Structural-functional decoupling in tobacco use disorder: Linking network dysfunction to molecular signatures.

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Abstract

Structural-functional coupling (SFC) has garnered significant attention in the study of various mental disorders due to its heightened sensitivity in detecting abnormalities. However, the SFC characteristics specific to tobacco use disorder (TUD) and the underlying neurobiological mechanisms remain elusive. We collected structural and functional magnetic resonance imaging data from 111 male patients with TUD and 92 male healthy controls (HCs). Node-level SFC differences between groups were quantified. Five machine learning models were employed to assess the potential of aberrant coupling patterns in predicting and diagnosing TUD. Furthermore, correlations between altered coupling, the spatial distribution of neurotransmitters, and gene expression profiles were examined. Compared to HCs, TUD subjects exhibited weakened nodal coupling between the executive control network (ECN), the default mode network (DMN) salience network (SN) and sensorimotor network (SMN), alongside enhanced coupling within the basal ganglia (BG). Extra trees classification demonstrated robust diagnostic and predictive capabilities. Notably, these coupling abnormalities were significantly associated with the spatial distribution of five distinct neurotransmitters and specific gene expression profiles. Our findings illuminate a decoupling (The SFC of TUD significantly deviates from HCs) pattern in TUD involving the ECN, DMN, SN and SMN and a hyperconnectivity anomaly within the BG. These alterations not only facilitate effective diagnosis but also exhibit spatial alignment with brain regions enriched for specific neurotransmitter systems and genetic expressions. This study contributes novel insights into the neurobiological underpinnings of TUD, offering potential avenues for preventive strategies and therapeutic interventions.

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