Abstact
Ageing is the largest risk factor for many chronic diseases. Studies of heterochronic parabiosis, substantiated by blood exchange and old plasma dilution, show that old-age-related factors are systemically propagated and have pro-geronic effects in young mice. However, the underlying mechanisms how bloodborne factors promote ageing remain largely unknown. Here, using heterochronic blood exchange in male mice, we show that aged mouse blood induces cell and tissue senescence in young animals after one single exchange. This induction of senescence is abrogated if old animals are treated with senolytic drugs before blood exchange, therefore attenuating the pro-geronic influence of old blood on young mice. Hence, cellular senescence is neither simply a response to stress and damage that increases with age, nor a chronological cell-intrinsic phenomenon. Instead, senescence quickly and robustly spreads to young mice from old blood. Clearing senescence cells that accumulate with age rejuvenates old circulating blood and improves the health of multiple tissues.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Plasma exosomes improve peripheral neuropathy via miR-20b-3p/Stat3 in type I diabetic rats
Journal of Nanobiotechnology Open Access 24 November 2023
-
Metformin potentiates nephrotoxicity by promoting NETosis in response to renal ferroptosis
Cell Discovery Open Access 17 October 2023
-
Geroprotective interventions converge on gene expression programs of reduced inflammation and restored fatty acid metabolism
GeroScience Open Access 12 September 2023
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
Data availability
Source data are provided with this paper. The data from this study are available from the corresponding author upon reasonable request.
References
Vijg, J. & Campisi, J. Puzzles, promises and a cure for ageing. Nature 454, 1065–1071 (2008).
Campisi, J. Aging, cellular senescence, and cancer. Annu Rev. Physiol. 75, 685–705 (2013).
Coppe, J. P. et al. Senescence-associated secretory phenotypes reveal cell-nonautonomous functions of oncogenic RAS and the p53 tumor suppressor. PLoS Biol. 6, 2853–2868 (2008).
Jeon, O. H. et al. Senescence cell-associated extracellular vesicles serve as osteoarthritis disease and therapeutic markers. JCI Insight https://doi.org/10.1172/jci.insight.125019 (2019).
Acosta, J. C. et al. A complex secretory program orchestrated by the inflammasome controls paracrine senescence. Nat. Cell Biol. 15, 978–990 (2013).
Mehdipour, M. et al. Plasma dilution improves cognition and attenuates neuroinflammation in old mice. Geroscience 43, 1–18 (2021).
Mehdipour, M. et al. Rejuvenation of three germ layers tissues by exchanging old blood plasma with saline-albumin. Aging 12, 8790–8819 (2020).
Rebo, J. et al. A single heterochronic blood exchange reveals rapid inhibition of multiple tissues by old blood. Nat. Commun. 7, 13363 (2016).
Mehdipour, M. et al. Rejuvenation of brain, liver and muscle by simultaneous pharmacological modulation of two signaling determinants, that change in opposite directions with age. Aging 11, 5628–5645 (2019).
Khrimian, L. et al. Gpr158 mediates osteocalcin’s regulation of cognition. J. Exp. Med. 214, 2859–2873 (2017).
Loffredo, F. S. et al. Growth differentiation factor 11 is a circulating factor that reverses age-related cardiac hypertrophy. Cell 153, 828–839 (2013).
Smith, L. K. et al. beta2-microglobulin is a systemic pro-aging factor that impairs cognitive function and neurogenesis. Nat. Med. 21, 932–937 (2015).
Castellano, J. M. et al. Human umbilical cord plasma proteins revitalize hippocampal function in aged mice. Nature 544, 488–492 (2017).
Villeda, S. A. et al. The ageing systemic milieu negatively regulates neurogenesis and cognitive function. Nature 477, 90–94 (2011).
Naito, A. T. et al. Complement C1q activates canonical Wnt signaling and promotes aging-related phenotypes. Cell 149, 1298–1313 (2012).
Li, L. et al. Impairment of chondrocyte proliferation after exposure of young murine cartilage to an aged systemic environment in a heterochronic parabiosis model. Swiss Med. Wkly 148, w14607 (2018).
Yousef, H. et al. Systemic attenuation of the TGF-beta pathway by a single drug simultaneously rejuvenates hippocampal neurogenesis and myogenesis in the same old mammal. Oncotarget 6, 11959–11978 (2015).
Yousef, H. et al. Aged blood impairs hippocampal neural precursor activity and activates microglia via brain endothelial cell VCAM1. Nat. Med. 25, 988–1000 (2019).
Wiley, C. D. & Campisi, J. From ancient pathways to aging cells-connecting metabolism and cellular senescence. Cell Metab. 23, 1013–1021 (2016).
Jeon, O. H. et al. Local clearance of senescent cells attenuates the development of post-traumatic osteoarthritis and creates a pro-regenerative environment. Nat. Med. 23, 775–781 (2017).
Bussian, T. J. et al. Clearance of senescent glial cells prevents tau-dependent pathology and cognitive decline. Nature 562, 578–582 (2018).
Rodier, F. & Campisi, J. Four faces of cellular senescence. J. Cell Biol. 192, 547–556 (2011).
Demaria, M. et al. An essential role for senescent cells in optimal wound healing through secretion of PDGF-AA. Dev. Cell 31, 722–733 (2014).
Baker, D. J. et al. Naturally occurring p16(Ink4a)-positive cells shorten healthy lifespan. Nature 530, 184–189 (2016).
Xu, M. et al. Senolytics improve physical function and increase lifespan in old age. Nat. Med. 24, 1246–1256 (2018).
Zhu, S. et al. Aging- and obesity-related peri-muscular adipose tissue accelerates muscle atrophy. PLoS ONE 14, e0221366 (2019).
Kishi, S. et al. Proximal tubule ATR regulates DNA repair to prevent maladaptive renal injury responses. J. Clin. Invest. 129, 4797–4816 (2019).
Ogrodnik, M. et al. Cellular senescence drives age-dependent hepatic steatosis. Nat. Commun. 8, 15691 (2017).
Zhu, Y. et al. New agents that target senescent cells: the flavone, fisetin, and the BCL-XL inhibitors, A1331852 and A1155463. Aging 9, 955–963 (2017).
Liu, A. et al. Young plasma reverses age-dependent alterations in hepatic function through the restoration of autophagy. Aging Cell https://doi.org/10.1111/acel.12708 (2018).
Huang, Q. et al. A young blood environment decreases aging of senile mice kidneys. J. Gerontol. A Biol. Sci. Med Sci. 73, 421–428 (2018).
Sousa-Victor, P. et al. MANF regulates metabolic and immune homeostasis in ageing and protects against liver damage. Nat. Metab. 1, 276–290 (2019).
Zhu, Y. et al. Identification of a novel senolytic agent, navitoclax, targeting the Bcl-2 family of anti-apoptotic factors. Aging Cell 15, 428–435 (2016).
Chang, J. et al. Clearance of senescent cells by ABT263 rejuvenates aged hematopoietic stem cells in mice. Nat. Med. 22, 78–83 (2016).
Wan, Q. L. et al. Intermediate metabolites of the pyrimidine metabolism pathway extend the lifespan of C. elegans through regulating reproductive signals. Aging 11, 3993–4010 (2019).
Li, W. et al. Thymidine phosphorylase participates in platelet signaling and promotes thrombosis. Circ. Res. 115, 997–1006 (2014).
Dumont, N. A. et al. Dystrophin expression in muscle stem cells regulates their polarity and asymmetric division. Nat. Med. 21, 1455–1463 (2015).
Chang, N. C. et al. The dystrophin glycoprotein complex regulates the epigenetic activation of muscle stem cell commitment. Cell Stem Cell 22, 755–768 e756 (2018).
Mehdipour, M. et al. Key age-imposed signaling changes that are responsible for the decline of stem cell function. Subcell. Biochem. 90, 119–143 (2018).
Lau, A., Kennedy, B. K., Kirkland, J. L. & Tullius, S. G. Mixing old and young: enhancing rejuvenation and accelerating aging. J. Clin. Invest. 129, 4–11 (2019).
Tang, H. et al. Single senescent cell sequencing reveals heterogeneity in senescent cells induced by telomere erosion. Protein Cell 10, 370–375 (2019).
Petit, C. et al. Proteomics approaches to define senescence heterogeneity and chemotherapy response. Proteomics 19, e1800447 (2019).
Wiley, C. D. et al. Analysis of individual cells identifies cell-to-cell variability following induction of cellular senescence. Aging Cell 16, 1043–1050 (2017).
Hernandez-Segura, A. et al. Unmasking transcriptional heterogeneity in senescent cells. Curr. Biol. 27, 2652–2660 e2654 (2017).
Cazin, C., Chiche, A. & Li, H. Evaluation of injury-induced senescence and in vivo reprogramming in the skeletal muscle. J. Vis. Exp. https://doi.org/10.3791/56201 (2017).
Kaiping, Y. Adipose Tissue Protocols: Methods in Molecular Biology 2nd edn (Humana Press, 2008).
Acknowledgements
We thank I. Silverstein for help with blood exchange procedures and T. Rando and a subaward from the Glenn Foundation for Medical Research for funding our early background work. This work was supported by a postdoctoral fellowship from the Glenn Foundation for Medical Research, Korea University grant nos. K2006261 and K2025261; the National Research Foundation of Korea Government grant nos. NRF 2020R1C1C1009921 (O.H.J.) and NIH T32 AG002266 (N.W.A.); the Pew Charitable Trust awarded to the Buck Institute for Research on Aging; by grants from the NIH nos. P01 AG017242 and R01 AG051729 (J.C.); grant nos. NIH 1R01AG071787, R56 AG058819, R01 EB023776, R01 HL139605, and the Open Philanthropy Foundation and the QB3 Calico Award (I.M.C.). A collaborative grant no. R56 AG052988 SA23061 (J.C. and I.M.C.) greatly aided these studies. Schematics of all experimental designs were created with BioRender.com.
Author information
Authors and Affiliations
Contributions
Conceptualization was developed by I.M.C., J.C., M.J.C. and O.H.J. The investigation was carried out by O.H.J. (all experiments). M.M. and M.J.C. did the blood exchange experiments. T.-H.G. did the in vivo experiments, immunofluorescence imaging and analysis. M.K. did the in vivo experiments. N.W.A. performed the in vivo studies of muscle function. Z.R.R., H.G.L., C.K. and J.E. conducted the immunofluorescence and immunohistochemistry imaging and analysis. F.A. maintained the 3MR mouse colony. V.W. performed imaging and pathological analysis of kidney. The original draft was written by I.M.C., J.C., P-Y.D., M.J.C. and O.H.J. Review and editing was carried out by all authors. The project was supervised by I.M.C., J.C. and O.H.J.
Corresponding authors
Ethics declarations
Competing interests
J.C. is a founder and shareholder of Unity Biotechnology, which develops senolytic drugs. All other authors declare no competing interests.
Peer review
Peer review information
Nature Metabolism thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Christoph Schmitt, in collaboration with the Nature Metabolism team.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Senescence-induction in non-senescent mouse cells (MDFs) in culture by serum from old mice.
(a) mRNA levels for Cdkn2a and Cdkn1a and SASP factors Il6, Mmp3 and Laminb1, normalized to Actb mRNA, determined by RT–PCR (n = 8 for young or old serum treatment for 3 days; n = 4 for young + old (50/50) serum treatment for 3 days). (b) Representative EdU (green; EdU negative non-proliferating SnCs in arrows), HMGB1 (red; SnCs marked by HMGB1 nuclear loss with arrows), Hoechst labelled nuclei (blue) visualized by fluorescence microscopy (3-6 images per n) and SA-β-gal staining (3-7 images per n) and (c) quantification of EdU-positive SnCs in MDFs 3 days after culturing in young, old or young + old (50/50) mouse serum (n = 4 for each group). (d) Bioluminescence from 3MR-expressing cells (Renilla luciferase assay) in non-senescent MDFs from cultured in young (4-month-old), old (32-month-old) or young+old (50/50) mouse serum for 6 days (A.U.) (n = 4 for young or old mouse serum; n = 6 for young+old mouse serum). Data are means ± s.e.m. of biologically independent samples. Statistical significance was tested using one-way ANOVA followed by Dunnett’s post hoc test for multiple comparisons with *, P < 0.05; **, P < 0.01; ***, P < 0.001. Scale bars, 100 μm. Rel, relative.
Extended Data Fig. 2 Aged blood decreases muscle strength in young mice.
(a) Twitch force generated by skeletal muscles and maximal rate of contraction and relaxation during contractions (n = 6 for YY; n = 8 for YO). (b) Representative images of Oil Red O staining and quantification of Oil Red O + area of skeletal muscles of young mice receiving old (YO; 4-10 images per mice / n = 5 mice) or young (YY; 3-5 images per mice / n = 6 mice) mouse blood, showing more accumulation of adipose tissues in endomysium (interstitial connective tissue) between fibers in YO mice and (c) percentage of fibrosis (n = 4 for YY; n = 5 mice; 3-4 images per mice). (d) Skeletal muscle fatigue assessment in YY and YO mice (n = 6 for YY and n = 5 for YO). (e) Running distance in meter of YY and YO on treadmill (n = 11 for YY and n = 8 for YO). (f) Latency time to fall off the rotarod as a measure of motor coordination. Data are means ± s.e.m. of biologically independent samples. A two-tailed Student t-test (a) and two-tailed t-test with a Welch’s correction (b-c, e-f) with *, P < 0.05; **, P < 0.01were used for statistical analysis. Scale bars are shown in each image.
Extended Data Fig. 3 DQ-treated old mice serum inhibits induction of senescence in non-senescent mouse cells (MDFs) in culture.
(a) Relative protein expression ratio (< 0.7-fold) of SASP proteins in plasma from DQ-treated C57BL/6J old mice (DQ; n = 4) normalized to vehicle treated C57BL/6J old mice (Veh; n = 3), measured by antibody array. Each data point represents an individual mouse. Additional SA-β-gal images of (b) kidney and (c) liver in young C57BL/6J mice receiving old C57BL/6J mice treated with Veh (YO+Veh) or DQ (YO+DQ). (d) Representative EdU (green; EdU negative non-proliferating SnCs in arrows), HMGB1 (red; SnCs marked by HMGB1 nuclear loss in arrows), and Hoechst labeled nuclei (blue) visualized by fluorescence microscopy (n = 4 for each group / at least 7 images per n) and (e) SA-β-gal staining in MDFs cultured in Veh- or DQ-treated old mice serum for 3 days (n = 4 for veh-treated old mice serum treated; n = 5 for DQ-treated old mice serum / at least 6 images per n). Quantification of (f) EdU + (n = 4 for Veh-treated old mice serum treated; n = 3 for DQ-treated old mice serum treated) and (g) SA-β-gal + (n = 4 per group) MDFs. (h) mRNA levels for Cdkn2a and Cdkn1a and SASP factors Il6 and Mmp3 3 days after culturing in Veh- or DQ-treated old mice serum, determined by RT–PCR (n = 4 for Veh-treated old mice serum treated; n = 5 for DQ-treated old mice serum treated). Data are means ± s.e.m. of biologically independent samples. Statistical significance was calculated using multiple t test with two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli, with Q = 5%, *q < 0.05; **q < 0.01 (a, h) and two-tailed Student’s t test (f-g) with *, P < 0.05. Scale bars are shown in each image.
Extended Data Fig. 4 Inhibition of age-related tissue phenotypes induced by aged circulation in kidney and liver of young animals after exchanging blood of old mice in which SnCs were removed by DQ.
(a) Representative images of KIM-1 (n = 5 mice for YO+Veh; n = 7 mice for YO+DQ / 6-10 images per mice) and LTL (n = 5 mice for YO+Veh; n = 7 mice for YO+DQ / 6-8 images per mice) and (b) quantification of KIM-1 positive area (%) and LTL + tubular number as a marker of healthy renal tubules. (c) Measurements of KIM-1 levels and (d) blood urea nitrogen and creatine in serum of YO+Veh (n = 5) and YO+DQ mice (n = 8). (e) Scores of ATN, interstitial inflammation, interstitial fibrosis and tubular atrophy of renal cortex (n = 5 for YO+Veh; n = 6 for YO+DQ). (f) Representative images of Oil red O (n = 5 mice for YO+Veh; n = 7 mice for YO+DQ / 8-15 images per mice), Sirius red (n = 5 mice for YO+Veh; n = 7 mice for YO+DQ; 10-15 images per mice) and Masson’s trichrome (n = 4 for YO+Veh; n = 5 for YO+DQ; 15-20 images per mice) staining and (g-h) quantification of Oil Red O-positive and fibrotic areas. (i) Quantification of fibrosis-related mRNAs encoding Col1a1, Col3a1, Col4a1, and Col4a2 in the liver (n = 4 for YO+Veh; n = 5 for YO+DQ). Data are means ± s.e.m. of biologically independent samples and each data point represents an individual mouse. A two-tailed t test with a Welch’s correction (b-d), Student’s t test (g-h) with *, P < 0.05; **, P < 0.01, multiple Mann-Whitney tests (e) and multiple t-tests (i) with a two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli, with Q = 5%, *q < 0.05 was used for statistical analysis. Scale bars are shown in each image. Rel, relative.
Extended Data Fig. 5 ABT263-treated old mouse serum abrogates senescence induction in non-senescent mouse cells (MDFs) in vivo and in culture.
(a) Representative luminescence images of young p16-3MR mice (3-month-old) receiving blood (22-month-old) from old C57BL/6J mice treated with vehicle (YO+Veh) or ABT263 (YO+ABT) 14 days after blood exchange (left) and quantification of the luminescence (right) (A.U.) (n = 4 mice for YO+Veh; n = 3 mice for YO+ABT). Each data point represents an individual mouse. (b) Representative EdU (green; EdU negative non-proliferating SnCs with arrows), HMGB1 (red; SnCs marked by nuclear loss with arrows), and Hoechst labeled nuclei (blue) visualized by immunostaining (n = 4 for each group / 5-8 images per n) and (c) SA-β-gal staining in MDFs cultured in Veh- or ABT-treated old mouse serum for 3 days (n = 4 for veh-treated old mice serum treated; n = 3 for ABT-treated old mouse serum; 3-6 images per n). Quantification of (d) EdU + and (e) SA-β-gal + MDFs. (f) mRNA levels for Cdkn2a and Cdkn1a and SASP factors Il6 and Mmp 3 days after culturing in Veh- or ABT-treated old mouse serum, determined by RT–PCR (n = 4 for each group). Data are means ± s.e.m. of biologically independent samples. Statistical significance was calculated using two-tailed Student’s t test (a, d-e) (exact P value was shown in the figures) and multiple t tests with a two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli, with Q = 5%, *q < 0.05 (f). Scale bars are shown in each image. Rel, relative.
Extended Data Fig. 6 Removal of SnCs by ABT263 inhibits age-related tissue phenotypes induced by an aged circulation in kidney and liver young tissues.
(a) Additional SA-β-gal images of kidney (left) and liver (right) in young C57BL/6J mice receiving old C57BL/6 blood treated with vehicle (YO+Veh) or ABT263 (YO+ABT). (b) HMGB1 immunohistochemistry (brown staining of HMGB1 re-localized to cytoplasm of kidney cells with arrows) (n = 5 per group; 10-15 images per mice). (c) Immunohistochemical staining for KIM-1 (n = 6 for YO+Veh; n = 4 for YO+ABT; 4-5 images per mice) and LTL (n = 5 per group; 5-7 images per mice) on kidney tissues and (d) quantification of KIM-1 + area (%). (e) Serum concentration of KIM-1 (n = 6 per group), (f) blood urea nitrogen (n = 12 for YO+Veh; n = 9 for YO+ABT) and creatine (n = 4 per group). (g) Representative images of Sirius Red (n = 6 for YO+Veh; n = 5 for YO+ABT; 10-15 images per mice) and Masson Trichrom staining and desmin immunohistochemistry (n = 6 mice for YO+Veh; n = 5 mice for YO+ABT; 10-15 images per mice) in livers. Arrows indicate collagen deposition. (h) Quantifications of fibrotic area, as % of area occupied by Sirius Red stain, and desmin + area (n = 6 for YO+Veh; n = 5 for YO+ABT). (i) Quantification of mRNAs encoding Col1a1, Col3a1, Col4a1 and Col4a2 in the liver (n = 6 per group). (j) Oil Red O + area (%) indicated as adiposity index (n = 6 per group; 5-9 images per mice). (k) Serum analyses for ALT (n = 8 for YO+Veh; n = 9 for YO+ABT) and bilirubin (n = 9 per group). All data are expressed as means± s.e.m. of biologically independent samples. A two-tailed t test with a Welch’s correction (d-f, h, j-k; *, P < 0.05) and multiple t test with a two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli, with Q = 5%, *q < 0.05; **q < 0.01 (i). Scale bars, 100 μm. Rel, relative.
Extended Data Fig. 7 Abrogation of senescence induction by ABT263 treatment of old mice before heterochronic apheresis attenuates the negative effects of old blood on skeletal muscle function.
(a) Representative images of Oil Red O staining and (b) % of Oil Red O + area in muscles of old mice receiving old blood (OO) or young blood (OY) mice 14 days after blood exchange (n = 6 mice for OO; n = 4 mice for OY; 6-10 images per mice). (c) Fibrosis index, calculated from images of H&E staining (n = 4 for OO; n = 5 for OY; 3 images per mice). (d) Skeletal muscle fatigue assessment (n = 4 for OO; n = 3 for OY) and (e) treadmill running distance in meters (n = 3 for OO; n = 4 for OY). (f) Maximal twitch force generated by muscles and maximal rate of contraction between onset of contraction and peak force and maximal rate of relaxation ranging from peak force until force had declined to baseline during contractions in YO+Veh and YO+ABT (n = 3 per group). (g) Representative images of Oil Red O and quantification of Oil Red O + staining of skeletal muscles (n = 7 mice for YO+Veh; n = 5 mice for YO+ABT; 5-8 images per mice). (h) Running distance in meters of on treadmill (n = 8 for YO+Veh; n = 6 for YO+ABT). (i) Measured energy expenditure and respiratory quotient (RQ) to assess ratio of CO2 produced to O2 consumed and food intake in metabolic cages during the day and night cycles (n = 6 for YO+Veh; n = 8 for YO+ABT). Data are the average of 4 day and night cycles for 4 consecutive days. Data are means ± s.e.m. of biologically independent samples. A two-tailed t test with a Welch’s correction (b-c, e), Student t-test (f-h) (*, P < 0.05), and one-way ANOVA, Tukey’s multiple comparison test with *, P < 0.05 (i) was used for statistical analysis. Scale bars, 100 µm.
Extended Data Fig. 8 Systemic cytokine levels in sera from young mice after heterochronic blood exchange and after blood exchange with old mice in which SnCs were removed by ABT263.
(a) Changes in cytokine levels in serum from YO+Veh and YO+ABT mice (n = 10 for each group). Box-and-whisker plots of log2-transformed fold change in mean fluorescence intensity (MFI) compared to the average of YO+Veh. (b) Changes in cytokine levels in serum from YY and YO mice (n = 10 for each group) using a Luminex array. Box-and-whisker plots of log2-transformed fold change in MFI compared to the average of YY. Box plots depict median, with whiskers indicating 10-90 percentile values of biologically independent samples. Statistical significance was calculated using 2-way RM ANOVA followed by two-stage step-up method of Benjamini, Krieger and Yekutieli, FDR < 0.05 (a-b). *q < 0.05; **q < 0.01; ***q < 0.001. (c) Venn diagram of serum proteins altered in young mice after blood exchange with old mice or with ABT263-treated old mice. The orange area indicates the four factors that increased in serum from YO compared to serum from YY (up YO). The blue area shows the six factors that decreased in YO+ABT compared to serum from YO+Veh (down YO+ABT). In the intersection of the orange and blue areas is one factor showing altered levels in both screens.
Extended Data Fig. 9 Removal of SnCs by ABT263 in young mice reduces capacity to induce senescence in young animals by blood exchange.
(a) Schematic showing isochronic pairings using blood exchange. Young C57BL/6J mice were exchanged with blood of young C57BL/6J mice either treated with vehicle (YY+Veh) or ABT263 (YY+ABT). (b) Fold change in gene expression of senescence and SASP markers, determined by RT–PCR, in skeletal muscle (gastrocnemius), kidney and liver of YY+ABT animals compared with YY+Veh 14 days after blood exchange. (c) Maximal twitch force generated by skeletal muscles, time to maximal rate of contraction and relaxation. (d) Skeletal muscle fatigue assessment. (e) Treadmill running distance in meters of YY+Veh and YY+ABT. Data are means ± s.e.m. of biologically independent samples and each data point represents an individual mouse. Data are collective of one independent experiment. n = 3 for each group in this experiment. Statistical significance was calculated using two-way ANOVA followed by two-stage step-up method of Benjamini, Krieger and Yekutieli, FDR < 0.05 (b) and two-tailed t-test with Welch’s correction (c, e), *P < 0.05. Rel, relative.
Extended Data Fig. 10 Systemic removal of SnCs by ABT263 in aged mice ablates rejuvenating effects by blood exchange.
(a) Schematic showing isochronic pairings using blood exchange. (b) Gene expression of senescence and SASP markers, in skeletal muscle (GA and TA), kidney and liver of old C57BL/6J mice receiving blood from old C57BL/6J mice treated with vehicle (OO+Veh) or ABT263 (OO+ABT) (n = 8 for OO+Veh; n = 5 for OO+ABT). (c) Absolute peak isometric torque of the plantarflexors, maximal rate of contraction between onset of contraction and peak force, and maximal rate of relaxation ranging from peak force until force had declined to baseline. (d) Skeletal muscle fatigue assessment (n = 4 for OO+Veh; n = 7 for OO+ABT). (e) Running distance in meters on treadmills (n = 9 for OO+Veh; n = 6 for OO+ABT). (f) Latency time to fall from the rotarod (n = 5 for OO+Veh; n = 7 for OO+ABT). (g) Serum analysis for KIM-1 (n = 7 for group) and blood urea nitrogen (n = 9 for OO+Veh; n = 7 for OO+ABT). (h) Adiposity (shown as a % of Oil Red O; n = 7 for OO+Veh; n = 6 for OO+ABT), collagen deposition (n = 5 for OO+Veh; n = 4 for OO+ABT), as the % of area occupied by Sirius Red stain, and desmin-positive-area (n = 5 for group). (i) Serum analysis for bilirubin and ALT (n = 6 for OO+Veh; n = 5 for OO+ABT). (j) Box-and-whisker plots of log2-transformed fold change in MFI compared to the average of OO+Veh. Box plots depict median, with whiskers indicating 10-90 percentile values (n = 6 for each group). Data are means ± s.e.m. Data are collective of two independent experiments. Multiple Mann-Whitney tests with a two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli, with Q = 5% (*q < 0.05; **q < 0.01) (b, j) and two-tailed t test with Welch’s correction, with *P < 0.05 (c, e-i) was used for statistical analysis. Rel, relative.
Supplementary information
Supplementary Information
Supplementary Figs. 1–6.
Supplementary Tables
Supplementary Table 1. Haematology profile in old mice before and after treated with vehicle (Veh) or ABT263 (ABT), Supplementary Table 2. Primers sequences used for RT–PCR, Supplementary Table 3. Scores used for pathological assessment of kidney.
Supplementary Data 1
Statistical source data.
Supplementary Data 2
Statistical source data.
Supplementary Data 3
Statistical source data.
Supplementary Data 4
Statistical source data.
Supplementary Data 5
Statistical source data.
Source data
Source Data Fig. 1
Statistical source data.
Source Data Fig. 2
Statistical source data.
Source Data Fig. 3
Statistical source data.
Source Data Fig. 4
Statistical source data.
Source Data Extended Data Fig. 1
Statistical source data.
Source Data Extended Data Fig. 2
Statistical source data.
Source Data Extended Data Fig. 3
Statistical source data.
Source Data Extended Data Fig. 4
Statistical source data.
Source Data Extended Data Fig. 5
Statistical source data.
Source Data Extended Data Fig. 6
Statistical source data.
Source Data Extended Data Fig. 7
Statistical source data.
Source Data Extended Data Fig. 8
Statistical source data.
Source Data Extended Data Fig. 9
Statistical source data.
Source Data Extended Data Fig. 10
Statistical source data.
Rights and permissions
About this article
Cite this article
Jeon, O.H., Mehdipour, M., Gil, TH. et al. Systemic induction of senescence in young mice after single heterochronic blood exchange. Nat Metab 4, 995–1006 (2022). https://doi.org/10.1038/s42255-022-00609-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s42255-022-00609-6
This article is cited by
-
Plasma exosomes improve peripheral neuropathy via miR-20b-3p/Stat3 in type I diabetic rats
Journal of Nanobiotechnology (2023)
-
Metformin potentiates nephrotoxicity by promoting NETosis in response to renal ferroptosis
Cell Discovery (2023)
-
Lysosomal control of senescence and inflammation through cholesterol partitioning
Nature Metabolism (2023)
-
Recent insights into the crosstalk between senescent cells and CD8 T lymphocytes
npj Aging (2023)
-
Aged hematopoietic stem cells entrap regulatory T cells to create a prosurvival microenvironment
Cellular & Molecular Immunology (2023)
