Literature DB >> 30273793

White matter microstructural correlates of relapse in alcohol dependence.

Yukai Zou1, Donna E Murray2, Timothy C Durazzo3, Thomas P Schmidt4, Troy A Murray4, Dieter J Meyerhoff5.   

Abstract

Identification of neural correlates of relapse to alcohol after treatment is clinically important as it may inform better substance abuse treatment. Few studies have specifically analyzed the white matter microstructure in treatment seekers as it might relate to relapse risk versus long-term abstinence. Using 4 Tesla diffusion tensor imaging, we compared two groups of one-month-abstinent treatment-seekers, who were classified based on their drinking status between six and nine months after treatment initiation. We hypothesized that subsequent relapsers had greater white matter microstructural deficits in specific brain regions than long-term abstainers. At one month of abstinence, 37 future relapsers versus 25 future abstainers had lower fractional anisotropy (a measure of axonal organization and membrane integrity) in the corpus callosum and right stria terminalis/fornix, higher diffusivity in the genu of the corpus callosum, left and right stria terminalis/fornix, and lower diffusivity in left anterior corona radiata. These differences existed despite similar lifetime and recent drinking and smoking histories in the groups. Longer smoking duration in relapsers was associated with lower fractional anisotropy in right stria terminalis/fornix. The study identified specific microstructural biomarkers of alcohol relapse risk in adults, contributing to the definition of a neurobiological relapse risk profile in alcohol use disorder.
Copyright © 2018. Published by Elsevier B.V.

Entities:  

Keywords:  Abstinence; Alcohol use disorder; Diffusion tensor imaging; Relapse risk; Smoking; White matter

Mesh:

Year:  2018        PMID: 30273793      PMCID: PMC6204088          DOI: 10.1016/j.pscychresns.2018.09.004

Source DB:  PubMed          Journal:  Psychiatry Res Neuroimaging        ISSN: 0925-4927            Impact factor:   2.376


  64 in total

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