Brain structural covariance network features are robust markers of early heavy alcohol use

Author:

Ottino‐González Jonatan12ORCID,Cupertino Renata B.3ORCID,Cao Zhipeng2ORCID,Hahn Sage2ORCID,Pancholi Devarshi2,Albaugh Matthew D.2ORCID,Brumback Ty4ORCID,Baker Fiona C.5ORCID,Brown Sandra A.6ORCID,Clark Duncan B.7,de Zambotti Massimiliano5ORCID,Goldston David B.8ORCID,Luna Beatriz7ORCID,Nagel Bonnie J.9ORCID,Nooner Kate B.10ORCID,Pohl Kilian M.511ORCID,Tapert Susan F.12ORCID,Thompson Wesley K.13ORCID,Jernigan Terry L.14ORCID,Conrod Patricia15ORCID,Mackey Scott2ORCID,Garavan Hugh2ORCID

Affiliation:

1. Division of Endocrinology The Saban Research Institute, Children's Hospital Los Angeles Los Angeles CA USA

2. Department of Psychiatry University of Vermont Larner College of Medicine Burlington VT USA

3. Department of Genetics University of California San Diego San Diego CA USA

4. Department of Psychological Science Northern Kentucky University Highland Heights KY USA

5. Center for Health Sciences, SRI International Menlo Park CA USA

6. Departments of Psychology and Psychiatry University of California San Diego, La Jolla CA USA

7. Department of Psychiatry University of Pittsburgh Pittsburgh PA USA

8. Department of Psychiatry and Behavioral Sciences Duke University School of Medicine Durham NC USA

9. Departments of Psychiatry and Behavioral Neuroscience Oregon Health and Science University Portland OR USA

10. Department of Psychology University of North Carolina Wilmington Wilmington NC USA

11. Department of Psychiatry and Behavioral Sciences Stanford University Stanford CA USA

12. Department of Psychiatry University of California San Diego San Diego CA USA

13. Department of Radiology University of California San Diego San Diego CA USA

14. Center for Human Development University of California San Diego CA USA

15. Department of Psychiatry Université de Montreal, CHU Ste Justine Hospital Montreal Québec Canada

Abstract

AbstractBackground and AimsRecently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)‐derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies.Design and SettingCross‐sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14–22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17–22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22–37 years).CasesCases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected.MeasurementsGraph theory metrics of segregation and integration were used to summarize SCN.FindingsMirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = −0.029, P = 0.002], lower modularity (AUC = −0.14, P = 0.004), lower average shortest path length (AUC = −0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = −0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar.ConclusionStructural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN‐derived metrics to detect brain‐related psychopathology.

Funder

National Institute on Alcohol Abuse and Alcoholism

National Institute on Drug Abuse

National Institute of Mental Health

National Institute of Child Health and Human Development

Publisher

Wiley

Subject

Psychiatry and Mental health,Medicine (miscellaneous)

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