key: cord-0896208-g2lrkikd
authors: Tian, Maoqing; Zhang, Lu; Zhu, Kai; Shen, Bo; Wang, Gang; Song, Yuan; Chen, Cheng; Liang, Wei; Guan, Yang; Ding, Guohua; Lei, Tiechi; Li, Xiaogang; Xie, Jingyuan; Tong, Yongqing; Wang, Huiming
title: Urinary SARS-CoV-2 RNA is An Indicator For The Progression and Prognosis of COVID-19 Disease
date: 2021-02-18
journal: Res Sq
DOI: 10.21203/rs.3.rs-203728/v1
sha: 0d73ea0d3e28b48c460eb64a6574826a04f04a84
doc_id: 896208
cord_uid: g2lrkikd

BACKGROUND: We aimed to analyse clinical characteristics and find potential factors predicting poor prognosis in patients with coronavirus disease 2019 (COVID-19). METHODS: We analyzed the demographic and clinical data of COVID-19 patients and detected SARS-CoV-2 RNA in urine sediments collected from 53 COVID-19 patients enrolled in Renmin Hospital of Wuhan University from January 31, 2020 to February 18, 2020 with qRT-PCR analysis, and then classified those patients based on clinical conditions (severe or non-severe syndrome) and urinary SARS-CoV-2 RNA (U(RNA)(−) or U(RNA)(+)). RESULTS: We found that COVID-19 patients with severe syndrome (severe patients) showed significantly higher positive rate (11 of 23, 47.8%) of urinary SARS-CoV-2 RNA than non-severe patients (4 of 30, 13.3%, p = 0.006). U(RNA)(+) patients or severe U(RNA)(+) subgroup exhibited higher prevalence of inflammation and immune discord, cardiovascular diseases, liver damage and renal disfunction, and higher risk of death than U(RNA)(−) patients. To understand the potential mechanisms underlying the viral urine shedding, we performed renal histopathological analysis on postmortems of patients with COVID-19 and found that severe renal vascular endothelium lesion characterized by increase of the expression of thrombomodulin and von Willebrand factor, markers to assess the endothelium dysfunction. We proposed a theoretical and mathematic model to depict the potential factors determining the urine shedding of SARS-CoV-2. CONCLUSIONS: This study indicated that urinary SARS-CoV-2 RNA detected in urine specimens can be used to predict the progression and prognosis of COVID-19 severity.

severe illness among COVID-19 patients and low prevalence of kidney involvement [3, [14] [15] [16] , coexisting with a low urinary virus RNA positive rate in COVID-19 patients, we hypothesize that the detection of urinary SARS-CoV-2 nucleic acid, which may resulted in renal and cardiovascular endothelial destruction to facilitate the virus access to the kidney parenchyma, with improved method may be used as a speci c biomarker to indicate the severity of COVID-19.

From January 31, 2020 to February 18, 2020, a total of 53 patients who were diagnosed with COVID-19 at Renmin Hospital of Wuhan University were tested for SARS-CoV-2 nucleic acid in urine samples with quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. To reduce false negative results, we collected the urine sediment samples from those patients at the admission day case by case. Based on the results of urine SARS-CoV-2 nucleic acid testing, we divided those patients into two groups, including the urinary SARS-CoV-2 negative group (U RNA -, 38 cases) and positive group (U RNA + , 15 cases). We then conducted a retrospective study on those patients' clinical characteristics, basic diseases and laboratory tests (Supplemental Fig. 1 ). The diagnosis of COVID-19 pneumonia was conducted by following the New Coronavirus Pneumonia Prevention and Control Guidance (5 th edition) published by the National Health Commission of China [17] . Our study was approved by the ethics committee of Renmin Hospital of Wuhan University (wdry2020-k064), the Ethics Commission of General Hospital of Central Theatre Command ([2020]017-1), and the Ethics Commission of Jinyintan Hospital (KY-2020-15.01). Written informed consent was waived by the Ethics Commission of the participated hospitals for emerging infectious diseases.

The data of epidemiological characteristics, clinical manifestation, radiology examination and laboratory examination were collected from the electronic medical records, and the laboratory examination included arterial blood gas test, myocardial infarction, heart failure, liver and kidney function, electrolytes, whole blood cell count, blood biochemistry, coagulation test, immune function and C-reactive protein. The illness conditions were assessed and de ned as severe and non-severe type depending on the existence of respiratory dysfunction, in that the severe type was de ned as that the oxygen saturation is less than 93% under resting status, or the arterial oxygen pressure (PaO 2 )/fraction of inspired oxygen (FiO 2 ) ratio is less than 300 mmHg. We identi ed 30 cases as non-severe patients and 23 as severe patients (Supplemental Fig. 1 ). All data were reviewed by a team of trained physicians.

The SARS-CoV-2 virus in urine from the 53 COVID-19 patients was detected with quantitative RT-PCR analysis as previously described [18] . In brief, the urine sediments from participants were collected for SARS-CoV-2 test with the detection kit (Bioperfectus, Taizhou, China). The ORF1ab gene (nCovORF1ab) and the N gene (nCoV-NP) were used for qRT-PCR analysis according to the manufacturer's instructions. Reaction mixture were prepared and qRT-PCR assay was then performed under the following conditions: incubation at 50 °C for 15 minutes and 95 °C for 5 minutes, 40 cycles of denaturation at 94°C for 15 seconds, and extending and collecting uorescence signal at 55 °C for 45 seconds.

Tissue sampling and processing Kidney samples were obtained from autopsies of 4 severe COVID-19 patients with multi-organ failure, including acute kidney injury (AKI) that was examined and con rmed in a designated pathology laboratory.

Immunohistochemical staining was performed on kidney specimens from autopsy for thrombomodulin (TM), and von

Willebrand factor (vWF) as previously described [19] . Brie y, the sections were incubated with primary anti-TM (Cat:  14318-1-AP, 1:100, rabbit IgG; Proteintech Group, USA), anti-vWF (Cat: 11778-1-AP, 1:100, rabbit IgG; Proteintech Group, USA), or rabbit-isotype antibody (control) (1:100; Dako) at 4°C overnight, followed by the incubation with the HRP-anti-Rabbit secondary antibodies for 1h at room temperature. Peroxidase activity was visualized with the DAB Elite kit (K3465, DAKO). Positive staining as brown coloration was viewed by a light microscope.

Continuous variables were expressed using the mean ± standard deviation (normal distribution) or medians and interquartile (IQR) values as appropriate (abnormal distribution). Categorical variables were shown as the percentages and counts. Two-independent group t-tests was used when the data were normally distributed, otherwise, wilcoxon rank-sum test was used. Chi-square tests and Fisher's exact tests were applied to categorical variables as appropriate.

The cumulative rate of in-hospital survival was investigated using the Kaplan-Meier method. All statistical analyses were performed using SPSS 22.0. p < 0.05 was considered as statistically signi cant.

Characterization of patients with U RNA + and U RNA -A total of 53 hospitalized COVID-19 patients were enrolled in this study. The characteristics of those patients were detailed in Table 1 . The median age of those patients was 52 years old (IQR, 42-66), and 58% of those patients were female. By testing SARS-CoV-2 nucleic acid in urine samples with qRT-PCR analysis, we found that 38 of those 53 patients were urinary SARS-CoV-2 negative (U RNA -) and 15 of them were urinary SARS-CoV-2 positive (U RNA + ). The U RNA + patients were older and more likely to experience chest tightness and shortness of breath than U RNA patients, but showed no signi cant differences in male/female distribution, fever, cough, sputum production, fatigue, radiological appearance, hypertension, diabetes, cardiovascular diseases, chronic renal disease (Table 1 ). In addition, U RNA + patients suffered more severe respiratory distress with manifestations of lower arterial oxygen pressure (PaO 2 ) and oxygen saturation (SaO 2 ) than U RNA patients as examined with arterial blood gas analysis ( Table 2 ). The leukopenia and lymphocytopenia were detected more frequently in routine blood test of U RNA + patients than those in blood test of U RNA patients (Fig. 1a) . Immune pro le evaluation identi ed a more frequent increase of serum CRP and IgE in U RNA + patients ( Fig. 1b and c) . In addition, we found that U RNA + patients had higher prevalence of increased serum levels of ALT (Fig. 1d) , higher percentage of decreased serum AST (Fig. 1e) , higher case percentage of increased serum myoglobin, ultra-TnI ( Fig. 1f and g), LDH (Fig. 1h) , urea (Fig. 1i) , and decreased eGFR ( Fig. 1j ) than U RNA patients. These data indicated that U RNA + patients had more severe lesions on organs of liver, heart, and kidney.

We further found that U RNA + patients showed signi cantly lower levels of T cells and T helper (Th) cells ( Fig. 2a Clinical features and prognosis of severe patients with U RNA + and U RNA -Above results implied a correlation of the urinary SARS-CoV-2 RNA with COVID-19 disease severity and the underlying conditions in COVID-19 patients. We hypothesized that urinary SARS-CoV-2 RNA may serve as a biomarker for predicting the clinical outcomes of severe COVID-19 patients. In the total of 53 patients, we identi ed 30 non-severe patients and 23 severe patients (Supplemental Fig. 1 ) based on the oxygen saturation (less than 93% under resting status) and the arterial oxygen pressure (PaO 2 )/fraction of inspired oxygen (FiO 2 ) ratio (less than 300 mmHg). Within the 23 severe patients, we found that 12 of those 23 server patients were urinary SARS-CoV-2 negative (SU RNA -) and 11 of them were U RNA + (SU RNA + ). The positive rate of urine SARS-CoV-2 RNA were signi cantly higher in sever patients (11/23 severe patients = 47.8%) than that in non-severe patients (4/30 non-severe patients = 13.3%) (Fig. 3a) . This result suggested that urine shedding SARS-CoV-2 correlated with the severity of the disease. To support this notion, we found that SU RNA + patients experienced more comorbidities, including higher prevalence of hypertension and cardiovascular diseases ( Fig. 3b-d) , and renal function impairment (Fig. 3e) . SU RNA + patients also showed signi cantly lower levers of eGFR ( Fig. 3f ) but higher levels of IgE and IgG ( Fig. 3g and h) than SU RNA patients. In addition, the U RNA + patients among 53 patients had a signi cantly higher risk of death than the U RNA patients (Fig.   4a ). Furthermore, the severe patients with U RNA + also demonstrated a higher risk of death than the severe patients with U RNA -, although the difference did not reach statistical signi cance between U RNA and U RNA + groups of severe patients (Fig. 4b) . These results suggested that U RNA + patients exhibited signi cantly higher risk of cardiovascular abnormality, liver injury, renal disfunction and death, and urinary SARS-CoV-2 RNA might serve as a predictive biomarker for determining the prognosis and outcome of the disease.

Endothelial dysfunction is prevalent in chronical cardiovascular disease and infectious or in ammatory diseases (such as that in virus-infected patients) [20] [21] [22] [23] [24] [25] [26] . TM and vWF have been recognized as biomarkers to assess the endothelium dysfunction [20] [21] [22] [23] [24] . We found that the expression of TM and vWF in interstitial vessels, glomerular, and tubules were higher in kidneys from died COVID-19 patients compared to that in kidneys from renal carcinoma patients (Fig. 5) , suggesting that renal vascular endothelial lesion might also associate with the severity of COVID-19

patients.

Theoretical and mathematic modeling of urine shedding of SARS-CoV-2 SARS-CoV-2 mainly infects host through respiratory tract and spread to other organs or tissues through blood circulation. Damaged vascular endothelial, which either preexisted or incurred by virus infection, allows virus in ltration between blood stream and tissue mesenchyme by passing through endothelium. Virus-related renal insult and urine shedding are determined by multifactor, such as the virus load of in ow, the vascular endothelial integrity, and the intensity of anti-virus response. In this study, we adopt a model of renal In ow-In ltration-Injury-Into urine ("4I" model) to illustrate the course and outcome of SARS-CoV-2 infection in COVID-19 patient kidney (Fig. 6a ). In this model, the kidney is simpli ed as an effector to response to the virus invasion (input) with the effects of renal damages and virus shedding (output). Output effects are determined by the input strength (amount of loading virus) and the intrinsic nature of the kidney, such as the integrity of vascular endothelium and local immunity (Fig. 6b) .

Although the compromised integrity of glomeruli and interstitial vascular vessels both allow the virus in ltration into kidney parenchyma, the in ltrating route through interstitial vessels is ignored, since the exuded virus is unlikely to infect tubular epithelial cells in which the ACE2 enriched in the brush border [27] . In that context, we propose a function equation and curve to solve the urinary excretion of viral nucleic acid, condition of vascular endothelial integrity and the circulating viral load in COVID-19 patients (Fig. 6c ).

We SARS-CoV-2 infection and transmission in human has been successfully reproduced in ferret model, in which SARS-CoV-2 viruses can be detected in both kidney tissues and urine [28] . Viral infection and replication in kidney tissues indicate that the virus might be shed through urine. However, the positive rates of urine SARS-CoV-2 RNA vary from 0-7.5% ( Table 3 ). The disparity in detection of the urinary SARS-CoV-2 RNA might be resulted in the false negative test of nucleic acid by qRT-PCR, which may be caused by inadequate sampling, low viral load, or other unknown factors [4, 5] . In the ferret model of SARS-CoV-2 infection, urinary SARS-CoV-2 RNA could be detected up to 8 days after the onset in the virus inoculated group in contrast to only 4 days in the directly contacted group [28] , suggesting that the amount of viral loads and the stages of illness may have impact on the positive test rates. In addition, appropriate sampling seems to be essential for avoiding false negative results in COVID-19 patient samples. In our study, we optimized and analyzed the specimens of urine sediments, and found that 15 of those 53 patients were urinary SARS-CoV-2 positive (U RNA + ) ( Table 1) . Our analysis showed a positive rate of 28.3% from 53 COVID-19 patients, which are higher than test results on routine urine sample testing (Table 3 ) [5, 7, 8, [10] [11] [12] [13] . This result suggested that our optimized urine SARS-CoV-2 RNA test method could improve the positive rate, which may assist in predicting the disease outcome, especially in severe patients.

We also observed that U RNA + patients or severe U RNA + subgroup showed higher prevalence of in ammation and immune discord, cardiovascular diseases, liver damage and renal disfunction, and higher risk of death than U RNA patients. The reason for the observed higher prevalence of developing severe clinical manifestations and higher risk of death in U RNA + patients might be caused by a high SARS-CoV-2 viral load, which was shown to to be highly associated with in-hospital mortality in COVID-19 patients [29] . The new or preexisting vascular endothelial damage in COVID-19 patients may also lead to the increase of in ammation and damage within infected tissue and the excretion of SARS-COV-2 into urine. Therefore, the evaluation of vascular endothelial damage may be an important prognostic tool to understand the outcomes of COVID-19 patients.

Studies on cellular mechanism have con rmed that SARS-CoV-2 shares the same membrane-bound angiotensinconverting enzyme 2 (ACE2) as SARS-CoV to gain access to its target cells [30] [31] [32] . In particular, kidneys show much more robust expression of ACE2 than respiratory organs, suggesting that kidney is a possible infecting target of SARS-CoV-2 [33] . The involvement of kidneys is usually evaluated in two aspects of renal functional impairment and renal insult. Acute renal injury (AKI) was rarely happened in COVID-19 patients with incidence of 3-9%, but herald very poor prognostic with very high mortality [3, 14] . Kidney insults manifestations of proteinuria (44%) and hematuria (26.7%), were commonly seen in COVID-19 infection [3, 14, 16] . Until recently, the renal involvement in COVID-19 patients remains a matter of widely concern and debate as one study suggested that the renal insults were uncommon in COVID-19 patients [9] . To resolve the difference and controversy, two major issues need to be addressed. The rst one is whether SARS-CoV-2 is able to infect the target cells through blood ow to kidney mesenchyme, and the second one is whether the infection can cause detrimental effects to the kidney tissue. Previous study has showed that spherical virus-like particles characteristic of coronavirus was found in the renal tubular epithelium and podocytes [34] . Considering that the infection of SARS-CoV-2 will trigger severe in ammation, we further explored whether SARS-CoV-2 infection induced renal endothelium dysfunction. We found that the expression of TM and vWF, biomarkers of endothelium dysfunction, were increased in renal tissues from died COVID-19 patients 

We optimized the method of urine SARS-CoV-2 RNA detection and signi cantly increased the positive detection rates.

We analyzed the clinical characteristics of patients with urinary nucleic acid positive SARS-CoV-2 RNA, and revealed a potential association of vascular endothelial damage with virus urine shedding. Furthermore, we established a model to analyze the relationship between virus urine excretion and the underlying disease condition. This study suggests that the detection of SARS-CoV-2 RNA in urine sediments can provide a robust biomarker for evaluation and prognosis for patients with COVID-19. 

All data generated or analyzed during this study are included in this published article.

The authors declare that they have no relevant nancial interests.

Maoqing Tian, Lu Zhang, Kai Zhu and Bo Shen contributed equally to this work. 

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Tables Table 1. Demographic and Clinical characteristics of 53 enrolled patients

We acknowledge all health care workers involved in the diagnosis and treatment of COVID-19 patients in Wuhan.

Sampling method ND: not determined