Autoantibodies are highly prevalent in non-SARS-CoV-2 respiratory infections and critical illness
Ontology highlight
ABSTRACT:
ORGANISM(S): Triticum aestivum Escherichia coli Bos taurus Sus scrofa Spodoptera frugiperda Homo sapiens Capra hircus
PROVIDER: GSE222765 | GEO | 2023/01/12
REPOSITORIES: GEO
Similar Datasets
Project description:We used protein arrays to measure IgG autoantibodies associated with Connective Tissue Diseases (CTDs) and Anti-Cytokine Antibodies (ACA) in patients with non-COVID-19 infections such as influenza
2023-01-12 | GSE222760 | GEO
Project description:We used protein arrays to measure IgG autoantibodies associated with Connective Tissue Diseases (CTDs) and Anti-Cytokine Antibodies (ACA) in patients with non-COVID-19 infections such as influenza
2023-01-12 | GSE222764 | GEO
Project description:The widespread presence of autoantibodies in acute infection with SARS-CoV-2 is increasingly recognized, but the prevalence of autoantibodies in non-SARS-CoV-2 infections and critical illness has not yet been reported. We profiled IgG autoantibodies in 267 patients from 5 independent cohorts with non-SARS-CoV-2 viral, bacterial, and noninfectious critical illness. Serum samples were screened using Luminex arrays that included 58 cytokines and 55 autoantigens, many of which are associated with connective tissue diseases (CTDs). Samples positive for anti-cytokine antibodies were tested for receptor blocking activity using cell-based functional assays. Anti-cytokine antibodies were identified in > 50% of patients across all 5 acutely ill cohorts. In critically ill patients, anti-cytokine antibodies were far more common in infected versus uninfected patients. In cell-based functional assays, 11 of 39 samples positive for select anti-cytokine antibodies displayed receptor blocking activity against surface receptors for Type I IFN, GM-CSF, and IL-6. Autoantibodies against CTD-associated autoantigens were also commonly observed, including newly detected antibodies that emerged in longitudinal samples. These findings demonstrate that anti-cytokine and autoantibodies are common across different viral and nonviral infections and range in severity of illness.
| S-EPMC9977421 | biostudies-literature
Project description:Autoantibodies are highly prevalent in non-SARS-CoV-2 respiratory infections and critical illness
| PRJNA923332 | ENA
Project description:Autoantibodies are highly prevalent in non-SARS-CoV-2 respiratory infections and critical illness [ACA]
| PRJNA923335 | ENA
Project description:Autoantibodies are highly prevalent in non-SARS-CoV-2 respiratory infections and critical illness [CTD]
| PRJNA923336 | ENA
Project description:Abstract Background: Many issues, such as severity assessment and antibody responses, remain to be answered eagerly for evaluation and understanding of COVID-19. Immune lesion is one of key pathogenesis of the disease. It would be helpful to understand the disease if an investigation on antigenemia and association was conducted in the patients with SARS-CoV-2 infection. Methods: A total of 156 patients admitted to the First People's Hospital of Hefei or Anhui Provincial Hospital on January to February 2020 were involved in this study. SARS-CoV-2 nucleocapsid (NP) antigen, specific IgM/IgG antibodies, and RNA were detected in sequential sera from three COVID-19 patients, and additional 153 COVID-19 patients by means of NP-antigen capture enzyme-linked immunosorbent assay, colloidal gold quick diagnosis, and real-time RT-PCR, respectively. The clinical types of COVID-19 patients were classified into asymptomatic, mild, moderate, severe, and critical, following on the Chinese guideline of COVID-19 diagnosis and treatment. The demographic and clinical data of patients were obtained for comparable analysis. Results: NP antigen was detected in 5 of 20 sequential sera collected from three COVID-19 patients with typically clinical symptoms, and 60.13% (92/153) expanded samples collected within 17 days after illness onset. No SARS-CoV-2 RNA segment was detected in these sera. The NP positive proportion reached a peak (84.85%, 28/33) on 6 to 8 days after illness onset. Both NP concentration and positive proportion were increased with the increase of clinical severity of COVID-19. Compared to NP negative patients, NP positive patients had older age [years, medians (interquartile ranges (IQR)), 49 (6) vs. 31 (11)], lower positive proportion of NP specific IgM [27.17% (25/92) vs. 59.02% (36/61)], and IgG [21.74% (20/92) vs. 59.02% (36/61)] antibodies, and longer duration [days, medians (IQR), 24 (10) vs. 21 (13)] from illness to recovery. Conclusions: SARS-CoV-2 NP antigenemia occurred in COVID-19, and presented highly prevalent at early stage of the disease. The antigenemia was related to clinical severity of the disease, and may be responsible for the delay of detectable SARS-Cov-2 IgM.
| S-EPMC9295937 | biostudies-literature
Project description:The efforts of the scientific community to tame the recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seem to have been diluted by the emergence of new viral strains. Therefore, it is imperative to understand the effect of mutations on viral evolution. We performed a time series analysis on 59,541 SARS-CoV-2 genomic sequences from around the world to gain insights into the kinetics of the mutations arising in the viral genomes. These 59,541 genomes were grouped according to month (January 2020 to March 2021) based on the collection date. Meta-analysis of these data led us to identify significant mutations in viral genomes. Pearson correlation of these mutations led us to the identification of 16 comutations. Among these comutations, some of the individual mutations have been shown to contribute to viral replication and fitness, suggesting a possible role of other unexplored mutations in viral evolution. We observed that the mutations 241C>T in the 5' untranslated region (UTR), 3037C>T in nsp3, 14408C>T in the RNA-dependent RNA polymerase (RdRp), and 23403A>G in spike are correlated with each other and were grouped in a single cluster by hierarchical clustering. These mutations have replaced the wild-type nucleotides in SARS-CoV-2 sequences. Additionally, we employed a suite of computational tools to investigate the effects of T85I (1059C>T), P323L (14408C>T), and Q57H (25563G>T) mutations in nsp2, RdRp, and the ORF3a protein of SARS-CoV-2, respectively. We observed that the mutations T85I and Q57H tend to be deleterious and destabilize the respective wild-type protein, whereas P323L in RdRp tends to be neutral and has a stabilizing effect. IMPORTANCE We performed a meta-analysis on SARS-CoV-2 genomes categorized by collection month and identified several significant mutations. Pearson correlation analysis of these significant mutations identified 16 comutations having absolute correlation coefficients of >0.4 and a frequency of >30% in the genomes used in this study. The correlation results were further validated by another statistical tool called hierarchical clustering, where mutations were grouped in clusters on the basis of their similarity. We identified several positive and negative correlations among comutations in SARS-CoV-2 isolates from around the world which might contribute to viral pathogenesis. The negative correlations among some of the mutations in SARS-CoV-2 identified in this study warrant further investigations. Further analysis of mutations such as T85I in nsp2 and Q57H in ORF3a protein revealed that these mutations tend to destabilize the protein relative to the wild type, whereas P323L in RdRp is neutral and has a stabilizing effect. Thus, we have identified several comutations which can be further characterized to gain insights into SARS-CoV-2 evolution.
| S-EPMC9603882 | biostudies-literature
Project description:Background: Testing of possibly infected individuals remains cornerstone of containing the spread of SARS-CoV-2. Detection dogs could contribute to mass screening. Previous research demonstrated canines' ability to detect SARS-CoV-2-infections but has not investigated if dogs can differentiate between COVID-19 and other virus infections. Methods: Twelve dogs were trained to detect SARS-CoV-2 positive samples. Three test scenarios were performed to evaluate their ability to discriminate SARS-CoV-2-infections from viral infections of a different aetiology. Naso- and oropharyngeal swab samples from individuals and samples from cell culture both infected with one of 15 viruses that may cause COVID-19-like symptoms were presented as distractors in a randomised, double-blind study. Dogs were either trained with SARS-CoV-2 positive saliva samples (test scenario I and II) or with supernatant from cell cultures (test scenario III). Results: When using swab samples from individuals infected with viruses other than SARS-CoV-2 as distractors (test scenario I), dogs detected swab samples from SARS-CoV-2-infected individuals with a mean diagnostic sensitivity of 73.8% (95% CI: 66.0-81.7%) and a specificity of 95.1% (95% CI: 92.6-97.7%). In test scenario II and III cell culture supernatant from cells infected with SARS-CoV-2, cells infected with other coronaviruses and non-infected cells were presented. Dogs achieved mean diagnostic sensitivities of 61.2% (95% CI: 50.7-71.6%, test scenario II) and 75.8% (95% CI: 53.0-98.5%, test scenario III), respectively. The diagnostic specificities were 90.9% (95% CI: 87.3-94.6%, test scenario II) and 90.2% (95% CI: 81.1-99.4%, test scenario III), respectively. Conclusion: In all three test scenarios the mean specificities were above 90% which indicates that dogs can distinguish SARS-CoV-2-infections from other viral infections. However, compared to earlier studies our scent dogs achieved lower diagnostic sensitivities. To deploy COVID-19 detection dogs as a reliable screening method it is therefore mandatory to include a variety of samples from different viral respiratory tract infections in dog training to ensure a successful discrimination process.
| S-EPMC8636992 | biostudies-literature
Project description:Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.
| S-EPMC8193731 | biostudies-literature