New horizons in frailty: Ageing and the deficit-scaling problem

Division of Geriatric Medicine, Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia, Canada.
Age and Ageing (Impact Factor: 3.64). 06/2013; 42(4). DOI: 10.1093/ageing/aft059
Source: PubMed


All the current frailty measures count deficits. They differ chiefly in which items, and how many, they consider. These differences are related: if a measure considers only a few items, to define broad risks those items need to integrate across several systems (e.g. mobility or function). If many items are included, the cumulative effect of small deficits can be considered. Even so, it is not clear just how small deficits can be. To better understand how the scale of deficit accumulation might impact frailty measurement, we consider how age-related, subcellular deficits might become macroscopically visible and so give rise to frailty. Cellular deficits occur when subcellular damage has neither been repaired nor cleared. With greater cellular deficit accumulation, detection becomes more likely. Deficit detection can be done by either subclinical (e.g. laboratory, imaging, electrodiagnostic) or clinical methods. Not all clinically evident deficits need cross a disease threshold. The extent to which cellular deficit accumulation compromises organ function can reflect not just what is happening in that organ system, but deficit accumulation in other organ systems too. In general, frailty arises in relation to the number of organ systems in which deficits accumulate. This understanding of how subcellular deficits might scale has implications for understanding frailty as a vulnerability state. Considering the cumulative effects of many small deficits appears to allow important aspects of the behaviour of systems close to failure to be observed. It also suggests the potential to detect frailty with less reliance on clinical observation than current methods employ.

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    • "Although many different measurement instruments have been proposed, most commentary generally has focussed on two approaches, deficit accumulation and the frailty phenotype (reviewed by de Vries et al.) (7). The deficit accumulation approach we propose here for use in mice accords with the deficit accumulation approach used in many previous studies in humans (2,4,53). It includes integrative measures such as grooming, strength, mobility, and measures of discomfort, so it measures deficits constituted broadly. "
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    ABSTRACT: We previously quantified frailty in aged mice with frailty index (FI) that used specialized equipment to measure health parameters. Here we developed a simplified, noninvasive method to quantify frailty through clinical assessment of C57BL/6J mice (5-28 months) and compared the relationship between FI scores and age in mice and humans. FIs calculated with the original performance-based eight-item FI increased from 0.06±0.01 at 5 months to 0.36±0.06 at 19 months and 0.38±0.04 at 28 months (n = 14). By contrast, the increase was graded with a 31-item clinical FI (0.02±0.005 at 5 months; 0.12±0.008 at 19 months; 0.33±0.02 at 28 months; n = 14). FI scores calculated from 70 self-report items from the first wave of the Survey of Health, Ageing and Retirement in Europe were plotted as function of age (n = 30,025 people). The exponential relationship between FI scores and age (normalized to 90% mortality) was similar in mice and humans for the clinical FI but not the eight-item FI. This noninvasive FI based on clinical measures can be used in longitudinal studies to quantify frailty in mice. Unlike the performance-based eight-item mouse FI, the clinical FI exhibits key features of the FI established for use in humans.
    The Journals of Gerontology Series A Biological Sciences and Medical Sciences 09/2013; 69(6). DOI:10.1093/gerona/glt136 · 5.42 Impact Factor
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    • "A large body of evidence can relate an increase in recovery time to age-associated damages and diseases (Franceschi et al. 2000; Rattan 2003; Gurtner et al. 2008; Akushevich et al. 2013; Yanai et al. 2011). The mechanisms by which recovery occurs are complex and involve a number of processes, at different levels of the organism, from the DNA repair response (Moskalev et al. 2012), to repair of chromosomal damage (Nicholls et al. 2011) to autophagy (Couve and Schmachtenberg 2011; Fortini and Dogliotti 2010; Vicencio et al. 2008), degradation of repair capacity (Koga et al. 2011), and a host of others (Tacutu et al. 2010b; Howlett and Rockwood 2013; Yashin et al. 2013). This multiplicity of specific mechanisms responsible for age-related decline in the recovery rate likely corresponds to decline in flexibility (Fabre et al. 2007) or loss of stress resistance with aging seen with decline in allostatic adaptation (Yashin et al. 2007b, c, 2013). "
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    ABSTRACT: The health of individuals is highly heterogeneous, as is the rate at which they age. To account for such heterogeneity, we have suggested that an individual’s health status can be represented by the number of health deficits (broadly defined by biological and clinical characteristics) that they accumulate. This allows health to be expressed in a single number: the frailty index (FI) is the ratio of the deficits present in a person to the total number of deficits considered (e.g. in a given database or experimental procedure). Changes in the FI characterize the rate of individual aging. The behavior of the FI is highly characteristic: it shows an age specific, nonlinear increase, (similar to Gompertz law), higher values in females, strong associations with adverse outcomes (e.g., mortality), and a universal limit to its increase (at FI ~0.7). These features have been demonstrated in dozens of studies. Even so, little is known about the origin of deficit accumulation. Here, we apply a stochastic dynamics framework to illustrate that the average number of deficits present in an individual is the product of the average intensity of the environmental stresses and the average recovery time. The age-associated increase in recovery time results in the accumulation of deficits. This not only explains why the number of deficits can be used to estimate individual differences in aging rates, but also suggests that targeting the recovery rate (e.g. by preventive or therapeutic interventions) will decrease the number of deficits that individuals accumulate and thereby benefit life expectancy. Electronic supplementary material The online version of this article (doi:10.1007/s10522-013-9446-3) contains supplementary material, which is available to authorized users.
    Biogerontology 07/2013; 14(6). DOI:10.1007/s10522-013-9446-3 · 3.29 Impact Factor

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