Summary: The vast majority of SARS-CoV-2 infections are uncomplicated and do not require hospitalization, but these infections contribute to ongoing transmission. There remains a critical need to identify host immune biomarkers predictive of virologic and clinical outcomes in planning future treatment studies of COVID-19. We recently completed a randomized clinical trial of Pegylated PegIinterferon Lambda for treatment of SARS-CoV-2 infected patients conducted in the Stanford COVID-19 CTRU. Leveraging longitudinal samples and data from this trial, we define early immunebaseline and infection-induced signatures that predict the duration of viral shedding, resolution of symptoms, and immunologic memory.
Overall Design: We recruited 108 subjects between age 18 to 75 who are PCR positive for SARS-CoV-2. The subjects were randomized to receive a single dose of Peginterferon Lambda or placebo at their first visit (day 0). In-person follow-up visits were conducted on Day 1, 3, 5, 7, 10, 14, 21, and 28, with the assessment of symptoms and vitals and collection of oropharyngeal swabs for SARS-CoV-2 testing. To profile the immune response in the COVID-19 patients, we conducted RNA-sequencing assays using blood samples collected at day 0 and day 5 after enrollment.
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Growth Protocol: | - |
Treatment Protocol: | - |
Extract Protocol: | First the samples were treated with Proteinase K, and then some extractions were performed using Quick-RNA MagBead Kit (R2132) on KingFisher. |
Library Construction Protocol: | Libraries were prepared using ZymoSeq RiboFree Total RNA Library Kit (R3000). |
Molecule Type: | rRNA- RNA |
Library Source: | |
Library Layout: | PAIRED |
Library Strand: | Forward; - |
Platform: | ILLUMINA |
Instrument Model: | Illumina NovaSeq 6000 |
Strand-Specific: | Specific; Unspecific |
Data Resource | GEN Sample ID | GEN Dataset ID | Project ID | BioProject ID | Sample ID | Sample Name | BioSample ID | Sample Accession | Experiment Accession | Release Date | Submission Date | Update Date | Species | Race | Ethnicity | Age | Age Unit | Gender | Source Name | Tissue | Cell Type | Cell Subtype | Cell Line | Disease | Disease State | Development Stage | Mutation | Phenotype | Case Detail | Control Detail | Growth Protocol | Treatment Protocol | Extract Protocol | Library Construction Protocol | Molecule Type | Library Layout | Strand-Specific | Library Strand | Spike-In | Strategy | Platform | Instrument Model | Cell Number | Reads Number | Gbases | AvgSpotLen1 | AvgSpotLen2 | Uniq Mapping Rate | Multiple Mapping Rate | Coverage Rate |
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