Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
1.
Sci Rep ; 12(1): 889, 2022 01 18.
Article in English | MEDLINE | ID: covidwho-1630723

ABSTRACT

Predicting the severity of COVID-19 remains an unmet medical need. Our objective was to develop a blood-based host-gene-expression classifier for the severity of viral infections and validate it in independent data, including COVID-19. We developed a logistic regression-based classifier for the severity of viral infections and validated it in multiple viral infection settings including COVID-19. We used training data (N = 705) from 21 retrospective transcriptomic clinical studies of influenza and other viral illnesses looking at a preselected panel of host immune response messenger RNAs. We selected 6 host RNAs and trained logistic regression classifier with a cross-validation area under curve of 0.90 for predicting 30-day mortality in viral illnesses. Next, in 1417 samples across 21 independent retrospective cohorts the locked 6-RNA classifier had an area under curve of 0.94 for discriminating patients with severe vs. non-severe infection. Next, in independent cohorts of prospectively (N = 97) and retrospectively (N = 100) enrolled patients with confirmed COVID-19, the classifier had an area under curve of 0.89 and 0.87, respectively, for identifying patients with severe respiratory failure or 30-day mortality. Finally, we developed a loop-mediated isothermal gene expression assay for the 6-messenger-RNA panel to facilitate implementation as a rapid assay. With further study, the classifier could assist in the risk assessment of COVID-19 and other acute viral infections patients to determine severity and level of care, thereby improving patient management and reducing healthcare burden.


Subject(s)
COVID-19 , Gene Expression Regulation , RNA, Messenger/blood , SARS-CoV-2/metabolism , Acute Disease , COVID-19/blood , COVID-19/mortality , Female , Humans , Male , Middle Aged , Predictive Value of Tests , Retrospective Studies
2.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296942

ABSTRACT

Knowledge of the factors contributing to the development of protective immunity after vaccination with COVID-19 mRNA vaccines is fragmentary. Thus we employed high-temporal-resolution transcriptome profiling and in-depth characterization of antibody production approaches to investigate responses to COVID-19 mRNA vaccination. There were marked differences in the timing and amplitude of the responses to the priming and booster doses. Notably, two distinct interferon signatures were identified, that differed based on their temporal patterns of induction. The first signature (S1), which was preferentially induced by type I interferon, peaked at day 2 post-prime and at day 1 post-boost, and in both instances was associated with subsequent development of the antibody response. In contrast, the second interferon signature (S2) peaked at day 1 both post-prime and post-boost but was found to be potently induced only post-boost, where it coincided with a robust inflammation peak. Notably, we also observed post-prime-like (S1++,S20/+) and post-boost-like (S1++,S2++) patterns of interferon response among COVID-19 patients. A post-boost-like signature was observed in most severely ill patients at admission to the intensive care unit and was associated with a shorter hospital stay. Interestingly, severely ill patients who stayed hospitalized the longest showed a peculiar pattern of interferon induction (S1-/0,S2+), that we did not observe following the administration of mRNA vaccines. In summary, high temporal resolution profiling revealed an elaborate array of immune responses elicited by priming and booster doses of COVID-19 mRNA vaccines. Furthermore, it contributed to the identification of distinct interferon-response phenotypes underpinning vaccine immunogenicity and the course of COVID-19 disease.

3.
BMJ Open ; 11(1): e044497, 2021 01 06.
Article in English | MEDLINE | ID: covidwho-1013055

ABSTRACT

INTRODUCTION: Accurate triage is an important first step to effectively manage the clinical treatment of severe cases in a pandemic outbreak. In the current COVID-19 global pandemic, there is a lack of reliable clinical tools to assist clinicians to perform accurate triage. Host response biomarkers have recently shown promise in risk stratification of disease progression; however, the role of these biomarkers in predicting disease progression in patients with COVID-19 is unknown. Here, we present a protocol outlining a prospective validation study to evaluate the biomarkers' performance in predicting clinical outcomes of patients with COVID-19. METHODS AND ANALYSIS: This prospective validation study assesses patients infected with COVID-19, in whom blood samples are prospectively collected. Recruited patients include a range of infection severity from asymptomatic to critically ill patients, recruited from the community, outpatient clinics, emergency departments and hospitals. Study samples consist of peripheral blood samples collected into RNA-preserving (PAXgene/Tempus) tubes on patient presentation or immediately on study enrolment. Real-time PCR (RT-PCR) will be performed on total RNA extracted from collected blood samples using primers specific to host response gene expression biomarkers that have been previously identified in studies of respiratory viral infections. The RT-PCR data will be analysed to assess the diagnostic performance of individual biomarkers in predicting COVID-19-related outcomes, such as viral pneumonia, acute respiratory distress syndrome or bacterial pneumonia. Biomarker performance will be evaluated using sensitivity, specificity, positive and negative predictive values, likelihood ratios and area under the receiver operating characteristic curve. ETHICS AND DISSEMINATION: This research protocol aims to study the host response gene expression biomarkers in severe respiratory viral infections with a pandemic potential (COVID-19). It has been approved by the local ethics committee with approval number 2020/ETH00886. The results of this project will be disseminated in international peer-reviewed scientific journals.


Subject(s)
Biomarkers/metabolism , COVID-19/metabolism , Critical Illness/epidemiology , Emergency Service, Hospital/statistics & numerical data , Pandemics , SARS-CoV-2 , Triage/methods , Adult , COVID-19/epidemiology , Female , Follow-Up Studies , Humans , Male , Middle Aged , Prognosis , Prospective Studies , Time Factors
SELECTION OF CITATIONS
SEARCH DETAIL