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Age-related liver endothelial zonation triggers steatohepatitis by inactivating pericentral endothelium-derived C-kit

Nature Aging volume 3, pages 258–274 (2023)Cite this article

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Abstract

Aging leads to systemic metabolic disorders, including steatosis. Here we show that liver sinusoidal endothelial cell (LSEC) senescence accelerates liver sinusoid capillarization and promotes steatosis by reprogramming liver endothelial zonation and inactivating pericentral endothelium-derived C-kit, which is a type III receptor tyrosine kinase. Specifically, inhibition of endothelial C-kit triggers cellular senescence, perturbing LSEC homeostasis in male mice. During diet-induced nonalcoholic steatohepatitis (NASH) development, Kit deletion worsens hepatic steatosis and exacerbates NASH-associated fibrosis and inflammation. Mechanistically, C-kit transcriptionally inhibits chemokine (C–X–C motif) receptor (CXCR)4 via CCAAT enhancer-binding protein α (CEBPA). Blocking CXCR4 signaling abolishes LSEC–macrophage–neutrophil cross-talk and leads to the recovery of C-kit-deficient mice with NASH. Of therapeutic relevance, infusing C-kit-expressing LSECs into aged mice or mice with diet-induced NASH counteracts age-associated senescence and steatosis and improves the symptoms of diet-induced NASH by restoring metabolic homeostasis of the pericentral liver endothelium. Our work provides an alternative approach that could be useful for treating aging- and diet-induced NASH.

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Fig. 1: Aging-induced hepatic steatosis.
Fig. 2: Aging reshaped liver endothelial zonation and inactivated pericentral endothelium-derived C-kit.
Fig. 3: Endothelial C-kit deficiency accelerated LSEC senescence and aggravated hepatic steatosis.
Fig. 4: Loss of endothelial C-kit accelerated NASH-associated fibrosis and liver inflammation.
Fig. 5: Endothelial C-kit inhibited CXCR4 transcription via CEBPA.
Fig. 6: Endothelial C-kit impeded CXCR4-mediated LSEC–macrophage–neutrophil cross-talk.
Fig. 7: Administration of AMD3100 attenuated steatosis and fibrosis in C-kit-deficient mice with NASH.
Fig. 8: C-kit+ LSEC infusion improves diet- and aging-induced steatosis.

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Data availability

The original RNA-seq datasets reported in this study have been deposited in the Gene Expression Omnibus database with the accession numbers GSE216592 and GSE216426. In addition, we also analyzed some published datasets including young and old human or mouse liver transcriptome-wide analysis datasets SE183915 and GSE167665, healthy and diet-induced NASH mouse RNA-seq data (GSE140994 and GSE119340) and ChIP–seq data (GSM1037658 and GSM1816817) (http://cistrome.org/db/#/). All statistical data associated with this study are contained in the Supplementary Data. All other data are available from the corresponding author upon reasonable request. Source data are provided with this paper.

References

  1. Cao, Y. & Wang, R. H. Associations among metabolism, circadian rhythm and age-associated diseases. Aging Dis. 8, 314–333 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Hamrick, M. W. & Stranahan, A. M. Metabolic regulation of aging and age-related disease. Ageing Res. Rev. 64, 101175 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Finkel, T. The metabolic regulation of aging. Nat. Med. 21, 1416–1423 (2015).

    Article  CAS  PubMed  Google Scholar 

  4. Regina, C. et al. Vascular ageing and endothelial cell senescence: molecular mechanisms of physiology and diseases. Mech. Ageing Dev. 159, 14–21 (2016).

    Article  CAS  PubMed  Google Scholar 

  5. Xu, X. et al. Age-related impairment of vascular structure and functions. Aging Dis. 8, 590–610 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Grunewald, M. et al. Counteracting age-related VEGF signaling insufficiency promotes healthy aging and extends life span. Science 373, eabc8479 (2021).

  7. Kim, I. H., Kisseleva, T. & Brenner, D. A. Aging and liver disease. Curr. Opin. Gastroenterol. 31, 184–191 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Bonomini, F., Rodella, L. F. & Rezzani, R. Metabolic syndrome, aging and involvement of oxidative stress. Aging Dis. 6, 109–120 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Harvey, B. E. NASH: regulatory considerations for clinical drug development and U.S. FDA approval. Acta Pharmacol. Sin. 43, 1210–1214 (2022).

    Article  CAS  PubMed  Google Scholar 

  10. Ibrahim, S. H., Hirsova, P. & Gores, G. J. Non-alcoholic steatohepatitis pathogenesis: sublethal hepatocyte injury as a driver of liver inflammation. Gut 67, 963–972 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Feldstein, A. E. et al. Hepatocyte apoptosis and fas expression are prominent features of human nonalcoholic steatohepatitis. Gastroenterology 125, 437–443 (2003).

    Article  PubMed  Google Scholar 

  12. Hammoutene, A. & Rautou, P. E. Role of liver sinusoidal endothelial cells in non-alcoholic fatty liver disease. J. Hepatol. 70, 1278–1291 (2019).

    Article  CAS  PubMed  Google Scholar 

  13. Miyao, M. et al. Pivotal role of liver sinusoidal endothelial cells in NAFLD/NASH progression. Lab. Invest. 95, 1130–1144 (2015).

    Article  CAS  PubMed  Google Scholar 

  14. Fang, Z. Q. et al. Notch-triggered maladaptation of liver sinusoidal endothelium aggravates nonalcoholic steatohepatitis through endothelial nitric oxide synthase. Hepatology 76, 742–758 (2022).

  15. Braet, F. & Wisse, E. Structural and functional aspects of liver sinusoidal endothelial cell fenestrae: a review. Comp. Hepatol. 1, 1 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Kus, E. et al. LSEC fenestrae are preserved despite pro-inflammatory phenotype of liver sinusoidal endothelial cells in mice on high fat diet. Front. Physiol. 10, 6 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Furuta, K. et al. Lipid-induced endothelial vascular cell adhesion molecule 1 promotes nonalcoholic steatohepatitis pathogenesis. J. Clin. Invest. 131, e143690 (2021).

  18. Zhang, H. et al. Targeting epigenetically maladapted vascular niche alleviates liver fibrosis in nonalcoholic steatohepatitis. Sci. Transl. Med. 13, eabd1206 (2021).

    Article  CAS  PubMed  Google Scholar 

  19. Inverso, D. et al. A spatial vascular transcriptomic, proteomic, and phosphoproteomic atlas unveils an angiocrine Tie–Wnt signaling axis in the liver. Dev. Cell 56, 1677–1693 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Rocha, A. S. et al. The angiocrine factor Rspondin3 is a key determinant of liver zonation. Cell Rep. 13, 1757–1764 (2015).

    Article  CAS  PubMed  Google Scholar 

  21. Su, T. et al. Single-cell transcriptomics reveals zone-specific alterations of liver sinusoidal endothelial cells in cirrhosis. Cell. Mol. Gastroenterol. Hepatol. 11, 1139–1161 (2021).

    Article  PubMed  Google Scholar 

  22. Zhu, S. et al. Liver endothelial Heg regulates vascular/biliary network patterning and metabolic zonation via Wnt signaling. Cell. Mol. Gastroenterol. Hepatol. 13, 1757–1783 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. MacParland, S. A. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Sun, X. & Harris, E. N. New aspects of hepatic endothelial cells in physiology and nonalcoholic fatty liver disease. Am. J. Physiol. Cell Physiol. 318, C1200–C1213 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Hennigs, J. K., Matuszcak, C., Trepel, M. & Körbelin, J. Vascular endothelial cells: heterogeneity and targeting approaches. Cells 10, 2712 (2021).

  26. Fujio, K. et al. Coexpression of stem cell factor and c-kit in embryonic and adult liver. Exp. Cell. Res. 224, 243–250 (1996).

    Article  CAS  PubMed  Google Scholar 

  27. Miettinen, M. & Lasota, J. KIT (CD117): a review on expression in normal and neoplastic tissues, and mutations and their clinicopathologic correlation. Appl. Immunohistochem. Mol. Morphol. 13, 205–220 (2005).

    Article  CAS  PubMed  Google Scholar 

  28. Ma, R., Martínez-Ramírez, A. S., Borders, T. L., Gao, F. & Sosa-Pineda, B. Metabolic and non-metabolic liver zonation is established non-synchronously and requires sinusoidal Wnts. eLife 9, e46206 (2020).

  29. Wang, W., Shui, L., Liu, Y. & Zheng, M. C-Kit, a double-edged sword in liver regeneration and diseases. Front. Genet. 12, 598855 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Luna, G., Paez, J. & Cardier, J. E. Expression of the hematopoietic stem cell antigen Sca-1 (LY-6A/E) in liver sinusoidal endothelial cells: possible function of Sca-1 in endothelial cells. Stem Cells Dev. 13, 528–535 (2004).

    Article  CAS  PubMed  Google Scholar 

  31. Duan, J. L. et al. Notch-regulated c-Kit-positive liver sinusoidal endothelial cells contribute to liver zonation and regeneration. Cell. Mol. Gastroenterol. Hepatol. 13, 1741–1756 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kalucka, J. et al. Single-cell transcriptome atlas of murine endothelial cells. Cell 180, 764–779 (2020).

    Article  CAS  PubMed  Google Scholar 

  33. Halpern, K. B. et al. Erratum: single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature 543, 742 (2017).

    Article  CAS  PubMed  Google Scholar 

  34. Wang, B., Zhao, L., Fish, M., Logan, C. Y. & Nusse, R. Self-renewing diploid Axin2+ cells fuel homeostatic renewal of the liver. Nature 524, 180–185 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Sadri, F., Rezaei, Z. & Fereidouni, M. The significance of the SDF-1/CXCR4 signaling pathway in the normal development. Mol. Biol. Rep. 49, 3307–3320 (2022).

    Article  CAS  PubMed  Google Scholar 

  36. Petit, I., Jin, D. & Rafii, S. The SDF-1–CXCR4 signaling pathway: a molecular hub modulating neo-angiogenesis. Trends Immunol. 28, 299–307 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Suratt, B. T. et al. Role of the CXCR4/SDF-1 chemokine axis in circulating neutrophil homeostasis. Blood 104, 565–571 (2004).

    Article  CAS  PubMed  Google Scholar 

  38. Dimova, I. et al. SDF-1/CXCR4 signalling is involved in blood vessel growth and remodelling by intussusception. J. Cell. Mol. Med. 23, 3916–3926 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Qing, J. et al. Dopamine receptor D2 antagonism normalizes profibrotic macrophage–endothelial crosstalk in non-alcoholic steatohepatitis. J. Hepatol. 76, 394–406 (2022).

    Article  CAS  PubMed  Google Scholar 

  40. van der Windt, D. J. et al. Neutrophil extracellular traps promote inflammation and development of hepatocellular carcinoma in nonalcoholic steatohepatitis. Hepatology 68, 1347–1360 (2018).

    Article  PubMed  Google Scholar 

  41. Honda, M. & Kubes, P. Neutrophils and neutrophil extracellular traps in the liver and gastrointestinal system. Nat. Rev. Gastroenterol. Hepatol. 15, 206–221 (2018).

    Article  CAS  PubMed  Google Scholar 

  42. Duan, J. L. et al. Endothelial Notch activation reshapes the angiocrine of sinusoidal endothelia to aggravate liver fibrosis and blunt regeneration in mice. Hepatology 68, 677–690 (2018).

    Article  CAS  PubMed  Google Scholar 

  43. Duan, J. L. et al. Shear stress-induced cellular senescence blunts liver regeneration through Notch–sirtuin 1–P21/P16 axis. Hepatology 75, 677–690 (2022).

    Article  Google Scholar 

Download references

Acknowledgements

We thank H. Han from the Fourth Military Medical University for technical assistance. This work was supported by grants from the National Key Research and Development Program of China (2016YFA0102100, 2021YFA1100500) and NSFC 81422009, 81770560, 81870430 and 82270637.

Author information

Author notes

  1. These authors contributed equally: Juan-Li Duan, Jing-Jing Liu, Bai Ruan.

Authors and Affiliations

  1. Department of Hepatobiliary Surgery, Xi-Jing Hospital, Fourth Military Medical University, Xi’an, China

    Juan-Li Duan, Jing-Jing Liu, Bai Ruan, Jian Ding, Zhi-Qiang Fang, Hao Xu, Ping Song, Chen Xu, Zhi-Wen Li, Wei Du, Ming Xu, Yu-Wei Ling, Fei He & Lin Wang

  2. Center of Clinical Aerospace Medicine and Department of Aviation Medicine, Fourth Military Medical University, Xi’an, China

    Bai Ruan

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Contributions

J.-J.L., J.-L.D., B.R. and J.D. performed experiments; Z.-Q.F., H.X. and P.S. assisted with animal experiments; C.X., Z.-W.L., W.D., M.X., Y.-W.L. and F.H. helped with data collection; L.W. wrote the manuscript and supervised the whole study.

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Correspondence to Lin Wang.

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Extended data

Extended Data Fig. 1 Aging leads to steatosis.

(A) Liver to body weight ratio of control and aged mice (n = 10, P = 0.0211). (B) Serum ALT, AST, ALB, and TBIL levels in control and aged mice (Ctrl: n = 5, aging: n = 7). (C, D) H&E staining of livers in mice (C) or patients (D). (E, F) GSEA of the sequencing data collected from a public database (GSE183915 and GSE167665). The enrichment of genes associated with aging and fatty acid biosynthesis was identified by comparing the younger and older groups of mice (E) and patients (F). The two-tailed Student’s t-test was used for comparisons of two groups. Bars represent means ± SD; ns, not significant; *P < 0.05.

Source data

Extended Data Fig. 2 Observation of aged mice fed with CDAA diet.

The control (8-week-old) and aged mice (24-month-old) were subjected to CDAA model. (A) Liver to body weight ratio in control (n = 6) and aged mice (n = 5) fed a CDAA diet (P = 0.0012). (B) Hepatic TG content in the livers of control (n = 6) and aged mice (n = 5) fed a CDAA diet (P = 0.0017). (C, D) Hepatic SA-β-gal, H&E (P = 0.015), Oil red O (P = 0.0156), Sirius red (P = 0.0178), αSMA (P = 0.0327), C-kit (P = 0.0069), and VE-cadherin (P = 0.0004) staining of control (n = 6) and aged mice (n = 5) fed a CDAA diet. Quantitative data are shown for the positive staining areas. The two-tailed Student’s t-test was used for comparisons of two groups. Bars represent means ± SD; *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Source data

Extended Data Fig. 3 IF staining of senescent LSECs.

(A) IF p27 (green), VE-cadherin (red), and Hoechst (blue) staining of aged livers. (B) IF senescence (green), VE-cadherin (red), and Hoechst (blue) staining of control and aged livers. (C) IF senescence (green), VE-cadherin (red), and Hoechst (blue) staining of control and Kit KO livers. The experiment was repeated for three times independently and the representative images were shown.

Source data

Extended Data Fig. 4 C-kit expression in NASH models.

(A) GSEA of pericentral and periportal marker gene expression in LSECs isolated from control mice and mice with NASH. (B) The relative mRNA levels of C-kit in LSECs isolated from mice with NASH, according to the previously published RNA-seq data (GSE140994: n = 5, P = 0.0038 and GSE119340: n = 3, P = 0.0093). (C) Western blot analysis of C-kit expression in the LSECs of control (n = 6) and MCD-diet-fed mice (n = 7). The ratios of C-kit to GAPDH were quantitatively compared (P = 0.0013). (D) qRT-PCR analysis of C-kit expression in LSECs of control mice and mice fed an MCD diet for 4, 6, or 8 weeks (n = 3). (E) IF staining for C-kit in livers of MCD-diet-fed and control mice. The positive areas of C-kit staining were quantified (n = 4). (F) IF staining for C-kit in livers of control and CDAA-diet-fed mice. The two-tailed Student’s t-test was used for comparisons of two groups. Differences among multiple groups were compared using one-way ANOVA. Bars represent means ± SD; **P < 0.01.

Source data

Extended Data Fig. 5 Investigation of C-kit KO mice.

(A) The strategy used to establish the Cdh5-Cre/ERT kitflox/flox mice. The 6-week-old endothelial C-kit KO mice and their controls fed with a normal diet were administrated with tamoxifen, rested for another 2 weeks and then sacrificed for further investigations. (B) Western blot analysis of C-kit expression in the LSECs of control (n = 4) and C-kit KO mice (n = 3). The ratios of C-kit to GAPDH were quantitatively compared (P = 0.0058). (C) Relative mRNA level of C-kit in the LSECs of control and C-kit KO mice (n = 3). (D) Serum ALT, AST, TC, TG, ALB, and TBIL levels in C-kit KO and control mice (n = 7). (E) Photographic and H&E staining images of liver samples from control and C-kit KO mice. Comparison of liver to body weight ratios of control and C-kit KO mice (n = 6, P = 0.0045). (F) Oil red O staining of liver samples from C-kit KO and control mice. The positive areas of staining were quantitatively compared (n = 6, P = 0.0011). (G) F4/80, laminin, Ki67, and Lyve-1 staining of liver samples from control and C-kit KO mice (n = 6). The fenestration of liver sinusoid was inspected by SEM (n = 3). Positive areas of staining and the number of fenestrae were quantitatively compared. The two-tailed Student’s t-test was used for comparisons of two groups. Bars represent means ± SD; ns, not significant; **P < 0.01, ****P < 0.0001.

Source data

Extended Data Fig. 6 RNA-sequencing data of C-kit KO mice.

(A) Heatmaps showing the expression of the top 50 genes (associated with liver EC-specific phenotypes, and liver arterial, venous, and capillary EC markers) in LSECs of control and C-kit KO mice (n = 3). (B) A heatmap showing the expression of the top 50 liver-specific EC metabolic marker genes in LSECs of control and C-kit KO mice (n = 3). (C) GSEA of the sequencing data shown in (A). (D) GSEA of the sequencing data shown in (B). (E) A heatmap showing the expression of senescence-associated genes in LSECs of control and C-kit KO mice (n = 3). (F) Enrichment of hallmark gene sets in LSECs of control and C-kit KO mice (n = 3).

Source data

Extended Data Fig. 7 CXCR4-modulated cellular migration and senescence.

(A) ELISA analysis of secreted SDF-1 in the supernatants of cultured LSECs isolated from control and C-kit KO mice (n = 3, P = 0.0407). (B) The relative mRNA levels of CXCR4 in LSECs isolated from control mice, and mice fed a CDAA diet for 6 or 12 weeks (CT, 6 W: n = 5; 12 W: n = 4). (C) C-kit and CXCR4 IHC staining of livers from healthy controls and patients with NASH. Black arrows represented areas of positive staining. (D) LSECs were transduced with a fluorescently-labeled negative control (NC) or a CXCR4-shRNA-expressing lentiviral vector. The knockdown of CXCR4 mRNA expression was determined by qRT-PCR (n = 3, P = 0.0031). (E) The transwell cell migration assay was performed using control LSECs and LSECs with knocked down CXCR4 expression. Macrophages and neutrophils (P = 0.0479) that had migrated to the lower transwell chamber were counted and quantitatively compared (n = 4). (F) SA-β-gal staining of livers collected from control, C-kit KO, and C-kit KO + AMD3100 mice. SA-β-gal+ cells were quantitatively compared (n = 3). The two-tailed Student’s t-test was used for comparisons of two groups. Differences among multiple groups were compared using one-way ANOVA. Bars represent means ± SD; *P < 0.05, **P < 0.01, ****P < 0.0001.

Source data

Extended Data Fig. 8 Blocking CXCR4 alleviates NASH in mice fed with CDAA diet.

(A) Liver to body weight ratios in control and AMD3100-treated mice fed a CDAA diet (n = 4, P = 0.0205). (B) Serum ALT (P = 0.0281), AST, ALB, TBIL, and TG levels examined in control (n = 4) and AMD3100-treated (n = 3) time on a CDAA diet. (C) H&E (P = 0.0059), Oil red O (P = 0.0006), Sirius red (P = 0.0147), F4/80 (P = 0.0002), and MPO staining of livers collected from control and AMD3100-treated CDAA-diet-fed mice. The positive areas of staining were quantitatively compared (n = 4). The two-tailed Student’s t-test was used for comparisons of two groups. Bars represent means ± SD; ns, not significant; *P < 0.05, **P < 0.01, ***P < 0.001.

Source data

Extended Data Fig. 9 Tracing of implanted C-kit+ LSECs.

(A) Flow cytometry analysis of the purity of CD117+ LSECs isolated using magnetic beads. (B) Spectral imaging results showing the engraftment of GFP-labeled C-kit+ LSECs into the liver, spleen, kidney, heart, and lung. (C) CM-Dil Dye-labeled C-kit+ LSECs (red) were detected in Lyve1+ LSECs (green) under a fluorescence microscope 24 h following cell infusion. White arrows in the enlarged images represented the co-localization of Dil and Lyve1. (D) GFP-labeled C-kit+ LSECs were imaged by spectral imaging system at 12, 24, and 72 h following splenic infusion. The hepatic fluorescence intensities were quantitatively compared (n = 3). (E) CM-Dil Dye-labeled C-kit+ LSECs were observed using spectral imaging system 12 and 24 h following splenic infusion. The hepatic fluorescence intensities were quantitatively compared (Ctrl, 12 h: n = 3; 24 h: n = 4). Differences among multiple groups were compared using one-way ANOVA. Bars represent means ± SD.

Source data

Extended Data Fig. 10 RNA-sequencing data of mice implanted with C-kit+ LSECs.

(A) A heatmap showing the expression of chemokine receptors in C-kit+ and C-kit− LSECs (n = 3). (B) GSEA of macrophage- and granulocyte-associated pathways in C-kit+ and C-kit− LSECs. (C) A heatmap showing the expression of inflammation-associated genes in C-kit+ and C-kit− LSECs (n = 3). (D) GSEA of the top 50 liver EC, pericentral, periportal, and metabolic marker genes and inflammation-associated pathways in C-kit+ and C-kit− LSECs. (E) A heatmap showing the expression of senescence-associated genes in C-kit+ and C-kit− LSECs (n = 3). (F) GSEA of the expression of aging- and senescence-associated genes in C-kit+ and C-kit− LSECs. (G) A heatmap showing the expression of chemokine-, inflammation-, fatty-acid-biosynthesis-, and oxidation-related genes in LSECs collected from MCD-diet-fed mice following the infusion of C-kit+ or C-kit− LSECs (n = 4). (H) GSEA of the expression of fatty-acid- biosynthesis-, oxidation-, and inflammation-associated genes in LSECs collected from MCD-diet-fed mice following the infusion of C-kit+ or C-kit− LSECs. (I) GSEA of the expression of pericentral marker genes, periportal marker genes, and genes associated with aging and senescence in LSECs collected from mice following C-kit+ or C-kit− LSEC infusion.

Supplementary information

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Supplementary Tables 1–3

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Supplementary Data 1

Gating strategy: liver NPCs were isolated for flow cytometry analysis. Briefly, the debris was first excluded. Next, dead cells were excluded using the 7-AAD cell viability reagent. Remaining cells were analyzed using the displayed markers accordingly. The gating strategy of the experimental group was based on analysis of the isotype control.

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Duan, JL., Liu, JJ., Ruan, B. et al. Age-related liver endothelial zonation triggers steatohepatitis by inactivating pericentral endothelium-derived C-kit. Nat Aging 3, 258–274 (2023). https://doi.org/10.1038/s43587-022-00348-z

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