Modelling Alzheimer's Disease
Alzheimer’s Disease is one of the most common forms of dementia; it causes progressive memory loss and cognitive decline. The pathological hallmarks of the condition are deposits of abnormal proteins, including beta amyloid and tau. But there are also a range of other factors that almost certainly contribute to the disease and might provide useful insights into the mechanism of the condition and act as a marker for its progression as well as the impact of potential disease-arresting treatments. And that’s what Quadri Adewale wanted to pull together: an integrated model of the imaging, metabolic profiles and underlying genetic expression patterns across the Alzheimer brain…
Quadri - There are a number of beliefs about the possible causes of Alzheimer's disease. For example, one of the beliefs is that Alzheimer's disease is caused by the deposition of a protein called amyloid. That is also another belief that the disease is associated with the formation of insoluble version of a protein called "tau". There are also other evidences pointing to the role of genes in the cause of the disease. So, in our research, we felt that if we could measure these biological processes, like the position of amyloid, abnormal function of genes, deposition of tau and so on, if we could measure these processes, perhaps we'll be able to understand the interactions between all these processes in causing disease.
Chris - Historically, the Alzheimer's field used to fall into two camps: "the BAPtists", who believed in beta amyloid, and "the TAUists", who believed in tangles of tau; you're saying actually, everyone needs to talk together and talk to the molecular biologists because, in fact, there might be a whole range of things all going on at the same time, which all interact. And we've got to unpick what the relationship is...
Quadri - Exactly! Apart from beta amyloid and tau, there are other processes, like inefficient usage of glucose, abnormal blood flow, and so on. So what we did in our study was to develop a method, using mathematics, and we applied this method to combine data obtained from Alzheimer's disease patients, as well as healthy people who are elderly. These data measure, those biological processes that we talked about earlier. Specifically, we looked at measurements of amyloid protein deposition, tau, blood flow in the brain, glucose breakdown and usage, the activities of the neurons, as well as death of neurons. Then we also looked at gene activities. Then we divided the participants into two. So we had those with Alzheimer's disease and those who are elderly, but healthy. We then use the healthy participants to study the process of healthy ageing while we use the Alzheimer's patients to study Alzheimer's disease progression. So using the mathematical methods that we developed, we asked which genes influence the interactions between all of that biological processes? And how does this interaction affect brain health in both aging and Alzheimer's disease?
Chris - I suppose it must be tricky to try to disentangle what is the healthy aging process from what then becomes pathological, because there's going to be a huge overlap. Did you manage to do that though?
Quadri - Yes! We found some overlap. To differentiate between the two, we discovered that Alzheimer's disease is a much more complex process than healthy ageing. So, for example, the number of genes that we found to underline healthy ageing were just eight, while the number of genes that we found for Alzheimer's disease were about 111. Which tells us that Alzheimer's Disease is a much more complex process. And, um, when we did the analysis of the biological parts with all the functions that are associated with these genes, we found that some of the functions in healthy ageing were also in Alzheimer's disease. But, uh, the functions we found in Alzheimer's disease were much more comprehensive than what we found in the healthy ageing.
Chris - Does this mean then, given that you've identified these genes, which, which appear to be so intrinsically linked to the process, that we can use them as some kind of diagnostic marker or that we could even use them as a progression marker to work out whether interventions, whether those are behavioural interventions, lifestyle interventions, even vaccines that people are coming up with to offset the progression of Alzheimer's disease, whether they're working?
Quadri - Yes. It's possible to use them as diagnostic markers. And I think the application area that's much more relevant to our work is using them for therapeutics, which genes are altered for each patient? And, um, if we could identify these, it's possible to design intervention for each patient. And as we know that, um, most of the drugs that we have out there, some of these drugs work for some groups of patients and they don't work for others. So in our study, we are able to disentangle these differences and we believe that if we apply these to the administration of basic interventions, uh, it will be very useful. So that's one part. The other part is that there are some beliefs that the cure for Alzheimer's disease might involve combination therapy. So what I mean by this is that instead of targeting beta-amyloid alone or tau alone, it might be more efficient to target as much as possible of the altered process in the disease.
Chris - And, of course, if you understand what genes are involved in the process, one has the opportunity to understand more about the mechanism of the disease and those mechanisms may vary between individuals and that sort of comes back to the point you're making about personalising the treatment.
Quadri - Exactly. Yes.
Chris - Does it throw open any avenues that we hadn't considered previously?
Quadri - Yes. Previous studies have only looked at which genes are altered or dysregulated in Alzheimer's disease. But in our study, we were able to - beyond identifying the genes that are implicated - we were able to know which other factors in the disease are being influenced by these genes? And, um, interestingly, most of the genes and the processes they've been reported in, in studies of animal models, and so mechanisms that we identify, a whole lot of them, have not been reported before. And this actually opens an avenue for the validation of these mechanisms that we identified.