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Data from Multimodal MRI Imaging Show Men and Women have Different Obesity Drivers

Article

Researchers found sex-specific brain signals that appear to confirm that different drivers lead men and women to develop obesity.

©wissanustock/AdobeStock

©wissanustock/AdobeStock

A team of researchers from UCLA found sex-specific brain signals that appear to confirm that different drivers lead men and women to develop obesity. Findings from the cross-sectional study were published April 4, 2023, in the journal Brain Communications.

“We found differeces in several of the brain’s networks associated with early life adversity, mental health quality, and the way sensory stimulation is experienced. The resulting brain signatures, based on multimodal MRI imaging, may help us more precisely tailor obesity interventions based on an individual’s sex,” said senior author Arpana Gupta, PhD, associate professor-in-residence, medicine, UCLA, in a university press release.

Findings from the cross-sectional study were published in Brain Communications.

Separate neuroimaging modalities have found mechanisms related to obesity and altered eating and drinking habits, however, “few, if any, studies have integrated data from multimodal brain imaging to predict sex-specific brain signatures related to obesity,” wrote Gupta and colleagues. Utilizing a data-driven approach, researchers integrated data from multimodal brain imaging and behavioral data to determine sex-specific brain-behavioral signatures present in persons with obesity.

“Given the widespread prevalence and adverse effects of obesity, it is important to understand the differences in the neural correlates of obesity between men and women. A better understanding of differences in brain signatures in obesity can be used to devise better treatment and effective lifestyle interventions,” wrote investigators.

The study included 183 participants aged 18-55 years who all completed multimodal neuroimaging, including morphometry, functional resting-state MRI, and a diffusion weighted scan. Also, participants completed a battery of behavioral and clinical questionnaires that assessed childhood trauma, anxiety and depression, visceral sensitivity, food addiction, bowel symptoms, personality traits, and several other factors.

“A Data Integration Analysis for Biomarker discovery using Latent Components (DIABLO) was conducted to determine whether clinical features, brain morphometry, functional connectivity, and anatomical connectivity could accurately differentiate participants stratified by obesity and sex,” wrote Gupta and colleagues.

For the purpose of the study, participants were classified as “high body mass index (BMI)” if they had a BMI greater than 25 kg/m2 and “nonobese BMI” if they had a BMI between 19-20 kg/m2. Among the cohort there were 23 men and 55 women with high BMI and 42 men and 63 women with nonobese BMI.

The 4 main findings of the study were:

  1. Greater choroid plexus and ventricular and volume in high BMI participants was associated with anatomical connectivity alterations in the cortico-basal ganglia-thalamo-cortical loop.
  2. Greater trauma early in life was associated with greater volume and surface area as well as anatomical connectivity of the anterior insula and greater sensorimotor-default mode network resting-state connectivity.
  3. When compared to men with high BMI, women with high BMI demonstrated lower mental health scores, which was associated with lower amygdala resting-state functional connectivity to the sensorimotor network.
  4. When compared to men with high BMI, women with high BMI had greater scores on the Pennebaker Inventory of Limbic Languidness questionnaire, which were associated with lower surface area and volume in the anterior cingulate cortex.

“Our results provide a sex-specific biological marker that could explain the short-term feeding regulation and sensory processing patterns seen in females with obesity,” wrote the research team. “To our knowledge, this is the first study to utilize a data-driven approach to predict the sex-specific obesity status of an individual based on multimodal brain signatures.”

Gupta and colleagues emphasized that their study identified associations, not cause and effect, so future studies will be needed to figure out whether changes in the brain are a factor in the development of obesity or a result of obesity.

“Although causality is unknown, the strong associations between clinical markers, such as anxiety, depression, obesity, and neural signatures suggest the importance of the bidirectional mechanistic connection of the gut-brain axis,” wrote Gupta et al.


Reference: Gupta A, Bhatt RR, Todorov S, et al. Integrated multimodal brain signatures predict sex-specific obesity status. Brain Communications. Published online April 4, 2023. doi:10.1093/braincomms/fcad098.


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