Understanding the physiology of the ageing individual: computational modelling of changes in metabolism and endurance

Abstract

One contribution of 12 to a theme issue 'The Human Physiome: a necessary key to the creative destruction of medicine'. Ageing and lifespan are strongly affected by metabolism. The maximal possible uptake of oxygen is not only a good predictor of performance in endurance sports, but also of life expectancy. Figuratively speaking, healthy ageing is a competitive sport. Although the root cause of ageing is damage to macromolecules, it is the balance with repair processes that is decisive. Reduced or intermittent nutrition, hormones and intracellular signalling pathways that regulate metabolism have strong effects on ageing. Homeostatic regulatory processes tend to keep the environment of the cells within relatively narrow bounds. On the other hand, the body is constantly adapting to physical activity and food consumption. Spontaneous fluctuations in heart rate and other processes indicate youth and health. A (homeo)dynamic aspect of homeostasis deteriorates with age. We are now in a position to develop computational models of human metabolism and the dynamics of heart rhythm and oxygen transport that will advance our understanding of ageing. Computational modelling of the connections between dietary restriction, metabolism and protein turnover may increase insight into homeostasis of the proteins in our body. In this way, the computational reconstruction of human physiological processes, the Physiome, can help prevent frailty and age-related disease.

Hyperbaric oxygenation for resuscitation and therapy of elderly patients with cerebral and cardio-respiratory dysfunction

“…This is accompanied by the gradual decline of gas exchange capacity of the lungs, and in the most severe cases results in gradual decline of oxygen concentration in the arterial blood, which can in turn exacerbate the myocardium dysfunction (78). All the deteriorative changes in the cardio-respiratory system generally manifest in the reduction of maximal oxygen uptake (VO 2 max) which has been considered one of the most informative parameters for biological age evaluation (79)(80)(81). This type of "physiomic" parameters of aging (81), focusing on energy metabolism measurements, may supplement various other "omic" markers of aging.…”

“…All the deteriorative changes in the cardio-respiratory system generally manifest in the reduction of maximal oxygen uptake (VO 2 max) which has been considered one of the most informative parameters for biological age evaluation (79)(80)(81). This type of "physiomic" parameters of aging (81), focusing on energy metabolism measurements, may supplement various other "omic" markers of aging.…”

The efficacy and safety of desflurane versus sevoflurane in elderly patients during general anaesthesia: a meta-analysis randomized controlled trials

“…With increasing life expectancy, more and more patients over 65 years of age account for an ever increasing need of surgical procedures, especially in developed countries [1,2]. Ageing has be recognized for years as a process of intrinsic deterioration that results in functional and structural with an irreversible and progressive changes [3,4]. These changes usually result in increasing the morbidity of the elderly patients and delayed recovery from general anesthesia [5].…”

Physical Activity and Nutrition INfluences In ageing (PANINI): consortium mission statement

“…PANINI will address this through focusing on the impact of nutrition and physical activity on mobility, muscle function, endocrine function, cognitive function, and inflammation in ageing at the cell and system level. Dysregulation of mitochondrial function in the muscle is a hallmark of ageing and age- and lifestyle-related diseases and so will be studied in skeletal muscle, applying a system biology approach through the mathematical modelling of metabolism [ 11 ]. This will include assessment of the impact of diet and physical activity on metabolic activity across different age groups through the use of the newly generated PANINI data as well as existing data sets of PANINI collaborators, e.g., NU-AGE, MYOAGE, and MUMC+.…”