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1.
J Infect Dis ; 227(3): 371-380, 2023 02 01.
Artículo en Inglés | MEDLINE | ID: mdl-36314635

RESUMEN

BACKGROUND: Evaluating the performance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serological assays and clearly articulating the utility of selected antigens, isotypes, and thresholds is crucial to understanding the prevalence of infection within selected communities. METHODS: This cross-sectional study, implemented in 2020, screened PCRconfirmed coronavirus disease 2019 patients (n 86), banked prepandemic and negative samples (n 96), healthcare workers and family members (n 552), and university employees (n 327) for antiSARS-CoV-2 receptor-binding domain, trimeric spike protein, and nucleocapsid protein immunoglobulin (Ig)G and IgA antibodies with a laboratory-developed enzyme-linked immunosorbent assay and tested how antigen, isotype and threshold choices affected the seroprevalence outcomes. The following threshold methods were evaluated: (i) mean 3 standard deviations of the negative controls; (ii) 100 specificity for each antigen-isotype combination; and (iii) the maximal Youden index. RESULTS: We found vastly different seroprevalence estimates depending on selected antigens and isotypes and the applied threshold method, ranging from 0.0 to 85.4. Subsequently, we maximized specificity and reported a seroprevalence, based on more than one antigen, ranging from 9.3 to 25.9. CONCLUSIONS: This study revealed the importance of evaluating serosurvey tools for antigen-, isotype-, and threshold-specific sensitivity and specificity, to interpret qualitative serosurvey outcomes reliably and consistently across studies.


Asunto(s)
COVID-19 , SARS-CoV-2 , Humanos , COVID-19/epidemiología , Estudios Seroepidemiológicos , Estudios Transversales , Proteínas de la Nucleocápside , Ensayo de Inmunoadsorción Enzimática/métodos , Sensibilidad y Especificidad , Inmunoglobulina G , Anticuerpos Antivirales , Glicoproteína de la Espiga del Coronavirus
2.
medRxiv ; 2022 Feb 28.
Artículo en Inglés | MEDLINE | ID: mdl-35262096

RESUMEN

The clinical course of infection due to respiratory viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), the causative agent of Coronavirus Disease 2019 (COVID-19) is thought to be influenced by the community of organisms that colonizes the upper respiratory tract, the oropharyngeal microbiome. In this study, we examined the oropharyngeal microbiome of suspected COVID-19 patients presenting to the Emergency Department and an inpatient COVID-19 unit with symptoms of acute COVID-19. Of 115 enrolled patients, 74 were confirmed COVID-19+ and 50 had symptom duration of 14 days or less; 38 acute COVID-19+ patients (76%) went on to require respiratory support. Although no microbiome features were found to be significantly different between COVID-19+ and COVID-19-patients, when we conducted random forest classification modeling (RFC) to predict the need of respiratory support for the COVID-19+ patients our analysis identified a subset of organisms and metabolic pathways whose relative abundance, when combined with clinical factors (such as age and Body Mass Index), was highly predictive of the need for respiratory support (F1 score 0.857). Microbiome Multivariable Association with Linear Models (MaAsLin2) analysis was then applied to the features identified as predicative of the need for respiratory support by the RFC. This analysis revealed reduced abundance of Prevotella salivae and metabolic pathways associated with lipopolysaccharide and mycolic acid biosynthesis to be the strongest predictors of patients requiring respiratory support. These findings suggest that composition of the oropharyngeal microbiome in COVID-19 may play a role in determining who will suffer from severe disease manifestations. Importance: The microbial community that colonizes the upper airway, the oropharyngeal microbiome, has the potential to affect how patients respond to respiratory viruses such as SARS-CoV2, the causative agent of COVID-19. In this study, we investigated the oropharyngeal microbiome of COVID-19 patients using high throughput DNA sequencing performed on oral swabs. We combined patient characteristics available at intake such as medical comorbidities and age, with measured abundance of bacterial species and metabolic pathways and then trained a machine learning model to determine what features are predicative of patients needing respiratory support in the form of supplemental oxygen or mechanical ventilation. We found that decreased abundance of some bacterial species and increased abundance of pathways associated bacterial products biosynthesis was highly predictive of needing respiratory support. This suggests that the oropharyngeal microbiome affects disease course in COVID-19 and could be targeted for diagnostic purposes to determine who may need oxygen, or therapeutic purposes such as probiotics to prevent severe COVID-19 disease manifestations.

3.
Front Microbiol ; 13: 1009440, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36246273

RESUMEN

The oropharyngeal microbiome, the collective genomes of the community of microorganisms that colonizes the upper respiratory tract, is thought to influence the clinical course of infection by respiratory viruses, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus Infectious Disease 2019 (COVID-19). In this study, we examined the oropharyngeal microbiome of suspected COVID-19 patients presenting to the Emergency Department and an inpatient COVID-19 unit with symptoms of acute COVID-19. Of 115 initially enrolled patients, 50 had positive molecular testing for COVID-19+ and had symptom duration of 14 days or less. These patients were analyzed further as progression of disease could most likely be attributed to acute COVID-19 and less likely a secondary process. Of these, 38 (76%) went on to require some form of supplemental oxygen support. To identify functional patterns associated with respiratory illness requiring respiratory support, we applied an interpretable random forest classification machine learning pipeline to shotgun metagenomic sequencing data and select clinical covariates. When combined with clinical factors, both species and metabolic pathways abundance-based models were found to be highly predictive of the need for respiratory support (F1-score 0.857 for microbes and 0.821 for functional pathways). To determine biologically meaningful and highly predictive signals in the microbiome, we applied the Stable and Interpretable RUle Set to the output of the models. This analysis revealed that low abundance of two commensal organisms, Prevotella salivae or Veillonella infantium (< 4.2 and 1.7% respectively), and a low abundance of a pathway associated with LPS biosynthesis (< 0.1%) were highly predictive of developing the need for acute respiratory support (82 and 91.4% respectively). These findings suggest that the composition of the oropharyngeal microbiome in COVID-19 patients may play a role in determining who will suffer from severe disease manifestations.

4.
JCI Insight ; 6(20)2021 10 22.
Artículo en Inglés | MEDLINE | ID: mdl-34403368

RESUMEN

In the COVID-19 pandemic, caused by SARS-CoV-2, many individuals experience prolonged symptoms, termed long-lasting COVID-19 symptoms (long COVID). Long COVID is thought to be linked to immune dysregulation due to harmful inflammation, with the exact causes being unknown. Given the role of the microbiome in mediating inflammation, we aimed to examine the relationship between the oral microbiome and the duration of long COVID symptoms. Tongue swabs were collected from patients presenting with COVID-19 symptoms. Confirmed infections were followed until resolution of all symptoms. Bacterial composition was determined by metagenomic sequencing. We used random forest modeling to identify microbiota and clinical covariates that are associated with long COVID symptoms. Of the patients followed, 63% developed ongoing symptomatic COVID-19 and 37% went on to long COVID. Patients with prolonged symptoms had significantly higher abundances of microbiota that induced inflammation, such as members of the genera Prevotella and Veillonella, which, of note, are species that produce LPS. The oral microbiome of patients with long COVID was similar to that of patients with chronic fatigue syndrome. Altogether, our findings suggest an association with the oral microbiome and long COVID, revealing the possibility that dysfunction of the oral microbiome may have contributed to this draining disease.


Asunto(s)
COVID-19/complicaciones , Disbiosis , Inflamación , Microbiota , Anciano , Bacterias/clasificación , Femenino , Microbioma Gastrointestinal , Humanos , Masculino , Persona de Mediana Edad , SARS-CoV-2 , Síndrome Post Agudo de COVID-19
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