04716nas a2201249   4500000000100000000000100001008004100002260001200043653001300055653001100068653000900079653001900088653001600107653002300123100001700146700002900163700002100192700002100213700001600234700001800250700002200268700003000290700001200320700001800332700002400350700002000374700002000394700002400414700001600438700002600454700001700480700001900497700002100516700002700537700002900564700001700593700001400610700002500624700001800649700001700667700002200684700002100706700002200727700001600749700002000765700002200785700001300807700001600820700001900836700001700855700001400872700001500886700002400901700001700925700001300942700002200955700002200977700004300999700002401042700001601066700002701082700002301109700002301132700002201155700002101177700003901198700002601237700001701263700002001280700002201300700002101322700002001343700002001363700002201383700002101405700002201426700001901448700002601467700001901493700001801512700002401530700001501554700001501569700002501584700002101609700001101630700002501641700001801666700002401684700002201708700002101730700002401751700001501775700002401790700002601814700002401840700002201864700002601886700002201912700002101934700002001955245006301975300001402038490000702052520139302059022001403452       2023                            d  c2023-0610aCOVID-1910aHumans10aLung10aLung Neoplasms10aMacrophages10aPulmonary Fibrosis1 aLisa Sikkema1 aCiro Ramírez-Suástegui1 aDaniel C. Strobl1 aTessa E. Gillett1 aLuke Zappia1 aElo Madissoon1 aNikolay S. Markov1 aLaure-Emmanuelle Zaragosi1 aYuge Ji1 aMeshal Ansari1 aMarie-Jeanne Arguel1 aLeonie Apperloo1 aMartin Banchero1 aChristophe Bécavin1 aMarijn Berg1 aEvgeny Chichelnitskiy1 aMei-I. Chung1 aAntoine Collin1 aAurore C. A. Gay1 aJanine Gote-Schniering1 aBaharak Hooshiar Kashani1 aKemal Inecik1 aManu Jain1 aTheodore S. Kapellos1 aTessa M. Kole1 aSylvie Leroy1 aChristoph H. Mayr1 aAmanda J. Oliver1 aMichael von Papen1 aLance Peter1 aChase J. Taylor1 aThomas Walzthoeni1 aChuan Xu1 aLinh T. Bui1 aCarlo De Donno1 aLeander Dony1 aAlen Faiz1 aMinzhe Guo1 aAustin J. Gutierrez1 aLukas Heumos1 aNi Huang1 aIgnacio L. Ibarra1 aNathan D. Jackson1 aPreetish Kadur Lakshminarasimha Murthy1 aMohammad Lotfollahi1 aTracy Tabib1 aCarlos Talavera-López1 aKyle J. Travaglini1 aAnna Wilbrey-Clark1 aKaylee B. Worlock1 aMasahiro Yoshida1 aLung Biological Network Consortium1 aMaarten van den Berge1 aYohan Bossé1 aTushar J. Desai1 aOliver Eickelberg1 aNaftali Kaminski1 aMark A. Krasnow1 aRobert Lafyatis1 aMarko Z. Nikolić1 aJoseph E. Powell1 aJayaraj Rajagopal1 aMauricio Rojas1 aOrit Rozenblatt-Rosen1 aMax A. Seibold1 aDean Sheppard1 aDouglas P. Shepherd1 aDon D. Sin1 aWim Timens1 aAlexander M. Tsankov1 aJeffrey Whitsett1 aYan Xu1 aNicholas E. Banovich1 aPascal Barbry1 aThu Elizabeth Duong1 aChristine S. Falk1 aKerstin B. Meyer1 aJonathan A. Kropski1 aDana Pe'er1 aHerbert B. Schiller1 aPurushothama Rao Tata1 aJoachim L. Schultze1 aSara A. Teichmann1 aAlexander V. Misharin1 aMartijn C. Nawijn1 aMalte D. Luecken1 aFabian J. Theis00aAn integrated cell atlas of the lung in health and disease  a1563-15770 v293 aSingle-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.  a1546-170X