Molecular Profiling of Coronavirus Disease 2019 (COVID-19) Autopsies Uncovers Novel Disease Mechanisms

Current understanding of coronavirus disease 2019 (COVID-19) pathophysiology is limited by disease heterogeneity, complexity, and a paucity of studies assessing patient tissues with advanced molecular tools. Rapid autopsy tissues were evaluated using multiscale, next-generation RNA-sequencing methods (bulk, single-nuclei, and spatial transcriptomics) to provide unprecedented molecular resolution of COVID-19-induced damage. 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 receptor-like receptor, or decorin. Single-nuclei RNA sequencing of olfactory bulb and prefrontal cortex highlighted remarkable diversity of coronavirus receptors. Angiotensin-converting enzyme 2 was rarely expressed, whereas basigin showed diffuse expression, and alanyl aminopeptidase, membrane, was associated with vascular/mesenchymal cell types. Comparison of lung and lymph node tissues from patients with different symptoms (one had died after a month-long hospitalization with multiorgan involvement, and the other had died after a few days of respiratory symptoms) with digital spatial profiling resulted in distinct molecular phenotypes. Evaluation of COVID-19 rapid autopsy tissues with advanced molecular techniques can identify pathways and effectors, map diverse receptors at the single-cell level, and help dissect differences driving diverging clinical courses among individual patients. Extension of this approach to larger data sets will substantially advance the understanding of the mechanisms behind COVID-19 pathophysiology.

Automated summary

The study utilized advanced molecular techniques to identify different regulatory pathways and effectors in COVID-19 rapid autopsy tissues, revealing diverse expression patterns of virus receptors. Digital spatial profiling could distinguish different disease phenotypes. These findings contribute to a better understanding of the pathophysiology of COVID-19.