Frontal cortical thinning and subcortical volume reductions in early adulthood obesity (original) (raw)
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Brain abnormalities in human obesity: A voxel-based morphometric study
NeuroImage, 2006
Obesity is accompanied by damage to several tissues. Overweight is a risk factor for Alzheimer's disease and other neurodegenerative disorders. Whether structural abnormalities associated with excess body fat may also occur in the brain is unknown. We sought to determine to what extent excess body fat is associated with regional alterations in brain structure using voxel-based morphometry (VBM), a whole-brain unbiased technique based upon high-definition 3D magnetic resonance imaging (MRI) scans normalized into a common standard space and allowing for an objective assessment of neuroanatomical differences throughout the brain. We studied 24 obese (11 male, 13 female; age: 32 T 8 years; body mass index [BMI]: 39.4 T 4.7 kg/m 2) and 36 lean (25 male, 11 female; mean age: 33 T 9 years; BMI: 22.7 T 2.2 kg/m 2) non-diabetic Caucasians. In comparison with the group of lean subjects, the group of obese individuals had significantly lower gray matter density in the post-central gyrus, frontal operculum, putamen, and middle frontal gyrus (P < 0.01 after adjustment for sex, age, handedness, global tissue density, and multiple comparisons). BMI was negatively associated with GM density of the left post-central gyrus in obese but not lean subjects. This study identified structural brain differences in human obesity in several brain areas previously involved in the regulation of taste, reward, and behavioral control. These alterations may either precede obesity, representing a neural marker of increased propensity to gaining weight, or occur as a consequence of obesity, indicating that also the brain is affected by increased adiposity.
Reduced cortical thickness associated with visceral fat and BMI
NeuroImage. Clinical, 2014
Structural brain imaging studies have shown that obesity is associated with widespread reductions in gray matter (GM) volume. Although the body mass index (BMI) is an easily accessible anthropometric measure, substantial health problems are more related to specific body fat compartments, like visceral adipose tissue (VAT). We investigated cortical thickness measures in a group of 72 healthy subjects (BMI range 20-35 kg/m(2), age range 19-50 years). Multiple regression analyses were performed using VAT and BMI as predictors and age, gender, total surface area and education as confounds. BMI and VAT were independently associated with reductions in cortical thickness in clusters comprising the left lateral occipital area, the left inferior temporal cortex, and the left precentral and inferior parietal area, while the right insula, the left fusiform gyrus and the right inferior temporal area showed a negative correlation with VAT only. In addition, we could show significant reductions i...
Neuroimage, 2009
Obesity is associated with increased risk for cardiovascular health problems including diabetes, hypertension, and stroke. These cardiovascular afflictions increase risk for cognitive decline and dementia, but it is unknown whether these factors, specifically obesity and type II diabetes, are associated with specific patterns of brain atrophy. We used tensor-based morphometry (TBM) to examine gray matter (GM) and white matter (WM) volume differences in 94 elderly subjects who remained cognitively normal for at least 5 years after their scan. Bivariate analyses with corrections for multiple comparisons strongly linked body mass index (BMI), fasting plasma insulin (FPI) levels, and Type II Diabetes Mellitus (DM2) with atrophy in frontal, temporal, and subcortical brain regions. A multiple regression model, also correcting for multiple comparisons, revealed that BMI was still negatively correlated with brain atrophy (FDR < 5%), while DM2 and FPI were no longer associated with any volume differences. In an Analysis of Covariance (ANCOVA) model controlling for age, gender, and race, obese subjects with a high BMI (BMI > 30) showed atrophy in the frontal lobes, anterior cingulate gyrus, hippocampus, and thalamus compared to individuals with a normal . Overweight subjects (BMI: 25-30) had atrophy in the basal ganglia and corona radiata of the WM. Overall brain volume did not differ between overweight and obese persons. Higher body mass index was associated with lower brain volumes in overweight and obese elderly subjects. Obesity is therefore associated with detectable brain volume deficits in cognitively normal elderly subjects.
The brain’s role in human obesity
e-Neuroforum, 2013
The most common cause for obesity is a positive energy balance, i.e. more energy is being consumed than is expended. The rise in obesity rates cannot be explained on the basis of our obesogenic environment alone, because large interindividual differences in weight status exist between people. Therefore, the cause is most probably to be found in an interaction between individual behaviour and our changed environment. This warrants the investigation of the brain's role in the development and maintenance of obesity that indeed has become a growing field in the neurosciences. This article will give an overview about the findings in neuroimaging associated with human obesity. Further, this article will elucidate the relationship between common genetic variation, eating behaviour and brain structure in the context of obesity. Finally, important open questions in the field will be summarised.
Voxel-based morphometry reveals brain gray matter volume changes in successful dieters
Obesity (Silver Spring, Md.), 2016
To compare regional brain volume predictors of percent weight loss (WL) in dieters with obesity (DwO) and in the same participants categorized as "successful" (≥7% WL) or "unsuccessful" dieters (<7% WL). DwO (n = 72) and participants with healthy weight (n = 22) completed a structural MRI at baseline and 3 months. All DwO participants were enrolled in a 12-week program consisting of a reduced calorie diet, increased physical activity, and behavioral modification. SPM8-based voxel-based morphometry processing streams were used for measurements of regional gray (GMV) and white matter volume and longitudinal changes in volume. Correlations between WL and baseline brain volume and change in brain volume, as well as differences between groups, were then tested. %WL was positively correlated with baseline GMV in right parahippocampal and orbitofrontal gyri in DwO. Successful dieters showed greater GMV loss in the left precentral gyrus and the insula compared with un...
Annals of the New York Academy of Sciences, 2006
The hypothalamus has a major role in the control of food intake. However, neurotracing studies have shown that the hypothalamus receives input from several other regions of the brain that are likely to modulate its activity. Of particular interest to the understanding of human eating behavior is the possible involvement of the cortex. Using positron emission tomography (PET), we generated functional brain maps of the neuroanatomical correlates of hunger (after a 36-h fast) and satiation (after oral administration of a liquid formula meal) in lean and obese subjects. Results in lean individuals indicate that the neuroanatomical correlates of hunger form a complex network of brain regions including the hypothalamus, thalamus, and several limbic/ paralimbic areas such as the insula, hippocampal/parahippocampal formation, and the orbitofrontal cortex. Satiation was associated with preferentially increased neuronal activity in the prefrontal cortex. Our studies also indicate that the brain responses to hunger/satiation in the hypothalamus, limbic/ paralimbic areas (commonly associated with the regulation of emotion), and prefrontal cortex (thought to be involved in the inhibition of inappropriate response tendencies) might be different in obese and lean individuals. In conclusion, neuroimaging of the human brain is proving to be an important tool for understanding the complexity of brain involvement in the regulation of eating behavior. PET studies might help to unravel the neuropathophysiology underlying human obesity.
American Journal of …, 2006
Background: In an exploratory positron emission tomography study of postprandial regional cerebral blood flow, which is a marker of neuronal activity, obese men differed from lean men in several brain regions, including the prefrontal cortex. The subjects received a meal proportional to their body size; therefore, the meal volume was different for each person. Objective: We investigated whether differences in the brain responses of obese and lean men to a meal represent satiety or feelings of gastric distension. Design: We studied 9 lean (x Ȁ SD body fat: 15 Ȁ 5%; age: 33 Ȁ 10 y) and 9 obese (body fat: 31 Ȁ 4%; age: 32 Ȁ 10 y) men given a fixed amount (400 mL) of a liquid meal. We compared their results with those in 11 lean (body fat: 16 Ȁ 5%; age: 35 Ȁ 8 y) and 11 obese (body fat: 33 Ȁ 5%; age: 28 Ȁ 5 y) previously studied men given a meal proportional to their body size. We performed analyses by using a two-level, random-effects approach in the STATISTICAL PARAMETRIC MAPPING software package and a significance level of P ͨ 0.001, uncorrected for multiple comparisons. Results: Compared with lean men, obese men had consistently less postprandial activation in the left dorsolateral prefrontal cortex, irrespective of meal size. Conclusion: Because the dorsolateral prefrontal cortex has been implicated in the inhibition of inappropriate behavior, satiety, and meal termination, differential responses of neuronal activity to food intake in this area may contribute to a propensity for obesity or to the difficulty in losing weight experienced by obese men.
Neurobehavioural Correlates of Obesity are Largely Heritable
Recent molecular genetic studies have shown that the majority of genes associated with obesity are expressed in the central nervous system. Obesity has also been associated with neurobehavioural factors such as brain morphology, cognitive performance, and personality. Here, we tested whether these neurobehavioural factors were associated with the heritable variance in obesity measured by body mass index (BMI) in the Human Connectome Project (N=895 siblings). Phenotypically, cortical thickness findings supported the 'right brain hypothesis' for obesity. Namely, increased BMI associated with decreased cortical thickness in right frontal lobe and increased thickness in the left frontal lobe, notably in lateral prefrontal cortex. In addition, lower thickness and volume in entorhinal-parahippocampal structures, and increased thickness in parietal-occipital structures in participants with higher BMI supported the role of visuospatial function in obesity. Brain morphometry results ...
Neuroimaging and obesity: current knowledge and future directions
Obesity Reviews, 2012
Neuroimaging is becoming increasingly common in obesity research as investigators try to understand the neurological underpinnings of appetite and body weight in humans. Positron emission tomography (PET), functional magnetic resonance imaging (fMRI) and magnetic resonance imaging (MRI) studies examining responses to food intake and food cues, dopamine function and brain volume in lean vs. obese individuals are now beginning to coalesce in identifying irregularities in a range of regions implicated in reward (e.g. striatum, orbitofrontal cortex, insula), emotion and memory (e.g. amygdala, hippocampus), homeostatic regulation of intake (e.g. hypothalamus), sensory and motor processing (e.g. insula, precentral gyrus), and cognitive control and attention (e.g. prefrontal cortex, cingulate). Studies of weight change in children and adolescents, and those at high genetic risk for obesity, promise to illuminate causal processes. Studies examining specific eating behaviours (e.g. external eating, emotional eating, dietary restraint) are teaching us about the distinct neural networks that drive components of appetite, and contribute to the phenotype of body weight. Finally, innovative investigations of appetite-related hormones, including studies of abnormalities (e.g. leptin deficiency) and interventions (e.g. leptin replacement, bariatric surgery), are shedding light on the interactive relationship between gut and brain. The dynamic distributed vulnerability model of eating behaviour in obesity that we propose has scientific and practical implications.
Medical Hypotheses, 2011
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