An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1 + profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas. </p

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP

An integrated cell atlas of the lung in health and disease

Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1+ profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas

Muslim Communities learning about second-hand smoke in Bangladesh (MCLASS II): study protocol for a cluster randomised controlled trial of a community-based smoke-free homes intervention, with or without Indoor Air Quality feedback

Background Second-hand smoke (SHS) is a serious health hazard costing 890,000 lives a year globally. Women and children in many economically developing countries are worst affected as smoke-free laws are only partially implemented and homes remain a major source of SHS exposure. There is limited evidence on interventions designed to reduce SHS exposure in homes, especially in community settings. Following a successful pilot, a community-based approach to promote smoke-free homes in Bangladesh, a country with a strong commitment to smoke-free environments but with high levels of SHS exposure, will be evaluated. The study aims to assess the effectiveness and cost-effectiveness of a community-based intervention, Muslims for better Health (M4bH), with or without Indoor Air Quality (IAQ) feedback, in reducing non-smokers’ exposure to SHS in the home. Methods/design Based on behaviour-change theories, M4bH and IAQ feedback are designed to discourage people from smoking indoors. M4bH consists of a set of messages couched within mainstream Islamic discourse, delivered weekly by faith leaders (imams and khatibs) in mosques over 12 weeks (one message each week). The messages address key determinants of current smoking behaviours including lack of knowledge and misconceptions on specific harms associated with SHS exposure. IAQ feedback consists of personalised information on IAQ measured by a particulate matter (PM2.5) monitor within the home. Following adaptation of M4bH and IAQ feedback for the Bangladeshi context, a three-arm cluster randomised controlled trial will be conducted in Dhaka. Forty-five mosques and 1800 households, with at least one smoker and one non-smoker, will be recruited. Mosques will be randomised to: M4bH and IAQ feedback; M4bH alone; or usual services only. The primary outcome is 24-h mean household concentration of indoor fine particulate matter (PM2.5) at 12 months post randomisation. Secondary outcomes are 24-h mean household PM2.5 at 3 months post randomisation, frequency and severity of respiratory symptoms, health care service use and quality of life. A cost-effectiveness analysis and process evaluation will also be conducted. Discussion The MCLASS II trial will test the potential of a community-based intervention to reduce second-hand smoke exposure at home and improve lung health among non-smokers in Bangladesh and beyond

Experiences of lifestyle change among women with gestational diabetes mellitus (GDM): A behavioural diagnosis using the COM-B model in a low-income setting

Lifestyle change can reduce the risk of developing type 2 diabetes among women with prior gestational diabetes mellitus (GDM). While understanding women’s lived experiences and views around GDM is critical to the development of behaviour change interventions to reduce this risk, few studies have addressed this issue in low- and middle- income countries. The aim of the study was to explore women’s lived experiences of GDM and the feasibility of sustained lifestyle modification after GDM in a low-income setting