Hypothalamus Diversity In Anorexia
Overview
The study delves into the intricate relationship between the hypothalamus, hormonal regulation, and weight-related disorders, namely anorexia nervosa (AN) and obesity. Recognizing the pivotal role of the hypothalamus in maintaining energy homeostasis, the research aims to identify morphometric alterations in specific hypothalamic subregions and their associations with appetite-regulating hormones.
To conduct this investigation, structural magnetic resonance imaging (MRI) data were collected from 78 AN patients, 27 individuals with obesity, and 100 normal-weight healthy controls.
Additionally, blood levels of key hormones—leptin, ghrelin, and insulin—were measured in a subset of each group. Utilizing an automated segmentation method, the hypothalamus and its subregions were meticulously delineated. Comparative analyses of volume variations among groups and correlational assessments between morphometric measurements and hormone levels were performed.
The findings revealed that, when accounting for total brain volume, AN patients exhibited a reduced volume in the inferior-tubular subregion (ITS). Conversely, obesity was associated with enlarged volumes in the anterior-superior, ITS, posterior subregions (PS), and the entire hypothalamus. Notably, no significant volumetric differences were observed between AN subtypes.
Correlation analyses uncovered a positive association between leptin and PS volume, while ghrelin demonstrated a negative correlation with the entire hypothalamus volume across the entire cohort. Importantly, the study found that appetite-regulating hormone levels did not mediate the effects of body mass index on volumetric measures.
Introduction
The regulation of food intake is a multifaceted process influenced by a complex interplay between signals of energy homeostasis and neuronal circuits governing the rewarding aspects of food consumption.Recent neurobiological research has advanced our understanding of the central role played by orexigenic and anorexigenic networks, primarily located in the brainstem and hypothalamus, in responding to hormonal and metabolic cues from peripheral sites.
Additionally, interactions between specific hypothalamic subregions and the mesocorticolimbic reward circuitry contribute significantly to modulating the rewarding aspects of food intake.Studies investigating gut-brain signaling mechanisms suggest that impaired homeostatic control of food intake and energy expenditure underlies both anorexia nervosa (AN) and obesity.
Despite residing at opposing extremes of the weight spectrum, individuals with AN and obesity exhibit a common characteristic—a blunted responsiveness to peripheral appetite regulation.
Notably, hormonal signaling in these conditions still adjusts to physiological needs, with anorexigenic hormones like leptin being reduced in AN patients and increased in individuals with obesity, while orexigenic hormones such as ghrelin exhibit an opposite pattern.
However, these metabolic signals do not result in adaptive strategies to achieve a normal body weight.The hypothalamus, as a key region in the central control of energy homeostasis, becomes a focal point for investigating pathological changes that might lead to the observed decoupling from hormonal appetite regulation in disordered eating behavior.
In obesity, associations with inflammation and gliosis of hypothalamic neurons have been reported, disrupting the delicate balance of body weight control and glucose homeostasis. Conversely, AN suggests an overactive control network that overrides homeostatic and reward-associated food processing, facilitating a state of starvation and heightened tolerance to physical hunger.
Previous investigations, including our own, have noted blunted reactivity of the hypothalamus to glucose ingestion in both AN and obesity. Moreover, while increased satiety-dependent connectivity between the hypothalamus and mesocorticolimbic brain regions was observed in obesity, no such relation was detected in AN.
These results underscore the detachment of central neuronal food processing from appetite regulation in both AN and obesity, underscoring the pivotal role of hypothalamic dysfunction in disordered eating behavior.
However, the intricate neuronal pathophysiology of homeostatic dysregulations remains an area insufficiently understood. The hypothalamus, with its multitude of nuclei and diverse functions, necessitates a closer examination of the association between energy imbalances in weight disorders and different subregions within this complex brain region.
While previous studies have explored whole-brain morphological alterations associated with AN and obesity, a focused analysis of subregion-specific morphological changes within the hypothalamus has been lacking, primarily due to methodological challenges in accurately segmenting its complex structure.
This advanced approach ensures precise and robust segmentation and volumetric measurement of the hypothalamus and its subregions. By utilizing this methodology, we aim to detect subtle subregion-specific abnormalities within the hypothalamus.
Hypotheses revolve around anticipating morphological changes in individuals with AN and obesity, examining whether these changes are generalized or subregion-specific, and understanding how they correlate with individual body weight.
Additionally, we seek to unravel the intricate relationship between structural hypothalamic alterations and body weight by considering the significant influence of appetite-regulating hormone levels.
Analyzing hypothalamic subregions promises to unveil crucial insights into the pathophysiology of energy imbalances in weight disorders, presenting a promising avenue for the development of novel therapeutic strategies. This study aspires to contribute to the evolving understanding of the intricate mechanisms governing disordered eating behavior.
Methods
Study Population:
A total of 205 German adult women were included in this study. This cohort comprised 78 individuals diagnosed with acute anorexia nervosa (AN), characterized by a body mass index (BMI) below 17.5 kg/m² and a mean age of 23 years.
Additionally, 27 participants with obesity, defined by a BMI of 30 kg/m² or higher and a mean age of 28 years, were recruited. The control group consisted of 100 healthy normal-weight women with a BMI ranging from 18.5 to 25 kg/m² and a mean age of 24 years. Participants were recruited from various sources, including the Department of General Internal Medicine and Psychosomatics at Heidelberg University Hospital.
Inclusion Criteria
– For the AN group: Individuals had to meet the diagnostic criteria for AN according to the Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) criteria, with a BMI falling between 13 and 17.5 kg/m².
– For the normal-weight controls: Participants had to have a BMI ranging from 18.5 to 25 kg/m² and no lifetime or current medical conditions that could potentially affect appetite or weight.
– For the obesity group: Participants had to have a BMI between 30 and 45 kg/m² and no lifetime or current medical illness that could potentially affect appetite or weight, including a diagnosis of an eating disorder.
Exclusion Criteria
– History of head injury or operation
– Neurological disorder
– Psychosis or bipolar disorder
– Current or lifetime substance abuse
– Borderline personality disorder
– Current use of psychotropic medications, except for selective serotonin reuptake inhibitors (SSRIs)
All participants provided written informed consent, and the study was approved by the medical ethics committee of the Medical Faculty at the Ruprecht Karl University in Heidelberg, Germany.
Hormone Blood Level Measurement:
Hormone levels, including total ghrelin, leptin, and insulin, were measured in a subset of the study population. Participants were instructed to fast overnight before blood sample collection. Plasma samples were obtained before magnetic resonance imaging (MRI) scans and stored for later measurement. Hormone concentrations were determined using commercially available kits.
Image Acquisition:
Structural T1-weighted images were acquired using a 3 Tesla scanner. The imaging parameters were standardized across participants to ensure consistency.
Image Processing:
Preprocessing of the T1 images was performed using an automated pipeline, including motion correction, skull stripping, and segmentation of brain structures. Total brain volume (TBV) was generated to account for global effects, and total intracranial volume (TIV) was calculated separately. Hypothalamus segmentation was conducted using a convolutional neural network-based method, providing accurate delineation of the hypothalamus and its subregions.
This comprehensive approach enabled detailed analysis of hypothalamic morphology and its association with weight disorders in the study population.
Analysis
Statistical analysis of clinical and volumetric measures was conducted using R (version 4.1.3). Various parameters including age, BMI, Eating Disorder Examination Questionnaire (EDEQ) scores, total intracranial volume (TIV), and levels of appetite-regulating hormones were compared across groups using appropriate statistical tests.
One-way analysis of variance (ANOVA) and post hoc Tukey tests were utilized for comparisons, with a significance level set at p < .05. Analysis of covariance (ANCOVA) was employed to compare total brain volume (TBV) between groups, adjusting for TIV and age.
For the primary analysis, volumes of the whole hypothalamus and its subregions were compared between groups using ANCOVA, adjusting for age, TIV, and TBV. This approach aimed to identify regional structural alterations independent of global effects.
A secondary analysis was performed using ANCOVA, adjusting only for age and TIV, to investigate alterations driven by global effects. Pairwise group comparisons were conducted using post hoc Tukey tests, correcting for multiple comparisons.
Subtypes within the AN group were compared using t-tests for continuous variables and general linear models for volumetric measures, adjusting for age, TIV, and TBV. Spearman’s partial correlation analysis was utilized to investigate associations between hypothalamic volumes and hormone levels, adjusting for covariates. Mediation analysis was performed to assess whether appetite-regulating hormones mediate the effects of BMI on volumetric measures.
Additionally, Spearman correlation analysis was conducted to explore the relationship between BMI and hypothalamic volumes in the entire cohort, adjusting for relevant covariates. Partial correlation analyses were performed within each patient group to examine associations between clinical parameters and hypothalamic volumes, adjusting for relevant covariates.
All statistical analyses were Bonferroni-corrected for multiple comparisons, with a significance level set at p < .05. The results demonstrated significant differences in demographics, clinical features, and hormone levels across groups, highlighting distinct characteristics associated with AN, obesity, and healthy controls.
Specifically, differences were observed in age, BMI, EDEQ scores, and hormone levels among the groups. Additionally, TBV showed significant differences between groups, indicating potential structural alterations associated with different weight disorders.
Results
Significant differences were observed across groups in various demographic and clinical parameters. Age (F2,202=11.37, p< .001), BMI (F2,202=1262.8, p<.001), mean Eating Disorder Examination Questionnaire (EDEQ) scores (F2,199=142.64, p< .001), as well as levels of leptin (F2,77=101.84, p< .001), ghrelin (F2,90=14.16, p< .001), and insulin (F2,77=26.1, p< .001) exhibited significant differences.
Specifically, individuals with obesity were significantly older than those with anorexia nervosa (AN) and healthy controls (HC) (p< .001). BMI was significantly higher in individuals with obesity compared to both HC and AN, and also higher in HC compared to AN (p< .001).
EDEQ scores were significantly higher in AN compared to individuals with obesity and HC (p< .001), and higher in individuals with obesity compared to HC (p< .001).
Leptin levels were significantly higher in individuals with obesity compared to both AN and HC (p< .001), and higher in HC compared to AN (p< .005). Ghrelin levels were significantly higher in AN compared to HC and individuals with obesity (p< .001).
Insulin levels were significantly higher in individuals with obesity compared to both AN and HC (p<.001), and higher in HC compared to AN (p< .05).
Analysis of covariance (ANCOVA) also revealed significant differences in total brain volume (TBV) between the groups (p< .001), with TBV being lower in AN compared to HC and individuals with obesity (p< .001). However, no significant difference was found in total intracranial volume (TIV) between the groups.
Further analysis using ANCOVA, with age, TIV, and TBV as covariates, demonstrated significant differences between groups in various hypothalamic subregion volumes, including anterior-superior (ASS), inferior-tubular (ITS), posterior (PS), and whole hypothalamus (HT) volumes (F2,201=5.1, p< .05; F2,201=7.7, p< .01; F2,201=7.2, p< .001; F2,201=8.9, p< .005, respectively).
Post hoc comparisons revealed larger volumes in these regions in individuals with obesity compared to the other groups. Additionally, ITS volume was significantly smaller in AN compared to HC. However, no significant differences were observed between AN subtypes.
In the whole cohort, leptin levels were positively correlated with PS volume (ρ=.33, p< .05), while ghrelin levels were negatively correlated with HT volume (ρ=.30, p< .05). However, no significant correlation was found between insulin levels and any measured volumes after correcting for multiple comparisons.
Within-group analysis showed a significant negative correlation between ghrelin and anterior-inferior subregion (AIS) volume in individuals with obesity (ρ=.63, p< .05). However, mediation analyses did not show significant mediation effects of leptin or ghrelin on BMI and hypothalamic volumes.
Furthermore, there was a significant positive correlation between BMI and ITS, PS, and HT volumes in the whole cohort (ρ=.19, p< .01; ρ=.26, p< .001; ρ=.27, p< .01, respectively). However, within-group correlation analysis did not reveal significant correlations between hypothalamic volumes and BMI, illness duration, age of illness onset, or EDEQ scores.
Conclusion
Despite observing associations between appetite-regulating hormone levels and hypothalamic morphometry, we did not find evidence of mediation effects of these hormones on the relationship between body mass index (BMI) and hypothalamic volume.
To date, few studies have explored morphometric alterations in hypothalamic subregions among individuals with AN and obesity.
A previous study reported larger and smaller volumes in the hypothalamus and its subregions in individuals with obesity and AN, respectively. However, this study did not adjust for total brain volume (TBV), potentially confounding the interpretation of results.
Similarly, our study found smaller volumes in the hypothalamus and its subregions in AN compared to healthy controls, without adjusting for TBV.
This suggests a widespread pattern of hypothalamic volume loss in AN, consistent with existing evidence of global brain volume reduction in acute AN. Adjusting for TBV is crucial to uncover regional alterations beyond the known global effect, as demonstrated by recent research highlighting regional structural alterations in the amygdala associated with hypoleptinemia.
Overall, our study contributes to the understanding of structural hypothalamic alterations in AN and obesity, emphasizing the importance of considering total brain volume adjustments in investigating regional changes in the hypothalamus.
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