UCSF

Objective

Little is known about the effects of polysubstance use and cigarette smoking on brain morphometry. This study examined neocortical brain morphometric differences between abstinent polysubstance dependent and alcohol-only dependent treatment seekers (ALC) as well as light drinking controls (CON), the associations of cigarette smoking in these polysubstance users (PSU), and morphometric relationships to cognition and inhibitory control.

Methods

All participants completed extensive neuropsychological assessments and 4 Tesla brain magnetic resonance imaging. PSU and ALC were abstinent for one month at the time of study. Parcellated morphological data (volume, surface area, thickness) were obtained with FreeSurfer methodology for the following bilateral components: dorso-prefrontal cortex (DPFC), anterior cingulate cortex (ACC), orbitofrontal cortex (OFC), and insula. Regional group differences were examined and structural data correlated with domains of cognition and inhibitory control.

Results

PSU had significantly smaller left OFC volume and surface area and trends to smaller right DPFC volume and surface area compared to CON; PSU did not differ significantly from ALC on these measures. PSU, however, had significantly thinner right ACC than ALC. Smoking PSU had significantly larger right OFC surface area than non-smoking PSU. No significant relationships between morphometry and quantity/frequency of substance use, alcohol use, or age of onset of heavy drinking were observed. PSU exhibited distinct relationships between brain structure and processing speed, cognitive efficiency, working memory and inhibitory control that were not observed in ALC or CON.

Conclusion

Polysubstance users have unique morphometric abnormalities and structure-function relationships when compared to individuals dependent only on alcohol and light drinking controls. Chronic cigarette smoking is associated with structural brain irregularities in polysubstance users. Further elucidation of these distinctive characteristics could help inform the development of targeted and thus potentially more effective treatments in this large but understudied population.