Objective: In this study, we aimed to characterize the plasma metabolic profiles of brain atrophy and alcohol dependence (s) and to identify the underlying pathogenesis of brain atrophy related to alcohol dependence.
Methods: We acquired the plasma samples of alcohol-dependent patients and performed non-targeted metabolomic profiling analysis to identify alterations of key metabolites in the plasma of BA-ADPs. Machine learning algorithms and bioinformatic analysis were also used to identify predictive biomarkers and investigate their possible roles in brain atrophy related to alcohol dependence.
Results: A total of 26 plasma metabolites were significantly altered in the BA-ADPs group when compared with a group featuring alcohol-dependent patients without brain atrophy (NBA-ADPs). Nine of these differential metabolites were further identified as potential biomarkers for BA-ADPs. Receiver operating characteristic curves demonstrated that these potential biomarkers exhibited good sensitivity and specificity for distinguishing BA-ADPs from NBA-ADPs. Moreover, metabolic pathway analysis suggested that glycerophospholipid metabolism may be highly involved in the pathogenesis of alcohol-induced brain atrophy.
Conclusion: This plasma metabolomic study provides a valuable resource for enhancing our understanding of alcohol-induced brain atrophy and offers potential targets for therapeutic intervention.
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| http://dx.doi.org/10.3389/fnmol.2022.999938 | DOI Listing |
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