An integrated cell atlas of the lung in health and disease.
An integrated cell atlas of the lung in health and disease.
复制标题
健康和疾病中的肺综合细胞图谱。
DOI：
10.1038/s41591-023-02327-2
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发表时间：
2023-06
期刊：
影响因子：
82.9
通讯作者：
Zhang, Kun
中科院分区：
文献类型：
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作者：
Sikkema, Lisa;Ramirez-Suastegui, Ciro;Strobl, Daniel C.;Gillett, Tessa E.;Zappia, Luke;Madissoon, Elo;Markov, Nikolay S.;Zaragosi, Laure-Emmanuelle;Ji, Yuge;Ansari, Meshal;Arguel, Marie-Jeanne;Apperloo, Leonie;Banchero, Martin;Becavin, Christophe;Berg, Marijn;Chichelnitskiy, Evgeny;Chung, Mei-i;Collin, Antoine;Gay, Aurore C. A.;Gote-Schniering, Janine;Kashani, Baharak Hooshiar;Inecik, Kemal;Jain, Manu;Kapellos, Theodore S.;Kole, Tessa M.;Leroy, Sylvie;Mayr, Christoph H.;Oliver, Amanda J.;von Papen, Michael;Peter, Lance;Taylor, Chase J.;Walzthoeni, Thomas;Xu, Chuan;Bui, Linh T.;De Donno, Carlo;Dony, Leander;Faiz, Alen;Guo, Minzhe;Gutierrez, Austin J.;Heumos, Lukas;Huang, Ni;Ibarra, Ignacio L.;Jackson, Nathan D.;Murthy, Preetish Kadur Lakshminarasimha;Lotfollahi, Mohammad;Tabib, Tracy;Talavera-Lopez, Carlos;Travaglini, Kyle J.;Wilbrey-Clark, Anna;Worlock, Kaylee B.;Yoshida, Masahiro;van den Berge, Maarten;Bosse, Yohan;Desai, Tushar J.;Eickelberg, Oliver;Kaminski, Naftali;Krasnow, Mark A.;Lafyatis, Robert;Nikolic, Marko Z.;Powell, Joseph E.;Rajagopal, Jayaraj;Rojas, Mauricio;Rozenblatt-Rosen, Orit;Seibold, Max A.;Sheppard, Dean;Shepherd, Douglas P.;Sin, Don D.;Timens, Wim;Tsankov, Alexander M.;Whitsett, Jeffrey;Xu, Yan;Banovich, Nicholas E.;Barbry, Pascal;Duong, Thu Elizabeth;Falk, Christine S.;Meyer, Kerstin B.;Kropski, Jonathan A.;Pe'er, Dana;Schiller, Herbert B.;Tata, Purushothama Rao;Schultze, Joachim L.;Teichmann, Sara A.;Misharin, Alexander, V;Nawijn, Martijn C.;Luecken, Malte D.;Theis, Fabian J.;Chen, Yuexin;Hagood, James S.;Agami, Ahmed;Horvath, Peter;Lundeberg, Joakim;Marquette, Charles-Hugo;Pryhuber, Gloria;Samakovlis, Chistos;Sun, Xin;Ware, Lorraine B.;Zhang, Kun
单细胞技术改变了我们对人体组织的理解。然而，研究通常只捕获有限数量的供体，并且在细胞类型定义上存在分歧。整合许多单细胞数据集可以解决个体研究的这些局限性，并捕获群体中存在的变异性。在这里，我们提出了集成的人类肺细胞图谱（HLCA），将人类呼吸系统的49个数据集组合成一个单一的图谱，涵盖来自486个个体的240多万个细胞。HLCA提供了具有匹配标记基因的共有细胞类型重新注释，包括罕见和以前未描述的细胞类型的注释。利用HLCA中个体的数量和多样性，我们确定了与人口统计学协变量（如年龄、性别和体重指数）相关的基因模块，以及沿支气管树近端至远端轴沿着改变表达的基因模块。将新数据映射到HLCA可以快速进行数据注释和解释。使用HLCA作为疾病研究的参考，我们确定了多种肺部疾病中的共享细胞状态，包括COVID-19中的SPP 1+促纤维化单核细胞衍生的巨噬细胞，肺纤维化和肺癌。总的来说，HLCA是在人类细胞图谱中开发和使用大规模、跨数据集器官图谱的一个例子。人类肺部的单细胞图谱，整合了来自486个个体的240万个细胞的数据，包括来自健康和患病肺部的样本，为生成器官规模的细胞图谱提供了路线图。
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. A single-cell atlas of the human lungs, integrating data from 2.4 million cells from 486 individuals and including samples from healthy and diseased lungs, provides a roadmap for the generation of organ-scale cell atlases.
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影响因子：
14.9
作者：
Gene Ontology Consortium
通讯作者：
Gene Ontology Consortium
DOI：
10.1126/science.abl5197
发表时间：
2022-05-13
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Domínguez Conde C;Xu C;Jarvis LB;Rainbow DB;Wells SB;Gomes T;Howlett SK;Suchanek O;Polanski K;King HW;Mamanova L;Huang N;Szabo PA;Richardson L;Bolt L;Fasouli ES;Mahbubani KT;Prete M;Tuck L;Richoz N;Tuong ZK;Campos L;Mousa HS;Needham EJ;Pritchard S;Li T;Elmentaite R;Park J;Rahmani E;Chen D;Menon DK;Bayraktar OA;James LK;Meyer KB;Yosef N;Clatworthy MR;Sims PA;Farber DL;Saeb-Parsy K;Jones JL;Teichmann SA
通讯作者：
Teichmann SA
影响因子：
30.8
作者：
Finucane HK;Reshef YA;Anttila V;Slowikowski K;Gusev A;Byrnes A;Gazal S;Loh PR;Lareau C;Shoresh N;Genovese G;Saunders A;Macosko E;Pollack S;Brainstorm Consortium;Perry JRB;Buenrostro JD;Bernstein BE;Raychaudhuri S;McCarroll S;Neale BM;Price AL
通讯作者：
Price AL
影响因子：
64.8
作者：
Delorey TM;Ziegler CGK;Heimberg G;Normand R;Yang Y;Segerstolpe Å;Abbondanza D;Fleming SJ;Subramanian A;Montoro DT;Jagadeesh KA;Dey KK;Sen P;Slyper M;Pita-Juárez YH;Phillips D;Biermann J;Bloom-Ackermann Z;Barkas N;Ganna A;Gomez J;Melms JC;Katsyv I;Normandin E;Naderi P;Popov YV;Raju SS;Niezen S;Tsai LT;Siddle KJ;Sud M;Tran VM;Vellarikkal SK;Wang Y;Amir-Zilberstein L;Atri DS;Beechem J;Brook OR;Chen J;Divakar P;Dorceus P;Engreitz JM;Essene A;Fitzgerald DM;Fropf R;Gazal S;Gould J;Grzyb J;Harvey T;Hecht J;Hether T;Jané-Valbuena J;Leney-Greene M;Ma H;McCabe C;McLoughlin DE;Miller EM;Muus C;Niemi M;Padera R;Pan L;Pant D;Pe'er C;Pfiffner-Borges J;Pinto CJ;Plaisted J;Reeves J;Ross M;Rudy M;Rueckert EH;Siciliano M;Sturm A;Todres E;Waghray A;Warren S;Zhang S;Zollinger DR;Cosimi L;Gupta RM;Hacohen N;Hibshoosh H;Hide W;Price AL;Rajagopal J;Tata PR;Riedel S;Szabo G;Tickle TL;Ellinor PT;Hung D;Sabeti PC;Novak R;Rogers R;Ingber DE;Jiang ZG;Juric D;Babadi M;Farhi SL;Izar B;Stone JR;Vlachos IS;Solomon IH;Ashenberg O;Porter CBM;Li B;Shalek AK;Villani AC;Rozenblatt-Rosen O;Regev A
通讯作者：
Regev A
影响因子：
64.8
作者：
通讯作者：
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