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Metabolic abnormalities in lobar and subcortical brain regions of abstinent polysubstance users: Magnetic resonance spectroscopic imaging

  • Christoph Abé
  • , Anderson Mon
  • , Michael E. Hoefer
  • , Timothy C. Durazzo
  • , David L. Pennington
  • , Thomas P. Schmidt
  • , Dieter J. Meyerhoff
  • University of California at San Francisco
  • San Francisco VA Medical Center

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

Aims: The aim of the study was to explore neurometabolic and associated cognitive characteristics of patients with polysubstance use (PSU) in comparison with patients with predominant alcohol use using proton magnetic resonance spectroscopy. Methods: Brain metabolite concentrations were examined in lobar and subcortical brain regions of three age-matched groups: 1-monthabstinent alcohol-dependent PSU, 1-month-abstinent individuals dependent on alcohol alone (ALC) and light drinking controls (CON). Neuropsychological testing assessed cognitive function. Results: While CON and ALC had similar metabolite levels, persistent metabolic abnormalities ( primarily higher myo-inositol) were present in temporal gray matter, cerebellar vermis and lenticular nuclei of PSU. Moreover, lower cortical gray matter concentration of the neuronal marker N-acetylaspartate within PSU correlated with higher cocaine (but not alcohol) use quantities and with a reduced cognitive processing speed. Conclusions: These metabolite group differences reflect cellular/astroglial injury and/or dysfunction in alcohol-dependent PSU. Associations of other metabolite concentrations with neurocognitive performance suggest their functional relevance. The metabolic alterations in PSU may represent polydrug abuse biomarkers and/or potential targets for pharmacological and behavioral PSU-specific treatment.

Original languageEnglish
Article numberagt056
Pages (from-to)543-551
Number of pages9
JournalAlcohol and Alcoholism
Volume48
Issue number5
DOIs
Publication statusPublished - Sep 2013
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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