Early life adversity impacts alterations in brain structure and food addiction in individuals with high BMI.

Obesity and food addiction are associated with distinct brain signatures related to reward processing, and early life adversity (ELA) also increases alterations in these same reward regions. However, the neural mechanisms underlying the effect of early life adversity on food addiction are unknown. Therefore, the aim of this study was to examine the interactions between ELA, food addiction, and brain morphometry in individuals with obesity. 114 participants with high body mass index (BMI) underwent structural MRIs, and completed several questionnaires (e.g., Yale Food Addiction Scale (YFAS), Brief Resilience Scale (BRS), Early Traumatic Inventory (ETI)). Freesurfer 6 was applied to generate the morphometry of brain regions. A multivariate pattern analysis was used to derive brain morphometry patterns associated with food addiction. General linear modeling and mediation analyses were conducted to examine the effects of ELA and resilience on food addiction in individuals with obesity. Statistical significance was determined at a level of p < 0.05. High levels of ELA showed a strong association between reward control brain signatures and food addiction (p = 0.03). Resilience positively mediated the effect of ELA on food addiction (B = 0.02, p = 0.038). Our findings suggest that food addiction is associated with brain signatures in motivation and reward processing regions indicative of dopaminergic dysregulation and inhibition of cognitive control regions. These mechanistic variabilities along with early life adversity suggest increased vulnerability to develop food addiction and obesity in adulthood, which can buffer by the neuroprotective effects of resilience, highlighting the value of incorporating cognitive appraisal into obesity therapeutic regimens.

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.

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.

Obesity is associated with a distinct brain-gut microbiome signature that connects Prevotella and Bacteroides to the brain's reward center.

The prevalence of obesity has risen to its highest values over the last two decades. While many studies have either shown brain or microbiome connections to obesity, few have attempted to analyze the brain-gut-microbiome relationship in a large cohort adjusting for cofounders. Therefore, we aim to explore the connection of the brain-gut-microbiome axis to obesity controlling for such cofounders as sex, race, and diet. Whole brain resting state functional MRI was acquired, and connectivity and brain network properties were calculated. Fecal samples were obtained from 287 obese and non-obese participants (males n = 99, females n = 198) for 16s rRNA profiling and fecal metabolites, along with a validated dietary questionnaire. Obesity was associated with alterations in the brain's reward network (nucleus accumbens, brainstem). Microbial diversity (p = .03) and composition (p = .03) differed by obesity independent of sex, race, or diet. Obesity was associated with an increase in Prevotella/Bacteroides (P/B) ratio and a decrease in fecal tryptophan (p = .02). P/B ratio was positively correlated to nucleus accumbens centrality (p = .03) and negatively correlated to fecal tryptophan (p = .004). Being Hispanic, eating a standard American diet, having a high Prevotella/Bacteroides ratio, and a high nucleus accumbens centrality were all independent risk factors for obesity. There are obesity-related signatures in the BGM-axis independent of sex, race, and diet. Race, diet, P/B ratio and increased nucleus accumbens centrality were independent risk factors for obesity. P/B ratio was inversely related to fecal tryptophan, a metabolite related to serotonin biosynthesis, and positively related to nucleus accumbens centrality, a region central to the brain's reward center. These findings may expand the field of therapies for obesity through novel pathways directed at the BGM axis.

Complex functional brain network properties in anorexia nervosa.

BACKGROUND: Anorexia nervosa (AN) is a disorder characterized by an incapacitating fear of weight gain and by a disturbance in the way the body is experienced, facets that motivate dangerous weight loss behaviors. Multimodal neuroimaging studies highlight atypical neural activity in brain networks involved in interoceptive awareness and reward processing. METHODS: The current study used resting-state neuroimaging to model the architecture of large-scale functional brain networks and characterize network properties of individual brain regions to clinical measures. Resting-state neuroimaging was conducted in 62 adolescents, 22 (21 female) with a history of AN and 40 (39 female) healthy controls (HCs). Sensorimotor and basal ganglia regions, as part of a 165-region whole-brain network, were investigated. Subject-specific functional brain networks were computed to index centrality. A contrast analysis within the general linear model covarying for age was performed. Correlations between network properties and behavioral measures were conducted (significance q < .05). RESULTS: Compared to HCs, AN had lower connectivity from sensorimotor regions, and greater connectivity from the left caudate nucleus to the right postcentral gyrus. AN demonstrated lower sensorimotor centrality, but higher basal ganglia centrality. Sensorimotor connectivity dyads and centrality exhibited negative correlations with body dissatisfaction and drive for thinness, two essential features of AN. CONCLUSIONS: These findings suggest that AN is associated with greater communication from the basal ganglia, and lower information propagation in sensorimotor cortices. This is consistent with the clinical presentation of AN, where individuals exhibit patterns of rigid habitual behavior that is not responsive to bodily needs, and seem "disconnected" from their bodies.

Individuals with anorexia nervosa (AN) usually report a fear of gaining weight. They often develop a dislike and distrust of their bodies, feeling that their bodies had somehow let them down. These fears can in turn lead to dangerous weight loss behaviors. Magnetic resonance imaging of the brain is a tool that helps highlight the underlying biological processes associated with AN. In the current study we aim to investigate how the connections in key regions of the brain are related to clinical and behavioral factors associated with AN. We found regions of two main networks were associated with body dissatisfaction and drive for thinness, which are key features of AN. The brain regions involved help explain why patients with AN have characteristics of feeling disconnected from their bodies, having difficulty labeling and regulating emotions, responding to biological needs such as hunger and fatigue, and differentiating experiences that will be rewarding. These results can help guide interventions that will be directed towards helping individuals with AN to better sense, decipher, and act on the various signals being communicated by their body.

A neuropsychosocial signature predicts longitudinal symptom changes in women with irritable bowel syndrome.

Irritable bowel syndrome (IBS) is a common disorder of brain-gut interactions characterized by chronic abdominal pain, altered bowel movements, often accompanied by somatic and psychiatric comorbidities. We aimed to test the hypothesis that a baseline phenotype composed of multi-modal neuroimaging and clinical features predicts clinical improvement on the IBS Symptom Severity Scale (IBS-SSS) at 3 and 12 months without any targeted intervention. Female participants (N = 60) were identified as "improvers" (50-point decrease on IBS-SSS from baseline) or "non-improvers." Data integration analysis using latent components (DIABLO) was applied to a training and test dataset to determine whether a limited number of sets of multiple correlated baseline'omics data types, including brain morphometry, anatomical connectivity, resting-state functional connectivity, and clinical features could accurately predict improver status. The derived predictive models predicted improvement status at 3-months and 12-months with 91% and 83% accuracy, respectively. Across both time points, non-improvers were classified as having greater correlated morphometry, anatomical connectivity and resting-state functional connectivity characteristics within salience and sensorimotor networks associated with greater pain unpleasantness, but lower default mode network integrity and connectivity. This suggests that non-improvers have a greater engagement of attentional systems to perseverate on painful visceral stimuli, predicting IBS exacerbation. The ability of baseline multimodal brain-clinical signatures to predict symptom trajectories may have implications in guiding integrative treatment in the age of precision medicine, such as treatments targeted at changing attentional systems such as mindfulness or cognitive behavioral therapy.

Early life adversity predicts brain-gut alterations associated with increased stress and mood.

Alterations in the brain-gut system have been implicated in various disease states, but little is known about how early-life adversity (ELA) impacts development and adult health as mediated by brain-gut interactions. We hypothesize that ELA disrupts components of the brain-gut system, thereby increasing susceptibility to disordered mood. In a sample of 128 healthy adult participants, a history of ELA and current stress, depression, and anxiety were assessed using validated questionnaires. Fecal metabolites were measured using liquid chromatography tandem mass spectrometry-based untargeted metabolomic profiling. Functional brain connectivity was evaluated by magnetic resonance imaging. Sparse partial least squares-discriminant analysis, controlling for sex, body mass index, age, and diet was used to predict brain-gut alterations as a function of ELA. ELA was correlated with four gut-regulated metabolites within the glutamate pathway (5-oxoproline, malate, urate, and glutamate gamma methyl ester) and alterations in functional brain connectivity within primarily sensorimotor, salience, and central executive networks. Integrated analyses revealed significant associations between these metabolites, functional brain connectivity, and scores for perceived stress, anxiety, and depression. This study reveals a novel association between a history of ELA, alterations in the brain-gut axis, and increased vulnerability to negative mood and stress. Results from the study raise the hypothesis that select gut-regulated metabolites may contribute to the adverse effects of critical period stress on neural development via pathways related to glutamatergic excitotoxicity and oxidative stress.

Altered brain structural connectivity in patients with longstanding gut inflammation is correlated with psychological symptoms and disease duration.

OBJECTIVE: We aimed to identify differences in network properties of white matter microstructure between asymptomatic ulcerative colitis (UC) participants who had a history of chronic gut inflammation, healthy controls (HCs) and a disease control group without gut inflammation (irritable bowel syndrome; IBS). DESIGN: Diffusion weighted imaging was conducted in age and sex-matched participants with UC, IBS, and HCs (N = 74 each), together with measures of gastrointestinal and psychological symptom severity. Using streamline connectivity matrices and graph theory, we aimed to quantify group differences in brain network connectivity. Regions showing group connectivity differences were correlated with measures showing group behavioral and clinical differences. RESULTS: UC participants exhibited greater centrality in regions of the somatosensory network and default mode network, but lower centrality in the posterior insula and globus pallidus compared to HCs (q < 0.05). Hub analyses revealed compromised hubness of the pallidus in UC and IBS compared to HCs which was replaced by increased hubness of the postcentral sulcus. Surprisingly, few differences in network matrices between UC and IBS were identified. In UC, centrality measures in the secondary somatosensory cortex were associated with depression (q < 0.03), symptom related anxiety (q < 0.04), trait anxiety (q < 0.03), and symptom duration (q < 0.05). CONCLUSION: A history of UC is associated with neuroplastic changes in several brain networks, which are associated with symptoms of depression, trait and symptom-related anxiety, as well as symptom duration. When viewed together with the results from IBS subjects, these findings suggest that chronic gut inflammation as well as abdominal pain have a lasting impact on brain network organization, which may play a role in symptoms reported by UC patients, even when gut inflammation has subsided.

Alterations in reward network functional connectivity are associated with increased food addiction in obese individuals.

Functional neuroimaging studies in obesity have identified alterations in the connectivity within the reward network leading to decreased homeostatic control of ingestive behavior. However, the neural mechanisms underlying sex differences in the prevalence of food addiction in obesity is unknown. The aim of the study was to identify functional connectivity alterations associated with: (1) Food addiction, (2) Sex- differences in food addiction, (3) Ingestive behaviors. 150 participants (females: N = 103, males: N = 47; food addiction: N = 40, no food addiction: N = 110) with high BMI ≥ 25 kg/m2 underwent functional resting state MRIs. Participants were administered the Yale Food Addiction Scale (YFAS), to determine diagnostic criteria for food addiction (YFAS Symptom Count ≥ 3 with clinically significant impairment or distress), and completed ingestive behavior questionnaires. Connectivity differences were analyzed using a general linear model in the CONN Toolbox and images were segmented using the Schaefer 400, Harvard-Oxford Subcortical, and Ascending Arousal Network atlases. Significant connectivities and clinical variables were correlated. Statistical significance was corrected for multiple comparisons at q < .05. (1) Individuals with food addiction had greater connectivity between brainstem regions and the orbital frontal gyrus compared to individuals with no food addiction. (2) Females with food addiction had greater connectivity in the salience and emotional regulation networks and lowered connectivity between the default mode network and central executive network compared to males with food addiction. (3) Increased connectivity between regions of the reward network was positively associated with scores on the General Food Cravings Questionnaire-Trait, indicative of greater food cravings in individuals with food addiction. Individuals with food addiction showed greater connectivity between regions of the reward network suggesting dysregulation of the dopaminergic pathway. Additionally, greater connectivity in the locus coeruleus could indicate that the maladaptive food behaviors displayed by individuals with food addiction serve as a coping mechanism in response to pathological anxiety and stress. Sex differences in functional connectivity suggest that females with food addiction engage more in emotional overeating and less cognitive control and homeostatic processing compared to males. These mechanistic pathways may have clinical implications for understanding the sex-dependent variability in response to diet interventions.

Understanding the Heterogeneity of Obesity and the Relationship to the Brain-Gut Axis.

Obesity is best understood as a multifactorial metabolic imbalances disorder. In a cross-sectional study, we aimed to explore sociodemographic and dietary determinants of obesity in relation to brain-gut homeostasis among overweight and obese individuals. Multivariate logistic regression models were used to examine obesity and its association with sociodemographic and dietary factors. Biological variables examined included the gut microbiome, fecal amino acid metabolites and brain structural volumes. Among 130 participants, there were higher odds of obesity if individuals were Hispanic (adjusted odds ratio (aOR) 1.56, p = 0.014). Compared to non-Hispanics, Hispanics differed in gut microbial composition (p = 0.046) with lower microbial species richness (Chao1) (p = 0.032) and evenness (Shannon) (p = 0.0029). Fourteen of the twenty fecal amino acids including branch-chain- and aromatic- amino acids were increased among Hispanics (q < 0.05). Brain structural volumes in reward regions were decreased in Hispanics (pallidum, q = 0.036; brainstem, q = 0.011). Correlation patterns suggest complex brain-gut interactions differ by Hispanic ethnicity. In conclusion, Hispanics expressed a unique brain-gut microbial signature, which was associated with obesity despite sociodemographic and dietary differences. Addressing ethnic disparities guided by biologic phenotypes may unlock novel understanding of obesity heterogeneity and treatment strategies.

Improvement in Uncontrolled Eating Behavior after Laparoscopic Sleeve Gastrectomy Is Associated with Alterations in the Brain-Gut-Microbiome Axis in Obese Women.

BACKGROUND: Bariatric surgery is proven to change eating behavior and cause sustained weight loss, yet the exact mechanisms underlying these changes are not clearly understood. We explore this in a novel way by examining how bariatric surgery affects the brain-gut-microbiome (BGM) axis. METHODS: Patient demographics, serum, stool, eating behavior questionnaires, and brain magnetic resonance imaging (MRI) were collected before and 6 months after laparoscopic sleeve gastrectomy (LSG). Differences in eating behavior and brain morphology and resting-state functional connectivity in core reward regions were correlated with serum metabolite and 16S microbiome data. RESULTS: LSG resulted in significant weight loss and improvement in maladaptive eating behaviors as measured by the Yale Food Addiction Scale (YFAS). Brain imaging showed a significant increase in brain volume of the putamen (p.adj < 0.05) and amygdala (p.adj < 0.05) after surgery. Resting-state connectivity between the precuneus and the putamen was significantly reduced after LSG (p.adj = 0.046). This change was associated with YFAS symptom count. Bacteroides, Ruminococcus, and Holdemanella were associated with reduced connectivity between these areas. Metabolomic profiles showed a positive correlation between this brain connection and a phosphatidylcholine metabolite. CONCLUSION: Bariatric surgery modulates brain networks that affect eating behavior, potentially through effects on the gut microbiota and its metabolites.

Impact of early adverse life events and sex on functional brain networks in patients with urological chronic pelvic pain syndrome (UCPPS): A MAPP Research Network study.

Pain is a highly complex and individualized experience with biopsychosocial components. Neuroimaging research has shown evidence of the involvement of the central nervous system in the development and maintenance of chronic pain conditions, including urological chronic pelvic pain syndrome (UCPPS). Furthermore, a history of early adverse life events (EALs) has been shown to adversely impact symptoms throughout childhood and into adulthood. However, to date, the role of EAL's in the central processes of chronic pain have not been adequately investigated. We studied 85 patients (56 females) with UCPPS along with 86 healthy controls (HCs) who had resting-state magnetic resonance imaging scans (59 females), and data on EALs as a part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network Study. We used graph theory methods in order to investigate the impact of EALs on measures of centrality, which characterize information flow, communication, influence, and integration in a priori selected regions of interest. Patients with UCPPS exhibited lower centrality in the right anterior insula compared to HCs, a key node in the salience network. Males with UCPPS exhibited lower centrality in the right anterior insula compared the HC males. Females with UCPPS exhibited greater centrality in the right caudate nucleus and left angular gyrus compared to HC females. Males with UCPPS exhibited lower centrality in the left posterior cingulate, angular gyrus, middle temporal gyrus, and superior temporal sulcus, but greater centrality in the precuneus and anterior mid-cingulate cortex (aMCC) compared to females with UCPPS. Higher reports of EALs was associated with greater centrality in the left precuneus and left aMCC in females with UCPPS. This study provides evidence for disease and sex-related alterations in the default mode, salience, and basal ganglia networks in patients with UCPPS, which are moderated by EALs, and associated with clinical symptoms and quality of life (QoL).