Combining Gray Matter Volume In The Cuneus And The Cuneus-Prefrontal Connectivity May Predict Early Relapse In Abstinent Alcohol-Dependent Patients

PLOS ONE(2018)

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摘要
BackgroundDeveloping more effective strategies to prevent relapse remains one of the major challenges of treating substance dependence. Previous studies have identified brain abnormalities in abstinent alcoholics. However, whether these persistent brain deficits in abstinence could predict early relapse to alcohol use has not been well established. This study aimed to identify biomarkers of relapse vulnerability by investigating persistent brain abnormalities in abstinent alcohol-dependent patients.MethodsBrain imaging and impulsive behavior data were collected from 56 abstinent alcohol-dependent male inpatients and 33 age-matched male healthy controls. Voxel-based morphometry was used to investigate the differences of grey matter volume between the groups. The resting-state functional connectivity was examined using brain areas with gray matter deficits as seed regions. A preliminary prospective study design was used to classify patients into abstainers and relapsers after a 62-day average abstinence period.ResultsCompared with healthy controls, both relapsers and abstainers exhibited significantly reduced gray matter volume in the cuneus. Functional connectivity analysis revealed that relapsers relative to abstainers demonstrated increased cuneus-centered negative functional connectivity within a network of brain regions which are involved in executive control and salience. Abnormal gray matter volume in the left cuneus and the functional connectivity between the right cuneus and bilateral dorsolateral prefrontal cortex could successfully predict relapse during the 3-month follow-up period.ConclusionsFindings suggest that the abnormal gray matter volume in the cuneus and resting-state cuneus-prefrontal functional connectivity may play an important role in poor treatment outcomes in alcoholics and serve as useful neural markers of relapse vulnerability.
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