The effect of consumption temperature on the homeostatic and hedonic responses to glucose ingestion in the hypothalamus and the reward system

Abstract

Background: Excessive consumption of sugar-sweetened beverages (SSBs) has been associated with obesity and related diseases. SSBs are often consumed cold, and both the energy content and temperature might influence the consumption behavior for SSBs. Objective: The main aim of this study was to elucidate whether consumption temperature and energy (i.e., glucose) content modulate homeostatic (hypothalamus) and reward [ventral tegmental area (VTA)] responses. Design: Sixteen healthy men participated in our study [aged 18-25 y; body mass index (kg/m 2 ): 20-23]. High-resolution functional magnetic resonance imaging data were collected after ingestion of 4 different study stimuli: plain tap water at room temperature (22°C), plain tap water at 0°C, a glucose-containing beverage (75 g glucose dissolved in 300 mL water) at 22°C, and a similar glucose drink at 0°C. Blood oxygen level-dependent (BOLD) changes from baseline (7 min preingestion) were analyzed over time in the hypothalamus and VTA for individual stimulus effects and for effects between stimuli. Results: In the hypothalamus, water at 22°C led to a significantly increased BOLD response; all other stimuli resulted in a direct, significant decrease in BOLD response compared with baseline. In the VTA, a significantly decreased BOLD response compared with baseline was found after the ingestion of stimuli containing glucose at 0°C and 22°C. These responses were not significantly modulated by consumption temperature. The consumption of plain water did not have a significant VTA BOLD effect. Conclusions: Our data show that glucose at 22°C, glucose at 0°C, and water at 0°C lowered hypothalamic activity, which is associated with increased satiation. On the contrary, the consumption of water at room temperature increased activity. All stimuli led to a similar VTA response, which suggests that all drinks elicited a similar hedonic response. Our results indicate that, in addition to glucose, the low temperature at which SSBs are often consumed also leads to a response from the hypothalamus and might strengthen the response of the VTA. This trial was registered at www.clinicaltrials.gov as NCT03181217.Am J Clin Nutr 2018;107:20-25.

Whole‐brain functional connectivity correlates of obesity phenotypes

“…Further, increased macroscale connectivity, particularly in the prefrontal, parietal, and cingulate cortices is known to be related to eating behaviors in people with obesity (Park et al, 2016; Park, Lee, et al, 2018; Park, Moon, et al, 2018). Indeed, imbalance in inhibitory control and food‐related reward system in the prefrontal cortex and paralimbic areas is associated with increased feelings of hunger (Tataranni et al, 1999; Tataranni & DelParigi, 2003) and may lead to overeating and weight gain (Brooks et al, 2013; Ding et al, 2020; Olivo et al, 2017; Steward, Juaneda‐Seguí, et al, 2019; Steward, Picó‐Pérez, et al, 2019; Vainik, Dagher, Dubé, & Fellows, 2013; Van Meer et al, 2019; Van Opstal et al, 2018; Van Opstal et al, 2019; Verdejo‐Román et al, 2017; Volkow, Wang, Telang, et al, 2008; Ziauddeen et al, 2015). In contrast, we found negative associations with obesity phenotypes in brain regions involved in multisensory processing, particularly precentral gyrus, inferior temporal gyrus, fusiform gyrus, superior temporal sulcus, and thalamus.…”

“…Obesity is thought to be caused by uncontrolled eating, which is highly associated with the imbalance in reward and inhibitory control processing of the brain (Martin et al, 2010; Moore, Sabino, Koob, & Cottone, 2017; Moreno‐Lopez, Contreras‐Rodriguez, Soriano‐Mas, Stamatakis, & Verdejo‐Garcia, 2016; Murray, Tulloch, Gold, & Avena, 2014; Val‐Laillet et al, 2015; Van Opstal, Wijngaarden, Grond, & Pijl, 2019; Verdejo‐Román, Vilar‐López, Navas, Soriano‐Mas, & Verdejo‐García, 2017; Ziauddeen, Alonso‐Alonso, Hill, Kelley, & Khan, 2015). Neurobiological studies have found that dysregulation of reward and inhibitory circuits gives rise to an increased threshold for satiation, ultimately leading to overeating (Martin et al, 2010; Murray et al, 2014; Steward, Miranda‐Olivos, Soriano‐Mas, & Fernández‐Aranda, 2019; Val‐Laillet et al, 2015; Van Opstal et al, 2018; Verdejo‐Román et al, 2017; Ziauddeen et al, 2015). Recent neuroimaging studies have increasingly shown associations between obesity and alterations in cortical and subcortical morphology (Herrmann, Tesar, Beier, Berg, & Warrings, 2019; Marqués‐Iturria et al, 2013; Shott et al, 2015), brain activity (Brooks, Cedernaes, & Schiöth, 2013; Goldstone et al, 2009; Gupta et al, 2018; Opel et al, 2015; Park, Hong, & Park, 2017; Steward, Juaneda‐Seguí, et al, 2019; Stoeckel et al, 2008; Van Meer et al, 2019), functional connectivity (García‐García et al, 2013; García‐García et al, 2015; Lips et al, 2014; Park, Seo, & Park, 2016; Park, Seo, Yi, & Park, 2015), and diffusivity (Gupta et al, 2017; Olivo et al, 2017; Steward, Picó‐Pérez, et al, 2019).…”

Brain activity and connectivity changes in response to nutritive natural sugars, non-nutritive natural sugar replacements and artificial sweeteners

“…The brain consumes about 20% of glucose derived energy in the human body [10]. The brain responds readily to ingestion of glucose because of its quick absorption [10][11][12], and glucose sensing neurons in the hypothalamus show a homeostatic satiety response almost immediately after ingestion [13][14][15][16][17]. Glucose ingestion has effects on both neuronal activity and functional connectivity throughout the brain in areas involved in reward and feeding behavior [16].…”

“…However, because of the complexity and involvement of various brain areas in the regulation of energy balance [33], fMRI investigations of whole brain responses might be more informative for this regulation. Measurements of local BOLD changes, a measure of neuronal activity [34], can be used to analyse the immediate effects of nutrient ingestion on very specific brain areas [13][14][15]35,36], but can also be used to determine whole brain effects on a voxel based level [37]. Analysis of functional connectivity has been used to provide further insights on the network level [16,38].…”

Body mass variations relate to fractionated functional brain hierarchies

“…High BMI is an indicator of obesity, a condition with increasing prevalence worldwide (World Health Organization, 2020) and a critical factor in the development of type 2 diabetes, cardiovascular disease, stroke, cancer, and metabolic syndrome (Jensen et al, 2014;Malik et al, 2013;Raji et al, 2010;Val-Laillet et al, 2015). In addition, multiple neurobiological processes related to obesity have been recognized, including mechanisms regulating eating behaviors, together with genetic and transcriptomic underpinnings (Locke et al, 2015;Martin et al, 2010;Murray et al, 2014;Van Opstal et al, 2018;Steward et al, 2019a;Vainik et al, 2013Vainik et al, , 2018Val-Laillet et al, 2015;Verdejo-Román et al, 2017;Ziauddeen et al, 2015).…”