Determinants of expression of SARS-CoV-2 entry-related genes in upper and lower airways.

Pathogenesis and treatment of chronic pulmonary disease

Determinants of SARS-CoV-2 receptor gene expression in upper and lower airways

The recent outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has led to a worldwide pandemic. One week after initial symptoms develop, a subset of patients progresses to severe disease, with high mortality and limited treatment options. To design novel interventions aimed at preventing spread of the virus and reducing progression to severe disease, detailed knowledge of the cell types and regulating factors driving cellular entry is urgently needed. Here we assess the expression patterns in genes required for COVID-19 entry into cells and replication, and their regulation by genetic, epigenetic and environmental factors, throughout the respiratory tract using samples collected from the upper (nasal) and lower airways (bronchi). Matched samples from the upper and lower airways show a clear increased expression of these genes in the nose compared to the bronchi and parenchyma. Cellular deconvolution indicates a clear association of these genes with the proportion of secretory epithelial cells. Smoking status was found to increase the majority of COVID-19 related genes including ACE2 and TMPRSS2 but only in the lower airways, which was associated with a significant increase in the predicted proportion of goblet cells in bronchial samples of current smokers. Both acute and second hand smoke were found to increase ACE2 expression in the bronchus. Inhaled corticosteroids decrease ACE2 expression in the lower airways. No significant effect of genetics on ACE2 expression was observed, but a strong association of DNA- methylation with ACE2 and TMPRSS2- mRNA expression was identified in the bronchus

Can learning health systems help organisations deliver personalised care?

There is increasing international policy and clinical interest in developing learning health systems and delivering precision medicine, which it is hoped will help reduce variation in the quality and safety of care, improve efficiency, and lead to increasing the personalisation of healthcare. Although reliant on similar policies, informatics tools, and data science and implementation research capabilities, these two major initiatives have thus far largely progressed in parallel. In this opinion piece, we argue that they should be considered as complementary, synergistic initiatives whereby the creation of learning health systems infrastructure can support and catalyse the delivery of precision medicine that maximises the benefits and minimises the risks associated with treatments for individual patients. We illustrate this synergy by considering the example of treatments for asthma, which is now recognised as an umbrella term for a heterogeneous group of related conditions

Comprehensive evaluation of smoking exposures and their interactions on DNA methylation

This is the author accepted manuscript.Data Sharing Statement: Data from the Norwegian Mother, Father and Child Cohort Study and the Medical Birth Registry of Norway used in this study are managed by the national health register holders in Norway (Norwegian Institute of public health) and can be made available to researchers, provided approval from the Regional Committees for Medical and Health Research Ethics (REC), compliance with the EU General Data Protection Regulation (GDPR) and approval from the data owners. The consent given by the participants does not open for storage of data on an individual level in repositories or journals. Researchers who want access to data sets for replication should apply through helsedata.no. Access to data sets requires approval from The Regional Committee for Medical and Health Research Ethics in Norway and an agreement with MoBa. Access to the START data is available upon application to the Norwegian Institute of Public Health (NIPH). An application form in English can be found at the NIPH website (http://www.fhi.no/en/). Questions regarding the START cohort can be directed to Siri Håberg ([email protected]). Access to the ALHS is available upon request through the Agricultural Health Study Executive committee. Interested parties will need to complete a data transfer agreement with NIEHS. Questions about the ALHS can be directed to Stephanie London ([email protected]). According to the terms of consent for GS participants, access to individual-level data (omics and phenotypes) must be reviewed by the GS Access Committee. Applications should be made to [email protected]. Guidance on the Generation Scotland Access Process and Policy can be found here: https://www.ed.ac.uk/generation-scotland/using-resources/access-to-resources Understanding Society data are available through the UK Data Service (https://ukdataservice.ac.uk/). Access to the Biobank-Based Integrative Omics Studies (BIOS) is available upon request. RNA-seq, DNA methylation, sex, age and cell count data can be requested and downloaded from the European Genome-phenome Archive (EGA), accession EGAS00001001077. An application form in English can be found at the BBMRI website: https://www.bbmri.nl/acquisition-use-analyze/biosBackground: Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS). Methods: We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina’s EPIC array for current smoking (2,560 exposed), quit <1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C). Findings: Using false discovery rate (FDR<0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4,025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3,049 and 1,067 druggable targets, including chemotherapy drugs. Interpretation: Many smoking-related methylation sites were identified with Illumina’s EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases.Norwegian Ministry of Health and Care ServicesMinistry of Education and ResearchResearch Council of NorwayNational Institutes of Health, National Institute of Environmental Health SciencesNational Cancer Institut