The use of geroprotectors to prevent multimorbidity: Opportunities and challenges. (January 2021) - Morsli, Samir; Bellantuono, Ilaria
Highlights: Over 60 % of people over the age of 65 suffer from multimorbidity and each disease is treated separately with problems of polypharmacy. Geroprotectors are drugs targeting mechanisms of ageing common to multiple age-related diseases and hold promise to improve the treatment of multimorbidity and reduce polypharmacy. Geroprotectors' mode of action differ in different tissues or in response to different mechanisms of ageing, suggesting that a blunt 'one drug for many diseases' approach may not work. Exploitation of artificial intelligence approaches to better understand how groups of diseases are clustered together and the underpinning molecular pathway of ageing specific to each cluster is required. The ultimate goal is the matching of the appropriate geroprotector with each cluster of diseases. Abstract: Over 60 % of people over the age of 65 will suffer from multiple diseases concomitantly but the common approach is to treat each disease separately. As age-associated diseases have common underlying mechanisms there is potential to tackle many diseases with the same pharmacological intervention. These are known as geroprotectors and could overcome the problems related to polypharmacy seen with the use of the single disease model. With some geroprotectors now reaching the end stage of preclinical studies and early clinical trials, there is a need to review the evidence and assess how they can be translated practically and effectively into routine practice. Despite promising evidence, there are many gaps and challenges in our understanding that must be addressed to make geroprotective medicine effective in the treatment of age-associated multimorbidity. Here we highlight the key barriers to clinical translation and discuss whether geroprotectors such as metformin, rapamycin and senolytics can tackle all age-associated diseases at the same dose, or whether a more nuanced approach is required. The evidence suggests that geroprotectors' mode of action may differ in different tissues or in response to different inducers of accelerating ageing, suggesting that a blunt 'one drug for many diseases' approach may not work. We make the case for the use of artificial intelligence to better understand multimorbidity, allowing identification of clusters and networks of diseases that are significantly associated beyond chance and the underpinning molecular pathway of ageing causal to each cluster. This will allow us to better understand the development of multimorbidity, select a more homogenous group of patients for intervention, match them with the appropriate geroprotector and identify biomarkers specific to the cluster.