Alterations in Functional and Structural Connectivity of Basal Ganglia Network in Patients with Obesity

A review of brain structural and functional changes using MRI technology in patients who received bariatric surgery

According to the World Health Organization, obesity is one of the most significant health issues currently because it increases risk for type 2 diabetes and cancer, heart disease, bone health, reproduction, and quality of living and it impacts approximately 500 million adults worldwide. This review analyzed the existing literature focusing on the effects of Metabolic and bariatric surgeries (MBS), including Roux-en-Y gastric bypass and sleeve gastrectomy on changes in brain function and anatomy using magnetic resonance imaging (MRI) technology. A PubMed search using the key words bariatric surgery and MRI conducted in December 2023 resulted in 544 articles. Our literature review identified 24 studies addressing neuroanatomic, neurophysiological, cognitive, and behavioral changes that occurred at different time intervals after different types of bariatric surgery. Our review of the literature found several reports indicating that MBS reverse neuroanatomic alterations and changes in functional connectivity associated with obesity. There were also reported improvements in cognitive performance, memory, executive function, attention, as well as decreased gustatory brain responses to food cues and resting state measures following bariatric surgery. There were instances of improved neural functioning associated with weight loss, suggesting that some neuroanatomic changes can be reversed following weight loss induced by bariatric surgery. Additionally, there were data suggesting that brain connectivity and metabolic health are improved following a bariatric surgical intervention. Together, the existing literature indicates an overall improvement in brain connectivity and health outcomes following bariatric surgery.

Metabolic dysfunction-associated steatotic liver disease is associated with effects on cerebral perfusion and white matter integrity

It is unclear whether early metabolic and inflammatory aberrations in the liver are associated with detrimental changes in brain structure and cognitive function. This cross-sectional study examines putative associations between metabolic dysfunction-associated steatotic liver disease (MASLD) and brain health in 36-55 year-old participants with obesity (n = 70) from the BARICO study (BAriatric surgery Rijnstate and Radboudumc neuroImaging and Cognition in Obesity). The participants underwent brain magnetic resonance imaging to study brain volumes and cortical thickness (3T MRI including T1-weighted magnetization-prepared rapid gradient-echo sequence), cerebral blood perfusion (arterial spin labeling) and white matter integrity (diffusion weighted imaging to assess mean-skeletonized mean diffusivity and fluid-attenuated inversion recovery to detect the presence of white matter hyperintensities (WMH)). The participants additionally performed neuropsychological tests to assess global cognition, working and episodic memory, verbal fluency and the ability to shift attention. Liver biopsies were collected and liver dysfunction was examined with histopathological, biochemical, and gene expression analyses. Linear regression analyses were performed between liver and brain parameters and the influence of body-mass index, diabetes and hypertension was explored. Early stages of liver disease were not associated with cognitive status but with cerebrovascular changes independently of age, sex, BMI, diabetes and hypertension: hepatic fibrosis development was associated with higher spatial coefficient of variation (sCoV) in the nucleus accumbens (NAcc), reflecting greater variations in cerebral perfusion and reduced vascular efficiency. Elevated hepatic levels of free cholesterol and cholesteryl esters were associated with increased WMH, indicating cerebral small vessel disease. RNA-seq and pathway analyses identified associations between sCoV in NAcc and WMH and the expression of hepatic genes involved in inflammation and cellular stress. Additionally, sCoV in NAcc correlated with plasma IL-6 levels suggesting that systemic-low grade inflammation may, at least partly, mediate this relationship. In conclusion, this study demonstrates that specific features of liver dysfunction (e.g. free cholesterol, onset of fibrosis) are associated with subtle cerebrovascular impairments, when changes in cognitive performance are not yet noticeable. These findings highlight the need for future research on therapeutic strategies that normalize metabolic-inflammatory aberrations in the liver to reduce the risk of cognitive decline.

A multi-modal framework improves prediction of tissue-specific gene expression from a surrogate tissue

BACKGROUND

Tissue-specific analysis of the transcriptome is critical to elucidating the molecular basis of complex traits, but central tissues are often not accessible. We propose a methodology, Multi-mOdal-based framework to bridge the Transcriptome between PEripheral and Central tissues (MOTPEC).

METHODS

Multi-modal regulatory elements in peripheral blood are incorporated as features for gene expression prediction in 48 central tissues. To demonstrate the utility, we apply it to the identification of BMI-associated genes and compare the tissue-specific results with those derived directly from surrogate blood.

FINDINGS

MOTPEC models demonstrate superior performance compared with both baseline models in blood and existing models across the 48 central tissues. We identify a set of BMI-associated genes using the central tissue MOTPEC-predicted transcriptome data. The MOTPEC-based differential gene expression (DGE) analysis of BMI in the central tissues (including brain caudate basal ganglia and visceral omentum adipose tissue) identifies 378 genes overlapping the results from a TWAS of BMI, while only 162 overlapping genes are identified using gene expression in blood. Cellular perturbation analysis further supports the utility of MOTPEC for identifying trait-associated gene sets and narrowing the effect size divergence between peripheral blood and central tissues.

INTERPRETATION

The MOTPEC framework improves the gene expression prediction accuracy for central tissues and enhances the identification of tissue-specific trait-associated genes.

FUNDING

This research is supported by the National Natural Science Foundation of China 82204118 (D.Z.), the seed funding of the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province (2020E10004), the National Institutes of Health (NIH) Genomic Innovator Award R35HG010718 (E.R.G.), NIH/NHGRI R01HG011138 (E.R.G.), NIH/NIA R56AG068026 (E.R.G.), NIH Office of the Director U24OD035523 (E.R.G.), and NIH/NIGMS R01GM140287 (E.R.G.).

Functional alterations in overweight/obesity: focusing on the reward and executive control network

Overweight (OW) and obesity (OB) have become prevalent issues in the global public health arena. Serving as a prominent risk factor for various chronic diseases, overweight/obesity not only poses serious threats to people's physical and mental health but also imposes significant medical and economic burdens on society as a whole. In recent years, there has been a growing focus on basic scientific research dedicated to seeking the neural evidence underlying overweight/obesity, aiming to elucidate its causes and effects by revealing functional alterations in brain networks. Among them, dysfunction in the reward network (RN) and executive control network (ECN) during both resting state and task conditions is considered pivotal in neuroscience research on overweight/obesity. Their aberrations contribute to explaining why persons with overweight/obesity exhibit heightened sensitivity to food rewards and eating disinhibition. This review centers on the reward and executive control network by analyzing and organizing the resting-state and task-based fMRI studies of functional brain network alterations in overweight/obesity. Building upon this foundation, the authors further summarize a reward-inhibition dual-system model, with a view to establishing a theoretical framework for future exploration in this field.

Diffusion time-related structure-function coupling reveals differential association with inter-individual variations in body mass index

Body mass index (BMI) is an indicator of obesity, and recent neuroimaging studies have demonstrated that inter-individual variations in BMI are associated with altered brain structure and function. However, the mechanism underlying the alteration of structure-function correspondence according to BMI is under-investigated. In this study, we studied structural and functional connectivity derived from diffusion MRI tractography and inter-regional correlations of functional MRI time series, respectively. We combined the structural and functional connectivity information using the Riemannian optimization approach. First, the low-dimensional principal eigenvectors (i.e., gradients) of the structural connectivity were generated by applying diffusion map embedding with varying diffusion times. A transformation was identified so that the structural and functional embeddings share the same coordinate system, and subsequently, the functional connectivity matrix was simulated. Then, we generated gradients from the simulated functional connectivity matrix. We found the most apparent cortical hierarchical organization differentiating between low-level sensory and higher-order transmodal regions in the middle of the diffusion time, indicating that the hierarchical organization of the brain may reflect the intermediate mechanisms of mono- and polysynaptic communications. Associations between the functional gradients and BMI were strongest when the hierarchical structure was the most evident. Moreover, the gradient-BMI association map was related to the microstructural features, and the findings indicated that the BMI-related structure-function coupling was significantly associated with brain microstructure, particularly in higher-order transmodal areas. Finally, transcriptomic association analysis revealed the potential biological underpinnings specifying gene enrichment in the striatum, hypothalamus, and cortical cells. Our findings provide evidence that structure-function correspondence is strongly coupled with BMI when hierarchical organization is the most apparent and that the associations are related to the multiscale properties of the brain, leading to an advanced understanding of the neural mechanisms related to BMI.

From the reward network to whole-brain metrics: structural connectivity in adolescents and young adults according to body mass index and genetic risk of obesity

BACKGROUND

Obesity is a multifactorial condition. Genetic variants, such as the fat mass and obesity related gene (FTO) polymorphism, may increase the vulnerability of developing obesity by disrupting dopamine signaling within the reward network. Yet, the association of obesity, genetic risk of obesity, and structural connectivity of the reward network in adolescents and young adults remains unexplored. We investigate, in adolescents and young adults, the structural connectivity differences in the reward network and at the whole-brain level according to body mass index (BMI) and the FTO rs9939609 polymorphism.

METHODS

One hundred thirty-two adolescents and young adults (age range: [10, 21] years, BMI z-score range: [-1.76, 2.69]) were included. Genetic risk of obesity was determined by the presence of the FTO A allele. Whole-brain and reward network structural connectivity were analyzed using graph metrics. Hierarchical linear regression was applied to test the association between BMI-z, genetic risk of obesity, and structural connectivity.

RESULTS

Higher BMI-z was associated with higher (B = 0.76, 95% CI = [0.30, 1.21], P = 0.0015) and lower (B = -0.003, 95% CI = [-0.006, -0.00005], P = 0.048) connectivity strength for fractional anisotropy at the whole-brain level and of the reward network, respectively. The FTO polymorphism was not associated with structural connectivity nor with BMI-z.

CONCLUSIONS

We provide evidence that, in healthy adolescents and young adults, higher BMI-z is associated with higher connectivity at the whole-brain level and lower connectivity of the reward network. We did not find the FTO polymorphism to correlate with structural connectivity. Future longitudinal studies with larger sample sizes are needed to assess how genetic determinants of obesity change brain structural connectivity and behavior.

The body mass index is associated with increased temporal variability of functional connectivity in brain reward system

The reward system has been proven to be contributed to the vulnerability of obesity. Previous fMRI studies have shown abnormal functional connectivity of the reward system in obesity. However, most studies were based on static index such as resting-state functional connectivity (FC), ignoring the dynamic changes over time. To investigate the dynamic neural correlates of obesity susceptibility, we used a large, demographically well-characterized sample from the Human Connectome Project (HCP) to determine the relationship of body mass index (BMI) with the temporal variability of FC from integrated multilevel perspectives, i.e., regional and within- and between-network levels. Linear regression analysis was used to investigate the association between BMI and temporal variability of FC, adjusting for covariates of no interest. We found that BMI was positively associated with regional FC variability in reward regions, such as the ventral orbitofrontal cortex and visual regions. At the intra-network level, BMI was positively related to the variability of FC within the limbic network (LN) and default mode network (DMN). At the inter-network level, variability of connectivity of LN with DMN, frontoparietal, sensorimotor, and ventral attention networks showed positive correlations with BMI. These findings provided novel evidence for abnormal dynamic functional interaction between the reward network and the rest of the brain in obesity, suggesting a more unstable state and over-frequent interaction of the reward network and other attention and cognitive networks. These findings, thus, provide novel insight into obesity interventions that need to decrease the dynamic interaction between reward networks and other brain networks through behavioral treatment and neural modulation.

Brain functional and structural magnetic resonance imaging of obesity and weight loss interventions

Obesity has tripled over the past 40 years to become a major public health issue, as it is linked with increased mortality and elevated risk for various physical and neuropsychiatric illnesses. Accumulating evidence from neuroimaging studies suggests that obesity negatively affects brain function and structure, especially within fronto-mesolimbic circuitry. Obese individuals show abnormal neural responses to food cues, taste and smell, resting-state activity and functional connectivity, and cognitive tasks including decision-making, inhibitory-control, learning/memory, and attention. In addition, obesity is associated with altered cortical morphometry, a lowered gray/white matter volume, and impaired white matter integrity. Various interventions and treatments including bariatric surgery, the most effective treatment for obesity in clinical practice, as well as dietary, exercise, pharmacological, and neuromodulation interventions such as transcranial direct current stimulation, transcranial magnetic stimulation and neurofeedback have been employed and achieved promising outcomes. These interventions and treatments appear to normalize hyper- and hypoactivations of brain regions involved with reward processing, food-intake control, and cognitive function, and also promote recovery of brain structural abnormalities. This paper provides a comprehensive literature review of the recent neuroimaging advances on the underlying neural mechanisms of both obesity and interventions, in the hope of guiding development of novel and effective treatments.

Exercise modifies hypothalamic connectivity and brain functional networks in women after bariatric surgery: a randomized clinical trial

BACKGROUND

Obesity is a disease that may involve disrupted connectivity of brain networks. Bariatric surgery is an effective treatment for obesity, and the positive effects on obesity-related conditions may be enhanced by exercise. Herein, we aimed to investigate the possible synergistic effects of Roux-en-Y Gastric Bypass (RYGB) and exercise training on brain functional networks.

METHODS

Thirty women eligible for bariatric surgery were randomly assigned to a Roux-en-Y gastric bypass (RYGB: n = 15, age = 41.0 ± 7.3 years) or RYGB plus Exercise Training (RYGB + ET: n = 15, age = 41.9 ± 7.2 years). Clinical, laboratory, and brain functional connectivity parameters were assessed at baseline, and 3 (POST3) and 9 months (POST9) after surgery. The 6-month, three-times-a-week, exercise intervention (resistance plus aerobic exercise) was initiated 3 months post-surgery (for RYGB + ET).

RESULTS

Exercise superimposed on bariatric surgery (RYGB + ET) increased connectivity between hypothalamus and sensorial regions (seed-to-voxel analyses of hypothalamic connectivity), and decreased default mode network (DMN) and posterior salience (pSAL) network connectivity (ROI-to-ROI analyses of brain networks connectivity) when compared to RYGB alone (all p-FDR < 0.05). Increases in basal ganglia (BG) network connectivity were only observed in the exercised training group (within-group analyses).

CONCLUSION

Exercise training is an important component in the management of post-bariatric patients and may improve the hypothalamic connectivity and brain functional networks that are involved in controlling food intake.

TRIAL REGISTRATION

Clinicaltrial.gov: NCT02441361.