The Time Of Day We Eat Is Associated with Diet-Induced Obesity

Post by Flora Moujaes 

What's the science? 

Worldwide obesity has nearly tripled since 1975: currently over 13% of the world’s adult population is obese. This increase in obesity is correlated with the more widespread availability of highly processed energy-dense rewarding foods that encourage snacking outside of regular meal times. However, it is not just the number of calories consumed that are important for understanding weight gain, but also when they are consumed. Proper maintenance of energy throughout the day requires that meals are synchronized with daily metabolic rhythms. For example, even if two mice consume the same number of calories, eating food at different times (e.g. snacking) could lead to obesity in one mouse but not the other. This issue is particularly prevalent in modern society as the central pacemaker is under constant dysregulation by artificial light. This week in Current Biology, Grippo et al. investigate the mechanisms through which the increased availability of energy-dense food and feed times lead to diet-induced obesity. 

How did they do it? 

To explore the mechanisms underlying diet-induced obesity, mice were either fed a diet comparable to that eaten in the wild, or had unlimited access to a high fat, high sugar diet. To examine the involvement of dopamine in diet-induced obesity, the cre-lox recombinase enzyme (an enzyme that allows you to knock out genes solely in subsets of cells e.g. the brain) was used to knock out the Drd1 gene in the brain. This gene encodes the D1 subtype of the dopamine receptor, which is the most abundant dopamine receptor in the central nervous system. These mice are referred to as the ‘knockout’ mice. Finally, to explore exactly where in the brain dopamine is involved in diet-induced obesity, the researchers selectively restored Drd1 expression in (1) the nucleus accumbens or (2) the suprachiasmatic nucleus (SCN). The nucleus accumbens was chosen as it is the reward processing center of the brain. The SCN was chosen as it is the main biological clock: the SCN receives light cues from the eyes and interprets them as the time of day, as well as cues when the body consumes and metabolizes food.

What did they find?

Researchers first showed that unlimited access to energy-dense food led to obesity. While mice fed a diet akin to that eaten in the wild maintained normal eating and exercise schedules and proper weight, mice with unlimited access to energy-dense food rapidly developed obesity, diabetes, and metabolic diseases. However, knockout mice with impaired dopamine D1 receptor functioning were resistant to weight gain following exposure to unlimited energy-dense food. Researchers also found that unlimited access to energy-dense food led to eating at irregular times. As nocturnal animals, mice usually eat 80% of their food during the night when exposed to a healthy diet, however mice with unlimited access to energy-dense food only ate 60% of their food during the night. In contrast, knockout mice with impaired dopamine D1 receptor functioning did not change their feeding times following exposure to unlimited energy-dense food. Taken together, these data suggest that D1 is important for the overconsumption of energy-dense food, predominantly during rest, leading to obesity.

Mice with restored D1 dopamine receptor functioning in the nucleus accumbens did not gain weight when exposed to unlimited energy-dense food - while they did increase their consumption of food during rest, they did not increase their overall calorie intake and therefore, did not become obese. In contrast, mice with restored D1 dopamine receptor functioning in the central circadian clock (SCN) did gain a substantial amount of weight when exposed to unlimited energy-dense food. Both their consumption of food at rest and overall calorie intake was significantly increased. Overall, this indicates that dopamine D1 receptor functioning in the central circadian clock (SCN) is crucial for diet-induced obesity. 

What's the impact? 

This study uncovered a novel mechanism for understanding how energy-dense diets lead to obesity, defining a connection between the reward and circadian pathways in the regulation of pathological calorie consumption. The authors demonstrate that dopaminergic signalling within the central circadian clock (SCN) disrupts the timing of feeding, resulting in an overconsumption of food, which leads to obesity, diabetes, and metabolic disease. This research not only has significant clinical implications by furthering our understanding of the mechanisms that underlie obesity but also helps to explain the growing popularity and effectiveness of diets that involve time-restricted feeding (e.g. intermittent fasting).

Grippo et al. Dopamine Signaling in the Suprachiasmatic Nucleus Enables Weight Gain Associated with Hedonic Feeding. Current Biology (2020). Access the original scientific publication here.

Astrocytes Detect Changes in Intracranial Pressure and Maintain the Homeostatic Control of Brain Blood Flow

Post by Amanda McFarlan 

What's the science?

Cerebral perfusion pressure, determined by the difference between mean arterial blood pressure and intracranial pressure (pressure inside the skull), is responsible for driving blood flow and delivering oxygen to brain tissue. Cerebral blood vessels within the brain are wrapped with the endfeet of astrocytes, a type of glial cell important for the metabolic and structural support of neurons. Blood vessels respond to changes in intracranial pressure by dilating or constricting, which likely causes structural changes to the astrocyte endfeet, and thus makes astrocytes ideally located to act as pressure sensors in the brain. This week in Nature Communications, Marina and colleagues tested the hypothesis that astrocytes in the brain act as physiological sensors that detect changes in blood flow. 

How did they do it?

The authors investigated how decreasing cerebral perfusion pressure affects cerebral blood flow. To induce acute decreases in cerebral perfusion pressure, the authors increased intracranial pressure in adult rats by infusing saline into the lateral cerebral ventricle. Then, they recorded changes in calcium levels from cortical astrocytes in response to increased intracranial pressure using in vivo 2-photon imaging. Next, the authors studied how astrocytes in the brainstem (close to the sympathetic nervous system control circuits) respond to changes in cerebral perfusion pressure. To do this, they used confocal microprobe imaging to record the frequency and duration of calcium signals from astrocytes of the ventrolateral medulla oblongata (part of the brainstem) in response to changes in cerebral perfusion pressure. Finally, the authors investigated the role of brainstem astrocytes in mediating homeostatic mechanisms that are initiated with increased intracranial pressure. To accomplish this, they interrupted the signalling between astrocytes and sympathetic nervous system neurons by virally expressing either the light chain of tetanus toxin (TeLC), the dominant negative SNARE (dnSNARE), or an ATP-degrading enzyme transmembrane prostatic acid phosphatase (TMPAP) in astrocytes of the ventrolateral medulla oblongata. They then measured arterial blood pressure, heart rate and sympathetic nerve activity in response to increased intracranial pressure.

What did they find?

The authors found that increasing the intracranial pressure by 10-15 mmHg (i.e. what would be expected to occur in response to an acute change in posture) caused a reduction in cerebral blood flow in the brain by 40% as well as increased systemic arterial blood pressure and heart rate, which facilitated oxygen delivery to the brain. Then, using 2-photon imaging, they revealed that cortical astrocytes had robust calcium signals in response to increased intracranial pressure, suggesting that the astrocyte activity was elevated. They also showed that the dilation of cortical blood vessels (that are wrapped by astrocyte endfeet) in response to increased intracranial pressure preceded the increased calcium signals in astrocytes. This suggests that astrocytes may play a role in mediating blood vessel dilation. Next, the authors found that, similar to astrocytes in the cortex, the frequency and duration of astrocyte calcium signals in the ventrolateral medulla oblongata (a region of the brainstem) was increased. Finally, they determined that control rats with intact astrocyte signalling showed increased levels of arterial blood pressure, heart rate and sympathetic nerve activity in response to increased intracranial pressure, while rats expressing either TeLC, dnSNARE or TMPAP in brainstem astrocytes did not show any change. Together, these findings suggest that brainstem astrocytes may use calcium-dependent signalling to activate sympathetic control circuits in response to changes in intracranial pressure.

What’s the impact?

This is the first study to show that both cortical and brainstem astrocytes sense changes in cerebral perfusion pressure in the brain. Moreover, brainstem astrocytes use calcium-dependent signalling to activate compensatory mechanisms that maintain blood flow and oxygen delivery to the brain. Together, these findings suggest that astrocytes may be important physiological sensors in the brain, responding to changes in pressure and activating sympathetic control circuits that help to maintain homeostatic control of cerebral blood flow. 

Marina et al. Astrocytes monitor cerebral perfusion and control systemic circulation to maintain brain blood flow. Nature Communications (2020). Access the original scientific publication here.

Pain Prediction Can Bias Pain Sensation

Post by Elisa Guma 

What's the science?

Pain is necessary for survival, both for quickly responding to aversive stimuli and for predicting potential harm from objects or situations. It is generally known that the experience of pain is related to nociception: the activation of special nerve endings in the body by potentially harmful stimuli such as mechanical (e.g. a sharp nail) or thermal (e.g. high heat). However, our experience of pain often deviates from nociception. Previously, it was shown that pain is influenced by our predictions of how painful the stimulus will be by using simple-Pavlovian cues. This week in the Journal of Neuroscience, Lim and colleagues show that pain can be strongly influenced by predictions from a conceptual schema. 

How did they do it?

The authors recruited 42 healthy adults and administered a series of tests in order to investigate how pain ratings are affected by a mismatch in pain prediction (top-down cognition; from the brain) and sensation due to nociception (bottom-up; from the body/nerves). First, a baseline pain rating was recorded for two heat stimuli used as the pain stimuli: 45°C (low) or 47°C (high). Next, all participants underwent functional magnetic resonance imaging while the pain tests were administered. This allowed the authors to make associations between neural responses to a) pain prediction and b) prediction errors. In the matched condition, participants learned a schema: when the value shown in the visual cue increased the pain produced by the heat stimulus also increased. Thus, visual cues stated “The incoming heat stimulus is at x% intensity”. The x value was a number between 0-100, and was increased linearly, with a 10-point increase corresponding to a 0.4 degree increase in stimulus temperature. 

In a second task set (mismatch level 1), the authors gradually introduced prediction errors where initially the cues continued to vary between 1-100, but the heat was held at either 45 ° C for cue values  0-40 or at 47 ° C for cue values from 61-100. Subsequently, the mismatch level was increased over a third and fourth task set (mismatch level 2) where the cues kept changing between 1-100, but the stimulus was always at 47°C . Participants were not given information on the mismatch and made their own decision on how much pain they felt after experiencing each cue-heat stimulus pairing. Finally, to better understand the factors that might mediate perceptual biases, a pain catastrophizing scale was administered, as well as a mindfulness questionnaire.

What did they find?

First, the authors established that participants were able to successfully detect a linear pattern between pain (heat) stimuli and cued (visual) stimulus intensities. Interestingly, the authors observed a bias in pain perception driven by the cue, such that the cue value had a greater influence on pain perception than the sensory stimulus. For the majority (5/8) of mismatched conditions for mismatch level 2, and (to a lesser degree) for mismatch level 1, participants partially updated their pain ratings with the change in heat stimulus, but the predictions had a stronger influence on perception than the prediction errors from the heat stimulus. 

The authors observed that areas typically involved in pain perception were responsive to increases in cued threat (cue stimulus increases), such as somatosensory regions, posterior insula and periaqueductal gray area (corrected, FLAME1). When prediction errors were high, more cognitive cortical areas became active. Finally, the authors investigated individual differences in pain perception and found that people who had higher catastrophizing behaviours and lower mindfulness or sensory awareness (as measured by a self-report scale) tended to be more affected by the cues or threat predictions. These behaviors involved the ventral and dorsal striatal circuitry, which are implicated in value-based vs. model-free or habitual decisions respectively.   

What’s the impact?

This study demonstrates that predictions that arise from learning concepts have a strong impact on pain perception even if there are prediction errors arising from sensory inputs. In other words, our prediction of pain based on a reported upcoming stimulus intensity impacts our pain even if the level of stimulus intensity eventually administered is not the same as the reported intensity. Further, changes in the levels of cued-threats altered activity in cognitive and sensory networks in an opposite manner, which underscores the role of these top-down and bottom-up networks in biasing pain perception. Finally, the authors were able to attribute behavioural patterns with perception, showing that individuals with higher mindful awareness and less fear of pain are better able to update their pain perception.

Lim et al. Threat prediction from schemas as a source of bias in pain perception. Journal of Neuroscience (2020). Access the original scientific publication here.