We usually think of age as the length of time we have been alive, which happens at the same rate for everyone. However, we often associate old age with a decline in brain health, which is not the same for everyone. Some brain health decline is fast and steep, while others have almost no decline. These individual differences impede separating normal ageing from the earliest signs of neurodegeneration. If we could distinguish them, therapies for the latter might be more successful. Lifestyle and genetics are influential to individual brain health. Their continued impact across a lifespan creates a spectrum of outcomes. Beneficial lifestyle choices plenish resources that could cushion brain health from later insults. Detrimental factors can advance disease progression by stimulating the root cause. They may also spend existing resources, reducing support for prospective issues. We use neuroimaging to observe brain changes linked to these factors. We combine imaging methods to understand the effect of age on structure and function. Knowing how we expect the brain to change also informs disease research. For example, unexpected changes may suggest susceptibility to disease.

Project aims

  • Better understand how genetics and environments can alter an individual’s ageing brain health.
  • Develop translational biomarkers that are sensitive to ageing outcomes in animals and humans.

References

  • Brusini, I., MacNicol, E., Kim, E., Smedby, Ö., Wang, C., Westman, E., Veronese, M., Turkheimer, F.E. and Cash, D., [Pre-print] (2021). MRI-derived brain age as a biomarker of ageing in rats: validation using a healthy lifestyle intervention. bioRxiv.
  • MacNicol E., Wright, P., Kim, E., Brusini, I., Esteban, O., Simmons, C., Turkheimer, F., et al. [Pre-print] (2021), “Age-specific adult rat brain MRI templates and tissue probability maps”, OSF Preprints, 17 February, available at:https://doi.org/10.31219/osf.io/htgqn.
  • MacNicol, E (2021). ‘Longitudinal Characterisation of Healthy Ageing in Rats using Multimodal Magnetic Resonance Imaging’, PhD thesis, King’s College London, London.

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