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BNA 2023 | Characterizing protein accumulation in primary vulnerable neurons in Alzheimer’s disease
Alessia Caramello, PhD, Imperial College London, London, UK, shares an overview of her work using imaging mass cytometry (IMC) to study neuronal vulnerability in Alzheimer’s disease (AD) post-mortem brain samples. The aim of the ongoing project is to characterize the subset of neurons that is lost at the earliest stages of AD, in order to improve our understanding of what makes them vulnerable, which may have diagnostic and therapeutic consequences. IMC was used to identify and characterize primary vulnerable neurons (PVNs) with a 35-antibody panel. This technique enabled the study of multiple subpopulations at the same time, as well as providing information on the accumulation of misfolded proteins within the cells. Preliminary results have demonstrated layer-specific neuronal vulnerability in AD that aligns with previously published data. These data also suggest that vulnerability only partly correlates with p-tau and Aβ accumulation, but further analysis is needed. Dr Caramello discusses her planned next steps, as well as her goals to publish this data as a resource for other researchers investigating PVNs. This interview took place at The BNA 2023 International Festival of Neuroscience in Brighton, UK.
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Transcript (edited for clarity)
One of the reasons why Alzheimer’s is really difficult to be treated is because it’s not easy to be diagnosed at early stages. So what we’re trying to understand is how is the pathology developing at the very early stages of Alzheimer’s so that we can develop some new diagnostic tools or treatments to diagnose the disease early and then treat it early. So the idea here was to identify the very specific neuronal subpopulations that are initially lost at early stages of Alzheimer’s and understand why these populations, what makes them different from the other neuronal cell populations which brings them to being vulnerable and eventually die...
One of the reasons why Alzheimer’s is really difficult to be treated is because it’s not easy to be diagnosed at early stages. So what we’re trying to understand is how is the pathology developing at the very early stages of Alzheimer’s so that we can develop some new diagnostic tools or treatments to diagnose the disease early and then treat it early. So the idea here was to identify the very specific neuronal subpopulations that are initially lost at early stages of Alzheimer’s and understand why these populations, what makes them different from the other neuronal cell populations which brings them to being vulnerable and eventually die. So first of all, the main question was how do we visualize these cells? Because there’s been other works, for example, using single nuclei RNA-sequencing that are very high throughput. So you can analyze almost all of the cells that are in the brain and you can find the populations that are lost. However, with the single nuclei RNA-sequencing, you lose the actual protein expression and you lose the spatial information. Other techniques that were more traditional use normal immunofluorescence or immunohistochemistry, which however have very low throughput. So you only are able to analyze 1 or 2 markers at the same time. So our technique, which is imaging mass cytometry, we put together, let’s say the spatial information, protein expression and the higher throughput of markers analysis. So kind of joining somehow, with pros and cons and limitations, but trying to put together the high throughput of single nuclei RNA-sequencing but protein expression of immunostaining.
And so the first question was how do we visualize the majority of neuronal cell population in the brain and then using that to identify which of these subpopulations are lost. And so imaging mass cytometry is really good because it allows you to stain up to 35 antibodies at the same time. So we could not only look at neuronal cell populations, but then we could also stain for protein misfolding, which is obviously something that is very important, a pathology hallmark in Alzheimer’s disease, which is again something that for example cannot be done in single nuclei RNA-sequencing. So the first big step was to try to optimize all of these antibodies and we’re conducting our research in the postmortem human brain, so it’s also pretty challenging because the quality of the tissue is not always great and very variable. After a couple of years I managed to optimize a pretty good amount of antibodies. So we did manage to conduct a first analysis and now in the process of analyzing all of the data which are they seem to be quite interesting.
We found some neuronal subpopulations that are selectively lost and these seem to be the same that have been previously identified in other studies. So this is quite good because it means that our results are replicable based on previous results. And we also looked at how selective loss is correlated with misfolded protein accumulation. It seems like we see an intracellular accumulation of beta amyloid, but I don’t want to go too much into these results because we’re still in the way of confirming them with other techniques. For now it seems really exciting and we’re hoping to then be able to publish these not only as interesting results on which to base further studies, but also as a tool that can that other people can use because obviously this would be kind of like the first data set of so many protein expression markers on a human post-mortem tissue. So hopefully would be good for other people to use as well.
So ideally in the future, if we are able to develop better brain imaging techniques, we will be able to monitor the activity of the first neurons that are affected in Alzheimer’s. And that would be a great tool for diagnosing the disease at very early stages and then at the same time knowing which are the populations that are affected and why, we will be able to develop drugs that could target specifically the cell population and specifically whatever molecular mechanism that is affecting their survival. So it’s a great project for both developing a future diagnostic tool but also drug target.