SARS-CoV-2 Viral Load Predicts Mortality in Patients with and without Cancer Who Are Hospitalized with COVID-19.
Ontology highlight
ABSTRACT:
SUBMITTER: Westblade LF
PROVIDER: S-EPMC7492074 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description: Not available
| S-EPMC7836878 | biostudies-literature
Project description:BackgroundThe interdependencies of viral replication and the host immune response in patients with coronavirus disease 2019 (COVID-19) remain to be defined. We investigated the viral determinants of antibody response, the predictors of nonseroconversion, and the role of antibodies on viral dynamics.MethodsThis was a prospective study in patients hospitalized with COVID-19 that was microbiologically confirmed by real-time polymerase chain reaction (RT-PCR). Serial nasopharyngeal and oropharyngeal swabs and plasma samples were obtained for measuring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA and antibodies (total and S-IgG/N-IgG), respectively.ResultsOf 132 patients included, 99 (75%) showed positive antibody titers after a median (Q1-Q3) of 11 (8-14) days. The median (Q1-Q3) follow-up was 74.5 (63.0-87.0) days. In an adjusted linear regression model, time to seropositivity was inversely associated with peak log SARS-CoV-2 viral load (P = .009) and positively with time to viral clearance (P = .004). Adjusted predictors of S-IgG levels were time to viral clearance (P < .001), bilateral lung infiltrates on admission (P = .011), and the time-dependent SARS-CoV-2 RNA (P < .001) and SARS-CoV-2 RNA area under the curve (P = .001). Thirty-three (25%) patients showed undetectable antibody titers. Patients who did not seroconvert had higher cycle threshold values of RT-PCR (38.0 vs 28.0; P < .001), had shorter time to viral clearance (3.0 vs 41.0; P < .001), and were more likely to have SARS-CoV-2 only detected on fecal samples (P < .001). Nonseroconvertors had also lower levels of blood inflammatory biomarkers on admission and lower disease severity.ConclusionsViral replication determines the magnitude of antibody response to SARS-CoV-2, which, in turn, contributes to viral clearance. COVID-19 patients who do not seroconvert exhibit a differential virological and clinical profile.
| S-EPMC7881755 | biostudies-literature
Project description:ACE2 on epithelial cells is the SARS-CoV-2 entry receptor. Single-cell RNA-sequencing data derived from two COVID-19 cohorts revealed that MAP4K3/GLK-positive epithelial cells were increased in patients. SARS-CoV-2-induced GLK overexpression in epithelial cells correlated with COVID-19 severity and vesicle secretion. GLK overexpression induced the epithelial cell-derived exosomes containing ACE2; the GLK-induced exosomes transported ACE2 proteins to recipient cells, facilitating pseudovirus infection. Consistently, ACE2 proteins were increased in the serum exosomes from another COVID-19 cohort. Remarkably, SARS-CoV-2 spike protein stimulated GLK, and GLK stabilized ACE2 in epithelial cells. Mechanistically, GLK phosphorylated ACE2 at two serine residues (Ser776, Ser783), leading to dissociation of ACE2 from its E3 ligase UBR4. Reduction of UBR4-induced Lys48-linked ubiquitination at three lysine residues (Lys26, Lys112, Lys114) of ACE2 prevented its degradation. Furthermore, SARS-CoV-2 pseudovirus or live virus infection in humanized ACE2 mice induced GLK and ACE2 protein levels, as well as ACE2-containing exosomes. Collectively, ACE2 stabilization by SARS-CoV-2-induced MAP4K3/GLK may contribute to the pathogenesis of COVID-19.
| S-SCDT-EMM-2022-15904 | biostudies-other
Project description:BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA loads in patient specimens may act as a clinical outcome predictor in critically ill patients with coronavirus disease 2019 (COVID-19).MethodsWe evaluated the predictive value of viral RNA loads and courses in the blood compared with the upper and lower respiratory tract loads of critically ill COVID-19 patients. Daily specimen collection and viral RNA quantification by reverse transcription quantitative polymerase chain reaction were performed in all consecutive 170 COVID-19 patients between March 2020 and February 2021 during the entire intensive care unit (ICU) stay (4145 samples analyzed). Patients were grouped according to their 90-day outcome as survivors (n=100) or nonsurvivors (n=70).ResultsIn nonsurvivors, blood SARS-CoV-2 RNA loads were significantly higher at the time of admission to the ICU (P=.0009). Failure of blood RNA clearance was observed in 33/50 (66%) of the nonsurvivors compared with 12/64 (19%) survivors (P<.0001). As determined by multivariate analysis, taking sociodemographic and clinical parameters into account, blood SARS-CoV-2 RNA load represents a valid and independent predictor of outcome in critically ill COVID-19 patients (odds ratio [OR; log10], 0.23; 95% CI, 0.12-0.42; P<.0001), with a significantly higher effect for survival compared with respiratory tract SARS-CoV-2 RNA loads (OR [log10], 0.75; 95% CI, 0.66-0.85; P<.0001). Blood RNA loads exceeding 2.51×103 SARS-CoV-2 RNA copies/mL were found to indicate a 50% probability of death. Consistently, 29/33 (88%) nonsurvivors with failure of virus clearance exceeded this cutoff value constantly.ConclusionsBlood SARS-CoV-2 load is an important independent outcome predictor and should be further evaluated for treatment allocation and patient monitoring.
| S-EPMC8522363 | biostudies-literature
Project description:Understanding viral load in patients infected with SARS-CoV-2 is critical to epidemiology and infection control. Previous studies have demonstrated that SARS-CoV-2 RNA can be detected for many weeks after symptom onset. The clinical significance of this finding is unclear and, in most patients, likely does not represent active infection. There are, however, patients who shed infectious virus for weeks. Detection of subgenomic RNA transcripts expressed by SARS-CoV-2 has been proposed to represent productive infection and may be a tractable marker for monitoring infectivity. Here, we use RT-PCR to quantify total and subgenomic nucleocapsid (N) and envelope (E) transcripts in 190 SARS-CoV-2 positive samples collected on hospital admission. We relate these findings to duration of symptoms. We find that all transcripts decline at the same rate; however, subgenomic E becomes undetectable before other transcripts. In Kaplan-Meier analysis the median duration of symptoms to a negative test is 14 days for sgE and 25 days for sgN. There is a linear decline in subgenomic RNA compared to total RNA suggesting subgenomic transcript copy number is highly dependent on copy number of total transcripts. The mean difference between total N and subgenomic N is 16-fold (4.0 cycles) and the mean difference between total E and sub-genomic E is 137-fold (7.1 cycles). This relationship is constant over duration of symptoms allowing prediction of subgenomic copy number from total copy number. Although Subgenomic E is undetectable at a time that may more closely reflect the duration of infectivity, its utility in determining active infection may be no more useful than a copy number threshold determined for total transcripts.
| S-EPMC7941648 | biostudies-literature
Project description:There are still conflicting data on the virological effects of the SARS-CoV-2 direct antivirals used in clinical practice, in spite of the documented clinical efficacy. The aim of this monocentric retrospective study was to compare virologic and laboratory data of patients admitted due to SARS-CoV-2 infection from March to December 2020 treated with either remdesivir (R), a protease inhibitor (lopinavir or darunavir/ritonavir (PI)) or no direct antiviral drugs (NT). Viral load variation was indirectly assessed through PCR cycle threshold (Ct) values on the nasopharyngeal swab, analyzing the results from swabs obtained at ward admission and 7 (±2) days later. Overall, 253 patients were included: patients in the R group were significantly older, more frequently males with a significantly higher percentage of severe COVID-19, requiring more often intensive care admission, compared to the other groups. Ct variation over time did not differ amongst the three treatment groups and did not seem to be influenced by corticosteroid use, even after normalization of the treatment groups for disease severity. Non-survivors had lower Ct on admission and showed a significantly slower viral clearance compared to survivors. CD4 T-lymphocytes absolute count assessed at ward admission correlated with a reduced Ct variation over time. In conclusion, viral clearance appears to be slower in COVID-19 non-survivors, while it seems not to be influenced by the antiviral treatment received.
| S-EPMC9959460 | biostudies-literature
Project description:Bacterial-viral interactions in saliva have been associated with morbidity and mortality for respiratory viruses such as influenza and SARS-CoV. However, such transkingdom relationships during SARS-CoV-2 infection are currently unknown. Here, we aimed to elucidate the relationship between saliva microbiota and SARS-CoV-2 in a cohort of newly hospitalized COVID-19 patients and controls. We used 16S rRNA sequencing to compare microbiome diversity and taxonomic composition between COVID-19 patients (n = 53) and controls (n = 59) and based on saliva SARS-CoV-2 viral load as measured using reverse transcription PCR (RT-PCR). The saliva microbiome did not differ markedly between COVID-19 patients and controls. However, we identified significant differential abundance of numerous taxa based on saliva SARS-CoV-2 viral load, including multiple species within Streptococcus and Prevotella. IMPORTANCE Alterations to the saliva microbiome based on SARS-CoV-2 viral load indicate potential biologically relevant bacterial-viral relationships which may affect clinical outcomes in COVID-19 disease.
| S-EPMC8515944 | biostudies-literature
Project description:There remains an urgent need to delinate immune cell states that contribute to mortality in critially ill COVID-19 patients. To better understand determinants of mortality, we performed high dimensional profiling of blood and respiratory samples from critially ill COVID-19 patients. Single-cell RNAseq based characterization of peripheral immune states reveal distinct expression profiles that were predictive of COVID-19 mortality. Temporal analysis revealed a that persistently elevated levels of inflammatory monocyte signatures and persistent interferon signaling preceeded concerted upregulation of inflammatory cytokines. Interrogation of lower respiratory tract saples revelaed that infected myeliod cells upregulated CXCL10, and elevated levels of CXCL10 in plasma were associated with a high risk of death. Overall, our data suggest a pivotal role for myeloid cell states in severe COVID-19 and may faciliate discovery of new diagnostics and therapeutics.
2021-12-08 | GSE180578 | GEO
Project description:The COVID-19 epidemic of 2019-20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline clinical characteristics of patients and their outcome data including their hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 infections was observed (p = 0.06, Fisher's exact). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. In summary, SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.
| S-EPMC7910290 | biostudies-literature
Project description:We developed three different protein arrays to measure IgG autoantibodies associated with Connective Tissue Diseases (CTDs), Anti-Cytokine Antibodies (ACA), and anti-viral antibody responses in 147 hospitalized COVID-19 patients in three different centers.
2021-07-24 | GSE180742 | GEO