Alzheimer’s disease is one of the most complex diseases known, with many different factors affecting its progression; identifying the main cause is still something that’s yet to be found.
The progressive neurodegeneration of the disease is characterised by the accumulation of β-amyloid plaques around nerve cells, and also neurofibrillary tangles that destroy the nerve’s cytoskeleton within the brain.
This leads to loss of cells and synapses which results in cortical atrophy; that is, the shrinkage of the brain (Figure 1, normal vs. diseased brain).
The main issue with treating Alzheimer’s is that the current diagnostics of it are poor. It is usually diagnosed towards the late stages of progression or by post-mortem examination of brain tissue. New methods are needed to help try and identify the disease earlier on and thus help treat it more effectively to slow its progression. This requires finding new biomarkers that can help characterise the progression of the disease.
High levels of a certain protein identified with the disease (ZAP70) can be used as a measure to see how evolved the disease is. We can model these on an interactive map to find links to other biomarkers that could also be an indicator of Alzheimer’s (Figure 2).
Once the biomarkers have been identified they can then be used as pharmaceutical targets to help try and treat the disease.
One possible target we came up with is the ADAM family of proteases which can be targeted to help try and reduce the level of β-amyloid production; an example drug for this is Congo red (Figure 3).
School of Mathematical Sciences, University of NottinghamUniversity Park NG7 2RD
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