Project description:Infection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA-Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups.
Project description:To reveal genetic determinants of susceptibility to COVID-19 severity in the population and further explore potential immune-related factors, we performed a genome-wide association study on 284 confirmed COVID-19 patients (cases) and 95 healthy individuals (controls). We compared cases and controls of European (EUR) ancestry and African American (AFR) ancestry separately. To further exploring the linkage between HLA and COVID-19 severity, we applied fine-mapping analysis to dissect the HLA association with mild and severe cases.
Project description:The coronavirus pandemic (COVID-19) is associated with secondary bacterial and fungal infections globally. In India, inappropriate use of glucocorticoids, high prevalence of diabetes mellitus and a conducive environment for fungal growth are considered as the main factors for increased incidence of COVID-19 associated mucormycosis (CAM). Few cases of CAM without steroid abuse and normal blood glucose levels were also reported during the pandemic. This study was designed to explore whether altered immune responses due to severe COVID-19 infection predisposes towards development of mucormycosis. The global transcriptome profiling of monocytes and granulocytic cells derived from CAM, Mucormycosis, COVID-19 and healthy control groups were performed to identify the differentially expressed genes (DEGs) involved in dysregulated host immune response towards respective diseased and healthy conditions.
Project description:Analysis of COVID-19 hospitalized patients, with different kind of symptoms, by human rectal swabs collection and 16S sequencing approach.
Project description:Respiratory viruses such as SARS-CoV-2 are pathogens that can reach pandemic proportions. The early human response to respiratory viruses are in the nasal cavity and nasopharyngeal regions. Defining biomarkers of disease trajectory at the time of a positive test is important for opting for treatment and monitoring decisions. We hypothesize that the nasopharyngeal tRNA profiles can be used to predict symptom severity resulting from SARS-CoV-2 infection. We carried out multiplex small RNA sequencing (MSR-seq) on nasopharyngeal swaps to measure the human tRNA response to SARS-CoV-2 infection. Our result simultaneously measured full-length tRNA abundance, tRNA modifications, and tRNA fragmentation among individuals that went on to develop no/mild or severe symptoms. We identified distinct tRNA signatures that can predict the clinical outcome of SARS-CoV-2 infected individual at the time of a positive test. These results highlight the utility of using host tRNA properties as biomarkers for clinical applications.
Project description:Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit, to identify two clusters that, in spite of no major clinical differences, have different gene expression profiles that reveal different underlying pathogenetic mechanisms and ultimately have different ICU outcome. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding a similar result. These results illustrate the potential of transcriptomic profiles to identify patient endotypes and point to relevant pathogenetic mechanisms in COVID-19.
Project description:Longitudinal cohort: 773 host response genes were profiled in previously vaccinated (n=16) and unvaccinated (n=14) COVID-19+ participants along with 5 healthy uninfected controls across a 2-week observational window Single timepoint cohort: 773 host response genes were profiled in 6 healthy uninfected participants