A new framework for host-pathogen interaction research.

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed.

Insufficient epitope-specific T cell clones are responsible for impaired cellular immunity to inactivated SARS-CoV-2 vaccine in older adults.

Aging is a critical risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine efficacy. The immune responses to inactivated vaccine for older adults, and the underlying mechanisms of potential differences to young adults, are still unclear. Here we show that neutralizing antibody production by older adults took a longer time to reach similar levels in young adults after inactivated SARS-CoV-2 vaccination. We screened SARS-CoV-2 variant strains for epitopes that stimulate specific CD8 T cell response, and older adults exhibited weaker CD8 T-cell-mediated responses to these epitopes. Comparison of lymphocyte transcriptomes from pre-vaccinated and post-vaccinated donors suggested that the older adults had impaired antigen processing and presentation capability. Single-cell sequencing revealed that older adults had less T cell clone expansion specific to SARS-CoV-2, likely due to inadequate immune receptor repertoire size and diversity. Our study provides mechanistic insights for weaker response to inactivated vaccine by older adults and suggests the need for further vaccination optimization for the old population.

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.

BACKGROUND: The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the development of the community-based Coronavirus Infectious Disease Ontology (CIDO) in early 2020. RESULTS: As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. CONCLUSION: CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications.

Epidemiological characteristics and pathological changes of primary glomerular diseases.

OBJECTIVE: By analyzing the pathological characteristics and clinical data of renal biopsy in our hospital in the past 20 years, to further understand the epidemic characteristics and pathological changes of primary glomerular disease, and to provide regional data for the big data of kidney disease in my country. METHODS: A retrospective analysis of 9448 patients with primary glomerular disease who were hospitalized in our hospital from January 1, 2000 to December 31, 2019, aged 18 years or older, and undergoing renal biopsy. Divided every 5 years into a group, a total of 4 groups (first group 2000.1.1-2004.12.31, second groups 2005.1.1-2009.12.31; third groups 2010.1.1-2014.12.31, fourth groups 2015.1.1-2019.12.31). RESULTS: ① There were more males than females, and male: female vs 1.53:1. The proportion of men in the past five years has increased compared with the previous 15 years. ② Mostly middle-aged, with a median age of 41.39 years old. The age is increasing over time. There are differences between the four groups, P <0.001; ③ The most common clinical manifestations are nephrotic syndrome, followed by chronic glomerulonephritis. Occult glomerulonephritis, the proportion of patients with nephrotic syndrome increases over time, first to fourth group (40.08%< 42.64% < 47.08%< 53.69%); ④ The most common pathology type from 2000 to 2009 was mesangial proliferative glomerulonephritis. IgA nephropathy was the most common type from 2010 to 2014, but the proportion of membranous nephropathy increased year by year, and it became the most common pathological type from 2015 to 2019; ⑤ The clinical and pathological manifestations of different genders are different, but there is no statistical difference. CONCLUSION: In the past 20 years, the primary glomerular disease is mainly middle-aged. There are more men than women. The most common type of clinical manifestation is nephrotic syndrome. The pathological type is mesangial proliferative glomerulonephritis. Over time, the average age is increasing, and the proportion of patients with renal syndrome is increasing. IgA nephropathy is the most common pathological type from 2010 to 2014, and membranous nephropathy has become the main pathological type in the past 5 years.

Trials and tribulations among members of Canada's Defence Team early in the pandemic: key insights from the COVID-19 Defence Team Survey. / Les défis auxquels ont fait face les membres de l'Équipe de la Défense du Canada au début de la pandémie : principales conclusions du sondage de l'Équipe de la Défense sur la COVID-19.

INTRODUCTION: Due to the unprecedented impact of COVID-19, there is a need for research assessing pandemic-related challenges and stressors. The current study aimed to assess key concerns and general well-being among members of Canada's Defence Team, including Canadian Armed Forces personnel and members of the Department of National Defence (DND) Public Service. METHODS: The COVID-19 Defence Team Survey was administered electronically to Defence Team staff in April and May of 2020 and was completed by 13 688 Regular Force, 5985 Reserve Force and 7487 civilian DND Public Service personnel. Along with demographic information, the survey included assessments of work arrangement, pandemic-related concerns, general well-being and social and organizational support. Weighted data (to ensure representation) were used in all analyses. RESULTS: The majority of respondents were working from home, with a small minority unable to work due to restrictions. Though many concerns were endorsed by a substantial proportion of respondents, the most prevalent concerns were related to the health and well-being of loved ones. The majority of respondents reported their partner, family, supervisors, friends, colleagues and children provided general support. Half of the civilian defence staff and one-third of military respondents reported a decline in mental health. Women, younger respondents, those with dependents and, in some cases, those who were single without children were at risk of lower well-being. CONCLUSION: The pandemic has negatively impacted a substantial portion of the Defence Team. When responding to future crises, it is recommended that leaders of organizations provide additional supports to higher-risk groups and to supervisors who are ideally positioned to support employees during challenging times.

SARS-CoV-2 variant B.1.1.7 caused HLA-A2+ CD8+ T cell epitope mutations for impaired cellular immune response.

Here, we evaluated the immune properties of the HLA-A2 restricted CD8+ T cell epitopes containing mutations from B.1.1.7, and furthermore performed a comprehensive analysis of the SARS-CoV-2 specific CD8+ T cell responses from COVID-19 convalescent patients and SARS-CoV-2 vaccinees recognizing the ancestral Wuhan strain compared to B.1.1.7. First, most of the predicted CD8+ T cell epitopes showed proper binding with HLA-A2, whereas epitopes from B.1.1.7 had lower binding capability than those from the ancestral strain. In addition, these peptides could effectively induce the activation and cytotoxicity of CD8+ T cells. Our results further showed that at least two site mutations in B.1.1.7 resulted in a decrease in CD8+ T cell activation and a possible immune evasion, namely A1708D mutation in ORF1ab1707-1716 and I2230T mutation in ORF1ab2230-2238. Our current analysis provides information that contributes to the understanding of SARS-CoV-2-specific CD8+ T cell responses elicited by infection of mutated strains or vaccination.

CD8+ T-Cell Epitope Variations Suggest a Potential Antigen HLA-A2 Binding Deficiency for Spike Protein of SARS-CoV-2.

We identified SARS-CoV-2 specific antigen epitopes by HLA-A2 binding affinity analysis and characterized their ability to activate T cells. As the pandemic continues, variations in SARS-CoV-2 virus strains have been found in many countries. In this study, we directly assess the immune response to SARS-CoV-2 epitope variants. We first predicted potential HLA-A*02:01-restricted CD8+ T-cell epitopes of SARS-CoV-2. Using the T2 cell model, HLA-A*02:01-restricted T-cell epitopes were screened for their binding affinity and ability to activate T cells. Subsequently, we examined the identified epitope variations and analyzed their impact on immune response. Here, we identified specific HLA-A2-restricted T-cell epitopes in the spike protein of SARS-CoV-2. Seven epitope peptides were confirmed to bind with HLA-A*02:01 and potentially be presented by antigen-presenting cells to induce host immune responses. Tetramers containing these peptides could interact with specific CD8+ T cells from convalescent COVID-19 patients, and one dominant epitope (n-Sp1) was defined. These epitopes could activate and generate epitope-specific T cells in vitro, and those activated T cells showed cytolytic activity toward target cells. Meanwhile, n-Sp1 epitope variant 5L>F significantly decreased the proportion of specific T-cell activation; n-Sp1 epitope 8L>V variant showed significantly reduced binding to HLA-A*02:01 and decreased proportion of n-Sp1-specific CD8+ T cell, which potentially contributes to the immune escape of SARS-CoV-2. Our data indicate that the variation of a dominant epitope will cause the deficiency of HLA-A*02:01 binding and T-cell activation, which subsequently requires the formation of a new CD8+ T-cell immune response in COVID-19 patients.

Identification of HLA-A2 restricted CD8+ T cell epitopes in SARS-CoV-2 structural proteins.

The outbreak of coronavirus disease 2019 (COVID-19) has now become a pandemic, and the etiologic agent is the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). T cell mediated immune responses play an important role in virus controlling; however, the understanding of the viral protein immunogenicity and the mechanisms of the induced responses are still limited. So, identification of specific epitopes and exploring their immunogenic properties would provide valuable information. In our study, we utilized the Immune Epitope Database and Analysis Resource and NetMHCpan to predict HLA-A2 restricted CD8+ T cell epitopes in structural proteins of SARS-CoV-2, and screened out 23 potential epitopes. Among them, 18 peptides showed strong or moderate binding with HLA-A2 with a T2A2 cell binding model. Next, the mixed peptides induced the increased expression of CD69 and highly expressed levels of IFN-γ and granzyme B in CD8+ T cells, indicating effective activation of specific CD8+ T cells. In addition, the peptide-activated CD8+ T cells showed significantly increased killing to the target cells. Furthermore, tetramer staining revealed that the activated CD8+ T cells mainly recognized seven epitopes. All together, we identified specific CD8+ T cell epitopes in SARS-CoV-2 structural proteins, which could induce the production of specific immune competent CD8+ T cells. Our work contributes to the understanding of specific immune responses and vaccine development for SARS-CoV-2.

Precision omics data integration and analysis with interoperable ontologies and their application for COVID-19 research.

Omics technologies are widely used in biomedical research. Precision medicine focuses on individual-level disease treatment and prevention. Here, we propose the usage of the term 'precision omics' to represent the combinatorial strategy that applies omics to translate large-scale molecular omics data for precision disease understanding and accurate disease diagnosis, treatment and prevention. Given the complexity of both omics and precision medicine, precision omics requires standardized representation and integration of heterogeneous data types. Ontology has emerged as an important artificial intelligence component to become critical for standard data and metadata representation, standardization and integration. To support precision omics, we propose a precision omics ontology hypothesis, which hypothesizes that the effectiveness of precision omics is positively correlated with the interoperability of ontologies used for data and knowledge integration. Therefore, to make effective precision omics studies, interoperable ontologies are required to standardize and incorporate heterogeneous data and knowledge in a human- and computer-interpretable manner. Methods for efficient development and application of interoperable ontologies are proposed and illustrated. With the interoperable omics data and knowledge, omics tools such as OmicsViz can also be evolved to process, integrate, visualize and analyze various omics data, leading to the identification of new knowledge and hypotheses of molecular mechanisms underlying the outcomes of diseases such as COVID-19. Given extensive COVID-19 omics research, we propose the strategy of precision omics supported by interoperable ontologies, accompanied with ontology-based semantic reasoning and machine learning, leading to systematic disease mechanism understanding and rational design of precision treatment and prevention. SHORT ABSTRACT: Precision medicine focuses on individual-level disease treatment and prevention. Precision omics is a new strategy that applies omics for precision medicine research, which requires standardized representation and integration of individual genetics and phenotypes, experimental conditions, and data analysis settings. Ontology has emerged as an important artificial intelligence component to become critical for standard data and metadata representation, standardization and integration. To support precision omics, interoperable ontologies are required in order to standardize and incorporate heterogeneous data and knowledge in a human- and computer-interpretable manner. With the interoperable omics data and knowledge, omics tools such as OmicsViz can also be evolved to process, integrate, visualize and analyze various omics data, leading to the identification of new knowledge and hypotheses of molecular mechanisms underlying disease outcomes. The precision COVID-19 omics study is provided as the primary use case to illustrate the rationale and implementation of the precision omics strategy.

Integrative web-based analysis of omics data for study of drugs against SARS-CoV-2.

Research on drugs against SARS-CoV-2 (cause of COVID-19) has been one of the major world concerns at present. There have been abundant research data and findings in this field. The interference of drugs on gene expression in cell lines, drug-target, protein-virus receptor networks, and immune cell infiltration of the host may provide useful information for anti-SARS-CoV-2 drug research. To simplify the complex bioinformatics analysis and facilitate the evaluation of the latest research data, we developed OmiczViz ( http://medcode.link/omicsviz ), a web tool that has integrated drug-cell line interference data, virus-host protein-protein interactions, and drug-target interactions. To demonstrate the usages of OmiczViz, we analyzed the gene expression data from cell lines treated with chloroquine and ruxolitinib, the drug-target protein networks of 48 anti-coronavirus drugs and drugs bound with ACE2, and the profiles of immune cell infiltration between different COVID-19 patient groups. Our research shows that chloroquine had a regulatory role of the immune response in renal cell line but not in lung cell line. The anti-coronavirus drug-target network analysis suggested that antihistamine of promethaziney and dietary supplement of Zinc might be beneficial when used jointly with antiviral drugs. The immune infiltration analysis indicated that both the COVID-19 patients admitted to the ICU and the elderly with infection showed immune exhaustion status, yet with different molecular mechanisms. The interactive graphic interface of OmiczViz also makes it easier to analyze newly discovered and user-uploaded data, leading to an in-depth understanding of existing findings and an expansion of existing knowledge of SARS-CoV-2. Collectively, OmicsViz is web program that promotes the research on medical agents against SARS-CoV-2 and supports the evaluation of the latest research findings.

Ontological modeling and analysis of experimentally or clinically verified drugs against coronavirus infection.

Our systematic literature collection and annotation identified 106 chemical drugs and 31 antibodies effective against the infection of at least one human coronavirus (including SARS-CoV, SAR-CoV-2, and MERS-CoV) in vitro or in vivo in an experimental or clinical setting. A total of 163 drug protein targets were identified, and 125 biological processes involving the drug targets were significantly enriched based on a Gene Ontology (GO) enrichment analysis. The Coronavirus Infectious Disease Ontology (CIDO) was used as an ontological platform to represent the anti-coronaviral drugs, chemical compounds, drug targets, biological processes, viruses, and the relations among these entities. In addition to new term generation, CIDO also adopted various terms from existing ontologies and developed new relations and axioms to semantically represent our annotated knowledge. The CIDO knowledgebase was systematically analyzed for scientific insights. To support rational drug design, a "Host-coronavirus interaction (HCI) checkpoint cocktail" strategy was proposed to interrupt the important checkpoints in the dynamic HCI network, and ontologies would greatly support the design process with interoperable knowledge representation and reasoning.

Emergency Management in a Dental Clinic During the Coronavirus Disease 2019 (COVID-19) Epidemic in Beijing.

BACKGROUND: In mid-March 2020, the World Health Organization declared that COVID-19 was to be characterised as a pandemic. The purpose of this article is to recommend emergency management procedures for dental clinics during this public health emergency. MATERIALS AND METHODS: We have implemented a series of emergency management measures to prevent cross-infection in our dental clinic during the COVID-19 pandemic, including personnel scheduling, division of the clinic into functional areas, limitation or delay of non-emergency patients, staff protection and infection controls, clinical environmental disinfection, and the use of online consultation services, among others. RESULTS: Due to public health policy and dental emergency management, the number of dental visitors to our clinic dropped sharply, and no COVID-19 suspected cases or high-risk patients received treatment. There have been no reports of infection of dental staff or patients during dental treatment in China to date. CONCLUSION: These public health policies and dental emergency management measures were effective in controlling cross-infection of COVID-19 in the dental clinic. PRACTICAL IMPLICATIONS: We share control measures for COVID-19, and hope that they will be helpful for dental professionals worldwide to continue to provide dental care in a safe and orderly manner.

Identification of risk factors for in-hospital death of COVID - 19 pneumonia -- lessions from the early outbreak.

BACKGROUND: To examine the clinical characteristics and identify independent risk factors for in-hospital mortality of 2019 novel coronavirus (COVID-19) pneumonia. METHODS: A total of 156 patients diagnosed with COVID-19 pneumonia at the Central Hospital of Wuhan from January 29, 2020, to March 20, 2020, and 20 healthy individuals were enrolled in this single-centered retrospective study. The epidemiological parameters, clinical presentations, underlying diseases, laboratory test results, and disease outcomes were collected and analyzed. RESULTS: The median age of all enrolled patients was 66 years. At least one underlying disease was identified in 101 COVID-19 patients, with hypertension being the most common one, followed by cardiovascular disease and diabetes. The most common symptoms identified upon admission were fever, cough, dyspnea, and fatigue. Compared to survival cases, patients who died during hospitalization had higher plasma levels of D-dimer, creatinine, creatine kinase, lactate dehydrogenase, lactate, and lower percentage of lymphocytes (LYM [%]), platelet count and albumin levels. Most enrolled patients received antibiotics and anti-viral treatment. In addition, 60 patients received corticosteroids, and 51 received intravenous immunoglobulin infusion. Forty-four patients received noninvasive ventilation and 19 received invasive ventilation. Respiratory failure was the most frequently observed complication (106 [67.9%]), followed by sepsis (103 [66.0%]), acute respiratory distress syndrome (ARDS) (67 [42.9%]), and septic shock (50 [32.1%]). Multivariable regression suggested that advanced age (OR [odds ratio] = 1.098, 95% CI [confidence interval]: 1.006-1.199, P = 0.037), shorter duration from onset to admission (OR = 0.853, 95% CI: 0.750-0.969, P = 0.015) and elevated lactate level upon admission (OR = 2.689, 95% CI: 1.044-6.926, P = 0.040) were independent risk factors for in-hospital mortality for COVID-19 infection. Meanwhile, increased LYM (%) at admission (OR = 0.787, 95% CI: 0.686-0.903, P = 0.001) indicated a better prognosis. CONCLUSIONS: In this study, we discovered that age, duration from onset to admission, LYM (%), and lactate level upon admission were independent factors that affecting the in-hospital mortality rate.

The comparative analysis of epidemiological characteristics between COVID-19 and SARS

Both COVID-19 and SARS are two serious infectious diseases caused by coronaviruses. The cause of both is still unknown and there are currently no effective treatments. Therefore, it is important to understand the epidemiological and pathological characteristics of COVID-19 and SARS for its prevention and treatment. This article reviewed the literature, combined with the latest research status at home and abroad, to explore the two diseases of COVID-19 and SARS from the etiology, spatial, time and population distributions and pathology. The results show that the two infectious diseases have many of the same clinical characteristics. There are some differences in the disease process, severity, and imaging. COVID-19 have stronger infectivity than SARS, but its mortality is lower than SARS, and the pathological changes of the two are also different. The article also compared the experiences and lessons learned during the SARS epidemic, sorted out the loopholes and deficiencies in disease prevention and control during the COVID-19 epidemic, and made recommendations for the problems at the current stage, so as to provides the certain scientific basis for preventing and treating the two diseases, and their pathogenesis research.

Clinical characteristics and laboratory results of pregnant women with COVID-19 in Wuhan, China.

OBJECTIVE: To evaluate the clinical characteristics and laboratory test results in pregnant women with coronavirus disease 2019 (COVID-19). METHODS: A retrospective study to review and compare clinical data including electronic medical records and laboratory tests from pregnant and nonpregnant patients admitted the Central Hospital of Wuhan, China from December 8, 2019 to April 1, 2020. RESULTS: A total of 72 women (30 pregnant and 42 nonpregnant) with COVID-19 were included. No patients developed severe pneumonia during the study. Compared with the nonpregnant group, pregnant patients were admitted to hospital earlier (0.25 vs 11.00 days; P<0.001), presented milder symptoms, had a higher rate of asymptomatic infection (26.7% vs 0%), and shorter length of hospital stay (14.5 vs 17.0 days; P<0.01). Laboratory test results showed that levels of inflammation markers such as white blood cell count, neutrophil count and percentage, C-reactive protein, procalcitonin, and D-dimer were significantly higher in pregnant women, whereas mean lymphocyte percentage was significantly lower compared with nonpregnant women. CONCLUSION: In some respects, the clinical characteristics and laboratory test results of COVID-19 in pregnant patients seems to be distinctive from their nonpregnant counterparts. Appropriate advice and positive treatment might be critical to the prognosis when dealing with these pregnant patients. Pregnant patients with COVID-19 had their own positive clinical characteristics and special laboratory test results. Responsive medical advice and active treatment for those patients are critical to recovery.

Clinical features of familial clustering in patients infected with 2019 novel coronavirus in Wuhan, China.

An epidemic caused by SARS-Coronavirus-2 (SARS-CoV-2) infection has appeared in Wuhan City in December 2019. The disease has shown a "clustering epidemic" pattern, and family-clustered onset has been the main characteristic. We collected data about 130 cases from 35 cluster-onset families (COFs) and 41 cases from 16 solitary-onset families (SOFs). The incidence of 2019 coronavirus disease (COVID-19) in COFs was significantly higher than that of SOFs. Our study also showed that patients with exposure to high-risk factors (respiratory droplets and close contact), advanced age, and comorbidities were more likely to develop COVID-19 in the COFs. In addition, advanced age and elevated neutrophil/lymphocyte ratio (NLR) were risk factors for death in patients with SARS-CoV-2 infection in the COFs.