Risk and protective factors of SARS-CoV-2 infection.
Ontology highlight
ABSTRACT:
SUBMITTER: Takagi H
PROVIDER: S-EPMC7436481 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The antibiotic catabolic process and myeloid cell homeostasis were activated while the T-cell response were relatively repressed in those with the risk of secondary infection.
2021-09-20 | GSE184401 | GEO
Project description: Not available
| S-EPMC7836793 | biostudies-literature
Project description:BackgroundSince the first recognition of the pandemic characteristics of SARS-CoV-2 infection, and before substantial case fatality data were available worldwide, public health agencies warned the public about the increased dangers of SARS-CoV-2 to persons with a variety of underlying physical conditions, many of which are more commonly found in persons over 50 years of age or in certain ethnic groups.ObjectiveTo investigate the statistical rather than the physiological basis in support of the abovementioned warnings, this study examines correlations globally on a nation-by-nation basis between the statistical data concerning COVID-19 fatalities and the statistics of potential comorbidities that may influence the severity of infection.MethodsThis study considers the statistics describing the populations of the 99 countries with the greatest numbers of SARS-CoV-2 infections at the time of the data cutoff. As national compilations of direct measures of immune system strength are not publicly available, the frequency of fatalities in those countries due to a variety of serious diseases is used as a proxy for the susceptibility of those populations to those same diseases.ResultsThe analysis produces plots and calculations of correlations and cross-correlations of COVID-19 case fatality rates and the risks of other potential cofactors. It exposes some reasons that may underlie the degree to which advanced age increases the risk of mortality of infection with SARS-CoV-2. In contrast with the strong influences of comorbidities on the seriousness of consequences of influenzas and their associated pneumonias, the correlations of the same set of risk factors with SARS-CoV-2 infection are considerably weaker. The general characteristics of the observed correlations strengthened through 3 cycles of analysis, starting in September 2020. The strongest correlations were with chronic kidney disease and coronary disease (approximately 0.28 and 0.20, respectively).ConclusionsThis study confirms early clinical observations that infection with SARS-CoV-2 presents an increased risk to persons over the age of 65 years. It does not support the suggestions presented by government agencies early in the pandemic that the risks are much greater for persons with certain common potential comorbidities.
| S-EPMC8404263 | biostudies-literature
Project description:Identifying Risk Factors for Secondary Infection Post-SARS-CoV-2 Infection
| PRJNA764515 | ENA
Project description:Dysregulated immune responses contribute to the excessive and uncontrolled inflammation observed in severe COVID-19. However, how immunity to SARS-CoV-2 is induced and regulated remains unclear. Here we uncover a role of the complement system in the induction of innate and adaptive immunity to SARS-CoV-2. Complement rapidly opsonizes SARS-CoV-2 particles via the lectin pathway. Complement-opsonized SARS-CoV-2 efficiently induces type-I interferon and pro-inflammatory cytokine responses via activation of dendritic cells, which are inhibited by antibodies against the complement receptors (CR) 3 and 4. Serum from COVID-19 patients, or monoclonal antibodies against SARS-CoV-2, attenuate innate and adaptive immunity induced by complement-opsonized SARS-CoV-2. Blocking of CD32, the FcγRII antibody receptor of dendritic cells, restores complement-induced immunity. These results suggest that opsonization of SARS-CoV-2 by complement is involved in the induction of innate and adaptive immunity to SARS-CoV-2 in the acute phase of infection. Subsequent antibody responses limit inflammation and restore immune homeostasis. These findings suggest that dysregulation of the complement system and FcγRII signaling may contribute to severe COVID-19.
| S-SCDT-10_1038-S44318-024-00061-0 | biostudies-other
Project description:The effects of obesity and smoking in the coronavirus disease 2019 (COVID-19) pandemic remain controversial. Angiotensin converting enzyme 2 (ACE2), a component of the renin-angiotensin system (RAS), is the human cell receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19. ACE2 expression increases on lung alveolar epithelial cells and adipose tissue due to obesity, smoking and air pollution. A significant relationship exists between air pollution and SARS-CoV-2 infection, as more severe COVID-19 symptoms occur in smokers; comorbid conditions due to obesity or excess ectopic fat accumulation as underlying risk factors for severe COVID-19 strongly encourage the virus/ACE2 receptor-ligand interaction concept. Indeed, obesity, air pollution and smoking associated risk factors share underlying pathophysiologies that are related to the Renin-Angiotensin-System in SARS-CoV-2 infection. The aim of this review is to emphasize the mechanism of receptor-ligand interaction and its impact on the enhanced risk of death due to SARS-CoV-2 infection.
| S-EPMC7227557 | biostudies-literature
Project description:ObjectiveTo identify risk factors for severe disease in children hospitalised for SARS-CoV-2 infection.DesignMulticentre retrospective cohort study.Setting18 hospitals in Canada, Iran and Costa Rica from 1 February 2020 to 31 May 2021.PatientsChildren<18 years of age hospitalised for symptomatic PCR-positive SARS-CoV-2 infection, including PCR-positive multisystem inflammatory syndrome in children (MIS-C).Main outcome measureSeverity on the WHO COVID-19 Clinical Progression Scale was used for ordinal logistic regression analyses.ResultsWe identified 403 hospitalisations. Median age was 3.78 years (IQR 0.53-10.77). At least one comorbidity was present in 46.4% (187/403) and multiple comorbidities in 18.6% (75/403). Eighty-one children (20.1%) met WHO criteria for PCR-positive MIS-C. Progression to WHO clinical scale score ≥6 occurred in 25.3% (102/403). In multivariable ordinal logistic regression analyses adjusted for age, chest imaging findings, laboratory-confirmed bacterial and/or viral coinfection, and MIS-C diagnosis, presence of a single (adjusted OR (aOR) 1.90, 95% CI 1.13 to 3.20) or multiple chronic comorbidities (aOR 2.12, 95% CI 1.19 to 3.79), obesity (aOR 3.42, 95% CI 1.76 to 6.66) and chromosomal disorders (aOR 4.47, 95% CI 1.25 to 16.01) were independent risk factors for severity. Age was not an independent risk factor, but different age-specific comorbidities were associated with more severe disease in age-stratified adjusted analyses: cardiac (aOR 2.90, 95% CI 1.11 to 7.56) and non-asthma pulmonary disorders (aOR 3.07, 95% CI 1.26 to 7.49) in children<12 years old and obesity (aOR 3.69, 1.45-9.40) in adolescents≥12 years old. Among infants<1 year old, neurological (aOR 10.72, 95% CI 1.01 to 113.35) and cardiac disorders (aOR 10.13, 95% CI 1.69 to 60.54) were independent predictors of severe disease.ConclusionWe identified risk factors for disease severity among children hospitalised for PCR-positive SARS-CoV-2 infection. Comorbidities predisposing children to more severe disease may vary by age. These findings can potentially guide vaccination programmes and treatment approaches in children.
| S-EPMC9358955 | biostudies-literature
Project description:To explore the relationship between SARS-CoV-2 infection in different time before operation and postoperative main complications (mortality, main pulmonary and cardiovascular complications) 30 days after operation; To determine the best timing of surgery after SARS-CoV-2 infection.
| 12454 | ecrin-mdr-crc
Project description:HAE cultures were infected with SARS-CoV, SARS-dORF6 or SARS-BatSRBD and were directly compared to A/CA/04/2009 H1N1 influenza-infected cultures. Cell samples were collected at various hours post-infection for analysis. Time Points = 0, 12, 24, 36, 48, 60, 72, 84 and 96 hrs post-infection for SARS-CoV, SARS-dORF6 and SARS-BatSRBD. Time Points = 0, 6, 12, 18, 24, 36 and 48 hrs post-infection for H1N1. Done in triplicate or quadruplicate for RNA Triplicates/quadruplicates are defined as 3/4 different wells, plated at the same time and using the same cell stock for all replicates. Time matched mocks done in triplicate from same cell stock as rest of samples. Culture medium (the same as what the virus stock is in) will be used for the mock infections. Infection was done at an MOI of 2.
2013-07-31 | E-GEOD-47960 | biostudies-arrayexpress
Project description:HAE cultures were infected with SARS-CoV, SARS-ddORF6 or SARS-BatSRBD and were directly compared to A/CA/04/2009 H1N1 influenza-infected cultures. Cell samples were collected at various hours post-infection for analysis. Time Points = 0, 12, 24, 36, 48, 60, 72, 84 and 96 hrs post-infection for SARS-CoV. Time Points = 0, 24, 48, 60, 72, 84 and 96 hrs post-infection forSARS-ddORF6 and SARS-BatSRBD. Time Points = 0, 6, 12, 18, 24, 36 and 48 hrs post-infection for H1N1. Done in triplicate/quadruplicate for RNA Triplicates/quadruplicates are defined as 3/4 different wells, plated at the same time and using the same cell stock for all replicates. Time matched mocks done in triplicate from same cell stock as rest of samples. Culture medium (the same as what the virus stock is in) will be used for the mock infections. Infection was done at an MOI of 2.
2013-07-31 | E-GEOD-47961 | biostudies-arrayexpress