The obese brain as a heritable phenotype: a combined morphometry and twin study

Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction

The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.

Neuroanatomical profile of BMI implicates impulsive delay discounting and general cognitive ability

OBJECTIVE

Obesity is a disorder of excessive adiposity, typically assessed via the anthropometric density measure of BMI. Numerous studies have implicated BMI with differences in brain structure, but with highly inconsistent findings.

METHODS

Machine learning elastic net regression models with cross-validation were conducted to characterize a neuroanatomical morphometry profile associated with BMI in 1100 participants (22% BMI > 30, n = 242) from the Human Connectome Project Young Adult project.

RESULTS

Using five-fold cross-validation, the multiregion neuroanatomical profile substantively predicted BMI (R2  = 10.05%), and this was robust in a held-out test set (R2  = 8.87%). In terms of specific regions, the neuroanatomical profile was enriched for nodes in the default mode, executive control, and salience networks. The relationship between the morphometry profile and BMI itself was partially mediated by impulsive delay discounting and general cognitive ability.

CONCLUSIONS

Taken together, these findings reveal a robust machine learning-derived neuroanatomical profile of BMI, one that comprises nodes in motivational brain networks and suggests the functional links to obesity are via self-regulatory capacity and cognitive function.

Differential impact of body mass index and leptin on baseline and longitudinal positron emission tomography measurements of the cerebral metabolic rate for glucose in amnestic mild cognitive impairment

Introduction

Several studies have suggested that greater adiposity in older adults is associated with a lower risk of Alzheimer's disease (AD) related cognitive decline, some investigators have postulated that this association may be due to the protective effects of the adipose tissue-derived hormone leptin. In this study we sought to demonstrate that higher body mass indices (BMIs) are associated with greater baseline FDG PET measurements of the regional cerebral metabolic rate for glucose (rCMRgl), a marker of local neuronal activity, slower rCMRgl declines in research participants with amnestic mild cognitive impairment (aMCI). We then sought to clarify the extent to which those relationships are attributable to cerebrospinal fluid (CSF) or plasma leptin concentrations.

Materials and methods

We used baseline PET images from 716 73 ± 8 years-old aMCI participants from the AD Neuroimaging Initiative (ADNI) of whom 453 had follow up images (≥6 months; mean follow up time 3.3 years). For the leptin analyses, we used baseline CSF samples from 81 of the participants and plasma samples from 212 of the participants.

Results

As predicted, higher baseline BMI was associated with greater baseline CMRgl measurements and slower declines within brain regions preferentially affected by AD. In contrast and independently of BMI, CSF, and plasma leptin concentrations were mainly related to less baseline CMRgl within mesocorticolimbic brain regions implicated in energy homeostasis.

Discussion

While higher BMIs are associated with greater baseline CMRgl and slower declines in persons with aMCI, these associations appear not to be primarily attributable to leptin concentrations.

Neural structural abnormalities behind altered brain activation in obesity: Evidence from meta-analyses of brain activation and morphometric data

Obesity represents a risk factor for disability with a major bearing on life expectancy. Neuroimaging techniques are contributing to clarify its neurobiological underpinnings. Here, we explored whether structural brain abnormalities might accompany altered brain activations in obesity. We combined and compared data from brain activation studies for food stimuli and the data reported in structural voxel-based morphometry studies. We found that obese individuals have reduced grey matter density and functional activations in the thalamus and midbrain. A functional connectivity analysis based on these two clusters and its quantitative decoding showed that these regions are part of the reward system functional brain network. Moreover, we found specific grey matter hypo-densities in prefrontal cortex for the obese subjects, regions involved in controlled behaviour. These results support theories of obesity that point to reduced bottom-up reward processes (i.e., the Reward Deficit Theory), but also top-down theories postulating a deficit in cognitive control (i.e., the Inhibitory Control Deficit Theory). The same results also warrant a more systematic exploration of obesity whereby the reward of food and the intentional control over consummatory behaviour is manipulated.

Obesity is associated with reduced orbitofrontal cortex volume: A coordinate-based meta-analysis

Neural models of obesity vary in their focus upon prefrontal and striatal differences. Animal and human studies suggest that differential functioning of the orbitofrontal cortex is associated with obesity. However, meta-analyses of functional neuroimaging studies have not found a clear relationship between the orbitofrontal cortex and obesity. Meta-analyses of structural imaging studies of obesity have shown mixed findings with regards to an association with reduced orbitofrontal cortex gray matter volume. To clarify these findings, we conducted a meta-analysis of 25 voxel-based morphometry studies, and found that greater body mass index is associated with decreased gray matter volume in the right orbitofrontal cortex (Brodmanns' areas 10 and 11), where family-wise corrected p < .05, N = 7,612. Use of the right orbitofrontal cortex as a seed in a Neurosynth Network Coactivation analysis showed that this region is associated with activity in the left frontal medial cortex, left temporal lobe, right precuneus cortex, posterior division of the left middle temporal gyrus, and right frontal pole. When Neurosynth Network Coactivation results were submitted as regions of interest in the Human Connectome Project data, we found that greater body mass index was associated with greater activity in left frontal medial cortex response to the Gambling Task, where p < .05, although this did not survive Bonferroni-correction. Our findings highlight the importance of the orbitofrontal cortex structure and functioning in neural models of obesity. Exploratory analyses suggest more studies are needed that examine the functional significance of reduced orbitofrontal cortex gray matter volume in obesity, and the effect of age and weight changes on this relationship using longitudinal designs.

Differences in brain structure and function in children with the FTO obesity-risk allele

OBJECTIVE

Noncoding alleles of the fat mass and obesity-associated (FTO) gene have been associated with obesity risk, yet the underlying mechanisms remain unknown. Risk allele carriers show alterations in brain structure and function, but previous studies have not disassociated the effects of genotype from those of body mass index (BMI).

METHODS

Differences in brain structure and function were examined in children without obesity grouped by their number of copies (0,1,2) of the FTO obesity-risk single-nucleotide polymorphism (SNP) rs1421085. One hundred five 5- to 10-year-olds (5th-95th percentile body fat) were eligible to participate. Usable scans were obtained from 93 participants (15 CC [homozygous risk], 31 CT [heterozygous] and 47 TT [homozygous low risk]).

RESULTS

Homozygous C allele carriers (CCs) showed greater grey matter volume in the cerebellum and temporal fusiform gyrus. CCs also demonstrated increased bilateral cerebellar white matter fibre density and increased resting-state functional connectivity between the bilateral cerebellum and regions in the frontotemporal cortices.

CONCLUSIONS

This is the first study to examine brain structure and function related to FTO alleles in young children not yet manifesting obesity. This study lends support to the notion that the cerebellum may be involved in FTO-related risk for obesity, yet replication and further longitudinal study are required.

Viscoelasticity of striatal brain areas reflects variations in body mass index of lean to overweight male adults

Although a variety of MRI studies investigated the link between body mass index (BMI) and parameters of neural gray matter (GM), the technique applied in most of these studies, voxel-based morphometry (VBM), focusses on the regional GM volume, a macroscopic tissue property. Thus, the studies were not able to exploit the BMI-related information contained in the GM microstructure although PET studies suggest that these factors are important. Here, we used cerebral MR Elastography (MRE) to characterize features of tissue microstructure by evaluating the propagation of shear waves applied to the skull and to assess local tissue viscoelasticity to test the link between this parameter and BMI in 22 lean to overweight males. Unlike the majority of existing MRE studies investigating neural viscoelasticity signals averaged across large brain regions, we used the viscoelasticity of individual voxels for our experiment. Our technique revealed a negative link between BMI and viscoelasticity of two areas of the striatal reward system, i.e., right putamen (t = -8.2; p_{FWE-corrected} = 0.005) and left globus pallidus (t = -7.1; p_FWE = 0.037) which was independent of GM volume at these coordinates. Finally, comparison of BMI models based on individual voxels vs. on signals averaged across brain atlas regions demonstrates that voxel-based models explain a significantly higher proportion of variance. Consequently, our findings show that cerebral MRE is suitable to identify medically relevant microstructural tissue properties. Using a voxel-wise analysis approach, we were able to utilize the high spatial resolution of MRE for mapping BMI-related information in the brain.

Shared genetic influences on adolescent body mass index and brain structure: A voxel-based morphometry study in twins

BACKGROUND

Previous research has demonstrated significant relationships between obesity and brain structure. Both phenotypes are heritable, but it is not known whether they are influenced by common genetic factors. We investigated the genetic etiology of the relationship between individual variability in brain morphology and BMIz using structural MRI in adolescent twins.

METHOD

The sample (n = 258) consisted of 54 monozygotic and 75 dizygotic twin pairs (mean(SD) age = 13.61(0.505), BMIz = 0.608(1.013). Brain structure (volume and density of gray and white matter) was assessed using VBM. Significant voxelwise heritability of brain structure was established using the Accelerated Permutation inference for ACE models (APACE) program, with structural heritability varying from 15 to 97%, depending on region. Bivariate heritability analyses were carried out comparing additive genetic and unique environment models with and without shared genetics on BMIz and the voxels showing significant heritability in the APACE analyses.

RESULTS

BMIz was positively related to gray matter volume in the brainstem and thalamus and negatively related to gray matter volume in the bilateral uncus and medial orbitofrontal cortex, gray matter density in the cerebellum, prefrontal lobe, temporal lobe, and limbic system, and white matter density in the brainstem. Bivariate heritability analyses showed that BMIz and brain structure share ∼1/3 of their genes and that ∼95% of the phenotypic correlation between BMIz and brain structure is due to shared additive genetic influences. These regions included areas related to decision-making, motivation, liking vs. wanting, taste, interoception, reward processing/learning, caloric evaluation, and inhibition.

CONCLUSION

These results suggested genetic factors are responsible for the relationship between BMIz and heritable BMIz related brain structure in areas related to eating behavior.

Impulsivity and body fat accumulation are linked to cortical and subcortical brain volumes among adolescents and adults

Obesity is associated not only with metabolic and physical health conditions, but with individual variations in cognition and brain health. This study examined the association between body fat (an index of excess weight severity), impulsivity (a vulnerability factor for obesity), and brain structure among adolescents and adults across the body mass index (BMI) spectrum. We used 3D T1 weighted anatomic magnetic resonance imaging scans to map the association between body fat and volumes in regions associated with obesity and impulsivity. Participants were 127 individuals (BMI: 18–40 kg/m²; M = 25.69 ± 5.15), aged 14 to 45 years (M = 24.79 ± 9.60; female = 64). Body fat was measured with bioelectric impendence technology, while impulsivity was measured with the UPPS-P Impulsive Behaviour Scale. Results showed that higher body fat was associated with larger cerebellar white matter, medial orbitofrontal cortex (OFC), and nucleus accumbens volume, although the latter finding was specific to adolescents. The relationship between body fat and medial OFC volume was moderated by impulsivity. Elevated impulsivity was also associated with smaller amygdala and larger frontal pole volumes. Our findings link vulnerability and severity markers of obesity with neuroanatomical measures of frontal, limbic and cerebellar structures, and unravel specific links between body fat and striatal volume in adolescence.

The effect of body mass index on glucagon-like peptide receptor gene expression in the post mortem brain from individuals with mood and psychotic disorders

There is an increasing interest in the putative role of glucagon-like peptide 1 receptor (GLP-1R) agonists as novel therapeutic agents for mental disorders. Herein, we investigated the expressions of GLP-1R and GLP-2R genes, and its relationship with body mass index (BMI), in the post-mortem brain tissue of patients with mood (MD) and psychotic disorders. Brain samples were localized to the dorsolateral prefrontal cortex (dlPFC) (n = 459) and hippocampus (n = 378). After adjustment for age, sex, ethnicity, post-mortem interval (PMI) and BMI, we observed significant differences, between healthy controls and MD subjects, in GLP-1R and GLP-2R gene expression in the dlPFC (β = 1.504, p = 0.004; and β = 1.305, p = 0.011, respectively); whereas in the hippocampus, only GLP-1R expression was significantly associated with MD (β = -1.28, p = 0.029). No significant differences were found in relation to schizophrenia. In addition, we observed a moderating effect of MD diagnosis on the associations between BMI, GLP-1R and GLP-2R expression values in the dlPFC (β = -0.05, p = 0.003; and β = -0.04, p = 0.004, respectively). There was a similar moderating effect for GLP-1R in the hippocampus (β = 0.043, 95% CI 0.003; 0.08 p = 0.03), but in an opposite direction than observed in the dlPFC. This is the first evidence of abnormal gene expression of GLP-1R and GLP-2R in postmortem brain of individuals with MD, providing a rationale for further inquiry and proof of principle interventional studies.

Prefronto-cerebellar neuromodulation affects appetite in obesity

Human neuroimaging studies have consistently reported changes in cerebellar function and integrity in association with obesity. To date, however, the nature of this link has not been studied directly. Emerging evidence suggests a role for the cerebellum in higher cognitive functions through reciprocal connections with the prefrontal cortex. The purpose of this exploratory study was to examine appetite changes associated with noninvasive prefronto-cerebellar neuromodulation in obesity. 12 subjects with class I obesity (mean BMI 32.9 kg/m²) underwent a randomized, single-blinded, sham-controlled, crossover study, during which they received transcranial direct current stimulation (tDCS; active/sham) aimed at simultaneously enhancing the activity of the prefrontal cortex and decreasing the activity of the cerebellum. Changes in appetite (state and food-cue-triggered) and performance in a food-modified working memory task were evaluated. We found that active tDCS caused an increase in hunger and desire to eat following food-cue exposure. In line with these data, subjects also tended to make more errors during the working memory task. No changes in basic motor performance occurred. This study represents the first demonstration that prefronto-cerebellar neuromodulation can influence appetite in individuals with obesity. While preliminary, our findings support a potential role for prefronto-cerebellar pathways in the behavioral manifestations of obesity.

Expression of dopamine signaling genes in the post-mortem brain of individuals with mental illnesses is moderated by body mass index and mediated by insulin signaling genes

Preclinical studies implicate insulin signaling as a modulator of dopamine transmission, but human data is currently limited. We hypothesize that changes in the expression of insulin receptor-related genes in the post-mortem brain tissue of patients with mood and psychotic disorders mediate the expression of dopamine regulation-related genes. From a database containing microarray data from the post-mortem dorsolateral prefrontal cortex (dlPFC) (healthy controls [HC]: n = 209; patients: n = 321) and hippocampus (HC: n = 180; patients: n = 196), we conducted a hypothesis-driven analysis through the a priori selection of 12 dopamine- and 3 insulin-related genes. Mediation and moderated mediation models, accounting for the role of body mass index (BMI), were used. In the dlPFC, expressions of insulin receptor- and dopamine regulation-related genes were moderated by BMI, with significantly lower expression in high BMI patients. In the hippocampus, there were significantly lower expressions of these genes, which were not moderated by BMI. Illnesses by BMI effects on expression of dopamine genes were fully mediated by expression of insulin receptor gene (INSR). Analysis of conditional indirect effects showed interactions between INSR and BMI, indicating significantly stronger indirect effects at higher BMI values. In the hippocampus we observed that expression of insulin receptor substrate 1 and 2 fully mediated the effects of illnesses on expression of dopamine genes. In conclusion, differential expression of dopamine-related genes was related to altered expression of insulin signaling genes. BMI had region-specific effects, supporting the hypothesis that metabolic systems are critical mediators of dopaminergic function.

Neurobehavioral correlates of obesity are largely heritable

Obesity is a widespread heritable health condition. Evidence from psychology, cognitive neuroscience, and genetics has proposed links between obesity and the brain. The current study tested whether the heritable variance in body mass index (BMI) is explained by brain and behavioral factors in a large brain imaging cohort that included multiple related individuals. We found that the heritable variance in BMI had genetic correlations 0.25–0.45 with cognitive tests, cortical thickness, and regional brain volume. In particular, BMI was associated with frontal lobe asymmetry and differences in temporal-parietal perceptual systems. Further, we found genetic overlap between certain brain and behavioral factors. In summary, the genetic vulnerability to BMI is expressed in the brain. This may inform intervention strategies.

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 neurobehavioral factors such as brain morphology, cognitive performance, and personality. Here, we tested whether these neurobehavioral 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 is 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 were supported by cognitive tests, which outlined a negative association between BMI and visuospatial function, verbal episodic memory, impulsivity, and cognitive flexibility. Personality–BMI correlations were inconsistent. We then aggregated the effects for each neurobehavioral factor for a behavioral genetics analysis and estimated each factor’s genetic overlap with BMI. Cognitive test scores and brain morphometry had 0.25–0.45 genetic correlations with BMI, and the phenotypic correlations with BMI were 77–89% explained by genetic factors. Neurobehavioral factors also had some genetic overlap with each other. In summary, obesity as measured by BMI has considerable genetic overlap with brain and cognitive measures. This supports the theory that obesity is inherited via brain function and may inform intervention strategies.

Obesity, dyslipidemia and brain age in first-episode psychosis

INTRODUCTION

Obesity and dyslipidemia may negatively affect brain health and are frequent medical comorbidities of schizophrenia and related disorders. Despite the high burden of metabolic disorders, little is known about their effects on brain structure in psychosis. We investigated, whether obesity or dyslipidemia contributed to brain alterations in first-episode psychosis (FEP).

METHODS

120 participants with FEP, who were undergoing their first psychiatric hospitalization, had <24 months of untreated psychosis and were 18-35 years old and 114 controls within the same age range participated in the study. We acquired 3T brain structural MRI, fasting lipids and body mass index. We used machine learning trained on an independent sample of 504 controls to estimate the individual brain age of study participants and calculated the BrainAGE score by subtracting the chronological from the estimated brain age.

RESULTS

In a multiple regression model, the diagnosis of FEP (B = 1.15, SE B = 0.31, p < 0.001) and obesity/overweight (B = 0.92, SE B = 0.35, p = 0.008) were each additively associated with BrainAGE scores (R² = 0.22, F(3, 230) = 21.92, p < 0.001). BrainAGE scores were highest in participants with FEP and obesity/overweight (3.83 years, 95%CI = 2.35-5.31) and lowest in normal weight controls (-0.27 years, 95%CI = -1.22-0.69). LDL-cholesterol, HDL-cholesterol or triglycerides were not associated with BrainAGE scores.

CONCLUSIONS

Overweight/obesity may be an independent risk factor for diffuse brain alterations manifesting as advanced brain age already early in the course of psychosis. These findings raise the possibility that targeting metabolic health and intervening already at the level of overweight/obesity could slow brain ageing in FEP.

Preliminary evidence for genetic overlap between body mass index and striatal reward response

The reward-processing network is implicated in the aetiology of obesity. Several lines of evidence suggest obesity-linked genetic risk loci (such as DRD2 and FTO) may influence individual variation in body mass index (BMI) through neuropsychological processes reflected in alterations in activation of the striatum during reward processing. However, no study has tested the broader hypotheses that (a) the relationship between BMI and reward-related brain activation (measured through the blood oxygenation-dependent (BOLD) signal) may be observed in a large population study and (b) the overall genetic architecture of these phenotypes overlap, an assumption critical for the progression of imaging genetic studies in obesity research. Using data from the Human Connectome Project (N = 1055 healthy, young individuals: average BMI = 26.4), we first establish a phenotypic relationship between BMI and ventral striatal (VS) BOLD during the processing of rewarding (monetary) stimuli (β = 0.44, P = 0.013), accounting for potential confounds. BMI and VS BOLD were both significantly influenced by additive genetic factors (H2r = 0.57; 0.12, respectively). Further decomposition of this variance suggested that the relationship was driven by shared genetic (ρ _g = 0.47, P = 0.011), but not environmental (ρ _E = -0.07, P = 0.29) factors. To validate the assumption of genetic pleiotropy between BMI and VS BOLD, we further show that polygenic risk for higher BMI is also associated with increased VS BOLD response to appetitive stimuli (calorically high food images), in an independent sample (N = 81; P _FWE-ROI < 0.005). Together, these observations suggest that the genetic factors link risk to obesity to alterations within key nodes of the brain's reward circuity. These observations provide a basis for future work exploring the mechanistic role of genetic loci that confer risk for obesity using the imaging genetics approach.