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Li G, Zhong D, Zhang N, Dong J, Yan Y, Xu Q, Xu S, Yang L, Hao D, Li CSR. The inter-related effects of alcohol use severity and sleep deficiency on semantic processing in young adults. Neuroscience 2024; 555:116-124. [PMID: 39059740 DOI: 10.1016/j.neuroscience.2024.07.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 06/24/2024] [Accepted: 07/16/2024] [Indexed: 07/28/2024]
Abstract
BACKGROUND Both alcohol misuse and sleep deficiency are associated with deficits in semantic processing. However, alcohol misuse and sleep deficiency are frequently comorbid and their inter-related effects on semantic processing as well as the underlying neural mechanisms remain to be investigated. METHODS We curated the Human Connectome Project data of 973 young adults (508 women) to examine the neural correlates of semantic processing in link with the severity of alcohol use and sleep deficiency. The latter were each evaluated using the first principal component (PC1) of principal component analysis of all drinking metrics and the Pittsburgh Sleep Quality Index (PSQI). We employed path modeling to elucidate the interplay among clinical, behavioral, and neural variables. RESULTS Among women, we observed a significant negative correlation between the left precentral gyrus (PCG) and PSQI scores. Mediation analysis revealed that the left PCG activity fully mediated the relationship between PSQI scores and word comprehension in language tasks. In women alone also, the right middle frontal gyrus (MFG) exhibited a significant negative correlation with PC1. The best path model illustrated the associations among PC1, PSQI scores, PCG activity, and MFG activation during semantic processing in women. CONCLUSIONS Alcohol misuse may lead to reduced MFG activation while sleep deficiency hinder semantic processing by suppressing PCG activity in women. The pathway model underscores the influence of sleep quality and alcohol consumption severity on semantic processing in women, suggesting that sex differences in these effects need to be further investigated.
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Affiliation(s)
- Guangfei Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Dandan Zhong
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Ning Zhang
- Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology, Sleep Center, Department of Neurology, China National Clinical Research Center of Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianyu Dong
- Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology, Sleep Center, Department of Neurology, China National Clinical Research Center of Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yan Yan
- The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
| | - Qixiao Xu
- Physical Education Department, Beijing University of Technology, Beijing, China
| | - Shuchun Xu
- Traditional Chinese Medicine Department, the University Hospital of Beijing University of Technology, Beijing, China
| | - Lin Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Dongmei Hao
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China.
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA; Wu Tsai Institute, Yale University, New Haven, CT, USA.
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Li Y, Yang L, Hao D, Chen Y, Ye-Lin Y, Li CSR, Li G. Functional Networks of Reward and Punishment Processing and Their Molecular Profiles Predicting the Severity of Young Adult Drinking. Brain Sci 2024; 14:610. [PMID: 38928610 PMCID: PMC11201596 DOI: 10.3390/brainsci14060610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 06/15/2024] [Accepted: 06/16/2024] [Indexed: 06/28/2024] Open
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.
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Affiliation(s)
- Yashuang Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing 100124, China; (Y.L.)
| | - Lin Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing 100124, China; (Y.L.)
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, 46022 Valencia, Spain
| | - Dongmei Hao
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing 100124, China; (Y.L.)
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, 46022 Valencia, Spain
| | - Yu Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA (C.-S.R.L.)
| | - Yiyao Ye-Lin
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, 46022 Valencia, Spain
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022 Valencia, Spain
| | - Chiang-Shan Ray Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA (C.-S.R.L.)
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06511, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06511, USA
| | - Guangfei Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing 100124, China; (Y.L.)
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, 46022 Valencia, Spain
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Othman EA. Editorial for "Cognitive Challenges Are Better in Distinguishing Binge From Nonbinge Drinkers: An Exploratory Deep-Learning Study of fMRI Data of Multiple Behavioral Tasks and Resting State". J Magn Reson Imaging 2023; 57:869-870. [PMID: 35822452 DOI: 10.1002/jmri.28350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 06/27/2022] [Indexed: 11/08/2022] Open
Affiliation(s)
- Elza Azri Othman
- School of Medical Imaging, Faculty of Health Sciences, Universiti Sultan Zainal Abidin, Kuala Nerus, Terengganu, 21300, Malaysia
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