In March 2022, the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) surged during the Coronavirus Disease 2019 (COVID‐19) pandemic in Shanghai, but over 90% of patients were mild. This study included 1139 COVID‐19 patients mildly infected with the Omicron variant of SARS‐CoV‐2 in Shanghai from May 1 to 10, 2022, aiming to clarify the demographic characteristics and clinical symptoms of patients with mild Omicron infection. The clinical phenotypes of Omicron infection were identified by model‐based cluster analysis to explore the features of different clusters. The median age of the patients was 41.0 years [IQR: 31.0–52.0 years] and 73.0% were male. The top three clinical manifestations are cough (57.5%), expectoration (48.3%), and nasal congestion and runny nose (43.4%). The prevalence of nasal congestion and runny nose varied significantly across the doses of vaccinations, with 23.1% in the unvaccinated population and 30%, 45.9%, and 44.3% in the 1‐dose, 2‐dose and 3‐dose vaccinated populations, respectively. In addition, there were significant differences for fever (23.1%, 26.0%, 28.6%, 18.4%), head and body heaviness (15.4%, 14.0%, 26.7%, 22.4%), and loss of appetite (25.6%, 30.0%, 33.6%, 27.7%). The unvaccinated population had a lower incidence of symptoms than the vaccinated population. Cluster analysis revealed that all four clusters had multisystemic symptoms and were dominated by both general and respiratory symptoms. The more severe the degree of the symptoms was, the higher the prevalence of multisystemic symptoms will be. The Omicron variant produced a lower incidence of symptoms in mildly infected patients than previous SARS‐CoV‐2 variants, but the clinical symptoms caused by the Omicron variant are more complex, so that it needs to be differentiated from influenza.

Clinical characteristics of 1139 mild cases of the SARS‐CoV‐2 Omicron variant infected patients in Shanghai

Clinical and mechanistic considerations in idiosyncratic drug-induced liver injury (iDILI) remain challenging topics when they are derived from mere case narratives or iDILI cases without valid diagnosis. To overcome these issues, attempts should be made on pathogenetic aspects based on published clinical iDILI cases firmly diagnosed by the original RUCAM (Roussel Uclaf Causality Assessment Method) or the RUCAM version updated in 2016. Analysis of RUCAM-based iDILI cases allowed for evaluating immune and genetic data obtained from the serum and the liver of affected patients. For instance, strong evidence for immune reactions in the liver of patients with RUCAM-based iDILI was provided by the detection of serum anti-CYP 2E1 due to drugs like volatile anesthetics sevoflurane and desflurane, partially associated with the formation of trifluoroacetyl (TFA) halide as toxic intermediates that form protein adducts and may generate reactive oxygen species (ROS). This is accompanied by production of anti-TFA antibodies detected in the serum of these patients. Other RUCAM-based studies on serum ANA (anti-nuclear antibodies) and SMA (anti-smooth muscle antibodies) associated with AIDILI (autoimmune DILI) syn DIAIH (drug-induced autoimmune hepatitis) provide additional evidence of immunological reactions with monocytes as one of several promoting immune cells. In addition, in the blood plasma of patients, mediators like the cytokines IL-22, IL-22 binding protein (IL-22BP), IL-6, IL-10, IL 12p70, IL-17A, IL-23, IP-10, or chemokines such as CD206 and sCD163 were found in DILI due to anti-tuberculosis drugs as ascertained by the prospective updated RUCAM, which scored a high causality. RUCAM-based analysis also provided compelling evidence of genetic factors such as HLA (human leucocyte antigen) alleles contributing to initiate iDILI by a few drugs. In conclusion, analysis of published RUCAM-based iDILI cases provided firm evidence of immune and genetic processes involved in iDILI caused by specific drugs.

/pdf/advances-in-idiosyncratic-drug-induced-liver-injury-issues-27pf1oyw.pdf

Advances in Idiosyncratic Drug-Induced Liver Injury Issues: New Clinical and Mechanistic Analysis Due to Roussel Uclaf Causality Assessment Method Use

https://doi.org/10.1016/j.aohep.2022.100763

Clinical characteristics of liver injury in SARS-CoV-2 Omicron variant- and Omicron subvariant-infected patients

Abstract Background Since the onset of the COVID-19 pandemic, SARS-CoV-2 has evolved into independent new forms, variants of concern (VOCs). While epidemiological data showed increased transmissibility of VOCs, their impact on clinical outcomes is less clear. This study aimed to investigate the differences between the clinical and laboratory features of children infected with VOCs. Methods This study included all cases with SARS-CoV-2-positive nasopharyngeal swabs obtained from patients referred to Children’s Medical Center (CMC), an Iranian referral hospital, between July 2021 and March 2022. The inclusion criteria for this study included all patients, regardless of age, who had a positive test anywhere in the hospital setting. Exclusion criteria for the study included those whose data was obtained from non-hospital outpatient settings, or referred from another hospital. The SARS-CoV-2 genome area encoding the S1 domain was amplified and sequenced. The type of variant in each sample was identified based on the mutations in the S1 gene. Demographic characteristics, clinical data, and laboratory findings were collected from the patient’s medical records. Results This study included 87 pediatric cases with confirmed COVID-19, with a median age of 3.5 years (IQR: 1-8.12). Data from sequencing reveals the type of variants as 5 (5.7%) alpha, 53 (60.9%) Delta, and 29 (33.3%) Omicron. The incidence of seizure was higher in patients with Alpha and Omicron infection compared to the Delta group. A higher incidence of diarrhea was reported in Alpha-infected patients, and a higher risk of disease severity, distress, and myalgia was associated with Delta infection. Conclusion Laboratory parameters did not mostly differ among the patients infected with Alpha, Delta, and Omicron. However, these variants may manifest different clinical features. Further studies with larger sample sizes are required to fully understand the clinical manifestations of each variant. 

https://bmcpediatr.biomedcentral.com/counter/pdf/10.1186/s12887-023-04042-w

Clinical and laboratory features of SARS-CoV-2 variants across multiple rounds of pandemic waves in hospitalized children in an Iranian referral hospital

Drugs are prescribed worldwide to treat diseases but with the risk of idiosyncratic drug-induced liver injury (iDILI). The most important difficulty is how best to establish causality. Based on strong evidence and principles of artificial intelligence (AI) to solve complex processes through quantitative algorithms using scored elements, progress was achieved with the Roussel Uclaf Causality Assessment Method (RUCAM) in its original and updated versions, often viewed now as the gold standard. As a highly appreciated diagnostic algorithm, the RUCAM is in global use with around 100,000 iDILI cases published worldwide using RUCAM to assess causality, largely outperforming any other specific causality assessment tool in terms of case numbers. Consequently, the RUCAM helps to establish a list of top-ranking drugs worldwide implicated in iDILI and to describe clinical and mechanistic features of iDILI caused by various drugs. In addition, the RUCAM was recently applied in iDILI cases of patients treated for coronavirus disease 2019 (COVID-19) infections or cancer patients treated with immune checkpoint inhibitors (ICIs), as well as in the search for new treatment options with conventional drugs in iDILI. Analyses of RUCAM-based iDILI cases are helpful to support pathogenetic steps like immune reactions, genetic predisposition as evidenced by human leucocyte antigens (HLA) genotypes for selected drugs, and the role of the gut microbiome. To achieve consistency in data collection, analysis, and specific clinical and pathogenetic presentation, researchers, regulatory agencies, and pharmaceutical firms should place iDILI and the updated RUCAM as the causality tool under one and the same hat in review articles and clinical guidelines for the diagnosis and treatment of iDILI.

Idiosyncratic DILI and RUCAM under One Hat: The Global View

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta and Omicron variants have become the dominant variants worldwide, and studies focused on liver injury in these patients are limited. Materials and methods In this study, 157 SARS-CoV-2-infected patients were enrolled, including 77 Delta variant-infected patients and 80 Omicron variant-infected patients. Liver injury data and clinical data were summarized and compared between patients infected with the two variants, additionally, patients with or without liver injury were also compared and multivariate analysis was performed to explore the predictive factors related to liver injury in SARS-CoV-2-infected patients. Results Liver injury was found in 18 (23.4%)/15 (18.8%) in Delta/Omicron variant-infected patients on admission, and 4 (5.2%)/1 (1.3%) in Delta/Omicron variant-infected patients during hospitalization, respectively. The ratios of liver injury did not differ between the two groups (χ2 = 1.571; P = 0.210). Among these patients, 17 (77.3%) and 12 (75.0%) Delta and Omicron variant-infected patients were considered to be related to SARS-CoV-2 infection, the biomarkers of liver function were mildly elevated, dominated by the parameter of cholangiocyte injury: 76.5% (13/17) and 83.3% (10/12) in Delta and Omicron variant-infected patients, and most of these patients recovered to normal during follow-up. Multivariate analysis showed that male sex [odds ratio (OR), 4.476; 95% confidence interval (CI), 1.235–16.222; P = 0.023] and high levels of peak viral load in the nasopharynx (OR, 3.022; 95% CI, 1.338–6.827; P = 0.008) were independent factors related to liver injury. Conclusion Cholangiocyte injury biomarkers are dominated in Delta and Omicron variant-infected patients, male sex and high levels of peak viral load in the nasopharynx are predictive factors related to liver injury in SARS-CoV-2-infected patients.

Clinical features and predictive factors related to liver injury in SARS-CoV-2 Delta and Omicron variant-infected patients

Colon cancer (Cc) is the third high-malignancy cancer in the world, and there are abundant publications about colon cancer. A Support Vector Machine classifier is used to extract the relation about mutated genes, microRNAs (miRNA) in Cc cells by mining scientific literature containing experimentally validated data. Three topology networks are constructed based on the extracted genes and miRNAs. The feed-back loops and self-adaption relations are found within these networks, and used for identifying the mechanism of colon cancer by comparing and analyzing the difference and relatedness among the networks. This study provides a fundamental hypothesis for further analysis of colon tumorigenesis.

Mutation Relation Extraction and Genes Network Analysis in Colon Cancer

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Clinical features and predictive factors related to liver injury in SARS-CoV-2 Delta and Omicron variant-infected patients

Mutation Relation Extraction and Genes Network Analysis in Colon Cancer