Cannabis use and neurocognitive performance at 13-14 Years-Old: Optimizing assessment with hair toxicology in the Adolescent brain cognitive development (ABCD) study

OBJECTIVE

Cannabis is widely used, including in early adolescence, with prevalence rates varying by measurement method (e.g., toxicology vs. self-report). Critical neurocognitive development occurs throughout adolescence. Given conflicting prior brain-behavior results in cannabis research, improved measurement of cannabis use in younger adolescents is needed.

METHODS

Data from the Adolescent Brain Cognitive Development (ABCD) Study Year 4 follow-up (participant age: 13-14 years-old) included hair samples assessed by LC-MS/MS and GC-MS/MS, quantifying THCCOOH (THC metabolite), THC, and cannabidiol concentrations, and the NIH Toolbox Cognitive Battery. Youth whose hair was positive for cannabinoids or reported past-year cannabis use were included in a Cannabis Use (CU) group (n = 123) and matched with non-using Controls on sociodemographics (n = 123). Standard and nested ANCOVAs assessed group status predicting cognitive performance, controlling for family relationships. Follow-up correlations assessed cannabinoid hair concentration, self-reported cannabis use, and neurocognition.

RESULTS

CU scored lower on Picture Memory (p = .03) than Controls. Within the CU group, THCCOOH negatively correlated with Picture Vocabulary (r = -0.20, p = .03) and Flanker Inhibitory Control and Attention (r = -0.19, p = .04), and past-year cannabis use was negatively associated with List Sorting Working Memory (r = -0.33, p = .0002) and Picture Sequence Memory (r = -0.19, p = .04) performances.

CONCLUSIONS

Youth who had used cannabis showed lower scores on an episodic memory task, and more cannabis use was linked to poorer performances on verbal, inhibitory, working memory, and episodic memory tasks. Combining hair toxicology with self-report revealed more brain-behavior relationships than self-report data alone. These youth will be followed to determine long-term substance use and neurocognition trajectories.

External hair contamination from cannabis and "light cannabis" delivered by smoking and vaping: An in vitro study

External contamination of hair by cannabis smoking requires a careful evaluation in forensic toxicology. Medical and recreational cannabis are increasingly consumed by e-cigarettes, which give rise to side-stream vapor. Moreover, products containing low Δ9-tetrahydrocannabinol (Δ9-THC) and rich in cannabidiol (CBD) started spreading legally. The goal of the present study was to assess whether hair analysis could allow to distinguish the type of delivered product, with low or high Δ9-THC, and the delivering mode, by smoking or vaping. Contamination of blank hair was mimicked by in vitro exposure to low- (0.4%) and high-Δ9-THC (9.7%) products delivered by smoking and vaping within a small confined system. Cannabis vaping extracts were prepared to deliver identical target Δ9-THC doses. Eighty samples were analyzed by ultrahigh-performance liquid chromatography mass spectrometry and quantified for Δ9-THC and CBD. After contamination by cannabis smoking, THC levels were in line with past in vitro and in vivo studies. Samples exposed to cannabis (169.30 ng/mg) showed significantly higher Δ9-THC than hair exposed to "light cannabis" (35.54 ng/mg), and the opposite was seen for the CBD/Δ9-THC ratio. Hair contaminated by vaping or smoking did not show a statistically different Δ9-THC content. Under our in vitro conditions, hair analysis might allow to discriminate whether external contamination is determined by products containing low or high Δ9-THC, but not the delivering mode. More research is needed in real-life conditions, to see whether the same also applies to the interpretation of forensic casework.

Concordance between substance use self-report and hair analysis in community-based adolescents

Background: Accurate drug use identification through subjective self-report and toxicological biosample (hair) analysis are necessary to determine substance use sequelae in youth. Yet consistency between self-reported substance use and robust, toxicological analysis in a large sample of youth is understudied.Objectives: We aim to assess concordance between self-reported substance use and hair toxicological analysis in community-based adolescents.Methods: Hair results by LC-MS/MS and GC-MS/MS and self-reported past-year substance use from an Adolescent Brain Cognitive Development (ABCD) Study subsample (N = 1,390; ages 9-13; 48% female) were compared. The participants were selected for hair selection through two methods: high scores on a substance risk algorithm selected 93%; 7% were low-risk, randomly selected participants. Kappa coefficients the examined concordance between self-report and hair results.Results: 10% of youth self-reported any past-year substance use (e.g. alcohol, cannabis, nicotine, and opiates), while a mostly non-overlapping 10% had hair results indicating recent substance use (cannabis, alcohol, non-prescription amphetamines, cocaine, nicotine, opiates, and fentanyl). In randomly selected low-risk cases, 7% were confirmed positive in hair. Combining methods, 19% of the sample self-reported substance use and/or had a positive hair sample. Kappa coefficient of concordance between self-report and hair results was low (kappa = 0.07; p = .007).Conclusions: Hair toxicology identified substance use in high-risk and low-risk ABCD cohort subsamples. Given low concordance between hair results and self-report, reliance on either method alone would incorrectly categorize 9% as non-users. Multiple methods for characterizing substance use history in youth improves accuracy. Larger representative samples are needed to assess the prevalence of substance use in youth.

Substance use onset in high-risk 9-13 year-olds in the ABCD study

AIM

A key aim of the Adolescent Brain Cognitive Development℠ (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting can obscure accurate drug use characterization. Hair toxicology provides objective historical substance use data but is rarely used in studies of youth. Here, we compare objective hair toxicology results with self-reported substance use in high-risk youth.

METHODS

A literature-based substance use risk algorithm prioritized 696 ABCD Study® hair samples from 677 participants for analysis at baseline, and 1 and 2-year follow-ups (spanning ages 9-13). Chi-square and t-tests assessed differences between participants' demographics, positive and negative hair tests, risk-for-use algorithm scores, and self-reported substance use.

RESULTS

Hair testing confirmed that 17% of at-risk 9-13 year-olds hair samples had evidence of past 3-month use of one (n = 97), two (n = 14), three (n = 2), or four (n = 2) drug classes. After considering prescribed medication and self-reported substance use, 10% had a positive test indicating substance use that was not reported. Participants with any positive hair result reported less sipping of alcohol (p < 0.001) and scored higher on the risk-for-use algorithm (p < 0.001) than those with negative toxicology results.

CONCLUSIONS

10% of hair samples from at-risk 9-13 year-olds tested positive for at least one unreported substance, suggesting underreporting in high-risk youth when participating in a research study. As hair testing prioritized youth with risk characteristics, the overall extent of underreporting will be calculated in future studies. Nonetheless, hair toxicology was key to characterizing substance use in high-risk youth.

The Cannabinoids Tetrahydrocannabinol, Cannabinol, Cannabidiol, Tetrahydrocannabivarin, and 11-nor-9-carboxy-∆9-THC in Hair

The cannabinoids tetrahydrocannabinol (THC), tetrahydrocannabivarin (THCV), cannabidiol (CBD), cannabinol (CBN) and (-)-11-nor-9-carboxy-∆9-tetrahydrocannabinol (THC-COOH) were determined in 4773 hair samples. Confirmation of THC-COOH was by GC-MS/MS. Confirmation of THC, THCV, CBN and CBD was by LC-MS/MS on an AB Sciex QTRAP 6500+ LC-MS/MS. The purpose of this work was not to utilize any analyte other than THC-COOH as indicative of ingestion, but to assess the absence or presence, and relative concentrations, of the other cannabinoid analytes in hair of marijuana users vs. primarily cannabidiol users. In this regard, ten percent of samples contained significantly higher concentrations of CBD relative to THC than the other 90%. A concentration of CBD that is five times greater than that of THC was proposed as good evidence of primarily CBD ingestion.THC concentrations in the samples ranged from < LOD (5 pg/mg) to 47,808 pg/mg hair, varying widely in the relationship between parent THC and the metabolite THC-COOH. CBN was present in most samples, but concentrations relative to THC decreased with increasing THC concentrations. Only 26% of the samples contained THCV detectable by the method. When present, THCV concentrations averaged 1.77% of THC. A limitation of the study is the lack of subject histories to determine types and amounts of products used and mode of ingestion. Also, not all THC from external contamination may have been removed. Nonetheless, the data provide a useful guide as to what cannabinoids may be found in hair, at what concentrations, under conditions of marijuana vs. likely primarily CBD use.

Identifying and Quantifying Cannabinoids in Biological Matrices in the Medical and Legal Cannabis Era

Background

Cannabinoid analyses generally included, until recently, the primary psychoactive cannabis compound, Δ9-tetrahydrocannabinol (THC), and/or its inactive metabolite, 11-nor-9-carboxy-THC, in blood, plasma, and urine. Technological advances revolutionized the analyses of major and minor phytocannabinoids in diverse biological fluids and tissues. An extensive literature search was conducted in PubMed for articles on cannabinoid analyses from 2000 through 2019. References in acquired manuscripts were also searched for additional articles.

Content

This article summarizes analytical methodologies for identification and quantification of multiple phytocannabinoids (including THC, cannabidiol, cannabigerol, and cannabichromene) and their precursors and/or metabolites in blood, plasma, serum, urine, oral fluid, hair, breath, sweat, dried blood spots, postmortem matrices, breast milk, meconium, and umbilical cord since the year 2000. Tables of nearly 200 studies outline parameters including analytes, specimen volume, instrumentation, and limits of quantification. Important diagnostic and interpretative challenges of cannabinoid analyses are also described. Medicalization and legalization of cannabis and the 2018 Agricultural Improvement Act increased demand for cannabinoid analyses for therapeutic drug monitoring, emergency toxicology, workplace and pain-management drug testing programs, and clinical and forensic toxicology applications. This demand is expected to intensify in the near future, with advances in instrumentation performance, increasing LC-MS/MS availability in clinical and forensic toxicology laboratories, and the ever-expanding knowledge of the potential therapeutic use and toxicity of phytocannabinoids.

Summary

Cannabinoid analyses and data interpretation are complex; however, major and minor phytocannabinoid detection windows and expected concentration ranges in diverse biological matrices improve the interpretation of cannabinoid test results.

Proof of active cannabis use comparing 11-hydroxy-∆9-tetrahydrocannabinol with 11-nor-9-carboxy-tetrahydrocannabinol concentrations

Testing hair for cannabis use has increasingly been scrutinised due to exposure to second-hand smoke or environmental contamination. Confirmation of drug use involving detection of metabolites such as 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH) and 11-hydroxy-delta-9-tetrahydrocannabinol (THC-OH) having very rarely been considered. We developed a new, simplified procedure with regard to expenditure of time and material to determine delta-9-tetrahydrocannabinol (THC, qualitatively), as well as THC-OH and THC-COOH (quantitatively) from 587 hair samples by liquid chromatography-tandem mass spectrometry (LC-MS/MS) which was compared to hitherto established methods (n = 3). Compared to conventional methanolic extraction alkaline dissolution resulted in higher concentrations for THC-OH. Concentrations determined from specimens ranged from 0.01 to 18.7 ng THC/mg hair, 0.05-37.6 pg THC-OH/mg hair, and from 0.1 to 54.3 pg THC-COOH/mg hair. THC was detectable in 70.4% samples along with both metabolites from more than half of these samples. In 12.9% of THC-positive cases, neither THC-OH nor THC-COOH were present. In 8.9% of THC-negative cases, it was possible to detect metabolites either alone or in combination. THC-OH could more frequently be detected than THC-COOH and appeared to be less susceptible to cosmetic treatment. In summary, THC-OH turned out to be a further suitable marker to prove cannabis use. Determination of both metabolites is recommended to unequivocally differentiate consumption from external exposure or contamination.