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Antwi I, Watkins D, Pedawi A, Ghrayeb A, Van de Vuurst C, Cory TJ. Substances of abuse and their effect on SAR-CoV-2 pathogenesis. NEUROIMMUNE PHARMACOLOGY AND THERAPEUTICS 2023; 2:301-316. [PMID: 38013836 PMCID: PMC10474379 DOI: 10.1515/nipt-2023-0004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 07/19/2023] [Indexed: 11/29/2023]
Abstract
Following the emergence of SARS-CoV-2, various reports suggest that there has been a significant increase in substance abuse due to social distancing and related issues. Several reports have suggested the impact of chronic substance use on individuals' physiological and psychological health. Therefore, there is a need to know the impact of SARS-CoV-2 on persons with substance use disorders. Individuals with substance use disorders are the most vulnerable groups and are at a high risk of SARS-CoV-2 infection due to their already existing health issues associated with substance use. This review discusses some of the molecular and systemic/organic effects chronic substance use such as alcohol, nicotine, marijuana (cannabis), opioids, methamphetamine, and cocaine have on SARS-CoV-2 infectivity and its potential cause for worsened disease outcomes in persons with substance use disorder. This will provide healthcare providers, public health policies, and researchers with the needed knowledge to address some of the many challenges faced during the Covid-19 pandemic to facilitate treatment strategies for persons with substance use disorders.
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Affiliation(s)
- Ivy Antwi
- Department of Clinical Pharmacy, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Destiny Watkins
- Department of Clinical Pharmacy, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Alahn Pedawi
- Department of Clinical Pharmacy, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Atheel Ghrayeb
- Department of Clinical Pharmacy, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Christine Van de Vuurst
- Department of Clinical Pharmacy, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Theodore J. Cory
- Department of Clinical Pharmacy, College of Pharmacy, University of Tennessee Health Science Center, Memphis, TN, USA
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Chen W, Zeng Y, Suo C, Yang H, Chen Y, Hou C, Hu Y, Ying Z, Sun Y, Qu Y, Lu D, Fang F, Valdimarsdóttir UA, Song H. Genetic predispositions to psychiatric disorders and the risk of COVID-19. BMC Med 2022; 20:314. [PMID: 35999565 PMCID: PMC9397166 DOI: 10.1186/s12916-022-02520-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 08/08/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Whether a genetic predisposition to psychiatric disorders is associated with coronavirus disease 2019 (COVID-19) is unknown. METHODS Our analytic sample consisted of 287,123 white British participants in UK Biobank who were alive on 31 January 2020. We performed a genome-wide association study (GWAS) analysis for each psychiatric disorder (substance misuse, depression, anxiety, psychotic disorder, and stress-related disorders) in a randomly selected half of the study population ("base dataset"). For the other half ("target dataset"), the polygenic risk score (PRS) was calculated as a proxy of individuals' genetic predisposition to a given psychiatric phenotype using discovered genetic variants from the base dataset. Ascertainment of COVID-19 was based on the Public Health England dataset, inpatient hospital data, or death registers in UK Biobank. COVID-19 cases from hospitalization records or death records were considered "severe cases." The association between the PRS for psychiatric disorders and COVID-19 risk was examined using logistic regression. We also repeated PRS analyses based on publicly available GWAS summary statistics. RESULTS A total of 143,562 participants (including 10,868 COVID-19 cases) were used for PRS analyses. A higher genetic predisposition to psychiatric disorders was associated with an increased risk of any COVID-19 and severe COVID-19. The adjusted odds ratio (OR) for any COVID-19 was 1.07 (95% confidence interval [CI] 1.02-1.13) and 1.06 (95% CI 1.01-1.11) among individuals with a high genetic risk (above the upper tertile of the PRS) for substance misuse and depression, respectively, compared with individuals with a low genetic risk (below the lower tertile). Slightly higher ORs were noted for severe COVID-19, and similar result patterns were obtained in analyses based on publicly available GWAS summary statistics. CONCLUSIONS Our findings suggest a potential role of genetic factors in the observed phenotypic association between psychiatric disorders and COVID-19. Our data underscore the need for increased medical surveillance for this vulnerable population during the COVID-19 pandemic.
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Affiliation(s)
- Wenwen Chen
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China.,Division of Nephrology, Kidney Research Institute, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Yu Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Chen Suo
- Department of Epidemiology & Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
| | - Huazhen Yang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yilong Chen
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Can Hou
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yao Hu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Zhiye Ying
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yajing Sun
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yuanyuan Qu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Donghao Lu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.,Med-X Center for Informatics, Sichuan University, Chengdu, China.,Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden.,Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Fang Fang
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Unnur A Valdimarsdóttir
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden.,Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA.,Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Huan Song
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China. .,Med-X Center for Informatics, Sichuan University, Chengdu, China. .,Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland.
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Cabral P. E-cigarette use and intentions related to psychological distress among cigarette, e-cigarette, and cannabis vape users during the start of the COVID-19 pandemic. BMC Psychol 2022; 10:201. [PMID: 35971158 PMCID: PMC9376900 DOI: 10.1186/s40359-022-00910-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 08/01/2022] [Indexed: 11/10/2022] Open
Abstract
Background This study examines associations between psychological distress, intentions to use e-cigarettes, and cigarette smoking, e-cigarette use, and cannabis consumption through e-cigarette use among a diverse sample of U.S. young adults. Procedures Young adults (N = 314; 72.5% female) were recruited to complete an online survey during the first few months of the COVID-19 pandemic. Results Associations between psychological distress and cigarette smoking, e-cigarette use, cannabis vaping, and intentions to use e-cigarettes were found. Current e-cigarette use (OR = 1.23, 95% CI 1.17, 1.28, p < .001; 7.5%) and cannabis vaping (OR = 2.03, 95% CI 1.88, 2.18, p < .001; 10%) was higher among female, possibly due to the significantly higher psychological distress reported among females. Interactions between intentions to use e-cigarettes and psychological distress variables were found for all smoking and vaping behaviors. Conclusions Public health efforts should increase focus on providing psychological services for young adults to improve coping strategies that are alternative to smoking and vaping behaviors.
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Affiliation(s)
- Patricia Cabral
- Department of Psychology, Occidental College, 1600 Campus Road, Los Angeles, CA, 90041, USA.
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