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Surface-based analysis; Sleep quality index; Resting-state; Network centrality; Neural mechanisms; Eating behaviors; Reward systems; Food reward; Obesity; Connectivity
Abstract:
Variations in body mass index (BMI) have been suggested to relate to atypical brain organization, yet connectome-level substrates of BMI and their neurobiological underpinnings remain unclear. Studying 325 healthy young adults, we examined associations between functional connectivity and inter-individual BMI variations. We utilized non-linear connectome manifold learning techniques to represent macroscale functional organization along continuous hierarchical axes that dissociate low level and higher order brain systems. We observed an increased differentiation between unimodal and heteromodal association networks in individuals with higher BMI, indicative of a disrupted modular architecture and hierarchy of the brain. Transcriptomic decoding and gene enrichment analyses identified genes previously implicated in genome-wide associations to BMI and specific cortical, striatal, and cerebellar cell types. These findings illustrate functional connectome substrates of BMI variations in healthy young adults and point to potential molecular associations. Bo-yong Park et al. use non-linear connectome manifold learning to examine the association between brain connectivity and inter-individual body mass index (BMI) in 325 young adults. They supplement these analyses with existing transcriptomic data, altogether suggesting several neural and molecular associations that may underlie BMI variations in healthy young adults.
