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- Sikkema, Lisa, et al.
(författare)
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An integrated cell atlas of the lung in health and disease
- 2023
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Ingår i: Nature Medicine. - : Springer Nature. - 1078-8956 .- 1546-170X. ; 29:6, s. 1563-1577
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Ngassie, Maunick Lefin Koloko, et al.
(författare)
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Age-associated differences in the human lung extracellular matrix
- 2023
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Ingår i: American Journal of Physiology - Lung Cellular and Molecular Physiology. - 1040-0605. ; 324:5, s. 799-814
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Tidskriftsartikel (refereegranskat)abstract
- Extracellular matrix (ECM) remodeling has been associated with chronic lung diseases. However, information about specific age-associated differences in lung ECM is currently limited. In this study, we aimed to identify and localize age-associated ECM differences in human lungs using comprehensive transcriptomic, proteomic, and immunohistochemical analyses. Our previously identified age-associated gene expression signature of the lung was re-analyzed limiting it to an aging signature based on 270 control patients (37–80 years) and focused on the Matrisome core geneset using geneset enrichment analysis. To validate the age-associated transcriptomic differences on protein level, we compared the age-associated ECM genes (false discovery rate, FDR < 0.05) with a profile of age-associated proteins identified from a lung tissue proteomics dataset from nine control patients (49–76 years) (FDR < 0.05). Extensive immunohistochemical analysis was used to localize and semi-quantify the age-associated ECM differences in lung tissues from 62 control patients (18–82 years). Comparative analysis of transcriptomic and proteomic data identified seven ECM proteins with higher expression with age at both gene and protein levels: COL1A1, COL6A1, COL6A2, COL14A1, FBLN2, LTBP4, and LUM. With immunohistochemistry, we demonstrated higher protein levels with age for COL6A2 in whole tissue, parenchyma, airway wall, and blood vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in lung parenchyma. Our study revealed that higher age is associated with lung ECM remodeling, with specific differences occurring in defined regions within the lung. These differences may affect lung structure and physiology with aging and as such may increase susceptibility to developing chronic lung diseases.
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