The ageing of the population is associated with major achievements of our civilization. Initiated with the second agricultural revolution three centuries ago, technological improvements in manufacturing, transportation, trade, communications, energy production, better sanitations and health care and development of antibiotics and vaccines (which reduced considerably infection diseases causes of death rates) were crucial for the accelerated increase of the population (Fogel 1997, Harman 2001, Kanungo 1980). Thus, since the early 1900s, humans life expectancy has dramatically increased from about 45 years to about 80 years and the world population has increased four times as great as the increase during the whole previous history of mankind (Fogel 1997, Fontana and Klein 2007, Timiras 1994, Vina et al 2007). This progressive demographic shift towards a more aged population (characterized by low fertility and low mortality rates) has become one of the major challenges for the biomedical community. (Rice and Fineman 2004, Taylor et al 2004). Economical implications from this socio-demographic change are expected and strategies to preserve future social security funds beneficiaries are needed to face future issues. For example, elderly persons who suffer from chronic conditions and require long-term care are the heaviest users of health care services and the age at chronic disease onset has not risen to the same extent as life expectancy (Rice and Fineman 2004). It is estimated that elderly obese may cost 35% more than someone normal weight for welfare (Lakdawalla et al 2005). Keeping as many people as possible free of risk or those at risk at the lowest risk possible and delaying chronic disease onset may have an important social impact, provide better quality of life and economically less resource requirements to support the increased age population (Denton and Spencer 2010, Dwyer 2006).
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Age is the major risk factor for a number of pathologies and death which limits today average life expectancy at birth to about 85 years and the maximum life span around 122 years (Harman 2001). Understanding the nature of ageing process has become a challenge to scientists, a subject that will be now be discussed.
Figure 1. Age-specific death rates of Swedish females in various periods from 1751
to 1950 (adapted from Harman 2001)
II- Ageing definition
Ageing has been described - although not universally accepted - as the accumulation of diverse deleterious changes in the cells and tissues with advancing age which leads to a gradual decline in the adaptability and function of an organism to its normal environment and increase risk of disease and death (Harman 2001, Kanungo 1980, Vina et al 2007). Ageing can also be regarded as a universal (shared by all living organisms), intrinsic (independent of environmental factors), progressive (continuous) and deleterious (likely to reduce functional competence) process (Timiras 1994, Vina et al 2007).
The period of ageing (often referred as senescence) is not well defined because it is not known at what stage of the life span deterioration of function begins, as different organs begin to decline in function at different times (Kanungo 1980, Nair 2005). Nevertheless, observing lifespan between species it seems that reproductive maturity, ageing and the maximum life span are associated (Kanungo 1980). Throughout this period of life, age-related changes and function decline occur (Figure 2). These include the appearance of wrinkles due to loss of subcutaneous fat; loss and greying of hair in the scalp; decrease of cardiac, respiratory and immunological functions and deterioration of the muscular system particular of the cardiac and skeletal muscles (Timiras 1994). At a cellular level, post-mitotic cells (cells without capacity to divide) such as neurons and muscle cells begin to die and a slower rate of turnover of pre-mitotic cells cause accumulation of old cells (Kanungo 1980). As a result, the impairment of organs functions and ageing occur.
Figure 2. Age-related humans function performance.
III- Ageing Theories: genes, environment and adaptation
Although most of these age-related changes are familiar to the general population, understanding the mechanisms that drive the ageing process and explain why, for example, life expectancies are different between species is far to be know and several ageing theories have been proposed in the last century (Rattan 2006).
Of these theories, evolutionary theories of ageing try to explain differences in observed ageing rates and longevity across species through interplay between the Darwinian processes of mutation and natural selection. Currently, the two major evolutionary theories are the mutation-accumulation theory and the antagonistic pleiotropic theory. Both theories were developed in the 1950s and can operate at the same time (Gavrilov and Gavrilova 2002, Ljubuncic and Reznick 2009, Partridge and Gems 2002, Rose et al 2008).
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According to Medawar mutation-accumulation theory, forces of natural selection decline with age as mutations that affect offspring and reproduction are strongly selected while mutations with a later age of onset will be passed to next generations as no natural selection mechanisms occur during ageing. Therefore, ageing results from the accumulation of late-acting deleterious mutations in future generations.
George Williams's antagonistic pleiotropy theory proposes that some mutations may have beneficial effects on reproduction ages but be harmful at later ages. These mutations are maintained in the gene pool as they have positive effects on reproduction ages and no natural selection removes them later in life when they act as deleterious. In this theory it is assumed that pleiotropic genes may have effects on several traits of an organism and affect the organism fitness in antagonistic way. Both theories can be related to genetics of ageing because biological evolution is possible only for heritable manifestations of ageing (Gavrilov and Gavrilova 2002). Thus, evolutionary theories of ageing suggest that ageing itself is not genetically programmed and no adaptive (Hayflick 2007, Kirkwood 2008, Robert et al 2010).
It is clear that the processes of ageing originate in the biology of cells (Holbrook et al 1996). In the last decades quick improvements in cellular and molecular biology have contributed to a better understanding of ageing mechanisms and several theories have been proposed. For example, genetic studies performed on species with short life spans suggest there is no specific genetic programme regulating ageing processes but that some genes, which have defined roles in metabolism, may be affected by the lifelong impact of molecular damage and become deleterious for the organism (Kirkwood 2008, Rattan 2006, Vina et al 2007). Several genes have been identified to improve or accelerate cellular repair systems and resistance to damage such as the Î4/Î4 genotype coding apolipoprotein E4 shown to be accompanied by early onset ather-arteriosclerosis and also neurodegenerative diseases (Robert et al 2010).
Another attractive area of research in biogerontology is the study of epigenetics of ageing. For example, it was suggested that caloric restriction induces important epigenetic regulations on sirtuin genes which induce an increase in life expectancy (Fontana and Klein 2007, Robert et al 2010). Nevertheless, understanding complex interactions and networks of gene products during ageing requires innovative and integrative technical tools such as bioinformatics and functional genomics (Rattan 2006).
As first described by Hayflick in the 1960s, normal cells enter an irreversible nonproliferative state after a finite number of divisions, referred as cellular senescence, which has been strongly linked to the organism ageing (Martien and Abbadie 2007). The progressive shortening of telomeres which block the cell division as a result of lack of telomerase enzyme was the first mechanism associated to cellular senescence.
More recently, it has been suggested that senescence is a reaction to cellular stress, particularly DNA damage and that oxidative stress is thought to be one of the major causes (Lu and Finkel 2008). Oxidative stress coexists with biological systems that require oxygen to sustain life and is caused by the byproducts of oxygen utilization, the reactive oxygen species (ROS). As the antioxidant systems are unable to counterbalance all the ROS generated during the life of the cell, ROS may induce oxidative damage and consequently cellular senescence through different mechanisms which include the activation of p53 by overexpression of ras oncogenes (oncogene induced-senescence) or the acceleration of the telomeres shortening (Hornsby 2010, Mallette and Ferbeyre 2007). Additionally, it was observed that oxidative damage accumulates in tissues with age. The association between DNA damage and irreversible cycle arrest contributes to the idea that senescence is primarily an anti-suppressor mechanism which causes neoplastic cells to stop diving and become targets for elimination by the innate immune system (Martien and Abbadie 2007). However, as the immune function declines with age, the rate of senescent cells elimination decreases. The accumulation of these cells in the organism may induce a cascade of immune and inflammation responses at a later age.
Currently, a leading theory known as mitochondrial theory of ageing, proposes that senescence may be the result of damage caused by ROS to the mitochondrial genome in post-mitotic cells (Vina et al 2007). As ROS are generated in the mitochondrial electron transport chain, mitochondrial DNA is much more oxidized with age than nuclear DNA. For example, it has been observed that respiratory activity of mitochondria decreases with age in liver, muscle and brain. Thus, oxidative stress, in combination with molecular inflammation, has also been related to sarcopenia (decline of muscle mass and strength with age) by interfering with the balance between protein synthesis and breakdown and causing mitochondrial dysfunction (Meng and Yu 2010, Sakuma and Yamaguchi 2010).
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In review, modern and evolutionary theories of ageing suggest that the absence of adaptive genomic information required to survive and regulate the accumulation of damage at later age is a major cause for ageing (Rose 2009). Currently, exciting and advanced strategies to reverse ageing (i.e. re-tuning genes adaptation to damage) are being studied and explored (Partridge 2010, Rae et al 2010, Rose 2008).
As described above, controlling environmental factors has a major influence on ageing. For instance, the heritability of life expectancy has been estimated to be 20-30% which suggests that environmental factors can contribute to a faster or a slower and successful ageing (Perls and Terry 2003, Rice and Fineman 2004). Caloric restriction has been tested in several species and it was shown that it may slow ageing (Fontana 2009, Hildt 2009). Additionally, resistance training has been suggested to be the most effective strategy to combat sarcopenia (Johnston et al 2008, Sakuma and Yamaguchi 2010). In contrast, lack of physical activity, high sugar and high fat diets accelerate the onset of chronic diseases (Rice and Fineman 2004, Rockenfeller and Madeo 2010). At this stage, it is a challenge to study nutrition and exercise as essential factors to prolong the period of healthy life and clarify knowledge regarding the effectiveness and efficacy of lifestyle interventions among the elderly population (Kirkwood 2006, Taylor et al 2004).
IV- Nutrition in the elderly
One of the most important aspects of human evolution in the last three centuries was the continuing improvements in nutrition (Fogel 1997). Nevertheless, today trends to an increasing sedentary behaviour and high energy dense diets are associated to the actual epidemic of overweight and obesity which is expected to accelerate the onset of age related diseases such as cardiovascular disease and other health issues like hip fractures (Kirkwood 2006, Taylor et al 2004).
Several studies have tried to identify how diet and nutrients may influence ageing and health. For example, a reduced calorie intake diet without essential nutrients deficiency (calorie restriction) has been shown to extend the lifespan of rodents and develop less age-related pathologies (Timiras 1994). Similar results were reported in studies on rhesus macaques where calorie restriction also seems to protect against sarcopenia (Bendlin et al 2010, Colman et al 2009). Probably, these systemic effects result from a decrease in inflammatory processes and oxidative damage. Nevertheless, calorie restriction it is not effective when started in older rodents and this is supported by the evidence that weight loss in vulnerable elderly is associated to increase mortality (Bamia et al 2010, Morley et al 2010).
Though energy intake and energy balance are major variables that affect health and ageing, several studies have examined the effects of nutrients on health (Everitt A et al 2006). For example, dietary patterns such as the Mediterranean diet, rich in fiber and unsaturated fatty acids appear to be relevant even in old age (de Groot and van Staveren 2010). At a nutrient level, it is well established the association between high sugar and high fat diets and the earlier onset of chronic diseases such as cardiovascular disease and diabetes (Rockenfeller and Madeo 2010). Vitamin D has been associated with bone mineralization, lower risk for osteoporosis and more recently it has been suggested that it may have beneficial effects on cardiovascular health and cognitive function (Buell J et al 2009, Dwyer 2006, Shepherd 2009). It is important to refer that elderly adults may be a group at risk for vitamin D deficiency especially in countries where sun exposure is low such as Ireland. (Hill T et al 2005).
Other vitamins such as B6, B12, folate, antioxidants such as vitamins C and E, very long chain fatty acids omega 3 have all received much attention in the last decade as several studies have looked at the effects of these nutrients in the ageing process (González-Gross M et al 2001, Shepherd 2009). For example, low multi B-vitamin inadequacy have been associated to increase risk for carcinogenesis (Liu et al 2008). Additionally, high homocysteine, low vitamin B status, inadequacy intake of vitamins C and E may be a nutrition risk factor for cognitive decline (González-Gross M et al 2001, Tucker et al 2005). In contrast, there is a little evidence supporting the benefits of omega-3 fatty acids on cognitive declines which requires more studies on this field (Donini et al 2007, Issa et al 2006, van Gelder et al 2007, Whelan 2008). Nevertheless, it is well known the anti-inflammatory and protective effects of these fatty acids against cardiovascular disease (Farzaneh-Far et al 2010). Finally, it is important to refer that nutrition has also an important role in maximizing training adaptations which enhances the idea of that a joint work between nutrition and exercise is essential to a successful ageing (Hawley 2002, Hawley JA et al 2006, Volek 2004)
V- Exercise and the elderly - studies description
There is a strong evidence of the health benefits of regular physical activity young and old populations (American College of Sports Medicine 2009, Flynn 2007, Schjerve et al 2008, Stewart et al 2007, Taylor et al 2004, Trejo-Gutierrez and Fletcher 2007, Warburton et al 2006). Physical activity induces a number of specific metabolic adaptations in skeletal muscle which includes the increase of mithocondria and oxidative capacities, the transformation of muscle fibre types, the increase in GLUT4 protein expression and glucose homeostasis (Rockl et al 2008). Exercise has been shown to improve body composition, fitness and cardiovascular function, enhance lipid profiles, glucose homeostasis and insulin sensitivity, reduce blood pressure and enhance endothelial function which results in important implications for the prevention of many chronic diseases like diabetes, cardiovascular disease, hypertension and obesity (Green et al 2004, Tambalis et al 2009, Turcotte and Fisher 2008, Warburton et al 2006).
As we get older important changes occur in our metabolism. For example, inflammation biomarkers such as CRP, TNF-α and IL-6, homocystein and oxidative stress production are associated with normal ageing (Kanapuru and Ershler 2009, Ventura et al 2009). For instance, CRP and TNF-α have been strongly associated to a higher risk for chronic disease and are considered stronger predictors of the risk of cardiovascular mortality than classical risk factors such as cholesterol and LDL (Davis et al 2008, Despres 2004, Puglisi and Fernandez 2008). Ageing is also associated to the decline of testosterone levels after the third decade in men which has been associated to an increase in LDL cholesterol, triglycerides and decrease of HDL (Kolovou et al 2010). Thus, it has been shown that better lipid profiles are associated to better survival in old groups (Galioto et al 2008, Landi et al 2008).
To review knowledge regarding the effects of exercise on metabolic health parameters in the elderly, a literature search was conducted using Medline/Pubmed database. Although there is a growing body of literature available that examined the effects of exercise on health in the elderly, just eight papers were selected to give an overview of the current research related to this subject. A summary of these studies is presented in Table 1. Fahlman and colleagues were the first group examining the plasma lipoproteins response to two different types of exercise in elderly women in 2002 (Fahlman et al 2002). A total of 45 healthy women aged 70-87 years were randomly assigned to an aerobic training, resistance training or a control group. The aerobic training (AT) group walked 3 days a week for 20 minutes in the beginning of the intervention and for 50 minutes after week 3 while the resistance training (RT) group did three sets of eight repetitions of eight different exercises three times a week; the control group maintained normal activity. The exercise interventions lasted 10 weeks. Their main findings were that both AT and RT groups had favourable changes in plasma lipoprotein levels. These improvements were independent of weight loss as there were no changes regarding body weight. It was suggested that intensity and amount of exercise may be associated to a reduction in cardiovascular risk. In 2004, Hammet and colleagues performed a randomized controlled study to assess the effects of six months of regular exercise training on CRP levels and body fat. Studies conducted before suggested that regular physical exercise might lower CRP levels by an anti-inflammatory action but the hypothesis of this study was that the exercise lowers CRP levels by reducing total or abdominal fat. A total of 61 healthy elderly subjects aged 60-85 years were recruited and randomised to either an exercise group or a control group. The exercise group underwent six months of exercise training, consisting of three supervised sessions and one unsupervised session each week. The training intensity was increased gradually so that by the fourth month, subjects were training 45min at a heart rate of 80% of their current estimated maximum oxygen consumption (VO2max). In this study, six months of exercise training in healthy elderly participants did not lower serum CRP levels and no body fat changes occurred despite a significant improvement in their cardiorespiratory fitness. It was suggested that the association between greater physical fitness and lower serum CRP levels is explained, at least in part, by long-term regular exercise that induce reduction of body fat (Hammett et al 2004). A very recent study has also found an association between strength gains, adiposity loss and chronic reduction in CRP concentrations after an exercise intervention in older adults (Martins et al 2010). In 2006, Zoppini and colleagues examined for six months the effects of a twice-weekly aerobic exercise programme, 50%-70% HRR, on plasma inflammatory biomarkers and endothelial dysfunction biomarkers in elderly type 2 diabetic patients. Although physical training increased HDL levels and reduced uric acid levels no changes were found in CRP and TNF-α levels, body weight, blood pressure, plasma triglyceride and LDL cholesterol concentrations. It was discussed that the type, intensity, frequency and duration of the exercise sessions selected for their study were a possible explanation for the failure to obtain significant changes in body weight and consequently improvements in metabolic biomarkers (Zoppini G et al 2005). Published in 2006, Kohut and colleagues compared the effects between a ten months aerobic training (AT) and a flexibility/strength training (FST) intervention on inflammatory biomarkers in elderly people aged between 64 years and 87 years (Kohut et al 2006). Eighty seven volunteers were randomly assigned to either the AT or FST group. Both groups had three supervised sessions per week during the ten months of intervention. Main findings from this study were that although both groups reduced levels of TNF-α, aerobic training also showed improvements in the levels of IL-6, IL-18 and CRP. The higher intensity exercise level performed by the AT group was suggested to explain the results. Vincent and colleagues examined the effects of resistance training in oxidative stress levels, homocysteine and lipid profile in normal-weight and overweight/obese elderly people (Vincent et al 2006). After a 6-month training program the resistance training groups showed lower levels of homocysteine, lipid hydroperoxides and thiobarbituric-reactive acid in both normal-weight and overweight/obese groups comparing to the controls. These results suggest that resistance training may reduce risk for cardiovascular disease independently of BMI in the elderly by reducing levels of oxidative stress and homocisteyne. A more recent study has also found that aerobic training had beneficial effects on antioxidant defense system (Karolkiewicz et al 2009).
Brooks and colleagues have studied the effects of resistance training on strength, insulin resistance, CRP, adiponectin and free fatty acid levels in a diabetic old population aged more than 55 years. Sixty two participants were randomised to a supervised strength training programme for 16 weeks, 3 times a week and 60-80% intensity of baseline 1RM or to a control group. Results from this intervention showed that high intensity training had a positive impact on strength and muscle quality and insulin sensitivity, increased adiponectin levels (which has an anti-inflammatory action) and reduced free fatty acids and CRP levels (Brooks et al 2007).
More recently, Nicklas and colleagues compared a twelve months physical activity intervention (combination of aerobic, strength, balance and flexibility training) with a successful ageing health education intervention in 424 elderly aged between 70 and 89 and with low functional performance. The main finding from this study was that physical activity intervention reduced the levels of IL-6 comparing to the successful ageing intervention (Nicklas et al 2008). Vale and colleagues have looked at the impact of aerobic training and strength training on serum levels of IGF-1 and cortisol. Participants underwent either a strength training programme that consisted of three supervised sessions per week (n=12), an aerobic training programme that included three supervised sessions of aquatic exercises per week (n=13) or a control group (n=10) that kept their normal activity. The main finding from this study was that IGF-1 levels increased only in the strength training group and no differences were found in the groups regarding cortisol which suggest that high-intensity strength training promotes anabolic effects in the elderly individuals (Vale et al 2009). Additionally, a very recent study also suggests that different improvements in IGFBP-3 and TNF-α may depend on different intensities of resistance training (Onambele-Pearson et al)
In addiction to these numerous health benefits for the elderly population, there is also a growing interest in exercise as a strategy to prevent cognition decline as it is well explained in two very recent reviews (Erickson KI and Kramer AF 2009, Lista and Sorrentino 2010, Liu-Ambrose T and Donaldson MG 2009). Although it is suspected that exercise may reduce cognitive decline by improving IGF-1 and homocysteine the mechanisms behind the effects of exercise on cognition are far to be fully understood (Erickson KI and Kramer AF 2009, Lista and Sorrentino 2010, Liu-Ambrose T and Donaldson MG 2009, Muscari et al 2009).
An overview at the major outcomes reported in studies that examined the effects of exercise in metabolic health biomarkers in elderly populations is given in table 2.
Overall, it seems that exercise training in the elderly induces beneficial improvements in several health biomarkers and possibly prevents cognitive decline in the elderly population. Nevertheless, more evidence is needed as many questions are still to be clarified. For instance, improvements in the lipid profile and inflammatory biomarkers in the elderly were not always reported. Health benefits from exercise training may depend on many variables such as the type, frequency and intensity of the exercise and even genes. Additionally, key metabolic biomarkers changes may be independently associated to changes in weight loss.
In review, more studies on this field of research integrating more comprehensive approaches and techniques are needed to better understand the complex biological mechanisms and metabolic interactions induced by exercise to extrapolate more accurate and specific guidelines to the population.
Metabolomics is an advanced analytical technique that examines metabolic patterns in biological samples (e.g. urine, blood, saliva) (Kussmann et al 2008). Metabolomics may generate assumptions rather than testing hypothesis as it gives a more detailed and unspecific information about the complex metabolic response to environmental factors such as nutrients or other external compounds (Pohjanen E et al 2007). This technique may detect thousands of low molecular weight metabolites and contribute to a better characterization of metabolic phenotypes. The application of metabolomics is achieved using analytical tools such as nuclear magnetic resonance spectroscopy and mass spectrometry. To analyse the complex data produced using these screening techniques, multivariate statistical methods such as principal component analysis are required to convert the massive metabolic data in more a more simplistic and effective information that allow researchers to create an hypothesis (Kussmann et al 2008). To date, very few studies have examined the effects of exercise in the human metabolome. A pioneer study carried by Pohjanen and colleagues in 2007 investigated the acute effects of strenuous exercise on healthy and regularly trained male subjects (Pohjanen E et al 2007). Metabolomics was also effectively used to evaluate metabolomic changes in subjects with insulin sensitivity after an exercise intervention as after a 12 week exercise programme, a number of metabolites were identified to be associated to the subjects' metabolomic response to exercise (Kuhl J et al 2008). Additionally, a very recent study has identified two dozens of metabolites such as niacimide to change after vigorous exercise (Burke et al 2010). Metabolomics was also applied for the first time in sports physiology research very recently (Bei Yan et al 2008). A group of professional rowers and a group of healthy male individuals (control) underwent a 2-week daily exercise programme. All the subjects were provided similar meals during the intervention which reduce the interference of diet on the results. Although biochemical parameters did not differ between the two groups before and after training, metabolomics showed to be effective to characterize metabolic changes in glucose metabolism, lipid metabolism, oxidative stress and amino acid metabolism. Metabolomics is a promising tool that may help researchers to clarify and understand deeper the metabolic effects of exercise on health. Therefore, the aim of this original research project is to evaluate the effects of different types of exercise on metabolic health parameters in the elderly and metabolic profiles. Overall, this research will add valuable knowledge to healthy ageing research by monitoring the effects of exercise on health parameters in this growing population group.