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Mega‐analysis of the brain‐age gap in substance use disorder: An ENIGMA Addiction working group study.

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Title: Mega‐analysis of the brain‐age gap in substance use disorder: An ENIGMA Addiction working group study.
Authors: Scheffler, Freda, Ipser, Jonathan, Pancholi, Devarshi, Murphy, Alistair, Cao, Zhipeng, Ottino‐González, Jonatan, Batalla, A., Brady, K. T., Cousijn, J., Dagher, A., Filbey, F. M., Foxe, J. J., Garza‐Villarreal, E. A., Goudriaan, A. E., Hester, R. H., Hutchison, K. E., Kaag, A. M., Kroon, E., Li, C. R., London, E. D.
Source: Addiction. Nov2024, Vol. 119 Issue 11, p1937-1946. 10p.
Subjects: Brain physiology, Substance abuse, Cross-sectional method, Research funding, Magnetic resonance imaging, Amphetamines, Descriptive statistics, World health, Alcohol-induced disorders, Machine learning, Neuroradiology, Algorithms, Disease complications
Abstract: Background and Aims: The brain age gap (BAG), calculated as the difference between a machine learning model‐based predicted brain age and chronological age, has been increasingly investigated in psychiatric disorders. Tobacco and alcohol use are associated with increased BAG; however, no studies have compared global and regional BAG across substances other than alcohol and tobacco. This study aimed to compare global and regional estimates of brain age in individuals with substance use disorders and healthy controls. Design: This was a cross‐sectional study. Setting: This is an Enhancing Neuro Imaging through Meta‐Analysis Consortium (ENIGMA) Addiction Working Group study including data from 38 global sites. Participants: This study included 2606 participants, of whom 1725 were cases with a substance use disorder and 881 healthy controls. Measurements: This study used the Kaufmann brain age prediction algorithms to generate global and regional brain age estimates using T1 weighted magnetic resonance imaging (MRI) scans. We used linear mixed effects models to compare global and regional (FreeSurfer lobestrict output) BAG (i.e. predicted minus chronological age) between individuals with one of five primary substance use disorders as well as healthy controls. Findings Alcohol use disorder (β = −5.49, t = −5.51, p < 0.001) was associated with higher global BAG, whereas amphetamine‐type stimulant use disorder (β = 3.44, t = 2.42, p = 0.02) was associated with lower global BAG in the separate substance‐specific models. Conclusions: People with alcohol use disorder appear to have a higher brain‐age gap than people without alcohol use disorder, which is consistent with other evidence of the negative impact of alcohol on the brain. [ABSTRACT FROM AUTHOR]
Copyright of Addiction is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Background and Aims: The brain age gap (BAG), calculated as the difference between a machine learning model‐based predicted brain age and chronological age, has been increasingly investigated in psychiatric disorders. Tobacco and alcohol use are associated with increased BAG; however, no studies have compared global and regional BAG across substances other than alcohol and tobacco. This study aimed to compare global and regional estimates of brain age in individuals with substance use disorders and healthy controls. Design: This was a cross‐sectional study. Setting: This is an Enhancing Neuro Imaging through Meta‐Analysis Consortium (ENIGMA) Addiction Working Group study including data from 38 global sites. Participants: This study included 2606 participants, of whom 1725 were cases with a substance use disorder and 881 healthy controls. Measurements: This study used the Kaufmann brain age prediction algorithms to generate global and regional brain age estimates using T1 weighted magnetic resonance imaging (MRI) scans. We used linear mixed effects models to compare global and regional (FreeSurfer lobestrict output) BAG (i.e. predicted minus chronological age) between individuals with one of five primary substance use disorders as well as healthy controls. Findings Alcohol use disorder (β = −5.49, t = −5.51, p &lt; 0.001) was associated with higher global BAG, whereas amphetamine‐type stimulant use disorder (β = 3.44, t = 2.42, p = 0.02) was associated with lower global BAG in the separate substance‐specific models. Conclusions: People with alcohol use disorder appear to have a higher brain‐age gap than people without alcohol use disorder, which is consistent with other evidence of the negative impact of alcohol on the brain. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Addiction is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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