Volumetric gray matter measures of amygdala and accumbens in childhood overweight/obesity

Abstract

ObjectivesNeuroimaging data suggest that pediatric overweight and obesity are associated with morphological alterations in gray matter (GM) brain structures, but previous studies using mainly voxel-based morphometry (VBM) showed inconsistent results. Here, we aimed to examine the relationship between youth obesity and the volume of predefined reward system structures using magnetic resonance (MR) volumetry. We also aimed to complement volumetry with VBM-style analysis.MethodsFifty-one Caucasian young subjects (32 females; mean age: 13.8±1.9, range: 10.2–16.5 years) were included. Subjects were selected from a subsample of the I.Family study examined in the Hungarian center. A T1-weighted 1 mm3 isotropic resolution image was acquired. Age- and sex-standardized body mass index (zBMI) was assessed at the day of MRI and ~1.89 years (mean±SD: 689±188 days) before the examination. Obesity related GM alterations were investigated using MR volumetry in five predefined brain structures presumed to play crucial roles in body weight regulation (hippocampus, amygdala, accumbens, caudate, putamen), as well as whole-brain and regional VBM.ResultsThe volumes of accumbens and amygdala showed significant positive correlations with zBMI, while their GM densities were inversely related to zBMI. Voxel-based GM mass also showed significant negative correlation with zBMI when investigated in the predefined amygdala region, but this relationship was mediated by GM density.ConclusionsOverweight/obesity related morphometric brain differences already seem to be present in children/adolescents. Our work highlights the disparity between volume and VBM-derived measures and that GM mass (combination of volume and density) is not informative in the context of obesity related volumetric changes. To better characterize the association between childhood obesity and GM morphometry, a combination of volumetric segmentation and VBM methods, as well as future longitudinal studies are necessary. Our results suggest that childhood obesity is associated with enlarged structural volumes, but decreased GM density in the reward system.

Predicting Body Mass Index From Structural MRI Brain Images Using a Deep Convolutional Neural Network

“…Previous studies using voxel-based (Taki et al, 2008) and tensor-based morphometry (Raji et al, 2010) found a relationship between BMI and the volume of gray and white matter in the medial temporal lobe. With regard to the amygdala, a positive relationship between BMI and amygdalar volume was already found in children and adolescents (Perlaki et al, 2018), young adults (Orsi et al, 2011), and elderly subjects (Widya et al, 2011); although a negative association has also been described (Kharabian Masouleh et al, 2016). Taken together, these results show that the DL approach paired with gradient-based visualization and more conventional neuroimaging methods provide converging evidence regarding the link between body weight and amygdalar structure.…”

Differences in Brain Volume between Metabolically Healthy and Unhealthy Overweight and Obese Children: The Role of Fitness

“…In the last few years, an increased body of evidence has emerged on obesity-related comorbidities and metabolic alterations and their relationship with structural brain abnormalities in children and adolescents [9,[34][35][36]. For instance, Perlaki et al [36] showed that a higher degree of obesity was associated with greater volumes in the amygdala and accumbens, regions involved in the food rewards. Interestingly, in our study, we observed that, in those who presented a MHO phenotype, global gray matter volume was marginally greater compared to those with a metabolically unhealthy profile.…”

Association between regional brain volumes and BMI z-score change over one year in children

“…Obesity is related to a host of co-morbidities that affect long term health outcomes as well as overall quality of life [2]. Increased weight has also been shown to be associated with altered brain morphology (i.e., gray matter density and/or regional volume) [3–6]. Associations between the morphometry of developing brain regions and adiposity during childhood and adolescence are of interest because significant growth and remodeling of gray matter occurs during this period [7], and because the emergence of overweight in youth often tracks into adulthood [8].…”

“…Associations between the morphometry of developing brain regions and adiposity during childhood and adolescence are of interest because significant growth and remodeling of gray matter occurs during this period [7], and because the emergence of overweight in youth often tracks into adulthood [8]. Furthermore, a recent study has highlighted that brain region volume is particularly related to body weight and body mass index z-scores (BMIz) in children [3]. Therefore, volumetric analysis may be particularly useful for understanding which regions of the brain are developmental important to weight gain and weight management over childhood and adolescence.…”

“…Increased response to food cues in this region has been shown to correlate with increased weight gain in young adults (18-19-year old participants) [12]. Several studies have examined nucleus accumbens volume in relation to body mass index (BMI) and have found that larger nucleus accumbens volumes tend to correlate with higher BMI in adults [13,14] and BMIz in children [3]. A recent study by Rapuano et al has also shown that nucleus accumbens volume is associated with genetic risk for the development of obesity in young children [11].…”