How Exercise Protects Neurons from Aging and Alzheimer’s

Post by Anastasia Sares

What's the science?

A number of studies are showing that physical activity and brain health go hand in hand, especially where aging and Alzheimer’s are concerned. But how exactly does exercising our body affect our brain cells? This week in Neurobiology of Aging, Berchtold and colleagues identified a few key cellular functions influenced by aging that might be recoverable through physical activity.

How did they do it?

The authors examined human brains post-mortem. The participants were part of a large project and health data about them was already being recorded (like hours of weekly exercise, age, or cognitive status). When a person in the study passed away, the authors obtained a small sample of brain tissue from the hippocampus: an important structure involved in memory formation. They broke open the cells from each sample and used microarray technology to find out what genes were being expressed. A microarray chip has thousands of small wells that bind to specific molecules, so by looking at where molecules were binding to the chip, it was possible to see which genes were activated. or expressed.

Two completely independent sets of data: one data set had two groups differing on amount of exercise (high- vs low-exercise), and the second data set had three groups, one with young adults (20-59 years), one with normal aging adults (69-99 years), and one with Alzheimer’s disease (AD; 73-99 years). In the first data set, the authors looked for differences in gene expression that were significantly affected by exercise. In the second set, they looked for differences in expression affected either by age (comparing younger vs. older participants), or cognitive status (older normal aging vs Alzheimer’s). Finally, the authors combined the results and found genes that were affected by both exercise and aging: they called these “anti-aging/AD genes.”

What did they find?

Of the overlapping genes, about 95% of the genes were affected in opposite ways by aging and exercise—70% of these genes showed declining expression with aging and increased expression with exercise. This suggests that exercise counteracts many of the effects of aging and Alzheimer’s. A large number of the genes were related to mitochondria: the structures inside a cell responsible for producing energy. Another group of genes were involved in communication between neurons at the synapse, where one neuron releases chemical messengers to be received by another. Other genes involved neuron infrastructure and plasticity.

What's the impact?

Energy production declines with age, even on the level of the cell. Exercise can keep neurons youthful, and it seems to do this by repairing gene expression, specifically for mitochondrial and synaptic functions. The authors’ use of independent datasets to verify their findings is an important research method that made their results more reliable.

Berchtold et al. Hippocampal gene expression patterns linked to late-life physical activity oppose age and AD-related transcriptional decline. Neurobiology of Aging (2019). Access the original scientific publication here.

Homeostatic Mechanisms Balance Synaptic Growth and Function

Post by Shireen Parimoo

What's the science?

Over the course of development, neural synapses (junctions where neurons communicate with their targets) grow, shrink, change in numbers, and undergo structural changes, but synaptic function or strength remains stable. Even in the presence of genetic mutations, synaptic strength often remains stable and within a narrow physiological range. It is currently not clear how synapses maintain consistent levels of activity despite the structural variability introduced during development or by mutations. This week in The Journal of Neuroscience, Goel and colleagues investigated the structural and functional neural mechanisms that help stabilize synaptic strength in mutant Drosophila (fruit flies) with disrupted synaptic growth.

How did they do it?

Aberrant synaptic growth and structure is associated with a variety of neural diseases. The authors first identified 300 genetic mutations linked to neural diseases and obtained Drosophila stocks that carried those mutations (mutant lines). They characterized the neuromuscular junction – a type of synapse connecting motor neurons and muscles in each of these 300 mutants. In particular, they measured synaptic growth based on a) the number of synaptic boutons (axon terminals) and b) synaptic strength by electrophysiologically recording the amplitude of excitatory post-synaptic potentials (EPSPs) evoked by stimulation. Mutant lines were selected if they had drastically altered synaptic growth but normal synaptic strength. To determine how synapses with enhanced or reduced growth maintain their strength, the authors investigated the relationship between structural and functional properties of synapses in mutant lines. Structural properties included parameters like the size of boutons and the number and area of active zones (synaptic regions where neurotransmitters are released) at a synapse. Postsynaptic parameters included the amount of postsynaptic neurotransmitter receptors. Functional properties included the quantal content of presynaptic neurons (i.e. the number of synaptic vesicles released upon stimulation) and the amplitude of the spontaneous EPSP events that occur in the absence of any stimulation. The authors systematically examined these properties in mutant lines with reduced and increased synaptic growth and compared them to wild-type Drosophila.  

What did they find?

The authors systematically probed synaptic growth and function in the 300 mutant lines and identified 12 with over-grown (too many boutons) or under-grown (fewer boutons) neuromuscular junctions, and 40 with reduced synaptic strength (EPSP amplitude) compared to wild-type Drosophila lines. For the mutant lines that had reduced EPSP amplitude, no change in synaptic growth was observed, indicating that defects in synaptic function occurred independent of altered growth. Conversely, normal synaptic strength was observed in the 12 mutants with dramatic changes in synaptic growth. The authors thus proposed a “homeostatic model” for maintenance of synaptic function, whereby neurotransmitter release at each bouton is reduced at synapses with more boutons but greater at synapses with fewer boutons. These mutants interestingly employed three main strategies to maintain normal synaptic output. When bouton numbers were massively reduced, either bouton size was enlarged to accommodate more neurotransmitter release and maintain normal synaptic strength or spontaneous EPSP amplitude and receptor levels were enhanced to increase postsynaptic sensitivity and compensate for reduced neurotransmitter release. In contrast, synaptic overgrowth mutants exhibited an increase in the total number of neurotransmitter release sites but each of these individual sites were smaller, leading to an adjustment in presynaptic release per bouton. Thus, homeostatic mechanisms stabilize overall synaptic strength while permitting substantial flexibility in synaptic growth.

What's the impact?

This study is the first to illustrate the adaptive pre- and postsynaptic mechanisms that help maintain synaptic strength despite large differences in synaptic growth. These findings enhance our understanding of how neural function remains stable while the underlying synaptic structure is constantly changing during development, maturation, aging, and even disease.

Goel et al. A screen for synaptic growth mutants reveals mechanisms that stabilize synaptic strength. The Journal of Neuroscience (2019). Access the original scientific publication here.

Early Skill Learning Occurs Predominantly at Rest

Post by Lincoln Tracy

What's the science?

Learning a new motor skill typically consists of short periods of active practice—physically doing the task—interspersed with short periods of rest. The combination of practice and rest strengthens the memory in our brain so we can perform the skill better. Traditionally, the consolidation of a new skill has been thought to occur over a period of hours or days. This week in Current Biology, Bönstrup and colleagues examined the time course of practice and rest in how we learn new motor skills on an unprecedented short time scale.

How did they do it?

Healthy right-handed individuals were recruited to participate in a two-day study where they trained and were tested on a procedural motor-skill task on successive days. The motor task involved pressing keys on a keypad in a specific sequence of five key presses. Participants were taught the key press sequence on the first day of the study. They used their left—or non-dominant—hand to perform the key press sequence while seeing the sequence on a computer monitor. Participants completed 36 training trials on the first day. Each trial involved a 10 second period where the participants practiced the key press sequence, followed by a 10 second rest period. Participants returned to the laboratory the next day and were tested on their performance on the task. Nine trials were performed on the testing day. Throughout both the training and testing days the brain activity of participants was recorded by magnetoencephalography (MEG) to identify potential brain mechanisms that supported skill learning.

What did they find?

The authors found that the early learning of the motor skill was driven by increases in performance between practice periods. That is, there was a greater increase in the speed at which participants completed the key press sequences between the end of one trial and the beginning of the next, rather than over the course of each trial. They also found that this learning was predicted by oscillating beta-band (16 – 22 Hz) activity in frontoparietal regions of the brain. Specifically, downregulation of this oscillating beta-band activity at rest was identified as the intrinsic neural signature that went along with performance increases in-between trials.

What's the impact?

This study is the first to show that a substantial part of early skill learning occurs while we are at rest, and that these improvements can be predicted by activity in the frontoparietal region of our brains. These findings significantly change the way researchers traditionally think about the time it takes us to form a memory and learn new skills—they show this can occur over a period of seconds, rather than hours or days.

Marlene Bönstrup et al. A Rapid Form of Offline Consolidation in Skill Learning. Current Biology (2019). Access the original scientific publication here.