Molecular Profiling of COVID-19 Autopsies Uncovers Novel Disease Mechanisms
Posted 07 Apr 2021
medRxiv DOI: 10.1101/2021.04.04.21253205
Posted 07 Apr 2021
Background: Current understanding of COVID-19 pathophysiology is limited by disease heterogeneity, complexity, and a paucity of studies evaluating patient tissues with advanced molecular tools. Methods: Autopsy tissues from two COVID-19 patients, one of whom died after a month-long hospitalization with multi-organ involvement while the other died after a few days of respiratory symptoms, were evaluated using multi-scale RNASeq methods (bulk, single-nuclei, and spatial RNASeq next-generation sequencing) to provide unprecedented molecular resolution of COVID-19 induced damage. Findings: Comparison of infected/uninfected tissues revealed four major regulatory pathways. Effectors within these pathways could constitute novel therapeutic targets, including the complement receptor C3AR1, calcitonin-like receptor or decorin. Single-nuclei RNA sequencing of olfactory bulb and prefrontal cortex highlighted remarkable diversity of coronavirus receptors. Angiotensin I converting enzyme 2 was rarely expressed, while Basignin showed diffuse expression, and alanyl aminopeptidase was associated with vascular/mesenchymal cell types. Comparison of lung and lymph node tissues from patients with different symptomatology with Digital Spatial Profiling resulted in distinct molecular phenotypes. Interpretation: COVID-19 is a far more complex and heterogeneous disease than initially anticipated. Evaluation of COVID-19 rapid autopsy tissues with advanced molecular techniques can identify pathways and effectors at play in individual patients, measure the staggering diversity of receptors in specific brain areas and other well-defined tissue compartments at the single-cell level, and help dissect differences driving diverging clinical courses among patients. Extension of this approach to larger datasets will substantially advance the understanding of the mechanisms behind COVID-19 pathophysiology. Funding: No external funding was used in this study.
- Downloaded 449 times
- Download rankings, all-time:
- Site-wide: 68,980
- In pathology: 328
- Year to date:
- Site-wide: 10,242
- Since beginning of last month:
- Site-wide: 3,987
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!