Genetic and environmental risk factors in the non-medical use of over-the-counter or prescribed analgesics, and their relationship to major classes of licit and illicit substance use and misuse in a population-based sample of young adult twins

Opioid use disorder in pediatric populations: considerations for perioperative pain management and precision opioid analgesia

INTRODUCTION

Opioids are commonly used for perioperative analgesia, yet children still suffer high rates of severe post-surgical pain and opioid-related adverse effects. Persistent and severe acute surgical pain greatly increases the child's chances of chronic surgical pain, long-term opioid use, and opioid use disorder.

AREAS COVERED

Enhanced recovery after surgery (ERAS) protocols are often inadequate in treating a child's severe surgical pain. Research suggests that 'older' and longer-acting opioids such as methadone are providing better methods to treat acute post-surgical pain. Studies indicate that lower repetitive methadone doses can decrease the incidence of chronic persistent surgical pain (CPSP). Ongoing research explores genetic components influencing severe surgical pain, inadequate opioid analgesia, and opioid use disorder. This new genetic research coupled with better utilization of opioids in the perioperative setting provides hope in personalizing surgical pain management, reducing pain, opioid use, adverse effects, and helping the fight against the opioid pandemic.

EXPERT OPINION

The opioid and analgesic pharmacogenomics approach can proactively 'tailor' a perioperative analgesic plan to each patient based on underlying polygenic risks. This transition from population-based knowledge of pain medicine to individual patient knowledge can transform acute pain medicine and greatly reduce the opioid epidemic's socioeconomic, personal, and psychological strains globally.

Longitudinal associations between age 20 problematic substance use and opioid use disorder incidence at age 30 - findings from an urban cohort

This study used data from a longitudinal prevention study in an urban cohort to examine associations between nicotine dependence, alcohol, and cannabis use disorder and disorder criteria at age 20, with opioid use disorder (OUD) incidence or criteria onset by age 30. The study sample included 1408 participants (57.5% female, 72.5% African American) drawn from two cohorts of participants in a mid-Atlantic region of the U.S. as part of a series of randomized controlled trials of elementary school-based universal prevention interventions. Lifetime cannabis use disorder (CUD), alcohol use disorder (AUD; both DSM-IV), and current nicotine dependence (Fagerstrom Test for Nicotine Dependence, FTND) assessed at age 20 were used to predict (1) DSM-IV lifetime OUD at age 30, and (2) OUD criteria between ages 20 and 30 in multivariable logistic regression models. Covariates for all analyses included sociodemographics (sex, race, and free/reduced-priced lunch status), community disadvantage, and intervention status. Nicotine dependence (FTND≥3) at age 20 predicted age 30 DSM-IV lifetime OUD (aOR = 2.37; 95% CI 1.02,5.54). The number of CUD criteria (aOR = 1.30; 95% CI 1.09,1.57) and nicotine dependence severity scores (aOR = 1.22; 95% CI = 1.05,1.41) at age 20 predicted any OUD criteria between the ages of 20 and 30. Findings are consistent with previous research on opioid use behavior in young adulthood and suggest that nicotine dependence and CUD criteria among urban young people predict onset of OUD and OUD criteria in young adulthood.

Specificity in genetic and environmental risk for prescription opioid misuse and heroin use

BACKGROUND

Many studies aggregate prescription opioid misuse (POM) and heroin use into a single phenotype, but emerging evidence suggests that their genetic and environmental influences may be partially distinct.

METHODS

In total, 7164 individual twins (84.12% complete pairs; 59.81% female; mean age = 30.58 years) from the Australian Twin Registry reported their lifetime misuse of prescription opioids, stimulants, and sedatives, and lifetime use of heroin, cannabis, cocaine/crack, illicit stimulants, hallucinogens, inhalants, solvents, and dissociatives via telephone interview. Independent pathway models (IPMs) and common pathway models (CPMs) partitioned the variance of drug use phenotypes into general and drug-specific genetic (a), common environmental (c), and unique environmental factors (e).

RESULTS

An IPM with one general a and one general e factor and a one-factor CPM provided comparable fit to the data. General factors accounted for 55% (a = 14%, e = 41%) and 79% (a = 64%, e = 15%) of the respective variation in POM and heroin use in the IPM, and 25% (a = 12%, c = 8%, e = 5%) and 80% (a = 38%, c = 27%, e = 15%) of the respective variation in POM and heroin use in the CPM. Across both models, POM emerged with substantial drug-specific genetic influence (26-39% of total phenotypic variance; 69-74% of genetic variance); heroin use did not (0% of total phenotypic variance; 0% of genetic variance in both models). Prescription sedative misuse also demonstrated significant drug-specific genetic variance.

CONCLUSIONS

Genetic variation in POM, but not heroin use, is predominantly drug-specific. Misuse of prescription medications that reduce experiences of subjective distress may be partially influenced by sources of genetic variation separate from illicit drug use.

Norwegian adolescents' use of energy drinks and painkillers and misuse of prescription drugs prior to and during the initial COVID-19 pandemic year: Evidence from the MyLife study

AIMS

This study aimed to examine and compare the use of energy drinks, over-the-counter (OTC) painkillers and misuse of prescription drugs in two cohorts of Norwegian adolescents entering high school (i.e. grade 11) immediately prior to and during the initial year of the COVID-19 pandemic.

METHODS

Accelerated longitudinal design and multi-cohort sampling enabled identification of the two socio-demographically comparable cohorts of grade 11 students: (a) COVID-19 cohort assessed in the autumn of 2020 (n=915) and (b) pre-COVID-19 cohort assessed in the autumn of 2018/19 (n=1621). Unadjusted and adjusted logistic and Poisson models were used to estimate the proportion of (mis)users and use frequencies among (mis)users in two cohorts.

RESULTS

Energy drinks use was both more common in the COVID-19 cohort (60.8% vs. 52.5%; adjusted odds ratio=1.40, 95% confidence interval (CI) 1.18-1.66, p<0.001) and more frequent among users from this cohort than among their pre-COVID-19 counterparts (9.58 vs. 7.79 days past month, adjusted incidence risk ratio (aIRR)=1.23, 95% CI 1.14-1.32, p<0.001). No cohort differences were observed in OTC painkillers use. Prescription drugs misuse was equally common in the two cohorts but was more frequent among misusers from the COVID-19 cohort than among their pre-COVID-19 counterparts (18.94 vs. 12.45 times past year, aIRR=1.52, 95% CI 1.10-2.10, p<0.001).

CONCLUSIONS

Norwegian adolescents from the COVID-19 cohort were more likely to use energy drinks and, once engaged in these behaviours, to use energy drinks and misuse prescription drugs more frequently than their pre-COVID-19 counterparts.

Are prescription misuse and illicit drug use etiologically distinct? A genetically-informed analysis of opioids and stimulants

BACKGROUND

Drug classes are grouped based on their chemical and pharmacological properties, but prescription and illicit drugs differ in other important ways. Potential differences in genetic and environmental influences on the (mis)use of prescription and illicit drugs that are subsumed under the same class should be examined. Opioid and stimulant classes contain prescription and illicit forms differentially associated with salient risk factors (common route of administration, legality), making them useful comparators for addressing this etiological issue.

METHODS

A total of 2410 individual Australian twins [Mage = 31.77 (s.d. = 2.48); 67% women] were interviewed about prescription misuse and illicit use of opioids and stimulants. Univariate and bivariate biometric models partitioned variances and covariances into additive genetic, shared environmental, and unique environmental influences across drug types.

RESULTS

Variation in the propensity to misuse prescription opioids was attributable to genes (41%) and unique environment (59%). Illicit opioid use was attributable to shared (71%) and unique (29%) environment. Prescription stimulant misuse was attributable to genes (79%) and unique environment (21%). Illicit stimulant use was attributable to genes (48%), shared environment (29%), and unique environment (23%). There was evidence for genetic influence common to both stimulant types, but limited evidence for genetic influence common to both opioid types. Bivariate correlations suggested that prescription opioid use may be more genetically similar to prescription stimulant use than to illicit opioid use.

CONCLUSIONS

Prescription opioid misuse may share little genetic influence with illicit opioid use. Future research may consider avoiding unitary drug classifications, particularly when examining genetic influences.

Positive associations between cannabis and alcohol use polygenic risk scores and phenotypic opioid misuse among African-Americans

BACKGROUND

This study examined whether polygenic risk scores (PRS) for lifetime cannabis and alcohol use were associated with misusing opioids, and whether sex differences existed in these relations in an urban, African-American sample.

METHODS

Data were drawn from three cohorts of participants (N = 1,103; 45% male) who were recruited in first grade as part of a series of elementary school-based, universal preventive intervention trials conducted in a Mid-Atlantic region of the U.S. In young adulthood, participants provided a DNA sample and reported on whether they had used heroin or misused prescription opioids in their lifetime. Three substance use PRS were computed based on prior GWAS: lifetime cannabis use from Pasman et al. (2018), heavy drinking indexed via maximum number of drinks from Gelernter et al. (2019), and alcohol consumption from Kranzler et al. (2019).

RESULTS

Higher PRS for lifetime cannabis use, greater heavy drinking, and greater alcohol consumption were associated with heightened risk for misusing opioids among the whole sample. Significant sex by PRS interactions were also observed such that higher PRS for heavy drinking and alcohol consumption were associated with a greater likelihood of opioid misuse among males, but not females.

CONCLUSION

Our findings further elucidate the genetic contributions to misusing opioids by showing that the genetics of cannabis and alcohol consumption are associated with lifetime opioid misuse among young adults, though replication of our findings is needed.

Fentanyl-induced acute and conditioned behaviors in two inbred mouse lines: Potential role for Glyoxalase

An increase in opioid-overdose deaths was evident before the COVID-19 pandemic, and has escalated since its onset. Fentanyl, a highly potent synthetic opioid, is the primary driver of these recent trends. The current study used two inbred mouse strains, C57BL/6 J and A/J, to investigate the genetics of behavioral responses to fentanyl. Mice were tested for conditioned place preference and fentanyl-induced locomotor activity. C57BL/6J mice formed a conditioned place preference to fentanyl injections and fentanyl increased their activity. Neither effect was noted in A/J mice. We conducted RNA-sequencing on the nucleus accumbens of mice used for fentanyl-induced locomotor activity. Surprisingly, we noted few differentially expressed genes using treatment as the main factor. However many genes differed between strains. We validated differences in two genes: suppressor APC domain containing 1 (Sapcd1) and Glyoxalase 1 (Glo1), with quantitative PCR on RNA from the nucleus accumbens and prefrontal cortex (). In both regions A/J mice had significantly higher expression of both genes than did C57BL/6 J. In prefrontal cortex, fentanyl treatment decreased Glo1 mRNA. Glyoxalase 1 catalyzes the detoxification of reactive alpha-oxoaldehydes such as glyoxal and methylglyoxal, is associated with anxiety and activity levels, and its inhibition reduces alcohol intake. We suggest that future studies assess the ability of Glo1 and related metabolites to modify opioid intake.

Genetic Vulnerability to Opioid Addiction

Opioid addiction, also referred to as opioid use disorder, continues to be a devastating problem throughout the world. Familial relation and twin studies have revealed opioid addiction, like other addictive diseases, to be profoundly influenced by genetics. Genetics studies of opioid addiction have affirmed the importance of genetics contributors in susceptibility to develop opioid addiction, and also have important implications on treatment for opioid addiction. But the complexity of the interactions of multiple genetic variants across diverse genes, as well as substantial differences in allelic frequencies across populations, thus far limits the predictive value of individual genetics variants.

Adolescent cannabis and tobacco use are associated with opioid use in young adulthood-12-year longitudinal study in an urban cohort

BACKGROUND AND AIMS

Cannabis, tobacco and alcohol use are prevalent among youth in the United States and may be risk factors for opioid use. The current study aimed at investigating associations between developmental trajectories of cannabis, tobacco and alcohol use in adolescence and opioid use in young adulthood in an urban cohort over the span of 12 years.

DESIGN

Cohort study of adolescents originally recruited for a randomized prevention trial with yearly assessments into young adulthood.

SETTING

Nine urban elementary schools in Baltimore, MD in the United States.

PARTICIPANTS

Participants (n = 583, 86.8% African American, 54.7% male) were originally recruited as first grade students.

MEASUREMENTS

Cannabis, tobacco and alcohol use were assessed annually from ages 14-18 years and opioid use from ages 19-26. Socio-demographics were assessed at age 6. Intervention status was also randomly assigned at age 6. Gender, race, free/reduced-priced lunch and intervention status were included as covariates in individual and sequential growth models.

FINDINGS

There were significant positive associations between the cannabis use intercept at age 14 and the opioid use intercept at age 19 (beta = 1.43; P = 0.028), the tobacco use intercept at age 14 and the opioid use intercept at age 19 (beta = 0.82; P = 0.042). Specifically, more frequent use of cannabis or tobacco at age 14 was associated with more frequent use of opioids at age 19.

CONCLUSIONS

Cannabis and tobacco use in early adolescence may be risk factors for opioid use in young adulthood among African Americans living in urban areas.

Identification of a sex-stratified genetic algorithm for opioid addiction risk

The opioid epidemic has had a devastating impact on our country, with wide-ranging effects on healthcare, corrections, employment, and social systems. Programs have been put in place for monitoring prescriptions, initiating and expanding medications for opioid use disorder, and harm reduction (i.e., naloxone distribution, needle exchanges). However, opportunities for personalization of opioid therapy based on addiction risk have been limited. The goal of the present study was to develop an objective risk assessment algorithm based on genetic markers that are correlated with opioid use disorder (OUD). A total of 180 single-nucleotide polymorphisms (SNPs) were tested in patients with and without OUD. SNPs selected for testing were associated with opioid metabolism and drug reward pathways based on previous studies. Of the 394 patients recruited, 200 had OUD and 194 served as controls without OUD but with prior opioid exposure. Logistic regression analyses stratified by sex identified ten unique SNPs in females and nine unique SNPs in males that were significantly associated with OUD. A Genetics Opioid Risk Score (GenORs) was calculated by counting the number of OUD risk-associated SNPs/genotypes for each patient. To evaluate the discrimination of the GenORs, a receiver operating characteristic (ROC) curve for each sex was generated and determined to be sensitive and specific. This represents the first published example of a sex-based genetic risk score with potential to predict OUD, and the first OUD algorithm to include opioid-associated pharmacokinetic genes.

Trajectories of cannabis use and risk for opioid misuse in a young adult urban cohort

BACKGROUND

Although much of the attention surrounding the opioid epidemic has focused on rural and suburban Whites and prescription opioids, heroin overdoses among urban Blacks are on the rise. While some argue that legalization of cannabis will combat the epidemic, there are concerns it ignores the shift in the epidemic and could increase vulnerability to opioid misuse. The goal of this study is to examine the association between cannabis use from adolescence to young adulthood with opioid misuse in a primarily urban Black cohort.

METHODS

Data are from a study of 580 youth (87 % Black and 71 % low SES) residing in Baltimore City followed from ages 6-26. Cannabis trajectories were identified between ages 14-26 using group-based trajectory modeling. Logistic regressions were conducted to examine the impact of trajectories on opioid misuse in young adulthood adjusting for individual, neighborhood and peer factors. Opioid misuse was defined as using heroin or narcotics or painkillers without a prescription between ages 19-26.

RESULTS

Four cannabis trajectories were identified: Low/Non-Users (59.7 %), Adolescent Onset Limited (19.5 %), Young Adult Onset (10.8 %), and Adolescent Onset Chronic (10.0 %). Adolescent Onset Chronic cannabis users had the highest rate of opioid misuse (44.8 %) followed by Adolescent Onset Limited (18.8 %), Young Adult Onset (14.8 %) and Low/Non-Users (8.3 %). Prevalences were significantly higher for Adolescent Onset groups relative to Low/Non-Users even after adjustment for individual, neighborhood and peer factors.

CONCLUSIONS

Adolescent onset cannabis use is associated with opioid misuse in young adulthood among urban Blacks even after adjustment for socioecological factors associated with opioid misuse.

Designing Effective Warnings about Addiction on the Patient Information Leaflet of Over-the-Counter Codeine Sold in England to University Students

(1) Background: The harm of misusing over-the-counter (OTC) codeine-containing medicines among university students in England is being increasingly recognized. Based on English university students, this paper aims to study the importance of information design on information communication, explore methods for effective warning design, and investigate university students’ perception of OTC codeine. (2) Methods: The effective warning design is addressed through case studies, answering correctness by the heat map generated from the eye-tracking experiment (ETE), and the total time spent on the tasks. User perceptions are made though online surveys. (3) Results: Information design significantly affects the way user processes information. Therefore, two emphasized warnings displayed in the headline, and the “possible side effect (PSE)” sections and warning signs of addiction presented under the PSE are suggested as effective ways to display warnings. For students’ perception of OTC codeine, 80% of university students are unfamiliar with the substance. After reading the patient information leaflets (PILs), 47% recommended tight regulation on codeine. (4) Conclusions: The misuse of OTC codeine could be a potential problem among English university students. The design of the PIL significantly influences the chance of unintentional medicine misuse. The display of warnings on the PILs of OTC codeine should be redesigned for better understanding.