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Resolving the fibrotic niche of human liver cirrhosis at single-cell level
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Abstract
Liver cirrhosis is a major cause of death worldwide and is characterized by extensive fibrosis. There are currently no effective antifibrotic therapies available. To obtain a better understanding of the cellular and molecular mechanisms involved in disease pathogenesis and enable the discovery of therapeutic targets, here we profile the transcriptomes of more than 100,000 single human cells, yielding molecular definitions for non-parenchymal cell types that are found in healthy and cirrhotic human liver. We identify a scar-associated TREM2+CD9+ subpopulation of macrophages, which expands in liver fibrosis, differentiates from circulating monocytes and is pro-fibrogenic. We also define ACKR1+ and PLVAP+ endothelial cells that expand in cirrhosis, are topographically restricted to the fibrotic niche and enhance the transmigration of leucocytes. Multi-lineage modelling of ligand and receptor interactions between the scar-associated macrophages, endothelial cells and PDGFRα+ collagen-producing mesenchymal cells reveals intra-scar activity of several pro-fibrogenic pathways including TNFRSF12A, PDGFR and NOTCH signalling. Our work dissects unanticipated aspects of the cellular and molecular basis of human organ fibrosis at a single-cell level, and provides a conceptual framework for the discovery of rational therapeutic targets in liver cirrhosis.
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“Focusing our analysis on the CD4+ T cell compartment, we identified FOXP3+ cells expressing canonical Treg cell transcripts, including IL2RA, CTLA4 and TNFRSF18 (Fig. 1D, right panel).”
From Regulatory T cells safeguard liver health during metabolic-associated steatohepatitis (2026) · cites this paper as [22]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“are equivalent to the scar-associated macrophages (SAM) in human MASH (6–8)”
From Lipid-associated macrophages' promotion of fibrosis resolution during MASH regression requires TREM2 (2024) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, conditioned media from TREM2+ SAM were reported to be more fibrogenic compared to their TREM2− non-scar-associated counterparts (6).”
From Lipid-associated macrophages' promotion of fibrosis resolution during MASH regression requires TREM2 (2024) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“that are characteristics of SAM described in humans (6, 7).”
From Lipid-associated macrophages' promotion of fibrosis resolution during MASH regression requires TREM2 (2024) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The growing accessibility of single-cell transcriptomics has also revealed the presence of numerous subsets/states of macrophages in any given injured tissue in humans (30–33).”
From Targeting macrophages in liver fibrosis (2026) · cites this paper as [31]
Experimental — accuracy not yet measured
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In the citing paper
“While the precise roles of the different subsets generated during injury and resolution are still under investigation, the prevailing dogma is that during active fibrogenesis, the macrophage pool is dominated by pro-inflammatory and pro-fibrogenic macrophages (31, 89, 90).”
From Targeting macrophages in liver fibrosis (2026) · cites this paper as [31]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“A good example of this is the population of macrophages in the fibrotic liver, which have been called LAMs, SAMs, and NAMs in different studies, despite largely sharing a conserved transcriptional profile (31, 104, 108).”
From Targeting macrophages in liver fibrosis (2026) · cites this paper as [31]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“these cells also produce mediators such as SPP1 and TGF-β that activate HSCs and hence may promote fibrogenesis (31).”
From Targeting macrophages in liver fibrosis (2026) · cites this paper as [31]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Notably, these cells exhibit a very similar transcriptional profile, with the precise name (LAM, SAM, or NAM) reflecting the different studies in which these cells were identified.”
From Targeting macrophages in liver fibrosis (2026) · cites this paper as [31]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Single-cell RNA-seq studies conducted by independent groups have identified, in human MASLD, macrophage subsets largely analogous to those previously described in mouse (196–198). These include resident KCs (VSIG4+/CD163+/MARCO+/TIMD4+), Mo-KCs (VSIG4+/CD163+/MARCO-/TIMD4-), LAMs (VSIG4-/TREM2+/CD9+) and C-LAMs (VSIG4-/CX3CR1+/CCR2+).”
From Strategies to promote liver fibrosis amelioration with involvement of restorative macrophages (2026) · cites this paper as [198]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“While sub-populations of macrophages and HSCs in the healthy human liver have been described in single-cell data10–12, these subpopulations, and potential gene expression variations within, have not been resolved within the lobule organization at single-cell resolution in the human liver.”
From Spatial transcriptomics of healthy and fibrotic human liver at single-cell resolution (2025) · cites this paper as [11]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“and fibrotic scars (SAM) (6)”
From Lipid-associated macrophages' promotion of fibrosis resolution during MASH regression requires TREM2 (2024) · cites this paper as [6]
The cited source says what the claim attributes to it.
In the citing paper
“On the other hand, those monocytes recruited to zones of steatosis and fibrosis appear to take on an alternative profile, which has been given multiple names, including lipid-associated macrophages (LAMs), scar-associated macrophages (SAMs) and NASH-associated macrophages (NAMs) (31, 104, 108, 109).”
From Targeting macrophages in liver fibrosis (2026) · cites this paper as [31]
The cited source says what the claim attributes to it.
In the citing paper
“Recent single-cell human liver studies have largely focused on chronic liver disease rather than ALF, with emphasis on non-parenchymal cell populations7–9”
From Multimodal decoding of human liver regeneration (2024) · cites this paper as [7]
The cited source says what the claim attributes to it.
In the citing paper
“Notably, TREM2+/CD9+ macrophages have been shown to exhibit a pro-fibrogenic phenotype and to accumulate within collagen-rich fibrotic niches in cirrhotic livers, leading to their designation as scar associated macrophages (SAMs) (198).”
From Strategies to promote liver fibrosis amelioration with involvement of restorative macrophages (2026) · cites this paper as [198]
The cited source says what the claim attributes to it.
In the citing paper
“except for the mere recognition as a marker of fibrosis-associated macrophages39,43–45, the role of TREM2 in regulating the pro-fibrotic AM phenotype in lung fibrosis remains unclear.”
From TREM2 promotes lung fibrosis via controlling alveolar macrophage survival and pro-fibrotic activity (2025) · cites this paper as [39]
The cited source says what the claim attributes to it.
In the citing paper
“In the liver, a TREM2+CD9+ subset of macrophages that differentiate from circulating monocytes expands during liver cirrhosis and contributes to fibrosis (Ramachandran et al., 2019).”
From TREM2 Modulation Remodels the Tumor Myeloid Landscape Enhancing Anti-PD-1 Immunotherapy (2020) · cites this paper as Ramachandran et al., 2019
The cited source says what the claim attributes to it.
In the citing paper
“Both macrophage populations were identified by expression of CD74, while Mac 2 cells also expressed CD5L and MARCO (Fig. 2d, i; Supplementary Fig. 6b), most consistent with non-inflammatory macrophages or Kupffer cells10,11,21.”
From Spatial transcriptomics of healthy and fibrotic human liver at single-cell resolution (2025) · cites this paper as [11]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Notably, the Treg frequency was significantly elevated in MASH livers relative to that of controls (Fig. 1E), echoing the Treg enrichment observed in the CDAHFD and AMLN models.”
From Regulatory T cells safeguard liver health during metabolic-associated steatohepatitis (2026) · cites this paper as [22]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“PDGFRB expression was concentrated along the edges of ALDOB-expressing hepatocytes in a distribution expected for HSCs, which are located in the subendothelial space11 (Supplementary Fig. 2a–f).”
From Spatial transcriptomics of healthy and fibrotic human liver at single-cell resolution (2025) · cites this paper as [11]
Experimental — accuracy not yet measuredIn the citing paper
“In the cirrhosis-enriched neighbourhoods, we recovered over-expression of known markers of scar-associated endothelium, including ACKR1 and PLVAP (Fig 5F) [2].”
From Differential abundance testing on single-cell data using k-nearest neighbor graphs (2022) · cites this paper as [2]
In the citing paper
“In addition to providing a first-of-its-kind liver cell atlas, this study revealed the presence of two disease-associated endothelial cell populations in the fibrotic niche, characterized as CD34+PLVAP+VWA1+ and CD34+PLVAP+ACKR1+ populations.”
From Inflammation and immunity in liver homeostasis and disease: a nexus of hepatocytes, nonparenchymal cells and immune cells (2025) · cites this paper as [335]
In the citing paper
“Moreover, this same study identified PDGFRA as a marker of scar-associated fibroblasts in cirrhotic livers.”
From Inflammation and immunity in liver homeostasis and disease: a nexus of hepatocytes, nonparenchymal cells and immune cells (2025) · cites this paper as [335]
In the citing paper
“One landmark study described the fibrotic niche in healthy and cirrhotic human livers via single-cell RNA sequencing [335].”
From Inflammation and immunity in liver homeostasis and disease: a nexus of hepatocytes, nonparenchymal cells and immune cells (2025) · cites this paper as [335]
In the citing paper
“ScRNAseq of human cirrhotic livers has identified a subset of TREM2+CD9+ macrophages enriched in heavily scarred regions of the liver that secrete cytokines and growth factors, including epidermal growth factor (EGF) and platelet-derived growth factor BB (PDGF-BB) to create a pro-fibrogenic niche for aHSCs (56).”
From Hepatic Stellate Cell-Immune Interactions in NASH (2022) · cites this paper as [56]
In the citing paper
“This population was found to associate closely with aHSCs and likely overlaps with the scar-associated TREM2+ CD9+ macrophages described by Ramachandran et al. in scRNAseq of human cirrhosis (20, 56).”
From Hepatic Stellate Cell-Immune Interactions in NASH (2022) · cites this paper as [56]
In the citing paper
“Separately, fibrogenic TREM2+CD9+ “scar-associated” macrophages have been characterized in human cirrhosis (56).”
From Hepatic Stellate Cell-Immune Interactions in NASH (2022) · cites this paper as [56]
In the citing paper
“In silico trajectory analysis, based on spliced vs. unspliced mRNA ratios, suggested that these cells were derived from blood monocytes.”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Immunofluorescence staining demonstrated that these TREM2+/CD9+ macrophages were highly enriched in the fibrotic niche.”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Ramachandran et al. used scRNAseq technology to identify a disease-associated TREM2+/CD9+ macrophage population that was significantly expanded in human cirrhotic livers.”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Ligand-receptor pairs were localised to the fibrotic niche between scar-associated macrophages expressing TNFSF12 and PDGFB with myofibroblast receptors TNFSF12A and PDGFRA, respectively.”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Gene ontology of the top differentially expressed genes identified pro-fibrogenic factors, such as IL-1B, TREM2 (triggering receptor expressed on myeloid cells 2), CXCR4, C-C motif chemokine receptor (CCR)2, CXCL8, TNFSF12 and vascular endothelial growth factor (VEGF)A, which regulate scar-producing myofibroblasts, upregulate inflammation and promote angiogenesis.”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Analysis of the transcriptome of these scar-associated macrophages demonstrated a phenotype analogous to TREM2+/CD9+ BMDMs in mice.”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Cognate, pro-fibrotic myofibroblast receptors were also identified for secreted phosphoprotein 1 and IL1β.75”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Ramachandran et al. used this approach to identify a distinct population of scar-associated mesenchymal cells in the human liver expressing high levels of fibrogenic genes and the myofibroblast marker, PDGFRA. These myofibroblasts were topographically restricted to fibrotic septae and ligand-receptor analysis revealed a number of pro-fibrogenic pathways including TNFRSF12A, PDGFR and Notch. These”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Scar-associated LSECs have been shown by scRNAseq to expand in human cirrhosis. These cells have a PLVAP+ and ACKR1+ transcriptome and demonstrate a number of pro-inflammatory ligand-receptor interactions, such as TGFB1-TGFBR3, JAG1-NOTCH1 and CCL2-ACKR1.75”
From Understanding the cellular interactome of non-alcoholic fatty liver disease (2022) · cites this paper as [75]
In the citing paper
“Seminal work from the Henderson group first profiled hepatic cells, including HSCs from fibrotic mouse and patient livers (50, 51), which has since been expanded to MASH by several other groups including ours.”
From Found in translation—Fibrosis in metabolic dysfunction–associated steatohepatitis (MASH) (2023) · cites this paper as [51]
In the citing paper
“LAMs are identified by the expression of TREM2, Tetraspanin CD9 (CD9), and SPP1, which also represent markers of scar-associated macrophages (SAMs) in cirrhotic patients, suggesting a common macrophage lineage in different liver injury models (51).”
From Found in translation—Fibrosis in metabolic dysfunction–associated steatohepatitis (MASH) (2023) · cites this paper as [51]
In the citing paper
“Animal models implicate HSCs and immune cells, especially macrophages, as major cellular drivers of extracellular matrix turnover, both through reduced secretion of ECM components and crosslinking enzymes as well as increased secretion of proteases and their inhibitors (51, 52, 64, 262, 270-274).”
From Found in translation—Fibrosis in metabolic dysfunction–associated steatohepatitis (MASH) (2023) · cites this paper as [51]
In the citing paper
“Mature and plasma B‐cell clusters have been also detected by sc‐RNAseq within areas of scarring in fibrotic livers of patients with cirrhosis.( 58 )”
From The Emerging Role of B Cells in the Pathogenesis of NAFLD (2021) · cites this paper as [58]
In the citing paper
“While many of these discoveries have been based on mouse models, scRNA-seq analyses from human livers have also identified SAMs as a unique population located in the fibrotic niche of cirrhotic livers of different disease aetiologies.74”
From An integrated view of anti-inflammatory and antifibrotic targets for the treatment of NASH (2023) · cites this paper as [74]
In the citing paper
“Increasingly sophisticated experimental approaches have allowed discovery of significant diversity and functional heterogeneity within the fibroblast population during organ fibrosis22–25 .”
From Fibrosis: from mechanisms to medicines (2020) · cites this paper as [22]
In the citing paper
“a single-cell census of the colonic mesenchyme revealed four subsets of fibroblasts in addition to pericytes and myofibroblasts, and identification of a fibroblast subpopulation proximal to the colonic crypt niche which expressed SOX6, F3 (CD142), and WNT genes essential for colonic epithelial stem cell function.”
From Fibrosis: from mechanisms to medicines (2020) · cites this paper as [22]
In the citing paper
“In colitis, this niche became dysregulated with emergence of an activated mesenchymal population expressing TNFSF14, fibroblastic reticular cell-associated genes, interleukin (IL)-33, and lysyl oxidases (LOX) leading to impaired epithelial proliferation and maturation”
From Fibrosis: from mechanisms to medicines (2020) · cites this paper as [22]
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Citations
Cites
Fiji: an open-source platform for biological-image analysis
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., et al. (2012) · Nature Methods · doi:10.1038/nmeth.2019 · Cited by 66,890
Robust enumeration of cell subsets from tissue expression profiles
Newman, A. M., Liu, C. L., Green, M. R., Gentles, A. J., Feng, W., Xu, Y., Hoang, C. D., Diehn, M., & Alizadeh, A. A. (2015) · Nature Methods · doi:10.1038/nmeth.3337 · Cited by 13,224
Integrating single-cell transcriptomic data across different conditions, technologies, and species
Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018) · Nature Biotechnology · doi:10.1038/nbt.4096 · Cited by 13,174
Design and validation of a histological scoring system for nonalcoholic fatty liver disease†
Kleiner, D. E., Brunt, E. M., Van Natta, M., Behling, C., Contos, M. J., Cummings, O. W., Ferrell, L. D., Liu, Y., Torbenson, M. S., Unalp‐Arida, A., et al. (2005) · Hepatology · doi:10.1002/hep.20701 · Cited by 10,791
QuPath: Open source software for digital pathology image analysis
Bankhead, P., Loughrey, M. B., Fernández, J. A., Dombrowski, Y., McArt, D. G., Dunne, P. D., McQuaid, S., Gray, R. T., Murray, L. J., Coleman, H. G., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-17204-5 · Cited by 8,908
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
Spatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055
Scenic: single-cell regulatory network inference and clustering.
Aibar, S., González-Blas, C. B., Moerman, T., Huynh-Thu, V. A., Imrichova, H., Hulselmans, G., Rambow, F., Marine, J.-C., Geurts, P., Aerts, J., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4463 · Cited by 6,520
Macrophage biology in development, homeostasis and disease
Wynn, T. A., Chawla, A., & Pollard, J. W. (2013) · Nature · doi:10.1038/nature12034 · Cited by 4,684
Self-citationMechanisms of NAFLD development and therapeutic strategies
Friedman, S. L., Neuschwander-Tetri, B. A., Rinella, M., & Sanyal, A. J. (2018) · Nature Medicine · doi:10.1038/s41591-018-0104-9 · Cited by 4,354
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Cui, H., Banerjee, S., Xie, N., Hussain, M., Jaiswal, A., Liu, H., Kulkarni, T., Antony, V. B., Liu, R.-M., Colonna, M., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-57024-0 · Cited by 74
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Xiao, Y., Batmanov, K., Hu, W., Zhu, K., Tom, A. Y., Guan, D., Jiang, C., Cheng, L., McCright, S. J., Yang, E. C., et al. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.adc9653 · Cited by 69
Zhang, H., Ma, Y., Cheng, X., Wu, D., Huang, X., Chen, B., Ren, Y., Jiang, W., Tang, X., Bai, T., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abd1206 · Cited by 65
De Muynck, K., Heyerick, L., De Ponti, F. F., Vanderborght, B., Meese, T., Van Campenhout, S., Baudonck, L., Gijbels, E., Rodrigues, P. M., Banales, J. M., et al. (2024) · Hepatology · doi:10.1097/hep.0000000000000557 · Cited by 64
The Origin and Fate of Liver Myofibroblasts
Kim, H. Y., Sakane, S., Eguileor, A., Carvalho Gontijo Weber, R., Lee, W., Liu, X., Lam, K., Ishizuka, K., Rosenthal, S. B., Diggle, K., et al. (2024) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2023.09.008 · Cited by 63
IL-8+ neutrophils drive inexorable inflammation in severe alcohol-associated hepatitis
Guan, Y., Peiffer, B., Feng, D., Parra, M. A., Wang, Y., Fu, Y., Shah, V. H., Cameron, A. M., Sun, Z., & Gao, B. (2024) · Journal of Clinical Investigation · doi:10.1172/jci178616 · Cited by 59
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Tadokoro, T., Murata, S., Kato, M., Ueno, Y., Tsuchida, T., Okumura, A., Kuse, Y., Konno, T., Uchida, Y., Yamakawa, Y., et al. (2024) · Science Translational Medicine · doi:10.1126/scitranslmed.adg0338 · Cited by 58
Yang, L.-X., Qi, C., Lu, S., Ye, X.-S., Merikhian, P., Zhang, D.-Y., Yao, T., Zhao, J.-S., Wu, Y., Jia, Y., et al. (2025) · Nature Communications · doi:10.1038/s41467-024-55738-1 · Cited by 57
Liebold, I., Meyer, S., Heine, M., Kuhl, A., Witt, J., Eissing, L., Fischer, A., Koop, A., Kluwe, J., Schulze zur Wiesch, J., et al. (2023) · Cells · doi:10.3390/cells12030341 · Cited by 55
Roehlen, N., Saviano, A., El Saghire, H., Crouchet, E., Nehme, Z., Del Zompo, F., Jühling, F., Oudot, M. A., Durand, S. C., Duong, F. H. T., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abj4221 · Cited by 54
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Podleśny-Drabiniok, A., Novikova, G., Liu, Y., Dunst, J., Temizer, R., Giannarelli, C., Marro, S., Kreslavsky, T., Marcora, E., & Goate, A. M. (2024) · Nature Communications · doi:10.1038/s41467-024-46315-7 · Cited by 52
Fibroblasts in liver cancer: functions and therapeutic translation
Affo, S., Filliol, A., Gores, G. J., & Schwabe, R. F. (2023) · The Lancet Gastroenterology & Hepatology · doi:10.1016/s2468-1253(23)00111-5 · Cited by 49
Lefere, S., Devisscher, L., & Tacke, F. (2020) · Expert Opinion on Investigational Drugs · doi:10.1080/13543784.2020.1718106 · Cited by 47
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Johnson, N. D., Wu, X., Still, C. D., Chu, X., Petrick, A. T., Gerhard, G. S., Conneely, K. N., & DiStefano, J. K. (2021) · Clinical Epigenetics · doi:10.1186/s13148-021-01129-y · Cited by 43
Guillot, A., Kohlhepp, M., Bruneau, A., Heymann, F., & Tacke, F. (2020) · Cancers · doi:10.3390/cancers12092449 · Cited by 46
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Spatial dimension of macrophage heterogeneity in liver diseases
Guillot, A., & Tacke, F. (2023) · eGastroenterology · doi:10.1136/egastro-2023-000003 · Cited by 40
Self-citationHeimberg, G., Kuo, T., DePianto, D., Heigl, T., Diamant, N., Salem, O., Scalia, G., Biancalani, T., Turley, S., Rock, J., et al. (2023) · doi:10.1101/2023.07.18.549537 · Cited by 40
Therapeutic blockade of ER stress and inflammation prevents NASH and progression to HCC
Boslem, E., Reibe, S., Carlessi, R., Smeuninx, B., Tegegne, S., Egan, C. L., McLennan, E., Terry, L. V., Nobis, M., Mu, A., et al. (2023) · Science Advances · doi:10.1126/sciadv.adh0831 · Cited by 39
Cruz Tleugabulova, M., Melo, S. P., Wong, A., Arlantico, A., Liu, M., Webster, J. D., Lau, J., Lechner, A., Corak, B., Hodgins, J. J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53700-9 · Cited by 38
Sojoodi, M., Erstad, D. J., Barrett, S. C., Salloum, S., Zhu, S., Qian, T., Colon, S., Gale, E. M., Jordan, V. C., Wang, Y., et al. (2022) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2022.01.015 · Cited by 35
Sfaira accelerates data and model reuse in single cell genomics
Fischer, D. S., Dony, L., König, M., Moeed, A., Zappia, L., Heumos, L., Tritschler, S., Holmberg, O., Aliee, H., & Theis, F. J. (2021) · Genome Biology · doi:10.1186/s13059-021-02452-6 · Cited by 33
The microenvironment in the development of MASLD-MASH-HCC and associated therapeutic in MASH-HCC
Wu, Q., Yang, Y., Lin, S., Geller, D. A., & Yan, Y. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1569915 · Cited by 32
Efferocytosis in liver disease
Shi, H., Moore, M. P., Wang, X., & Tabas, I. (2024) · JHEP Reports · doi:10.1016/j.jhepr.2023.100960 · Cited by 30
Chan, M. M., Daemen, S., Beals, J. W., Terekhova, M., Yang, B. Q., Fu, C. F., He, L., Park, A. C., Smith, G. I., Razani, B., et al. (2023) · JHEP Reports · doi:10.1016/j.jhepr.2023.100877 · Cited by 29
Uhlig, M., Billig, S., Wienhold, J., & Schumacher, D. (2025) · Cells · doi:10.3390/cells14050345 · Cited by 29
EHBP1 suppresses liver fibrosis in metabolic dysfunction-associated steatohepatitis
Ma, F., Longo, M., Meroni, M., Bhattacharya, D., Paolini, E., Mughal, S., Hussain, S., Anand, S. K., Gupta, N., Zhu, Y., et al. (2025) · Cell Metabolism · doi:10.1016/j.cmet.2025.01.020 · Cited by 29
Liver-resident memory T cells: life in lockdown
Pallett, L. J., & Maini, M. K. (2022) · Seminars in Immunopathology · doi:10.1007/s00281-022-00932-w · Cited by 28
Mechanisms of liver fibrosis in metabolic syndrome
Mehal, W. (2023) · eGastroenterology · doi:10.1136/egastro-2023-100015 · Cited by 28
Multicytokine-producing CD4+ T cells characterize the livers of patients with NASH
Woestemeier, A., Scognamiglio, P., Zhao, Y., Wagner, J., Muscate, F., Casar, C., Siracusa, F., Cortesi, F., Agalioti, T., Müller, S., et al. (2023) · JCI Insight · doi:10.1172/jci.insight.153831 · Cited by 28
Iwata, A., Maruyama, J., Natsuki, S., Nishiyama, A., Tamura, T., Tanaka, M., Shichino, S., Seki, T., Komai, T., Okamura, T., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-06357-5 · Cited by 25
Wang, Y., Guan, Y., Feng, D., Maccioni, L., Parra, M. A., Peiffer, B., Mackowiak, B., Kuwabara, T., Mori, K., Mukoyama, M., et al. (2025) · Cellular & Molecular Immunology · doi:10.1038/s41423-025-01343-1 · Cited by 23
Liu, H., Yin, G., Franco Leonardi, B., Lan, T., Ait Ahmed, Y., Berger, H., Kohlhepp, M. S., Amiridze, N., Martagón Calderón, N., Frau, C., et al. (2025) · Gut · doi:10.1136/gutjnl-2024-334425 · Cited by 23
Self-citationAdvancements in MAFLD Modeling with Human Cell and Organoid Models
Wang, S.-X., Yan, J.-S., & Chan, Y.-S. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231911850 · Cited by 22
New therapeutic target for alcohol-associated hepatitis (AH): AH-associated IL-8+ neutrophils
Guan, Y., Feng, D., Maccioni, L., Wang, Y., & Gao, B. (2024) · eGastroenterology · doi:10.1136/egastro-2024-100166 · Cited by 21
Sinusoidal communication in chronic liver disease
Gibert-Ramos, A., Andrés-Rozas, M., Pastó, R., Alfaro-Retamero, P., Guixé-Muntet, S., & Gracia-Sancho, J. (2025) · Clinical and Molecular Hepatology · doi:10.3350/cmh.2024.0734 · Cited by 20
GDF2 and BMP10 coordinate liver cellular crosstalk to maintain liver health
Zhao, D., Huang, Z., Li, X., Wang, H., Hou, Q., Wang, Y., Yan, F., Yang, W., Liu, D., Yi, S., et al. (2024) · eLife · doi:10.7554/elife.95811 · Cited by 17
Lee, J., Kim, C. M., Cha, J. H., Park, J. Y., Yu, Y. S., Wang, H. J., Sung, P. S., Jung, E. S., & Bae, S. H. (2022) · Cells · doi:10.3390/cells11213387 · Cited by 16
Ex Vivo Tools and Models in MASLD Research
Velliou, R.-I., Giannousi, E., Ralliou, C., Kassi, E., & Chatzigeorgiou, A. (2024) · Cells · doi:10.3390/cells13221827 · Cited by 15
Angiocrine Signaling in Sinusoidal Health and Disease
Cooper, S. A., Kostallari, E., & Shah, V. H. (2023) · Seminars in Liver Disease · doi:10.1055/a-2128-5907 · Cited by 15
Zhao, W., Yuan, W., Dong, T., Qi, W., Feng, Z., Li, C., & Sun, Y. (2025) · Communications Biology · doi:10.1038/s42003-025-08160-2 · Cited by 16
Yu, X., Tian, W., Bao, X., Li, Z., Tu, H., Xu, X., Chen, J., Zhang, Q., Chen, J., Liu, C., et al. (2026) · Hepatology · doi:10.1097/hep.0000000000001427 · Cited by 14
Prominent role of gut dysbiosis in the pathogenesis of cystic fibrosis-related liver disease in mice
Bertolini, A., Nguyen, M., Zehra, S. A., Taleb, S. A., Bauer-Pisani, T., Palm, N., Strazzabosco, M., & Fiorotto, R. (2024) · Journal of Hepatology · doi:10.1016/j.jhep.2024.03.041 · Cited by 13
Yang, T., Zhang, Y., Duan, C., Liu, H., Wang, D., Liang, Q., Chen, X., Ma, J., Cheng, K., Chen, Y., et al. (2025) · Experimental & Molecular Medicine · doi:10.1038/s12276-024-01371-3 · Cited by 11
Novel regulators of hepatic macrophages in liver fibrosis
Tang, X., Bai, M., Du, X., Wang, H., Liu, M., Fu, X., Zhang, H., Liang, S., & Wang, L. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1705503 · Cited by 12
Sanchez Vasquez, J. D., Nkongolo, S., Traum, D., Sotov, V., Kim, S. C., Mahamed, D., Mehrotra, A., Patel, A., Chen, D. Y., Fung, S., et al. (2025) · Journal of Clinical Investigation · doi:10.1172/jci175241 · Cited by 11
Jung, S., Singh, K., & del Sol, A. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa283 · Cited by 9
Yang, Y., Jeong, J., Su, T., Lai, S., Zhang, P., Garcia-Milian, R., Graham, M., Liu, X., McConnell, M. J., Utsumi, T., et al. (2024) · JHEP Reports · doi:10.1016/j.jhepr.2024.101069 · Cited by 9
Krishnan, A., Ozturk, N. B., Cutshaw, K. A., Guicciardi, M. E., Kitagataya, T., Olson, K. E., Pavelko, K. D., Sherman, W., Wixom, A. Q., Jalan-Sakrikar, N., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-52710-3 · Cited by 8
Macrophage heterogeneity in liver fibrosis
Wang, W., Li, S., Liu, Y., Ding, X., Yang, Y., Chen, S., Cao, J., Tacke, F., Dong, W., & Lan, T. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1639455 · Cited by 8
Self-citationM. S. Barron, A., Fabre, T., & De, S. (2024) · F1000Research · doi:10.12688/f1000research.143472.1 · Cited by 8
Chen, S., Zhu, Y., Wang, J., Zhao, X., Zhai, X., Hu, L., He, X., Li, Z., Guo, Y., Wang, S., et al. (2025) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2025.120029 · Cited by 7
Iwakiri, Y. (2024) · Clinical and Molecular Hepatology · doi:10.3350/cmh.2024.0343 · Cited by 7
Live-cell imaging of human liver fibrosis using hepatic micro-organoids
Guan, Y., Fang, Z., Hu, A., Roberts, S., Wang, M., Ren, W., Johansson, P. K., Heilshorn, S. C., Enejder, A., & Peltz, G. (2025) · JCI Insight · doi:10.1172/jci.insight.187099 · Cited by 6
Chen, Y., Zhou, J., Tang, C., Zhu, P., Xu, Z., Song, X., Zhang, J., Cen, L., Zeng, H., Ke, Y., et al. (2025) · Cellular & Molecular Biology Letters · doi:10.1186/s11658-025-00824-5 · Cited by 4
“To further investigate the heterogeneity of macrophage populations, we performed subclus-ter analysis on the basis of characteristic surface markers [12, 19–21].”
Targeting macrophages in liver fibrosis
González del Barrio, L., Ipsen, D. H., Pfister, D. R., Hancz, D., & Scott, C. L. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1835489 · Cited by 3
Strategies to promote liver fibrosis amelioration with involvement of restorative macrophages
Aquino, J. B. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1792423 · Cited by 1
Regulatory T cells safeguard liver health during metabolic-associated steatohepatitis
Hanna, B. S., Langston, P. K., Marin-Rodero, M., Ramirez, R. N., Wan, M., Benoist, C., & Mathis, D. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2536314123 · Cited by 1
Metadata
- Authors
- Ramachandran, P., Dobie, R., Wilson-Kanamori, J. R., Dora, E. F., Henderson, B. E. P., Luu, N. T., Portman, J. R., Matchett, K. P., Brice, M., Marwick, J. A., Taylor, R. S., Efremova, M., Vento-Tormo, R., Carragher, N. O., Kendall, T. J., Fallowfield, J. A., Harrison, E. M., Mole, D. J., Wigmore, S. J., Newsome, P. N., Weston, C. J., Iredale, J. P., Tacke, F., Pollard, J. W., Ponting, C. P., Marioni, J. C., Teichmann, S. A., & Henderson, N. C.
- Affiliations
- Centre for Inflammation Research (GB)
- University Hospitals Birmingham NHS Foundation Trust (GB)
- Edinburgh Cancer Research (GB)
- Wellcome Sanger Institute (GB)
- Edinburgh Royal Infirmary (GB)
- National Institute for Health and Care Research (GB)
- Charité – Universitätsmedizin Berlin (DE)
- Albert Einstein College of Medicine (US)
- Institute of Genetics and Cancer (GB)
- European Bioinformatics Institute (GB)
- Corresponding author
- Ramachandran, P.
- Henderson, N. C.
- ORCID
- Ramachandran, P.
- Dobie, R.
- Henderson, B. E. P.
- Luu, N. T.
- Portman, J. R.
- Matchett, K. P.
- Brice, M.
- Taylor, R. S.
- Efremova, M.
- Carragher, N. O.
- Kendall, T. J.
- Fallowfield, J. A.
- Harrison, E. M.
- Mole, D. J.
- Wigmore, S. J.
- Newsome, P. N.
- Weston, C. J.
- Iredale, J. P.
- Tacke, F.
- Pollard, J. W.
- Ponting, C. P.
- Marioni, J. C.
- Teichmann, S. A.
- Henderson, N. C.
- Venue
- Nature
- Published
- 2019-10-09
- Volume
- 575
- Issue
- 7783
- Pages
- 512-518
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6876711
- OpenAlex
- W2979595830
- Cited by
- 1,784
- References
- 98
- Citations by year
- 2026: 306 · 2025: 319 · 2024: 293 · 2023: 286 · 2022: 220 · 2021: 221 · 2020: 131 · 2019: 7
- FWCI
- 92.30
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Nature (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- Wellcome Trust (RE/18/5/34216, 103749, 101067/Z/13/Z, WT206194, 103749/Z/14/Z)
- University Hospitals Birmingham NHS Foundation Trust
- NIHR Bristol Biomedical Research Centre
- Cancer Research UK (22231)
- National Institute for Health and Care Research
- British Heart Foundation (RM/17/3/33381, RE/18/5/34216)
- Department of Health and Social Care
- Children's Liver Disease Foundation
- Tenovus
- University of Birmingham
- University of Bristol
- Medical Research Council (RM/17/3/33381, MC_PC_15049, MR/N008340/1, 103749, MC_PC_15075, MR/P008887/1, MC_UU_00007/15, MC_PC_15041, RE/18/5/34216, MR/N022556/1)
- Biotechnology and Biological Sciences Research Council (BB/N018869/1, RE/18/5/34216)
- Birmingham Biomedical Research Centre
- Topics
- Health Sciences › Medicine › Hepatology › Liver physiology and pathology
- Health Sciences › Medicine › Hepatology › Liver Diseases and Immunity
- Health Sciences › Medicine › Hepatology › Liver Disease Diagnosis and Treatment
- Keywords
- liver cirrhosis, liver fibrosis, fibrotic niche, monocyte differentiation, collagen synthesis, TNFRSF12A, Notch signaling, non-parenchymal cells
- MeSH terms
- Animals, Duffy Blood-Group System, Female, Humans, Liver, Liver Cirrhosis, Macrophages, Male, Membrane Glycoproteins, Membrane Proteins, Phenotype, Receptors, Cell Surface, Receptors, Immunologic, Case-Control Studies, Cell Lineage, Receptor, Platelet-Derived Growth Factor alpha, Hepatocytes, Endothelial Cells, Mice, Hepatic Stellate Cells, Transendothelial and Transepithelial Migration, Single-Cell Analysis, Transcriptome, Tetraspanin 29
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