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.

Profiling COVID-19 Vaccine Adverse Events by Statistical and Ontological Analysis of VAERS Case Reports.

Since the beginning of the COVID-19 pandemic, vaccines have been developed to mitigate the spread of SARS-CoV-2, the virus that causes COVID-19. These vaccines have been effective in reducing the rate and severity of COVID-19 infection but also have been associated with various adverse events (AEs). In this study, data from the Vaccine Adverse Event Reporting System (VAERS) was queried and analyzed via the Cov19VaxKB vaccine safety statistical analysis tool to identify statistically significant (i.e., enriched) AEs for the three currently FDA-authorized or approved COVID-19 vaccines. An ontology-based classification and literature review were conducted for these enriched AEs. Using VAERS data as of 31 December 2021, 96 AEs were found to be statistically significantly associated with the Pfizer-BioNTech, Moderna, and/or Janssen COVID-19 vaccines. The Janssen COVID-19 vaccine had a higher crude reporting rate of AEs compared to the Moderna and Pfizer COVID-19 vaccines. Females appeared to have a higher case report frequency for top adverse events compared to males. Using the Ontology of Adverse Event (OAE), these 96 adverse events were classified to different categories such as behavioral and neurological AEs, cardiovascular AEs, female reproductive system AEs, and immune system AEs. Further statistical comparison between different ages, doses, and sexes was also performed for three notable AEs: myocarditis, GBS, and thrombosis. The Pfizer vaccine was found to have a closer association with myocarditis than the other two COVID-19 vaccines in VAERS, while the Janssen vaccine was more likely to be associated with thrombosis and GBS AEs. To support standard AE representation and study, we have also modeled and classified the newly identified thrombosis with thrombocytopenia syndrome (TTS) AE and its subclasses in the OAE by incorporating the Brighton Collaboration definition. Notably, severe COVID-19 vaccine AEs (including myocarditis, GBS, and TTS) rarely occur in comparison to the large number of COVID-19 vaccinations administered in the United States, affirming the overall safety of these COVID-19 vaccines.

Long-Term Exposure to Ambient PM2.5 and Increased Risk of CKD Prevalence in China.

BACKGROUND: Fine particulate matter (PM2.5) is an important environmental risk factor for cardiopulmonary diseases. However, the association between PM2.5 and risk of CKD remains under-recognized, especially in regions with high levels of PM2.5, such as China. METHODS: To explore the association between long-term exposure to ambient PM2.5 and CKD prevalence in China, we used data from the China National Survey of CKD, which included a representative sample of 47,204 adults. We estimated annual exposure to PM2.5 before the survey date at each participant's address, using a validated, satellite-based, spatiotemporal model with a 10 km×10 km resolution. Participants with eGFR <60 ml/min per 1.73 m2 or albuminuria were defined as having CKD. We used a logistic regression model to estimate the association and analyzed the influence of potential modifiers. RESULTS: The 2-year mean PM2.5 concentration was 57.4 µg/m3, with a range from 31.3 to 87.5 µg/m3. An increase of 10 µg/m3 in PM2.5 was positively associated with CKD prevalence (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.22 to 1.35) and albuminuria (OR, 1.39; 95% CI, 1.32 to 1.47). Effect modification indicated these associations were significantly stronger in urban areas compared with rural areas, in males compared with females, in participants aged <65 years compared with participants aged ≥65 years, and in participants without comorbid diseases compared with those with comorbidities. CONCLUSIONS: These findings regarding the relationship between long-term exposure to high ambient PM2.5 levels and CKD in the general Chinese population provide important evidence for policy makers and public health practices to reduce the CKD risk posed by this pollutant.

Development of the International Classification of Diseases Ontology (ICDO) and its application for COVID-19 diagnostic data analysis.

BACKGROUND: The 10th and 9th revisions of the International Statistical Classification of Diseases and Related Health Problems (ICD10 and ICD9) have been adopted worldwide as a well-recognized norm to share codes for diseases, signs and symptoms, abnormal findings, etc. The international Consortium for Clinical Characterization of COVID-19 by EHR (4CE) website stores diagnosis COVID-19 disease data using ICD10 and ICD9 codes. However, the ICD systems are difficult to decode due to their many shortcomings, which can be addressed using ontology. METHODS: An ICD ontology (ICDO) was developed to logically and scientifically represent ICD terms and their relations among different ICD terms. ICDO is also aligned with the Basic Formal Ontology (BFO) and reuses terms from existing ontologies. As a use case, the ICD10 and ICD9 diagnosis data from the 4CE website were extracted, mapped to ICDO, and analyzed using ICDO. RESULTS: We have developed the ICDO to ontologize the ICD terms and relations. Different from existing disease ontologies, all ICD diseases in ICDO are defined as disease processes to describe their occurrence with other properties. The ICDO decomposes each disease term into different components, including anatomic entities, process profiles, etiological causes, output phenotype, etc. Over 900 ICD terms have been represented in ICDO. Many ICDO terms are presented in both English and Chinese. The ICD10/ICD9-based diagnosis data of over 27,000 COVID-19 patients from 5 countries were extracted from the 4CE. A total of 917 COVID-19-related disease codes, each of which were associated with 1 or more cases in the 4CE dataset, were mapped to ICDO and further analyzed using the ICDO logical annotations. Our study showed that COVID-19 targeted multiple systems and organs such as the lung, heart, and kidney. Different acute and chronic kidney phenotypes were identified. Some kidney diseases appeared to result from other diseases, such as diabetes. Some of the findings could only be easily found using ICDO instead of ICD9/10. CONCLUSIONS: ICDO was developed to ontologize ICD10/10 codes and applied to study COVID-19 patient diagnosis data. Our findings showed that ICDO provides a semantic platform for more accurate detection of disease profiles.

Renin-angiotensin system inhibitor is associated with the reduced risk of all-cause mortality in COVID-19 among patients with/without hypertension.

Consecutively hospitalized patients with confirmed coronavirus disease 2019 (COVID-19) in Wuhan, China were retrospectively enrolled from January 2020 to March 2020 to investigate the association between the use of renin-angiotensin system inhibitor (RAS-I) and the outcome of this disease. Associations between the use of RAS-I (angiotensin-converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB)), ACEI, and ARB and in-hospital mortality were analyzed using multivariate Cox proportional hazards regression models in overall and subgroup of hypertension status. A total of 2771 patients with COVID-19 were included, with moderate and severe cases accounting for 45.0% and 36.5%, respectively. A total of 195 (7.0%) patients died. RAS-I (hazard ratio (HR)= 0.499, 95% confidence interval (CI) 0.325-0.767) and ARB (HR = 0.410, 95% CI 0.240-0.700) use was associated with a reduced risk of all-cause mortality among patients with COVID-19. For patients with hypertension, RAS-I and ARB applications were also associated with a reduced risk of mortality with HR of 0.352 (95% CI 0.162-0.764) and 0.279 (95% CI 0.115-0.677), respectively. RAS-I exhibited protective effects on the survival outcome of COVID-19. ARB use was associated with a reduced risk of all-cause mortality among patients with COVID-19.

Early versus late acute kidney injury among patients with COVID-19-a multicenter study from Wuhan, China.

BACKGROUND: Acute kidney injury (AKI) is an important complication of coronavirus disease 2019 (COVID-19), which could be caused by both systematic responses from multi-organ dysfunction and direct virus infection. While advanced evidence is needed regarding its clinical features and mechanisms. We aimed to describe two phenotypes of AKI as well as their risk factors and the association with mortality. METHODS: Consecutive hospitalized patients with COVID-19 in tertiary hospitals in Wuhan, China from 1 January 2020 to 23 March 2020 were included. Patients with AKI were classified as AKI-early and AKI-late according to the sequence of organ dysfunction (kidney as the first dysfunctional organ or not). Demographic and clinical features were compared between two AKI groups. Their risk factors and the associations with in-hospital mortality were analyzed. RESULTS: A total of 4020 cases with laboratory-confirmed COVID-19 were included and 285 (7.09%) of them were identified as AKI. Compared with patients with AKI-early, patients with AKI-late had significantly higher levels of systemic inflammatory markers. Both AKIs were associated with an increased risk of in-hospital mortality, with similar fully adjusted hazard ratios of 2.46 [95% confidence interval (CI) 1.35-4.49] for AKI-early and 3.09 (95% CI 2.17-4.40) for AKI-late. Only hypertension was independently associated with the risk of AKI-early. While age, history of chronic kidney disease and the levels of inflammatory biomarkers were associated with the risk of AKI-late. CONCLUSIONS: AKI among patients with COVID-19 has two clinical phenotypes, which could be due to different mechanisms. Considering the increased risk for mortality for both phenotypes, monitoring for AKI should be emphasized during COVID-19.