Genetic and non-genetic factors affecting the expression of COVID-19 relevant genes in the large airway epithelium

Abstract

Particular host and environmental factors influence susceptibility to severe COVID-19. We analyzed RNA-sequencing data from bronchial epithelial brushings - a relevant tissue for SARS-CoV-2 infection - obtained from three cohorts of uninfected individuals, and investigated how non-genetic and genetic factors affect the regulation of host genes implicated in COVID-19. We found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections. These data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.

Control-theoretic immune tradeoffs explain SARS-CoV-2 virulence and transmission variation

“…α scales linearly with [Cs]. A small fraction of respiratory epithelial cells are susceptible to SARS-CoV-2 when compared to rhinovirus, respiratory syncytial virus, and influenza (18)(19)(20)(21)(22). A small susceptible cell fraction enables large relative variation consistent with reported single-cell data (20, 21) (Figure 2B-C).…”

Diabetes, obesity, metabolism, and SARS-CoV-2 infection: the end of the beginning

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15LO1 dictates glutathione redox changes in asthmatic airway epithelium to worsen type 2 inflammation

“…While awaiting data release via dbGaP, investigators may contact the senior author (Wenzel) of this study or go to the SARP website (46) to access to the data via the ancillary study mechanism for SARP. Count data for the SARP cohort was obtained from Dr. Stephanie Christianson/UCSF and as published recently (47).…”