A systematic review of diffusion tensor imaging studies in obesity

Association of physical function with connectivity in the sensorimotor and dorsal attention networks: why examining specific components of physical function matters

Declining physical function with aging is associated with structural and functional brain network organization. Gaining a greater understanding of network associations may be useful for targeting interventions that are designed to slow or prevent such decline. Our previous work demonstrated that the Short Physical Performance Battery (eSPPB) score and body mass index (BMI) exhibited a statistical interaction in their associations with connectivity in the sensorimotor cortex (SMN) and the dorsal attention network (DAN). The current study examined if components of the eSPPB have unique associations with these brain networks. Functional magnetic resonance imaging was performed on 192 participants in the BNET study, a longitudinal and observational trial of community-dwelling adults aged 70 or older. Functional brain networks were generated for resting state and during a motor imagery task. Regression analyses were performed between eSPPB component scores (gait speed, complex gait speed, static balance, and lower extremity strength) and BMI with SMN and DAN connectivity. Gait speed, complex gait speed, and lower extremity strength significantly interacted with BMI in their association with SMN at rest. Gait speed and complex gait speed were interacted with BMI in the DAN at rest while complex gait speed, static balance, and lower extremity strength interacted with BMI in the DAN during motor imagery. Results demonstrate that different components of physical function, such as balance or gait speed and BMI, are associated with unique aspects of brain network organization. Gaining a greater mechanistic understanding of the associations between low physical function, body mass, and brain physiology may lead to the development of treatments that not only target specific physical function limitations but also specific brain networks.

The effects of a six-month exercise intervention on white matter microstructure in older adults at risk for diabetes

Older adults with prediabetes or obesity (i.e., those at risk for diabetes) exhibit impaired structural brain networks. Given findings that resistance training (RT) can combat brain impairments in many populations, this study aimed to test the effects of this type of exercise on white matter microstructure in older adults at risk for diabetes. Seventeen community-dwelling older adults (mean age 67.8 ± 5.7, 52.9 % female) with prediabetes or obesity were randomly allocated to thrice weekly RT or balance and tone training (BAT; control group) for six months. Diffusion weighted imaging via a 3T scanner was used to assess changes in white matter parameters -fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) - over time. Participants in the RT group showed no significant changes in FA but had increased MD and RD in various regions related to cognitive function including the cingulate gyrus. Participants in the control group had both increased and decreased FA depending on the specific white matter tracts; increased FA was seen in areas related to motor coordination such as the middle cerebellar peduncle. The control group also exhibited decreased MD and RD in areas responsible for motor function (e.g., left anterior limb of the internal capsule). We conclude that both resistance and balance exercises result in changes in white matter microstructure albeit in divergent tracts that may be linked to the specific exercises performed.

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.

Causal Relationship between Aging and Anorexia Nervosa: A White-Matter-Microstructure-Mediated Mendelian Randomization Analysis

This study employed a two-step Mendelian randomization analysis to explore the causal relationship between telomere length, as a marker of aging, and anorexia nervosa and to evaluate the mediating role of changes in the white matter microstructure across different brain regions. We selected genetic variants associated with 675 diffusion magnetic resonance imaging phenotypes representing changes in brain white matter. F-statistics confirmed the validity of the instruments, ensuring robust causal inference. Sensitivity analyses, including heterogeneity tests, horizontal pleiotropy tests, and leave-one-out tests, validated the results. The results show that telomere length is significantly negatively correlated with anorexia nervosa in a unidirectional manner (p = 0.017). Additionally, changes in specific white matter structures, such as the internal capsule, corona radiata, posterior thalamic radiation, left cingulate gyrus, left longitudinal fasciculus, and left forceps minor (p < 0.05), were identified as mediators. These findings enhance our understanding of the neural mechanisms, underlying the exacerbation of anorexia nervosa with aging; emphasize the role of brain functional networks in disease progression; and provide potential biological targets for future therapeutic interventions.

Pathways explaining racial/ethnic and socio-economic disparities in brain white matter integrity outcomes in the UK Biobank study

Pathways explaining racial/ethnic and socio-economic status (SES) disparities in white matter integrity (WMI) reflecting brain health, remain underexplored, particularly in the UK population. We examined racial/ethnic and SES disparities in diffusion tensor brain magnetic resonance imaging (dMRI) markers, namely global and tract-specific mean fractional anisotropy (FA), and tested total, direct and indirect effects through lifestyle, health-related and cognition factors using a structural equations modeling approach among 36,184 UK Biobank participants aged 40-70 y at baseline assessment (47% men). Multiple linear regression models were conducted, testing independent associations of race/ethnicity, socio-economic and other downstream factors in relation to global mean FA, while stratifying by Alzheimer's Disease polygenic Risk Score (AD PRS) tertiles. Race (Non-White vs. White) and lower SES predicted poorer WMI (i.e. lower global mean FA) at follow-up, with racial/ethnic disparities in FAmean involving multiple pathways and SES playing a central role in those pathways. Mediational patterns differed across tract-specific FA outcomes, with SES-FAmean total effect being partially mediated (41% of total effect = indirect effect). Furthermore, the association of poor cognition with FAmean was markedly stronger in the two uppermost AD PRS tertiles compared to the lower tertile (T2 and T3: β±SE: -0.0009 ± 0.0001 vs. T1: β±SE: -0.0005 ± 0.0001, P < 0.001), independently of potentially confounding factors. Race and lower SES were generally important determinants of adverse WMI outcomes, with partial mediation of socio-economic disparities in global mean FA through lifestyle, health-related and cognition factors. The association of poor cognition with lower global mean FA was stronger at higher AD polygenic risk.

Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.

Opposite changes in morphometric similarity of medial reward and lateral non-reward orbitofrontal cortex circuits in obesity

Obesity has a profound impact on metabolic health thereby adversely affecting brain structure and function. However, the majority of previous studies used a single structural index to investigate the link between brain structure and body mass index (BMI), which hinders our understanding of structural covariance between regions in obesity. This study aimed to examine the relationship between macroscale cortical organization and BMI using novel morphometric similarity networks (MSNs). The individual MSNs were first constructed from individual eight multimodal cortical morphometric features between brain regions. Then the relationship between BMI and MSNs within the discovery sample of 434 participants was assessed. The key findings were further validated in an independent sample of 192 participants. We observed that the lateral non-reward orbitofrontal cortex (lOFC) exhibited decoupling (i.e., reduction in integration) in obesity, which was mainly manifested by its decoupling with the cognitive systems (i.e., DMN and FPN) while the medial reward orbitofrontal cortex (mOFC) showed de-differentiation (i.e., decrease in distinctiveness) in obesity, which was mainly represented by its de-differentiation with the cognitive and attention systems (i.e., DMN and VAN). Additionally, the lOFC showed de-differentiation with the visual system in obesity, while the mOFC showed decoupling with the visual system and hyper-coupling with the sensory-motor system in obesity. As an important first step in revealing the role of underlying structural covariance in body mass variability, the present study presents a novel mechanism that underlies the reward-control interaction imbalance in obesity, thus can inform future weight-management approaches.

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.

Diffusion tensor imaging findings in the hunger and satiety centers of the brain after bariatric surgery: a preliminary study

PURPOSE

To investigate the alterations in the diffusion tensor imaging (DTI) parameters measured in the hunger and satiety centers of the brain before and after bariatric surgery (BS) in morbidly obese patients.

METHODS

Fourty morbidly obese patients were evaluated before and after BS. Mean diffusivity (MD) and fractional anisotropy (FA) values were calculated from 14 related brain locations, and the DTI parameters were analyzed.

RESULTS

After the BS, the mean BMI of the patients decreased from 47.53 ± 5.21 to 31.48 ± 4.21. The MD and FA values in the all of the hunger and satiety centers was found statistically significant different in the pre-surgery period compared to the post-surgery period (for each; p-value < 0.001).

CONCLUSION

The FA and MD changes after BS may be attributed to reversible neuroinflammatory alterations in the hunger and satiety centers. Decreased MD and FA values after BS may be explained by the neuroplastic structural recovery in the related brain locations.

Interaction Between a High-Fat Diet and Tau Pathology in Mice: Implications for Alzheimer's Disease

BACKGROUND

Obesity is a modifiable risk factor for Alzheimer's disease (AD). However, its relation with tau pathology (i.e., aberrant tau protein behavior in tauopathies such as AD) has been inconclusive.

OBJECTIVE

This study investigated the interaction between a high-fat diet (HFD) and tau pathology in adult male mice.

METHODS

Transgenic mice overexpressing human P301S Tau (those with the pathology) and wild-type (WT) littermates were subjected to behavioral tests, functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and western blotting analysis to investigate the effects of prolonged HFD versus regular diet during adulthood.

RESULTS

HFD increased body weight in both WT and P301S mice but had minimal effect on blood glucose levels. The brain response to HFD was tau genotype-specific. WT mice exhibited decreased recognition memory and enhanced network connectivity in fMRI, while P301S mice exhibited white matter tract disorganization in DTI as the sole significant finding. The reduction of insulin receptor β, insulin downstream signaling, neuronal nuclear protein, CD68-positive phagocytic activity, and myelin basic protein level were confined to the cortex of WT mice. In contrast to P301S mice, WT mice showed significant changes in the tau protein and its phosphorylation levels along with increased soluble neurofilament light levels in the hippocampus.

CONCLUSIONS

HFD-induced brain dysfunction and pathological changes were blunted in mice with the pathology and more profound in healthy mice. Our findings highlight the need to consider this interaction between obesity and tau pathology when tailoring treatment strategies for AD and other tauopathies.

White Matter Integrity Abnormalities in Healthy Overweight Individuals Revealed by Whole Brain Meta-Analysis of Diffusion Tensor Imaging Studies

Objective

This study aimed to conduct a coordinate-based meta-analysis (CBMA) to investigate white matter (WM) abnormalities in healthy individuals with overweight or obesity.

Methods

A systematic literature search using Web of Science and PubMed datasets was performed. Original investigations that used diffusion tensor imaging (DTI) to explore fractional anisotropy (FA) differences between healthy overweight/obese individuals and normal weight controls were collected. The meta-analysis was conducted using the seed-based d mapping (SDM) software, employing stringent thresholds for significance. Sensitivity analyses and meta-regression analysis were also performed to examine the robustness of the results and explore potential associations with age and body mass index (BMI).

Results

The analysis included five studies comprising 232 overweight/obese individuals and 219 healthy normal weight controls. The findings showed that overweight/obese individuals exhibited reduced fractional anisotropy (FA) in specific regions, namely, the right superior longitudinal fasciculus (SLF), the splenium of the corpus callosum (CC), and the right median network, cingulum. Meta-regression analysis further revealed that these FA reductions were associated with age.

Conclusion

These findings provided insights into the potential impact of overweight/obesity on cognition, emotion, and neural functions and highlighted the significance of early prevention and intervention for overweight on the basis of neuroimaging.

Evaluation of the white matter integrity in morbidly obese patients before and after bariatric surgery; a diffusion tensor imaging study

PURPOSE

To investigate the difference in FA (Fractional anisotropy), ADC (Apparent diffusion coefficient), RD (Radial diffusivity) and AD (axial diffusivity) values of white matter (WM) tracts in morbidly obese subjects before and after bariatric surgery (BS).

MATERIALS AND METHODS

A group of thirty-nine morbidly obese subjects are evaluated before and 4-6 months after BS. ADC, FA, RD and AD values of 17 distinct neuroanatomic localizations are measured and DTI parameters are analyzed.

RESULTS

Following the BS, the patients' mean BMI decreased from 47.665.21 to 31.723.97. A significant difference is displayed between the pre-surgery and post-surgery FA values of SLF, SFOF, ALIC, fornix, ILF, CST, MCP (p = 0.010, p < 0.001, p = 0.048, p = 0.014, p = 0.012, p = 0.012, p = 0.040 respectively). Following BS, decrease in FA values in the mentioned areas are detected. ADC values obtained from MCP are significantly lower in the post-BS period compared to pre-BS period (p = 0.018). There was a statistically significant difference between the pre-surgery and post-surgery AD values of SLF, SFOF, ILF, ALIC, EC, CST, and MCP (p = 0.001, p = 0.022, p = 0.001, p = 0.011, p = 0.001, p = 0.000, p = 0.000, respectively). Following the BS, AD values of the SLF, SFOF, ILF, ALIC, EC, CST, and MCP are decreased. RD values measured from GCC are significantly lower in the post-BS period compared to pre-BS period (p = 0.008).

CONCLUSION

Our study supported the hypothesis of the BS-induced reversibility of the low-grade inflammation in WM tracts in the morbidly obese group following BS. Our DTI results may represent the subacute period findings of the reversal of low-grade inflammation after BS.

Multivariate resting-state functional connectomes predict and characterize obesity phenotypes

The univariate obesity-brain associations have been extensively explored, while little is known about the multivariate associations between obesity and resting-state functional connectivity. We therefore utilized machine learning and resting-state functional connectivity to develop and validate predictive models of 4 obesity phenotypes (i.e. body fat percentage, body mass index, waist circumference, and waist-height ratio) in 3 large neuroimaging datasets (n = 2,992). Preliminary evidence suggested that the resting-state functional connectomes effectively predicted obesity/weight status defined by each obesity phenotype with good generalizability to longitudinal and independent datasets. However, the differences between resting-state functional connectivity patterns characterizing different obesity phenotypes indicated that the obesity-brain associations varied according to the type of measure of obesity. The shared structure among resting-state functional connectivity patterns revealed reproducible neuroimaging biomarkers of obesity, primarily comprising the connectomes within the visual cortex and between the visual cortex and inferior parietal lobule, visual cortex and orbital gyrus, and amygdala and orbital gyrus, which further suggested that the dysfunctions in the perception, attention and value encoding of visual information (e.g. visual food cues) and abnormalities in the reward circuit may act as crucial neurobiological bases of obesity. The recruitment of multiple obesity phenotypes is indispensable in future studies seeking reproducible obesity-brain associations.

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.

Integrated multi-modal brain signatures predict sex-specific obesity status

Investigating sex as a biological variable is key to determine obesity manifestation and treatment response. Individual neuroimaging modalities have uncovered mechanisms related to obesity and altered ingestive behaviours. However, few, if any, studies have integrated data from multi-modal brain imaging to predict sex-specific brain signatures related to obesity. We used a data-driven approach to investigate how multi-modal MRI and clinical features predict a sex-specific signature of participants with high body mass index (overweight/obese) compared to non-obese body mass index in a sex-specific manner. A total of 78 high body mass index (55 female) and 105 non-obese body mass index (63 female) participants were enrolled in a cross-sectional study. All participants classified as high body mass index had a body mass index greater than 25 kg/m2 and non-obese body mass index had a body mass index between 19 and 20 kg/m2. Multi-modal neuroimaging (morphometry, functional resting-state MRI and diffusion-weighted scan), along with a battery of behavioural and clinical questionnaires were acquired, including measures of mood, early life adversity and altered ingestive behaviours. A Data Integration Analysis for Biomarker discovery using Latent Components was conducted to determine whether clinical features, brain morphometry, functional connectivity and anatomical connectivity could accurately differentiate participants stratified by obesity and sex. The derived models differentiated high body mass index against non-obese body mass index participants, and males with high body mass index against females with high body mass index obtaining balanced accuracies of 77 and 75%, respectively. Sex-specific differences within the cortico-basal-ganglia-thalamic-cortico loop, the choroid plexus-CSF system, salience, sensorimotor and default-mode networks were identified, and were associated with early life adversity, mental health quality and greater somatosensation. Results showed multi-modal brain signatures suggesting sex-specific cortical mechanisms underlying obesity, which fosters clinical implications for tailored obesity interventions based on sex.

Is adiposity associated with white matter microstructural health and intelligence differently in males and females?

OBJECTIVE

The role of vascular risk factors in age-related brain degeneration has long been the subject of intense study, but the role of obesity remains understudied. Given known sex differences in fat storage and usage, this study investigates sex differences in the association between adiposity and white matter microstructural integrity, an important early marker of brain degeneration.

METHODS

This study assesses the associations between adiposity (abdominal fat ratio and liver proton density fat fraction) and brain health (measures of intelligence and white matter microstructure using diffusion-tensor imaging [DTI]) in a group of UK Biobank participants.

RESULTS

This study finds that intelligence and DTI metrics are indeed associated with adiposity differently in males and females. These sex differences are distinct from those in the associations of DTI metrics with age and blood pressure.

CONCLUSIONS

Taken together, these findings suggest that there are inherent sex-driven differences in how brain health is associated with obesity.

Short-term high-fat diet alters the mouse brain magnetic resonance imaging parameters consistently with neuroinflammation on males and metabolic rearrangements on females. A pre-clinical study with an optimized selection of linear mixed-effects models

Introduction

High-fat diet (HFD) consumption is known to trigger an inflammatory response in the brain that prompts the dysregulation of energy balance, leads to insulin and leptin resistance, and ultimately obesity. Obesity, at the same, has been related to cerebral magnetic resonance imaging (MRI) alterations, but the onset of HFD-induced neuroinflammation, however, has been principally reported on male rodents and by ex vivo methods, with the effects on females and the origin of MRI changes remaining unassessed.

Methods

We characterized the onset and evolution of obesity on male and female mice during standard or HFD administration by physiological markers and multiparametric MRI on four cerebral regions involved in appetite regulation and energy homeostasis. We investigated the effects of diet, time under diet, brain region and sex by identifying their significant contributions to sequential linear mixed-effects models, and obtained their regional neurochemical profiles by high-resolution magic angle spinning spectroscopy.

Results

Male mice developed an obese phenotype paralleled by fast increases in magnetization transfer ratio values, while females delayed the obesity progress and showed no MRI-signs of cerebral inflammation, but larger metabolic rearrangements on the neurochemical profile.

Discussion

Our study reveals early MRI-detectable changes compatible with the development of HFD-induced cerebral cytotoxic inflammation on males but suggest the existence of compensatory metabolic adaptations on females that preclude the corresponding detection of MRI alterations.