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.
Citation
@article{sikkema2023,
author = {Sikkema, Lisa and Ramírez-Suástegui, Ciro and C. Strobl,
Daniel and E. Gillett, Tessa and Zappia, Luke and Madissoon, Elo and
S. Markov, Nikolay and Zaragosi, Laure-Emmanuelle and Ji, Yuge and
Ansari, Meshal and Arguel, Marie-Jeanne and Apperloo, Leonie and
Banchero, Martin and Bécavin, Christophe and Berg, Marijn and
Chichelnitskiy, Evgeny and Chung, Mei-i and Collin, Antoine and C.
A. Gay, Aurore and Gote-Schniering, Janine and Hooshiar Kashani,
Baharak and Inecik, Kemal and Jain, Manu and S. Kapellos, Theodore
and M. Kole, Tessa and Leroy, Sylvie and H. Mayr, Christoph and J.
Oliver, Amanda and von Papen, Michael and Peter, Lance and J.
Taylor, Chase and Walzthoeni, Thomas and Xu, Chuan and T. Bui, Linh
and De Donno, Carlo and Dony, Leander and Faiz, Alen and Guo, Minzhe
and J. Gutierrez, Austin and Heumos, Lukas and Huang, Ni and L.
Ibarra, Ignacio and D. Jackson, Nathan and Kadur Lakshminarasimha
Murthy, Preetish and Lotfollahi, Mohammad and Tabib, Tracy and
Talavera-López, Carlos and J. Travaglini, Kyle and Wilbrey-Clark,
Anna and B. Worlock, Kaylee and Yoshida, Masahiro and Biological
Network Consortium, Lung and van den Berge, Maarten and Bossé, Yohan
and J. Desai, Tushar and Eickelberg, Oliver and Kaminski, Naftali
and A. Krasnow, Mark and Lafyatis, Robert and Z. Nikolic, Marko and
E. Powell, Joseph and Rajagopal, Jayaraj and Rojas, Mauricio and
Rozenblatt-Rosen, Orit and A. Seibold, Max and Sheppard, Dean and P.
Shepherd, Douglas and D. Sin, Don and Timens, Wim and M. Tsankov,
Alexander and Whitsett, Jeffrey and Xu, Yan and E. Banovich,
Nicholas and Barbry, Pascal and Elizabeth Duong, Thu and S. Falk,
Christine and B. Meyer, Kerstin and A. Kropski, Jonathan and Pe’er,
Dana and B. Schiller, Herbert and Rao Tata, Purushothama and L.
Schultze, Joachim and A. Teichmann, Sara and V. Misharin, Alexander
and C. Nawijn, Martijn and D. Luecken, Malte and J. Theis, Fabian},
title = {An Integrated Cell Atlas of the Lung in Health and Disease},
journal = {Nature Medicine},
volume = {29},
number = {6},
pages = {1563-1577},
date = {2023-08-06},
url = {https://lazappi.id.au/publications/2023-sikkema-HLCA},
doi = {10.1038/s41591-023-02327-2},
issn = {1078-8956},
langid = {en},
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.}
}