I am a biogerontologist, studying the biological causes of ageing and potential treatments, supported by a UKRI Future Leaders Fellowship funding (upcoming). Where I am qualified to comment, I respond below to questions posed in the Call for Evidence.
1) How complete is the scientific understanding of the biological processes of ageing and their epidemiologies?
Understanding is substantial and supported by robust evidence. Evidence comes from (i) human studies and (ii) repeatable observations amongst animals, hinting at the conserved biological basis of ageing. Interacting processes appear to regulate ageing, including (at least):
a) Microbiome. Bacteria living on the body (microbiota), and particularly in the gut, have emerged recently as major determinants of lifelong health1. Alterations to the microbiota have been catalogued in aged humans. Perturbing or eliminating microbiota extends lifespan of diverse animals, and rejuvenation has been reported when aged individuals are given the microbiota of younger individuals2. Bacteria also play key roles in metabolising drugs that may be used to extend healthspan3. The microbiome also produces nutrients that are absorbed by the gut, which direct host physiology and constitute a reservoir of potentially exploitable therapeutics.
b) Nutrition. Moderately reduced nutrient intake (dietary restriction) is the most widely-reported way to retard ageing4. Epidemiological evidence indicates the importance of diet to human ageing. In experimental animal systems, reducing either total intake or specific nutrients - especially protein - extends lifespan and healthspan5. The importance of qualitative dietary changes, e.g. reducing protein:carbohydrate ratio, is widely recognised6. Intermittent fasting may also improve healthspan, though it remains to be established whether this mimics mechanistic impacts of dietary restriction, or operates through independent mechanisms7. Ongoing research is investigating whether these phenomena result from altered metabolism, signalling and gene expression, or a combination of the.
c) Cellular signalling. Nutrient signalling networks integrate information about nutrient availability. Evidence for their roles in ageing is abundant. Experimentally reducing nutrient signalling - especially insulin/IGF and Target of rapamycin (Tor) - repeatably extends animal lifespan and healthspan8. These networks are shared (evolutionarily conserved) in humans and other animals and, accordingly, human genetic variants in these pathways are associated to human ageing. These pathways are "druggable", and substantial ongoing effort is dedicated to establishing whether approved drugs can be repurposed to combat ageing9,10.
d) Gene expression. Gene regulation is a key determinant of ageing11. Proteins that modulate gene expression (transcription factors) are the major outputs of cellular signalling. Certain transcription factors, especially the Forkhead family, are (i) genetically required for benefits of experimentally reduced animal nutrient signalling12,13, and (ii) genetically associated with human longevity14.
e) Epigenetics. Epigenetic modifications modulate activities of transcription factors on gene expression. The ability to predict human age from a collection of epigenetic marks ("Horvath's clock")15 underlines a correlation between epigenomic regulation and human ageing. Whether this relationship is causal remains to be established, but it is now apparent that an individual animal's epigenome can be "programmed", e.g. by transient nutritional alterations16, to modulate ageing.
f) Proteostasis. Gene expression programs are enacted by the production of corresponding proteins. Protein production (translation) and maintenance (proteostasis) is emerging as an important determinant of ageing17.
2) What technologies will be needed to facilitate treatments for ageing and ageing- related diseases?
Achieving the goal of five years' extra healthspan will require the direct, personalised treatment of individuals who are already aged (i.e. in addition to the longer-term goal of lifelong interventions to improve public health prognoses). Individual variation in historical lifestyles, as well as genetics and diet, will generate baseline biological variation that must be assessed if these interventions are to be targeted effectively. For example, current procedures to assay microbiota and epigenomic state by shotgun sequencing easily cost thousands of pounds. Such costs could be mitigated by new sequencing technologies and dedicated high-throughput facilities for their application to patient samples. This technological drive may also dovetail with the 100,000 genomes initiative, or technologies used therein.
3) What opportunities are there for industry in the development of new technologies to help increase health span? In which areas of medical research and technology development does the UK excel?
Opportunities to develop precision therapeutics and new technologies are abundant. Personalised biotics and diets are avenues that could be widely marketable and adoptable by virtue of their low cost and the positive public perception of non-pharmacological interventions. The UK has both an excellent research base in this field (multiple Russell Group universities) and matched industrial sector (e.g. Microbiotica, Cambridge).
1) O'Toole & Jeffery, Science. 2015, DOI: 10.1126/science.aac8469
2) Smith et al, eLife. 2017, DOI: 10.7554/eLife.27014
3) Pryor et al, Cell. 2019, DOI: 10.1016/j.cell.2019.08.003
4) Piper et al, Cell Metabolism. 2011, DOI: 10.1016/j.cmet.2011.06.013
5) Grandison et al, Nature. 2009, DOI: 10.1038/nature08619
6) Solon-Biet et al, Cell Metabolism. 2014, DOI: 10.1016/j.cmet.2014.02.009
7) Catterson et al, Current Biology. 2018, DOI: 10.1016/j.cub.2018.04.015
8) Kenyon, Nature. 2010, DOI: 10.1038/nature08980
9) Slack et al, Cell. 2015, DOI: 10.1016/j.cell.2015.06.023
10) Harrison et al, Nature, 2009. DOI: 10.1038/nature08221
11) Dobson et al, PLoS Genetics, 2019. DOI: 10.1371/journal.pgen.1008212
12) Slack et al, Aging Cell, 2011. DOI: 10.1111/j.1474-9726.2011.00707.x
13) Kenyon et al, Nature, 1993. DOI: 10.1038/366461a0
14) Willcox et al, PNAS, 2008. DOI: 10.1073/pnas.0801030105
15) Horvath, Genome Biology, 2013. DOI: 10.1186/gb-2013-14-10-r115
16) Dobson et al, Cell Reports, 2017. DOI: 10.1016/j.celrep.2016.12.029
17) Labbadia et al, Cell Reports, 2017. DOI: 10.1016/j.celrep.2017.10.038
20 September 2019