The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Single-cell transcriptome analysis of human skin identifies novel fibroblast subpopulation and enrichment of immune subsets in atopic dermatitis
Open accessAbstract
BACKGROUND Atopic dermatitis (AD) is a prevalent inflammatory skin disease with a complex pathogenesis, involving immune cell and epidermal abnormalities. Despite whole tissue biopsy studies that have advanced the mechanistic understanding of AD, single-cell-based molecular alterations are largely unknown. OBJECTIVE To construct a detailed, high-resolution atlas of cell populations, and to assess variability in cell composition and cell-specific gene expression in the skin of AD patients versus controls METHODS: We performed single-cell RNA-sequencing on skin biopsies from 5 patients with AD (4 lesional samples, 5 non-lesional samples) and 7 healthy control subjects, using 10x Genomics. RESULTS We created transcriptomic profiles for 39,042 AD (lesional and non-lesional) and healthy skin cells. Fibroblasts demonstrated a novel COL6A5+COL18A1+ subpopulation that was unique to lesional AD, and expressed CCL2 and CCL19 cytokines. A corresponding LAMP3+ dendritic cell (DC) population that expressed the CCL19 receptor CCR7 was also unique to AD lesions, illustrating a potential role for fibroblast signaling to immune cells. Lesional AD samples were characterized by expansion of inflammatory DCs (CD1A+FCER1A+) and tissue resident memory T-cells (CD69+CD103+). The frequencies of type 2 (IL13+)/type 22 (IL22+) T-cells were higher than type 1 (IFNG+) in lesional AD, while this ratio was diminished slightly in non-lesional AD and further in controls. CONCLUSION AD lesions were characterized by expanded type 2/type 22 T-cells and inflammatory DCs, and a unique inflammatory fibroblast that may interact with immune cells to regulate lymphoid cell organization and type 2 inflammation.
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Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353
Stimulation of CD25(+)CD4(+) regulatory T cells through GITR breaks immunological self-tolerance
Shimizu, J., Yamazaki, S., Takahashi, T., Ishida, Y., & Sakaguchi, S. (2002) · Nature Immunology · doi:10.1038/ni759 · Cited by 1,729
Gittler, J. K., Shemer, A., Suárez-Fariñas, M., Fuentes-Duculan, J., Gulewicz, K. J., Wang, C. Q. F., Mitsui, H., Cardinale, I., de Guzman Strong, C., Krueger, J. G., et al. (2012) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2012.07.012 · Cited by 981
Self-citationControl of TH2 polarization by the chemokine monocyte chemoattractant protein-1
Gu, L., Tseng, S., Horner, R. M., Tam, C., Loda, M., & Rollins, B. J. (2000) · Nature · doi:10.1038/35006097 · Cited by 832
CCL27–CCR10 interactions regulate T cell–mediated skin inflammation
Homey, B., Alenius, H., Müller, A., Soto, H., Bowman, E. P., Yuan, W., McEvoy, L., Lauerma, A. I., Assmann, T., Bünemann, E., et al. (2002) · Nature Medicine · doi:10.1038/nm0202-157 · Cited by 807
Metabolic functions of FABPs—mechanisms and therapeutic implications
Hotamisligil, G. S., & Bernlohr, D. A. (2015) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2015.122 · Cited by 712
Noda, S., Suárez-Fariñas, M., Ungar, B., Kim, S. J., de Guzman Strong, C., Xu, H., Peng, X., Estrada, Y. D., Nakajima, S., Honda, T., et al. (2015) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2015.08.015 · Cited by 657
Self-citationTh2 Cytokines and Atopic Dermatitis
B. Brandt, E. (2011) · Journal of Clinical & Cellular Immunology · doi:10.4172/2155-9899.1000110 · Cited by 655
Nograles, K. E., Zaba, L. C., Shemer, A., Fuentes-Duculan, J., Cardinale, I., Kikuchi, T., Ramon, M., Bergman, R., Krueger, J. G., & Guttman-Yassky, E. (2009) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2009.03.041 · Cited by 627
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Metadata
- Authors
- He, H., Suryawanshi, H., Morozov, P., Gay-Mimbrera, J., Del Duca, E., Kim, H. J., Kameyama, N., Estrada, Y., Der, E., Krueger, J. G., Ruano, J., Tuschl, T., & Guttman-Yassky, E.
- Venue
- Journal of Allergy and Clinical Immunology
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 145
- Issue
- 6
- Pages
- 1615-1628
- ISSN
- 0091-6749 (ISSN-L)
- OpenAlex
- W3005233576
- Cited by
- 503
- References
- 64
- FWCI
- 39.36
- Type
- journal article
- Language
- en
- Open access
- green
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- He, H., Suryawanshi, H., Morozov, P., Gay-Mimbrera, J., Del Duca, E., Kim, H. J., Kameyama, N., Estrada, Y., Der, E., Krueger, J. G., Ruano, J., Tuschl, T., & Guttman-Yassky, E. (2020). Single-cell transcriptome analysis of human skin identifies novel fibroblast subpopulation and enrichment of immune subsets in atopic dermatitis. Journal of Allergy and Clinical Immunology. https://doi.org/10.1016/j.jaci.2020.01.042
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