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Demographically framing trade-offs between sensitivity and specificity illuminates selection on immunity

Nature Ecology & Evolutionvolume 1pages17661772 (2017) | Download Citation

Abstract

A fundamental challenge faced by the immune system is to discriminate contexts meriting activation from contexts in which activation would be harmful. Selection pressures on this ability are likely to be acute: the penalty of mis-identification of pathogens (therefore failure to attack them) is mortality or morbidity linked to infectious disease, which could reduce fitness by reducing lifespan or fertility; the penalty associated with mis-identification of host (therefore self-attack) is immunopathology, whose fitness costs can also be extreme. Here we use classic epidemiological tools to frame this trade-off between sensitivity and specificity of immune activation, exploring implications for evolution of immune discrimination. We capture the expected increase in the evolutionarily optimal sensitivity under higher pathogen mortality risk, and a decrease in sensitivity with increased immunopathology mortality risk; but a number of non-intuitive predictions also emerge. All else being equal, optimal sensitivity decreases with increasing lifespan; and, where sensitivity can vary over age, decreases at late ages not solely attributable to immunosenescence are predicted. These results both enrich and challenge previous predictions concerning the relationship between life expectancy and optimal evolved defenses, highlighting the need to account for epidemiological setting, lifestage-specific immune priorities, and immune discrimination in future investigations.

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References

  1. 1.

    Land, W. G. How evolution tells us to induce allotolerance. Exp. Clin. Transplant. 13, 46–54 (2015).

  2. 2.

    Chen, G. Y. & Nuñez, G. Sterile inflammation: sensing and reacting to damage. Nat. Rev. Immunol. 10, 826–837 (2010).

  3. 3.

    Rathinam, V. A. K., Vanaja, S. K. & Fitzgerald, K. A. Regulation of inflammasome signaling. Nat. Immunol. 13, 333–342 (2012).

  4. 4.

    Crișan, T. O., Netea, M. G. & Joosten, L. A. Innate immune memory: implications for host responses to damage‐associated molecular patterns. Eur. J. Immunol. 46, 817–828 (2016).

  5. 5.

    Pradeu, T. & Cooper, E. L. The danger theory: 20 years later. Front. Immunol. 3, 287 (2012).

  6. 6.

    Tate, A. T. & Graham, A. L. Dynamic patterns of parasitism and immunity across host development influence optimal strategies of resource allocation. Am. Nat. 186, 495–512 (2015).

  7. 7.

    Graham, A. L., Allen, J. E. & Read, A. F. Evolutionary causes and consequences of immunopathology. Annu. Rev. Ecol. Evol. Syst. 36, 373–397 (2005).

  8. 8.

    Råberg, L., Graham, A. L. & Read, A. F. Decomposing health: tolerance and resistance to parasites in animals. Phil. Trans. R. Soc. B 364, 37–49 (2009).

  9. 9.

    Cressler, C. E., Graham, A. L. & Day, T. Evolution of hosts paying manifold costs of defence. Proc. R. Soc. B 282, 20150065 (2015).

  10. 10.

    Frank, S. A. Immune response to parasitic attack: evolution of a pulsed character. J. Theor. Biol. 219, 281–290 (2002).

  11. 11.

    Hurford, A. & Day, T. Immune evasion and the evolution of molecular mimicry in parasites. Evolution 67, 2889–2904 (2013).

  12. 12.

    Ang, C. W., Jacobs, B. C. & Laman, J. D. The Guillain–Barré syndrome: a true case of molecular mimicry. Trends Immunol. 25, 61–66 (2004).

  13. 13.

    Lazzaro, B. P. & Rolff, J. Danger, microbes, and homeostasis. Science 332, 43–44 (2011).

  14. 14.

    Perelson, A. S. & Oster, G. F. Theoretical studies of clonal selection: minimal antibody repertoire size and reliability of self–non-self discrimination. J. Theor. Biol. 81, 645–670 (1979).

  15. 15.

    Nesse, R. M. Natural selection and the regulation of defenses: a signal detection analysis of the smoke detector principle. Evol. Hum. Behav. 26, 88–105 (2005).

  16. 16.

    Simmen, M. W. Genome-scale relationships between cytosine methylation and dinucleotide abundances in animals. Genomics 92, 33–40 (2008).

  17. 17.

    Rima, B. K. & McFerran, N. V. Dinucleotide and stop codon frequencies in single-stranded RNA viruses. J. Gen. Virol. 78, 2859–2870 (1997).

  18. 18.

    Greenbaum, B. D., Levine, A. J., Bhanot, G. & Rabadan, R. Patterns of evolution and host gene mimicry in influenza and other RNA viruses. PLoS Pathog. 4, e1000079 (2008).

  19. 19.

    Boots, M., Donnelly, R. & White, A. Optimal immune defence in the light of variation in lifespan. Parasite Immunol. 35, 331–338 (2013).

  20. 20.

    Mayer, A., Thierry, M., Rivoire, O. & Walczak, A. M. Diversity of immune strategies explained by adaptation to pathogen statistics. Proc. Natl Acad. Sci. USA 113, 8630–8635 (2016).

  21. 21.

    Hamilton, W. D. The moulding of senescence by natural selection. J. Theor. Biol. 12, 12–45 (1966).

  22. 22.

    Baudisch, A. Hamilton’s indicators of the force of selection. Proc. Natl Acad. Sci. USA 102, 8263–8268 (2005).

  23. 23.

    Anderson, R. M. & May, R. M. Infectious Diseases of Humans. (Oxford Univ. Press, Oxford, 1991).

  24. 24.

    Mossong, J. et al. Social contacts and mixing patterns relevant to the spread of infectious diseases. PloS Med. 5, e74 (2008).

  25. 25.

    Shaw, A. C., Goldstein, D. R. & Montgomery, R. R. Age-dependent dysregulation of innate immunity. Nat. Rev. Immunol. 13, 875–887 (2013).

  26. 26.

    Khan, I., Agashe, D. & Rolff, J. Early-life inflammation, immune response and ageing. Proc. R. Soc. B 284, 20170125 (2017).

  27. 27.

    Urban, M. C., Bürger, R. & Bolnick, D. I. Asymmetric selection and the evolution of extraordinary defences. Nat. Commun. 4, 2085 (2013).

  28. 28.

    Katzourakis, A. et al. Larger mammalian body size leads to lower retroviral activity. PLoS Pathog. 10, e1004214 (2014).

  29. 29.

    Morran, L. T., Schmidt, O. G., Gelarden, I. A., Parrish, R. C. II & Lively, C. M. Running with the Red Queen: host–parasite coevolution selects for biparental sex. Science 333, 216–218 (2011).

  30. 30.

    Gaunt, E. et al. Elevation of CpG frequencies in influenza A genome attenuates pathogenicity but enhances host response to infection. eLife 5, e12735 (2016).

  31. 31.

    Martin, L. B. II, Weil, Z. M. & Nelson, R. J. Immune defense and reproductive pace of life in Peromyscus mice. Ecology 88, 2516–2528 (2007).

  32. 32.

    Pohar, J. et al. Species-specific minimal sequence motif for oligodeoxyribonucleotides activating mouse TLR9. J. Immunol. 195, 4396–4405 (2015).

  33. 33.

    Pohar, J., Kužnik Krajnik, A., Jerala, R. & Benčina, M. Minimal sequence requirements for oligodeoxyribonucleotides activating human TLR9. J. Immunol. 194, 3901–3908 (2015).

  34. 34.

    Renshaw, M. et al. Cutting edge: impaired Toll-like receptor expression and function in aging. J. Immunol. 169, 4697–4701 (2002).

  35. 35.

    Simon, A. K., Hollander, G. A. & McMichael, A. Evolution of the immune system in humans from infancy to old age. Proc. R. Soc. B 282, 20143085 (2015).

  36. 36.

    de Jong, M. D. et al. Fatal outcome of human influenza A (H5N1) is associated with high viral load and hypercytokinemia. Nat. Med. 12, 1203–1207 (2006).

  37. 37.

    Long, G. H. & Graham, A. L. Consequences of immunopathology for pathogen virulence evolution and public health: malaria as a case study. Evol. Appl. 4, 278–291 (2011).

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Acknowledgements

A.L.G. was supported by an ETH Zürich Gastprofessorship.

Author information

Affiliations

  1. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA

    • C. Jessica E. Metcalf
    •  & Andrea L. Graham
  2. Office of Population Research, Princeton University, Princeton, NJ 08544, USA

    • C. Jessica E. Metcalf
  3. Department of Biological Sciences, Vanderbilt University, Nashville, TN 37240, USA

    • Ann T. Tate

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Contributions

C.J.E.M. conceived the idea; A.L.G., C.J.E.M. and A.T.T. wrote the draft.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to C. Jessica E. Metcalf.

Electronic supplementary material

  1. Supplementary Information

    Supplementary Figures 1–4

  2. Supplementary Code

    EvolDiscrim.R—Annotated R code needed to repeat the analysis

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DOI

https://doi.org/10.1038/s41559-017-0315-3

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