Brain structure and obesity

Visceral and Subcutaneous Abdominal Fat Predict Brain Volume Loss at Midlife in 10,001 Individuals

Abdominal fat is increasingly linked to brain health. A total of 10,001 healthy participants were scanned on 1.5T MRI with a short whole-body MR imaging protocol. Deep learning with FastSurfer segmented 96 brain regions. Separate models segmented visceral and subcutaneous abdominal fat. Regression analyses of abdominal fat types and normalized brain volumes were evaluated, controlling for age and sex. Logistic regression models determined the risk of brain total gray and white matter volume loss from the highest quartile of visceral fat and lowest quartile of these brain volumes. This cohort had an average age of 52.9 ± 13.1 years with 52.8% men and 47.2% women. Segmented visceral abdominal fat predicted lower volumes in multiple regions including: total gray matter volume (r = -.44, p<.001), total white matter volume (r =-.41, p<.001), hippocampus (r = -.39, p< .001), frontal cortex (r = -.42, p<.001), temporal lobes (r = -.44, p<.001), parietal lobes (r = -.39, p<.001), occipital lobes (r =-.37, p<.001). Women showed lower brain volumes than men related to increased visceral fat. Visceral fat predicted increased risk for lower total gray matter (age 20-39: OR = 5.9; age 40-59, OR = 5.4; 60-80, OR = 5.1) and low white matter volume: (age 20-39: OR = 3.78; age 40-59, OR = 4.4; 60-80, OR = 5.1). Higher subcutaneous fat is related to brain volume loss. Elevated visceral and subcutaneous fat predicted lower brain volumes and may represent novel modifiable factors in determining brain health.

Edge Density Imaging Identifies White Matter Biomarkers of Late-Life Obesity and Cognition

Alzheimer disease (AD) and obesity are related to disruptions in the white matter (WM) connectome. We examined the link between the WM connectome and obesity and AD through edge-density imaging/index (EDI), a tractography-based method that characterizes the anatomical embedding of tractography connections. A total of 60 participants, 30 known to convert from normal cognition or mild-cognitive impairment to AD within a minimum of 24 months of follow up, were selected from the Alzheimer disease Neuroimaging Initiative (ADNI). Diffusion-weighted MR images from the baseline scans were used to extract fractional anisotropy (FA) and EDI maps that were subsequently averaged using deterministic WM tractography based on the Desikan-Killiany atlas. Multiple linear and logistic regression analysis were used to identify the weighted sum of tract-specific FA or EDI indices that maximized correlation to body-mass-index (BMI) or conversion to AD. Participants from the Open Access Series of Imaging Studies (OASIS) were used as an independent validation for the BMI findings. The edge-density rich, periventricular, commissural and projection fibers were among the most important WM tracts linking BMI to FA as well as to EDI. WM fibers that contributed significantly to the regression model related to BMI overlapped with those that predicted conversion; specifically in the frontopontine, corticostriatal, and optic radiation pathways. These results were replicated by testing the tract-specific coefficients found using ADNI in the OASIS-4 dataset. WM mapping with EDI enables identification of an abnormal connectome implicated in both obesity and conversion to AD.

Regional gray matter changes in steatotic liver disease provide a neurobiological link to depression: A cross-sectional UK Biobank cohort study

BACKGROUND

Steatotic liver disease (SLD) is characterized by excessive accumulation of lipids in the liver. It is associated with elevated risk of hepatic and cardiometabolic diseases, as well as mental disorders such as depression. Previous studies revealed global gray matter reduction in SLD. To investigate a possible shared neurobiology with depression, we examined liver fat-related regional gray matter alterations in SLD and its most significant clinical subgroup metabolic dysfunction-associated steatotic liver disease (MASLD).

METHODS

We analyzed regional cortical thickness and area obtained from brain MRI in 29,051 participants in UK Biobank. Liver fat amount was computed as proton density fat fraction (PDFF) from liver MRI scans. We examined the relationship between brain structure and PDFF, adjusting for sociodemographic, physical, lifestyle, and environmental factors, as well as alcohol intake and a spectrum of cardiometabolic covariates. Finally, we compared patterns of brain alterations in SLD/MASLD and major depressive disorder (MDD) using previously published results.

RESULTS

PDFF-related gray matter alterations were region-specific, involving both increases and decreases in cortical thickness, and increased cortical area. In several regions, PDFF effects on gray matter could also be attributed to cardiometabolic covariates. However, PDFF was consistently associated with lower cortical thickness in middle and superior temporal regions and higher cortical thickness in pericalcarine and right frontal pole regions. PDFF-related alterations for the SLD and the MASLD group correlated with those observed in MDD (Pearson r = 0.45-0.54, p < 0.01).

CONCLUSION

These findings suggest the presence of shared biological mechanisms linking MDD to SLD and MASLD. They might explain the well-known elevated risk of depression in these groups and support early lifestyle interventions and treatment of metabolic risk factors for the successful management of the interconnected diseases depression and SLD/MASLD.

Impact of Sleeve Gastrectomy on Brain Structural Integrity

INTRODUCTION

Potential brain structural differences in people with obesity (PwO) who achieve over or less than 50% excess weight loss (EWL) after sleeve gastrectomy (SG) are currently unknown. We compared measures of gray matter volume (GMV) and white matter (WM) microstructural integrity of PwO who achieved over or less than 50% EWL after SG with a group of controls with obesity (CwO) without a past history of metabolic bariatric surgery.

METHODS

Sixty-two PwO underwent 1.5 T MRI scanning: 24 who achieved more than 50% of EWL after SG ("group a"), 18 who achieved less than 50% EWL after SG ("group b"), and 20 CwO ("group c"). Voxel-based morphometry and tract-based spatial Statistics analyses were performed to investigate GMV and WM differences among groups. Multiple regression analyses were performed to investigate relationships between structural and psychological measures.

RESULTS

Group a demonstrated significantly lower GMV loss and higher WM microstructural integrity with respect to group b and c in some cortical regions and several WM tracts. Positive correlations were observed in group a between WM integrity and several psychological measures; the lower the WM integrity, the higher the mental distress, emotional dysregulation, and binge eating behavior.

CONCLUSION

The present results gain a new understanding of the neural mechanisms of outcome in patients who undergo SG. We found limited GMV changes and extensive WM microstructural differences between PwO who achieved over or less than 50% EWL after SG, which may be due to higher vulnerability of WM to the metabolic dysfunction present in PwO.

Sex as a Determinant of Age-Related Changes in the Brain

The notion of notable anatomical, biochemical, and behavioral distinctions within male and female brains has been a contentious topic of interest within the scientific community over several decades. Advancements in neuroimaging and molecular biological techniques have increasingly elucidated common mechanisms characterizing brain aging while also revealing disparities between sexes in these processes. Variations in cognitive functions; susceptibility to and progression of neurodegenerative conditions, notably Alzheimer's and Parkinson's diseases; and notable disparities in life expectancy between sexes, underscore the significance of evaluating aging within the framework of gender differences. This comprehensive review surveys contemporary literature on the restructuring of brain structures and fundamental processes unfolding in the aging brain at cellular and molecular levels, with a focus on gender distinctions. Additionally, the review delves into age-related cognitive alterations, exploring factors influencing the acceleration or deceleration of aging, with particular attention to estrogen's hormonal support of the central nervous system.

Body mass index-dependent shifts along large-scale gradients in human cortical organization explain dietary regulatory success

Making healthy dietary choices is essential for keeping weight within a normal range. Yet many people struggle with dietary self-control despite good intentions. What distinguishes neural processing in those who succeed or fail to implement healthy eating goals? Does this vary by weight status? To examine these questions, we utilized an analytical framework of gradients that characterize systematic spatial patterns of large-scale neural activity, which have the advantage of considering the entire suite of processes subserving self-control and potential regulatory tactics at the whole-brain level. Using an established laboratory food task capturing brain responses in natural and regulatory conditions (N = 123), we demonstrate that regulatory changes of dietary brain states in the gradient space predict individual differences in dietary success. Better regulators required smaller shifts in brain states to achieve larger goal-consistent changes in dietary behaviors, pointing toward efficient network organization. This pattern was most pronounced in individuals with lower weight status (low-BMI, body mass index) but absent in high-BMI individuals. Consistent with prior work, regulatory goals increased activity in frontoparietal brain circuits. However, this shift in brain states alone did not predict variance in dietary success. Instead, regulatory success emerged from combined changes along multiple gradients, showcasing the interplay of different large-scale brain networks subserving dietary control and possible regulatory strategies. Our results provide insights into how the brain might solve the problem of dietary control: Dietary success may be easier for people who adopt modes of large-scale brain activation that do not require significant reconfigurations across contexts and goals.

Electrophysiological Characteristics of Inhibitive Control for Adults with Different Physiological or Psychological Obesity

Individuals exhibiting high scores on the fatness subscale of the negative-physical-self scale (NPSS-F) are characterized by heightened preoccupation with body fat accompanied by negative body image perceptions, often leading to excessive dieting behaviors. This demographic constitutes a considerable segment of the populace in China, even among those who are not obese. Nonetheless, scant empirical inquiries have delved into the behavioral and neurophysiological profiles of individuals possessing a healthy body mass index (BMI) alongside elevated NPSS-F scores. This study employed an experimental paradigm integrating go/no-go and one-back tasks to assess inhibitory control and working memory capacities concerning food-related stimuli across three adult cohorts: those with normal weight and low NPSS-F scores, those with normal weight and high NPSS-F scores, and individuals classified as obese. Experimental stimuli comprised high- and low-caloric-food pictures with concurrent electroencephalogram (EEG) and photoplethysmogram (PPG) recordings. Individuals characterized by high NPSS-F scores and normal weight exhibited distinctive electrophysiological responses compared to the other two cohorts, evident in event-related potential (ERP) components, theta and alpha band oscillations, and heart rate variability (HRV) patterns. In essence, the findings underscore alterations in electrophysiological reactivity among individuals possessing high NPSS-F scores and a healthy BMI in the context of food-related stimuli, underscoring the necessity for increased attention to this demographic alongside individuals affected by obesity.

Towards a Deeper Understanding: Utilizing Machine Learning to Investigate the Association between Obesity and Cognitive Decline-A Systematic Review

Background/Objectives: Several studies have shown a relation between obesity and cognitive decline, highlighting a significant global health challenge. In recent years, artificial intelligence (AI) and machine learning (ML) have been integrated into clinical practice for analyzing datasets to identify new risk factors, build predictive models, and develop personalized interventions, thereby providing useful information to healthcare professionals. This systematic review aims to evaluate the potential of AI and ML techniques in addressing the relationship between obesity, its associated health consequences, and cognitive decline. Methods: Systematic searches were performed in PubMed, Cochrane, Web of Science, Scopus, Embase, and PsycInfo databases, which yielded eight studies. After reading the full text of the selected studies and applying predefined inclusion criteria, eight studies were included based on pertinence and relevance to the topic. Results: The findings underscore the utility of AI and ML in assessing risk and predicting cognitive decline in obese patients. Furthermore, these new technology models identified key risk factors and predictive biomarkers, paving the way for tailored prevention strategies and treatment plans. Conclusions: The early detection, prevention, and personalized interventions facilitated by these technologies can significantly reduce costs and time. Future research should assess ethical considerations, data privacy, and equitable access for all.

Childhood maltreatment influences adult brain structure through its effects on immune, metabolic, and psychosocial factors

Childhood maltreatment (CM) leads to a lifelong susceptibility to mental ill-health which might be reflected by its effects on adult brain structure, perhaps indirectly mediated by its effects on adult metabolic, immune, and psychosocial systems. Indexing these systemic factors via body mass index (BMI), C-reactive protein (CRP), and rates of adult trauma (AT), respectively, we tested three hypotheses: (H1) CM has direct or indirect effects on adult trauma, BMI, and CRP; (H2) adult trauma, BMI, and CRP are all independently related to adult brain structure; and (H3) childhood maltreatment has indirect effects on adult brain structure mediated in parallel by BMI, CRP, and AT. Using path analysis and data from N = 116,887 participants in UK Biobank, we find that CM is related to greater BMI and AT levels, and that these two variables mediate CM's effects on CRP [H1]. Regression analyses on the UKB MRI subsample (N = 21,738) revealed that greater CRP and BMI were both independently related to a spatially convergent pattern of cortical effects (Spearman's ρ = 0.87) characterized by fronto-occipital increases and temporo-parietal reductions in thickness. Subcortically, BMI was associated with greater volume, AT with lower volume and CPR with effects in both directions [H2]. Finally, path models indicated that CM has indirect effects in a subset of brain regions mediated through its direct effects on BMI and AT and indirect effects on CRP [H3]. Results provide evidence that childhood maltreatment can influence brain structure decades after exposure by increasing individual risk toward adult trauma, obesity, and inflammation.

White adipose tissue distribution and amount are associated with increased white matter connectivity

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a deeper characterization of body composition is required, especially considering the links between abdominal obesity and metabolic dysfunction. This study aims to enhance our understanding of the relationship between obesity and WM connectivity by directly assessing the amount and distribution of fat tissue. Whole-body magnetic resonance imaging (MRI) was employed to evaluate total adipose tissue (TAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT), while MR liver spectroscopy measured liver fat content in 63 normal-weight, overweight, and obese males. WM connectivity was quantified using microstructure-informed tractography. Connectome-based predictive modeling was used to predict body composition metrics based on WM connectomes. Our analysis revealed a positive dependency between BMI, TAT, SAT, and WM connectivity in brain regions involved in reward processing and appetite regulation, such as the insula, nucleus accumbens, and orbitofrontal cortex. Increased connectivity was also observed in cognitive control and inhibition networks, including the middle frontal gyrus and anterior cingulate cortex. No significant associations were found between WM connectivity and VAT or liver fat. Our findings suggest that altered neural communication between these brain regions may affect cognitive processes, emotional regulation, and reward perception in individuals with obesity, potentially contributing to weight gain. While our study did not identify a link between WM connectivity and VAT or liver fat, further investigation of the role of various fat depots and metabolic factors in brain networks is required to advance obesity prevention and treatment approaches.

Associations between antipsychotics-induced weight gain and brain networks of impulsivity

Given the unpredictable rapid onset and ubiquitous consequences of weight gain induced by antipsychotics, there is a pressing need to get insights into the underlying processes at the brain system level that will allow stratification of "at risk" patients. The pathophysiological hypothesis at hand is focused on brain networks governing impulsivity that are modulated by neuro-inflammatory processes. To this aim, we investigated brain anatomy and functional connectivity in patients with early psychosis (median age: 23 years, IQR = 21-27) using anthropometric data and magnetic resonance imaging acquired one month to one year after initiation of AP medication. Our analyses included 19 patients with high and rapid weight gain (i.e., ≥5% from baseline weight after one month) and 23 patients with low weight gain (i.e., <5% from baseline weight after one month). We replicated our analyses in young (26 years, IQR = 22-33, N = 102) and middle-aged (56 years, IQR = 51-62, N = 875) healthy individuals from the general population. In early psychosis patients, higher weight gain was associated with poor impulse control score (β = 1.35; P = 0.03). Here, the observed brain differences comprised nodes of impulsivity networks - reduced frontal lobe grey matter volume (Pcorrected = 0.007) and higher striatal volume (Pcorrected = 0.048) paralleled by disruption of fronto-striatal functional connectivity (R = -0.32; P = 0.04). Weight gain was associated with the inflammatory biomarker plasminogen activator inhibitor-1 (β = 4.9, P = 0.002). There was no significant association between increased BMI or weight gain and brain anatomy characteristics in both cohorts of young and middle-aged healthy individuals. Our findings support the notion of weight gain in treated psychotic patients associated with poor impulse control, impulsivity-related brain networks and chronic inflammation.

Association between Body Mass Index and Brain Health in Adults: A 16-Year Population-Based Cohort and Mendelian Randomization Study

Background: The cumulative effect of body mass index (BMI) on brain health remains ill-defined. The effects of overweight on brain health across different age groups need clarification. We analyzed the effect of cumulative BMI on neuroimaging features of brain health in adults of different ages. Methods: This study was based on a multicenter, community-based cohort study. We modeled the trajectories of BMI over 16 years to evaluate cumulative exposure. Multimodality neuroimaging data were collected once for volumetric measurements of the brain macrostructure, white matter hyperintensity (WMH), and brain microstructure. We used a generalized linear model to evaluate the association between cumulative BMI and neuroimaging features. Two-sample Mendelian randomization analysis was performed using summary level of BMI genetic data from 681,275 individuals and neuroimaging genetic data from 33,224 individuals to analyze the causal relationships. Results: Clinical and neuroimaging data were obtained from 1,074 adults (25 to 83 years). For adults aged under 45 years, brain volume differences in participants with a cumulative BMI of >26.2 kg/m2 corresponded to 12.0 years [95% confidence interval (CI), 3.0 to 20.0] of brain aging. Differences in WMH were statistically substantial for participants aged over 60 years, with a 6.0-ml (95% CI, 1.5 to 10.5) larger volume. Genetic analysis indicated causal relationships between high BMI and smaller gray matter and higher fractional anisotropy in projection fibers. Conclusion: High cumulative BMI is associated with smaller brain volume, larger volume of white matter lesions, and abnormal microstructural integrity. Adults younger than 45 years are suggested to maintain their BMI below 26.2 kg/m2 for better brain health. Trial Registration: This study was registered on clinicaltrials.gov (Clinical Indicators and Brain Image Data: A Cohort Study Based on Kailuan Cohort; No. NCT05453877; https://clinicaltrials.gov/ct2/show/NCT05453877).

Interactive Relations of Body Mass Index, Cardiorespiratory Fitness, and Sex to Cognitive Function in Older Adults

OBJECTIVE

The course of cognitive aging is influenced by multiple health factors. This cross-sectional study investigated the interactive relations between body mass index (BMI), maximum oxygen consumption (VO2max), and sex on neuropsychological outcomes in community-dwelling predominantly older adults.

METHODS

Participants were 164 healthy adults [M (SD) = 64.6 (12.5) years, 56% men, 87% white] who participated in an investigation of cardiovascular risk factors and brain health. Multivariable regression analysis, adjusted for age, education, ethnicity, smoking, alcohol consumption, and depression, examined the interactive relations of BMI, VO2max, and sex to multiple neuropsychological outcomes.

RESULTS

Significant BMI*VO2max*sex interactions for Grooved Pegboard dominant (p = .019) and nondominant (p = .005) hands revealed that men with lower VO2max (l/min) displayed worse performance with each hand as BMI increased (p's < .02). A significant BMI*sex interaction for Logical Memory-Delayed Recall (p = .036) (after adjustment for blood glucose) showed that men, but not women, with higher BMI demonstrated worse performance (p = .036). Lastly, significant main effects indicated that lower VO2max was related to poorer logical memory, and higher BMI was associated with poorer Trail Making B and Stroop interference scores (p's < .05).

CONCLUSIONS

Among men, higher cardiorespiratory fitness may protect against the negative impact of greater BMI on manual dexterity and motor speed, making VO2max a target for intervention. Higher BMI is further associated with poorer executive function and verbal memory (in men), and lower VO2max is associated with poorer verbal memory.

Association of variability in body size with neuroimaging metrics of brain health: a population-based cohort study

Background

The relationship between the fluctuation in body size and brain health is poorly understood. This study aimed to examine the associations of long-term variability in body mass index (BMI) and waist-to-hip ratio (WHR) with neuroimaging metrics that approximate brain health.

Methods

This cohort study recruited 1114 participants aged 25-83 years from a multicenter, community-based cohort study in China. We modeled the BMI and WHR trajectories of participants during 2006-2018 and assessed the BMI and WHR variability (direction and speed of change) by calculating the slope. Generalized linear models were applied to investigate the associations of BMI and WHR variability with MRI markers of brain tissue volume, white matter microstructural integrity, white matter hyperintensity (WMH), and cerebral small vessel disease (CSVD).

Findings

Progressive weight gain during follow-up was associated with lower global fractional anisotropy (beta = -0.18, 95% confidence interval [CI] -0.34 to -0.02), higher mean diffusivity (beta = 0.15, 95% CI 0.01-0.30) and radial diffusivity (beta = 0.17, 95% CI 0.02-0.32). Weight loss was also associated with a lower burden of periventricular WMH (beta = -0.26, 95% CI -0.48 to -0.03) and a lower risk of moderate-to-severe basal ganglia enlarged perivascular spaces (BG-EPVS, odds ratio [OR] = 0.41, 95% CI 0.20-0.83). Among overweight populations, weight loss was linked with smaller volumes of WMH (beta = -0.47, 95% CI -0.79 to -0.15), periventricular WMH (beta = -0.57, 95% CI -0.88 to -0.26), and deep WMH (beta = -0.36, 95% CI -0.69 to -0.03), as well as lower risk of CSVD (OR = 0.22, 95% CI 0.08-0.62), lacune (OR = 0.12, 95% CI 0.01-0.91) and moderate-to-severe BG-EPVS (OR = 0.24, 95% CI 0.09-0.61). In adults with central obesity, WHR loss was positively associated with larger gray matter volume (beta = 0.50, 95% CI 0.11-0.89), hippocampus volume (beta = 0.62, 95% CI 0.15-1.09), and parahippocampal gyrus volume (beta = 0.85, 95% CI 0.34-1.37). The sex-stratification and age-stratification analyses revealed similar findings with the main results, with the pattern of associations significantly presented in the individuals at mid-life and late-life.

Interpretation

Long-term stability of BMI level is essential for maintaining brain health. Progressive weight gain is associated with impaired white matter microstructural integrity. Weight and WHR losses are associated with improved general brain health. Our results contribute to a better understanding of the integrated associations between variations in obesity measures and brain health.

Funding

This study was supported by grants No. 62171297 (Han Lv) and 61931013 (Zhenchang Wang) from the National Natural Science Foundation of China, No. 7242267 from the Beijing Natural Science Foundation (Han Lv), and No. [2015] 160 from the Beijing Scholars Program (Zhenchang Wang).

Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI

There is inconsistent evidence for an association of obesity with white matter microstructural alterations. Such inconsistent findings may be related to the cumulative effects of obesity and alcohol dependence. This study aimed to investigate the possible interactions between alcohol dependence and overweight/obesity on white matter microstructure in the human brain. A total of 60 inpatients with alcohol dependence during early abstinence (44 normal weight and 16 overweight/obese) and 65 controls (42 normal weight and 23 overweight/obese) were included. The diffusion tensor imaging (DTI) measures [fractional anisotropy (FA) and radial diffusivity (RD)] of the white matter microstructure were compared between groups. We observed significant interactive effects between alcohol dependence and overweight/obesity on DTI measures in several tracts. The DTI measures were not significantly different between the overweight/obese and normal-weight groups (although widespread trends of increased FA and decreased RD were observed) among controls. However, among the alcohol-dependent patients, the overweight/obese group had widespread reductions in FA and widespread increases in RD, most of which significantly differed from the normal-weight group; among those with overweight/obesity, the alcohol-dependent group had widespread reductions in FA and widespread increases in RD, most of which were significantly different from the control group. This study found significant interactive effects between overweight/obesity and alcohol dependence on white matter microstructure, indicating that these two controllable factors may synergistically impact white matter microstructure and disrupt structural connectivity in the human brain.

Sex-Specific Association of Body Mass Index with Hippocampal Subfield Volume and Cognitive Function in Non-Demented Chinese Older Adults

Recent research suggests a possible association between midlife obesity and an increased risk of dementia in later life. However, the underlying mechanisms remain unclear. Little is known about the relationship between body mass index (BMI) and hippocampal subfield atrophy. In this study, we aimed to explore the associations between BMI and hippocampal subfield volumes and cognitive function in non-demented Chinese older adults. Hippocampal volumes were assessed using structural magnetic resonance imaging. Cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). A total of 66 participants were included in the final analysis, with 35 females and 31 males. We observed a significant correlation between BMI and the hippocampal fissure volume in older females. In addition, there was a negative association between BMI and the RBANS total scale score, the coding score, and the story recall score, whereas no significant correlations were observed in older males. In conclusion, our findings revealed sex-specific associations between BMI and hippocampal subfield volumes and cognitive performance, providing valuable insights into the development of effective interventions for the early prevention of cognitive decline.

The obesity paradox and ventriculoperitoneal shunting in aneurysmal subarachnoid hemorrhage patients undergoing microsurgical clipping

BACKGROUND

Aneurysmal subarachnoid hemorrhage (aSAH) can be devastating. Identifying predisposing factors is paramount in reducing aSAH-related mortality. Obesity's negative impact on health is well-established. However, the controversial "obesity paradox" in neurosurgery suggests that obesity may confer a survival advantage in SAH. We hypothesized that obesity would have a negative impact on outcomes following surgical clipping in aSAH.

METHODS

A single-institution retrospective review was performed of aSAH patients undergoing surgical clipping from 2017 to 2021. Demographics and clinically relevant variables were collected. Obesity was defined as body mass index >30. Primary outcome was death or severe disability (mRS 4-6) at last follow-up. Secondary outcome was VPS placement. Multivariable Cox proportional-hazards model identified predictors of poor outcome. Kaplan-Meier curves identified survivorship differences between obese and non-obese patients.

RESULTS

Poor outcome occurred in 11 of 52 total patients (21.2 %). There were no differences in demographics or distribution of Hunt Hess (HH), modified Fisher Grade (mFG), or external ventricular drain (EVD) placement between obese and non-obese patients. On univariate analysis, hypertension, older age, and non-obesity were predictive of poor outcome. On multivariable analysis, only obesity remained significant, suggesting a protective effect from poor outcome (HR 0.45 [0.21-0.95], p = 0.037). VPS placement occurred in 6 (11.5 %) patients for which obesity was not a significant predictor.

CONCLUSIONS

Obesity may have a protective effect against poor outcome following surgical clipping in aSAH. Additionally, obesity does not appear to increase rate of EVD conversion to VPS. Thus, our study suggests that obesity should not preclude patients from open surgical intervention when clinically appropriate.

Obesity is associated with alterations in anatomical connectivity of frontal-corpus callosum

Obesity has been linked to abnormal frontal function, including the white matter fibers of anterior portion of the corpus callosum, which is crucial for information exchange within frontal cortex. However, alterations in white matter anatomical connectivity between corpus callosum and cortical regions in patients with obesity have not yet been investigated. Thus, we enrolled 72 obese and 60 age-/gender-matched normal weight participants who underwent clinical measurements and diffusion tensor imaging. Probabilistic tractography with connectivity-based classification was performed to segment the corpus callosum and quantify white matter anatomical connectivity between subregions of corpus callosum and cortical regions, and associations between corpus callosum-cortex white matter anatomical connectivity and clinical behaviors were also assessed. Relative to normal weight individuals, individuals with obesity exhibited significantly greater white matter anatomical connectivity of corpus callosum-orbitofrontal cortex, which was positively correlated with body mass index and self-reported disinhibition of eating behavior, and lower white matter anatomical connectivity of corpus callosum-prefrontal cortex, which was significantly negatively correlated with craving for high-calorie food cues. The findings show that alterations in white matter anatomical connectivity between corpus callosum and frontal regions involved in reward and executive control are associated with abnormal eating behaviors.

Brain energetics and glucose transport in metabolic diseases: role in neurodegeneration

OBJECTIVES

Neurons and glial cells are the main functional and structural elements of the brain, and the former depends on the latter for their nutritional, functional and structural organization, as well as for their energy maintenance.

METHODS

Glucose is the main metabolic source that fulfills energetic demands, either by direct anaplerosis or through its conversion to metabolic intermediates. Development of some neurodegenerative diseases have been related with modifications in the expression and/or function of glial glucose transporters, which might cause physiological and/or pathological disturbances of brain metabolism. In the present contribution, we summarized the experimental findings that describe the exquisite adjustment in expression and function of glial glucose transporters from physiologic to pathologic metabolism, and its relevance to neurodegenerative diseases.

RESULTS

A exhaustive literature review was done in order to gain insight into the role of brain energetics in neurodegenerative disease. This study made evident a critical involvement of glucose transporters and thus brain energetics in the development of neurodegenerative diseases.

DISCUSSION

An exquisite adjustment in the expression and function of glial glucose transporters from physiologic to pathologic metabolism is a biochemical signature of neurodegenerative diseases.

Obesity paradox in older sarcopenic adults - a delay in aging: A systematic review and meta-analysis

The prognostic significance of obesity in sarcopenic adults is controversial. This systematic review and meta-analysis aimed to investigate the effect of additional obesity on health outcomes in sarcopenia. MEDLINE, EMBASE, Scopus and CENTRAL were systematically searched for studies to compare health outcomes of adults with sarcopenic obesity (SO) to those of sarcopenic non-obese (SNO) adults. We also considered the methods of assessing obesity. Of 15060 records screened, 65 papers were included (100612 participants). Older community-dwelling SO adults had 15% lower mortality risk than the SNO group (hazard ratio, HR: 0.85, 95% confidence interval 0.76, 0.94) even when obesity was assessed by measurement of body composition. Additionally, meta-regression analysis revealed a significant negative linear correlation between the age and the HR of all-cause mortality in SO vs. SNO community-dwelling adults, but not in severely ill patients. Compared with SNO, SO patients presented lower physical performance, higher risk for metabolic syndrome, but similar cognitive function, risk of falls and cardiovascular diseases. Age-related obesity, SO and later fat loss leading to SNO represent consecutive phases of biological aging. Additional obesity could worsen the health state in sarcopenia, but above 65 years SO represents a biologically earlier phase with longer life expectancy than SNO.

Neurohormonal response patterns to hunger, satiation, and postprandial fullness in normal weight, anorexia nervosa, and obesity

BACKGROUND

Food intake is regulated by homeostatic and hedonic systems that interact in a complex neuro-hormonal network. Dysregulation in energy intake can lead to obesity (OB) or anorexia nervosa (AN). However, little is known about the neurohormonal response patterns to food intake in normal weight (NW), OB, and AN.

MATERIAL & METHODS

During an ad libitum nutrient drink (Ensure®) test (NDT), participants underwent three pseudo-continuous arterial spin labeling (pCASL) MRI scans. The first scan was performed before starting the NDT after a > 12 h overnight fast (Hunger), the second after reaching maximal fullness (Satiation), and the third 30-min after satiation (postprandial fullness). We measured blood levels of ghrelin, cholecystokinin (CCK), glucagon-like peptide (GLP-1), and peptide YY (PYY) with every pCASL-MRI scan. Semiquantitative cerebral blood flow (CBF) maps in mL/100 gr brain/min were calculated and normalized (nCBF) with the CBF in the frontoparietal white matter. The hypothalamus (HT), nucleus accumbens [NAc] and dorsal striatum [DS] were selected as regions of interest (ROIs).

RESULTS

A total of 53 participants, 7 with AN, 17 with NW (body-mass index [BMI] 18.5-24.9 kg/m2 ), and 29 with OB (BMI ≥30 kg/m2 ) completed the study. The NW group had a progressive decrease in all five ROIs during the three stages of food intake (hunger, satiation, and post-prandial fullness). In contrast, participants with OB showed a minimal change from hunger to postprandial fullness in all five ROIs. The AN group had a sustained nCBF in the HT and DS, from hunger to satiation, with a subsequent decrease in nCBF from satiation to postprandial fullness. All three groups had similar hormonal response patterns with a decrease in ghrelin, an increase in GLP-1 and PYY, and no change in CCK.

CONCLUSION

Conditions of regulated (NW) and dysregulated (OB and AN) energy intake are associated with distinctive neurohormonal activity patterns in response to hunger, satiation, and postprandial fullness.

Associations between adiposity and white matter hyperintensities: Cross-sectional and longitudinal analyses of 34,653 participants

OBJECTIVES

White matter hyperintensities (WMH) increase the risk of stroke and cognitive impairment. This study aims to determine the cross-sectional and longitudinal associations between adiposity and WMH.

METHODS

Participants were enrolled from the UK Biobank cohort. Associations of concurrent, past, and changes in overall and central adiposity with WMH were investigated by linear and nonlinear regression models. The association of longitudinal adiposity and WMH volume changes was determined by a linear mixed model. Mediation analysis investigated the potential mediating effect of blood pressure.

RESULTS

In 34,653 participants with available adiposity measures and imaging data, the concurrent obese group had a 25.3% (β [95% CI] = 0.253 [0.222-0.284]) higher WMH volume than the ideal weight group. Increment in all adiposity measures was associated with a higher WMH volume. Among them, waist circumference demonstrated the strongest effect (β [95% CI] = 0.113 [0.101-0.125]). Past adiposity also demonstrated similar effects. Among the subset of 2664 participants with available WMH follow-up data, adiposity measures were predictive of WMH change. Regarding changes of adiposity, compared with ideal weight stable group, those who turned from ideal weight to overweight/obese had a 8.1% higher WMH volume (β [95% CI] = 0.081 [0.039-0.123]), while participants who turned from overweight/obese to ideal weight demonstrated no significant WMH volume change. Blood pressure partly meditates the associations between adiposity and WMH.

CONCLUSIONS

Both concurrent and past adiposity were associated with a higher WMH volume. The detrimental effects of adiposity on WMH occurred throughout midlife and in the elderly and may still exist after changes in obesity status.

Dynamical alterations of brain function and gut microbiome in weight loss

Objective

Intermittent energy restriction (IER) is an effective weight loss strategy. However, little is known about the dynamic effects of IER on the brain-gut-microbiome axis.

Methods

In this study, a total of 25 obese individuals successfully lost weight after a 2-month IER intervention. FMRI was used to determine the activity of brain regions. Metagenomic sequencing was performed to identify differentially abundant gut microbes and pathways in from fecal samples.

Results

Our results showed that IER longitudinally reduced the activity of obese-related brain regions at different timepoints, including the inferior frontal orbital gyrus in the cognitive control circuit, the putamen in the emotion and learning circuit, and the anterior cingulate cortex in the sensory circuit. IER longitudinally reduced E. coli abundance across multiple timepoints while elevating the abundance of obesity-related Faecalibacterium prausnitzii, Parabacteroides distasonis, and Bacterokles uniformis. Correlation analysis revealed longitudinally correlations between gut bacteria abundance alterations and brain activity changes.

Conclusions

There was dynamical alteration of BGM axis (the communication of E. coli with specific brain regions) during the weight loss under the IER.

The interaction of obesity with susceptible gene polymorphisms in the relationship with mild cognitive impairment

Mild cognitive impairment (MCI) in the elderly is threatening the mental health of the elderly, and the interaction of some factors is worth exploring. This study aims to explore the interactions of obesity and gene polymorphisms in the relationship with MCI. A total of 2555 community resident dwellings include 444 participants who met MCI criteria recruited from the Ningxia province of China. Fourteen MCI-susceptible single nucleotide polymorphisms were detected using a high-throughput mass spectrometer. The interaction was examined by performing the multifactor dimensionality reduction model and unconditional logistic regression model. Logistic regression showed that obesity (OR = 1.42, 95%CI: 1.04-1.94), rs2075650G allele carrying (OR = 17.95, 95%CI: 1.32-244.95), rs11556505T allele carrying (OR = 0.06, 95%CI: 0.01-0.87) were statistically associated with MCI. Multifactor dimensionality reduction analysis showed a strong antagonistic effect between obesity and rs4402960 (Interaction dendrogram between obesity and rs4402960 is red) and a weak synergy effect on rs7901695 (Interaction dendrogram between obesity and rs7901695 is green). The hierarchical analysis showed obesity is a risk factor for MCI in the non-rs4402960T allele carrier group (OR = 1.55, 95%CI: 1.02-2.35). This study found that obesity is an independent risk factor for MCI, and the interactions with MCI-susceptible gene polymorphisms suggest a possible precision preventive intervention program should be developed to reduce the risk of MCI among individuals with obesity in the community.

Greater socioenvironmental risk factors and higher chronic pain stage are associated with thinner bilateral temporal lobes

INTRODUCTION

Previous research indicates ethnic/race group differences in pain and neurodegenerative diseases. Accounting for socioenvironmental factors reduces ethnic/race group differences in clinical and experimental pain. In the current study sample, we previously reported that in individuals with knee pain, ethnic/race group differences were observed in bilateral temporal lobe thickness, areas of the brain associated with risk for Alzheimer's disease, and related dementias. The purpose of the study was to determine if socioenvironmental factors reduce or account for previously observed ethnic/race group differences and explore if a combined effect of socioenvironmental risk and chronic pain severity on temporal lobe cortices is evident.

METHODS

Consistent with the prior study, the sample was comprised of 147 adults (95 women, 52 men), 45-85 years of age, who self-identified as non-Hispanic Black (n = 72) and non-Hispanic White (n = 75), with knee pain with/at risk for osteoarthritis. Measures included demographics, health history, pain questionnaires, cognitive screening, body mass index, individual- and community-level socioenvironmental factors (education, income, household size, marital and insurance status, and area deprivation index), and brain imaging. We computed a summative socioenvironmental risk index.

RESULTS

Regression analyses showed that with the inclusion of socioenvironmental factors, the model was significant (p < .001), and sociodemographic (ethnic/race) group differences were not significant (p = .118). Additionally, findings revealed an additive stress load pattern indicating thinner temporal lobe cortices with greater socioenvironmental risk and chronic pain severity (p = .048).

IMPLICATIONS

Although individual socioenvironmental factors were not independent predictors, when collectively combined in models, ethnic/race group differences in bilateral temporal lobe structures were not replicated. Further, combined socioenvironmental risk factors and higher chronic pain severity were associated with thinner bilateral temporal lobes.

SH2B1 Tunes Hippocampal ERK Signaling to Influence Fluid Intelligence in Humans and Mice

Fluid intelligence is a cognitive domain that encompasses general reasoning, pattern recognition, and problem-solving abilities independent of task-specific experience. Understanding its genetic and neural underpinnings is critical yet challenging for predicting human development, lifelong health, and well-being. One approach to address this challenge is to map the network of correlations between intelligence and other constructs. In the current study, we performed a genome-wide association study using fluid intelligence quotient scores from the UK Biobank to explore the genetic architecture of the associations between obesity risk and fluid intelligence. Our results revealed novel common genetic loci (SH2B1, TUFM, ATP2A1, and FOXO3) underlying the association between fluid intelligence and body metabolism. Surprisingly, we demonstrated that SH2B1 variation influenced fluid intelligence independently of its effects on metabolism but partially mediated its association with bilateral hippocampal volume. Consistently, selective genetic ablation of Sh2b1 in the mouse hippocampus, particularly in inhibitory neurons, but not in excitatory neurons, significantly impaired working memory, short-term novel object recognition memory, and behavioral flexibility, but not spatial learning and memory, mirroring the human intellectual performance. Single-cell genetic profiling of Sh2B1-regulated molecular pathways revealed that Sh2b1 deletion resulted in aberrantly enhanced extracellular signal-regulated kinase (ERK) signaling, whereas pharmacological inhibition of ERK signaling reversed the associated behavioral impairment. Our cross-species study thus provides unprecedented insight into the role of SH2B1 in fluid intelligence and has implications for understanding the genetic and neural underpinnings of lifelong mental health and well-being.

The complex relationship between obesity and neurodegenerative diseases: an updated review

Obesity is a global epidemic, affecting roughly 30% of the world's population and predicted to rise. This disease results from genetic, behavioral, societal, and environmental factors, leading to excessive fat accumulation, due to insufficient energy expenditure. The adipose tissue, once seen as a simple storage depot, is now recognized as a complex organ with various functions, including hormone regulation and modulation of metabolism, inflammation, and homeostasis. Obesity is associated with a low-grade inflammatory state and has been linked to neurodegenerative diseases like multiple sclerosis (MS), Alzheimer's (AD), and Parkinson's (PD). Mechanistically, reduced adipose expandability leads to hypertrophic adipocytes, triggering inflammation, insulin and leptin resistance, blood-brain barrier disruption, altered brain metabolism, neuronal inflammation, brain atrophy, and cognitive decline. Obesity impacts neurodegenerative disorders through shared underlying mechanisms, underscoring its potential as a modifiable risk factor for these diseases. Nevertheless, further research is needed to fully grasp the intricate connections between obesity and neurodegeneration. Collaborative efforts in this field hold promise for innovative strategies to address this complex relationship and develop effective prevention and treatment methods, which also includes specific diets and physical activities, ultimately improving quality of life and health.

Physiological Mechanisms Inherent to Diabetes Involved in the Development of Dementia: Alzheimer's Disease

Type 2 diabetes mellitus (T2D) is a metabolic disease reaching pandemic levels worldwide. In parallel, Alzheimer's disease (AD) and vascular dementia (VaD) are the two leading causes of dementia in an increasingly long-living Western society. Numerous epidemiological studies support the role of T2D as a risk factor for the development of dementia. However, few basic science studies have focused on the possible mechanisms involved in this relationship. On the other hand, this review of the literature also aims to explore the relationship between T2D, AD and VaD. The data found show that there are several alterations in the central nervous system that may be promoting the development of T2D. In addition, there are some mechanisms by which T2D may contribute to the development of neurodegenerative diseases such as AD or VaD.

Cardiovascular risk factors in secondary progressive multiple sclerosis: A cross-sectional analysis from the MS-STAT2 randomized controlled trial

BACKGROUND AND PURPOSE

There is increasing evidence that cardiovascular risk (CVR) contributes to disability progression in multiple sclerosis (MS). CVR is particularly prevalent in secondary progressive MS (SPMS) and can be quantified through validated composite CVR scores. The aim was to examine the cross-sectional relationships between excess modifiable CVR, whole and regional brain atrophy on magnetic resonance imaging, and disability in patients with SPMS.

METHODS

Participants had SPMS, and data were collected at enrolment into the MS-STAT2 trial. Composite CVR scores were calculated using the QRISK3 software. Prematurely achieved CVR due to modifiable risk factors was expressed as QRISK3 premature CVR, derived through reference to the normative QRISK3 dataset and expressed in years. Associations were determined with multiple linear regressions.

RESULTS

For the 218 participants, mean age was 54 years and median Expanded Disability Status Scale was 6.0. Each additional year of prematurely achieved CVR was associated with a 2.7 mL (beta coefficient; 95% confidence interval 0.8-4.7; p = 0.006) smaller normalized whole brain volume. The strongest relationship was seen for the cortical grey matter (beta coefficient 1.6 mL per year; 95% confidence interval 0.5-2.7; p = 0.003), and associations were also found with poorer verbal working memory performance. Body mass index demonstrated the strongest relationships with normalized brain volumes, whilst serum lipid ratios demonstrated strong relationships with verbal and visuospatial working memory performance.

CONCLUSIONS

Prematurely achieved CVR is associated with lower normalized brain volumes in SPMS. Future longitudinal analyses of this clinical trial dataset will be important to determine whether CVR predicts future disease worsening.

Brain disease research based on functional magnetic resonance imaging data and machine learning: a review

Brain diseases, including neurodegenerative diseases and neuropsychiatric diseases, have long plagued the lives of the affected populations and caused a huge burden on public health. Functional magnetic resonance imaging (fMRI) is an excellent neuroimaging technology for measuring brain activity, which provides new insight for clinicians to help diagnose brain diseases. In recent years, machine learning methods have displayed superior performance in diagnosing brain diseases compared to conventional methods, attracting great attention from researchers. This paper reviews the representative research of machine learning methods in brain disease diagnosis based on fMRI data in the recent three years, focusing on the most frequent four active brain disease studies, including Alzheimer's disease/mild cognitive impairment, autism spectrum disorders, schizophrenia, and Parkinson's disease. We summarize these 55 articles from multiple perspectives, including the effect of the size of subjects, extracted features, feature selection methods, classification models, validation methods, and corresponding accuracies. Finally, we analyze these articles and introduce future research directions to provide neuroimaging scientists and researchers in the interdisciplinary fields of computing and medicine with new ideas for AI-aided brain disease diagnosis.

Higher body weight-dependent neural activation during reward processing

Obesity is associated with alterations in brain structure and function, particularly in areas related to reward processing. Although brain structural investigations have demonstrated a continuous association between higher body weight and reduced gray matter in well-powered samples, functional neuroimaging studies have typically only contrasted individuals from the normal weight and obese body mass index (BMI) ranges with modest sample sizes. It remains unclear, whether the commonly found hyperresponsiveness of the reward circuit can (a) be replicated in well-powered studies and (b) be found as a function of higher body weight even below the threshold of clinical obesity. 383 adults across the weight spectrum underwent functional magnetic resonance imaging during a common card-guessing paradigm simulating monetary reward. Multiple regression was used to investigate the association of BMI and neural activation in the reward circuit. In addition, a one-way ANOVA model comparing three weight groups (normal weight, overweight, obese) was calculated. Higher BMI was associated with higher reward response in the bilateral insula. This association could no longer be found when participants with obesity were excluded from the analysis. The ANOVA revealed higher activation in obese vs. lean, but no difference between lean and overweight participants. The overactivation of reward-related brain areas in obesity is a consistent finding that can be replicated in large samples. In contrast to brain structural aberrations associated with higher body weight, the neurofunctional underpinnings of reward processing in the insula appear to be more pronounced in the higher body weight range.

Assessing volumetric brain differences in migraine and depression patients: a UK Biobank study

BACKGROUND

Migraine and depression are two of the most common and debilitating conditions. From a clinical perspective, they are mostly prevalent in women and manifest a partial overlapping symptomatology. Despite the high level of comorbidity, previous studies hardly investigated possible common patterns in brain volumetric differences compared to healthy subjects. Therefore, the current study investigates and compares the volumetric difference patterns in sub-cortical regions between participants with migraine or depression in comparison to healthy controls.

METHODS

The study included data from 43 930 participants of the large UK Biobank cohort. Using official ICD10 diagnosis, we selected 712 participants with migraine, 1 853 with depression and 23 942 healthy controls. We estimated mean volumetric difference between the groups for the different sub-cortical brain regions using generalized linear regression models, conditioning the model within the levels of BMI, age, sex, ethnical background, diastolic blood pressure, current tobacco smoking, alcohol intake frequency, Assessment Centre, Indices of Multiple Deprivation, comorbidities and total brain volume.

RESULTS

We detected larger overall volume of the caudate (mean difference: 66, 95% CI [-3, 135]) and of the thalamus (mean difference: 103 mm³, 95% CI [-2, 208]) in migraineurs than healthy controls. We also observed that individuals with depression appear to have also larger overall (mean difference: 47 mm³, 95% CI [-7, 100]) and gray matter (mean difference: 49 mm³, 95% CI [2, 95]) putamen volumes than healthy controls, as well as larger amygdala volume (mean difference: 17 mm³, 95% CI [-7, 40]).

CONCLUSION

Migraineurs manifested larger overall volumes at the level of the nucleus caudate and of the thalamus, which might imply abnormal pain modulation and increased migraine susceptibility. Larger amygdala and putamen volumes in participants with depression than controls might be due to increased neuronal activity in these regions.

Brain alterations associated with overweight evaluated by body mass index or body fat index in an elderly population: the PROOF study

Background/objectives

Obesity is a complex health issue in which the brain plays a role yet to be determined, especially in the elderly. Indeed, in the ageing population, the balance between fat and lean mass is different; thus, the co-influence between the brain and obesity may differ between the elderly and younger subjects. Our main goal is thus to explore the relationship between the brain and obesity using two different approaches to measure obesity: body mass index (BMI) and an index centred on fat mass, the body fat index (BFI).

Subjects/methods

Among the 1,011 subjects of the PROOF population, 273 subjects aged 75 years underwent 3D magnetic resonance imaging as well as dual-energy X-ray absorptiometry to assess fat mass. Voxel-based morphometry was used to explore the local differences in brain volume with obesity.

Results

Higher BMI and BFI were associated with higher grey matter (GM) volume in the left cerebellum. Higher BMI and BFI were mainly associated with higher white matter volume in the left and right cerebellum and near the right medial orbital gyrus. Higher BMI was also associated with higher GM volume in the brainstem, whereas higher BFI was associated with higher GM volume in the left middle temporal gyrus. No decrease in white matter was associated with BMI or BFI.

Conclusion

In the elderly, the relationship between the brain and obesity does not depend on the marker of obesity. Supra-tentorial brain structures seem to be slightly associated with obesity, whereas the cerebellum seems to be one of the key structures related to obesity.

Machine learning model to predict obesity using gut metabolite and brain microstructure data

A growing body of preclinical and clinical literature suggests that brain-gut-microbiota interactions may contribute to obesity pathogenesis. In this study, we use a machine learning approach to leverage the enormous amount of microstructural neuroimaging and fecal metabolomic data to better understand key drivers of the obese compared to overweight phenotype. Our findings reveal that although gut-derived factors play a role in this distinction, it is primarily brain-directed changes that differentiate obese from overweight individuals. Of the key gut metabolites that emerged from our model, many are likely at least in part derived or influenced by the gut-microbiota, including some amino-acid derivatives. Remarkably, key regions outside of the central nervous system extended reward network emerged as important differentiators, suggesting a role for previously unexplored neural pathways in the pathogenesis of obesity.

Sex-specific relationships between obesity, physical activity, and gray and white matter volume in cognitively unimpaired older adults

Independently, obesity and physical activity (PA) influence cerebral structure in aging, yet their interaction has not been investigated. We examined sex differences in the relationships among PA, obesity, and cerebral structure in aging with 340 participants who completed magnetic resonance imaging (MRI) acquisition to quantify grey matter volume (GMV) and white matter volume (WMV). Height and weight were measured to calculate body mass index (BMI). A PA questionnaire was used to estimate weekly Metabolic Equivalents. The relationships between BMI, PA, and their interaction on GMV Regions of Interest (ROIs) and WMV ROIs were examined. Increased BMI was associated with higher GMV in females, an inverse U relationship was found between PA and GMV in females, and the interaction indicated that regardless of BMI greater PA was associated with enhanced GMV. Males demonstrated an inverse U shape between BMI and GMV, and in males with high PA and had normal weight demonstrated greater GMV than normal weight low PA revealed by the interaction. WMV ROIs had a linear relationship with moderate PA in females, whereas in males, increased BMI was associated with lower WMV as well as a positive relationship with moderate PA and WMV. Males and females have unique relationships among GMV, PA and BMI, suggesting sex-aggregated analyses may lead to biased or non-significant results. These results suggest higher BMI, and PA are associated with increased GMV in females, uniquely different from males, highlighting the importance of sex-disaggregated models. Future work should include other imaging parameters, such as perfusion, to identify if these differences co-occur in the same regions as GMV.

Association between body mass index and subcortical volume in pre-adolescent children with autism spectrum disorder: An exploratory study

Conflicting associations exist between autism spectrum disorder (ASD) and subcortical brain volumes. This study assessed whether obesity might have a confounding influence on associations between ASD and brain subcortical volumes. A comprehensive investigation evaluating the relationship between ASD, obesity, and subcortical structure volumes was conducted. Data obtained included body mass index (BMI) and T1-weighted structural magnetic resonance images for children with and without ASD diagnoses from the Autism Brain Imaging Data Exchange database. Brain subcortical volumes were calculated using vol2Brain software. Hierarchical linear regression analyses were performed to explore the subcortical volumes similarly or differentially associated with BMI in children with or without ASD and examine association and interaction effects regarding ASD and subcortical volume impact on the Social Responsiveness Scale and Vineland Adaptive Behavior Scale (VABS) scores. Bilateral caudate nuclei were smaller in children with ASD than in control participants. Significant interactions were observed between ASD diagnosis and BMI regarding the left caudate, right and left putamen, and right and left ventral diencephalon (DC) volumes (β = -0.384, p = 0.010; β = -0.336, p = 0.030; β = -0.317, p = 0.040; β = 0.322, p = 0.010; β = 0.295, p = 0.021, respectively) and between ASD diagnosis and right and left ventral DC volumes regarding the VABS scores (β = 0.434, p = 0.014; β = 0.495, p = 0.007, respectively). However, each subcortical structure volume included in the ventral DC area could not be measured separately. The results identified subcortical volumes differentially associated with obesity in children with ASD compared with typically developing peers. BMI may need to be considered an important confounder in future research examining brain subcortical volumes within ASD.

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.

The relationship between fat mass and obesity associated gene polymorphism rs9939609 and resting cerebral blood flow in a midlife sample with overweight and obesity

Background

The single nucleotide polymorphism (SNP) rs9939609 in the fat mass and obesity associated fat mass and obesity associated gene (FTO) gene has been linked with increased BMI in adults. Higher BMI has been associated with poor brain health and may exert deleterious effects on neurocognitive health through cerebral hypoperfusion. However, it is unclear if there is a relationship between the FTO genotype and cerebral perfusion, or whether FTO genotype moderates the effects of weight loss on cerebral perfusion. Using data from a randomized controlled behavioral weight loss trial in adults with overweight and obesity, we tested (1) whether carriers of the A allele for FTO rs9939609 demonstrate different patterns of resting cerebral blood flow (rCBF) compared to T carriers, and (2) whether the FTO genotype moderates the effects of weight loss on rCBF. We hypothesized that carriers of the A allele would exhibit lower resting CBF in frontal brain areas compared to T/T homozygotes at baseline, and that intervention-induced weight loss may partially remediate these differences.

Methods and results

One hundred and five adults (75.2% female, mean age 44.9 years) with overweight or obesity were included in the analyses. These participants represent a subsample of participants in a larger randomized controlled trial (NCT01500356). A resting pseudo-continuous arterial spin labeling (pCASL) scan was acquired to examine rCBF. Age, sex, and BMI were included as covariates. At baseline, A carriers had greater rCBF in a diffuse cluster extending into the brainstem, motor cortex, and occipital lobe, but lower perfusion in the temporal lobe. We found no evidence that FTO moderated the effect of the intervention group assignment on rCBF changes.

Conclusion

Overall, these results indicate that (a) individual variation in rCBF within a sample with overweight and obesity may be attributed to a common FTO variant, but (b) a weight loss intervention is effective at increasing rCBF, regardless of FTO genotype.

Functional Relationship between Inhibitory Control, Cognitive Flexibility, Psychomotor Speed and Obesity

In the last decades, it has been proposed that executive functions may be particularly vulnerable to weight-related issues. However, evidence on the matter is mixed, especially when the effects of sociodemographic variables are weighted. Thus, the current study aimed at further examining the relationship between executive functions and obesity. To this aim, we compared treatment-seeking overweight, obese, and morbidly obese patients with normal-weight control participants. We examined general executive functioning (Frontal Assessment Battery−15) and different executive subdomains (e.g., inhibitory control, verbal fluency, and psychomotor speed) in a clinical sample including 208 outpatients with different degrees of BMI (52 overweight, BMI 25−30, M age = 34.38; 76 obese, BMI 30−40, M age = 38.00; 80 morbidly obese, BMI > 40, M age = 36.20). Ninety-six normal-weight subjects served as controls. No difference on executive scores was detected when obese patients were compared with over- or normal-weight subjects. Morbidly obese patients reported lower performance on executive scores than obese, overweight, and normal-weight subjects. Between-group difference emerged also when relevant covariates were taken into account. Our results support the view that morbid obesity is associated with lower executive performance, also considering the critical role exerted by sociodemographic (i.e., sex, age, and education) variables. Our results support the view that executive functioning should be accounted into the management of the obese patient because of non-negligible clinical relevance in diagnostic, therapeutic, and prognostic terms.

Neuroinflammatory responses following zinc or branched-chain amino acids supplementation in obese rats

The excessive production of pro-inflammatory mediators, characteristic of obesity, leads to neuroinflammation. Zinc (Zn) and the branched-chain amino acids (BCAA) are supplements known for their immunomodulatory properties. Our goal was to evaluate if Zn or BCAA supplementation can affect long-term recognition memory and neuroinflammatory parameters of obese rats after a high-fat diet (HFD). Three-month-old Wistar rats were divided into six groups: Standard diet (SD) + vehicle; SD + Zn; SD + BCAA; High-fat diet (HFD) + vehicle; HFD + Zn; and HFD + BCAA. Diets were administrated for 19 weeks, Zn (1,2 mg/kg/day) or BCAA (750 mg/kg/day) supplementation was conducted in the last 4 weeks. Long-term recognition memory was evaluated by the novel object recognition test. IL-1β immunoreactivity in the cortex and hippocampus, and IL-6 levels in the cortex tissue were assessed. Astrogliosis were evaluated through GFAP + cell count and morphological analysis (Sholl Method). Zn supplementation improved object recognition memory in HFD-fed rats, which was not observed following BCAA supplementation. The levels of IL-6 in the cerebral cortex were higher after HFD, which was not diminished after neither supplementation. Obesity also led to increased IL-1β immunoreactivity in the cerebral cortex and hippocampus, which was reduced by Zn. BCAA supplementation also diminished IL-1β immunoreactivity, but only in the hippocampus. We also showed that astrocyte reactivity caused by HFD is area-dependent, being the cerebral cortex more susceptible to the diet. Even though BCAA and Zn can affect IL-1β immunoreactivity and astrocyte morphology, only Zn improved memory. Future studies are needed to clarify the pathways by which Zn improves cognition in obesity.

Food cue reactivity: Neurobiological and behavioral underpinnings

The modern obesogenic environment contains an abundance of food cues (e.g., sight, smell of food) as well cues that are associated with food through learning and memory processes. Food cue exposure can lead to food seeking and excessive consumption in otherwise food-sated individuals, and a high level of food cue responsivity is a risk factor for overweight and obesity. Similar food cue responses are observed in experimental rodent models, and these models are therefore useful for mechanistically identifying the neural circuits mediating food cue responsivity. This review draws from both experimental rodent models and human data to characterize the behavioral and biological processes through which food-associated stimuli contribute to overeating and weight gain. Two rodent models are emphasized - cue-potentiated feeding and Pavlovian-instrumental transfer - that provide insight in the neural circuits and peptide systems underlying food cue responsivity. Data from humans are highlighted that reveal physiological, psychological, and neural mechanisms that connect food cue responsivity with overeating and weight gain. The collective literature identifies connections between heightened food cue responsivity and obesity in both rodents and humans, and identifies underlying brain regions (nucleus accumbens, amygdala, orbitofrontal cortex, hippocampus) and endocrine systems (ghrelin) that regulate food cue responsivity in both species. These species similarities are encouraging for the possibility of mechanistic rodent model research and further human research leading to novel treatments for excessive food cue responsivity in humans.

Hyperinsulinemia alters insulin receptor presentation and internalization in brain microvascular endothelial cells

Insulin receptors are internalized by endothelial cells to facilitate their physiological processes; however, the impact of hyperinsulinemia in brain endothelial cells is not known. Thus, the aim of this study was to elucidate the impact hyperinsulinemia plays on insulin receptor internalization through changes in phosphorylation, as well as the potential impact of protein tyrosine phosphatase 1B (PTP1B). Hippocampal microvessels were isolated from high-fat diet fed mice and assessed for insulin signaling activation, a process known to be involved with receptor internalization. Surface insulin receptors in brain microvascular endothelial cells were labelled to assess the role hyperinsulinemia plays on receptor internalization in response to stimulation, with and without the PTP1B antagonist, Claramine. Our results indicated that insulin receptor levels increased in tandem with decreased receptor signaling in the high-fat diet mouse microvessels. Insulin receptors of cells subjected to hyperinsulinemic treatment demonstrate splice variation towards decreased IR-A mRNA expression and demonstrate a higher membrane-localized proportion. This corresponded with decreased autophosphorylation at sites critical for receptor internalization and signaling. Claramine restored signaling and receptor internalization in cells treated with hyperinsulinemia. In conclusion, hyperinsulinemia impacts brain microvascular endothelial cell insulin receptor signaling and internalization, likely via alternative splicing and increased negative feedback from PTP1B.

Functional Magnetic Resonance Imaging and Obesity-Novel Ways to Seen the Unseen

Obesity remains a pandemic of the 21st century. While there are many causes of obesity and potential treatments that are currently known, source data indicate that the number of patients is constantly increasing. Neural mechanisms have become the subject of research and there has been an introduction of functional magnetic resonance imaging in obesity-associated altered neural signaling. Functional magnetic resonance imaging has been established as the gold standard in the assessment of neuronal functions related to nutrition. Thanks to this, it has become possible to delineate those regions of the brain that show altered activity in obese individuals. An integrative review of the literature was conducted using the keywords ““functional neuroimaging” OR “functional magnetic resonance “OR “fmri” and “obesity” and “reward circuit and obesity” in PubMed and Google Scholar databases from 2017 through May 2022. Results in English and using functional magnetic resonance imaging to evaluate brain response to diet and food images were identified. The results from functional magnetic resonance imaging may help to identify relationships between neuronal mechanisms and causes of obesity. Furthermore, they may provide a substrate for etiology-based treatment and provide new opportunities for the development of obesity pharmacotherapy.

Effects of Obesity, Blood Pressure, and Blood Metabolic Biomarkers on Grey Matter Brain Healthcare Quotient: A Large Cohort Study of a Magnetic Resonance Imaging Brain Screening System in Japan

This study investigated the relationship between grey matter (GM) volume and blood biomarkers, blood pressure, and obesity. We aimed to elucidate lifestyle factors that promote GM volume loss. A total of 1799 participants underwent the brain dock as a medical checkup. Data regarding blood pressure, obesity measurements, and standard blood biomarkers were obtained. Further, brain magnetic resonance imaging (MRI), including high-resolution T1-weighted imaging, was performed. We calculated the grey matter brain healthcare quotient (GM-BHQ), which represents GM volume as a deviation value. After adjusting for confounding variables, multiple regression analysis revealed that body mass index (BMI) (b = −0.28, p < 0.001), gamma-glutamyltransferase (γ-GTP) (b = −0.01, p = 0.16), and fasting blood glucose (b = −0.02, p = 0.049) were significantly correlated with GM-BHQ. Although the current cross-sectional study cannot determine a cause-and-effect relationship, elevated BMI, γ-GTP, and fasting blood glucose could promote GM volume loss.

Role of Cardiovascular Risk Factors on the Association Between Physical Activity and Brain Integrity Markers in Older Adults

BACKGROUND AND OBJECTIVES

Physical activity has been associated with a decreased risk for dementia, but the mechanisms underlying this association remain to be determined. Our objective was to assess whether cardiovascular risk factors mediate the association between physical activity and brain integrity markers in older adults.

METHODS

At baseline, participants from the Age-Well study completed a physical activity questionnaire and underwent cardiovascular risk factors collection (systolic blood pressure, body mass index [BMI], current smoker status, and high-density lipoprotein cholesterol, total cholesterol, and insulin levels) and multimodal neuroimaging (structural MRI, diffusion MRI, FDG-PET, and florbetapir PET). Multiple regressions were conducted to assess the association among physical activity, cardiovascular risk factors, and neuroimaging. Mediation analyses were performed to test whether cardiovascular risk factors mediated the associations between physical activity and neuroimaging.

RESULTS

A total of 134 cognitively unimpaired older adults (≥65 years) were included. Higher physical activity was associated with higher gray matter (GM) volume (β = 0.174, p = 0.030) and cerebral glucose metabolism (β = 0.247, p = 0.019) but not with amyloid deposition or white matter integrity. Higher physical activity was associated with lower insulin level and BMI but not with the other cardiovascular risk factors. Lower insulin level and BMI were related to higher GM volume but not to cerebral glucose metabolism. When controlling for insulin level and BMI, the association between physical activity and cerebral glucose metabolism remained unchanged, while the association with GM volume was lost. When insulin level and BMI were entered in the same model, only BMI remained a significant predictor of GM volume. Mediation analyses confirmed that insulin level and BMI mediated the association between physical activity and GM volume. Analyses were replicated within Alzheimer disease-sensitive regions and results remained overall similar.

DISCUSSION

The association between physical activity and GM volume is mediated by changes in insulin level and BMI. In contrast, the association with cerebral glucose metabolism seems to be independent from cardiovascular risk factors. Older adults engaging in physical activity experience cardiovascular benefits through the maintenance of a lower BMI and insulin level, resulting in greater structural brain integrity. This study has implications for understanding how physical activity affects brain health and may help in developing strategies to prevent or delay age-related decline.

TRIAL REGISTRATION INFORMATION

EudraCT: 2016-002,441-36; IDRCB: 2016-A01767-44; ClinicalTrials.gov Identifier: NCT02977819.

Circulating neurofilament is linked with morbid obesity, renal function, and brain density

Neurofilament light chain (NfL) is a novel biomarker reflecting neuroaxonal damage and associates with brain atrophy, and glial fibrillary acidic protein (GFAP) is a marker of astrocytic activation, associated with several neurodegenerative diseases. Since obesity is associated with increased risk for several neurodegenerative disorders, we hypothesized that circulating NfL and GFAP levels could reflect neuronal damage in obese patients. 28 morbidly obese and 18 lean subjects were studied with voxel based morphometry (VBM) MRI to assess gray and white matter densities. Serum NfL and GFAP levels were determined with single-molecule array. Obese subjects were re-studied 6 months after bariatric surgery. Morbidly obese subjects had lower absolute concentrations of circulating NfL and GFAP compared to lean individuals. Following bariatric surgery-induced weight loss, both these levels increased. Both at baseline and after weight loss, circulating NfL and GFAP values correlated inversely with eGFR. Cross-sectionally, circulating NfL levels correlated inversely with gray matter (GM) density, and this association remained significant also when accounting for age and total eGFR. GFAP values did not correlate with GM density. Our data suggest that when determining circulating NfL and GFAP levels, eGFR should also be measured since renal function can affect these measurements. Despite the potential confounding effect of renal function on NfL measurement, NfL correlated inversely with gray matter density in this group of subjects with no identified neurological disorders, suggesting that circulating NfL level may be a feasible biomarker of cerebral function even in apparently neurologically healthy subjects.

The Association of Obesity and Cardiorespiratory Fitness in Relation to Cognitive Flexibility: An Event-Related Potential Study

This study investigates an association between obesity and cardiorespiratory fitness concerning their potential effects on cognitive flexibility in young adults from behavioral and neuroelectrical perspectives. Eligible young adults (N = 140, 18–25 years) were assigned into one of four groups, according to their status of obesity (i.e., body mass index) and cardiorespiratory fitness levels (i.e., estimated maximal oxygen uptake), namely, normal weight with high cardiorespiratory fitness (NH), obese with high cardiorespiratory fitness (OH), normal weight with low cardiorespiratory fitness (NL), and obese with low cardiorespiratory fitness (OL). The task-switching test was utilized, and its induced endogenous (P3) and exogenous (N1) event-related potential components were recorded. Concerning behavioral indices, the NH demonstrated superior behavioral performance across global switching and local switching of the task-switching test compared to individuals with lower cardiorespiratory fitness and obesity (i.e., NL, OH, and OL). Additionally, the OH demonstrated better performance than the OL during the heterogeneous condition. For neuroelectrical indices, the NH had larger mean P3 amplitudes during global and local switching than the other three groups. A larger N1 amplitude was also observed in the NH during local switching than in the OH group. The findings suggest that cardiorespiratory fitness has beneficial effects on cognitive flexibility, attentional resource allocation, and sensory evaluation in young adults. Furthermore, our research provided novel evidence showing that cardiorespiratory fitness might potentially alleviate the adverse effects of obesity on cognitive flexibility in young adults.

Obesity as a Risk Factor for Dementia and Alzheimer's Disease: The Role of Leptin

Obesity is a growing worldwide health problem, affecting many people due to excessive saturated fat consumption, lack of exercise, or a sedentary lifestyle. Leptin is an adipokine secreted by adipose tissue that increases in obesity and has central actions not only at the hypothalamic level but also in other regions and nuclei of the central nervous system (CNS) such as the cerebral cortex and hippocampus. These regions express the long form of leptin receptor LepRb, which is the unique leptin receptor capable of transmitting complete leptin signaling, and are the first regions to be affected by chronic neurocognitive deficits, such as mild cognitive impairment (MCI) and Alzheimer's Disease (AD). In this review, we discuss different leptin resistance mechanisms that could be implicated in increasing the risk of developing AD, as leptin resistance is frequently associated with obesity, which is a chronic low-grade inflammatory state, and obesity is considered a risk factor for AD. Key players of leptin resistance are SOCS3, PTP1B, and TCPTP whose signalling is related to inflammation and could be worsened in AD. However, some data are controversial, and it is necessary to further investigate the underlying mechanisms of the AD-causing pathological processes and how altered leptin signalling affects such processes.

Prenatal caffeine exposure: association with neurodevelopmental outcomes in 9- to 11-year-old children

BACKGROUND

Despite the widespread use of caffeine including consumption during pregnancy, the effect of prenatal caffeine exposure on child brain development and behavior is unclear.

METHODS

To address this, we used data from the Adolescent Brain and Cognitive Development Study (n = 11,875 children aged 9-11 years from 22 sites across the United States). We explored the associations between prenatal caffeine exposure and various developmental outcomes including birth outcomes, physical health, behavior problems, cognition, substance use and brain structure in children, and evaluated dose effects.

RESULTS

Among 9,978 children (4,745 females) who had valid data for prenatal caffeine exposure and whose mothers did not use drugs of abuse after knowing of pregnancy, 4,170 (41.79%) had no prenatal caffeine exposure, 2,292 (22.97%) had daily, 1,933 (19.37%) had weekly, and 1,583 (15.86%) had less than weekly exposures. Prenatal caffeine exposure including the widely recommended 'safe' dose was associated with greater externalizing problems, whereas greater BMI and soda consumption were only observed in children with high dose exposures (3+ per day). Notably, the effect size for association of externalizing problems with prenatal caffeine exposure was comparable with that reported for prenatal alcohol (The American Journal of Psychiatry, 177, 2020 and 1060) and prenatal cannabis (JAMA Psychiatry, 78, 2020 and 64) exposures from previous ABCD publications. Additionally, prenatal caffeine exposure was associated with brain structural changes that included greater posterior and lower frontal cortical thickness and altered parietooccipital sulcal depth.

CONCLUSIONS

The recommended 'safe' dose of caffeine during pregnancy should be carefully studied to assess whether the behavioral and brain correlates observed here are clinically relevant and determine whether it needs adjustment. Because of the high prevalence of caffeine use in the general population, studies on prenatal exposure to drugs of abuse should include prenatal caffeine use as a covariate.

Food-Approach Eating Behaviors and Brain Morphology: The Generation R Study

Food-approach eating behaviors are associated with an increased risk of developing overweight/obesity and binge-eating disorder, while obesity and binge-eating disorder have also been linked with altered brain morphology in adults. To understand these associations, we examined the association of food-approach eating behaviors during childhood with adolescents' brain morphology. The sample included 1,781 adolescents with assessments of eating behaviors at ages 4 and 10 years and brain imaging data at 13 years from a large, population-based cohort. Food approach eating behaviors (enjoyment of food, emotional overeating, and food responsiveness) were assessed using the Child Eating Behavior Questionnaire. Additionally, we assessed binge eating symptoms using two items from the Development and Well-Being Assessment at 13 years of age. Adolescents participated in an MRI procedure and measures of brain morphology, including cerebral white, cerebral gray and subcortical gray matter volumes, were extracted from T1-weighted images processed using FreeSurfer. Enjoyment of food and food responsiveness at the age of 4 and 10 years were positively associated with cerebral white matter and subcortical gray matter volumes at age 13 years (e.g., enjoyment of food at 4 years and cerebral white matter: β = 2.73, 95% CI 0.51, 4.91). Enjoyment of food and food responsiveness at 4 years of age, but not at 10 years, were associated with a larger cerebral gray matter volume at 13 years of age (e.g., enjoyment of food at 4 years: β = 0.24, 95% CI 0.03, 0.45). No statistically significant associations were found for emotional overeating at both ages and brain measurements at 13 years of age. post-hoc analyses showed no associations of food-approach eating behaviors with amygdala or hippocampus. Lastly, we did not observe significant associations of binge-eating symptoms with global brain measurements and a priori-defined regions of interest, including the right frontal operculum, insular and orbitofrontal cortex. Our findings support an association between food-approach eating behaviors, especially enjoyment of food and food responsiveness, and brain morphology in adolescence. Our findings add important knowledge to previous studies that were mostly conducted in adults, by suggesting that the eating behavior-brain link may be visible earlier in life. Further research is needed to determine causality.