Multi-modal MRI classifiers identify excessive alcohol consumption and treatment effects in the brain.
Robust neuroimaging markers of neuropsychiatric disorders have proven difficult to obtain. In alcohol use disorders, profound brain structural deficits can be found in severe alcoholic patients, but the heterogeneity of unimodal MRI measurements has so far precluded the identification of selective biomarkers, especially for early diagnosis. In the present work we used a combination of multiple MRI modalities to provide comprehensive and insightful descriptions of brain tissue microstructure. We performed a longitudinal experiment using Marchigian-Sardinian (msP) rats, an established model of chronic excessive alcohol consumption, and acquired multi-modal images before and after 1 month of alcohol consumption (6.8 ± 1.4 g/kg/day, mean ± SD), as well as after 1 week of abstinence with or without concomitant treatment with the antirelapse opioid antagonist naltrexone (2.5 mg/kg/day). We found remarkable sensitivity and selectivity to accurately classify brains affected by alcohol even after the relative short exposure period. One month drinking was enough to imprint a highly specific signature of alcohol consumption. Brain alterations were regionally specific and affected both gray and white matter and persisted into the early abstinence state without any detectable recovery. Interestingly, naltrexone treatment during early abstinence resulted in subtle brain changes that could be distinguished from non-treated abstinent brains, suggesting the existence of an intermediate state associated with brain recovery from alcohol exposure induced by medication. The presented framework is a promising tool for the development of biomarkers for clinical diagnosis of alcohol use disorders, with capacity to further inform about its progression and response to treatment.
Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Spain.|Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain.
Alejandro
A
Cosa
Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Spain.
Andrea
A
Moreno
Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Spain.
Jesús
J
Pacheco-Torres
School of Pharmacy University of Camerino, Camerino, Italy.
Roberto
R
Ciccocioppo
Department of Pharmacology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Petri
P
Hyytiä
Department of Psychopharmacology, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany.
Wolfgang H
WH
Sommer
Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain.
David
http://orcid.org/0000-0002-2825-3646
D
Moratal
Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Spain.
Santiago
S
Canals
D000428:Alcohol Drinking; D000437:Alcoholism; D000818:Animals; D001921:Brain / Q000000981:diagnostic imaging / Q000187:drug effects*; D002492:Central Nervous System Depressants / Q000494:pharmacology*; D004195:Disease Models, Animal; D000431:Ethanol / Q000494:pharmacology*; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging; D009271:Naltrexone / Q000494:pharmacology; D009292:Narcotic Antagonists / Q000494:pharmacology; D051381:Rats
D002492:Central Nervous System Depressants; D009292:Narcotic Antagonists; D000431:Ethanol; D009271:Naltrexone
alcohol use disorders; classification algorithms; machine learning; multi-modal MRI; naltrexone; rat