Expression profiling by high throughput sequencing Other
Summary
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 100 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS) remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, which are a function both of viral load (high vs. low) and transcriptional signatures (splicing isoforms, T-cell receptor expression, cell state regression). These findings reveal a massive disruption of cellular and transcriptional pathways from COVID-19 that can inform subsequent studies on the pathophysiology SARS-CoV-2 as well as other viruses.
Overall design
The molecular mechanisms and clinical manifestations of COVID-19 are still poorly understood, especially in terms of the differences between COVID-19, influenza virus, Acute Respiratory Distress Syndrome (ARDS), and other viral infections. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections (regions of interest, ROIs) with 373 areas of interest (i.e., samples). Note that 1 or more AOIs can be found in a given ROI. The dataset comprises the GeoMx data samples only. Specifically, there are five groups (Covid-19_High, Covid-19_Low, Non-viral [ARDS], Flu, and Normal). The breakdown of Patients, ROIs, and AOIs are as follows: Covid-19_High, 4 patients and 86 AOIs within 86 ROIs; Covid-19_Low, 4 patients and 94 AOIs within 94 ROIs; Non-viral, 3 patients and 67 AOIs within 63 ROIs; Flu, 2 patients and 46 AOIs within 42 ROIs; Normal, 3 patients and 64 AOIs within 60 ROIs. For each AOI (sample), digital spatial profiling was performed using NanoStiring's Cancer Transcriptome Atlas (CTA) with Covid-19 spike-in genes.
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