement in model discrimination when both CKD and baseline serum creatinine were included. CONCLUSIONS: Proteinuria and hematuria values on dipstick urinalysis can be utilized to predict AKI and RRT in hospitalized patients with COVID-19. We derived formulas using these two readily available values to help prognosticate kidney outcomes in these patients. Furthermore, the incorporation of CKD or baseline creatinine increases the accuracy of these formulas.

Using social media to crowdsource collection of urine samples during a national pandemic.

The COVID-19 pandemic and subsequent lockdown had a substantial impact on normal research operations. Researchers needed to adapt their methods to engage at-home participants. One method is crowdsourcing, in which researchers use social media to recruit participants, gather data, and collect samples. We utilized this method to develop a diagnostic test for Interstitial Cystitis/Bladder Pain Syndrome (IC/BPS). Participants were recruited via posts on popular social-media platforms, and enrolled via a website. Participants received and returned a mail kit containing bladder symptom surveys and a urine sample cup containing room-temperature preservative. Using this method, we collected 1254 IC/BPS and control samples in 3 months from all 50 United States. Our data demonstrate that crowdsourcing is a viable alternative to traditional research, with the ability to reach a broad patient population rapidly. Crowdsourcing is a powerful tool for at-home participation in research, particularly during the lockdown caused by the COVID-19 pandemic.

Proteomic and metabolomic profiling of urine uncovers immune responses in patients with COVID-19.

The utility of the urinary proteome in infectious diseases remains unclear. Here, we analyzed the proteome and metabolome of urine and serum samples from patients with COVID-19 and healthy controls. Our data show that urinary proteins effectively classify COVID-19 by severity. We detect 197 cytokines and their receptors in urine, but only 124 in serum using TMT-based proteomics. The decrease in urinary ESCRT complex proteins correlates with active SARS-CoV-2 replication. The downregulation of urinary CXCL14 in severe COVID-19 cases positively correlates with blood lymphocyte counts. Integrative multiomics analysis suggests that innate immune activation and inflammation triggered renal injuries in patients with COVID-19. COVID-19-associated modulation of the urinary proteome offers unique insights into the pathogenesis of this disease. This study demonstrates the added value of including the urinary proteome in a suite of multiomics analytes in evaluating the immune pathobiology and clinical course of COVID-19 and, potentially, other infectious diseases.

Could urinary kidney injury molecule-1 be a good marker in subclinical acute kidney injury in mild to moderate COVID-19 infection?

PURPOSE: To evaluate urinary kidney injury molecule-1 (uKIM-1), which is a proximal tubule injury biomarker in subclinical acute kidney injury (AKI) that may occur in COVID-19 infection. METHODS: The study included proteinuric (n = 30) and non-proteinuric (n = 30) patients diagnosed with mild/moderate COVID-19 infection between March and September 2020 and healthy individuals as a control group (n = 20). The uKIM-1, serum creatinine, cystatin C, spot urine protein, creatinine, and albumin levels of the patients were evaluated again after an average of 21 days. RESULTS: The median (interquartile range) uKIM-1 level at the time of presentation was 246 (141-347) pg/mL in the proteinuric group, 83 (29-217) pg/mL in the non-proteinuric group, and 55 (21-123) pg/mL in the control group and significantly high in the proteinuric group than the others (p < 0.001). Creatinine and cystatin C were significantly higher in the proteinuric group than in the group without proteinuria, but none of the patients met the KDIGO-AKI criteria. uKIM-1 had a positive correlation with PCR, non-albumin proteinuria, creatinine, cystatin C, CRP, fibrinogen, LDH, and ferritin, and a negative correlation with eGFR and albumin (p < 0.05). In the multivariate regression analysis, non-albumin proteinuria (p = 0.048) and BUN (p = 0.034) were identified as independent factors predicting a high uKIM-1 level. After 21 ± 4 days, proteinuria regressed to normal levels in 20 (67%) patients in the proteinuric group. In addition, the uKIM-1 level, albuminuria, non-albumin proteinuria, and CRP significantly decreased. CONCLUSIONS: Our findings support that the kidney is one of the target organs of the COVID-19 and it may cause proximal tubule injury even in patients that do not present with AKI or critical/severe COVID-19 infection.

Minimal Change Disease Following the Pfizer-BioNTech COVID-19 Vaccine.

We report on the development of minimal change disease (MCD) with nephrotic syndrome and acute kidney injury (AKI), shortly after first injection of the BNT162b2 COVID-19 vaccine (Pfizer-BioNTech). A 50-year-old previously healthy man was admitted to our hospital following the appearance of peripheral edema. Ten days earlier, he had received the first injection of the vaccine. Four days after injection, he developed lower leg edema, which rapidly progressed to anasarca. On admission, serum creatinine was 2.31 mg/dL and 24-hour urinary protein excretion was 6.9 grams. As kidney function continued to decline over the next days, empirical treatment was initiated with prednisone 80 mg/d. A kidney biopsy was performed and the findings were consistent with MCD. Ten days later, kidney function began to improve, gradually returning to normal. The clinical triad of MCD, nephrotic syndrome, and AKI has been previously described under a variety of circumstances, but not following the Pfizer-BioNTech COVID-19 vaccine. The association between the vaccination and MCD is at this time temporal and by exclusion, and by no means firmly established. We await further reports of similar cases to evaluate the true incidence of this possible vaccine side effect.

Biosafety Level 2 cabinet UV-C light exposure of sports antidoping human urine samples does not affect the stability of selected prohibited substances.

The current study examined the stability of several antidoping prohibited substances analytes in urine after 15-min exposure to UV-C light in a Biosafety Level 2 cabinet. The urine matrices were exposed within the original antidoping bottles with the aim to destroy DNA/RNA and possible SARS CoV-2. The analytes small molecules Phase I and Phase II metabolites and peptides, in total 444, endogenous, internal standards, and prohibited substances, pH, and specific gravity in urine were studied. The accredited analytical methods were used by Anti-Doping Laboratory Qatar for the comparison of data of the same urine samples analyzed with and without UV-C exposure. In the study conditions, no problems of stability were detected in the substances spiked in the urine samples exposed in the UV-C irradiation.

Study of SARS-CoV-2 in semen and urine samples of a volunteer with positive naso-pharyngeal swab.

INTRODUCTION: The recent appearance of SARS-CoV-2 in Wuhan in 2019 has started a pandemic which has involved over a million people worldwide. A matter of debate is the possible viral detection in different body fluids than respiratory droplets. Thus, we evaluated the possible presence of SARS-CoV-2 in semen and urine samples of a volunteer with confirmed COVID-19. MATERIALS AND METHODS: A 31-year-old man with fever, myalgia, anosmia, and ageusia was tested and found positive for SARS-CoV-2 through a pharyngeal swab. Eight days after he provided semen and urine samples in which viral RNA presence was measured using a Real time RT PCR system (RealStar SARS-CoV-2 RT-PCR, Altona Diagnostics) targeting E and S viral genes. RESULTS AND DISCUSSION: Semen and urine samples search for SARS-CoV-2 RNA was negative. Although this should be interpreted cautiously, it may be possible that either the viral clearance kinetics in these matrices matches the progressive clinical recovery of the patient or that the virus was never present in these fluids at the time of the laboratory diagnosis.