Nucleus accumbens cytoarchitecture predicts weight gain in children

Rapuano, Kristina M.; Laurent, Jennifer; Hagler, Donald J.; Hatton, Sean N.; Thompson, Wesley K.; Jernigan, Terry L.; Dale, Anders M.; Casey, B. J.; Watts, Richard

doi:10.1073/pnas.2007918117

Cited by 56 publications

(86 citation statements)

References 106 publications

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“…Accumbens, a structure associated with motivation and reward, and part of the dopamine motivation system 36 , showed the strongest positive associations. This is generally in line with prior studies documenting larger accumbens volume in children with increased genetic risk for obesity 37 , and in predominantly adult obesity across patients with major depressive disorders and healthy controls 11 , and increased accumbens cell density in obese children 38 , and supports the assumption of a critical role of brain mechanisms for reward and reinforcement learning for lifestyle and dietary choices and obesity.…”

Section: Discussionsupporting

confidence: 90%

Population-based body–brain mapping links brain morphology with anthropometrics and body composition

et al. 2021

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Understanding complex body–brain processes and the interplay between adipose tissue and brain health is important for understanding comorbidity between psychiatric and cardiometabolic disorders. We investigated associations between brain structure and anthropometric and body composition measures using brain magnetic resonance imaging (MRI; n = 24,728) and body MRI (n = 4973) of generally healthy participants in the UK Biobank. We derived regional and global measures of brain morphometry using FreeSurfer and tested their association with (i) anthropometric measures, and (ii) adipose and muscle tissue measured from body MRI. We identified several significant associations with small effect sizes. Anthropometric measures showed negative, nonlinear, associations with cerebellar/cortical gray matter, and brain stem structures, and positive associations with ventricular volumes. Subcortical structures exhibited mixed effect directionality, with strongest positive association for accumbens. Adipose tissue measures, including liver fat and muscle fat infiltration, were negatively associated with cortical/cerebellum structures, while total thigh muscle volume was positively associated with brain stem and accumbens. Regional investigations of cortical area, thickness, and volume indicated widespread and largely negative associations with anthropometric and adipose tissue measures, with an opposite pattern for thigh muscle volume. Self-reported diabetes, hypertension, or hypercholesterolemia were associated with brain structure. The findings provide new insight into physiological body–brain associations suggestive of shared mechanisms between cardiometabolic risk factors and brain health. Whereas the causality needs to be determined, the observed patterns of body–brain relationships provide a foundation for understanding the underlying mechanisms linking psychiatric disorders with obesity and cardiovascular disease, with potential for the development of new prevention strategies.

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Section: Discussionsupporting

confidence: 90%

Population-based body–brain mapping links brain morphology with anthropometrics and body composition

et al. 2021

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“…However, multicompartment diffusion MRI models such as DBSI are capable of providing more accurate data about specific tissue microstructural changes than traditional DTI (21,34). Using restriction spectrum imaging (RSI), Rapuano et al showed that NAcc cellular density (i.e., restricted isotropic component fraction) is higher in children with obesity, and NAcc microstructure is a significant predictor of weight gain after 1 year (16). The authors suggested that this finding could be related to increased glial cells (e.g., astrocytes, microglia), which is suggestive of local neuroinflammation.…”

Section: Discussionmentioning

confidence: 99%

Nucleus accumbens microstructure mediates the relationship between obesity and eating behavior in adults

Samara

Rutlin

et al. 2021

Obesity

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Objective Basal ganglia regions are part of the brain’s reward‐processing networks and are implicated in the neurobiology of obesity and eating disorders. This study examines basal ganglia microstructural properties in adults with and without obesity. Methods Diffusion basis spectrum imaging (DBSI) images were analyzed to obtain putative imaging markers of neuroinflammation. Relationships between basal ganglia DBSI metrics and reward sensitivity and eating behaviors were also explored. Results A total of 46 participants (25 people with obesity; aged 20‐40 years; 37 women) were included. Relative to the people in the normal‐weight group, people with obesity had smaller caudate and larger nucleus accumbens (NAcc) volumes (p < 0.05) and lower DBSI fiber fraction (reflecting apparent axonal/dendrite density) in NAcc and putamen, higher DBSI nonrestricted fraction (reflecting tissue edema) in NAcc and caudate, and higher DBSI restricted fraction (reflecting tissue cellularity) in putamen (p ≤ 0.01, all). Increased emotional and reward eating behaviors were related to lower NAcc axonal/dendrite density and greater tissue edema (p ≤ 0.002). The relationships between emotional eating and adiposity measures were mediated by NAcc microstructure. Conclusions These findings provide evidence that microstructural alterations in basal ganglia relate to obesity and insights linking NAcc microstructure and eating behavior in adults.

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“…Higher adipose tissue levels as indexed by waist circumference (WC), waist-to-hip ratio (WHR), body mass index (BMI), and increased subcutaneous (ASAT) and visceral (VAT) adipose tissue measures have all been associated with global brain volume decreases (Debette & Markus, 2010;Gunstad et al, 2005;Mulugeta et al, 2021;Ward et al, 2005). Moreover, regional findings have consistently shown negative associations between obesity and brain grey matter volume (Gurholt et al, 2020;Pannacciulli et al, 2006;Taki et al, 2008;Walther et al, 2010) and white matter microstructure, including reduced white matter tract coherence (Friedman et al, 2014;Willette & Kapogiannis, 2015), white matter integrity (Marks et al, 2011;Stanek et al, 2011;Xu et al, 2013), microstructural changes in childhood (Rapuano et al, 2020), and increased axonal and myelin damage (Mueller et al, 2011;Xu et al, 2013) based on diffusion MRI. White matter volumetric studies have revealed less consistent findings, reporting both positive (Walther et al, 2010), negative (Raji et al, 2010) and no (Gunstad et al, 2005) significant associations between brain white matter volume and adiposity.…”

Section: Introductionmentioning

confidence: 99%

Adipose tissue distribution from body MRI is associated with cross-sectional and longitudinal brain age in adults

Beck

Lange

Alnæs

et al. 2021

Preprint

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There is an intimate body-brain connection in ageing, and obesity is a key risk factor for poor cardiometabolic health and neurodegenerative conditions. Although research has demonstrated deleterious effects of obesity on brain structure and function, the majority of studies have used conventional measures such as waist-to-hip ratio, waist circumference, and body mass index. While sensitive to gross features of body composition, such global anthropomorphic features fail to describe regional differences in body fat distribution and composition, and to determine visceral adiposity, which is related to a range of metabolic conditions. In this mixed cross-sectional and longitudinal design (interval mean = 19.7, standard deviation = 0.5 months), including 790 healthy individuals (mean (range) age = 46.7 (18-94) years, 53% women), we investigated cross-sectional body magnetic resonance imaging (MRI, n = 286) measures of adipose tissue distribution in relation to longitudinal brain structure using MRI-based morphometry and diffusion tensor imaging (DTI). We estimated tissue-specific brain age at two time points and performed Bayesian multilevel modelling to investigate the associations between adipose measures at follow-up and brain age gap (BAG) at baseline and follow-up. We also tested for interactions between BAG and both time and age on each adipose measure. The results showed credible associations between T1-based BAG and liver fat, muscle fat infiltration (MFI), and weight-to-muscle ratio (WMR), indicating older-appearing brains in people with higher measures of adipose tissue. Longitudinal evidence supported interaction effects between time and MFI and WMR on T1-based BAG, indicating accelerated ageing over the course of the study period in people with higher measures of adipose tissue. The results show that specific measures of fat distribution are associated with brain ageing and that different compartments of adipose tissue may be differentially linked with increased brain ageing, with potential to identify key processes involved in age-related transdiagnostic disease processes.

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Nucleus accumbens cytoarchitecture predicts weight gain in children

Cited by 56 publications

References 106 publications

Population-based body–brain mapping links brain morphology with anthropometrics and body composition

Population-based body–brain mapping links brain morphology with anthropometrics and body composition

Nucleus accumbens microstructure mediates the relationship between obesity and eating behavior in adults

Adipose tissue distribution from body MRI is associated with cross-sectional and longitudinal brain age in adults

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