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Aberrant engagement of P-selectin drives hematopoietic stem cell aging in mice

Nature Aging volume 5, pages 1010–1024 (2025)Cite this article

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Abstract

During aging, hematopoietic stem cell (HSC) function progressively declines which can lead to reduced blood cell production and regeneration. This work uncovered that cell surface presentation of P-selectin (CD62P, encoded by Selp) increases in a large fraction of aging HSCs driven by a proinflammatory milieu in mice. Notably, expression of P-selectin molecularly and functionally dichotomized the aging HSC pool; stem cells presenting with highly abundant P-selectin were hallmarked by aging-associated gene expression programs and reduced repopulation capacity upon regenerative stress. Ectopic expression of Selp in young HSCs was sufficient to impair long-term reconstitution potential and impair erythropoiesis. Mechanistically, we uncovered that P-selectin receptor activation by its primary ligand, P-selectin glycoprotein ligand-1, suppressed aging-associated gene expression, and, reversely, lack of P-selectin signaling led to HSC premature aging. Collectively, our study uncovered a functional role of P-selectin engagement in regulating HSC regeneration and driving stem cell aging when perturbed.

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Fig. 1: P-selectin-overexpressing HSCs are associated with age-associated hematological phenotypes.
Fig. 2: Selp overexpression is sufficient to compromise regenerative and erythroid lineage capacity in HSCs.
Fig. 3: P-selectin-presenting HSCs harbor transcriptional and functional hallmarks of aging.
Fig. 4: IL-1β-independent induction of Selp with age can be rescued by young BM niche.
Fig. 5: Ligand engagement of P-selectin attenuates inflammatory pathway activation and aging.
Fig. 6: Premature aging of Selp-deficient HSCs.

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Data availability

Raw RNA-seq data for this paper are available at GEO under GSE194273 and GSE269360. The HSC aging signature is available at https://agingsignature.webhosting.rug.nl/. RNA-seq data for HSCs from TNF and IL-1β administration are available at GEO under GSE115403 and GSE165810, respectively. RNA-seq data for IL-1R1KO HSCs are available at GEO under GSE163503. The scRNA-seq data used for correlation analysis are available at GEO under GSE59114, GSE70657 and GSE232022. The mouse Genome assembly GRCm38 is available at https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001635.20/. Source data are provided with this paper. All other data are available from the corresponding authors upon reasonable request.

Code availability

No custom codes were used in this paper for analysis of RNA-seq data. The codes used for data analyses can be found at https://github.com/daozheng367/Selp_Nature_aging.

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Acknowledgements

We thank all members of the de Haan lab and the Will lab for critical feedback and discussion of the study. We also thank L. Bystrykh at ERIBA for assistance with data analysis and discussion. We thank the UMCG Flow cytometry Unit facility staff J. Teunis, T. Bijma and G.Mesander and the Stem Cell FACS and Xenotransplantation Facility and Flow Cytometry Core Facility at Einstein for their assistance on cell sorting and analysis. We thank D. A. Heller and P. Raju at Memorial Sloan Kettering Cancer Center for providing the SelpKO mice. This work was supported by ARCH (the European Union-sponsored Horizon 2020 Research and Innovation Program) under Marie Skłodowska-Curie grant agreement number 813091 and the Netherlands Organization for Scientific Research (grant number 12583) to G.d.H.; and US National Institutes of Health (NIH)-sponsored individual research grants (R01) number DK10513, number CA230756 and number HL157948 (to B.W.) and Cancer Center Support grant (P30) number CA013330. D.Y. was supported by a China Student Council Fellowship. B.W. is the Diane and Arthur B. Belfer Scholar in Cancer Research at Albert Einstein College of Medicine and a Leukemia and Lymphoma Society Scholar. M.M. is supported by the ASH Junior Faculty Scholar Award (2023) and grant number R01HL174801.

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Authors and Affiliations

  1. European Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen, University of Groningen, Groningen, the Netherlands

    Daozheng Yang, Natalia Skinder, Arthur Flohr Svendsen, Bertien Dethmers-Ausema, Ellen Weersing & Gerald de Haan

  2. Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY, USA

    Daozheng Yang, Jiahao Chen, Victor Thiruthuvanathan, Chi Zhang, Maria Maryanovich & Britta Will

  3. Department of Oncology, Albert Einstein College of Medicine, Bronx, NY, USA

    Yun-Ruei Kao & Britta Will

  4. Sanquin Research, Landsteiner Laboratory, Amsterdam, the Netherlands

    Arthur Flohr Svendsen & Gerald de Haan

  5. Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Chi Zhang

  6. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine Research, Albert Einstein College of Medicine, Bronx, NY, USA

    Britta Will

  7. Institute for Aging Studies, Albert Einstein College of Medicine, Bronx, NY, USA

    Britta Will

  8. Montefiore Einstein Comprehensive Cancer Center, Albert Einstein College of Medicine–Montefiore Health System, Bronx, NY, USA

    Britta Will

  9. Amsterdam UMC Cancer Center Amsterdam, Department of Hematology, Amsterdam, the Netherlands

    Gerald de Haan

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  1. Daozheng Yang
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Contributions

Conceptualization: D.Y., B.W. and G.d.H. Methodology: D.Y., M.M., B.W. and G.d.H. Investigation: D.Y., N.S., B.D.-A., E.W. and V.T. Formal analysis: D.Y., Y.-R.K., J.C., C.Z. and A.F.S. Writing—original draft: D.Y. Writing—review and editing: D.Y., B.W. and G.d.H. Supervision: G.d.H.

Corresponding authors

Correspondence to Britta Will or Gerald de Haan.

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The authors declare no competing interests.

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Nature Aging thanks Leif Ludwig, K. Lenhard Rudolph and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Phenotypic and functional changes of hematopoietic parameters with age.

(a) Hemoglobin (Hb) concentration and hematocrit (Ht) in young (n = 20) and old (n = 28) mice. ***P = 0.0007 (Hb), ***P = 0.0003 (Ht), two-tailed t-test. Data are presented as mean values +/− SD. (b) WBC count in young (n = 20) and old (n = 28) mice. Data are presented as mean values +/− SD. (c) Frequencies of Myeloid (CD11b+Gr-1+), B (B220+) and T (CD3+) cells in young (n = 3) and old (n = 5) PB. *P = 0.028, **P = 0.0016, unpaired t-test with Holm-Sidak correction. Data are presented as mean values +/− SD. (d-e) Frequencies of HSPCs in young and old BM. CMP, GMP, MEP, MkP (Lin-Sca-1-Kit+CD41 + CD150+), megakaryocyte progenitor (young = 7, old = 5); CLP (Lin-Sca-1lowKitlowCD135 + CD127+), common lymphoid progenitor (young = 5, old = 5); CFU-E (Lin-Sca-1-Kit+CD41-CD150-CD105+), colony-forming units-erythroid; PreCFU-E (Lin-Sca-1-Kit+CD41-CD150 + CD105+), pre-colony-forming units-erythroid; preGMP/GMP (Lin-Sca-1-Kit+CD41-CD150-CD105-), pre-common myeloid progenitor/common myeloid progenitor; preMegE (Lin-Sca-1-Kit+CD41-CD150 + CD105-), pre-megakaryocyte/erythroid progenitor (young = 7, old = 5). *P = 0.011 (GMP), *P = 0.043 (MEP), *P = 0.033 (CFU-E), two-tailed t-test. Data are presented as mean values +/− SD. (f) The number of colonies (size 6, cell number >30000) generated by 60 young and old LT-HSCs in liquid culture at day 14, respectively. Data are from 3 independent replicates. **P = 0.0064, two-tailed t-test. Data are presented as mean values +/− SD. (g) The number of colonies generated by 100 young and old LT-HSCs in semi-solid culture at day 14, respectively. Data are from 3 independent replicates. **P = 0.0012, two-tailed t-test. Data are presented as mean values +/− SD. (h) F tests for the variances between young and old parameters. (i) SELP expression in young and old human HSCs (CD34 + CRHBP + HOPX+) from scRNA-seq data GSE18029829, ****P < 0.0001, two-tailed t-test. (j) FACS plot of aged LT-HSCs indicating the expression of P-selectin (x) and CD150 (y). CD150lo and CD150hi LT-HSCs were defined as the lower 30% and the higher 30% CD150-expressing LT-HSCs, respectively. (k) P-selectin MFI in CD150lo and CD150hi LT-HSCs. *P = 0.016, Paired t-test. (l) Representative FACS plot shows the frequency of Selphi HSCs of the BM used for imaging. (m) Distance of HSCs to Mks (n = 79 Selplo/neg HSCs; 51 Selphi HSCs). Data is from 3 mice.

Source data

Extended Data Fig. 2 PB lineage output and BM engraftment of Selp-overexpressing HSCs.

(a-d) Frequencies of donor-derived overall BM cells (a) and HSPCs (b) in secondary recipients BM (Selplo = 5, Selphi = 6). Data are from 2 independent replicates. Two-tailed t-test. Data are presented as mean values +/− SD. (e) Frequencies of Selplo (n = 5) and Selphi (n = 6) HSCs generated Myeloid, B and T cells in PB of secondary recipients at indicated weeks post-transplantation. Data are from 2 independent replicates. Two-way ANOVA followed by Sidak test. Data are presented as mean values +/− SD. (f) P-selectin MFI on donor-derived HSCs in secondary recipients. Selplo (n = 5) and Selphi (n = 6). Two-tailed t-test. Data are presented as mean values +/− SD. (g) FACS plots show the transduction efficiency 5 days after transduction. Transduced cells are GFP+. (h) Validation of Selp overexpression in transduced cells (GFP+) 5 days after transduction by FACS. The FACS plot shows P-selectin MFI on young SelpEV, SelpOE and old HSCs. (i) Frequencies of SelpEV (n = 5) and SelpOE (n = 5) HSCs generated Mye, B and T cells in PB of secondary recipients at indicated weeks post-transplantation. Data are from 2 independent replicates. *P = 0.032, two-way ANOVA followed by Sidak test. Data are presented as mean values +/− SD. (j) Frequencies of SelpEV and SelpOE LT-HSCs generated platelets in PB of secondary recipients at indicated weeks post-transplantation (n = 10). Data are from 3 independent replicates. Two-way ANOVA followed by Sidak test. Data are presented as mean values +/− SD. (k-n) Frequencies of donor-derived overall BM cells (j) and HSPCs (k-m) in secondary recipients BM (SelpEV = 5, SelpOE = 5). Data are from 2 independent replicates. *P = 0.0496, two-tailed t-test. Data are presented as mean values +/− SD.

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Extended Data Fig. 3 Transcriptional analyses of Selphi HSC gene signature.

(a) Sorting strategy of Selplo and Selphi HSCs and RNA-seq design of Selplo and Selphi HSCs. (b) Principal Coordinates Analysis (PCoA) of aged Selplo and Selphi LT-HSCs. Samples from the same mouse were indicated by circles. (c) Heatmap showing the 162 DEGs in Selphi LT- HSCs. (d) Dotplot showing the biological processes (BP) enriched in down-regulated genes. The color of the dots represents the p value (Fisher exact test) highest (red) to lowest (blue). The size of the dots represents the number of enriched DEGs. The x-axis represents the ratio of the number of enriched DEGs in the total genes of that category. (e) GSEA of down-regulated genes in HSC aging signature27 in the expression files of Selphi vs Selplo LT-HSCs. Normalized enrichment score (NES) and FDR are provided. (f-g) Correlation analyses of up-regulated genes in Selphi HSCs with HSC aging signature27 (f, P = 6.9 × 10−15; g, P < 2.2 × 10−16), HSC myeloid bias signature29 (f, P = 2.4 × 10−16; g, P < 2.2 × 10−16), IL-1β activating genes (f, P = 1.6 × 10−08; g, P < 2.2 × 10−16) and TNF activating genes (f, P = 3.3 × 10−12; g, P < 2.2 × 10−16), using single-cell expression data from GSE59114 ref. 41 (f) and GSE232022 ref. 13 (g), respectively. Values on x and y axis are the enrichment scores of the gene sets in single cell. Correlation using Pearson coefficient R and linear regression t-test. Gene sets can be found in Supplementary Table 1.

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Extended Data Fig. 4 Responses of HSCs to TNF-α and IL-1β and transcriptional alterations of aged HSCs after transplantation in young recipients.

(a) Left panel showing the experiment design. Right panel showing P-selectin MFI on HSCs from mice after single treatment with TNF-α at day 1. Two-tailed t-test. Data are presented as mean values +/− SD. (b) The experiment design of in vitro differentiation assay with or without IL-1β treatment. (c-d) Differentiation of young and old LT-HSCs in conditions without (c, n = 12) or with (d, n = 8) IL-1β. Data are from 2 or 3 independent replicates. Vehicle: P = 0.1252 (day6), **P = 0.0041 (day8), **P = 0.0062 (day 10); IL-1β: ****P < 0.0001 (day 6 and day 8), P = 0.4257 (day 10), two-way ANOVA followed by Sidak test. Data are presented as mean values +/− SD. (e) DEGs in aged donor and donor-derived HSCs. Volcano plot shows the distribution of the false discovery rate (FDR) (-log10FDR) and the fold changes (logFC). Up-regulated and down-regulated genes are indicated in red and blue, respectively (FDR < 0.001). Selp is indicated in the plot. (f) Principal Coordinates Analysis (PCoA) of both pre-and post-transplant LT-HSC samples. (g-h) Dotplots showing the KEGG pathways enriched in both up-regulated (g) and down-regulated (h) genes upon transplantation. The color of the dots represents the p value (Fisher exact test) highest (red) to lowest (blue). The size of the dots represents the number of enriched DEGs. The x-axis represents the percentage of the number of enriched DEGs in the total genes of that category. (i-j) Correlation analyses of Post-TXP restoration genes with IL-1β activating genes, TNF activating genes and HSC aging signature27 using single-cell expression data from GSE59114 ref. 41 (i, P < 2.2 × 10−16 for all correlations) and GSE232022 ref. 13 (j, P < 2.2 × 10−16 for all correlations). Values on x and y axis are the enrichment scores of the gene sets in single cell. Correlation analyses using Pearson coefficient R and linear regression t-test. Gene sets can be found in Supplementary Table 1, 2.

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Extended Data Fig. 5 Down-regulated genes upon PSGL-1 treatment tend to be repressed upon aged HSCs transplanted to young recipients.

(a) DEGs in SelpKO HSCs upon PSGL-1 treatment. Volcano plot showing distribution of the false discovery rate (FDR) (-log10FDR) and the fold changes (logFC). Up-regulated and down-regulated genes are indicated in red and blue, respectively (FDR < 0.05). (b) Correlation analyses of Post-TXP down-regulated genes with IL6 activating genes using single-cell expression data from GSE70657 ref. 40, GSE59114 ref. 41 and GSE232022 ref. 13, respectively. Values on x and y axis are the enrichment scores of the gene sets in single cell. Correlation analyses using Pearson coefficient R and linear regression t-test, P < 2.2 × 10−16 for all correlation. Gene sets can be found in Supplementary Tables 1 and 2. Linear regression line and 95% confidence interval is presented. (c) Venn diagram showing overlapping genes between down-regulated genes upon transplantation and PSGL-1 exposure. 15 common genes are depicted under the diagram. (d-e) Correlation analyses of genes repressed by PSGL-1 with Post-TXP down-regulated genes and up-regulated HSC aging signature genes27 using single-cell expression data from GSE70657 ref. 40 (d) (Post−TXP_down, P < 1.3 × 10−05; HSC_Aging_up, P = 0.02) and GSE59114 ref. 41 (e) (Post−TXP_down, P < 9.5 × 10−14; HSC_Aging_up, P = 6.4 × 10−11). Values on x and y axis are the enrichment scores of the gene sets in single cell. Correlation analyses using Pearson coefficient R and linear regression t-test. Gene sets can be found in Supplementary Tables 1–3. Linear regression line and 95% confidence interval is presented. (f) Gating strategy of P-selectin+ cells from LSK fraction of HPC7 cells. (g-h) Phophoflow analysis for p-ERK1/2, p-STAT3 and p-p38 of LSK P-selectin+ HPC7 cells with or without PSGL-1 treatment for 15 minutes (upper panel) or 1 hour (lower panel) with (h) or without (g) Selpin. Bar plot shows MFI fold changes (n = 3). **P = 0.004, *P = 0.0116, two-tailed t-test. Data are presented as mean values +/− SD.

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Extended Data Fig. 6 Molecular and functional characterization of SelpKO HSCs.

(a) Validation of Selp deletion52 at exon 3 in the SelpKO vs SelpWT HSC RNA-seq data. The coverage of the alignments at Selp exon 3 was visualized by IGV. (b-c) Correlation analyses of genes upregulated in SelpKO HSCs with upregulated genes in HSC aging, IL6 activating genes and IL-1β activating genes using single-cell expression data from GSE70657 ref. 40 (b) and GSE59114 ref. 41 (c), respectively. Values on x and y axis are the enrichment scores of the gene sets in single cell. Correlation analyses using Pearson coefficient R and linear regression t-test. Gene sets can be found in Supplementary Tables 1 and 4. Linear regression line and 95% confidence interval is presented. (d) WBC, RBC and PLT counts for SelpWT and SelpKO mouse PB (n = 4). Data are presented as mean values +/− SD. (e) Validation of P-selectin presentation by FACS in SelpWT and SelpKO BM. (f) Frequencies of CMP, GMP and MEP in SelpWT and SelpKO BM (n = 4). **P = 0.002 (CMP), ***P = 0.0002 (GMP), *P = 0.027 (MEP), two-tailed t-test. Data are presented as mean values +/− SD. (g) Frequencies of DCs, monocytes (Mon), neutrophils (Neu) macrophages (Mac) CD8 T cells CD4 T cells and B cells in SelpWT and SelpKO BM (n = 4). *P = 0.027, two-tailed t-test. Data are presented as mean values +/− SD. (h) Frequencies of 50 SelpWT and SelpKO HSCs-derived BM cells in primary recipients. Data are from 2 independent replicates (n = 12). P = 0.0810 (Paired t-test). (i) Transplantation design of 200 SelpWT and 200 SelpKO LT-HSCs (n = 3). (j) WBC chimerism in PB of transplantation of 200 SelpWT and SelpKO LT-HSCs at indicated weeks (n = 3). **P = 0.0071 (week 8), ***P = 0.0006 (week 12), ***P = 0.0003 (week 16), two-way ANOVA followed by Sidak test. Data are presented as mean values +/− SD. (k) Frequencies of Myeloid, B and T cells in PB of 200 SelpWT and 200 SelpKO HSC transplantation at indicated weeks (n = 3). Data are presented as mean values +/− SD.

Source data

Supplementary information

Supplementary Information

Gating strategy of PB and BM samples.

Reporting Summary

Supplementary Table 1

Transcriptional analysis related to Fig. 3.

Supplementary Table 2

Transcriptional analysis related to Fig. 4.

Supplementary Table 3

Transcriptional analysis related to Fig. 5.

Supplementary Table 4

Transcriptional analysis related to Fig. 6.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Transcriptome analysis.

Source Data Fig. 4

Statistical source data and transcriptome analysis.

Source Data Fig. 5

Statistical source data and transcriptome analysis.

Source Data Fig. 6

Statistical source data and transcriptome analysis.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Transcriptome analysis.

Source Data Extended Data Fig. 4

Statistical source data and transcriptome analysis.

Source Data Extended Data Fig. 5

Statistical source data and transcriptome analysis.

Source Data Extended Data Fig. 6

Statistical source data and transcriptome analysis.

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Yang, D., Skinder, N., Kao, YR. et al. Aberrant engagement of P-selectin drives hematopoietic stem cell aging in mice. Nat Aging 5, 1010–1024 (2025). https://doi.org/10.1038/s43587-025-00880-8

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