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Antagonistic pleiotropy and mutation accumulation influence human senescence and disease

Nature Ecology & Evolution volume 1, Article number: 0055 (2017) Cite this article

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Matters Arising to this article was published on 24 June 2019

Abstract

Senescence has long been a public health challenge as well as a fascinating evolutionary problem. There is neither a universally accepted theory for its ultimate causes, nor a consensus about what may be its impact on human health. Here we test the predictions of two evolutionary explanations of senescence—mutation accumulation and antagonistic pleiotropy—which postulate that genetic variants with harmful effects in old ages can be tolerated, or even favoured, by natural selection at early ages. Using data from genome-wide association studies (GWAS), we study the effects of genetic variants associated with diseases appearing at different periods in life, when they are expected to have different impacts on fitness. Data fit theoretical expectations. Namely, we observe higher risk allele frequencies combined with large effect sizes for late-onset diseases, and detect a significant excess of early–late antagonistically pleiotropic variants that, strikingly, tend to be harboured by genes related to ageing. Beyond providing systematic, genome-wide evidence for evolutionary theories of senescence in our species and contributing to the long-standing question of whether senescence is the result of adaptation, our approach reveals relationships between previously unrelated pathologies, potentially contributing to tackling the problem of an ageing population.

Senescence, the biological process of organismic decay with ageing, is coupled with an increased risk of certain diseases. With an estimated threefold increase in the number of people above age 80 yr in the next half century1, age-related diseases pose a global public health challenge. Knowledge of the evolutionary causes of senescence could contribute new strategies for managing age-related diseases. While many evolutionary hypotheses on the causes of senescence have been proposed2, the most established ones are the mutation accumulation (MA) theory3, the antagonistic pleiotropy (AP) theory of senescence4 and the disposable soma (DS) theory5. The two first hypotheses rely on the reduced efficiency of natural selection with increased age. The MA theory proposes that deleterious mutations with effects expressed later in life should be more difficult for natural selection to eliminate6. The AP theory adds an adaptive aspect: mutations that are damaging for the organism later in life (and hence contribute to senescence) could actually be favoured by natural selection if they are advantageous early in life, resulting in increased reproductive success of their carriers7,8. Finally the DS theory suggests that organisms face a trade-off between dedicating energy to reproduction or investing it in the maintenance and growth of their somas. The AP and DS theories both suggest that senescence is simply a by-product of an investment early in life and, indeed, many authors agree that DS is a particular instance of AP9,10. While AP specifies that genetic variants favoured in the fertile stages may cause ageing or physiological decay later in life, DS specifies that senescence occurs because of genetic variants favoured when fostering reproduction at the cost of impairing the growth and maintenance of the somatic parts of the organism, which will eventually lead to the accumulation of molecular and cellular damage. Besides these three, other evolutionary hypotheses have also been proposed (Supplementary Information section 1). As senescence is a highly complex phenomenon, ideas about it are better understood as complementing than as excluding each other. Still, each theory makes predictions that suggest ways of testing them. For instance, the MA and the AP hypotheses both predict that specific mutations in particular genes will cause senescence, while the DS theory is based on the general failure of repair mechanisms, which will lead to stochastic accumulation of molecular and cellular damage.

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Figure 1: Evidence for mutation accumulation and antagonistic pleiotropy from characteristics of disease-associated SNPs in GWAS.

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Acknowledgements

This work was supported by Ministerio de Ciencia e Innovación, Spain (SAF2011-29239 to E.B., and BFU2012-38236 and BFU2015-68649-P to A.N.), by Direcció General de Recerca, Generalitat de Catalunya (2014SGR1311 and 2014SGR866), by the Spanish National Institute of Bioinfomatics of the Instituto de Salud Carlos III (PT13/0001/0026) and by FEDER (Fondo Europeo de Desarrollo Regional)/FSE (Fondo Social Europeo). U.M.M. is supported by Project 3 of NIGMS P01 GM099568 (B. Weir, University of Washington). E.B. is the recipient of an ICREA Academia Award. The authors thank J. Bertranpetit, P. Muñoz-Cánoves, R. Nesse and B. Charlesworth for helpful comments and advice. We also thank H. Laayouni, F. Casals and F. Calafell for comments on the manuscript, and the Navarro Lab members, especially D. Hartasánchez and M. Brasó, for discussion and comments.

Author information

Authors and Affiliations

  1. Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain

    Juan Antonio Rodríguez, Urko M. Marigorta, David A. Hughes, Nino Spataro, Elena Bosch & Arcadi Navarro

  2. School of Biology, Georgia Institute of Technology, Atlanta, 30332, Georgia, USA

    Urko M. Marigorta

  3. Centre de Regulació Genòmica (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Catalonia 08003, Spain

    Arcadi Navarro

  4. National Institute for Bioinformatics (INB), Barcelona, Catalonia 08003, Spain

    Arcadi Navarro

  5. Institució Catalana de Recerca i Estudis Avançats (ICREA), Catalonia 08003, Spain

    Arcadi Navarro

Authors
  1. Juan Antonio Rodríguez
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Contributions

J.A.R., U.M.M., E.B. and A.N. conceived the study. J.A.R. and N.S. performed analyses. J.A.R., U.M.M., D.A.H., N.S., E.B. and A.N. analysed and interpreted the data. J.A.R., D.A.H., N.S., E.B. and A.N. wrote the manuscript.

Corresponding authors

Correspondence to Elena Bosch or Arcadi Navarro.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Discussion; Supplementary Figures 1–6; Supplementary Tables 1–10 (PDF 942 kb)

Supplementary Data 1

Estimated age of onset for the diseases used in the present study. (XLS 25 kb)

Supplementary Data 2

List of the associations SNP-disease retrieved from the GWAS Catalog and used for the present study. (XLS 484 kb)

Supplementary Data 3

List of the 266 pleiotropies found in the present study. These include both, the ones involving the same SNP in two diseases and these involving pairs of SNPs with r2 ≥ 0.8. (XLS 66 kb)

Supplementary Data 4

Chi square 2×2 tables for number of pleiotropies inside each defined category, considering early–late thresholds from 10 to 60. (XLS 39 kb)

Supplementary Data 5

Antagonistic early–late pleiotropies (r2 ≥ 0.8.) (n = 26) for an age threshold of 46 years as transition early–late. (XLS 24 kb)

Supplementary Data 6

Pleiotropy and comorbidity overlap. (XLS 20 kb)

Supplementary Data 7

Excess of pleiotropy in different gene sets at different levels, compared to genome-wide. (XLS 23 kb)

Supplementary Data 8

Genes in the Sousa-Victor et al. ageing gene set28. (XLS 30 kb)

Supplementary Data 9

Disease–SNP associations reported after crossing ageing genes from Sousa-Victor et al.28 with the GWAS Catalog used in present study. (XLS 31 kb)

Supplementary Data 10

Pleiotropies found in the Sousa-Victor et al. ageing gene set28. (XLS 25 kb)

Supplementary Data 11

Genes in the Magalhães et al. ageing gene set29. (XLS 46 kb)

Supplementary Data 12

Disease–SNP associations reported after crossing genes from Magalhães et al.29 with the GWAS Catalog used in present study. (XLS 39 kb)

Supplementary Data 13

Pleiotropies found in the Magalhães et al. ageing gene set29. (XLS 29 kb)

Supplementary Data 14

Genes in the Harries et al. age expression changing gene set30. (XLS 42 kb)

Supplementary Data 15

Disease–SNP associations reported after crossing ageing genes from Harries et al.30 with the GWAS Catalog used in the present study. (XLS 27 kb)

Supplementary Data 16

Pleiotropies found in the Harries et al. age expression changing gene set30. (XLS 21 kb)

Supplementary Data 17

Number of SNPs, diseases and average risk allelic frequency for early and late at each age threshold (10 to 60 years) from Fig. 1a. (XLS 25 kb)

Supplementary Data 18

Number of SNPs, diseases and average genetic variance for early and late at each age threshold (10 to 60 years) from Fig. 1b. (XLS 26 kb)

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Rodríguez, J., Marigorta, U., Hughes, D. et al. Antagonistic pleiotropy and mutation accumulation influence human senescence and disease. Nat Ecol Evol 1, 0055 (2017). https://doi.org/10.1038/s41559-016-0055

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