Single cell sequencing reveals cellular landscape alterations in the airway mucosa of patients with pulmonary long COVID (preprint)

To elucidate the important cellular and molecular drivers of pulmonary long COVID, we generated a single-cell transcriptomic map of the airway mucosa using bronchial brushings from patients with long COVID who reported persistent pulmonary symptoms. Adults with and without long COVID were recruited from the general community in greater Vancouver, Canada. The cohort was divided into those with pulmonary long COVID (PLC), which was defined as persons with new or worsening respiratory symptoms following at least one year from their initial acute SARS-CoV-2 infection (N=9); and control subjects defined as SARS-CoV-2 infected persons whose acute respiratory symptoms had fully resolved or individuals who had not experienced acute COVID-19 (N=9). These participants underwent bronchoscopy from which a single cell suspension was created from bronchial brush samples and then sequenced. A total of 56,906 cells were recovered for the downstream analysis, with 34,840 cells belonging to the PLC group. A dimensionality reduction plot shows a unique cluster of neutrophils in the PLC group (p<.05). Ingenuity Pathway Analysis revealed that neutrophil degranulation pathway was enriched across epithelial cells. Differential gene expression analysis between the PLC and control groups demonstrated upregulation of mucin genes in secretory cell clusters. A single-cell transcriptomic landscape of the small airways shows that the PLC airways harbors a dominant neutrophil cluster and an upregulation in the neutrophil-associated activation signature with increased expression of MUC genes in the secretory cells. Together, they suggest that pulmonary symptoms of long COVID may be driven by chronic small airway inflammation.

Multi-omics highlights ABO plasma protein as a causal risk factor for COVID-19 (preprint)

SARS-CoV-2 is responsible for the coronavirus disease 2019 (COVID-19) and the current health crisis. Despite intensive research efforts, the genes and pathways that contribute to COVID-19 remain poorly understood. We therefore used an integrative genomics (IG) approach to identify candidate genes responsible for COVID-19 and its severity. We used Bayesian colocalization (COLOC) and summary-based Mendelian randomization to combine gene expression quantitative trait loci (eQTLs) from the Lung eQTL (n=1,038) and eQTLGen (n=31,784) studies with published COVID-19 genome-wide association study (GWAS) data from the COVID-19 Host Genetics Initiative. Additionally, we used COLOC to integrate plasma protein quantitative trait loci (pQTL) from the INTERVAL study (n=3,301) with COVID-19-associated loci. Finally, we determined any causal associations between plasma proteins and COVID-19 using multi-variable two-sample Mendelian randomization (MR). We found that the expression of 20 genes in lung and 31 genes in blood was associated with COVID-19. Of these genes, only three (LZTFL1, SLC6A20 and ABO) had been previously linked with COVID-19 in GWAS. The novel loci included genes involved in interferon pathways (IL10RB, IFNAR2 and OAS1). Plasma ABO protein, which is associated with blood type in humans, demonstrated a significant causal relationship with COVID-19 in MR analysis; increased plasma levels were associated with an increased risk of having COVID-19 and risk of severe COVID-19. In summary, our study identified genes associated with COVID-19 that may be prioritized for future investigation. Importantly, this is the first study to demonstrate a causal association between plasma ABO protein and COVID-19.

Inhaled corticosteroids downregulate SARS-CoV-2-related gene expression in COPD: results from a RCT (preprint)

RationaleChronic obstructive pulmonary disease (COPD) is a risk factor for severe COVID-19. Inhaled corticosteroids (ICS) are commonly prescribed for the prevention of acute exacerbations in people with COPD, but their use is associated with increased risk of respiratory infections. The effects of ICS on SARS-CoV-2 susceptibility or COVID-19 severity are currently unknown. ObjectivesTo determine the effects of ICS treatment on the bronchial epithelial cell expression of key SARS-CoV-2-related genes in volunteers with COPD. MethodsWe performed a randomized, open-label, parallel treatment trial of 12 weeks treatment with ICS in combination with long-acting beta-agonist (formoterol/budesonide 12/400 {micro}g twice daily or salmeterol/fluticasone propionate 25/250 {micro}g twice daily), or treatment with LABA only (formoterol 12 {micro}g twice daily), in volunteers with mild to very severe COPD. We obtained bronchial epithelial cell samples via bronchoscopy before and after treatment, and determined transcriptome-wide gene expression by RNA sequencing. Main Results63 volunteers were randomized to receive treatment. Compared to formoterol alone, formoterol/budesonide treatment decreased the expression of the SARS-CoV-2 receptor gene ACE2 and the host cell protease gene ADAM17. These genes were highly co-expressed with innate immune response genes, particularly those of the type I interferon and anti-viral response pathways, which also tended to decrease following ICS treatment. ConclusionsThis is the first randomized controlled trial to show that ICS affect the expression of key SARS-CoV-2-related genes in COPD. Their relation to important anti-viral response genes may have critical implications for SARS-CoV-2 susceptibility or COVID-19 severity in this vulnerable population.

Gene Expression Network Analysis Provides Potential Targets Against SARS-CoV-2 (preprint)

ABSTRACTBACKGROUND Cell entry of SARS-CoV-2, the novel coronavirus causing COVID-19, is facilitated by host cell angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). We aimed to identify and characterize genes that are co-expressed with ACE2 and TMPRSS2, and to further explore their biological functions and potential as druggable targets.METHODS Using the gene expression profiles of 1,038 lung tissue samples, we performed a weighted gene correlation network analysis (WGCNA) to identify modules of co-expressed genes. We explored the biology of co-expressed genes using bioinformatics databases, and identified known drug-gene interactions.RESULTS ACE2 was in a module of 681 co-expressed genes; 12 genes with moderate-high correlation with ACE2 (r>0.3, FDR<0.05) had known interactions with existing drug compounds. TMPRSS2 was in a module of 1,086 co-expressed genes; 15 of these genes were enriched in the gene ontology biologic process ‘Entry into host cell’, and 53 TMPRSS2-correlated genes had known interactions with drug compounds.CONCLUSION Dozens of genes are co-expressed with ACE2 and TMPRSS2, many of which have plausible links to COVID-19 pathophysiology. Many of the co-expressed genes are potentially targetable with existing drugs, which may help to fast-track the development of COVID-19 therapeutics.Competing Interest StatementS.M. reports personal fees from Novartis and Boehringer-Ingelheim, outside the submitted work. W.T. reports fees to Institution from Roche-Ventana, AbbVie, Merck-Sharp-Dohme and Bristol-Myers-Squibb, outside the submitted work. M.B. reports research grants paid to University from Astra Zeneca, Novartis, outside the submitted work. D.D.S. reports research funding from AstraZeneca and received honoraria for speaking engagements from Boehringer Ingelheim and AstraZeneca over the past 36 months, outside of the submitted work.View Full Text