A rare case of cardiogenic shock caused by takotsubo syndrome associated with SARS-CoV-2 infection: The value of echocardiography in the diagnosis and monitoring of the efficacy of extracorporeal membrane oxygenation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mainly invades the respiratory system, but may also cause various cardiovascular complications. We report a rare case of myocarditis associated with SARS-CoV-2 infection. A 61-year-old man was admitted to the hospital with a positive nucleic acid test for SARS-CoV-2. A sudden increase in troponin level (up to .144 ng/mL) was observed on the 8th day after admission. He developed symptoms of heart failure and progressed rapidly to cardiogenic shock. Echocardiography on the same day showed reduced left ventricular ejection fraction, reduced cardiac output, and segmental ventricular wall motion abnormalities. Takotsubo cardiomyopathy associated with SARS-CoV-2 infection was considered based on the typical echocardiography findings. We immediately started veno-arterial extracorporeal membrane oxygenation (VA-ECMO) treatment. The patient was successfully withdrawn from VA-ECMO after 8 days following recovery of ejection fraction to 65% and all indicators qualifying the withdrawal criteria. Echocardiography plays an important role in dynamic monitoring of cardiac changes in such cases and can help determine the timing of extracorporeal membrane oxygenation treatment and withdrawal.

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.

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.

Differential COVID-19 Symptoms Given Pandemic Locations, Time, and Comorbidities During the Early Pandemic.

BACKGROUND: COVID-19 pandemic is disaster to public health worldwide. Better perspective on COVID's features early in its course-prior to the development of vaccines and widespread variants-may prove useful in the understanding of future pandemics. Ontology provides a standardized integrative method for knowledge modeling and computer-assisted reasoning. In this study, we systematically extracted and analyzed clinical phenotypes and comorbidities in COVID-19 patients found at different countries and regions during the early pandemic using an ontology-based bioinformatics approach, with the aim to identify new insights and hidden patterns of the COVID-19 symptoms. RESULTS: A total of 48 research articles reporting analysis of first-hand clinical data from over 40,000 COVID-19 patients were surveyed. The patients studied therein were diagnosed with COVID-19 before May 2020. A total of 18 commonly-occurring phenotypes in these COVID-19 patients were first identified and then classified into different hierarchical groups based on the Human Phenotype Ontology (HPO). This meta-analytic approach revealed that fever, cough, and the loss of smell and taste were ranked as the most commonly-occurring phenotype in China, the US, and Italy, respectively. We also found that the patients from Europe and the US appeared to have more frequent occurrence of many nervous and abdominal symptom phenotypes (e.g., loss of smell, loss of taste, and diarrhea) than patients from China during the early pandemic. A total of 22 comorbidities, such as diabetes and kidney failure, were found to commonly exist in COVID-19 patients and positively correlated with the severity of the disease. The knowledge learned from the study was further modeled and represented in the Coronavirus Infectious Disease Ontology (CIDO), supporting semantic queries and analysis. Furthermore, also considering the symptoms caused by new viral variants at the later stages, a spiral model hypothesis was proposed to address the changes of specific symptoms during different stages of the pandemic. CONCLUSIONS: Differential patterns of symptoms in COVID-19 patients were found given different locations, time, and comorbidity types during the early pandemic. The ontology-based informatics provides a unique approach to systematically model, represent, and analyze COVID-19 symptoms, comorbidities, and the factors that influence the disease outcomes.

Clinical features and outcomes of seven patients with COVID-19 in a family cluster.

BACKGROUND: The family cluster is one of most important modes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission throughout China, and more details are needed about how family clusters cause the spread of coronavirus disease 2019 (COVID-19). CASE PRESENTATION: We retrospectively reviewed 7 confirmed cases from one family cluster. Both clinical features and laboratory examination results were described. Patient 1 had been in close contact with someone who was later confirmed to have COVID-19 in Wuhan City before he returned back to his hometown. He had dinner with 6 other members in his family. All the persons developed COVID-19 successively except for one older woman who neither had dinner with them nor shared a sleeping room with her husband. Six patients had mild or moderate COVID-19 but one older man with underlying diseases progressed into the severe type. After general and symptomatic treatments, all the patients recovered. CONCLUSIONS: In a family cluster, having dinner together may be an important mode for the transmission of SARS-CoV-2. In this setting, most cases are mild with a favorable prognosis, while elderly patients with underlying diseases may progress into the severe type. For someone who has close contact with a confirmed case, 14-day isolation is necessary to contain virus transmission.

A 55-Day-Old Female Infant Infected With 2019 Novel Coronavirus Disease: Presenting With Pneumonia, Liver Injury, and Heart Damage.

BACKGROUND: Previous studies on the pneumonia outbreak caused by the 2019 novel coronavirus disease (COVID-19) were mainly based on information from adult populations. Limited data are available for children with COVID-19, especially for infected infants. METHODS: We report a 55-day-old case with COVID-19 confirmed in China and describe the identification, diagnosis, clinical course, and treatment of the patient, including the disease progression from day 7 to day 11 of illness. RESULTS: This case highlights that children with COVID-19 can also present with multiple organ damage and rapid disease changes. CONCLUSIONS: When managing such infant patients with COVID-19, frequent and careful clinical monitoring is essential.