Journal: BMC Medical Genomics, 2021, doi: 10.1186/s12920-021-01035-5
Authors: Alannah Hillmer, Caroul Chawar, Stephanie Sanger, Alessia D’Elia, Mehreen Butt, Raveena Kapoor, Flavio Kapczinski, Lehana Thabane & Zainab Samaan
Abstract:
Background: With the increase in cannabis use rates, cannabis use disorder is being reported as one of the most common drug use disorders globally. Cannabis use has several known physical, psychological, and social adverse events, such as altered judgement, poor educational outcomes, and respiratory symptoms. The propensity for taking cannabis and the development of a cannabis use disorder may be genetically influenced for some individuals. Heritability estimates suggest a genetic basis for cannabis use, and several genome-wide association studies (GWASs) have identified possible regions of association, albeit with inconsistent findings. This systematic review aims to summarize the findings from GWASs investigating cannabis use and cannabis use disorder.
Methods: This systematic review incorporates articles that have performed a GWAS investigating cannabis use or cannabis use disorder. MEDLINE, Web of Science, EMBASE, CINAHL, GWAS Catalog, GWAS Central, and NIH Database of Genotype and Phenotype were searched using a comprehensive search strategy. All studies were screened in duplicate, and the quality of evidence was assessed using the quality of genetic association studies (Q-Genie) tool. All studies underwent qualitative synthesis; however, quantitative analysis was not feasible.
Results: Our search identified 5984 articles. Six studies met our eligibility criteria and were included in this review. All six studies reported results that met our significance threshold of p ≤ 1.0 × 10–7. In total 96 genetic variants were identified. While meta-analysis was not possible, this review identified the following genes, ANKFN1, INTS7, PI4K2B, CSMD1, CST7, ACSS1, and SCN9A, to be associated with cannabis use. These regions were previously reported in different mental health conditions, however not in relation to cannabis use.
Conclusion: This systematic review summarized GWAS findings within the field of cannabis research. While a meta-analysis was not possible, the summary of findings serves to inform future candidate gene studies and replication efforts.
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Journal: NBER Working Paper No. 29038, 2021, doi: 10.3386/w29038
Authors: Joseph J. Sabia, Dhaval M. Dave, Fawaz Alotaibi & Daniel I. Rees
Abstract:
Recreational marijuana laws (RMLs), which legalize the possession of small quantities of marijuana for recreational use, have been adopted by 18 states and the District of Columbia. Opponents argue that RML-induced increases in marijuana consumption will serve as a “gateway” to harder drug use and crime. Using data covering the period 2000-2019 from a variety of national sources (the National Survey of Drug Use and Health, the Uniform Crime Reports, the National Vital Statistics System, and the Treatment Episode Data Set) this study is the first to comprehensively examine the effects of legalizing recreational marijuana on hard drug use, arrests, drug overdose deaths, suicides, and treatment admissions. Our analyses show that RMLs increase adult marijuana use and reduce drug-related arrests over an average post-legalization window of three to four years. There is little evidence to suggest that RML-induced increases in marijuana consumption encourage the use of harder substances or violent criminal activity.
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Journal: Translational Research, 2021, doi: 10.1016/j.trsl.2021.03.018
Authors: Charles Marks, Gabriel Carrasco-Escobar, Rocío Carrasco-Hernández, Steffanie A Strathdee, Davey Smith & Annick Bórquez
Abstract:
The opioid crisis in the United States has been defined by waves of drug- and locality-specific Opioid use-Related Epidemics (OREs) of overdose and bloodborne infections, among a range of health harms. The ability to identify localities at risk of such OREs, and better yet, to predict which ones will experience them, holds the potential to mitigate further morbidity and mortality. This narrative review was conducted to identify and describe quantitative approaches aimed at the “risk assessment,” “detection” or “prediction” of OREs in the United States. We implemented a PubMed search composed of the: (1) objective (eg, prediction), (2) epidemiologic outcome (eg, outbreak), (3) underlying cause (ie, opioid use), (4) health outcome (eg, overdose, HIV), (5) location (ie, US). In total, 46 studies were included, and the following information extracted: discipline, objective, health outcome, drug/substance type, geographic region/unit of analysis, and data sources. Studies identified relied on clinical, epidemiological, behavioral and drug markets surveillance and applied a range of methods including statistical regression, geospatial analyses, dynamic modeling, phylogenetic analyses and machine learning. Studies for the prediction of overdose mortality at national/state/county and zip code level are rapidly emerging. Geospatial methods are increasingly used to identify hotspots of opioid use and overdose. In the context of infectious disease OREs, routine genetic sequencing of patient samples to identify growing transmission clusters via phylogenetic methods could increase early detection capacity. A coordinated implementation of multiple, complementary approaches would increase our ability to successfully anticipate outbreak risk and respond preemptively. We present a multi-disciplinary framework for the prediction of OREs in the US and reflect on challenges research teams will face in implementing such strategies along with good practices.
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Journal: International Journal of Mental Health and Addiction, 2021, doi: 10.1007/s11469-021-00604-0
Authors: Scott Graupensperger, Jennifer M. Cadigan, Clare Einberger & Christine M. Lee
Abstract:
Alongside direct health concerns pertaining to the SARS-CoV-2 virus, the stressors and life disruptions associated with the COVID-19 pandemic may provoke secondary concerns for health and well-being. The implications of COVID-19-related stressors may be particularly salient for young adults, who are at higher-risk for mental health concerns and substance use behaviors. We developed a multifaceted scale that assessed distinct domains of COVID-19-related stressors and examined associations between these stressors and indices of mental health, well-being, and substance use (alcohol and marijuana use). In April—June of 2020, 1181 young adults were recruited from two- and four-year colleges to participate in this study (Mage = 20.40; 59.95% women). Exploratory factor analysis identified five domains of COVID-19-related stressors: job insecurity, social/relational, financial, illness-related, and school-related. The overall pattern of results indicated that COVID-19-related stressors were related to poorer mental health and well-being. Social/relational stressors emerged as a primary concern most strongly associated with indices of mental health and alcohol use, relative to other stressors. However, illness-related stressors and school-related stressors were associated with less alcohol use. Stressors associated with the COVID-19 pandemic may impact young adults’ health and well-being but disentangling various stressor domains informs more tailored intervention and prevention strategies.
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Journal: JMIR Mental Health, 2021, doi: 10.2196/26873.
Authors: Minda A Gowarty, Meghan R Longacre, Roger Vilardaga, Nathan J Kung, Ashley E Gaughan-Maher & Mary F Brunette
Abstract:
Background: Young adults with serious mental illness (SMI) have higher smoking rates and lower cessation rates than young adults without SMI. Scalable interventions such as smartphone apps with evidence-based content (eg, the National Cancer Institute’s [NCI’s] QuitGuide and quitSTART) could increase access to potentially appealing and effective treatment for this group but have yet to be tested in this population.
Objective: The goal of this user-centered design study is to determine the user experience (including usability and acceptability) of 2 widely available apps developed by the NCI-QuitGuide and quitSTART-among young adult tobacco users with SMI.
Methods: We conducted usability and acceptability testing of QuitGuide and quitSTART among participants with SMI aged between 18 and 35 years who were stable in community mental health treatment between 2019 and 2020. Participants were randomly assigned to use QuitGuide or quitSTART on their smartphones. App usability was evaluated at baseline and following a 2-week field test of independent use via a video-recorded task completion protocol. Using a mixed method approach, we triangulated 4 data sources: nonparticipant observation, open-ended interviews, structured interviews (including the System Usability Scale [SUS]), and backend app use data obtained from the NCI. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using thematic analysis.
Results: Participants were 17 smokers who were not interested in quitting, with a mean age of 29 (SD 4) years; 41% (n=7) presented with psychotic disorders. Participants smoked an average of 15 (SD 7) cigarettes per day. The mean SUS scores for QuitGuide were similar at visits one and two (mean 64, SD 18 and mean 66, SD 18, respectively). The mean SUS scores for quitSTART numerically increased from visit one (mean 55, SD 20) to visit two (mean 64, SD 16). Acceptability scores followed the same pattern. Observed task completion rates were at least 75% (7/9 for QuitGuide, 6/8 for quitSTART) for both apps at both visits for all but 2 tasks. During the 13-day trial period, QuitGuide and quitSTART users interacted with their assigned app on an average of 4.6 (SD 2.8) days versus 10.8 (SD 3.5) days, for a mean total of 5.6 (SD 3.8) interactions versus 41 (SD 26) interactions, and responded to a median of 1 notification (range 0-8) versus 18.5 notifications (range 0-37), respectively. Qualitative comments indicated moderate to high satisfaction overall but also included concerns about the accuracy of the apps’ feedback.
Conclusions: Both QuitGuide and quitSTART had acceptable levels of usability and mixed levels of acceptability among young adults with SMI. The higher level of engagement with quitSTART suggests that quitSTART may be a favorable tool for young adult smokers with SMI. However, clinical support or coaching may be needed to overcome initial usability issues.
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