A human circulating immune cell landscape in aging and COVID-19
Open accessAbstract
Age-associated changes in immune cells have been linked to an increased risk for infection. However, a global and detailed characterization of the changes that human circulating immune cells undergo with age is lacking. Here, we combined scRNA-seq, mass cytometry and scATAC-seq to compare immune cell types in peripheral blood collected from young and old subjects and patients with COVID-19. We found that the immune cell landscape was reprogrammed with age and was characterized by T cell polarization from naive and memory cells to effector, cytotoxic, exhausted and regulatory cells, along with increased late natural killer cells, age-associated B cells, inflammatory monocytes and age-associated dendritic cells. In addition, the expression of genes, which were implicated in coronavirus susceptibility, was upregulated in a cell subtype-specific manner with age. Notably, COVID-19 promoted age-induced immune cell polarization and gene expression related to inflammation and cellular senescence. Therefore, these findings suggest that a dysregulated immune system and increased gene expression associated with SARS-CoV-2 susceptibility may at least partially account for COVID-19 vulnerability in the elderly.
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Immune cell disorganization associated with aging may contribute to the heightened severity of COVID-19 and COPD in the elderly.
“Notably, immune cell disorganization associated with aging may contribute to the heightened severity of COVID-19 and chronic obstructive pulmonary disease (COPD) in the elderly.169,177”
From Inflammation and aging: signaling pathways and intervention therapies (2023) · cites this paper as [177]
The Discussion (page unavailable) explicitly describes a potential contribution of aging-related immune cell disorganization to greater COVID-19 severity in older patients. The paper does not address COPD, so it supports only the COVID-19 part of the citing sentence. (LLM, conf=0.88)
Experimental — accuracy not yet measuredSARS-CoV-2 infection induces polarization of peripheral blood immune cell subsets typical of ageing, including expression of inflammation- and senescence-associated genes.
“SARS-CoV-2 infection was shown to induce polarization of peripheral blood immune cell subsets that is typical for ageing and includes the expression of genes associated with inflammation and senescence82.”
From COVID-19 and cellular senescence (2023) · cites this paper as [82]
Coronavirus susceptibility genes, including CD147, CD26, and ANPEP, are upregulated with age.
“coronavirus susceptibility genes, among them CD147, CD26 and ANPEP (encoding aminopeptidase N; see ref.82 for details), are upregulated with age.”
From COVID-19 and cellular senescence (2023) · cites this paper as [82]
ROS increase with age because of mitochondrial dysfunction and inflammation, can drive NLRP3 inflammasome activation, and likely contribute further to COVID-19 pathophysiology in the elderly.
“ROS increase with age due to mitochondrial dysfunction and inflammation, and can also drive NLRP3 inflammasome activation, likely further contributing to COVID-19 pathophysiology in the elderly58,76,77.”
From SARS-CoV-2, COVID-19 and the aging immune system (2021) · cites this paper as [76]
Monocytes from older COVID-19 patients are enriched for an IFNγ response and for expression of TNFα, IL-1β and CXCL8.
“mass cytometry and single cell RNA-seq analysis of monocytes from older COVID-19 patients showed they were enriched for IFNγ response, and the expression of TNFα, IL-1β, and CXCL876.”
From SARS-CoV-2, COVID-19 and the aging immune system (2021) · cites this paper as [76]
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Cites
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2013) · Cell · doi:10.1016/j.cell.2013.05.039 · Cited by 14,982 · see citing works
Metascape provides a biologist-oriented resource for the analysis of systems-level datasets
Zhou, Y., Zhou, B., Pache, L., Chang, M., Khodabakhshi, A. H., Tanaseichuk, O., Benner, C., & Chanda, S. K. (2019) · Nature Communications · doi:10.1038/s41467-019-09234-6 · Cited by 14,611 · see citing works
COVID-19: consider cytokine storm syndromes and immunosuppression
Mehta, P., McAuley, D. F., Brown, M., Sanchez, E., Tattersall, R. S., & Manson, J. J. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30628-0 · Cited by 9,664 · see citing works
Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy
Onder, G., Rezza, G., & Brusaferro, S. (2020) · JAMA · doi:10.1001/jama.2020.4683 · Cited by 4,171 · see citing works
Estimates of the severity of coronavirus disease 2019: a model-based analysis
Verity, R., Okell, L. C., Dorigatti, I., Winskill, P., Whittaker, C., Imai, N., Cuomo-Dannenburg, G., Thompson, H., Walker, P. G. T., Fu, H., et al. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30243-7 · Cited by 3,660 · see citing works
Self-citationInflammaging: a new immune–metabolic viewpoint for age-related diseases
Franceschi, C., Garagnani, P., Parini, P., Giuliani, C., & Santoro, A. (2018) · Nature Reviews Endocrinology · doi:10.1038/s41574-018-0059-4 · Cited by 3,586 · see citing works
AP-1 as a regulator of cell life and death
Shaulian, E., & Karin, M. (2002) · Nature Cell Biology · doi:10.1038/ncb0502-e131 · Cited by 2,961 · see citing works
Pathological inflammation in patients with COVID-19: a key role for monocytes and macrophages
Merad, M., & Martin, J. C. (2020) · Nature Reviews Immunology · doi:10.1038/s41577-020-0331-4 · Cited by 2,472 · see citing works
Pathogenic T-cells and inflammatory monocytes incite inflammatory storms in severe COVID-19 patients
Zhou, Y., Fu, B., Zheng, X., Wang, D., Zhao, C., Qi, Y., Sun, R., Tian, Z., Xu, X., & Wei, H. (2020) · National Science Review · doi:10.1093/nsr/nwaa041 · Cited by 1,295 · see citing works
Van Hove, H., Martens, L., Scheyltjens, I., De Vlaminck, K., Pombo Antunes, A. R., De Prijck, S., Vandamme, N., De Schepper, S., Van Isterdael, G., Scott, C. L., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0393-4 · Cited by 1,160 · see citing works
Mrdjen, D., Pavlovic, A., Hartmann, F. J., Schreiner, B., Utz, S. G., Leung, B. P., Lelios, I., Heppner, F. L., Kipnis, J., Merkler, D., et al. (2018) · Immunity · doi:10.1016/j.immuni.2018.01.011 · Cited by 1,010 · see citing works
Satpathy, A. T., Granja, J. M., Yost, K. E., Qi, Y., Meschi, F., McDermott, G. P., Olsen, B. N., Mumbach, M. R., Pierce, S. E., Corces, M. R., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0206-z · Cited by 980 · see citing works
Qi, F., Qian, S., Zhang, S., & Zhang, Z. (2020) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2020.03.044 · Cited by 905 · see citing works
Immune cell profiling of COVID-19 patients in the recovery stage by single-cell sequencing
Wen, W., Su, W., Tang, H., Le, W., Zhang, X., Zheng, Y., Liu, X., Xie, L., Li, J., Ye, J., et al. (2020) · Cell Discovery · doi:10.1038/s41421-020-0168-9 · Cited by 730 · see citing works
Self-citationAn atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics
Angelidis, I., Simon, L. M., Fernandez, I. E., Strunz, M., Mayr, C. H., Greiffo, F. R., Tsitsiridis, G., Ansari, M., Graf, E., Strom, T.-M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08831-9 · Cited by 637 · see citing works
Increased cell-to-cell variation in gene expression in ageing mouse heart
Bahar, R., Hartmann, C. H., Rodriguez, K. A., Denny, A. D., Busuttil, R. A., Dollé, M. E. T., Calder, R. B., Chisholm, G. B., Pollock, B. H., Klein, C. A., et al. (2006) · Nature · doi:10.1038/nature04844 · Cited by 603 · see citing works
Single-Cell Transcriptomic Atlas of Primate Ovarian Aging
Wang, S., Zheng, Y., Li, J., Yu, Y., Zhang, W., Song, M., Liu, Z., Min, Z., Hu, H., Jing, Y., et al. (2020) · Cell · doi:10.1016/j.cell.2020.01.009 · Cited by 592 · see citing works
Self-citationRadzikowska, U., Ding, M., Tan, G., Zhakparov, D., Peng, Y., Wawrzyniak, P., Wang, M., Li, S., Morita, H., Altunbulakli, C., et al. (2020) · Allergy · doi:10.1111/all.14429 · Cited by 542 · see citing works
Single-cell analysis reveals T cell infiltration in old neurogenic niches
Dulken, B. W., Buckley, M. T., Navarro Negredo, P., Saligrama, N., Cayrol, R., Leeman, D. S., George, B. M., Boutet, S. C., Hebestreit, K., Pluvinage, J. V., et al. (2019) · Nature · doi:10.1038/s41586-019-1362-5 · Cited by 521 · see citing works
A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring
Alpert, A., Pickman, Y., Leipold, M., Rosenberg-Hasson, Y., Ji, X., Gaujoux, R., Rabani, H., Starosvetsky, E., Kveler, K., Schaffert, S., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0381-y · Cited by 513 · see citing works
Human innate immunosenescence: causes and consequences for immunity in old age
Panda, A., Arjona, A., Sapey, E., Bai, F., Fikrig, E., Montgomery, R. R., Lord, J. M., & Shaw, A. C. (2009) · Trends in Immunology · doi:10.1016/j.it.2009.05.004 · Cited by 502 · see citing works
A mitochondrial UPR-mediated metabolic checkpoint regulates hematopoietic stem cell aging
Mohrin, M., Shin, J., Liu, Y., Brown, K., Luo, H., Xi, Y., Haynes, C. M., & Chen, D. (2015) · Science · doi:10.1126/science.aaa2361 · Cited by 490 · see citing works
Aging of the immune system: Focus on inflammation and vaccination
Pinti, M., Appay, V., Campisi, J., Frasca, D., Fülöp, T., Sauce, D., Larbi, A., Weinberger, B., & Cossarizza, A. (2016) · European Journal of Immunology · doi:10.1002/eji.201546178 · Cited by 439 · see citing works
CD147 as a Target for COVID-19 Treatment: Suggested Effects of Azithromycin and Stem Cell Engagement
Ulrich, H., & Pillat, M. M. (2020) · Stem Cell Reviews and Reports · doi:10.1007/s12015-020-09976-7 · Cited by 418 · see citing works
Vaccination in the elderly: The challenge of immune changes with aging
Ciabattini, A., Nardini, C., Santoro, F., Garagnani, P., Franceschi, C., & Medaglini, D. (2018) · Seminars in Immunology · doi:10.1016/j.smim.2018.10.010 · Cited by 411 · see citing works
Caloric Restriction Reprograms the Single-Cell Transcriptional Landscape of Rattus Norvegicus Aging
Ma, S., Sun, S., Geng, L., Song, M., Wang, W., Ye, Y., Ji, Q., Zou, Z., Wang, S., He, X., et al. (2020) · Cell · doi:10.1016/j.cell.2020.02.008 · Cited by 349 · see citing works
Self-citationAging increases cell-to-cell transcriptional variability upon immune stimulation
Martinez-Jimenez, C. P., Eling, N., Chen, H.-C., Vallejos, C. A., Kolodziejczyk, A. A., Connor, F., Stojic, L., Rayner, T. F., Stubbington, M. J. T., Teichmann, S. A., et al. (2017) · Science · doi:10.1126/science.aah4115 · Cited by 339 · see citing works
Immune Signaling in Neurodegeneration
Hammond, T. R., Marsh, S. E., & Stevens, B. (2019) · Immunity · doi:10.1016/j.immuni.2019.03.016 · Cited by 336 · see citing works
Single-cell chromatin modification profiling reveals increased epigenetic variations with aging
Cheung, P., Vallania, F., Warsinske, H. C., Donato, M., Schaffert, S., Chang, S. E., Dvorak, M., Dekker, C. L., Davis, M. M., Utz, P. J., et al. (2018) · Cell · doi:10.1016/j.cell.2018.03.079 · Cited by 323 · cited 2× · see citing works
“For humans, mass cytometry analysis showed that aging increased epigenetic variations in circulatory immune cells (Cheung et al., 2018).”
BackgroundHow B cells capture, process and present antigens: a crucial role for cell polarity
Yuseff, M.-I., Pierobon, P., Reversat, A., & Lennon‐Duménil, A. (2013) · Nature reviews. Immunology · doi:10.1038/nri3469 · Cited by 308 · see citing works
Ong, S.-M., Hadadi, E., Dang, T.-M., Yeap, W.-H., Tan, C. T.-Y., Ng, T.-P., Larbi, A., & Wong, S.-C. (2018) · Cell Death & Disease · doi:10.1038/s41419-018-0327-1 · Cited by 233 · see citing works
Delay of T cell senescence by caloric restriction in aged long-lived nonhuman primates
Messaoudi, I., Warner, J., Fischer, M. B., Park, B., Hill, B. J., Mattison, J. A., Lane, M. A., Roth, G. S., Ingram, D. K., Picker, L. J., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0606661103 · Cited by 225 · see citing works
Hickman, H. D., Reynoso, G. V., Ngudiankama, B. F., Cush, S. S., Gibbs, J. S., Bennink, J. R., & Yewdell, J. W. (2015) · Immunity · doi:10.1016/j.immuni.2015.02.009 · Cited by 218 · see citing works
Immunosenescence: deficits in adaptive immunity in the elderly
Hakim, F. T., & Gress, R. E. (2007) · Tissue Antigens · doi:10.1111/j.1399-0039.2007.00891.x · Cited by 215 · see citing works
Watson, N., Ding, B., Zhu, X., & Frisina, R. D. (2017) · Ageing Research Reviews · doi:10.1016/j.arr.2017.10.002 · Cited by 213 · see citing works
Takenaka, M. C., & Quintana, F. J. (2016) · Seminars in Immunopathology · doi:10.1007/s00281-016-0587-8 · Cited by 181 · see citing works
A single-cell transcriptomic landscape of primate arterial aging
Zhang, W., Zhang, S., Yan, P., Ren, J., Song, M., Li, J., Lei, J., Pan, H., Wang, S., Ma, X., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15997-0 · Cited by 163 · see citing works
Self-citationMeplazumab treats COVID-19 pneumonia: an open-labelled, concurrent controlled add-on clinical trialPreprint
Bian, H., Zheng, Z., Wei, D., Zhang, Z., Kang, W., Hao, C.-Q., Dong, K., Kang, W., Xia, J., Miao, J., et al. (2020) · medRxiv · doi:10.1101/2020.03.21.20040691 · Cited by 162 · see citing works
SIRT7 antagonizes human stem cell aging as a heterochromatin stabilizer
Bi, S., Liu, Z., Wu, Z., Wang, Z., Liu, X., Wang, S., Ren, J., Yao, Y., Zhang, W., Song, M., et al. (2020) · Protein & Cell · doi:10.1007/s13238-020-00728-4 · Cited by 160 · see citing works
Self-citationGrabiec, A. M., & Hussell, T. (2016) · Seminars in Immunopathology · doi:10.1007/s00281-016-0555-3 · Cited by 144 · see citing works
Pont, F., Tosolini, M., & Fournié, J. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz601 · Cited by 131 · see citing works
Single-cell omics in ageing: a young and growing field
He, X., Memczak, S., Qu, J. T., Belmonte, J. C. I., & Liu, G. (2020) · Nature Metabolism · doi:10.1038/s42255-020-0196-7 · Cited by 128 · see citing works
Self-citationAttacking Latent HIV with convertibleCAR-T Cells, a Highly Adaptable Killing Platform
Herzig, E., Chan, K., Packard, T. A., Vardi, N., Schwarzer, R., Gramatica, A., Deeks, S. G., Williams, S. R., Landgraf, K. E., Killeen, N. P., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.002 · Cited by 101 · see citing works
Aged murine hematopoietic stem cells drive aging-associated immune remodeling
Leins, H., Mulaw, M., Eiwen, K., Sakk, V., Liang, Y., Denkinger, M., Geiger, H., & Schirmbeck, R. (2018) · Blood · doi:10.1182/blood-2018-02-831065 · Cited by 95 · see citing works
Wu, J., Zhang, H., Zheng, Y., et al. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01847 · Cited by 89 · see citing works
Self-citationA single-cell transcriptomic atlas of primate pancreatic islet aging
Li, J., Zheng, Y., Yan, P., Song, M., Wang, S., Sun, L., Liu, Z., Ma, S., Belmonte, J. C. I., Chan, P., et al. (2020) · National Science Review · doi:10.1093/nsr/nwaa127 · Cited by 76 · see citing works
Self-citationTelomere-dependent and telomere-independent roles of RAP1 in regulating human stem cell homeostasis
Zhang, X., Liu, Z., Liu, X., Wang, S., Zhang, Y., He, X., Sun, S., Ma, S., Shyh‐Chang, N., Liu, F., et al. (2019) · Protein & Cell · doi:10.1007/s13238-019-0610-7 · Cited by 55 · see citing works
Self-citationRuffin, N., Gea‐Mallorquí, E., Brouiller, F., Jouve, M. J., Silvin, A., See, P., Dutertre, C., Ginhoux, F., & Benaroch, P. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911007116 · Cited by 50 · see citing works
Hutten, T. J. A., Thordardottir, S., Fredrix, H., Janssen, L. M. A., Woestenenk, R., Tel, J., Joosten, B., Cambi, A., Heemskerk, M. H. M., Franssen, G. M., et al. (2016) · The Journal of Immunology · doi:10.4049/jimmunol.1600011 · Cited by 47 · see citing works
Dendritic cells derived from TBP‐2‐deficient mice are defective in inducing T cell responses
Son, A., Nakamura, H., Okuyama, H., Oka, S., Yoshihara, E., Liu, W., Matsuo, Y., Kondo, N., Masutani, H., Ishii, Y., et al. (2008) · European Journal of Immunology · doi:10.1002/eji.200737939 · Cited by 38 · see citing works
IL-4/IL-13 polarization of macrophages enhances Ebola virus glycoprotein-dependent infection
Rogers, K. J., Brunton, B. A., Mallinger, L., Bohan, D., Sevcik, K. M., Chen, J., Ruggio, N., & Maury, W. J. (2019) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0007819 · Cited by 33 · see citing works
Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19Preprint
Han, L., Wei, X., Liu, C., Volpe, G., Wang, Z., Pan, T., Yuan, Y., Lei, Y., Lai, Y., Ward, C., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.10.022103 · Cited by 28 · see citing works
Radzikowska, U., Ding, M., Tan, G., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.14.090332 · Cited by 27 · see citing works
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Li, X., Li, C., Zhang, W., Wang, Y., Qian, P., & Huang, H. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01502-8 · Cited by 1,443 · see citing works
Self-citationTransfer learning enables predictions in network biology
Theodoris, C. V., Xiao, L., Chopra, A., Chaffin, M. D., Al Sayed, Z. R., Hill, M. C., Mantineo, H., Brydon, E. M., Zeng, Z., Liu, X. S., et al. (2023) · Nature · doi:10.1038/s41586-023-06139-9 · Cited by 1,193 · see citing works
Self-citationCOVID-19 immune features revealed by a large-scale single-cell transcriptome atlas
Ren, X., Wen, W., Fan, X., Hou, W., Su, B., Cai, P., Li, J., Liu, Y., Tang, F., Zhang, F., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.053 · Cited by 865 · see citing works
Self-citationCOVID-19 and the human innate immune system
Schultze, J. L., & Aschenbrenner, A. C. (2021) · Cell · doi:10.1016/j.cell.2021.02.029 · Cited by 714 · see citing works
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Fulop, T., Larbi, A., Pawelec, G., Khalil, A., Cohen, A. A., Hirokawa, K., Witkowski, J. M., & Franceschi, C. (2021) · Clinical Reviews in Allergy & Immunology · doi:10.1007/s12016-021-08899-6 · Cited by 464 · see citing works
Mou, Y., Du, Y., Zhou, L., Yue, J., Hu, X., Liu, Y., Chen, S., Lin, X., Zhang, G., Xiao, H., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.796288 · Cited by 432 · see citing works
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Bartleson, J. M., Radenkovic, D., Covarrubias, A. J., Furman, D., Winer, D. A., & Verdin, E. (2021) · Nature Aging · doi:10.1038/s43587-021-00114-7 · Cited by 359 · see citing works
Huang, Z., Chen, B., Liu, X., Li, H., Xie, L., Gao, Y., Duan, R., Li, Z., Zhang, J., Zheng, Y., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2023216118 · Cited by 247 · see citing works
Self-citationSwanson, E., Lord, C., Reading, J., Heubeck, A. T., Genge, P. C., Thomson, Z., Weiss, M. D., Li, X.-J., Savage, A. K., Green, R. R., et al. (2021) · eLife · doi:10.7554/elife.63632 · Cited by 267 · see citing works
Terekhova, M., Swain, A., Bohacova, P., Aladyeva, E., Arthur, L., Laha, A., Mogilenko, D. A., Burdess, S., Sukhov, V., Kleverov, D., et al. (2023) · Immunity · doi:10.1016/j.immuni.2023.10.013 · Cited by 199 · see citing works
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Schmitt, C. A., Tchkonia, T., Niedernhofer, L. J., Robbins, P. D., Kirkland, J. L., & Lee, S. (2023) · Nature Reviews Immunology · doi:10.1038/s41577-022-00785-2 · Cited by 153 · see citing works
Vaena, S., Chakraborty, P., Lee, H. G., Janneh, A. H., Kassir, M. F., Beeson, G., Hedley, Z., Yalcinkaya, A., Sofi, M. H., Li, H., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109076 · Cited by 92 · see citing works
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Calabrò, A., Accardi, G., Aiello, A., Caruso, C., & Candore, G. (2023) · Frontiers in Aging · doi:10.3389/fragi.2023.1272118 · Cited by 71 · see citing works
CellDrift: inferring perturbation responses in temporally sampled single-cell data
Jin, K., Schnell, D., Li, G., Salomonis, N., Prasath, V. B. S., Szczesniak, R., & Aronow, B. J. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac324 · Cited by 11 · see citing works
- Authors
- Zheng, Y., Liu, X., Le, W., Xie, L., Li, H., Wen, W., Wang, S., Ma, S., Huang, Z., Ye, J., Shi, W., Ye, Y., Liu, Z., Song, M., Zhang, W., Han, J.-D. J., Belmonte, J. C. I., Xiao, C., Qu, J., Wang, H., Liu, G.-H., & Su, W.
- Affiliations
- Sun Yat-sen University (CN)
- Wuhan Hankou Hospital (CN)
- Second Military Medical University (CN)
- Capital Medical University (CN)
- Chinese Academy of Sciences (CN)
- Peking University (CN)
- Corresponding author
- Qu, Jing
- Wang, Hongyang
- Liu, Guang-Hui
- Su, Wenru
- ORCID
- Venue
- Protein & Cell
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-08-11
- Volume
- 11
- Issue
- 10
- Pages
- 740-770
- ISSN
- 1674-800X (ISSN-L)
- 1674-8018
- PMC
- PMC7417788
- OpenAlex
- W3048745453
- Cited by
- 270
- References
- 53
- Citations by year
- 2026: 18 · 2025: 29 · 2024: 55 · 2023: 39 · 2022: 49 · 2021: 64 · 2020: 16
- FWCI
- 13.62
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Protein & Cell (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Immunology and Microbiology › Immunology › Immune responses and vaccinations
- Keywords
- aging, COVID-19 pandemic, SARS-CoV-2 susceptibility, circulating immune cells, T cell exhaustion, regulatory T cells, natural killer cells, age-associated B cells, inflammatory monocytes, cellular senescence, inflammation, immune reprogramming, older adults
- MeSH terms
- Betacoronavirus, Cytokine Release Syndrome, COVID-19, SARS-CoV-2, Adult, Aged, Aged, 80 and over, Aging, Disease Susceptibility, Flow Cytometry, Humans, Immune System, Immunocompetence, Inflammation, Middle Aged, Pneumonia, Viral, Mass Spectrometry, Gene Rearrangement, CD4-Positive T-Lymphocytes, Cytokines, Sequence Analysis, RNA, Coronavirus Infections, Gene Expression Regulation, Developmental, Cell Lineage, Gene Expression Profiling, Chromatin Assembly and Disassembly, Young Adult, Pandemics, Single-Cell Analysis, Transcriptome
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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