ArticleDrug and alcohol dependence2022
White matter microstructure differences in individuals with dependence on cocaine, methamphetamine, and nicotine: Findings from the ENIGMA-Addiction working group.
Article in Drug and alcohol dependence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 27 citations in OpenAlex.
- Along-Tract Microstructural Alterations Associated with Stimulant Misuse Localized using Diffusion MRI Tractometry.bioRxiv : the preprint server for biology · 2026Article
- Phenome-wide analysis of genetically imputed neuroimaging phenotypes reveals associations with psychiatric traits in a multi-ancestry cohort.medRxiv : the preprint server for health sciences · 2025Article
- The mesocorticolimbic system in stimulant use disorder.Molecular psychiatry · 2025Review
- Family History of Substance Use and Stressful Life Events Impact Adolescent Maturation of Cerebral White Matter.Addiction biology · 2025Article
- Repetitive transcranial magnetic stimulation reduces nicotine dependence and potentially modulates white matter microstructure in smokers: a pilot study by diffusion spectrum imaging.Frontiers in neurology · 2025Article
- Frontal White Matter Changes and Craving Recovery in Inpatients With Heroin Use Disorder.JAMA network open · 2024Article
- Methamphetamine-related working memory difficulties underpinned by reduced frontoparietal responses.Addiction biology · 2024Article
- Brain dysfunctions and neurotoxicity induced by psychostimulants in experimental models and humans: an overview of recent findings.Neural regeneration research · 2024Article
- Transcranial magnetic stimulation for methamphetamine use disorder: A scoping review within the neurocircuitry model of addiction.Psychiatry research · 2024Article
- FRONTAL WHITE MATTER CHANGES INDICATE RECOVERY WITH INPATIENT TREATMENT IN HEROIN ADDICTION.medRxiv : the preprint server for health sciences · 2024Article
- Imaging neuroinflammation in individuals with substance use disorders.The Journal of clinical investigation · 2024Review
- Comparison of three magnetic resonance imaging measures of brain iron in healthy and cocaine use disorder participants.NMR in biomedicine · 2024Article
- Neurological, Behavioral, and Pathophysiological Characterization of the Co-Occurrence of Substance Use and HIV: A Narrative Review.Brain sciences · 2023Review
- Chronic Cocaine Use and White Matter Coherence: A Diffusion Tensor Imaging Study.Journal of studies on alcohol and drugs · 2023Article
- Whole-brain white matter abnormalities in human cocaine and heroin use disorders: association with craving, recency, and cumulative use.Molecular psychiatry · 2023Article
- Association between white matter microstructure and cognitive function in patients with methamphetamine use disorder.Human brain mapping · 2023Article
- The evolution of Big Data in neuroscience and neurology.Journal of big data · 2023Article
- Brain tract structure predicts relapse to stimulant drug use.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- White matter alterations in chronic MDMA use: Evidence from diffusion tensor imaging and neurofilament light chain blood levels.NeuroImage. Clinical · 2022Article
Corrections and comments
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Authors and funding
31 authors at 13 institutions in 6 countries.
Funding
Abstract
backgroundNicotine and illicit stimulants are very addictive substances. Although associations between grey matter and dependence on stimulants have been frequently reported, white matter correlates have received less attention.
methodsEleven international sites ascribed to the ENIGMA-Addiction consortium contributed data from individuals with dependence on cocaine (n = 147), methamphetamine (n = 132) and nicotine (n = 189), as well as non-dependent controls (n = 333). We compared the fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) of 20 bilateral tracts. Also, we compared the performance of various machine learning algorithms in deriving brain-based classifications on stimulant dependence.
resultsThe cocaine and methamphetamine groups had lower regional FA and higher RD in several association, commissural, and projection white matter tracts. The methamphetamine dependent group additionally showed lower regional AD. The nicotine group had lower FA and higher RD limited to the anterior limb of the internal capsule. The best performing machine learning algorithm was the support vector machine (SVM). The SVM successfully classified individuals with dependence on cocaine (AUC = 0.70, p < 0.001) and methamphetamine (AUC = 0.71, p < 0.001) relative to non-dependent controls. Classifications related to nicotine dependence proved modest (AUC = 0.62, p = 0.014).
conclusionsStimulant dependence was related to FA disturbances within tracts consistent with a role in addiction. The multivariate pattern of white matter differences proved sufficient to identify individuals with stimulant dependence, particularly for cocaine and methamphetamine.
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