Clinical Usefulness of SARS-CoV-2 Detection and Diagnosis in Patients with COVID-19 = 코로나19 환자에서 SARS-CoV2 검출 및 진단의 임상적 유용성

다국어 초록 (Multilingual Abstract)

Background: Coronavirus disease 2019 (COVID-19), a mild to severe respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The diagnostic accuracy of real-time polymerase chain reaction (RT-qPCR) primers in clinical practice remain unproven which includes CDC- and WHO-recommended primers. However, the clinical relevance of RNAemia and antigenemia has not been well documented in the literature. In this study I aimed to examine the clinical relevance of SARS-CoV-2 RNAemia and nucleocapsid protein antigenemia in association with COVID-19 severity. In addition kinetics of viral load in various respiratory samples were tested for diagnostic accuracy according to variants of SARS-CoV-2 in COVID-19 patients.

Methods: The accuracy of reverse transcription-polymerase chain reaction (RT-qPCR) were analyzed using an in-house–designed primer set (iNP) targeting the nucleocapsid protein along with WHO and CDC recommended primers and various commercial primers. The accuracy was also assessed by virus culture or seroconversion. Furthermore, we explored a cohort study of COVID-19 patients and their prospects with evidence of RNAemia using RT-qPCR in serum. In addition I explored the kinetic responses of antigenemia, RNAemia, and viral loads in various respiratory tract specimens in COVID-19 Patients along with various clinical characteristics. Moreover I analyzed the correlation of various risk factors with COVID-19 mortality. I also studied the viral load kinetics and diagnostic accuracy of COVID-19 patients with respective of SARS-CoV-2 variants, which includes wild-type, delta and omicron variants using RT-qPCR assay using upper and lower respiratory tract specimens.

Results: When a cutoff value of the cycle threshold (Ct) was set to 35, RT-qPCRs using WHO RdRp primer and CDC N1, N2, and N3 primers showed sensitivity 42.1–63.2% and specificity 90.5–100% in sputum and sensitivity 65.2–69.6% and specificity 65.2–69.6% in nasopharyngeal samples. Sputum testing had the highest sensitivity, followed by nasopharyngeal testing (P = 0.0193). Our results suggest that iNP RT-qPCR has better sensitivity and specificity than RT-qPCR with WHO (P < 0.0001) or CDC (N1: P = 0.0012, N2: P = 0.0013, N3: P = 0.0012) primers. The presence of RNAemia in critical or fatal cases was the highest (66.7%), followed by severe (12.5%) and mild to moderate (1.7%) in admission samples. Viral RNAemia was detected on admission and 1st week samples, however, RNAemia was not detected on the samples collected on the second week post-symptom onset. Multiple regression analysis showed that the RNAemia was an independent predictor for the disease severity (P = 0.021), and the Kaplan-Meier survival curve estimated an increased mortality rate in COVID-19 RNAemia cases (P < 0.001). In addition, the presence of antigenemia in asymptomatic patients on admission and 1st week were 27% and 22%, however none of the samples collected on 2nd week possess any antigenemia. Kaplan–Meier survival curves predicted a higher mortality rate when there is an elevated concentration of antigenemia in follow-up samples (P = 0.005). Univariate analysis designates that age, PSI, elevated antigenemia and RNAemia were predictive rick factors of mortality and with multivariate logistic regression analysis, age and RNAemia were risk factors of mortality. In SARS-CoV-2 variant diagnostic detection the sensitivity/specificity of NP gene RT-qPCR results of saliva sample of omicron variant has higher sensitivity (AUC- 1.000) compared with delta (AUC- 0.875) and wild-type type (AUC- 0.878) saliva samples. Our results reports that there is no significant difference in the viral load in saliva samples of vaccinated or non-vaccinated patients infected with SARS-CoV-2 omicron variants.

Conclusions: In conclusion, I demonstrated that sputum RT-qPCR analysis has the highest sensitivity, followed by nasopharyngeal, saliva, and oropharyngeal samples. We also suggests that considerable improvement is needed for RT-qPCR WHO and CDC primer sets in detection of SARS-CoV-2. In addition, RNAemia of SARS-CoV-2 infection is a predictive risk factor for clinical severity in COVID-19 patients. Furthermore we demonstrated the potential relation and correlation between the antigenemia concentration and RNAemia viral load in blood in the mortality outcome. Our study suggests that the saliva sample of omicron variant have better sensitivity than wild-type type and delta variant saliva samples. However there is no significant difference in viral load of saliva samples in vaccinated or non-vaccinated patients of delta and omicron variant infected patients with COVID-19.

국문 초록 (Abstract)

배경: 코로나바이러스감염증 (COVID-19)은 코로나 19 바이러스 (SARS-CoV-2)로 인해 발병하며, 무증상 에서부터 중증까지 발현되는 호흡기 질환이다. COVID-19 진단에는 PCR검사를 이용한 분자진단과 항원항체검사를 이용한 면역학적진단법이 이용된다. PCR진단에 CDC 또는 WHO에서 권장하는 프라이머를 이용한 실시간 역전사 중합효소 연쇄 반응(RT-qPCR)이 이용되나 임상적 유용성을 비교한 연구는 거의 없다. 바이러스 RNA 혈증 및 항원 혈증의 임상적 유용성 또한 아직 입증되지 않았다. 이 연구는 SARS-CoV-2 RNA혈증, 항원 혈증및 변이에 따른 진단 정확도의 평가를 통해 SARS-CoV-2 진단에 사용되는 항원검사의 임상적 유용성에 대한 연구를 수행하고자 하였다.

방법: 실시간 역전사 중합효소 연쇄 반응(RT-qPCR)의 정확도 평가를 위해 WHO 및 CDC에서 권장하는 프라이머 및 다양한 상용 프라이머와 함께 연구자가 디자인한 뉴클레오캡시드 단백질을 표적으로 하는 프라이머 세트(iNP)를 제작하여 비교하였다. COVID-19 확진은 바이러스가 배양되거나 항체가 4배 상승된 경우로 정의하였다. 환자의 혈청 샘플의 바이러스 RNA copies와 항원농도를 확인하여 COVID-19 환자의 임상적 유용성을 평가하였다. 상부 및 하부 호흡기 검체를 이용하여 야생형, 델타 및 오미크론 변이체에 따른 COVID-19 환자의 SARS-CoV-2에 대한 iNP RT-qPCR 의 진단 정확도를 평가하였다.

결과: 사이클 역치(Ct)의 컷오프 값을 35로 설정했을 때 WHO RdRp 프라이머와 CDC의 N1, N2, N3 프라이머를 사용한 RT-qPCR결과 객담에서 민감도 42.1~63.2%, 특이도 90.5~100%, 비인두 검체에서 민감도 65.2~69.6%, 특이도 65.2~69.6%를 보였다. 객담을 이용할 경우 민감도가 가장 높았고 비인두, 타액, 구인두 검체의 순서를 보였다. (P = 0.0193). 정확도 평가 연구 결과 iNP RT-qPCR이 WHO(P < 0.0001) 또는 CDC(N1: P = 0.0012, N2: P = 0.0013, N3: P = 0.0012) 프라이머를 사용한 RT-qPCR보다 더 나은 민감도와 특이도를 확인하였다. RNA혈증의 유무는 위중하거나 치명적인 환자군에서 가장 높았고(66.7%), 중증(12.5%) 및 경증 내지 중등도(1.7%)순 이였다. 입원 및 1주차 검체에서 바이러스성 RNA혈증이 검출되었으나, 증상 발현 후 2주차에 채취한 검체에서는 RNA혈증이 검출되지 않았다. 다중회귀분석은 RNA혈증이 질병의 중증도에 대한 독립적인 예측인자임을 보여주었고(P = 0.021), Kaplan-Meier 생존 곡선 검사상 추적 검체에서 항원 혈증 농도가 증가할 때 더 높은 사망률을 보였다(P = 0.005). 단변량 분석에서는 연령, PSI, 상승된 항원 혈증 및 RNA혈증이 사망의 예측 위험인자로 나타났고 다변량 로지스틱 회귀 분석에서는 나이 및 RNA혈증이 사망의 위험인자로 나타났다. 변이에 따른 진단 정확도 평가에서 iNP 유전자 RT-qPCR 검사 결과, 오미크론 변이 환자의 타액 샘플을 이용한 민감도가 델타 변이체(AUC-0.875) 및 야생형(AUC-0.878) 타액 샘플과 비교하여 더 높은 민감도(AUC-1.000)를 보였다. 그러나 SARS-CoV-2 오미크론 변이체에 감염된 환자의 백신 접종 또는 미접종 환자의 타액 샘플에서 바이러스 양에 유의한 차이는 없었다.

결론: SARS-CoV-2 에 대한 RT-qPCR 분석에서 가장 높은 민감도를 보이는 것은 객담 검체였고 비인두, 타액, 구인두 검체의 순서를 보였다. 또한 SARS-CoV-2의 검출에서 연구자가 디자인한 RT-qPCR 의 정확도가 훨씬 높아 WHO 및 CDC 프라이머 세트에 대해 개선이 필요한 것으로 생각된다. SARS-CoV-2 감염의 RNA혈증은 COVID-19 환자의 임상 중증도에 대한 위험 예측 인자임을 확인했다. 항원 혈증 농도의 상승과 혈액 내 RNA혈증 바이러스 부하가 사망률과 상관관계를 입증하였다. 또한 오미크론 변이의 타액 샘플이 야생형 및 델타 변이 타액 샘플보다 더 나은 민감도를 가지고 있음을 확인하였다.

목차 (Table of Contents)

• LIST OF TABLES 1
• LIST OF FIGURES 3
• ABSTRACT (IN KOREAN) 5
• ABSTRACT (IN ENGLISH) 9
• I. INTRODUCTION 13
• 1.1. Background of SARS-CoV-2 13
• 1.2. Clinical manifestations and characteristics of COVID-19 14
• 1.3. Viral shedding and diagnosis of SARS-CoV-2 in COVID-19 patients 15
• 1.4. SARS-CoV-2 demographic factors, laboratory indicators, social and lifestyle risk factors in COVID-19 patients 18
• II. OBJECTIVE AND SCOPE 22
• 2.1. Objective and scope of the present study 22
• 2.2. Diagnostic accuracy of SARS-CoV2 real-time polymerase chain reaction 23
• 2.3. SARS-CoV-2 RNAemia as a prognostic factor in disease severity on COVID-19 patients 24
• 2.4. SARS-CoV2 Antigenemia as a prognostic markers in COVID 19 patients 25
• 2.5. SARS-CoV-2 viral kinetics in accordance with different variants 26
• III. MATERIALS AND METHODS 28
• 3.1. Participants and data source 28
• 3.2. SARS-CoV-2 specimen sampling from COVID-19 patients 28
• 3.3. SARS-CoV-2 viral RNA extraction 29
• 3.4. Identification of SARS-CoV-2 infectious virus using cell culture 29
• 3.5. Indirect ELISA for antibody detection 30
• 3.6. Detection of N antigen for antigenemia using sandwich ELISA 32
• 3.7. The Immunofluorescence assay for the detection of SARS-CoV-2 33
• 3.8. One step reverse transcription quantitative real time PCR (RT-qPCR) for SARS-CoV-2 viral RNA detection 34
• 3.9. SARS-CoV-2 genome variant detection 37
• 3.10. Classification of COVID-19 patients in accordance to Severity 38
• 3.11. Statistical Methods 38
• IV. RESULTS 40
• 4.1. Diagnostic accuracy of SARS-CoV2 real-time polymerase chain reaction 40
• 4.1.1. Clinical characteristic of patients 40
• 4.1.2. Assessment of cross-reactivity of other respiratory viruses and bacteria using in vitro RT-qPCR analysis 43
• 4.1.3. Evaluation of SARS-CoV-2 via RT-qPCR 45
• 4.1.4. Diagnostic accuracy of samples up to 3 days after admission along with comparison with various RT-qPCR primer and probe sets 48
• 4.1.5. Analysis of the specificity and sensitivity of RT-qPCR depending on the duration of COVID-19 53
• 4.1.6. Comparison of the specificity and sensitivity of iNP RT-qPCR among sputum, nasopharyngeal, saliva, and oropharyngeal samples 57
• 4.2. SARS-CoV-2 RNAemia as a prognostic factor of disease severity on COVID-19 patients 58
• 4.2.1. Clinical characteristics COVID-19 patients in RNAemia assay 58
• 4.2.2. Laboratory and biochemical characteristics of the patients 60
• 4.2.3. RNAemia-positive serum/plasma cell culture 61
• 4.2.4. Assessment of viral RNAemia in serum/plasma samples 61
• 4.2.5. Correlation of RNAemia with upper and lower respiratory tract specimens 63
• 4.2.6. Clinical risk factors in association with RNAemia 67
• 4.3. SARS-CoV2 Antigenemia as a prognostic markers in COVID 19 patients 70
• 4.3.1. Demographic and clinical characteristics of COVID-19 patients in assessment of antigenemia 70
• 4.3.2. Laboratory characteristics of patients with COVID-19 on admission 72
• 4.3.3. Evaluation of viral Np-protein antigenemia in serum/plasma samples 74
• 4.3.4. Investigation of the sensitivity and specificity of antigenemia and upper and lower respiratory track specimens 77
• 4.3.5. Examination of viral RNAemia and antigenemia in serum/plasma samples 79
• 4.3.6. Assessment of the presence of RNAemia and antigenemia concentration and percentage in accordance with time interval from symptom 83
• 4.3.7. Evaluation of RNAemia and antigenemia at different time point in accordance with disease severity 85
• 4.3.8. Analysis of predictive risk factors for mortality using logistic regression analysis 87
• 4.4. SARS-CoV-2 viral kinetics in accordance with different variants 88
• 4.4.1. Patients and samples for variant analysis 88
• 4.4.2. Examination of SARS-CoV-2 viral load of different variants and specimens using NP, E, and RdRp-gene using RT-qPCR 88
• 4.4.3. Phylogenetic analysis of partial Spike protein for variant determination 91
• 4.4.4. Analysis of comparison of specificity and sensitivity of wild-type, delta and omicron variants samples 93
• 4.4.5. Assessment of viral RNA copy numbers according to vaccinated and non-vaccinated patients 96
• V. DISCUSSION 98
• VI. CONCLUSIONS 108
• VII. REFERENCES 110
• VIII. ACKNOWLEDGEMENTS 135
• ◊ DEDICATION 138

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