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Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” Tiên lượng mức độ trầm trọng bệnh nhân nhiễm Covid-19 số CD24-CSF1R Prediction of severity of COVID-19-infected patients using CD24-CSF1R index Nguyễn Tấn Thanh Giang1, Lê Tâm Vy1, Nguyễn Thành Đạt1, Trương Ngọc Minh2, Ngô Thanh Vân3, Nguyễn Minh Nam3* Trường Đại học Tân Tạo, Việt Nam Trường Đại học Quốc Tế - Đại học Quốc gia Thành phố Hồ Chí Minh, Việt Nam Khoa Y – Đại học Quốc gia Thành phố Hồ Chí Minh, Việt Nam * Tác giả liên hệ: nmnam@medvnu.edu.vn THƠNG TIN TĨM TẮT Bệnh Coronavirus 2019 (COVID-19) coronavirus gây hội chứng hơ hấp cấp tính nghiêm trọng đại dịch toàn cầu Hầu hết bệnh nhân khơng có triệu chứng; nhiên, bệnh nhân nặng phải đối mặt với nguy Ngày nhận: tổn thương tạng, chí tử vong Do tiến triển nặng bất Ngày nhận lại: thường biến chứng hơ hấp khơng dự đốn trước, hệ Duyệt đăng: thống chăm sóc sức khỏe trở nên tải Do đó, nghiên cứu tiến hành nhằm tìm thị dự đoán mức độ nghiêm trọng COVID-19 Dữ liệu lâm sàng biểu gen Từ khóa: 126 bệnh nhân lấy từ Gene Expression Omnibus SARS-CoV-2, COVID-19, dấu database Dữ liệu thô xử lý phương pháp ấn sinh học, số CD24Transcripts Per Million (TPM) chuyển thành log2 CSF1R, miễn dịch (TPM + 1) Đồ thị Violin, Kaplan-Meier plot, ROC curve phân tích hồi quy tỷ lệ Cox thực để đánh giá giá trị Keywords: tiên lượng số thiết lập Kết cho thấy, số SARS-CoV-2, COVID-19, biomarker, CD24-CSF1R Index, CD24-CSF1R dự đốn xác bệnh nhân chuyển vào ICU với AUC 0,8524 Bệnh nhân có số cao có số ngày khơng immunity thở máy Chỉ số có khả tiên lượng tốt nguy dùng máy thở Tóm lại, chúng tơi chứng minh số CD24-CSF1R dự đốn mức độ nghiêm trọng bệnh nhân COVID-19, từ giúp cải thiện hiệu phân tầng mức độ nặng bệnh nhân DOI: ABSTRACT The COVID-19 pandemic causes serious clinical manifestations Most patients are asymptomatic; however, critically ill patients still face a high risk of organ injury and/or worsening death Due to asymptotia and unexpected respiratory complications, healthcare systems have been overloaded Thus, this study aimed to identify a predictor that can predict the COVID-19 severity Clinical and gene expression data were retrieved from the Gene Expression 298 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” Omnibus database, which consists of 126 patients Raw data were processed using the Transcripts Per Million (TPM) method and then transformed using log2 (TPM+1) for normalization Violin plots, Kaplan-Meier curves, ROC curves, and multivariate proportional Cox regression analyses were performed to evaluate the prognostic value of the established index We found that the CD24-CSF1R Index was significantly associated with ICU admission and ventilatory status The ROC curve produced a relatively accurate prediction of ICU admission with an AUC of 0.8524 In addition, patients with a high index had significantly fewer ventilator-free days than patients with a low index Furthermore, the established index showed a strong prognostic ability for the risk of using machine ventilation in multivariate Cox regression analysis In conclusion, we investigated the CD24-CSF1R Index as a novel predictor of COVID-19 severity A high index score was associated with COVID-19 severity The established index could be considered as a potential biomarker that improves the effectiveness of patients’ severe stratification, prognostic methods, and lightens the healthcare system load in COVID19 Introduction In the last months of 2019, a novel virus is known as coronavirus disease 2019 (COVID-19) which appeared as an epidemic that hit China with many patients with pneumonia of unknown etiology (Corman et al., 2020) It then spreads out as a global pandemic After new cases started developing common signs of fever, cough, dyspnea, and by the same token, having fewer common symptoms of headache, sore throat, and runny nose Currently, COVID-19 does not appear to slow down Not only many deaths increase, but people are also affected by more serious consequences, such as the economy (Susilawati, Falefi, & Purwoko, 2020), education (Tadesse & Muluye, 2020), psychology (Keshky, El Sayed, Basyouni, & Al Sabban, 2020), and especially the healthcare system (Lasater et al., 2021) Severe acute respiratory syndrome coronavirus (SARS-CoV-2) is transferred by the respiratory system, and various new mutant strains are more dangerous (Machhi et al., 2020) Although a high percentage of infected patients have good prognoses, 510% still develop severe symptoms and require assistance in ICU and about 88% of them have been supported by mechanical ventilation because of acute hypoxemic respiratory failure (ARDS) (Lim et al., 2021) Due to airborne infections, overcrowding and understaffing have been created in numerous hospitals (Scales, 2020) Consequently, the current health system is paralyzed Most patients are asymptomatic and not require hospitalization (McIntosh, Hirsch, & Bloom, 2020) However, there is still a critical list characterized by respiratory dysfunction and/or various organ injuries Currently, the investigation of the disease progression of COVID-19 mainly depends on clinical manifestations (da Rosa Mesquita et al., 2021) Meanwhile, as part of the screening 299 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” process, a quick test is crucial to classify patients’ symptoms before considering them to be hospitalized However, the classification methods remain constrained, and no effective methods have been proposed This highlights that the start of the first symptoms, including mild and atypical symptoms, should be commenced by isolation practices (Cevik et al., 2020) However, with delays in the stratification of patients, the effectiveness of SARS-CoV-2 prevention might be challenging with early detection Therefore, it is necessary to develop a potent approach for problem-solving Although there are several classification methods for COVID-19 patients, they remain limited To begin with viral loads of SARS-CoV-2, several related studies have considered it to be associated with systemic inflammation, disease progression, and increased risk of death (Fajnzylber et al., 2020) The SARS-CoV-2 viral loads are similar in asymptomatic and symptomatic patients (He et al., 2020), and asymptomatic carrier popularity was greater than 50% among those who tested positive (Crisanti & Cassone, 2020) Thus, SARS-CoV-2 viral loads correlated with disease progression need to be determined in further studies Recently, TMPRSS2 was found to be a potential biomarker for COVID-19 outcomes which exhibited sex differences in COVID-19 patients’ outcomes and correlated with disease severity (Strope & Chau, 2020) Nonetheless, these results are a literature review and website statistics and are on the list of future direction studies (Strope & Chau, 2020) Furthermore, smell dysfunction was also considered to label infected cases at an early stage, but meaningful relationships between disease severity and comorbidities were not found (Moein et al., 2020) Although proteinuria was used to test the correlation of COVID-19 severity in the urine samples as a biomarker, the kidney involvement in COVID-19 infection seems multifactorial and not only because of viral infection (Ouahmi et al., 2021) In short, there is a demand for assisting the previous methods and optimizing the estimated prevalence of infection in COVID19 patients at the early stage of diagnosis and prognosis, thereby reducing healthcare workers’ deficiencies Despite the consent of SARS-CoV-2 vaccine utilization, its variants still appear to be more dangerous and resist vaccines However, the effectiveness of vaccine protection remains limited Thus, a biomarker is necessary to support patient stratification, especially in Vietnam To discover novel biomarkers for predicting disease severity in COVID-19 patients, we identified two genes, CD24 (small cell lung carcinoma cluster antigen) and CSF1R (Colony Stimulating Factor Receptor), which were significantly correlated with clinical information In this study, we hypothesized that a two-gene expression difference (CD24-CSF1R) might be a novel biomarker for predicting disease severity in COVID-19 patients Materials and methods 2.1 Data collection and reprocessing RNA-Seq datasets of COVID-19 patients were retrieved from the National Center for Biotechnology Information Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/) The criteria for screening data were that the dataset must contain information related to COVID-19 severity, such as admission into the intensive care unit (ICU), disease severity, Charlson comorbidity index score, mechanical ventilatory status, and some other clinical information (age, sex) Finally, we collected a dataset with accession number GSE157103 for our study A total of 126 300 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” samples were collected from 100 COVID-19 patients and 26 non-COVID-19 patients The raw data were normalized using the Transcripts Per Million (TPM) method and then transformed using log2 (TPM +1) Normalized data were used to calculate the differential gene expression between CD24 and CSF1R to establish the CD24-CSF1R Index for further analysis 2.2 Correlation between the CD24-CSF1R Index and the COVID-19 severityrelated clinical information Normalized data from 126 patients were analyzed to compare the difference in the established index between two patient groups who were admitted to the ICU and those who were not admitted to the ICU, as well as ventilator-requiring and no ventilatorrequiring groups The mRNA expression levels of CD24 and CSF1R alone were also analyzed All data were represented as violin plots 2.3 Evaluate the established index's ability to predict ICU admission in COVID19 patients To assess the performance of the CD24-CSF1R Index, an ROC curve analysis was conducted using an online web tool named easyROC (http://www.biosoft.hacettepe.edu.tr/easyROC/) (Goksuluk, Korkmaz, Zararsiz, & Karaagaoglu, 2016) The file containing information about the ICU admission, CD24CSF1R Index, and Charlson score was uploaded to the website We set up ICU as the status variable, yes as the category for cases, and used the ROC01 method to determine the optimal cut-off values 2.4 Correlation between the CD24-CSF1R Index and the clinical information in COVID-19 patients The patients were divided into two groups based on the cut-off value of the CD24CSF1R Index in the ROC analysis Then, Kaplan-Meier curve analysis was carried out to compare the machine ventilation-free days between these two groups of COVID-19 patients Univariate analysis was used to evaluate the correlation between the established index and clinical variables in COVID-19 patients Multivariate proportional Cox regression analysis was performed to evaluate the impact of covariates including age, sex, and Charlson score on the independent prognostic ability of the CD24-CSF1R Index 2.5 Network analysis of protein interactions The search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database v11.5 (http://www.stringdb.org/) was used to predict the protein interaction network of CD24 and CSF1R with other proteins The network between proteins was built based on information from many sources, such as experimental data and computational prediction methods The analytical parameters were set according to the default indicators 2.6 Statistical analysis All statistical analyses were conducted using the R version 3.6.3 and Python version 3.9.6 programming language software (https://www.r-project.org/, https://www.python.org/) and their corresponding packages to assess the prognostic value of the established index T-tests were used to compare the difference between two groups of clustered data, while ANOVA tests were used to compare more than two 301 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” groups, and all data were displayed using violin plots by seaborn Python package Kaplan-Meier curve analysis was performed using the log-rank test from the survminer R package The Chi-squared tests were used in the univariate analysis All significance tests were two-sided, and a p-value of less than 0.05 was considered statistically significant Results 3.1 A high index score was associated with COVID-19 severity The GSE157103 cohort included 126 patients and was used to identify whether there was any difference in the mRNA expression levels of CD24 and CFS1R between patients with COVID-19 admitted to the Intensive Care Unit (ICU) (n = 50) and those not admitted to the ICU (n = 50) The results represented as violin plots showed that the mRNA expression level of CD24 was significantly higher in patients with ICU settings than in patients without ICU (p = 1.102e-05, Fig.1A) In addition, CSF1R was highly expressed in the COVID-19/non-ICU group compared to the COVID-19/ICU group (p = 1.155e-09; Fig 1B) Due to the distinct expression patterns between CD24 and CSF1R in the context of ICU settings in COVID-19 patients, we integrated these two immunerelated genes into an index so-called “CD24-CSF1R Index” and determined whether there is better discrimination based on this established index between two patient groups The violin plot indicated a significant difference between the patients with COVID-19 admitted to the ICU and those not admitted to the ICU (p = 4.186e-11, Fig 1C) Figure 1: The violin plots of the mRNA expression levels of CD24, CSF1R 302 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” and CD24-CSF1R Index Note: Violin plots of the mRNA expression levels of CD24 (A, D), CSF1R (B, E), and CD24-CSF1R Index (C, F) between non-COVID and COVID patients with or without ICU admission and mechanical ventilation The mRNA expression levels of CD24 and CFS1R were also analyzed to identify the correlation with clinical information regarding the COVID-19 patient's ventilatory status Similarly, the mRNA level of CD24 was significantly overexpressed in the COVID-19 patients requiring ventilatory support compared to patients not requiring mechanical ventilation while the CSF1R exhibited a higher expression level in the nonventilator group (Fig 1D, 1E) The p-values based on the t-test in the analysis were 4.175e-04 and 5.859e-07, respectively In addition, the CD24-CSF1R Index also showed an obvious distinction between the two groups in terms of ventilatory status (p = 1.278e07; Fig 1F) Taken together, these results indicate that the “CD24-CSF1R Index” could be a potential indicator of COVID-19 severity 3.2 The CD24-CSF1R Index correctly classified COVID-19 severity Figure 2: ROC curve analysis of the CD24-CSF1R Index and Charlson score Note: The red line represents for the established index, and the green line represents for the Charlson score To identify how well the “CD24-CSF1R Index” can classify COVID-19 patients, a web tool for ROC curve analysis was utilized to evaluate the ability to accurately predict COVID-19 severity of the established index The 100 COVID-19 patients with the CD24-CSF1R Index were designated as a high or low risk of the ICU admission based on the COVID-19 patients' ICU admission status The Area Under the Curve 303 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” (AUC) is a useful summary of the Receiver operating characteristic (ROC) curve that can measure a classifier's ability to distinguish between groups The AUC indicates how efficiently the model distinguishes between positive and negative classes, in which the greater the AUC, the better the performance of the model We identified an optimal cutoff index of 0.6922305 based on the ROC01 method as a potential inclusion standard for ICU admission of COVID-19 patients (AUC 0.8524, 95% CI 0.777- 0.927) Sensitivity versus 1-specificity was plotted to build an ROC curve (Fig 2) Interestingly, the model based on the CD24-CSF1R Index showed a significantly better prediction of disease severity compared to the model based on Charlson score (AUC 0.5402, 95% CI 0.4260.655) (Richardson et al., 2020) The ROC curve produced a sensitivity of 84% (95% CI 71-93), a specificity of 80% (95% CI 66-90), a positive predictive value of 80.8% (95% CI 67-91), and a negative predictive value of 83.3% (95% CI 70-92) with this cut-off index These performance measures were superior to the Charlson score (Table 1) ROC curve analysis again insisted on a good discriminatory power of the established index compared to patient classification based on Charlson score Table Performance Measures of the CD24-CSF1R Index and Charlson score in ROC curve analysis Performance Measures Charlson score Sensitivity 0.54 (0.39-0.68) CD24-CSF1R Index 0.84 (0.71-0.93) Specificity 0.5 (0.36-0.65) 0.8 (0.66-0.90) Positive Predictive Value 0.52 (0.37-0.66) 0.808 (0.67-0.91) Negative Predictive Value 0.52 (0.38-0.66) 0.833 (0.70-0.92) Note: The values in brackets are the values within the 95% confidence interval 3.3 The CD24-CSF1R Index is an evaluable determinant for the requirement of mechanical ventilation in COVID-19 patients 304 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” Figure 3: Kaplan-Meier curves of the CD24-CSF1R Index and Charlson score based on ventilation status of COVID-19 patients Note: KM plots of Charlson score (A) and CD24-CSF1R Index (B) of COVID-19 patients The p-value was calculated by log-rank tests For further analysis, 100 COVID-19 patients were divided into two risk groups (low index group versus high index group) based on the above cut-off value of the CD24CSF1R Index Kaplan Meier curve analysis was then performed on two groups of COVID-19 patients to confirm whether the established index was associated with ventilatory status The KM curve on two groups divided according to the cut-off value of the Charlson score was also obtained for comparison The findings showed a significant correlation between the Charlson score and the ventilatory status of COVID19 patients in which a low score showed a higher risk leading to ventilatory necessity (p = 0.0197, Fig 3A) This seems to be contradictory since a high Charlson score was expected to result in a poor outcome This inconsistency implied that the Charlson score could not predict the risk of a patient requiring ventilatory support In contrast, the established index is significantly associated with ventilatory support in COVID-19 patients Patients with a high index, in particular, had significantly fewer ventilator-free days than those with a low index (p = 6.07e-07, Fig 3B) 3.4 The CD24-CSF1R Index was found to be a reliable predictor of COVID-19 diagnosis 305 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” Figure 4: Multivariate hazard regression analysis of clinical variables Note: N is the number of COVID-19 patients in each group The hazard ratio in brackets is the value within the 95% CI The p-value was calculated based on the log-rank test One of the most crucial analyses of CD24-CSF1R Index was its capacity to predict clinical outcomes The established index was significantly associated with mechanical ventilation status and the Charlson score (p < 0.005, Table 2) Multivariate Cox regression analysis was performed to confirm whether the CD24-CSF1R Index could provide independent prognostic information for the machine ventilator requirement Covariates, including age, sex, and Charlson score, were added to the model to evaluate factors related to the independent prognostic ability of the established index As shown in figure 4, the results indicated that age, sex, and Charlson score showed no significant correlation with ventilatory support of COVID-19 patients, while the established index displayed a strong prognostic ability for the risk of using mechanical ventilator (p < 0.001) This suggests that the CD24-CSF1R Index could be an independent predictor of the need for mechanical ventilation in COVID-19 patients Table Clinical information of COVID-19 patients in two patient groups classified by the CD24CSF1R Index 306 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” CD24-CSF1R Index Variables Total High Number of Low 100 51 (51.00) 49 (49.00) 63 45 (45.00) 27 (27.00) 18 (18.00) NA (1.00) (0.00) (1.00) female 38 (38.00) 19 (19.00) 19 (19.00) male 62 (62.00) 32 (32.00) 30 (30.00) Machine no 50 (50.00) 10 (10.00) 40 (40.00) ventilation yes 50 (50.00) 41 (41.00) (9.00) (9.00) (2.00) (7.00) 19 (19.00) (9.00) 10 (10.00) 20 (20.00) 11 (11.00) (9.00) 13 (13.00) 10 (10.00) (3.00) 11 (11.00) (5.00) (6.00) (7.00) (0.00) (7.00) 6 (6.00) (2.00) (4.00) 10 (10.00) (7.00) (3.00) (2.00) (2.00) (0.00) (2.00) (2.00) (0.00) 11 (1.00) (1.00) (0.00) patients (%) Age 0.1324 Sex Charlson score p-value 0.0005 0.012 Note: p -values were obtained from the χ2 -test 3.5 Interactions and relationships of CD24 and CSF1R with other proteins The protein–protein interaction network analysis was predicted using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database v11.5 The interactions between proteins are built based on information from many sources, including experimental data and computational prediction methods with high reliability The analysis revealed an interactive network of CD24 and CSF1R with ten other proteins, 307 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” including SLGLEC10, SELP, HMGB1, TYROBP, GRB2, TNFSF11, SPI1, IL34, CSF1, and CBL (Fig 5) Therein, CD24 was observed to interact with SELP, which was detected through a pull-down assay by BioGRID (Goksuluk et al., 2016), whereas CSF1R was demonstrated to interact with GRB2, CBL, and CSF1 from experimental information Furthermore, CSF1R also co-expressed with TYROBP, IL34, and SPI1 Figure 5: Protein interaction networks of CD24 and CSF1R Note: This protein network was generated by STRING Discussion COVID-19, this year, is still an obstacle to our lives which is invisible and transmits through the airborne As a result, human activities are stuck and lead to numerous serious consequences in income, the economy (Bank, 2020), education (Wayne, Green, & Neilson, 2020), psychology (Wang, Wang, & Yang, 2020), transportation, and an overloaded healthcare system (Lasater et al., 2021) Although several studies on COVID-19 have been conducted, vaccine protection still faces the rapid evolution of new mutant strains (Moore & Offit, 2021) Adults who have been fully vaccinated can carry the same viral load of coronavirus variants as unvaccinated people (Griffin, 2021) Even after receiving the vaccine, the healthcare system still faces understaffed and overcrowded front-line forces in pandemic prevention (Scales, 2020) In this study, we determined a CD24-CSF1R Index that could be considered as a new way to lighten the healthcare load The present study aimed to highlight the differences in the severity levels of infected cases which could help to classify and predict the risk of hospitalization at the early stage of disease infection Unfortunately, there is currently no permanent prevention and/or treatment for these viral episodes (Ali & Alharbi, 2020) Acute respiratory disease syndrome (ARDS) 308 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” was first observed in patients with severe COVID-19 through anatomical/histological reports from the lungs, which revealed excessive inflammatory activation and impairment of the bronchial and alveolar epithelium (Lai et al., 2020) Recent studies have reported that lung and systemic host innate immune responses affect survival outcomes in cases of positive or negative outcomes by triggering uncontrolled inflammation called “cytokine storm” (Hu, Huang, & Yin, 2021) This was explained by the host cellular signaling pathways and proteases involved in these processes (Sun et al., 2020) Therefore, immune-related genes should be studied more thoroughly to open a novel approach for COVID-19 diagnosis Until now, no functional documentation of the exact biological role of CD24 and CSF1R in the SARS-CoV-2 virus has been published CD24 plays an important role in modulating B-cell activation responses, which promotes the AG-dependent proliferation of B-cells and prevents the differentiation of their terminals (nonpolymorphic regions) to form cell antibodies (Suzuki et al., 2001) Its function is supposed to be a suppressor of antibody formation when the SARS-CoV-2 viruses affect the body Accordingly, to reduce the suppression of CD24 in its nonpolymorphic regions, MK-7110 has been used as a drug targeted at CD24 to diminish inflammation in SARS-CoV-2 infection, which has the potential to reduce the risk of death and organ failure, and is associated with a shorter recovery time (Hulshizer et al., 2021) Similarly, the mRNA expression level of CD24 was observed to increase in critically ill patients in our study (p = 1.102e-05, Fig 1A) CSF1R is a cell-surface receptor for CSF1 and IL34 (Bourette et al., 1993), which also controls pro-inflammatory chemokines and plays an important role in the innate immune system and inflammatory development (Auffray, Sieweke, & Geissmann, 2009) Furthermore, CSF1R plays a more important role in the regulation of hematopoietic precursor cell survival, proliferation, and differentiation (Guo et al., 2019) Additionally, CSF1R is found primarily in monocytes and macrophages (Guo et al., 2019) Meanwhile, CD24 expression levels were higher in the severe patients than in the mild ones; the expression level of CFS1R in our study revealed a downregulation curve in the severe patients (p = 1.155e-09, Fig 1B) The up-regulation of CD24 and downregulation of CFS1R in SARS-CoV-2 infection were associated with aggressive severe behaviors and predicted worse clinical outcomes, suggesting that these two could be potential prognostic predictors in the age of precision medicine We established the gene index (CD24-CSF1R) in which a high-index score significantly correlated with the requirement of mechanical ventilation, which can be used to predict the hospital course demand of COVID-19 patients Further, we analyzed the index between ventilation and non-ventilation, together with ICU status This index is also associated with this clinical information In addition, in the multivariate hazard Cox regression analysis, the index was found to be a strong independent biomarker that is self-reliable with other covariates The CD24-CSF1R Index’s classification ability was also superior to that of the Charlson score by the ROC model Additionally, the protein interaction networks were chosen to be related to the index score involved in macrophage colony-stimulating factor receptor binding, cytokine activity, cytokine receptor binding, positive regulation of macrophage proliferation, and several signaling pathways (Fig 5) Macrophage colony-stimulating factor (CSF1) 309 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” regulates macrophage activation and immune responses In many cases, CFS1 regulates the function of macrophages during viral infection while respiratory viruses replicate within macrophages to escape immune detection (Sweet & Hume, 2003) CSF1R requirement for the development of Langerhans cells (LCs) and microglia is interleukin 34 (IL34), which acts as a tissue-restricted ligand of CSF1R (Mathews et al., 2019) Mediators of multiple functions, LCs can interact directly with pathogens to produce effector cytokines and express different pattern recognition receptors, to bind and capture pathogens (Cunningham, Carbone, & Geijtenbeek, 2008) Microglia are involved in phagocytosis and engulf various materials, such as cellular debris, lipids, invading viruses, and bacteria (Chen, Zhong, & Li, 2019) Moreover, CSF1 and SPI1 (transcription factor PU.1) are key regulators of pulmonary dendritic cells and macrophages (Desch, Henson, & Jakubzick, 2013) Besides, Cbl proto-oncogene, E3 ubiquitin-protein ligase (CBL), and high mobility group protein B1 (HMGB1) are drug targets for the assessment of chloroquine efficacy in treating COVID-19 infection (SOUCHELNYTSKYI & Souchelnytskyi, 2020) Growth factor receptor-bound protein (GBR2) is a receptor of Interleukin-6 (IL6) whose serum levels significantly increase in patients suffering from COVID-19 (Abbasifard & Khorramdelazad, 2020) Next, protein tyrosine kinase-binding protein (TYROBPTYRO) also known as DAP12 combined with killer-cell activating receptor-associated protein (KARAP) to form an adapter that is involved in a broad array of biological functions such as a component of Natural Killer (NK) cell anti-viral (Sjölin et al., 2002) and anti-tumoral (Diefenbach et al., 2002) activities; as well as displayed inflammatory reactions (Tomasello & Vivier, 2005) as well as P-selectin precursor (SELP) (Xing, Cheng, Zha, & Yi, 2017), and tumor necrosis factor ligand superfamily member 11 (TNFSF11) (Cosgriff et al., 2021) Sialic acid-binding Ig-like lectin 10 (SIGLEG10) expressed a large amount in B1 cells which control inflammation by producing interleukin-10 (IL-10), interleukin-35 (IL-35), and granulocyte-macrophage colony-stimulating factor (GM-CFS) (Royster, Wang, & Aziz, 2021) which significantly causes death in COVID-19 patients (Ghasempour Dabaghi, Rabiee Rad, & Saberian, 2021) These genes have important functions in immunity which emphasizes the critical role of our gene index in the severity of COVID-19 Conclusion In conclusion, our study discovered that the CD24-CSF1R Index had a significant correlation with ICU admission and ventilatory status In detail, COVID-19 patients with a high index had significantly shorter mechanical ventilation-free days and higher risk of ICU admission than low-index patients Thus, it is more likely to predict the severity of COVID-19 patients and hospital course Besides, the gene-based index and its immunecomponent neighbors’ network in protein-protein interaction may decipher their roles in interaction with the SARS-CoV-2 virus as a causality of survival This may aid the healthcare system more efficiently as well as would be able to accommodate an emergency room physician’s ability to triage critically ill cases and predict prognosis during treatment periods; we suggest that the index could be used to predict COVID-19 severity in Vietnamese patients Moreover, CD24 and CSF1R may potentially serve as novel targets for drug development This is reinforced by the fact that MK-7110 - a drug target of CD24 was currently tested for COVID-19 patients in phase III clinical trial stage 310 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” by Merck company Its results indicated a single dose of MK-7110 displayed 60% improvement in clinical status and decreased 50% mortality of infected patients compared to placebo It opened a new avenue for antiviral drug development which effectively assist COVID-19 treatment Reference Abbasifard, 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Index” could be a potential indicator of COVID-19 severity 3.2 The CD24-CSF1R Index correctly classified COVID-19 severity Figure 2: ROC curve analysis of the CD24-CSF1R Index and Charlson score Note:... Kaplan-Meier curves of the CD24-CSF1R Index and Charlson score based on ventilation status of COVID-19 patients Note: KM plots of Charlson score (A) and CD24-CSF1R Index (B) of COVID-19 patients The... in COVID-19 patients Table Clinical information of COVID-19 patients in two patient groups classified by the CD24CSF1R Index 306 Hội thảo Khoa học Trẻ “Vaccine COVID-19: Nghiên cứu Ứng dụng” CD24-CSF1R
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