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PD1 blockade improves survival and CD8+ cytotoxic capacity, without increasing inflammation, during normal microbial experience in old mice

Nature Aging (2024)Cite this article

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Abstract

By 2030, individuals 65 years of age or older will make up approximately 20% of the world’s population1. Older individuals are at the highest risk for mortality from infections, largely due to the pro-inflammatory, dysfunctional immune response, which is collectively known as immunosenescence2. During aging, CD8+ T cells acquire an exhausted phenotype, including increased expression of inhibitory receptors, such as programmed cell death 1 (PD1), a decline in effector function and elevated expression of inflammatory factors3,4,5,6,7. PD1 reduces T cell receptor activity via SHP2-dependent dephosphorylation of multiple pathways; accordingly, inhibiting PD1 activity through monoclonal antibodies increases CD8+ T cell effector response in young mice8,9,10,11. Attempts to improve CD8+ T cell responses by blocking inhibitory receptors are attractive; however, they can lead to adverse immune events due to overamplification of T cell receptor signaling and T cell activation12,13. Here we investigated the effect of monoclonal anti-PD1 immunotherapy during normal microbial experience, otherwise known as exposure to dirty mice, to determine whether it either improves exhausted CD8+ T cell responses in old mice or leads to a heightened inflammatory response and increased mortality.

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Fig. 1: Inflammation is increased in old mice after NME.
Fig. 2: CD8+ T cells bearing markers of exhaustion are expanded in old mice after NME.
Fig. 3: PD1 checkpoint blockade improves survival to NME in old mice.
Fig. 4: PD1 checkpoint blockade improves CD8+ T cell cytotoxic capacity.

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Data availability

All genomics and sequencing data will be publicly available at the Gene Expression Omnibus (GEO) on the date of publication under accession number GSE250165. All other data supporting the findings of this study are available as source data files or from the corresponding author upon reasonable request. Source data are provided with this paper.

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Acknowledgements

BioRender was used to generate schematics under the following agreement numbers: KB26KBLQB7, MN26KBLQDJ, LB26KBLQFA, FT26KBLQH9, DG26KBLQIS, EY26KBLQMN, AY26KBLQOD, JC26KBLQQ6, VS26KBLQRO, XG26KBLQTV and FT26KBLQVN. We also acknowledge and thank the University of Minnesota Flow Cytometry Resource, the University of Minnesota Genomic Center and J. E. Abrahante Lloréns for the use of their machines and expertise. This work was supported by National Institutes of Health grants R00AG058800 (C.D.C.), R21AG078638 (C.D.C.), R01AG079913-01 (C.D.C.) and R01AI155468 (S.E.H.) and T32AG029796 (K.J.V.D.); the Fesler-Lampert Chair in Aging Studies (C.D.C.); the Glenn Foundation for Medical Research/AFAR Grants for Junior Faculty (C.D.C.); the McKnight Land-Grant (C.D.C.); the Irene Diamond Fund/AFAR Postdoctoral Transition Award (M.J.Y.); the Medical Discovery Team on the Biology of Aging (C.D.C.); and a Longevity Impetus Grant from the Norn Group (K.J.V.D.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Biochemistry, Molecular Biology and Biophysics Graduate Program, Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA

    Korbyn J. V. Dahlquist & Christina D. Camell

  2. Department of Biochemistry, Molecular Biology and Biophysics, Institute on the Biology of Aging and Metabolism, University of Minnesota, Minneapolis, MN, USA

    Korbyn J. V. Dahlquist, Matthew J. Yousefzadeh, Carolina Soto-Palma, Stephanie H. Cholensky, Declan M. Smith, Sara E. Hamilton & Christina D. Camell

  3. Center for Immunology, University of Minnesota, Minneapolis, MN, USA

    Korbyn J. V. Dahlquist, Matthew A. Huggins, Mark Pierson, Sara E. Hamilton & Christina D. Camell

  4. Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA

    Matthew A. Huggins, Mark Pierson & Sara E. Hamilton

  5. Department of Medicine, Columbia Center for Translational Immunology, Columbia Center for Healthy Longevity, Columbia University, New York, NY, USA

    Matthew J. Yousefzadeh

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Contributions

K.J.V.D. carried out most experiments. M.A.H., M.J.Y., S.H.C., M.P., D.M.S. and C.D.C. assisted with experiments. C.S-P. performed bioinformatics analysis. S.E.H. provided insight into experimental design and interpretation of data. K.J.V.D. and C.D.C. conceived the project, analyzed the data and wrote the paper. All authors read, edited and approved the final version of the paper.

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Correspondence to Christina D. Camell.

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Nature Aging thanks Nicole La Gruta, Janet Lord 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 Inflammation is increased in old mice after NME.

(a-b) Experiment 2. a. Enrichment plots of selected upregulated pathways (IL6 JAK STAT3 signaling, Inflammatory response, TNFA signaling via NFKB and Interferon Gamma Response). b. Enrichment plots of selected downregulated pathways (Bile acid metabolism and Fatty Acid Metabolism). (c) Experiment 4. c. Survival curve measured for 30 days after initiation of NME. (1-month NCD n = 8, 1-month HFD n = 8). P-value: P > 0.9999(ns). (d) Experiment 5. d. Survival curve measured for 30 days after initiation of NME. (5-month NCD n = 8, 5-month HFD n = 8). P-value: P > 0.9999(ns). (e) Experiment 6. e. Survival curve measured for 30 days after initiation of NME. (6-month NCD n = 8, 6-month HFD n = 5). P-value: P = 0.7519(ns). Statistical significance was determined with Log-rank (Mantel Cox) test (c-e). All data are presented as Means ± SEM. All p-values can be found in source data.

Source data

Extended Data Fig. 2 CD8+ T-cells bearing markers of exhaustion are expanded in old mice after NME.

(a-e,i-j) Experiment 2. a. CD45+ Live and IV− gating in liver, lung, spleen, and mLN. b. IV− cells as a percentage of CD45+ Live cells in the lung, spleen, and mLN. P-values: Lung: young SPF vs old SPF P = 4.766E-06(****), young SPF vs old NME P = 0.0003(***), old SPF vs young NME P = 4.569E-07(****), young NME vs old NME P = 1.5592E-05(****). c. IV− leukocyte subsets in mLN. d. CD73+ IgM− cells as a percentage of IV- B220+ cells in the liver, lung, mLN, and spleen. P-values: Liver: young SPF vs old NME P = 0.0175(*), old SPF vs old NME P = 0.0199(*), young NME vs old NME P = 3.4536E-06(****); Lung: young SPF vs old NME P = 0.0216(*), old SPF vs old NME P = 0.0499(*), young NME vs old NME P = 9.0894E-05(****); Spleen: young SPF vs old NME P = 0.0001(***), old SPF vs old NME P = 0.0005(***), young NME vs old NME P = 1.2504E-09(****). e. Memory cell subsets as a frequency of IV- CD8+ PD1+ cells. f. Representative contour plots of PD1 spleen expression by IV− CD45+ CD4+ CD44+ cells. Numbers are average frequencies. (g-h) Experiment 9. g. PD1+ cells as a percentage of NK cells or h. NKT cells in the liver, lung, mLN, and spleen. P-values: Liver: old SPF vs young NME P = 2.750E-06(****), young NME vs old NME P = 0.0015(**). i. CXCR5+ cells or j. KLRG1+ cells as a percentage of CD8+ IV− CD45+ live cells in the liver, lung, mLN, and spleen. P-values: Lung: young NME vs old NME P = 0.0018(**); mLN: young SPF vs young NME P = 0.0440(*). Statistical significance was determined with two-way ANOVA with Tukey’s (b,d,i,j) or Šidák multiple comparisons test (c,g,h). All data are presented as Means ± SEM. All p-values can be found in source data.

Source data

Extended Data Fig. 3 PD1 checkpoint blockade improves survival to NME in old mice.

(a) Experiments 9 and 11. a. Anti-PD1 intervention and prevention day 7 experimental schematic. (b-e) Experiment 17. b. Young anti-PD1 prevention survival experimental schematic. c. Survival curve measured for 30 days after initiation of NME. P-value: P = 0.5064(ns). d. GzmB+ cells as a percentage of CD8+ CD44+ PD1+ cells in young isotype or prevention anti-PD1 treated mice exposed to NME through cohousing. P-value: P = 0.9130(ns). e. Quantification of GzmB+ cells as a percentage of CD8+ CD44+ PD1− cells in young isotype or prevention anti-PD1 treated mice exposed to NME through cohousing. P-value: P = 0.5179(ns). Statistical significance was determined with Log-rank (Mantel Cox) test (c) or unpaired two-tailed t-test with 95% confidence (d-e). All data are presented as Means ± SEM. All p-values can be found in source data.

Source data

Extended Data Fig. 4 PD1 checkpoint blockade improves CD8+ T-cell cytotoxic capacity.

(a) Experiment 12. a. Representative flow cytometry contour plots in spleen and liver on day 7 of NME indicating depletion efficacy. (b-c) Experiment 13. b. IFNγ and TNFα expression as a percentage of CD8+ CD44+ PD1+ cells or c. PD1− cells after stimulation with PMA+ ionomycin. (d) Experiment 15. d. GzmB+ cells as a frequency of CD8+ PD1+ cells from blood. P-value: old anti-PD1 lived P = 0.0047(**). (e-g) Experiment 14. e. Anti-PD1 SPF day 7 experimental schematic. f. GzmB+ cells as a percentage of CD8+ CD44+ PD1+ cells from old SPF mice. P-value: P = 0.9081(ns). g. GzmB+ cells as a percentage of CD8+ CD44+ PD1− cells from old SPF mice. P-value: P = 0.4928(ns). (h-i) Experiment 18. h. GzmB+ cells as a percentage of IV− CD8+ CD44+ CD62L− PD1+ cells in young and old mice after fisetin treatment or vehicle control. P-values: Liver: young vehicle vs old fisetin P = 0.0014(**), young fisetin vs old fisetin P = 0.0358(*), old vehicle vs old fisetin P = 0.4195(ns); spleen: old vehicle vs old fisetin P = 0.9922(ns). i. GzmB+ cells as a percentage of IV+ CD8+ CD44+ CD62L− PD1+cells in young and old mice after fisetin treatment or vehicle control. P-values: Liver: young vehicle vs old fisetin P = 0.0432(*), young fisetin vs old vehicle P = 0.0147(*), young fisetin vs old fisetin P = 0.0094(**), old vehicle vs old fisetin P = 0.9974(ns); spleen: old vehicle vs old fisetin P = 0.7303(ns). Statistical significance was determined with multiple unpaired two-tailed t-tests with 95% confidence (b-c) or RM two-way ANOVA with Šidák multiple comparisons test (d) or unpaired two-tailed t-test with 95% confidence (f-g) or two-way ANOVA with Tukey’s multiple comparisons test (h-i). All data are presented as Means ± SEM. All p-values can be found in source data.

Source data

Extended Data Fig. 5 Representative gating strategies 1.

a. Representative flow cytometry pseudocolor plots for flow cytometry data shown in Fig. 2 and Extended Data Fig. 2.

Extended Data Fig. 6 Representative gating strategies 2.

a. Representative flow cytometry pseudocolor plots for flow cytometry data shown in Figs. 2–4 and Extended Data Figs. 2–4.

Supplementary information

Supplementary Information

Supplementary Table 1.

Reporting Summary

Supplementary Table 2

Liver GSEA upregulated genes.

Supplementary Table 3

Liver GSEA downregulated genes.

Source data

Source Data Fig. 1

Raw data, statistics and P values for Fig. 1.

Source Data Fig. 2

Raw data, statistics and P values for Fig. 2.

Source Data Fig. 3

Raw data, statistics and P values for Fig. 3.

Source Data Fig. 4

Raw data, statistics and P values for Fig. 4.

Source Data Extended Data Fig. 1

Raw data, statistics and P values for Extended Data Fig. 1.

Source Data Extended Data Fig. 2

Raw data, statistics and P values for Extended Data Fig. 2.

Source Data Extended Data Fig. 3

Raw data, statistics and P values for Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Raw data, statistics and P values for Extended Data Fig. 4.

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Dahlquist, K.J.V., Huggins, M.A., Yousefzadeh, M.J. et al. PD1 blockade improves survival and CD8+ cytotoxic capacity, without increasing inflammation, during normal microbial experience in old mice. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00620-4

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