7 May 2011. Scientists have long wondered why certain brain regions bear the brunt of Alzheimer’s disease. Plaques preferentially clog up the default-mode network, a set of interconnected brain regions that are most active when people are letting their minds wander. This network has a higher basal metabolism than other brain regions, and makes heavy use of glycolysis, or the incomplete burning of glucose, for energy. Now, a paper in the May 1 online Nature Neuroscience ties these observations together, suggesting that brain activity, as measured by glycolysis, influences Aβ deposition. Researchers led by David Holtzman at Washington University, St. Louis, Missouri, found that levels of extracellular, soluble Aβ in mouse brain correspond to local activity levels, with higher activity linked to more Aβ. Regions of the mouse brain that are analogous to the default-mode network in humans had the highest levels of glycolysis—and Aβ. Significantly, when the researchers raised or lowered neuronal activity, they saw corresponding changes in Aβ levels and plaque development later in life. “This may be one of the first explanations for why you get [AD pathology] in these areas,” Holtzman told ARF. The results also suggest that modulating brain activity in these networks, either pharmacologically or through lifestyle changes, could help prevent or delay AD.
The finding “argues that synaptic activity may be the dominant factor controlling Aβ levels and plaque formation,” Roberto Malinow at the University of California in San Diego wrote to ARF (see full comment below). He was not involved in the study. Sam Gandy at the Mount Sinai Medical Center in New York City noted in an e-mail, “The data here are beautiful and compelling.”
The default-mode network has caught the attention of scientists in the last decade. Early on, Randy Buckner at Washington University and Bill Klunk of University of Pittsburgh Medical School realized that its regions are the ones that deposit amyloid plaques early on in the course of AD (see ARF related news story on Buckner et al., 2005), and Buckner then worked with Keith Johnson’s group at Massachusetts General Hospital, Boston, to extend the analysis to cortical hub regions (see ARF related news story on Buckner et al., 2009). Other researchers have found that activity changes in these networks, as seen by functional imaging, foreshadow the development of AD (see ARF related news story on Greicius et al., 2004; Hedden et al., 2009; ARF related news story on Sperling et al., 2009). Most recently, research groups led by Marcus Raichle and Mark Mintun at WashU demonstrated increased glycolysis in these same regions using imaging techniques (see ARF related news story on Vaishnavi et al., 2010 and Vlassenko et al., 2010), which hinted at a connection between energy metabolism and Aβ pathology.
Holtzman’s group brings a different approach to the problem. These scientists developed in vivo microdialysis to measure the levels of soluble Aβ and other molecules in the interstitial fluid between cells. In previous work, they showed that jacking up synaptic activity with electrical probes increased the levels of extracellular, soluble Aβ in mice, while blocking activity with drugs lowered Aβ levels, demonstrating a direct relationship between activity and Aβ (see ARF related news story on Cirrito et al., 2005; ARF related news story on Cirrito et al., 2008). The group saw a similar link between activity and Aβ levels in people who received microdialysis as part of their neurological status monitoring following acute brain injury. Immediately after injury, levels of Aβ in the interstitial fluid were extremely low, but rose as the brain recovered and resumed synaptic activity (see ARF related news story on Brody et al., 2008).
Holtzman and colleagues wanted to take this further by examining the effects of endogenous synaptic activity on different brain regions, as well as looking at the long-term effects of varying Aβ levels. First author Adam Bero verified that aged Tg2576 AD mice had regional patterns of Aβ plaque deposition very similar to those seen in humans with AD, indicating that this mouse would be a useful model. Bero then showed that the concentrations of Aβ40 and Aβ42 in interstitial fluid in four-month-old mice were highest in areas that would have the most plaques at 18 months. Wild-type mice showed lower absolute levels but the same regional pattern in their ISF Aβ, suggesting this represents normal physiology.
To tie Aβ to brain activity, Bero and colleagues measured levels of lactate, which is produced by glycolysis. Lactate levels have been shown to correlate with neurotransmitter-mediated synaptic activity (see, e.g., Uehara et al., 2008) and indeed are frequently measured in humans as part of neurologic status monitoring after acute trauma. They found that the amount of lactate in the interstitial fluid varied in tandem with Aβ in both Tg2576 and wild-type mice.
The authors then employed several approaches to modulate neuronal activity. One was pharmacological: They administered picrotoxin, a GABA antagonist, to increase synaptic activity, and tetrodotoxin to decrease activity. Levels of lactate and Aβ in the interstitial space went up or down in parallel with activity. Bero and colleagues also manipulated physiological activity, by stimulating or trimming the mouse’s whiskers on one side and looking at corresponding changes in the barrel cortex connected to those whiskers. Aβ levels rose after whiskers were stimulated, while both lactate and Aβ dropped in barrel cortex after they were trimmed, again linking Aβ release to synaptic activity. In contrast to the clear relationship between Aβ levels and activity, Aβ levels did not correlate well with regional differences in clearance rates, or with differences in APP processing.
Bero and colleagues switched to seven-month-old APP/PS1 mice to examine the long-term effects of whisker manipulation, because this strain develops aggressive fibrillar plaques at a young age. After 28 days of whisker trimming, plaques on the deprived side grew only about one-quarter as much as those on the control side. Fewer new plaques formed, again suggesting that activity promotes pathology.
This presents a puzzle, as numerous epidemiological studies have suggested that cognitive stimulation and greater education, which presumably depend on greater neuronal activity, delay the onset of AD, not promote it. One possible answer, the authors suggest, is that activating task-oriented brain areas may reduce metabolism in the vulnerable default-mode network and therefore slow down Aβ deposition there. Holtzman told ARF, however, that it is equally plausible that education merely helps mask the early effects of AD, resulting in a later diagnosis, and does not affect Aβ pathways. If that is true, what causes some people to get AD while others do not?
Although the answer will require more research, there are some clues. For one thing, people who carry the ApoE4 risk allele have higher resting-state metabolism in the default-mode network (see ARF related news story on Filippini et al., 2009). They also have more brain amyloid. Holtzman noted that this network is the most used throughout the day. “I wonder if the explanation for what we’re finding in this paper has to do with how efficiently the brain utilizes its prominent networks,” he suggested. For example, perhaps specific genes regulate efficiency of brain energy metabolism, with some people having less efficient energy metabolism in the brain than others, resulting in more Aβ release, suggested Holtzman. Lifestyle factors such as stress and lack of sleep may also increase network metabolism, he said.
Holtzman is particularly interested in the sleep connection. His group previously showed that Aβ levels in the interstitial fluid fall during sleep (see ARF related news story on Kang et al., 2009). In the current paper, Holtzman and colleagues demonstrated that levels of lactate and Aβ are highest in young Tg2576 mice when they are awake, and lowest when they are asleep, suggesting that sleep is beneficial. In ongoing work, Holtzman is using animal models to study the mechanisms behind this effect. He is also measuring sleep patterns and AD biomarkers in healthy middle-aged people. His hypothesis is that people who regularly get more or better sleep will have less AD biomarkers as they age. “If you have very efficient sleep-wake cycles every day for most of your life, maybe that allows these networks to stay in balance better,” Holtzman speculated. Recently, researchers found that lack of sleep can cause localized “napping” among groups of neurons, which may explain why sleep-deprivation affects cognition. And other groups have linked dramatic changes in sleep patterns to cognitive decline, as well (see ARF related news story).
Holtzman believes the correlation between default-mode network activity and Aβ levels has significant implications for AD prevention. If people could modulate their brain network activity with lifestyle factors or medications, he said, it might delay disease onset.—Madolyn Bowman Rogers.
Bero AW, Yan P, Roh JH, Cirrito JR, Stewart FR, Raichle ME, Lee JM, Holtzman DM. Neuronal activity regulates the regional vulnerability to amyloid-beta deposition. Nat Neurosci. 2011 May 1. Abstract