ABSTRACT
Besides parenchymal changes that have been described extensively in COVID-19, bronchiectasis is also reported but detailed characterization of airway changes is lacking. Hence, we aimed to quantify the number of visible airways and their diameters in end-stage COVID-19 lungs. Explanted right lungs, obtained after lung transplantation (n=2) or autopsy (n=1) (65.3+/-26.7 days after symptom onset), were inflated to total lung capacity, frozen and scanned with whole lung microCT (155 mum). Airways were segmented using Mimics Innovation Suite (Materialise, Belgium) and airway count and diameter were assessed using Neuronstudio. Three discarded donor lungs were used as controls. Number of visible airways increased in COVID-19 lungs compared to controls (fig.1a) potentially caused by airway remodeling and bronchiectasis (fig.1b, red arrows) due to fibrotic rearrangement (fig. 1b). Small airway count (diameter 0-2 mm) in generation (G) 1-11 was lower in COVID-19 patients compared to controls, with a shift of small airways from lower generations (G1-11) to higher generations (G12-27) in COVID-19 patients. Simultaneously, airways with a diameter > 2 mm were increased in all generations in COVID-19 (present until G21 compared to G13 in controls). This study shows that COVID-19 causes a remodeling of the (small) airways, leading to an increase of visible airways and diameter of large and small airways, similar to that seen in idiopathic pulmonary fibrosis due to traction bronchiectasis. (Figure Presented).
ABSTRACT
Rationale: Recent advancements in sequencing technologies have led to a substantial increase in the scale and resolution of transcriptomic data. Despite this progress, accessibility to this data, particularly among those who are coming from non-computational backgrounds is limited. To facilitate improved access and exploration of our single-cell RNA sequencing data, we generated several data sharing, mining and dissemination portals to accompany our idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), and lung endothelial cells (Lung EC) cell atlases. Descriptions and links of each website can be found here: https://medicine.yale.edu/lab/kaminski/research/atlas/. Methods: Each interactive data mining website is coded in the R language using the Shiny package and is hosted by Shinyapps.io. Percell expression data for each website is stored on a MySQL database hosted by Amazon Web Services (AWS). Time-associated website engagement statistics and gene query information is collected for each website using a combination of Google Analytics and a gene search table stored on our MySQL database. User exploration of available data is facilitated through several easy-touse visualization tools available on each website. Results: Website usage statistics since the publication of each website shows that 9,772 unique users from 56 countries and five continents have accessed at least one of the three websites. At the time of writing, 300,748 total queries have been made for 15,627 unique genes across the websites. The top five searched genes for the IPF Cell Atlas are CD14, ACE2, ACTA2, IL11 and MUC5B while for the COPD Cell Atlas they are FAM13A, MIRLET7BHG, HHIP, ISM1 and DDT. Finally, the top searched genes for the Lung Endothelial Cell Atlas are BMPR2, PECAM1, EDNRB, APLNR and PROX1. Of note, interaction with the IPF Cell Atlas increased dramatically at the start of the COVID-19 pandemic, with queries for the ACE2 gene, the putative binding receptor for the SARS-CoV-2 virus, increasing substantially at the pandemic's onset in the United States. Conclusions: Usage statistics, gene query information and feedback from users, both within academia and industry, have shown broad engagement with our websites by individuals across computational and non-computational backgrounds. We envision widespread adoption of web-based portals similar to ours will facilitate novel discoveries within these complex datasets and new scientific collaborations.