The ageing systemic milieu negatively regulates neurogenesis and cognitive function

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In the central nervous system, ageing results in a precipitous decline in adult neural stem/progenitor cells and neurogenesis, with concomitant impairments in cognitive functions1. Interestingly, such impairments can be ameliorated through systemic perturbations such as exercise1. Here, using heterochronic parabiosis we show that blood-borne factors present in the systemic milieu can inhibit or promote adult neurogenesis in an age-dependent fashion in mice. Accordingly, exposing a young mouse to an old systemic environment or to plasma from old mice decreased synaptic plasticity, and impaired contextual fear conditioning and spatial learning and memory. We identify chemokines—including CCL11 (also known as eotaxin)—the plasma levels of which correlate with reduced neurogenesis in heterochronic parabionts and aged mice, and the levels of which are increased in the plasma and cerebrospinal fluid of healthy ageing humans. Lastly, increasing peripheral CCL11 chemokine levels in vivo in young mice decreased adult neurogenesis and impaired learning and memory. Together our data indicate that the decline in neurogenesis and cognitive impairments observed during ageing can be in part attributed to changes in blood-borne factors.

At a glance


  1. Heterochronic parabiosis alters neurogenesis in an age-dependent fashion.
    Figure 1: Heterochronic parabiosis alters neurogenesis in an age-dependent fashion.

    a, Schematic showing parabiotic pairings. b, e, Representative fields of Dcx (b) and BrdU (e) immunostaining of young (3–4 months; yellow) and old (18–20 months; grey) isochronic and heterochronic parabionts 5 weeks after parabiosis (arrowheads point to individual cells; scale bars, 100μm). cf, Quantification of neurogenesis (c, d) and proliferating cells (e, f) in the young (c, e; top) and old (d, f; bottom) dentate gyrus (DG) after parabiosis. Data from 12 young isochronic, 10 young heterochronic, 6 old isochronic and 12 old heterochronic parabionts. g, h, Population spike amplitude (PSA) was recorded from the dentate gyrus of young parabionts. Representative electrophysiological profiles (g) and LTP levels (h) are shown for young heterochronic and isochronic parabionts. Data from 4–5 mice per group. All are data represented as mean + s.e.m.; *P<0.05; **P<0.01, t-test.

  2. Factors from an old systemic environment decrease neurogenesis and impair learning and memory.
    Figure 2: Factors from an old systemic environment decrease neurogenesis and impair learning and memory.

    a, Schematic of young (3–4 months) or old (18–22 months) plasma extraction and intravenous (i.v.) injection into young (3 months) adult mice. b, Representative field of Dcx immunostaining of young adult mice after plasma injection treatment four times over 10 days (scale bar, 100μm). c, Quantification of neurogenesis in the young dentate gyrus after plasma injection. Data from 8 mice injected with young plasma and 7 mice injected with old plasma. d, e, Hippocampal learning and memory assessed by contextual fear conditioning (d) and RAWM (e) paradigms in young adult mice after young or old plasma injections nine times over 24 days. d, Percent freezing time 24h after training. Data from 8 mice per group. e, Number of entry arm errors before finding platform. Data from 12 mice per group. All data represented as mean±s.e.m.; *P<0.05; **P<0.01, t-test (c, d), repeated measures ANOVA, Bonferroni post-hoc test (e).

  3. Systemic chemokine levels increase during ageing and heterochronic parabiosis, and correlate with decreased neurogenesis.
    Figure 3: Systemic chemokine levels increase during ageing and heterochronic parabiosis, and correlate with decreased neurogenesis.

    a, Venn diagram of results from ageing and parabiosis proteomic screens. In grey are shown the seventeen age-related plasma factors that correlated most strongly with decreased neurogenesis, in red are shown the fifteen plasma factors that increased between young isochronic and young heterochronic parabionts, and in the brown intersection are the six factors elevated in both screens. Data from 5–6 mice per age group. b, c, Changes in plasma concentrations of CCL11 with age (b) and young heterochronic parabionts pre- and post- parabiotic pairing (c). d, e, Changes in plasma (d; r = 0.40; P = 5.6×10−7; 95% confidence interval = 0.26–0.53) and CSF (e) concentrations of CCL11 with age in healthy human subjects. All data represented as dot plots with mean; *P<0.05; **P<0.01; ***P<0.001, t-test (c, e), ANOVA, Tukey’s post-hoc test (a, b), and Mann–Whitney U Test (d).

  4. Systemic exposure to CCL11 inhibits neurogenesis and impairs learning and memory.
    Figure 4: Systemic exposure to CCL11 inhibits neurogenesis and impairs learning and memory.

    a, Schematic of young (3–4 months) mice injected intraperitoneally with CCL11 or vehicle, and in combination with anti-CCL11 neutralizing or isotype control antibody (Ab). b, Representative field of Dcx-positive cells for each treatment group (n = 6–10 mice) treated four times over 10 days. i.p., intraperitoneal. Scale bar, 100μm. c, Quantification of neurogenesis in the dentate gyrus after treatment. d, Schematic of young adult mice given unilateral stereotaxic injections of anti-CCL11 neutralizing or isotype control antibody followed by systemic injections with either recombinant CCL11 or PBS (vehicle). e, Representative field of Dcx-positive cells in adjacent sides of the dentate gyrus for each treatment group (n = 3–11 mice). Scale bar, 100μm. f, Quantification of neurogenesis in the dentate gyrus after systemic and stereotaxic treatment. Bars represent mean number of cells in each section. g, h, Learning and memory assessed by contextual fear conditioning (g) and RAWM (h) paradigms in young adult mice injected with CCL11 or vehicle every 3 days for 5 weeks (n = 12–16 mice per group). All data are represented as mean±s.e.m.; *P<0.05; **P<0.01; ANOVA, Dunnet’s or Tukey’s post-hoc test (c, f); repeated measures ANOVA, Bonferroni post-hoc test (k).


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Author information


  1. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California 94305, USA

    • Saul A. Villeda,
    • Jian Luo,
    • Kira I. Mosher,
    • Markus Britschgi,
    • Gregor Bieri,
    • Trisha M. Stan,
    • Nina Fainberg,
    • Zhaoqing Ding,
    • Alexander Eggel,
    • Kurt M. Lucin,
    • Eva Czirr,
    • Jeong-Soo Park,
    • Thomas A. Rando &
    • Tony Wyss-Coray
  2. Neuroscience IDP Program, Stanford University School of Medicine, Stanford, California 94305, USA

    • Saul A. Villeda,
    • Kira I. Mosher &
    • Tony Wyss-Coray
  3. AfaSci Research Laboratory, Redwood City, California, 94063, USA

    • Bende Zou &
    • Xinmin S. Xie
  4. School of Life Sciences, Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland

    • Gregor Bieri
  5. Immunology IDP Program, Stanford University School of Medicine, Stanford, California 94305, USA

    • Trisha M. Stan,
    • Zhaoqing Ding &
    • Tony Wyss-Coray
  6. Institute of Molecular Regenerative Medicine, Paracelsus Medical University, Strubergasse 21, A-5020 Salzburg, Austria

    • Sebastien Couillard-Després &
    • Ludwig Aigner
  7. Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, Washington 98108-1597, USA

    • Ge Li &
    • Elaine R. Peskind
  8. Veterans Affairs Northwest Network Mental Illness Research, Education, and Clinical Center, Seattle, Washington 98108-1597, USA

    • Elaine R. Peskind
  9. Layton Aging & Alzheimer's Disease Center, Oregon Health and Science University, CR131, 3181 SW Sam Jackson Park Road, Portland, Oregon 97201-3098, USA; and Portland VA Medical Center, Portland, Oregon 97207, USA

    • Jeffrey A. Kaye &
    • Joseph F. Quinn
  10. Department of Neurosciences, University of California San Diego, 9500 Gilman Drive #0948, La Jolla, California 92093-0948, USA

    • Douglas R. Galasko
  11. Center for Tissue Regeneration, Repair and Restoration, VA Palo Alto Health Care System, Palo Alto, California 94304, USA

    • Thomas A. Rando &
    • Tony Wyss-Coray
  12. The Glenn Laboratories for the Biology of Aging, Stanford University School of Medicine, Stanford, California 94305, USA

    • Thomas A. Rando
  13. Present addresses: CNS Discovery, pRED, F. Hoffmann-La Roche Ltd., CH-4070 Basel, Switzerland (M.B.); Department of Biochemistry, College of Medicien, Dankook University, Cheonan 330-714, South Korea (J.S.P.).

    • Markus Britschgi &
    • Jeong-Soo Park


S.A.V. and T.W.-C. developed the concept and designed all experiments. S.A.V. and J.L. designed and performed in vivo experiments. S.A.V. performed behavioural experiments. K.I.M. assisted with surgery. B.Z. and X.S.X. performed electrophysiology. M.B. and A.E. analysed human data. G.B. assisted with fear conditioning and irradiation analysis. S.A.V., T.M.S. and J.-S.P. performed in vitro experiments. T.M.S. assisted with MCSF analysis. N.F. assisted with radial arm maze. Z.D. performed flow cytometry. K.M.L. performed irradiation. E.C. assisted with in vivo plasma experiments. D.R.G., G.L., E.R.P., J.A.K. and J.F.Q. identified aging subjects and provided human samples. S.C.-D. and L.A. provided reagents and mice. T.A.R. provided reagents, conceptual advice and edited the manuscript. S.A.V. collected data, performed data analysis and generated figures. S.A.V. and T.W.-C. wrote the manuscript. T.W.-C. supervised all aspects of this project. All authors had the opportunity to discuss results and comment on the manuscript.

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