Progress in neuro-psychopharmacology & biological psychiatry · 2026
Aberrant inter-subject functional heterogeneity in frontoparietal and attention networks marks tobacco use disorder.
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Xu Xuefeng, Dong Guang-Heng
Аннотация
BACKGROUND: Tobacco use disorder (TUD) represents a significant global health challenge. Inter-subject variability in functional connectivity (IVFC) serves as a key neural indicator for explaining cognitive differences; however, its characteristics and genetic underpinnings in the TUD individuals remain unclear.
METHODS: This study included 200 male TUD patients and 185 male healthy controls (HCs) who underwent magnetic resonance imaging scanning. IVFC was constructed at both the regional (ROI) and network levels. Five machine learning methods, including the support vector machines (SVM) were employed to evaluate the predictive and classificatory performance of IVFC. Neurochemical and genetic analyses were further conducted to explore potential genetic mechanisms.
RESULTS: The TUD group exhibited significantly higher IVFC at both the ROI and network levels compared to HCs. SVM and other models effectively distinguished TUD patients from HCs, identifying the frontoparietal network (FPN), ventral attention network (VAN), and dorsal attention network (DAN) as the most discriminative features. ROI-level IVFC was significantly associated with the spatial distribution of key neurotransmitter systems, including dopamine, and correlated with the expression of 4427 genes. These genes were enriched in pathways related to synaptic function and the phosphorylation regulation.
CONCLUSION: Compared to HCs, individuals with TUD exhibited significant IVFC abnormalities, with disruptions in the FPN, VAN, and DAN as core neural features. Within the TUD group, ROI-level IVFCs were associated with neurotransmitter systems and gene expression, offering preliminary insights into clinical heterogeneity. These findings suggest that IVFC alterations-particularly in the FPN, VAN, and DAN-may serve as candidate neuroimaging biomarkers for TUD, pending validation in future longitudinal studies.
METHODS: This study included 200 male TUD patients and 185 male healthy controls (HCs) who underwent magnetic resonance imaging scanning. IVFC was constructed at both the regional (ROI) and network levels. Five machine learning methods, including the support vector machines (SVM) were employed to evaluate the predictive and classificatory performance of IVFC. Neurochemical and genetic analyses were further conducted to explore potential genetic mechanisms.
RESULTS: The TUD group exhibited significantly higher IVFC at both the ROI and network levels compared to HCs. SVM and other models effectively distinguished TUD patients from HCs, identifying the frontoparietal network (FPN), ventral attention network (VAN), and dorsal attention network (DAN) as the most discriminative features. ROI-level IVFC was significantly associated with the spatial distribution of key neurotransmitter systems, including dopamine, and correlated with the expression of 4427 genes. These genes were enriched in pathways related to synaptic function and the phosphorylation regulation.
CONCLUSION: Compared to HCs, individuals with TUD exhibited significant IVFC abnormalities, with disruptions in the FPN, VAN, and DAN as core neural features. Within the TUD group, ROI-level IVFCs were associated with neurotransmitter systems and gene expression, offering preliminary insights into clinical heterogeneity. These findings suggest that IVFC alterations-particularly in the FPN, VAN, and DAN-may serve as candidate neuroimaging biomarkers for TUD, pending validation in future longitudinal studies.