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Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50–70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.

Although effective treatments exist, alcohol use disorder (AUD) is undertreated. We used a cascade of care framework to understand gaps in care for persons with AUD. Using 2015–2019 National Survey on Drug Use and Health data, we evaluated the following steps in the cascade of care: (1) adult prevalence of AUD; (2) proportion of adults with AUD who utilized health care in the past 12 months; (3) proportion with AUD screened about their alcohol use; (4) proportion with AUD who received a brief intervention about their alcohol misuse; (5) proportion with AUD who received information about treatment for alcohol misuse; and (6) proportion with AUD who received treatment. Analyses were stratified by AUD severity. Of the 214,505 persons included in the sample, the weighted prevalence of AUD was 7.8% (95% CI 7.6–8.0%). Cascades of care showed the majority of individuals with AUD utilized health care in the past 12 months [81.4% (95% CI 80.7–82.1%)] and were screened about alcohol use [69.9% (95% CI 68.9–70.8%)]. However, only a minority of individuals received subsequent steps of care, including 11.6% (95% CI 11.0–12.2%) who reported receiving a brief intervention, 5.1% (95% CI 4.6–5.6%) who were referred to treatment, and 5.8% (95% CI 5.4–6.3%) who received treatment. Similar patterns were observed when cascades of care were stratified by AUD severity. Persons with AUD commonly utilize health care and are often screened about alcohol use, but few receive treatment. Healthcare settings—particularly primary care settings—represent a prime opportunity to implement AUD treatment to improve outcomes in this high‐risk population. Using data from the National Survey on Drug Use and Health, we developed a cascade of care for alcohol use disorder (AUD). We found that most persons with AUD visited a doctor and were screened about alcohol use during the past year, but few received intervention. These results suggest there is a missed opportunity in health care settings to engage persons with AUD in care, and point to the need for improved implementation of evidence‐based AUD treatments in these environments.

An extreme overvalued belief is shared by others in a person's cultural, religious, or subcultural group. The belief is often relished, amplified, and defended by the possessor of the belief and should be differentiated from a delusion or obsession. Over time, the belief grows more dominant, more refined, and more resistant to challenge. The individual has an intense emotional commitment to the belief and may carry out violent behavior in its service. Study participants (n5109 forensic psychiatrists) were asked to select among three definitions (i.e., obsession, delusion, and extreme overvalued belief) as the motive for the criminal behavior seen in 12 randomized fictional vignettes. Strong interrater agreement (kappa50.91 [95% CI 0.830.98]) was seen for vignettes representing extreme overvalued belief. Vignettes representing delusion and obsession also had strong reliability (kappa = 0.99 for delusion and 0.98 for obsession). This preliminary report suggests that forensic psychiatrists, given proper definitions, possess a substantial ability to identify delusion, obsession, and extreme overvalued belief. The rich historical foundation of extreme overvalued belief and this small survey study highlight the benefit of inclusion of extreme overvalued belief in future glossaries of the Diagnostic and Statistical Manual. [ABSTRACT FROM AUTHOR]

To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z= −5.39, p= 7.2 × 10–8). This variant regulates the transcriptomic profiles of SLC30A9and BEND4in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N> 360,000) found association of this variant with propensity to use dietary supplements (p= 1.68 × 10–8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8(EUR + AFR z= 4.69, p= 10–6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z= 5.55, p= 2.9 × 10–8) and a significant association with musculoskeletal disorders in the UK Biobank (p= 4.88 × 10–7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n= 466,571) was positively associated with OD (OD vs. unexposed controls, p= 8.1 × 10–5; OD cases vs. exposed controls, p= 0.054) and OE (exposed vs. unexposed controls, p= 3.6 × 10–5). A PRS based on a GWAS of neuroticism (n= 390,278) was positively associated with OD (OD vs. unexposed controls, p= 3.2 × 10–5; OD vs. exposed controls, p= 0.002) but not with OE (p= 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction.

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case–control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n= 46,568; African, n= 6,280). Independent, genome-wide significant effects of different ADH1Bvariants were identified in European (rs1229984; P= 9.8 × 10–13) and African ancestries (rs2066702; P= 2.2 × 10–9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit–hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

Aim:This study tests whether polygenic risk scores (PRSs) for nicotine metabolism predict smoking behaviors in independent data. Materials & methods:Linear regression, logistic regression and survival analyses were used to analyze nicotine metabolism PRSs and nicotine metabolism, smoking quantity and smoking cessation. Results:Nicotine metabolism PRSs based on two genome wide association studies (GWAS) meta-analyses significantly predicted nicotine metabolism biomarkers (R2range: 9.2–16; minimum p  7.6 × 10-8). The GWAS top hit variant rs56113850 significantly predicted nicotine metabolism biomarkers (R2range: 14–17; minimum p  4.4 × 10-8). There was insufficient evidence for these PRSs predicting smoking quantity and smoking cessation. Conclusion:Results suggest that nicotine metabolism PRSs based on GWAS meta-analyses predict an individual's nicotine metabolism, so does use of the top hit variant. We anticipate that PRSs will enter clinical medicine, but additional research is needed to develop a more comprehensive genetic score to predict smoking behaviors.

There is evidence that low‐level alcohol use, drinking 1 to 2 drinks on occasion, is protective for cardiovascular disease, but increases the risk of cancer. Synthesizing the overall impact of low‐level alcohol use on health is therefore complex. The objective of this paper was to examine the association between frequency of low‐level drinking and mortality. Two data sets with self‐reported alcohol use and mortality follow‐up were analyzed: 340,668 individuals from the National Health Interview Survey (NHIS) and 93,653 individuals from the Veterans Health Administration (VA) outpatient medical records. Survival analyses were conducted to evaluate the association between low‐level drinking frequency and mortality. The minimum risk drinking frequency among those who drink 1 to 2 drinks per occasion was found to be 3.2 times weekly in the NHIS data, based on a continuous measure of drinking frequency, and 2 to 3 times weekly in the VA data. Relative to these individuals with minimum risk, individuals who drink 7 times weekly had an adjusted hazard ratio (HR) of all‐cause mortality of 1.23 (p< 0.0001) in the NHIS data, and individuals who drink 4 to 7 times weekly in the VA data also had an adjusted HR of 1.23 (p= 0.01). Secondary analyses in the NHIS data showed that the minimum risk was drinking 4 times weekly for cardiovascular mortality, and drinking monthly or less for cancer mortality. The associations were consistent in stratified analyses of men, women, and never smokers. The minimum risk of low‐level drinking frequency for all‐cause mortality appears to be approximately 3 occasions weekly. The robustness of this finding is highlighted in 2 distinctly different data sets: a large epidemiological data set and a data set of veterans sampled from an outpatient clinic. Daily drinking, even at low levels, is detrimental to one's health. This study evaluated the association between mortality and frequency of light drinking (1–2 drinks). In both an epidemiological dataset (NHIS) and a clinical outpatient dataset (VA), we found increased risk of all‐cause mortality among those who drank 4 or more times weekly relative to those who drank less frequently. This suggests that frequent low‐level drinking increases mortality.

Recent trends in alcoholic liver disease, alcohol‐related emergency room admissions, and alcohol use disorder prevalence as measured by general‐population surveys have raised concerns about rising alcohol‐related morbidity and mortality in the United States. In contrast, upward trends in per capita alcohol consumption have been comparatively modest. To resolve these discordant observations, we sought to examine trends in the prevalence of alcohol use and binge drinking from 6 regularly or periodically administered national surveys using a meta‐analytic approach. Annual or periodic prevalence estimates for past‐12‐month or past‐30‐day alcohol use and binge drinking were estimated for available time points between the years 2000 and 2016. Estimates were combined in a random‐effects regression model in which prevalence was modeled as a log‐linear function of time to obtain meta‐analytic trend estimates for the full population and by sex, race, age, and educational attainment. Meta‐analysis–derived estimates of average annual percentage increase in the prevalence of alcohol use and binge drinking were 0.30% per year (95% CI: 0.22%, 0.38%) and 0.72% per year (95% CI: 0.46%, 0.98%), respectively. There was substantial between‐survey heterogeneity among trend estimates, although there was notable consistency in the degree to which trends have impacted various demographic groups. For example, most surveys found that the changes in prevalence for alcohol use and binge drinking were large and positive for ages 50 to 64 and 65 and up, and smaller, negative, or nonsignificant for ages 18 to 29. Significant increases in the prevalence of alcohol use and of binge drinking over the past 10 to 15 years were observed, but not for all demographic groups. However, the increase in binge drinking among middle‐aged and older adults is substantial and may be driving increasing rates of alcohol‐related morbidity and mortality. Estimates from a meta‐analysis of six national surveys show that the prevalence of binge drinking among adults increased by about 7% over the past decade. While lower than estimates from an earlier study, increases were more pronounced among older age groups, e.g., binge drinking increased by 38% among individuals ages 65 and over. The large increases in binge drinking among older Americans is likely driving sharp increases in alcohol‐related morbidity and mortality, while increases in alcohol sales per‐capita have been relatively small.

Smoking cessation treatment outcomes may be heavily influenced by genetic variations among smokers. Therefore, identifying specific variants that affect response to different pharmacotherapies is of major interest to the field. In the current study, we systematically review all studies published in or after the year 1990 which examined one or more gene–drug interactions for smoking cessation treatment. Out of 644 citations, 46 articles met the inclusion criteria for the systematic review. We summarize evidence on several genetic polymorphisms (CHRNA5-A3-B4, CYP2A6, DBH, CHRNA4, COMT, DRD2, DRD4 and CYP2B6) and their potential moderating pharamacotherarpy effects on patient cessation efficacy rates. These findings are promising and call for further research to demonstrate the effectiveness of genetic testing in personalizing treatment decision-making and improving outcome.

Genetic information about smoking and smoking-related diseases could be used to identify individual disease risk, motivate quit attempts, and optimize smoking cessation treatment.The incorporation of genomic information into routine care settings is a burgeoning area for investigation in behavioral medicine. The past decade has witnessed rapid advancements in knowledge of genetic biomarkers associated with smoking behaviors and tobacco-related morbidity and mortality, providing the basis for promising genomic applications in clinical and community settings. We assessed the current state of readiness for implementing genomic applications involving variation in the α5 nicotinic cholinergic receptor subunit gene CHRNA5and smoking outcomes (behaviors and related diseases) using a process that could be translatable to a wide range of genomic applications in behavioral medicine. We reviewed the scientific literature involving CHRNA5genetic variation and smoking cessation, and then summarized and synthesized a chain of evidence according to analytic validity, clinical validity, clinical utility, and ethical, legal, and social implications (ACCE), a well-established set of criteria used to evaluate genomic applications. Our review identified at least three specific genomic applications for which implementation may be considered, including the use of CHRNA5genetic test results for informing disease risk, optimizing smoking cessation treatment, and motivating smoking behavior change. For these genomic applications, we rated analytic validity as convincing, clinical validity as adequate, and clinical utility and ethical, legal, and social implications as inadequate. For clinical genomic applications involving CHRNA5variation and smoking outcomes, research efforts now need to focus on establishing clinical utility. This approach is compatible with pre-implementation research, which is also needed to accelerate translation, improve innovation design, and understand and refine system processes involved in implementation. This study informs the readiness to incorporate smoking-related genomic applications in real-world settings and facilitates cross-disciplinary collaboration to accelerate the integration of evidence-based genomics in behavioral medicine.

Internet-based technologies are increasingly being used for research studies. However, it is not known whether Internet-based approaches will effectively engage participants from diverse racial and socioeconomic backgrounds.

Purpose:Internet-based technologies are increasingly being used for research studies. However, it is not known whether Internet-based approaches will effectively engage participants from diverse racial and socioeconomic backgrounds.Methods:A total of 967 participants were recruited and offered genetic ancestry results. We evaluated viewing Internet-based genetic ancestry results among participants who expressed high interest in obtaining the results.Results:Of the participants, 64% stated that they were very or extremely interested in their genetic ancestry results. Among interested participants, individuals with a high school diploma (n = 473) viewed their results 19% of the time relative to 4% of the 145 participants without a diploma (P < 0.0001). Similarly, 22% of participants with household income above the federal poverty level (n = 286) viewed their results relative to 10% of the 314 participants living below the federal poverty level (P < 0.0001). Among interested participants both with a high school degree and living above the poverty level, self-identified Caucasians were more likely to view results than self-identified African Americans (P < 0.0001), and females were more likely to view results than males (P = 0.0007).Conclusion:In an underserved population, engagement in Internet-based research was low despite high reported interest. This suggests that explicit strategies should be developed to increase diversity in Internet-based research.Genet Med 19 2, 240–243.

Patients with Bipolar disorder smoke more than the general population. Smoking negatively impacts mortality and clinical course in Bipolar disorder patients. Prior studies have shown contradictory results regarding the impact of psychosis on smoking behavior in Bipolar disorder. We analyzed a large sample of Bipolar disorder and Schizoaffective disorder, Bipolar Type patients and predicted those with a history of psychosis would be more likely to be nicotine dependent. Data from subjects and controls were collected from the Genomic Psychiatry Cohort (GPC). Subjects were diagnosed with Bipolar disorder without psychosis (N = 610), Bipolar disorder with psychosis (N = 1544). Participants were classified with or without nicotine dependence. Diagnostic groups were compared to controls (N = 10065) using logistic regression. Among smokers (N = 6157), those with Bipolar disorder had an increased risk of nicotine dependence (OR = 2.5; P< 0.0001). Patients with Bipolar disorder with psychosis were more likely to be dependent than Bipolar disorder patients without psychosis (OR = 1.3; P= 0.03). Schizoaffective disorder, Bipolar Type patients had more risk of nicotine dependence when compared to Bipolar disorder patients with or without psychosis (OR = 1.2; P= 0.02). Bipolar disorder patients experiencing more severity of psychosis have more risk of nicotine dependence. © 2015 Wiley Periodicals, Inc.

The goal of this study was to examine participant responses to disclosure of genetic results in a minority population at high risk for depression and anxiety.

Purpose:The goal of this study was to examine participant responses to disclosure of genetic results in a minority population at high risk for depression and anxiety.Methods:Eighty-two subjects in a genetic study of nicotine dependence were offered personalized genetic results. All were nicotine-dependent and 64% self-identified as African American. Pathway Genomics was used to evaluate genetic risks for five complex diseases. Participants returned 4–8 weeks after enrollment for in-person genetic counseling interviews and evaluation of baseline measures. A telephone follow-up was performed 4–8 weeks later to assess responses to results.Results:Fifty of the 82 subjects (61%) were interested in receiving genetic results. These participants had multiple risk factors, including high baseline measures of depression (66%) and anxiety (32%), as well as low rates of employment (46%), adequate health literacy (46%), and health insurance (45%). Pathway Genomics reported “increased risk” for at least one disease in 77% of subjects. Ninety-five percent of participants reported that they appreciated the genetic results, and receiving these results was not associated with changes in symptoms of depression or anxiety. Furthermore, after return of genetic results, smoking cessation attempts increased (P = 0.003).Conclusion:Even in an underserved population at high risk for adverse psychological reactions, subjects responded positively to personalized genetic results.Genet Med 17 5, 374–379.

Owing to the clinical relationship between bipolar disorder and nicotine dependence, we investigated two research questions: (i) are genetic associations with nicotine dependence different in individuals with bipolar disorder as compared with individuals without bipolar disorder, and (ii) do loci earlier associated with nicotine dependence have pleiotropic effects on these two diseases.

The XVII World Congress of Psychiatric Genetics, sponsored by The International Society of Psychiatric Genetics (ISPG) took place in San Diego, California from 4 to 8 November 2009. Approximately 550 participants gathered to discuss the latest molecular genetic findings relevant to serious mental illness, including schizophrenia, mood disorders, substance abuse, autism, and attention deficit disorder. Recent advances in the field were discussed, including the genome-wide association studies results, copy number variation (CNV) in the genome, genomic imaging, and large multicenter collaborations. The following report, written by junior travel awardees who were assigned sessions as rapporteurs represents some of the areas covered in oral presentation during the conference, and reports on some of the notable major new findings described at this 2009 World Congress of Psychiatric Genetics.

Schizophrenia is a neurodevelopmental psychiatric disorder characterized by a variety of structural brain abnormalities that appear to progress across the course of illness. Schizophrenia also is highly heritable, and one gene that has emerged as a possible susceptibility factor is G72. G72influences brain development and activity by an as‐yet unclear mechanism, and multiple studies have reported associations between G72and schizophrenia. We were interested in linking these domains of investigation by determining whether G72also influences the rate of longitudinal structural brain changes in individuals with schizophrenia. As part of the Iowa Longitudinal Study of Recent Onset Psychoses, we genotyped four G72polymorphisms previously associated with schizophrenia in 110 subjects with schizophrenia or schizoaffective disorder from whom we had obtained two brain MRI scans an average of 3 years apart. The four polymorphisms captured three haplotypes, one of which was strongly associated with an increased rate of frontal lobe volume decrement. This same haplotype was also associated with more severe psychotic symptoms at the time of the second scan. These data thus suggest that variation in G72modulates the progressive brain changes that characterize schizophrenia. © 2009 Wiley‐Liss, Inc.

Many industries generate volatile organic compounds (VOCs) in dilute streams which must be removed before being released into the environment. Mathematical models for biological filters which can remediate waste streams are useful both as predictive tools and as a means to better understand the fundamental processes involved. Optimization of the system also necessitates a better understanding of the mechanisms by which biofilters work and can be approached through modeling and maximizing appropriate conditions for removal. In a trickle-bed bioreactor, VOCs (n-pentane and isobutane) were passed over a biofilm-coated packing which degraded the VOCs. Bacterial growth was controlled via liquid nutrient-limited media trickled through the reactor. Results from this trickle-bed system were analyzed by applying a simple mathematical model to accurately describe the processes which are believed to play important roles. The model was based on a two-step process: mass transfer in which the VOCs diffuse into the liquid biofilm, and kinetics by which VOCs are degraded by the biofilm. Modeling results revealed that both kinetic and mass transfer resistances were significant under typical operating conditions.

IMPORTANCE: Although overall rates of opioid use have been plateauing, coprescriptions of benzodiazepines and opioids have increased greatly in recent years. It is unknown whether this combination is an independent risk factor for all-cause mortality as opposed to being more frequently used by persons with a baseline elevated risk of death. OBJECTIVE: To evaluate whether benzodiazepine use, with or without opioid use, is associated with increased all-cause mortality relative to the use of low-risk antidepressants. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used a large, nationally representative US data set (the National Health and Nutrition Examination Surveys [NHANES]) from 1999 to 2015. Eight cycles of NHANES data were used, spanning 37?610 person-years of follow-up time among 5212 individuals. Statistical analysis was performed from August 24, 2019, through May 23, 2020. EXPOSURES: The primary exposure variable was benzodiazepine and opioid coprescriptions. Individuals taking selective serotonin reuptake inhibitors (SSRIs) served as an active comparator reference group. MAIN OUTCOMES AND MEASURES: All-cause mortality was obtained via linkage of NHANES to the National Death Index. Propensity scores were calculated from covariates associated with sociodemographic factors, comorbidities, and medication use for more than 1000 prescription types. Propensity score–weighted mortality hazards were calculated from Cox proportional hazards regression models. RESULTS: Of 5212 participants aged 20 years or older (1993 men [38.2%]; mean [SD] age, 54.8 [16.9] years) followed up for a median of 6.7 years (range, 0.2-16.8 years), 101 deaths (33.0 per 1000 person-years) occurred among those receiving cotreatment, 236 deaths (26.5 per 1000 person-years) occurred among those receiving only benzodiazepines, and 227 deaths (20.2 per 1000 person-years) occurred among SSRI recipients taking neither opioids nor benzodiazepines. After propensity score weighting, a significant increase in all-cause mortality was associated with benzodiazepine and opioid cotreatment (hazard ratio, 2.04 [95% CI, 1.65-2.52]) and benzodiazepines without opioids (hazard ratio, 1.60 [95% CI, 1.33-1.92]). Subgroup analyses revealed an increased risk of mortality for individuals receiving cotreatment who were 65 years or younger but not for those older than 65 years; similar findings were observed for those receiving benzodiazepines without opioids. CONCLUSIONS AND RELEVANCE: This study found a significant increase in all-cause mortality associated with benzodiazepine use with or without opioid use in comparison with SSRI use. Benzodiazepine and opioid cotreatment, in particular, was associated with a 2-fold increase in all-cause mortality even after taking into account medical comorbidities and polypharmacy burden.