How Vesicles Shuttle Tau Filaments Throughout the Brain in Alzheimer's Disease

Post by Lila Metko

The takeaway

Many cell types, including neurons, release compartments called extracellular vesicles (EVs) for signaling and transportation. The cell’s transportation of tau, a protein that misfolds and propagates in Alzheimer’s disease, is carried out through these EVs. This research reveals that impairments in the function of lysosomes, organelles involved in breaking down cellular waste, may be involved in the association of tau with EVs and shows that tau filaments in EVs are short and tethered to their membranes. 

What's the science?

Tau is a protein that maintains the structural integrity of neurons in healthy individuals but becomes hyperphosphorylated, misfolded and aggregated in the brains of people with Alzheimer’s disease. Tau has a greater ability to seed new misfolded proteins when associated with EVs. It is unknown which types of tau associate with EVs, which EVs contain tau, and how tau associates with EVs. This November in Nature Neuroscience, Fowler and colleagues investigate how EVs shuttle tau throughout the brain. 

How did they do it?

The authors analyzed frontal and temporal lobe tissue that had been obtained from Alzheimer’s disease patients post-mortem. They separated the tissue using density gradient centrifugation, a type of analysis that separates molecules by density. This allows for the different subtypes of EVs to be separated into different fractions. The fractions were then analyzed by liquid chromatography-tandem mass spectrometry and immunoblotting to determine the protein content of the EV types. Additionally, they confirmed the ability of the EVs to seed further tau aggregation using cell culture and a transgenic mouse line, expressing human tau. Cryo-electron microscopy and Cryo-electron tomography were used to analyze the structure of the tau filaments found in the EVs. 

What did they find?

The authors found that only fractions 4-6, fractions with medium to high density, contained EVs with tau filaments and that these fractions also had the highest amount of lysosomal proteins. Further analysis showed that there were two types of tau filaments within the EVs, one with a symmetrical organization of its subcomponents and another with a non-symmetrical organization that was shorter than those found in neurofibrillary tangles (aggregated tau protein deposits seen in Alzheimer’s disease). Shorter tau filaments have a greater ability to seed tau assembly in animal models. The authors also found that tau filaments within EVs were either tethered to the EV membrane or tethered to a tau filament that was connected to the membrane. Additionally, these filaments were all tethered at their ends. This gives researchers insight into the tethering process of tau filaments to EVs and could potentially inform therapeutic interventions. 

What's the impact?

This research provides further insight into how tau filaments are transported out of the cell through EVs and propagate through the brain in Alzheimer’s disease. These findings can help us to develop therapeutics that target tau propagation. 

Access the original scientific publication here.

How Sleep Improves Behavioral Performance

Post by Laura Maile

The takeaway

Sleep is known to improve learning and memory, but the underlying neural mechanisms are not well understood. In the visual and prefrontal cortex of the brain, synchrony of neural network activity is decreased following sleep, which correlates with improved performance in visual tasks. 

What's the science?

Most previous research on how sleep improves learning and memory has been done in humans, where only non-invasive procedures like EEG are possible, or in rodents where studies have only investigated the influence of sleep on memory. 

This week in Science, Kharas and colleagues used multielectrode arrays inserted in the brain to record neuronal activity in macaques to see how sleep affects performance on behavioral tasks. The electrodes were inserted into specific brain areas to detect the changes in activity patterns across populations of neurons during behavioral tasks and sleep, offering the authors a more accurate view of non-rapid eye movement (NREM) sleep-related activity. Using macaque monkeys allowed them to observe performance in complex tasks than is possible with other non-human mammals.

How did they do it?

Five macaque monkeys were trained to complete visual discrimination tasks while experimenters recorded their brain activity. Monkeys then completed identical tasks before and after 30-minute rest periods, where their brain activity was continually monitored. NREM sleep was confirmed during rest periods using a polysomnogram (combination of electroencephalogram, eye movement, and muscle monitoring) and video analysis of their eyes and face. Multielectrode arrays, consisting of sets of multiple electrodes inserted into distinct areas of the visual cortex and prefrontal cortex, were used to measure neural activity during the tasks and the rest period. Local field potentials (LFP) were recorded, which allowed experimenters to detect neural activity across a population of neurons and analyze patterns of synchronized activity in specific frequency bands. Next, they replaced sleep with a 30-minute period of neural stimulation in the delta frequency, using the implanted electrodes in the V4 visual cortex. They repeated the neural activity analysis and the behavioral tasks before and after stimulation. Finally, they used network modeling of the visual cortex to model the observed changes in activity seen in the visual tasks following sleep. This allowed them to determine the likely cause of the observed changes in activity and synchrony that were associated with better performance. 

What did they find?

During the NREM phases of 30-minute sleep periods, LFP analysis of neuronal spiking activity showed decreased power in the gamma band and increased power in the low-frequency bands, especially the delta band, commonly associated with sleep. The increases in the delta band were associated with an increase in synchronization of neuronal firing in all tested brain areas. Performance in a visual discrimination task improved in monkeys after sleep and compared to control monkeys that sat in a dark room but were not allowed to sleep. Neural activity of the sampled population of neurons became desynchronized after sleep in all recorded areas and noise correlation decreased after sleep. Neural firing increased in all brain areas during the task after sleep but remained unchanged in monkeys that did not sleep. 

Importantly, the observed changes in synchronized activity and neural firing were correlated to improved performance in behavioral tasks. They found that by stimulating V4 visual cortex in the delta frequency while the animal was awake, they were able to achieve similar effects on neural firing, synchrony of activity, and behavioral performance that occurred due to sleep. This suggests that the increase in synchronized activity seen during sleep leads to reduced synchrony during tasks completed after sleep, allowing increased accuracy of system activity and improved task performance. Finally, the authors’ network models revealed that depression of inhibitory synapses likely accounts for the observed changes in neural population activity seen during the behavioral task after sleep. This suggests that the improvements in the discrimination task may be due to a net increase in excitatory synaptic activity between cortical neurons.

What's the impact?

This study found that activity across neural networks in the visual and prefrontal cortex becomes more synchronized during sleep, but less synchronized after sleep. This decrease in synchrony is associated with increased firing and improved performance in visual discrimination tasks. This study was also the first to demonstrate successful invasive electrode stimulation of distinct brain areas to improve performance in behavioral tasks, which could lead to future improvements in brain neuromodulation in humans. 

Access the original scientific publication here.

The Relationship Between COVID and Cognitive Function

Post by Anastasia Sares

The takeaway

A new meta-analysis showed that having COVID-19 (even a mild to moderate case) was linked to lower performance on cognitive tests after a person was no longer infected. Severe cases were linked to worse performance than mild or moderate cases. This is part of a larger pattern for viral diseases in general. 

What’s the science?

Getting infected with SARS-CoV-2—the virus that causes COVID-19—can lead to symptoms like fatigue and brain fog, which sometimes last long after a person has recovered from the virus itself. In light of these symptoms, it is important to understand what effect COVID-19 may have on the public's long-term cognitive health. We need to know whether people’s self-reported cognitive issues correspond to actual performance on cognitive tests—in other words, an objective cognitive impact. Many studies were published on this topic during the years of the pandemic, but to better understand the trends, we need more than a lot of individual studies. Each study has slightly different methods and is conducted on a different group of people. Meta-analysis is a technique that takes the results from many different studies and aggregates them to help us come to an overall conclusion.

Recently in Neuropsychology Review, Austin and colleagues conducted a meta-analysis to understand the objective cognitive effects of COVID-19 infection.

How did they do it?

The authors sifted through multiple databases of scientific literature using keywords related to Sars-Cov-2/COVID and cognitive functioning, searching specifically for studies that evaluated cognition after the initial acute phase of the disease. They eliminated studies that were duplicates, did not address their main questions, did not involve mild to moderate COVID cases, or did not include objective measures of cognitive functioning (among other criteria). Then, they divided the studies into three categories: first, those that compared cognitive performance between a non-COVID control group and a mild-COVID group, second, those that compared the performance of a mild COVID group to an established testing norm, and third, a group mild or moderate COVID versus a group with severe COVID symptoms. The prediction was that the COVID groups would perform worse overall than the standardized norms as well as the control groups and that severe COVID would lead to worse performance than mild or moderate COVID. 

What did they find?

In all three groups, scores across the cognitive testing spectrum were lower for the COVID groups. Memory, language, and combined measures were significantly affected. In addition, the groups with severe COVID performed worse than those with mild or moderate COVID in attention, memory, and executive function. However, visuospatial functioning was not affected. It is important to mention that the size of these effects was not large and differed quite a bit across studies; they were most pronounced in those with long-lasting symptoms after their illness. The authors gave some possible explanations for why COVID might lead to cognitive symptoms. The virus could have direct effects on brain tissue, or it may contribute indirectly via neural inflammation and other stress-induced processes. People may also experience distraction due to ongoing physical pain or depressive symptoms. These ideas are based on what we know about similar dynamics in other viral diseases such as influenza, herpes, and hepatitis. Ultimately, there are many questions left to be answered, especially as this virus evolves and changes over time.

What’s the bottom line?

As COVID-19 transitions from being pandemic (new and spreading out of control) to endemic (constantly present in the population but more predictable), it is important to understand how it affects cognitive health, especially since the population is also aging in many countries. Given this new risk to cognitive health, it is more important than ever to focus on finding therapies that can prevent or slow cognitive decline.

Access the original scientific publication here.