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COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets
Open accessAbstract
COVID-19, which is caused by SARS-CoV-2, can result in acute respiratory distress syndrome and multiple organ failure1–4, but little is known about its pathophysiology. Here we generated single-cell atlases of 24 lung, 16 kidney, 16 liver and 19 heart autopsy tissue samples and spatial atlases of 14 lung samples from donors who died of COVID-19. Integrated computational analysis uncovered substantial remodelling in the lung epithelial, immune and stromal compartments, with evidence of multiple paths of failed tissue regeneration, including defective alveolar type 2 differentiation and expansion of fibroblasts and putative TP63+ intrapulmonary basal-like progenitor cells. Viral RNAs were enriched in mononuclear phagocytic and endothelial lung cells, which induced specific host programs. Spatial analysis in lung distinguished inflammatory host responses in lung regions with and without viral RNA. Analysis of the other tissue atlases showed transcriptional alterations in multiple cell types in heart tissue from donors with COVID-19, and mapped cell types and genes implicated with disease severity based on COVID-19 genome-wide association studies. Our foundational dataset elucidates the biological effect of severe SARS-CoV-2 infection across the body, a key step towards new treatments. Single-cell analysis of lung, heart, kidney and liver autopsy samples shows the molecular and cellular changes and immune response resulting from severe COVID-19 infection.
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Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Self-citationClinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Self-citationClinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30566-3 · Cited by 27,263
Self-citationRSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
Fast, sensitive and accurate integration of single-cell data with Harmony
Korsunsky, I., Millard, N., Fan, J., Slowikowski, K., Zhang, F., Wei, K., Baglaenko, Y., Brenner, M., Loh, P.-R., & Raychaudhuri, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0619-0 · Cited by 10,488
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Self-citationSCANPY: large-scale single-cell gene expression data analysis
Wolf, F. A., Angerer, P., & Theis, F. J. (2018) · Genome Biology · doi:10.1186/s13059-017-1382-0 · Cited by 8,881
Pathological findings of COVID-19 associated with acute respiratory distress syndrome
Xu, Z., Shi, L., Wang, Y., Zhang, J., Huang, L., Zhang, C., Liu, S., Zhao, P., Liu, H., Zhu, L., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30076-x · Cited by 8,545
Self-citationVirological assessment of hospitalized patients with COVID-2019
Wölfel, R., Corman, V. M., Guggemos, W., Seilmaier, M., Zange, S., Müller, M. A., Niemeyer, D., Jones, T. C., Vollmar, P., Rothe, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2196-x · Cited by 6,661
Endothelial cell infection and endotheliitis in COVID-19
Varga, Z., Flammer, A. J., Steiger, P., Haberecker, M., Andermatt, R., Zinkernagel, A. S., Mehra, M. R., Schuepbach, R. A., Ruschitzka, F., & Moch, H. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30937-5 · Cited by 6,358
MAGMA: Generalized Gene-Set Analysis of GWAS Data
de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004219 · Cited by 3,653
Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients
Hadjadj, J., Yatim, N., Barnabei, L., Corneau, A., Boussier, J., Smith, N., Péré, H., Charbit, B., Bondet, V., Chenevier-Gobeaux, C., et al. (2020) · Science · doi:10.1126/science.abc6027 · Cited by 2,984
Autoantibodies against type I IFNs in patients with life-threatening COVID-19
Bastard, P., Rosen, L. B., Zhang, Q., Michailidis, E., Hoffmann, H.-H., Zhang, Y., Dorgham, K., Philippot, Q., Rosain, J., Béziat, V., et al. (2020) · Science · doi:10.1126/science.abd4585 · Cited by 2,662
Self-citationSingle-cell landscape of bronchoalveolar immune cells in patients with COVID-19
Liao, M., Liu, Y., Yuan, J., Wen, Y., Xu, G., Zhao, J., Cheng, L., Li, J., Wang, X., Wang, F., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0901-9 · Cited by 2,614
Self-citationPartitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604
Self-citationHCA Lung Biological Network, Sungnak, W., Huang, N., Bécavin, C., Berg, M., Queen, R., Litvinukova, M., Talavera-López, C., Maatz, H., Reichart, D., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0868-6 · Cited by 2,501
Ziegler, C. G. K., Allon, S. J., Nyquist, S. K., Mbano, I. M., Miao, V. N., Tzouanas, C. N., Cao, Y., Yousif, A. S., Bals, J., Hauser, B. M., et al. (2020) · Cell · doi:10.1016/j.cell.2020.04.035 · Cited by 2,284
Self-citationInborn errors of type I IFN immunity in patients with life-threatening COVID-19
Zhang, Q., Bastard, P., Liu, Z., Le Pen, J., Moncada-Velez, M., Chen, J., Ogishi, M., Sabli, I. K. D., Hodeib, S., Korol, C., et al. (2020) · Science · doi:10.1126/science.abd4570 · Cited by 2,229
Self-citationMultiorgan and Renal Tropism of SARS-CoV-2
Puelles, V. G., Lütgehetmann, M., Lindenmeyer, M. T., Sperhake, J. P., Wong, M. N., Allweiss, L., Chilla, S., Heinemann, A., Wanner, N., Liu, S., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2011400 · Cited by 1,775
Neuropathology of patients with COVID-19 in Germany: a post-mortem case series
Matschke, J., Lütgehetmann, M., Hagel, C., Sperhake, J. P., Schröder, A. S., Edler, C., Mushumba, H., Fitzek, A., Allweiss, L., Dandri, M., et al. (2020) · The Lancet Neurology · doi:10.1016/s1474-4422(20)30308-2 · Cited by 1,300
A cellular census of human lungs identifies novel cell states in health and in asthma
Vieira Braga, F. A., Kar, G., Berg, M., Carpaij, O. A., Polanski, K., Simon, L. M., Brouwer, S., Gomes, T., Hesse, L., Jiang, J., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0468-5 · Cited by 896
Decoding human fetal liver haematopoiesis
Popescu, D.-M., Botting, R. A., Stephenson, E., Green, K., Webb, S., Jardine, L., Calderbank, E. F., Polanski, K., Goh, I., Efremova, M., et al. (2019) · Nature · doi:10.1038/s41586-019-1652-y · Cited by 606
Self-citationKobayashi, Y., Tata, A., Konkimalla, A., Katsura, H., Lee, R. F., Ou, J., Banovich, N. E., Kropski, J. A., & Tata, P. R. (2020) · Nature Cell Biology · doi:10.1038/s41556-020-0542-8 · Cited by 559
Self-citationTemporal and spatial heterogeneity of host response to SARS-CoV-2 pulmonary infection
Desai, N., Neyaz, A., Szabolcs, A., Shih, A. R., Chen, J. H., Thapar, V., Nieman, L. T., Solovyov, A., Mehta, A., Lieb, D. J., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-20139-7 · Cited by 245
Self-citationJagadeesh, K. A., Dey, K. K., Montoro, D. T., Mohan, R., Gazal, S., Engreitz, J. M., Xavier, R. J., Price, A. L., & Regev, A. (2022) · Nature Genetics · doi:10.1038/s41588-022-01187-9 · Cited by 239
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Xu, E., Xie, Y., & Al-Aly, Z. (2022) · Nature Medicine · doi:10.1038/s41591-022-02001-z · Cited by 530
Metadata
- Authors
- Delorey, T. M., Ziegler, C. G. K., Heimberg, G., Normand, R., Yang, Y., Segerstolpe, Å., Abbondanza, D., Fleming, S. J., Subramanian, A., Montoro, D. T., Jagadeesh, K. A., Dey, K. K., Sen, P., Slyper, M., Pita-Juárez, Y. H., Phillips, D., Biermann, J., Bloom-Ackermann, Z., Barkas, N., Ganna, A., Gomez, J., Melms, J. C., Katsyv, I., Normandin, E., Naderi, P., Popov, Y. V., Raju, S. S., Niezen, S., Tsai, L. T.-Y., Siddle, K. J., Sud, M., Tran, V. M., Vellarikkal, S. K., Wang, Y., Amir-Zilberstein, L., Atri, D. S., Beechem, J., Brook, O. R., Chen, J., Divakar, P., Dorceus, P., Engreitz, J. M., Essene, A., Fitzgerald, D. M., 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, D. E., Miller, E. M., Muus, C., Niemi, M., Padera, R., Pan, L., Pant, D., Pe’er, C., Pfiffner-Borges, J., Pinto, C. J., Plaisted, J., Reeves, J., Ross, M., Rudy, M., Rueckert, E. H., Siciliano, M., Sturm, A., Todres, E., Waghray, A., Warren, S., Zhang, S., Zollinger, D. R., Cosimi, L., Gupta, R. M., Hacohen, N., Hibshoosh, H., Hide, W., Price, A. L., Rajagopal, J., Tata, P. R., Riedel, S., Szabo, G., Tickle, T. L., Ellinor, P. T., Hung, D., Sabeti, P. C., Novak, R., Rogers, R., Ingber, D. E., Jiang, Z. G., Juric, D., Babadi, M., Farhi, S. L., Izar, B., Stone, J. R., Vlachos, I. S., Solomon, I. H., Ashenberg, O., Porter, C. B. M., Li, B., Shalek, A. K., Villani, A.-C., Rozenblatt-Rosen, O., & Regev, A.
- Venue
- Nature
- Published
- 2021-04-29
- Volume
- 595
- Issue
- 7865
- Pages
- 107-113
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3157263169
- Cited by
- 794
- References
- 26
- FWCI
- 43.27
- Type
- journal article
- Language
- en
- Open access
- bronze
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