Thymus of the essence?
We've considered cancer and its relationship to aging on a number of previous occasions. Studies published in the British Journal of Cancer in 2011 and 2018 concluded that around 40% of cases are attributable to known modifiable lifestyle and environmental factors, which is a substantial minority. Whilst risk for specific cancer subtypes will be more or less amenable to lifestyle and environment interventions than this, it is beyond doubt that the longer we live, the higher our risk of cancer becomes. But why?
A 2014 analysis of analysis of age and cancer risk proposed the view that "For most adults, age is coincidentally associated with preventable chronic conditions, avoidable exposures, and modifiable risk behaviors that are causally associated with cancer". This seems a sensible preventative outlook for individuals, since conditions such as diabetes, metabolic syndrome and chronic infections (such as hepatitis C) do increase cancer risk. However that proposal does not address direct causality in a meaningful way. A prevailing view has been that the growing burden of cellular mutation with time is the primary driver of cancer. This has come to be known as the multiple-hit hypothesis whereby accumulated mutations leads to cancer. This idea has been explored using both power-law and Erlang distributions to establish the best way to describe the number of such aberrations in tumours of various types. This hypothesis can be summarised simply: as we age we accumulate DNA damage, and ultimately this causes cancer.
However, recent research posits that the accumulation of mutations is not the whole story and that the bulk of increasing cancer risk with age arises from immunosenescence, i.e. the decreasing function of the immune system with increasing age. When a cell becomes damaged and potentially cancerous, this should be handled by apoptosis (cell death) or cellular senescence (that latter process bringing its own issues). Cells that evade those mechanisms should be prevented from causing harm by the immune system. This latest proposal is that cancers arise from a failure in the immune system to contain cancerous cells, and the researchers used models to demonstrate that their hypothesis offers a better explanation of the available data than the multiple-hit approach. Their model is based around the rate of shrinkage (involution) in the thymus as we age. The thymus is responsible for maturation of immune system T cells, and it begins to shrink as soon as we reach sexual maturity. As the thymus shrinks so does its ability to deliver naive T cells, resulting in a reduced ability to respond to new threats.
We see the impact of immunosenescence in other areas, such as the decreased effectiveness of vaccines and increased susceptability to novel pathogens. Therapies to prevent thymic involution or even regenerate the thymus and related organ systems, could prove important in multiple ways. While certain drastic approaches would likely prove effective they are unlikely to achieve wide-spread acceptance for humans. More realistically, evidence is building that we could add a reduction in immunosenescence to the numerous benefits of exercise. Indeed, a recent study showed highly physically active cyclists aged 55-79 could maintain thymic outputs comparable with healthy 20-36 year-olds. However, the ability to regularly cycle 100km in your sixties and seventies sets a high bar, defining a very select group the wider population are unlikely to become members of. For this reason there is serious work underway on medical rejuvination of the thymus, with a research team in Arizona being allocated a $10 million grant to study what they describe as a "holy grail of aging".
References:
Parkin, D.M, Boyd, L., Walker, L.C. (2011) The fraction of cancer attributable to lifestyle and environmental factors in the UK in 2010. British Journal of Cancer: 2011 Dec 6; 105(Suppl 2): S77–S81. DOI: 10.1038/bjc.2011.489
Brown, K et al (2018) The fraction of cancer attributable to modifiable risk factors in England, Wales, Scotland, Northern Ireland, and the United Kingdom in 2015. British Journal of Cancer: Published online: 23 March 2018. DOI: 10.1038/s41416-018-0029-6
White, M.C. et al (2014) Age and Cancer Risk A Potentially Modifiable Relationship. American Journal of Preventative Medicine: Volume 46, Issue 3, Supplement 1, Pages S7–S15 DOI: https://doi.org/10.1016/j.amepre.2013.10.029
Frigyesi, A. et al (2003) Power Law Distribution of Chromosome Aberrations in Cancer. Cancer Research: Volume 63, Issue 21
Belikov, A.V.(2017) The number of key carcinogenic events can be predicted from cancer incidence. Scientific Reports: Sci Rep. 2017; 7: 12170. DOI: 10.1038/s41598-017-12448-7
Palmer, S., Albergante, L., Blackburn, C.C, Newman, T.J. (2018) Thymic involution and rising disease incidence with age. Proceedings of the National Academy of Sciences: PNAS 2018; published ahead of print February 5, 2018 DOI: https://doi.org/10.1073/pnas.1714478115
Childs, B.G. et al (2014) Senescence and apoptosis: dueling or complementary cell fates?. EMBO Reports: EMBO Rep. 2014 Nov; 15(11): 1139–1153. DOI: 10.15252/embr.201439245
Belikov, A.V.(2013) Immunosenescence and Novel Vaccination Strategies for the Elderly. Scientific Reports: Sci Rep. 2017; 7: 12170. DOI: 10.1038/s41598-017-12448-7
Dorrington, M.G., Bowdish, D.M.E (2013) The number of key carcinogenic events can be predicted from cancer incidence. Frontiers in Immunology:Front Immunol. 2013; 4: 171. DOI: 10.3389/fimmu.2013.00171
Turner, J.E, Brum, P.C. (2017) Does Regular Exercise Counter T Cell Immunosenescence Reducing the Risk of Developing Cancer and Promoting Successful Treatment of Malignancies? Oxidative Medicine and Cellular Longevity Oxid Med Cell Longev. 2017; 2017: 4234765. DOI: 10.1155/2017/4234765
Duggal, N.A. et al (2018) Major features of immunesenescence, including reduced thymic output, are ameliorated by high levels of physical activity in adulthood Aging Cell Open Access, 8 March 2018 DOI: https://doi.org/10.1111/acel.12750
Previous posts
Lump sum or annuity?
The Curse of Cause of Death Models
Stephen's earlier blog explained the origin of the very useful result relating the life-table survival probability \({}_tp_x\) and the hazard rate \(\mu_{x+t}\), namely:
\[ {}_tp_x = \exp \left( - \int_0^t \mu_{x+s} \, ds \right). \qquad (1) \]
To complete the picture, we add the assumption that the future lifetime of a person now aged \(x\) is a random variable, denoted by \(T_x\), and the connection with expression (1) which is:
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