Kick-starting mechanoadaptation in aged bones

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Animals can modify the shape and mass of their individual limb bones to accommodate both habitual and new, imposed mechanical forces. This is perhaps best exemplified by the increases in bone mass that are seen in the dominant, serving arm of tennis players versus their non-serving, ball-throwing arm - we term the process by which these changes are achieved mechano-adaptation. If we understood the way such mechano-adaptive increases in bone mass were coordinated, we would be able to mimic them and, thus, alleviate any decreases in bone mass that places specific regions of bones at risk of fracture. This risk of fracture is very obvious in ageing bones, which fail to exhibit the capacity for such structural modification in response to imposed forces. There are massive, often hidden, consequences of such failure to adapt, which are increasing dramatically with enhanced longevity and lifestyle choices - the costs to health and society are huge. There is one main reason why we don't understand how bone mechano-adaptation is coordinated. The reason is that until now we have not been able to match microscopic level bone bending in response to imposed forces with the precise location of the ensuing structural increases in bone formation. We have recently made three advances that now make this possible. We have developed: i) a non-surgical model for imposing controllable forces to the tibia in living mice, ii) a means of measuring the extent of bending over the entire surface of small bones, and iii) recently acquired a machine that allows a precise microscopic 3D analysis of where bone is actively being formed. This creates a unique and timely opportunity. It was previously thought that mechano-adaptive processes acted to minimise the 'greatest' bending. We have generated pilot data that have allowed us to predict that, in contrast, bones adapt in order to minimise the 'steepest' local bending gradients on their surface. To test this we will bend some bones in mature mice that we know will adapt by increasing bone formation. To test whether steep bending gradients 'drive' formation we will: i) measure the bending pattern to generate a 'contour map' across the tibial bone surface, while it is being exposed to mechanical forces; ii) produce a 3D picture of the entire tibia describing exactly where bone formation takes place; iii) explore the overall changes in tibial structure by high-power 3D X-ray imaging, and iv) create virtual, digital computer images of the changes induced by these mechanical forces. These studies will determine which specific mechanical force is responsible for promoting bone formation and whether this occurs where bending gradients are indeed steepest. This will be useful if it can be used to modify bones which fail to fulfil their structural load-bearing role, as in ageing. Our pilot data from aged mouse bone are therefore crucial as they show that bending gradients appear less 'steep'; the general magnitude of bending engendered by force increases and the steepest gradients are consequently less severe. Using the methods described above as well as measures of bone quality and cellular responses to mechanical stimulation, we will explore if tibiae in aged mice exhibit a reduced cellular sensitivity to bending forces and/or a reduced mechanical stimulus capable of promoting adaptation. Our pilot studies have also shown that aged mouse bones do not exhibit mechano-adaptation and, intriguingly, that this can be restored to aged bones by prior imposition of a prolonged period without habitual use. We propose to explore the factors that change with this restoration, in the hope that we can identify how to kick-start mechano-adaptation in aged bones and thus alleviate the risk of fracture. Defining the drivers of adaptive increases in new bone formation in a precise 3D manner will also allow future studies to pinpoint the cellular events that are necessary to coordinate mechano-adaptation.