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Author:

Li, Y. (Li, Y..) | Yang, L. (Yang, L..) | Hao, D. (Hao, D..) | Chen, Y. (Chen, Y..) | Ye-Lin, Y. (Ye-Lin, Y..) | Li, C.-S.R. (Li, C.-S.R..) | Li, G. (Li, G..)

Indexed by:

Scopus SCIE

Abstract:

Alcohol misuse is associated with altered punishment and reward processing. Here, we investigated neural network responses to reward and punishment and the molecular profiles of the connectivity features predicting alcohol use severity in young adults. We curated the Human Connectome Project data and employed connectome-based predictive modeling (CPM) to examine how functional connectivity (FC) features during wins and losses are associated with alcohol use severity, quantified by Semi-Structured Assessment for the Genetics of Alcoholism, in 981 young adults. We combined the CPM findings and the JuSpace toolbox to characterize the molecular profiles of the network connectivity features of alcohol use severity. The connectomics predicting alcohol use severity appeared specific, comprising less than 0.12% of all features, including medial frontal, motor/sensory, and cerebellum/brainstem networks during punishment processing and medial frontal, fronto-parietal, and motor/sensory networks during reward processing. Spatial correlation analyses showed that these networks were associated predominantly with serotonergic and GABAa signaling. To conclude, a distinct pattern of network connectivity predicted alcohol use severity in young adult drinkers. These “neural fingerprints” elucidate how alcohol misuse impacts the brain and provide evidence of new targets for future intervention. © 2024 by the authors.

Keyword:

neurotransmitter alcohol misuse alcohol use disorder fMRI receptor connectome

Author Community:

  • [ 1 ] [Li Y.]Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing, 100124, China
  • [ 2 ] [Yang L.]Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing, 100124, China
  • [ 3 ] [Yang L.]Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, 100124, China
  • [ 4 ] [Yang L.]BJUT-UPV Joint Research Laboratory in Biomedical Engineering, Valencia, 46022, Spain
  • [ 5 ] [Hao D.]Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing, 100124, China
  • [ 6 ] [Hao D.]Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, 100124, China
  • [ 7 ] [Hao D.]BJUT-UPV Joint Research Laboratory in Biomedical Engineering, Valencia, 46022, Spain
  • [ 8 ] [Chen Y.]Department of Psychiatry, Yale University School of Medicine, New Haven, 06510, CT, United States
  • [ 9 ] [Ye-Lin Y.]BJUT-UPV Joint Research Laboratory in Biomedical Engineering, Valencia, 46022, Spain
  • [ 10 ] [Ye-Lin Y.]Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, Valencia, 46022, Spain
  • [ 11 ] [Li C.-S.R.]Department of Psychiatry, Yale University School of Medicine, New Haven, 06510, CT, United States
  • [ 12 ] [Li C.-S.R.]Department of Neuroscience, Yale University School of Medicine, New Haven, 06511, CT, United States
  • [ 13 ] [Li C.-S.R.]Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, 06520, CT, United States
  • [ 14 ] [Li C.-S.R.]Wu Tsai Institute, Yale University, New Haven, 06511, CT, United States
  • [ 15 ] [Li G.]Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing, 100124, China
  • [ 16 ] [Li G.]Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, 100124, China
  • [ 17 ] [Li G.]BJUT-UPV Joint Research Laboratory in Biomedical Engineering, Valencia, 46022, Spain

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Source :

Brain Sciences

ISSN: 2076-3425

Year: 2024

Issue: 6

Volume: 14

3 . 3 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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