Evaluation of biomarkers for ageing in populations of the youngest old and the oldest old
Lead Research Organisation:
Newcastle University
Department Name: Clinical Medical Sciences
Abstract
Nearly all major diseases of modern times are age-dependent, that means, high age is the most important risk factor for cardiovascular disease, dementias, many forms of tumours, diabetes and so on. However, biological age can be very different from what is measured in years and days. Everyone knows that some people are ?young for their age?, while others age much faster than suggested by their years. Genes, environmental factors and chance together cause these differences. This tells us two important things: First, ageing is malleable, it is possible to intervene and to slow down human ageing. Secondly, such intervention will not only increase lifespan, but will most probably also postpone the occurrence of major diseases.
The problem with interventions into the ageing process is that their efficiency is very hard to measure. One cannot wait for the death of a person to decide whether a certain combination of nutrients and vitamins was good in slowing down ageing. For that, biomarkers are needed, physical parameters that can be measured today but will tell us not only how old this person is biologically but also how fast he or she will age over, say, the next 10 years. In recent years, improved understanding of the biology of ageing has led to the identification of a number of candidate biomakers of ageing. However, in order to see whether they are really good enough, they need to be tested on large numbers of people of different ages, they need to be tested in combination with each other, and they need to be tested longitudinally, that means we need to know how they change as an individual ages. We propose to do these tests, and we hope to come up with a combination of markers that will improve prediction of risk for major age-related diseases and thus allow early assessment of the efficiency of preventive interventions.
Findings from our research will be vigorously disseminated through contacts with NHS and other stakeholder groups, including older persons? action groups, as represented in the North East Forum on Ageing (?Years Ahead?), and beyond. Findings will also be disseminated through conventional academic publications, conference presentations, web site, other media (as appropriate), and via our networks of collaborators.
The problem with interventions into the ageing process is that their efficiency is very hard to measure. One cannot wait for the death of a person to decide whether a certain combination of nutrients and vitamins was good in slowing down ageing. For that, biomarkers are needed, physical parameters that can be measured today but will tell us not only how old this person is biologically but also how fast he or she will age over, say, the next 10 years. In recent years, improved understanding of the biology of ageing has led to the identification of a number of candidate biomakers of ageing. However, in order to see whether they are really good enough, they need to be tested on large numbers of people of different ages, they need to be tested in combination with each other, and they need to be tested longitudinally, that means we need to know how they change as an individual ages. We propose to do these tests, and we hope to come up with a combination of markers that will improve prediction of risk for major age-related diseases and thus allow early assessment of the efficiency of preventive interventions.
Findings from our research will be vigorously disseminated through contacts with NHS and other stakeholder groups, including older persons? action groups, as represented in the North East Forum on Ageing (?Years Ahead?), and beyond. Findings will also be disseminated through conventional academic publications, conference presentations, web site, other media (as appropriate), and via our networks of collaborators.
Technical Summary
Ageing is the single largest risk factor for death and major diseases. However, biological age can differ significantly from calendaric age. Moreover, the rate of ageing is highly variable between individuals, and this is particularly evident amongst the oldest old. Given the high impact of environmental factors on ageing trajectories, reliable markers of biological age will have great potential in preventive medicine, intervention validation and risk assessment.
?Classical? markers of biological age include systolic blood pressure, hand grip strength, forced respiratory volume, cholesterol and glucose blood levels and cognitive/neuropsychological tests. While these markers are well validated, their prognostic potential is low, even if combined in biomarker batteries. In recent years, many more candidate markers have been discovered on the basis of a greatly improved understanding of the cell and molecular biology of ageing. Telomere length in white blood cells is the best characterized of these so far, but even this has not been sufficiently evaluated in human populations or interlinked with other markers. Moreover, the complex dynamics of the ageing process makes it highly likely that the prognostic power of individual biomarkers varies with age group. However, there are only indirect data available for comparisons between age groups, and longitudinal assessments of intra-individual changes in biomarkers of ageing with time are scarce.
Thus we propose the construction of an interrelated panel of biomarkers of ageing. This will combine ?classical? markers with recent ones developed on the basis of well-established molecular, cellular and physiological ageing mechanisms. We will evaluate these markers both individually and as a panel in two population-based samples ? the MRC National Survey of Health and Development (NSHD), a cohort of the ?youngest old? aged 53-60 years, and the NorthEast 85+ (NE85+) study of the ?oldest old? (aged 85-90 years) ? by testing their association with major health outcomes cross-sectionally and prospectively. Telomere length data obtained in a local population of the ?youngest old? (Newcastle 1000 Families study ? N1000F) will be used to assess and standardize the impact of geographic background between the two main populations. The NE85+ study will immediately allow the examination of longitudinal trajectories of the chosen biomarkers. These population studies will be complemented by a clinical sample of patients at early stages of age-related disease.
?Classical? markers of biological age include systolic blood pressure, hand grip strength, forced respiratory volume, cholesterol and glucose blood levels and cognitive/neuropsychological tests. While these markers are well validated, their prognostic potential is low, even if combined in biomarker batteries. In recent years, many more candidate markers have been discovered on the basis of a greatly improved understanding of the cell and molecular biology of ageing. Telomere length in white blood cells is the best characterized of these so far, but even this has not been sufficiently evaluated in human populations or interlinked with other markers. Moreover, the complex dynamics of the ageing process makes it highly likely that the prognostic power of individual biomarkers varies with age group. However, there are only indirect data available for comparisons between age groups, and longitudinal assessments of intra-individual changes in biomarkers of ageing with time are scarce.
Thus we propose the construction of an interrelated panel of biomarkers of ageing. This will combine ?classical? markers with recent ones developed on the basis of well-established molecular, cellular and physiological ageing mechanisms. We will evaluate these markers both individually and as a panel in two population-based samples ? the MRC National Survey of Health and Development (NSHD), a cohort of the ?youngest old? aged 53-60 years, and the NorthEast 85+ (NE85+) study of the ?oldest old? (aged 85-90 years) ? by testing their association with major health outcomes cross-sectionally and prospectively. Telomere length data obtained in a local population of the ?youngest old? (Newcastle 1000 Families study ? N1000F) will be used to assess and standardize the impact of geographic background between the two main populations. The NE85+ study will immediately allow the examination of longitudinal trajectories of the chosen biomarkers. These population studies will be complemented by a clinical sample of patients at early stages of age-related disease.