Early life stress and body-mass-index modulate brain connectivity in alcohol use disorder.
Khushbu AgarwalPaule Valery JosephRui ZhangMelanie L SchwandtVijay A RamchandaniNancy DiazgranadosDavid GoldmanReza MomenanPublished in: Translational psychiatry (2024)
Early life stress (ELS) significantly increases susceptibility to alcohol use disorder (AUD) by affecting the interplay between the executive and the salience networks (SNs). The link between AUD and higher body-mass index (BMI) is known, but we lack understanding of how BMI impacts the relationship between ELS and brain connectivity in individuals with AUD. To bridge this gap, we investigated the main and interaction effects of ELS and BMI on brain connectivity in individuals with AUD compared to non-AUD participants (n = 77 sex-matched individuals per group). All participants underwent resting-state functional magnetic resonance imaging, revealing intriguing positive functional connectivity between SN seeds and brain regions involved in somatosensory processing, motor coordination and executive control. Examining the relationship of brain connectivity with ELS and BMI, we observed positive associations with the correlations of SN seeds, right anterior insula (RAIns) and supramarginal gyrus (SMG) with clusters in motor [occipital cortex, supplementary motor cortex]; anterior cingulate cortex (ACC) with clusters in frontal, or executive, control regions (middle frontal gyrus; MFG, precentral gyrus) that reportedly are involved in processing of emotionally salient stimuli (all |β | > 0.001, |p | < 0.05). Interestingly, a negative association of the interaction effect of ELS events and BMI measures with the functional connectivity of SN seeds ACC with decision-making (MFG, precentral gyrus), RAIns and RSMG with visuo-motor control regions (occipital cortex and supplementary motor cortex) (all |β | = -0.001, |p | < 0.05). These findings emphasize the moderating effect of BMI on ELS-associated SN seed brain connectivity in AUD. Understanding the neural mechanisms linking BMI, ELS and AUD can guide targeted interventions for this population.