Brain structural covariance network differences in adults with alcohol dependence and heavy-drinking adolescents
Publication year
2022Author(s)
Number of pages
14 p.
Source
Addiction, 117, 5, (2022), pp. 1312-1325ISSN
Publication type
Article / Letter to editor
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Organization
SW OZ BSI OGG
Journal title
Addiction
Volume
vol. 117
Issue
iss. 5
Languages used
English (eng)
Page start
p. 1312
Page end
p. 1325
Subject
Developmental PsychopathologyAbstract
Background and aims: Graph theoretic analysis of structural covariance networks (SCN) provides an assessment of brain organization that has not yet been applied to alcohol dependence (AD). We estimated whether SCN differences are present in adults with AD and heavy drinking adolescents at age 19 and age 14, prior to substantial exposure to alcohol. Design: Cross-sectional sample of adults and a cohort of adolescents. Correlation matrices for cortical thicknesses across 68 regions were summarized with graph theoretic metrics. Setting and participants: 745 adults with AD and 979 non-dependent controls from 24 sites curated by the ENIGMA-Addiction working group, and 297 hazardous drinking adolescents and 594 controls at age 14 and 19 from the IMAGEN study, all from Europe. Measurements: Metrics of network segregation (modularity, clustering coefficient, and local efficiency) and integration (average shortest path length and global efficiency). Findings: The younger AD adults had lower network segregation and higher integration relative to non-dependent controls. Compared with controls, the hazardous drinkers at age 19 showed lower modularity (Area-under-the-curve [AUC] difference = -0.0142, confidence interval [CI] 95% [-0.1333, 0.0092]; p-value = 0.017), clustering coefficient (AUC difference = -0.0164 CI 95% [-0.1456, 0.0043], p-value = 0.008), and local efficiency (AUC difference = -0.0141 CI 95% [-0.0097, 0.0034], p-value = 0.010), as well as lower average shortest path length (AUC difference = -0.0405 CI 95% [-0.0392, 0.0096]; p-value = 0.021) and higher global efficiency (AUC difference = 0.0044 CI 95% [-0.0011, 0.0043]; p-value = 0.023). The same pattern was present at age 14 with lower clustering coefficient (AUC difference = -0.0131 CI 95% [-0.1304, 0.0033]; p-value = 0.024), lower average shortest path length (AUC difference = -0.0362 CI 95% [-0.0334, 0.0118]; p-value = 0.019), and higher global efficiency (AUC difference = 0.0035 CI 95% [-0.0011, 0.0038]; p-value = 0.048). Conclusions: Cross-sectional analyses indicate a specific structural covariance network profile is an early marker of alcohol dependence in adults. Similar effects in a cohort of heavy drinking adolescents, observed both at age 19 and prior to substantial alcohol exposure at age 14, suggest that this pattern may be a pre-existing risk factor for problematic drinking.
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- Academic publications [246936]
- Electronic publications [134293]
- Faculty of Social Sciences [30577]
- Open Access publications [107816]
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