Different Profiles of Microglial Activation in Alzheimer's disease

What's the science?

Microglia, the immune cells of the brain, may contribute to Alzheimer’s disease by becoming activated in response to brain pathology (also known as neuroinflammation). Currently, whether neuroinflammation is associated with Alzheimer’s progression (harms the brain) or whether it may be protective (helps to “eat” plaques in the brain) is still a matter of debate. This week in BrainHamelin and colleagues used PET imaging to examine how microglial activation in the brain is related to Alzheimer’s disease progression.

How did they do it?

PET imaging was used to measure the uptake of a radiotracer (18F-DPA-714) in the brain binding to activated microglia. A large group of patients with Alzheimer’s disease were scanned twice for activated microglia, once at baseline and once two years later. They were then followed up annually and scanned with MRI to measure brain volume (measure of Alzheimer’s progression) and given annual cognitive tests to assess dementia severity and cognitive function. Based on this, patients were split into “fast and slow decliner” categories. The microglial activation levels over time were also analyzed compared to a control group of healthy participants.

What did they find?

Having a high level of microglial activation at baseline was predictive of being a slow decliner. In patients with a high baseline neuroinflammation, cognitive performance was better and brain volume was more preserved, suggesting that more microglial activation at baseline is protective. At two years follow-up, microglial activation was higher in Alzheimer’s participants but not controls as would be expected. Increased microglial activation over time was related to worsening cognitive scores and brain atrophy, suggesting that it is harmful. However, when they examined neuroinflammation over time at an individual level, they found that those with the highest baseline microglial activation had the lowest increase in microglial activation over time. They concluded that there is a dynamic relationship, whereby neuroinflammation may affect patients differently, depending on their original level of microglial activity. Microglial activation appears to be protective initially, but exacerbates Alzheimer’s disease over time; to a greater extent in those who had low levels of microglial activation to begin with.


What's the impact?

This is the first study to show that neuroinflammation may affect individuals with Alzheimer’s disease differently depending on their baseline level of microglial activity. It shows us that microglial activation may be helpful or harmful depending on the individual and how far their disease has progressed. Understanding the role microglial activation play in Alzheimer’s disease is an essential part of understanding how the disease progresses.

L. Hamelin et al., Distinct dynamic profiles of microglial activation are associated with progression of Alzheimer's disease. Brain (2018). Access the original scientific publication here.

A Model for the Spread of Tau through Connected Tracts in the Human Brain

What's the science?

In Alzheimer’s disease, tau proteins accumulate in the hippocampus resulting in neurofibrillary tangles. Beta-amyloid plaques, another form of protein aggregation, are thought to help tau proteins spread. One way that tau may spread from neuron to neuron is through neural connections, while another possibility is that it simply spreads to neurons located close by. This week in Nature Neuroscience, Jacobs and colleagues used brain imaging to ask: ‘How does  tau spread?’

How did they do it?

Healthy older participants from the Harvard Aging and Brain Study were scanned over several years with positron emission tomography (PET) imaging to measure tau and beta-amyloid in the brain, and diffusion tensor imaging (DTI) to measure connectivity (of white matter tracts) in the brain. They tested whether beta-amyloid in the brain at baseline predicts hippocampal volume loss. They then measured whether this volume loss predicts abnormalities in the hippocampal cingulum bundle (a white matter tract that innervates the hippocampus and connects it with the posterior cingulate cortex) and in turn, whether these abnormal connections predict the accumulation of tau in the posterior cingulate cortex. They ran control analyses with another tract (that does not innervate the hippocampus) and another close by region. Associations with memory and executive functions were also assessed to understand the clinical relevance. 

What did they find?

Brain beta-amyloid level at baseline predicted hippocampal volume loss. The hippocampal volume loss also predicted abnormal white matter tract connectivity over time in the hippocampal cingulum bundle, but not in other white matter tracts close by that do not directly connect with the hippocampus. The abnormal connectivity in this tract predicted the accumulation of tau in a connected region called the posterior cingulate cortex, but not in another adjacent control region. Collectively, these changes were associated with memory decline over time. This means that early Alzheimer’s pathology (beta-amyloid) initiates a cascade of hippocampal volume loss followed by abnormal tract connectivity and the spreading of tau along this tract. 


What's the impact?

This is the first study to confirm that tau likely spreads via neural connections (rather than just to regions close by) from the hippocampus, facilitated by beta-amyloid in the brain. Clarifying the order in which Alzheimer’s pathology spreads, as well as the mechanism through which it spreads is critical for helping to target the advancement of Alzheimer’s disease.


You can reach out to her about her work at @DrHeidiJacobs on Twitter.

H. I. L. Jacobs et al., Structural tract alterations predict down-stream tau accumulation in amyloid positive older individuals. Nat. Neurosci. (2018). Access the original scientific publication here.

Amyloid-β Proteins Differ Between Alzheimer’s Disease Subtypes

What’s the science?

Alzheimer’s disease can be genetically inherited (familial/heritable) or sporadic. A key feature of the disease is the build up of amyloid-β proteins in the brain. A mutant form of amyloid-β is found in heritable Alzheimer’s disease, and is thought to cause the misfolding of normal amyloid-β proteins, leading to a more rapid build up. Recently in PNASCondello and colleagues probed the structure of different conformations or strains of amyloid-β proteins, to see whether they differ between heritable and sporadic Alzheimer’s.

How did they do it?

They performed confocal spectral imaging using three fluorescent dyes that bind to amyloid protein and are sensitive to protein structure in mouse and human brains. Different dyes bind differently to distinct protein conformations. In mice, they combined mutated and non-mutated amyloid-β, to test whether the mutated form could cause protein misfolding.

What did they find?

The heritable and sporadic amyloid-β plaques exhibited different fluorescence intensities after staining with the three dyes, meaning they could be differentiated. The fluorescence emission spectra also differed between disease types, suggesting different protein conformations. In mice, when mutated and non-mutated amyloid-β were mixed, the mutated amyloid-β acted as a template allowing the normal amyloid-β to misfold.


What’s the impact?

This is the first study to use this fluorescence microscopy technique to assess different strains of amyloid-β. The different protein structure in these amyloid-β strains could help to explain differences in the rate of disease progression, for example between familial Alzheimer’s disease compared to sporadic Alzheimer’s disease. Understanding the differences in protein structure between these amyloid strains may help clarify how they cause other proteins to misfold and the disease to spread.

C. Condello et al., Structural heterogeneity and intersubject variability of Aβ in familial and sporadic Alzheimer’s disease. PNAS. 115(4) (2018).

Access the original scientific publication here.