The relationship of waist circumference and body mass index to grey matter volume in community dwelling adults with mild obesity

Habenula Volume and Functional Connectivity Changes Following Laparoscopic Sleeve Gastrectomy for Obesity Treatment

BACKGROUND

Neuroimaging studies have revealed alterations in habenular (Hb) structure and functional connectivity (FC) in psychiatric conditions. The Hb plays a particularly critical role in regulating negative emotions, which trigger excessive food intake and obesity. However, obesity and weight loss intervention (i.e., laparoscopic sleeve gastrectomy [LSG])-associated changes in Hb structure and FC have not been studied.

METHODS

We used voxel-based morphometry analysis to measure changes in gray matter volume (GMV) in the Hb in 56 patients with obesity at pre-LSG and 12 months post-LSG and in 78 normal-weight (NW) control participants. Then, we conducted Hb seed-based resting-state FC (RSFC) to examine obesity-related and LSG-induced alterations in RSFC. Finally, we used mediation analysis to characterize the interrelationships among Hb GMV, RSFC, and behaviors.

RESULTS

Compared with NW participants, Hb GMV was smaller in patients at pre-LSG and increased at 12 months post-LSG to levels equivalent to that of NW; in addition, increases in Hb GMV were correlated with reduced body mass index (BMI). Compared with NW participants, pre-LSG patients showed greater RSFCs of the Hb-insula, Hb-precentral gyrus, and Hb-rolandic operculum and weaker RSFCs of the Hb-thalamus, Hb-hypothalamus, and Hb-caudate; LSG normalized these RSFCs. Decreased RSFC of the Hb-insula was correlated with reduced BMI, Yale Food Addiction Scale rating, and emotional eating; reduced hunger levels were correlated with increased RSFCs of the Hb-thalamus and Hb-hypothalamus; and reduced BMI and Yale Food Addiction Scale ratings were correlated with increased RSFCs of the Hb-thalamus and Hb-hypothalamus, respectively. The bidirectional relationships between Hb GMV and RSFC of the Hb-insula contributed to reduced BMI.

CONCLUSIONS

These findings indicate that LSG increased Hb GMV and that its related improvement in RSFC of the Hb-insula may mediate long-term benefits of LSG for eating behaviors and weight loss.

Neuroimaging Investigations of Obesity: a Review of the Treatment of Sex from 2010

PURPOSE OF REVIEW

To summarize the results of adult obesity neuroimaging studies (structural, resting-state, task-based, diffusion tensor imaging) published from 2010, with a focus on the treatment of sex as an important biological variable in the analysis, and identify gaps in sex difference research.

RECENT FINDINGS

Neuroimaging studies have shown obesity-related changes in brain structure, function, and connectivity. However, relevant factors such as sex are often not considered. We conducted a systematic review and keyword co-occurrence analysis. Literature searches identified 6281 articles, of which 199 met inclusion criteria. Among these, only 26 (13%) considered sex as an important variable in the analysis, directly comparing the sexes (n = 10; 5%) or providing single-sex/disaggregated data (n = 16, 8%); the remaining studies controlled for sex (n = 120, 60%) or did not consider sex in the analysis (n = 53, 27%). Synthesizing sex-based results, obesity-related parameters (e.g., body mass index, waist circumference, obese status) may be generally associated with more robust morphological alterations in men and more robust structural connectivity alterations in women. Additionally, women with obesity generally expressed increased reactivity in affect-related regions, while men with obesity generally expressed increased reactivity in motor-related regions; this was especially true under a fed state. The keyword co-occurrence analysis indicated that sex difference research was especially lacking in intervention studies. Thus, although sex differences in the brain associated with obesity are known to exist, a large proportion of the literature informing the research and treatment strategies of today has not specifically examined sex effects, which is needed to optimize treatment.

Brain patterns of pace - but not rhythm - are associated with vascular disease in older adults

Background

Distinct domains of gait such as pace and rhythm are linked to an increased risk for cognitive decline, falls, and dementia in aging. The brain substrates supporting these domains and underlying diseases, however, remain relatively unknown. The current study aimed to identify patterns of gray matter volume (GMV) associated with pace and rhythm, and whether these patterns vary as a function of vascular and non-vascular comorbidities.

Methods

A cross-sectional sample of 297 older adults (M Age = 72.5 years ± 7.2 years, 43% women) without dementia was drawn from the Tasmanian Study of Cognition and Gait (TASCOG). Factor analyses were used to reduce eight quantitative gait variables into two domains. The "pace" domain was primarily composed of gait speed, stride length, and double support time. The "rhythm" domain was composed of swing time, stance time, and cadence. Multivariate covariance-based analyses adjusted for age, sex, education, total intracranial volume, and presence of mild cognitive impairment identified gray matter volume (GMV) patterns associated with pace and rhythm, as well as participant-specific expression (or factor) scores for each pattern.

Results

Pace was positively associated with GMV in the right superior temporal sulcus, bilateral supplementary motor areas (SMA), and bilateral cerebellar regions. Rhythm was positively associated with GMV in bilateral SMA, prefrontal, cingulate, and paracingulate cortices. The GMV pattern associated with pace was less expressed in participants with any vascular disease; this association was also found independently with hypertension, diabetes, and myocardial infarction.

Conclusion

Both pace and rhythm domains of gait were associated with the volume of brain structures that have been linked to controlled and automatic aspects of gait control, as well as with structures involved in multisensory integration. Only the brain structures associated with pace, however, were associated with vascular disease.

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.

Relationship Between Acyl and Desacyl Ghrelin Levels with Insulin Resistance and Body Fat Mass in Type 2 Diabetes Mellitus

PURPOSE

Although strong evidence suggests that ghrelin plays an important role in regulating energy balance, the effects of acylated ghrelin (AG) and deacylated ghrelin (DAG) on fat mass are largely undefined. This study aimed to investigate the differential associations of both forms of ghrelin with insulin resistance and body fat mass in patients with type 2 diabetes mellitus (T2DM).

PATIENTS AND METHODS

A total of 162 patients with type 2 diabetes were recruited and classified based on BMI and visceral fat area (VFA) as VFA normal group (n = 78), normal-BMI VFA obesity group (n = 20) and high-BMI VFA obesity group (n = 64). VFA and subcutaneous fat area (SFA) were detected by bioelectrical impedance analysis. Blood samples were collected to measure fasting glucose, insulin, lipids, AG and DAG levels after clinical examination.

RESULTS

Compared with VFA normal group, DAG levels were significantly lower (421.7 ± 106.0 and 388.7 ± 96.5 pg/mL vs 524.4 ± 141.5 pg/mL, P < 0.01) in the two VFA obesity groups. No significant difference was found in AG levels within three groups. Among all subjects, BMI, VFA, SFA, fasting insulin and HOMA-IR were negatively correlated with DAG but positively with AG/DAG ratio (P < 0.01). In contrast, AG was positively correlated with HOMA-IR and fasting glucose (P < 0.01). Multiple stepwise regression analysis showed that fasting glucose was the independent factor of AG, VFA and HOMA-IR were the independent factors related to DAG.

CONCLUSION

DAG levels have a strong negative association with excess body fat mass and insulin resistance, whereas AG levels are closely related to elevated blood glucose levels in T2DM patients.

Obesity and Gray Matter Volume Assessed by Neuroimaging: A Systematic Review

Obesity has become a major public and individual health problem due to its high worldwide prevalence and its relation with comorbid conditions. According to previous studies, obesity is related to an increased risk of cognitive impairment and dementia. This systematic review aims to further examine the present state of the art about the association between obesity and gray matter volume (GMV) as assessed by magnetic resonance imaging (MRI). A search was conducted in Pubmed, SCOPUS and Cochrane of those studies released before 1 February 2021 including MRIs to assess the GMVs in obese participants. From this search, 1420 results were obtained, and 34 publications were finally included. Obesity was mainly measured by the body mass index, although other common types of evaluations were used (e.g., waist circumference, waist-to-hip ratio and plasma leptin levels). The selected neuroimaging analysis methods were voxel-based morphometry (VBM) and cortical thickness (CT), finding 21 and 13 publications, respectively. There were 30 cross-sectional and 2 prospective longitudinal studies, and 2 articles had both cross-sectional and longitudinal designs. Most studies showed a negative association between obesity and GMV. This would have important public health implications, as obesity prevention could avoid a potential risk of GMV reductions, cognitive impairment and dementia.

Is Obesity Associated with Lower Mini Mental Test Scores among Elderly? A Cross Sectional Study

OBJECTIVES

Obesity leads to many chronic diseases and its association with cognitive impairment is controversial. The objective was to investigate the association between obesity, anthropometric measurements and cognitive functions of elderly.

METHODS

Planned cross-sectionally, community-dwelling Cypriots (aged ≥ 50 years) without any neurological disorders, were included. Cognitive impairment evaluated by Mini Mental State Examination (MMSE) was the dependent variable. Socio-demographic variables, anthropometric measurements and obesity were the independent variables. The data was collected via face-to-face interview. Logistic regression models were constituted to determine the association of anthropometric measurements, obesity and dementia.

RESULTS

The mean age of participants (n = 541) was 60.0 ± 8.7 for women (n = 377) and 61.5 ± 6.0 years for men (n = 164). According to MMSE, 26.0% of women and 11.0% of men had mild-dementia, and the rest scored normal. After adjusted for age and sex, each unit increase in BMI (OR: 1.045, 95%CI: 1.008-1.091), Waist to height ratio (WHtR; OR: 1.030, 95%CI: 1.006-1.055) and Mid upper arm circumference (MUAC; OR: 1.077, 95%CI: 1.016-1.141) increases the risk of mild-dementia. When education, employment and smoking were included in the models, significance of anthropometric measurements was diminished and only sex and education were remained significant for all.

CONCLUSION

After controlled for age and sex, increment in anthropometric measurements increased the risk of dementia but when education was taken into consideration, this significant association was diminished showing that sex and education is more predominant in a heterogeneous group in means of education. Thus, for heterogeneous groups it might be better to revise MMSE. To determine the association between obesity and dementia cohort studies with longer follow-up duration with larger samples are needed.

Structural Brain Changes Associated with Overweight and Obesity

Obesity is a global health problem with a broad set of comorbidities, such as malnutrition, metabolic syndrome, diabetes, systemic hypertension, heart failure, and kidney failure. This review describes recent findings of neuroimaging and two studies of cell density regarding the roles of overnutrition-induced hypothalamic inflammation in neurodegeneration. These studies provided consistent evidence of smaller cortical thickness or reduction in the gray matter volume in people with overweight and obesity; however, the investigated brain regions varied across the studies. In general, bilateral frontal and temporal areas, basal nuclei, and cerebellum are more commonly involved. Mechanisms of volume reduction are unknown, and neuroinflammation caused by obesity is likely to induce neuronal loss. Adipocytes, macrophages of the adipose tissue, and gut dysbiosis in overweight and obese individuals result in the secretion of the cytokines and chemokines that cross the blood-brain barrier and may stimulate microglia, which in turn also release proinflammatory cytokines. This leads to chronic low-grade neuroinflammation and may be an important factor for apoptotic signaling and neuronal death. Additionally, significant microangiopathy observed in rat models may be another important mechanism of induction of apoptosis. Neuroinflammation in neurodegenerative diseases (such as Alzheimer's and Parkinson's diseases) may be similar to that in metabolic diseases induced by malnutrition. Poor cognitive performance, mainly in executive functions, in individuals with obesity is also discussed. This review highlights the neuroinflammatory and neurodegenerative mechanisms linked to obesity and emphasizes the importance of developing effective prevention and treatment intervention strategies for overweight and obese individuals.

Does obesity exacerbate brain lesion volume and atrophy in patients with multiple sclerosis?

BACKGROUND

Obesity is common among patients with multiple sclerosis (pwMS) and has been shown to exacerbate central inflammation, a key factor in disease progression. The purpose of this cross-sectional study is to examine the possible relationships between obesity, as measured by body mass index (BMI), and MS-related brain changes in atrophy and lesion volume, as measured from MRI, in a large, representative sample of pwMS.

METHODS

BMI and MRI data, along with demographic and disease variables, were acquired from the Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) registry. Unadjusted and adjusted partial correlations, controlling for gender, race, age, education level, MS phenotype, disability and disease duration, examined the associations between BMI and MRI outcomes, which included brain parenchymal fraction, white matter fraction, gray matter fraction, thalamic volume, and T2 lesion volume.

RESULTS

The sample consisted of 3,046 pwMS. Unadjusted and adjusted BMI-MRI correlations accounted for between 0.4% and 2.0% of shared variance (R²). When considering the relationship between MRI outcomes and BMI category (normal weight, overweight, obese), multiple regression analyses continued to show minimal association, with BMI category accounting for no more than 1.5% of shared variance.

CONCLUSIONS

No clinically meaningful associations were found between BMI and MRI outcomes in this large, representative sample of MS patients, regardless of demographics and disease variables. These unexpected negative results will require replication with a longitudinal design using more precise measures of obesity.

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.

The interrelationship of body mass index with gray matter volume and resting-state functional connectivity of the hypothalamus

Background

The hypothalamus plays an important role in regulating body weight through its interactions with multiple brain circuits involved in distinct aspects of feeding behavior. Yet, how hypothalamic gray matter volume (GMV) and connectivity may be related to individual differences in body weight remains unclear. We tested the hypothesis that the hypothalamus shows enhanced resting-state functional connectivity (rsFC) with regions of the reward, motivation, and motor circuits in positive correlation with body mass index (BMI) and the opposite with those associated with inhibitory control. We further examined the interdependent relationships between hypothalamic GMV, connectivity, and body weight.

Methods

Using seed-based rsFC and voxel-based morphometry analyses, we examined the relationship between the rsFC and GMV of the hypothalamus and BMI in 105 healthy humans. Additionally, we employed mediation analyses to characterize the inter-relationships between hypothalamic connectivity, GMV, and BMI.

Results

A whole-brain multiple regression showed that BMI was positively correlated with hypothalamic rsFC with the insula, thalamus, globus pallidus, and cerebellum, and negatively correlated with hypothalamic rsFC with the superior parietal lobule. Thus, higher BMI was associated with enhanced hypothalamic connectivity with regions involved in motivated feeding and reduced connectivity with those in support of cognitive control of food intake. A second whole-brain multiple regression revealed a positive correlation between hypothalamic GMV and the hypothalamus-posterior insula connectivity. Finally, the relationship between hypothalamic GMV and BMI was significantly and bidirectionally mediated by the hypothalamus-posterior insula connectivity.

Conclusions

The current findings suggest that the hypothalamus differentially interacts with the motivation, motor, and control circuits to regulate BMI. We further found evidence for the interdependence of hypothalamic structure, function, and body weight, which provides potential insights into the brain mechanisms of obesity.

A Metabolic Obesity Profile Is Associated With Decreased Gray Matter Volume in Cognitively Healthy Older Adults

Obesity is a risk factor for cognitive decline and gray matter volume loss in aging. Studies have shown that different metabolic factors, e.g., dysregulated glucose metabolism and systemic inflammation, might mediate this association. Yet, even though these risk factors tend to co-occur, they have mostly been investigated separately, making it difficult to establish their joint contribution to gray matter volume structure in aging. Here, we therefore aimed to determine a metabolic profile of obesity that takes into account different anthropometric and metabolic measures to explain differences in gray matter volume in aging. We included 748 elderly, cognitively healthy participants (age range: 60 - 79 years, BMI range: 17 - 42 kg/m2) of the LIFE-Adult Study. All participants had complete information on body mass index, waist-to-hip ratio, glycated hemoglobin, total blood cholesterol, high-density lipoprotein, interleukin-6, C-reactive protein, adiponectin and leptin. Voxelwise gray matter volume was extracted from T1-weighted images acquired on a 3T Siemens MRI scanner. We used partial least squares correlation to extract latent variables with maximal covariance between anthropometric, metabolic and gray matter volume and applied permutation/bootstrapping and cross-validation to test significance and reliability of the result. We further explored the association of the latent variables with cognitive performance. Permutation tests and cross-validation indicated that the first pair of latent variables was significant and reliable. The metabolic profile was driven by negative contributions from body mass index, waist-to-hip ratio, glycated hemoglobin, C-reactive protein and leptin and a positive contribution from adiponectin. It positively covaried with gray matter volume in temporal, frontal and occipital lobe as well as subcortical regions and cerebellum. This result shows that a metabolic profile characterized by high body fat, visceral adiposity and systemic inflammation is associated with reduced gray matter volume and potentially reduced executive function in older adults. We observed the highest contributions for body weight and fat mass, which indicates that factors underlying sustained energy imbalance, like sedentary lifestyle or intake of energy-dense food, might be important determinants of gray matter structure in aging.