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“Evidence on the Acute and Residual Neurocognitive Effects of Cannabis Use in Adolescents and Adults: a Systematic Meta-review of Meta-analyses”, Dellazizzo et al 2022

2022-dellazizzo.pdf: “Evidence on the acute and residual neurocognitive effects of cannabis use in adolescents and adults: a systematic meta-review of meta-analyses”⁠, Laura Dellazizzo, Stéphane Potvin, Sabrina Giguère, Alexandre Dumais (2022-01-19; ⁠, ; similar):

Background: Cannabis is among the most consumed psychoactive substances world-wide. Considering changing policy trends regarding the substance, it is crucial to understand more clearly its potential acute and residual adverse effects from a public health viewpoint. Cognitive function is one of the targeted areas with conflicting findings. This meta-review measured the magnitude of acute and residual effects of cannabis on cognition in adolescents and adults provided by meta-analyses and evaluated quality of evidence.

Methods: A systematic search was performed in PubMed⁠, PsycINFO⁠, Web of Science and Google Scholar⁠. Meta-analyses were included if they quantitatively examined the performances of users from the general population on cognitive tasks.

Results: The search retrieved 10 eligible meta-analyses (71 effects sizes, n = 43 761) with evidence ranging from low to moderate quality, which were categorized into domains of cognitive functions: executive functions (k = 7), learning and memory (k = 5), attention (k = 4), processing speed (k = 5), perceptual motor function (k = 2) and language (k = 2).

Verbal learning and memory displayed the most robust evidence and were most impaired by acute cannabis intoxication that persisted after intoxication passed. Small-to-moderate acute and residual adverse effects were reported for executive functioning. Cannabis use led to small deficits in inhibitory processes and flexibility, whereas small-to-moderate deficits were reported for working memory and decision-making. Evidence regarding processing speed and attention has shown that cannabis administration induced small-to-moderate adverse effects and residual neurocognitive deficits were observed in heavy cannabis-using youths. Results showed no statistically-significant difference between cannabis users and non-users on language, and small-to-moderate effects for simple motor skills.

Conclusion: Meta-analytical data on the acute effects of cannabis use on neurocognitive function have shown that cannabis intoxication leads to small to moderate deficits in several cognitive domains. These acute impairments accord with documented residual effects, suggesting that the detrimental effects of cannabis persist beyond acute intake.

…Despite the findings provided in this meta-review, several elements need to be discussed when interpreting results. First and foremost, the meta-analyses discussed comprised cross-sectional data with several analyses having relatively small sample sizes, which limits the inference of a causal relationship between cannabis use and cognition as well as the generalizability of results…Although most of the evidence on the cognitive sequelae of cannabis use has been provided by cross-sectional data associated with methodological limitations, a growing number of longitudinal studies, which are useful to address causal inferences, have emerged. This has led to several reviews examining, among others, evidence provided by prospective designed studies[20, 27, 31, 81]. For instance, Bourque et al 27 noted similar findings to those observed in cross-sectional data. Indeed, most studies showed declines in both executive functioning and verbal learning/​memory[82–95], while results were less consistent for processing speed[82, 85, 88, 90, 94–96]. Furthermore, longitudinal data have similarly shed light on the hypotheses that have been put forth to explain the association between cannabis use and cognitive functions (see Bourque et al 27 for an overview). A first hypothesis, that has received mixed evidence, specifies that cannabis use leads to persistent cognitive impairments. These neurotoxic effects last although cannabis users reduce their intake or quit altogether. While some longitudinal studies suggest that cognitive deficits resolve following abstinence[92, 94], other studies have confirmed that cannabis use frequency led to subsequent long-term cognitive decline (ie. executive function) regardless of prolonged cannabis intake, while adjusting for covariates[84, 87, 97]. Following, the premorbid cognitive vulnerability hypothesis proposes that individuals at increased risk of using the substance more regularly already presented cognitive deficits before cannabis use onset. Several studies have shown that specific cognitive impairments (ie. memory and executive functions) seemed to incline individuals to earlier onset of use in addition to more frequent use in comparison to non-using individuals[83–86, 98]. However, such findings were not evident in all studies[82, 87, 97, 99, 100] and some studies more probably support the common antecedent hypothesis[86, 98], which postulates that common factors (eg. externalizing behaviour) may predispose individuals to both cannabis use and cognitive deficits in users. Hence, results from longitudinal co-twin studies have suggested that cannabis use may not necessarily cause neurocognitive decline, but rather that factors related to family background, such as genetic and shared environmental factors, may more clearly explain worse cognitive performances amid cannabis users[86, 98].

“Independent Contribution of Polygenic Risk for Schizophrenia and Cannabis Use in Predicting Psychotic-like Experiences in Young Adulthood: Testing Gene × Environment Moderation and Mediation”, Elkrief et al 2021

2021-elkrief.pdf: “Independent contribution of polygenic risk for schizophrenia and cannabis use in predicting psychotic-like experiences in young adulthood: testing gene × environment moderation and mediation”⁠, Laurent Elkrief, Bochao Lin, Mattia Marchi, Mohammad H. Afzali, Tobias Banaschewski, Arun L. W. Bokde et al (2021-09-23; ; similar):

Background: It has not yet been determined if the commonly reported cannabis-psychosis association is limited to individuals with pre-existing genetic risk for psychotic disorders.

Methods: We examined whether the relationship between polygenic risk score for schizophrenia (PRS-Sz) and psychotic-like experiences (PLEs), as measured by the Community Assessment of Psychic Experiences-42 (CAPE-42) questionnaire, is mediated or moderated by lifetime cannabis use at 16 years of age in 1740 of the individuals of the European IMAGEN cohort. Secondary analysis examined the relationships between lifetime cannabis use, PRS-Sz and the various sub-scales of the CAPE-42. Sensitivity analyses including covariates, including a PRS for cannabis use, were conducted and results were replicated using data from 1223 individuals in the Dutch Utrecht cannabis cohort.

Results: PRS-Sz statistically-significantly predicted cannabis use (p = 0.027) and PLE (p = 0.004) in the IMAGEN cohort. In the full model, considering PRS-Sz and covariates, cannabis use was also statistically-significantly associated with PLE in IMAGEN (p = 0.007). Results remained consistent in the Utrecht cohort and through sensitivity analyses. Nevertheless, there was no evidence of a mediation or moderation effects.

Conclusions: These results suggest that cannabis use remains a risk factor for PLEs, over and above genetic vulnerability for schizophrenia. This research does not support the notion that the cannabis-psychosis link is limited to individuals who are genetically predisposed to psychosis and suggests a need for research focusing on cannabis-related processes in psychosis that cannot be explained by genetic vulnerability.

“Adolescent Cannabis Use and Adult Psychoticism: A Longitudinal Co-twin Control Analysis Using Data from Two Cohorts”, Schaefer et al 2021

2021-schaefer.pdf: “Adolescent cannabis use and adult psychoticism: A longitudinal co-twin control analysis using data from two cohorts”⁠, Jonathan D. Schaefer, Seon-Kyeong Jang, Scott Vrieze, William G. Iacono, Matt McGue, Sylia Wilson (2021-09-23; ; similar):

Epidemiological studies have repeatedly shown that individuals who use cannabis are more likely to develop psychotic disorders than individuals who do not. It has been suggested that these associations represent a causal effect of cannabis use on psychosis, and that psychosis risk may be particularly elevated when use occurs in adolescence or in the context of genetic vulnerability. This study, however, does not support these hypotheses, suggesting instead that observed associations are more likely due to confounding by common vulnerability factors.

Observational studies have repeatedly linked cannabis use and increased risk of psychosis. We sought to clarify whether this association reflects a causal effect of cannabis exposure or residual confounding.

We analyzed data from 2 cohorts of twins who completed repeated, prospective measures of cannabis use (n = 1544) and cannabis use disorder symptoms (n = 1458) in adolescence and a dimensional measure of psychosis-proneness (the Personality Inventory for DSM-5 Psychoticism scale) in adulthood. Twins also provided molecular genetic data, which were used to estimate polygenic risk of schizophrenia.

Both cumulative adolescent cannabis use and use disorder were associated with higher Psychoticism scores in adulthood. However, we found no evidence of an effect of cannabis on Psychoticism or any of its facets in co-twin control models that compared the greater-cannabis-using twin to the lesser-using co-twin. We also observed no evidence of a differential effect of cannabis on Psychoticism by polygenic risk of schizophrenia.

Although cannabis use and disorder are consistently associated with increased risk of psychosis, the present results suggest this association is likely attributable to familial confounds rather than a causal effect of cannabis exposure. Efforts to reduce the prevalence and burden of psychotic illnesses thus may benefit from greater focus on other therapeutic targets.

…One powerful approach that can be helpful in testing for residual confounding involves comparing both monozygotic (MZ) and dizygotic (DZ) twins who differ in their cannabis exposure. Termed “discordant twin” or “co-twin control” analyses, this approach allows for examination of the effects of cannabis use while simultaneously controlling for all measured and unmeasured genetic and environmental factors shared between twins (McGue et al 2010). If cannabis is a causal contributor to long-term psychotic illness, both MZ and DZ twins who use more cannabis in adolescence than their co-twins should be more likely to experience psychosis. If this “twin difference” is not observed, it suggests the association between cannabis and psychosis is likely driven by confounding familial factors.

To date, only 2 studies have tested links between cannabis and psychotic symptoms using co-twin comparisons. Both reported that these associations were largely attributable to shared familial factors, but also that they observed evidence consistent with a small, independent, and potentially causal effect (Karcher et al 2019⁠; Nesvåg et al 2017). However, these studies are also characterized by a shared set of limitations, which constrains the implications of their findings.

One limitation is that both studies used data from cross-sectional surveys of adult twins, which precluded tests focusing specifically on cannabis use occurring during the sensitive period of adolescence. A second limitation is that both studies used single, lifetime assessments of cannabis use and use disorder, which are subject to the many well-documented sources of bias that reduce the accuracy of retrospective measures (eg. normal forgetting, revisionist recall). Methodological research suggests that this reduction in accuracy may be particularly problematic in a twin study context, as exposure measurement error tends to bias within-twin-pair estimates more dramatically than corresponding unpaired associations (Frisell et al 2012). Finally, the relatively coarse, binary measures of cannabis exposure used by these studies (including current use [yes/​no], frequent use [>100×/​not], and lifetime use disorder) are characterized by reduced variability relative to more continuous measures of cannabis use, and thus a reduced power to detect effects. Co-twin control studies of cannabis and psychosis that employ repeated, dimensional measures of cannabis use over time are thus needed to address these concerns and establish more accurate estimates of cannabis’s true causal effects.

The present study aimed to address these needs by examining associations between adolescent cannabis exposure and psychosis in a twin sample that combines data from 2 longitudinal cohort studies at the Minnesota Center for Twin and Family Research (MCTFR). In contrast to the few previous co-twin control studies, twins in these cohorts were assessed repeatedly using gold-standard, self-report and interview measures of cannabis use administered prospectively throughout adolescence. Using these measures, we created a continuous index measuring cumulative cannabis use prior to and during adolescence (“adolescent cannabis use index”) and a binary variable indicating presence or absence of a diagnosable cannabis use disorder (ie. abuse or dependence) prior to and during adolescence.

Does Adolescent Cannabis Exposure Predict Greater Adult Psychoticism Independent of Shared Environmental and Genetic Factors, Consistent With a Causal Effect? Results from co-twin control analyses are also presented in Table 4. Co-twin control models capitalize on twin differences to examine effects of cannabis exposure accounting for familial liability. In contrast to our individual-level analyses, these models indicated predominantly statistically-significant between-pair effects (estimates ranging from 0.14 to 0.20 for cannabis use index and from 0.43 to 0.59 for cannabis use disorder), suggesting an effect of preexisting, shared familial liability. They also indicated consistently small, nonsignificant within-pair effects (estimates ranging from −0.01 to 0.01 for cannabis use index and from −0.04 to 0.06 for cannabis use disorder), suggesting no effect of cannabis exposure (for full model results, see Supplemental Table 6).

Do We Find Evidence Suggesting a Potential Causal Effect of Cannabis on Psychoticism in Genetically Vulnerable Individuals? Although we observed no statistically-significant within-pair associations suggesting a causal effect of cannabis exposure on psychoticism in the full analytic sample, this does not rule out the possibility that cannabis may increase psychoticism in subsets of particularly vulnerable individuals. Consequently, we next conducted analyses examining this possibility using one of the most obvious indicators of potential vulnerability: polygenic risk of schizophrenia. Results from these analyses are presented in Table 5. Our first set of models showed that, consistent with our expectations, twins with higher schizophrenia polygenic risk scores tended to score higher on our measure of adult psychoticism as well as its facet scales. Higher polygenic risk of schizophrenia was also associated with higher scores on our adolescent cannabis use index (β [95% CI] = 0.08 [0.02, 0.14], p = 0.014), and higher likelihood of meeting criteria for an adolescent cannabis use disorder (OR [95% CI] = 1.53 [1.11, 2.20], p = 0.010). Our second set of models indicated that schizophrenia polygenic risk and each measure of cannabis exposure both generally made incremental contributions to the prediction of scores on the adult psychoticism scale and its facets. Our third set of models tested the hypothesis that cannabis and polygenic risk interact such that individuals with higher levels of genetic risk are more affected by adolescent cannabis exposure. Interactions between the cannabis use index and polygenic risk in these models were all nonsignificant (βs [95% CIs] ranging from −0.04 [−0.10, 0.02] to 0.04 [−0.02, 0.10], all ps ≥ 0.213). Similarly, all interactions between cannabis use disorder and polygenic risk in corresponding models were also nonsignificant (βs [95% CIs] ranging from −0.04 [−0.20, 0.12] to 0.12 [−0.04, 0.28], all ps ≥ 0.141), except in the model predicting Perceptual Dysregulation (β [95% CI] = 0.17 [0.01, 0.34], p = 0.038). Nevertheless, because this single statistically-significant result would not survive correction for multiple testing, we conclude that results suggest little to no moderation of the effects of cannabis on Psychoticism by polygenic risk of schizophrenia overall.

“Decriminalization of Cannabis; the Effects on the Drug Market via the Dark Web”, Boekhoudt 2021

2021-boekhoudt.pdf: “Decriminalization of Cannabis; the effects on the drug market via the dark web”⁠, Nicolien Boekhoudt (2021-07-02; ; backlinks):

The rise of the internet the drug market partly moved to the dark web, and the rise of discussion regarding decriminalization of drugs.

That’s what leads to this paper, where research has been performed to find if there is a dependency between drug law and the number of drug transactions. This paper explains research performed on existing data on the dark web. It covers how the statistical analysis on the available data has been performed.

This research shows that there are statistically-significant differences between the number of transactions between countries. Whereas it does not show that there is a dependency between policy and number of transaction. It does show which countries have a high number of transactions compared to other countries.

[Keywords: drug traffic, legalization, decriminalization, cannabis, marijuana, dark web, EU]

“The Relationship between Cannabis and Schizophrenia: a Genetically Informed Perspective”, Johnson et al 2021

2021-johnson.pdf: “The relationship between cannabis and schizophrenia: a genetically informed perspective”⁠, Emma C. Johnson, Alexander S. Hatoum, Joseph D. Deak, Renato Polimanti, Robin M. Murray, Howard J. Edenberg et al (2021-05-05; ⁠, ; similar):

Background and Aims: While epidemiological studies support a role for heavy, high-potency cannabis use on first-episode psychosis, genetic models of causation suggest reverse causal effects of schizophrenia on cannabis use liability. We estimated the genetic relationship between cannabis use disorder (CUD) and schizophrenia (SCZ) and tested whether liability for CUD is causally associated with increased liability to SCZ while adjusting for tobacco smoking.

Design: This study used summary statistics from published genome-wide association studies (GWAS). We used genomic structural equation modeling (GSEM)⁠, latent causal variable (LCV) analysis⁠, and multivariable Mendelian randomization to examine genetic relationships between CUD, cannabis ever-use, ever-smoked tobacco regularly, nicotine dependence and SCZ, and to test for a causal relationship between liability to CUD and liability to SCZ.

Setting: Genome-wide association studies were published previously as part of international consortia.

Participants: Sample sizes of the GWAS summary statistics used in this study ranged from 161 405 to 357 806 individuals of European ancestry.

Measurements: Genome-wide summary statistics for CUD and SCZ were the primary measurements, while summary statistics for cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence were included as additional variables in the genomic structural equation models and the multivariable Mendelian randomization analyses.

Findings: Genetic liability to CUD was statistically-significantly associated with SCZ [β = 0.29, 95% confidence interval (CI) = 0.11, 0.46, p = 0.001], even when accounting for cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence as simultaneous predictors. We found mixed evidence of a causal relationship, with the latent causal variable analysis finding no evidence of causality (genetic causality proportion = −0.08, 95% CI = −0.40, 0.23, p = 0.87) but the multivariable Mendelian randomization analyses suggesting a statistically-significant, risk-increasing effect of CUD on liability to SCZ (β = 0.10, 95% CI = 0.02, 0.18, p = 0.02), accounting for the additional risk factors (cannabis ever-use, ever-smoked tobacco regularly and nicotine dependence).

Conclusions: Genetic liability for cannabis use disorder appears to be robustly associated with schizophrenia, above and beyond tobacco smoking and cannabis ever-use, with mixed evidence to support a causal relationship between cannabis use disorder and schizophrenia.

[Keywords: cannabis, genome-wide association study, genomic structural equation modeling, latent causal variable model, multivariable Mendelian randomization, schizophrenia, tobacco]

“Is Marijuana Really a Gateway Drug? A Nationally Representative Test of the Marijuana Gateway Hypothesis Using a Propensity Score Matching Design”, Jorgensen 2021

2021-jorgensen.pdf: “Is marijuana really a gateway drug? A nationally representative test of the marijuana gateway hypothesis using a propensity score matching design”⁠, Cody Jorgensen (2021-04-06; ; similar):

Marijuana use has been proposed to serve as a “gateway” that increases the likelihood that users will engage in subsequent use of harder and more harmful substances, known as the marijuana gateway hypothesis (MGH). The current study refines and extends the literature on the MGH by testing the hypothesis using rigorous quasi-experimental, propensity score-matching methodology in a nationally representative sample.

Using 3 waves of data from the National Longitudinal Study of Adolescent to Adult Health (1994–2002), 18 propensity score-matching tests of the marijuana gateway hypothesis were conducted. 6 of the 18 tests were statistically-significant; however, only 3 were substantively meaningful. These 3 tests found weak effects of frequent marijuana use on illicit drug use but they were also sensitive to hidden bias.

Results from this study indicate that marijuana use is not a reliable gateway cause of illicit drug use. As such, prohibition policies are unlikely to reduce illicit drug use.

“A New and Improved Genome Sequence of Cannabis Sativa”, Braich et al 2020

“A New and Improved Genome Sequence of Cannabis sativa”⁠, Shivraj Braich, Rebecca C. Baillie, German C. Spangenberg, Noel O. I. Cogan (2020-12-13; similar):

Cannabis is a diploid species (2n = 20), the estimated haploid genome sizes of the female and male plants using flow cytometry are 818 and 843 Mb respectively. Although the genome of Cannabis has been sequenced (from hemp, wild and high-THC strains), all assemblies have significant gaps. In addition, there are inconsistencies in the chromosome numbering which limits their use. A new comprehensive draft genome sequence assembly (~900 Mb) has been generated from the medicinal cannabis strain Cannbio-2, that produces a balanced ratio of cannabidiol and delta-9-tetrahydrocannabinol using long-read sequencing. The assembly was subsequently analysed for completeness by ordering the contigs into chromosome-scale pseudomolecules using a reference genome assembly approach, annotated and compared to other existing reference genome assemblies. The Cannbio-2 genome sequence assembly was found to be the most complete genome sequence available based on nucleotides assembled and BUSCO evaluation in Cannabis sativa with a comprehensive genome annotation. The new draft genome sequence is an advancement in Cannabis genomics permitting pan-genome analysis, genomic selection as well as genome editing.

“Use of Genetically Informed Methods to Clarify the Nature of the Association Between Cannabis Use and Risk for Schizophrenia”, Gillespie & Kendler 2020

2020-gillespie.pdf: “Use of Genetically Informed Methods to Clarify the Nature of the Association Between Cannabis Use and Risk for Schizophrenia”⁠, Nathan A. Gillespie, Kenneth S. Kendler (2020-11-04; ⁠, ; similar):

When evaluating efforts to reduce cannabis use as a means of preventing schizophrenia, the proportion of this association that is causal is critical. Given the high heritability of schizophrenia, we reviewed reports that relied on 4 genetic methods (Table) capable of addressing the nature of the cannabis-schizophrenia association. We evaluated 3 hypotheses: (1) it is entirely causal, (2) it is partly causal and partly confounded by genetic/​familial effects and/​or reverse causation, or (3) it is entirely noncausal. (We are unable to review the literature regarding short-term psychiatric effects of cannabis administration.)

Confounding here refers to genetic risks that increase the probability of both using/​misusing cannabis and schizophrenia, thereby explaining at least part of the association. In this example, reverse causality refers to a theoretical underlying mechanism in which schizophrenia liability or symptoms increase the risk of using cannabis. The first 2 methods are natural experiments, discordant relative design, and Mendelian randomization, that directly evaluate each hypothesis. The 2 other methods, linkage disequilibrium score regression (LDSR) and polygenic risks scores (PRSs), measure genetic associations, which, although less definitive, provide evidence of correlated genetic risks that undermine the plausibility of hypothesis 1.

…As summarized in the Table, when triangulating across 4 genetically informative methods, the findings, with considerable but not complete consistency, argue against hypothesis 1. Although the number of available studies is modest, there is relatively reliable evidence across multiple methods that the cannabis-schizophrenia association stems partly from shared familial/​genetic risk factors and/​or reverse causation. We also have good evidence against hypothesis 3, ie, familial/​genetic risk factors explaining all of the association. The 1 study that directly estimated the degree of familial confounding 4 suggests that it is substantial and accounts for more than half of the observed association. Results from LDSR and PRS methods suggest more modest degrees of confounding while raising the possibility of reverse causation. A prudent conclusion is that the observed cannabis-schizophrenia association in the general population may arise from some potential causal effect of cannabis on the risk of schizophrenia, while an appreciable proportion of the association is not causal. When based on associations observed in the population (ie. without control for confounders), claims made about the changes in risk for schizophrenia stemming from changing levels of cannabis use are very likely to be exaggerated and potentially substantially so.

“Illicit Drug Prices and Quantity Discounts: A Comparison between a Cryptomarket, Social Media, and Police Data”, Moeller et al 2020

“Illicit drug prices and quantity discounts: A comparison between a cryptomarket, social media, and police data”⁠, Kim Moeller, Rasmus Munksgaard, Jakob Demant (2020-10-09; ; backlinks; similar):

Background: Illicit drugs are increasingly sold on cryptomarkets and on social media. Buyers and sellers perceive these online transactions as less risky than conventional street-level exchanges. Following the Risks & Prices framework, law enforcement is the largest cost component of illicit drug distribution. We examine whether prices on cryptomarkets are lower than prices on social media and prices reported by law enforcement on primarily offline markets.

Methods: Data consists of online advertisements for illicit drugs in Sweden in 2018, scraped from the cryptomarket Flugsvamp 2.0 (n = 826) and collected with digital ethnography on Facebook (n = 446). Observations are advertisements for herbal cannabis (n = 421), cannabis resin, hash (n = 594), and cocaine (n = 257) from 156 sellers. Prices are compared with estimates from Swedish police districts (n = 53). Three multilevel linear regression models are estimated, one for each drug type, comparing price levels and discount elasticities for each platform and between sellers on each platform. Results: Price levels are similar on the two online platforms, but cocaine is slightly more expensive on social media. There are quantity discounts for all three drug types on both platforms with coefficients between −0.10 and −0.21. Despite the higher competition between sellers on cryptomarkets, prices are not lower compared to social media. Online price levels for hash and cocaine are similar to those reported by police at the 1 g level. Conclusion

Mean prices and quantity discounts are similar in the two online markets. This provides support for the notion that research on cryptomarkets can also inform drug market analysis in a broader sense. Online advertisements for drugs constitute a new detailed transaction-level data source for supply-side price information for research.

[Keywords: drug prices, risks and prices, Sweden, cryptomarket, social media, online drug sales]

“Familial Factors May Not Explain the Effect of Moderate-to-heavy Cannabis Use on Cognitive Functioning in Adolescents: a Sibling-comparison Study”, Ellingson et al 2020

2020-ellingson.pdf: “Familial factors may not explain the effect of moderate-to-heavy cannabis use on cognitive functioning in adolescents: a sibling-comparison study”⁠, Jarrod M. Ellingson, J. Megan Ross, Evan Winiger, Michael C. Stallings, Robin P. Corley, Naomi P. Friedman et al (2020-09-03; ; similar):

Aims: To examine whether moderate adolescent cannabis use has neurocognitive effects that are unexplained by familial confounds, which prior family-controlled studies may not have identified.

Design: A quasi-experimental, sibling-comparison design was applied to a prospective, observational study of adolescents with moderate cannabis use. Participants were recruited from 2001 to 2006 (mean age = 17 years). A second wave of data was collected from 2008 to 2013 (mean age = 24 years).

Setting: Two US metropolitan communities.

Participants: A total of 1192 adolescents from 596 families participated in this study. Participants were primarily male (64%) and racially and ethnically diverse (non-Hispanic white = 45%). A sibling in each family was a clinical proband identified due to delinquent behaviors. Whereas prior family-controlled studies have used samples of primarily infrequent cannabis users (mean = 1–2 days/​month), participants here endorsed levels of cannabis use comparable to findings from epidemiological cohort studies (mean = 7–9 days/​month).

Measurements: Semi-structured clinical interviews assessed drug use, and a neuropsychological battery assessed cognitive abilities. Covariates included age at assessment, gender and alcohol use.

Findings: After correcting for multiple testing, a greater frequency and earlier onset of regular cannabis use were associated with poorer cognitive performance, specifically on tests of verbal memory. Further, after accounting for familial factors shared by siblings and alcohol use, poorer verbal memory performance was still associated with greater life-time frequency of cannabis use at wave 1 [b = −0.007 (−0.002, −0.012), adjusted p = 0.036]; earlier cannabis use at wave 2 [b = −0.12 (−0.05, −0.19), adjusted p = 0.006; b = −0.14 (−0.06, −0.23), adjusted p = 0.006]; and greater frequency of past 6 months use at wave 2 [b = −0.02 (−0.01, −0.03), adjusted p = 0.002; b = −0.02 (−0.01, −0.03), adjusted p = 0.008].

Conclusions: Moderate adolescent cannabis use may have adverse effects on cognitive functioning, specifically verbal memory, that cannot be explained by familial factors.

“A World Without Pain: Does Hurting Make Us Human?”, Levy 2020

“A World Without Pain: Does hurting make us human?”⁠, Ariel Levy (2020-01-06; backlinks; similar):

Cameron is entirely insensitive to physical pain. As a child, she fell and hurt her arm while roller-skating, but had no idea she’d broken it until her mother noticed that it was hanging strangely. Giving birth was no worse…Cameron was having a trapeziectomy, an operation to remove a small bone at the base of the thumb joint. Though her hands never hurt, they’d become so deformed by arthritis that she couldn’t hold a pen properly. She’d had a similar experience with her hip, which had recently been replaced; it didn’t hurt, but her family noticed that she wasn’t walking normally. She saw her local doctor about it several times, but the first question was always “How much pain are you in?” And the answer was always “None.” (“The third time I was there I think they figured, ‘We’ll just take an X-ray to shut this woman up’”, Cameron told me. “Then the X-ray came in and it was really bad. Everything was all distorted and mangled and crumbling. He said, ‘Wow. This has got to be done.’”)…Cameron is beguiled by the idea that she can help alleviate others’ suffering—she remembers the terrible migraines that tormented her mother. Her father, however, was pain-free. “I never saw him take an aspirin”, Cameron said. “I’m convinced he was the same as me, because I never heard my father complaining about any pain, ever. He died suddenly, of a brain hemorrhage—I think other people would have had a warning.” ·…People with severe congenital neuropathy tend to die young, because they injure themselves so frequently and severely. (Without pain, children are in constant danger. They swallow something burning hot, the esophagus ruptures, bacteria spill into the internal organs, and terminal sepsis sets in. They break their necks roughhousing. To protect some patients, doctors have removed all their teeth to prevent them from chewing off their tongues and bleeding to death.) ·…Cameron does not have neuropathy: she can feel all the sensations the rest of us do, except pain. The most striking difference between her and everyone else is the way she processes endocannabinoids—chemicals that exist naturally in every human brain. Endocannabinoids mitigate our stress response, and they bind to the same receptors as the THC in the kind of cannabis you smoke. Normally, they are broken down by an enzyme called fatty acid amide hydrolase, or FAAH. But Cameron has a mutation on her FAAH gene that makes the enzyme less effective—so her endocannabinoids build up. She has extraordinarily high levels of one in particular: anandamide, whose name is derived from the Sanskrit word for “bliss.” · About a third of the population has a mutation in the FAAH gene, which provides increased levels of anandamide. “That phenotype—low levels of anxiety, forgetfulness, a happy-go-lucky demeanor—isn’t representative of how everyone responds to cannabis, but you see a lot of the prototypical changes in them that occur when people consume cannabis”, said Matthew Hill, a biologist at the University of Calgary’s Hotchkiss Brain Institute, who was a co-author of the Cameron paper. The FAAH gene, like every gene, comes in a pair. People who have the mutation in one allele of the gene seem a little high; people who have it in both even more so. Jo Cameron is fully baked. “When I met Jo for the first time, I was just struck by her”, Cox, an affable forty-year-old with a scruffy beard, told me, one afternoon in his lab at U.C.L. “She was very chatty. Did you notice that?” (It’s hard to miss.) “I said to her, ‘Are you worried about what’s going to happen today?’ Because she was meeting our clinicians to have a skin biopsy and do quantitative sensory testing—pain-threshold tests. She said, ‘No. In fact, I’m never worried about anything.’” Cox told me that it was difficult to get through everything in the time they’d allotted, because Cameron was so friendly and loquacious with the scientists, even as they burned her, stuck her with pins, and pinched her with tweezers until she bled. This imperviousness to pain is what makes her distinct from everyone else with a FAAH mutation. They, like even the most committed stoners, can still get hurt. ·…I asked Matthew Hill—a renowned expert on cannabinoids and stress—if there was any downside to Cameron’s biology, and he laughed out loud. “Yes! From an evolutionary perspective, it would be tremendously destructive for a species to have that”, he said. Without fear, you drown in waves that you shouldn’t be swimming in; you take late-night strolls in cities that you don’t know; you go to work at a construction site and neglect to put on a hard hat. “Her phenotype is only beneficial in an environment where there is no danger”, Hill asserted. “If you can’t be concerned about a situation where you’d be at risk of something adverse happening to you, you are more likely to put yourself in one. Anxiety is a highly adaptive process: that’s why every mammalian species exhibits some form of it.” · Unlike other pain-insensitive people, Cameron has made it into her seventies without getting badly hurt. Sometimes she realizes that she’s burning her hand on the stove because she smells singeing; sometimes she cuts herself in the garden and sees that she’s bleeding. But none of that has been severe, and Cameron did raise two children safely into adulthood. “The human brain is very capable of learning, ‘This is what’s appropriate to do in this situation’”, Hill said. Cameron’s relative cautiousness may have developed imitatively. “And there may not have been that much threat presented to her—she’s lived in a rural community in Scotland”, he concluded. “Maybe she hasn’t had to deal with that much that would physically or emotionally harm her.” ·…One complicating question is how much of Cameron’s Cameronness is really a consequence of her FAAH mutation and FAAH OUT deletion. She has plenty of other genes, after all, and her upbringing and her early environment also played a role in making her who she is. Since the paper was published, Matthew Hill has heard from half a dozen people with pain insensitivity, and he told me that many of them seemed nuts. “If you had this phenotype and weren’t a generally pleasant person like Jo—maybe you’re, like, a douche-y frat boy—the way that you would process this might be entirely different. Our whole perception of this phenotype is explicitly based on the fact that it was Jo who presented it.”

“Sequence and Annotation of 42 Cannabis Genomes Reveals Extensive Copy Number Variation in Cannabinoid Synthesis and Pathogen Resistance Genes”, McKernan et al 2020

“Sequence and annotation of 42 cannabis genomes reveals extensive copy number variation in cannabinoid synthesis and pathogen resistance genes”⁠, Kevin J. McKernan, Yvonne Helbert, Liam T. Kane, Heather Ebling, Lei Zhang, Biao Liu, Zachary Eaton, Stephen McLaughlin et al (2020-01-05; similar):

Cannabis is a diverse and polymorphic species. To better understand cannabinoid synthesis inheritance and its impact on pathogen resistance, we shotgun sequenced and assembled a Cannabis trio (sibling pair and their offspring) utilizing long read single molecule sequencing. This resulted in the most contiguous Cannabis sativa assemblies to date. These reference assemblies were further annotated with full-length male and female mRNA sequencing (Iso-Seq) to help inform isoform complexity, gene model predictions and identification of the Y chromosome. To further annotate the genetic diversity in the species, 40 male, female, and monoecious cannabis and hemp varietals were evaluated for copy number variation (CNV) and RNA expression. This identified multiple CNVs governing cannabinoid expression and 82 genes associated with resistance to Golovinomyces chicoracearum, the causal agent of powdery mildew in cannabis. Results indicated that breeding for plants with low tetrahydrocannabinolic acid (THCA) concentrations may result in deletion of pathogen resistance genes. Low THCA cultivars also have a polymorphism every 51 bases while dispensary grade high THCA cannabis exhibited a variant every 73 bases. A refined genetic map of the variation in cannabis can guide more stable and directed breeding efforts for desired chemotypes and pathogen-resistant cultivars.

“Analysis of the Supply of Drugs and New Psychoactive Substances by Europe-based Vendors via Darknet Markets in 2017–18: Background Paper Commissioned by the EMCDDA for the EU Drug Markets Report 2019”, Christin & Thomas 2019

“Analysis of the supply of drugs and new psychoactive substances by Europe-based vendors via darknet markets in 2017–18: Background paper commissioned by the EMCDDA for the EU Drug Markets Report 2019”⁠, Nicolas Christin, Jeremy Thomas (2019-11-21; ; backlinks; similar):

Online anonymous marketplaces are a relatively recent technological development that enables sellers and buyers to transact online with far stronger anonymity guarantees than are available on traditional electronic commerce platforms. This has led certain individuals to engage in transactions of illicit or illegal goods. We investigated how commerce on online anonymous marketplaces evolved after the takedown of the AlphaBay marketplace. Namely, we studied, over the summers of 2017 and 2018, a collection of market-places—Dream Market, TradeRoute, Berlusconi, and Valhalla. In this report, we present an analysis of sales, with a focus on the drug supply coming from the European Union (EU). Keeping in mind the limitations inherent to such data collection, we found that, for the period and the marketplaces considered:

  • The overall ecosystem appears to have (slightly) grown again since the combined takedown of the AlphaBay and Hansa marketplaces, and now exceeds EUR 750 000 euros per day. This calls into question the long-term impact of such takedowns on the overall online anonymous marketplace ecosystem.
  • Dream Market is overwhelmingly the dominant marketplace, and its daily volume exceeds previous numbers gathered for AlphaBay (Christin, 2017).
  • EU-based suppliers represent ~43% of all drug sales; this is in line with the 46% for marketplaces previously studied (Christin, 2016) in the 2011–15 period, and a marked increase compared with the roughly 25% observed in the subsequent AlphaBay study (Christin, 2017).
  • EU-originating drugs continued to come primarily from Germany, the Netherlands, and the United Kingdom.
  • Cannabis, cocaine and other stimulants altogether continued to represent the majority of all EU-based drug sales.
  • The supply of new psychoactive substances (NPS) remained modest with revenues below EUR 10 000 per day at market peak, but these slightly increased compared with our previous measurements.
  • As in our previous studies, marketplace vendors primarily operated in the retail space, but there was evidence of larger (bulk) sales. Volume-based discounting tended to occur, albeit at relatively modest levels.
  • As in our previous studies, half of the vendors specialised in one type of drug, and half of the drug sellers tended to stick to a given weight category.
  • Most of the trends observed in this report confirm what we had previously found for other market-places in the 2011–17 period (Christin, 2016, 2017). In other words, despite takedowns and scams, the ecosystem, as a whole, appears relatively stable over time, with the fluctuation in the European sales share noted above indicating an exception.

…we collected 35 scrapes of four markets—Dream Market, Traderoute, Valhalla, and Berlusconi Market—between summer 2017 and summer 2018.

[Full report: “EU Drug Markets Report: 2019”⁠, DOI: 10.2810/561192.]

“Investigating the Causal Effect of Cannabis Use on Cognitive Function With a Quasi-experimental Co-twin Design”, Ross et al 2019

2019-ross.pdf: “Investigating the causal effect of cannabis use on cognitive function with a quasi-experimental co-twin design”⁠, J. Megan Ross, Jarrod M. Ellingson, Soo Hyun Rhee, John K. Hewitt, Robin P. Corley, Jeffrey M. Lessem et al (2019-11-02; )

“Sibling Comparisons Elucidate the Associations between Educational Attainment Polygenic Scores and Alcohol, Nicotine and Cannabis”, Salvatore et al 2019

2019-salvatore.pdf: “Sibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabis”⁠, Jessica E. Salvatore, Peter B. Barr, Mallory Stephenson, Fazil Aliev, Sally I‐Chun Kuo, Jinni Su, Arpana Agrawal et al (2019-10-28; )

“Large-scale GWAS Reveals Insights into the Genetic Architecture of Same-sex Sexual Behavior”, Ganna et al 2019

“Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior”⁠, Andrea Ganna, Karin J. H. Verweij, Michel G. Nivard, Robert Maier, Robbee Wedow, Alexander S. Busch, Abdel Abdellaoui et al (2019-08-29; ⁠, ⁠, ⁠, ; similar):

Twin studies and other analyses of inheritance of sexual orientation in humans has indicated that same-sex sexual behavior has a genetic component. Previous searches for the specific genes involved have been underpowered and thus unable to detect genetic signals. Ganna et al 2019 perform a genome-wide association study on 493,001 participants from the United States, the United Kingdom, and Sweden to study genes associated with sexual orientation (see the Perspective by Mills). They find multiple loci implicated in same-sex sexual behavior indicating that, like other behavioral traits, nonheterosexual behavior is polygenic.

Introduction: Across human societies and in both sexes, some 2 to 10% of individuals report engaging in sex with same-sex partners, either exclusively or in addition to sex with opposite-sex partners. Twin and family studies have shown that same-sex sexual behavior is partly genetically influenced, but previous searches for the specific genes involved have been underpowered to detect effect sizes realistic for complex traits.

Rationale: For the first time, new large-scale datasets afford sufficient statistical power to identify genetic variants associated with same-sex sexual behavior (ever versus never had a same-sex partner), estimate the proportion of variation in the trait accounted for by all variants in aggregate, estimate the genetic correlation of same-sex sexual behavior with other traits, and probe the biology and complexity of the trait. To these ends, we performed genome-wide association discovery analyses on 477,522 individuals from the United Kingdom and United States, replication analyses in 15,142 individuals from the United States and Sweden, and follow-up analyses using different aspects of sexual preference.

Results: In the discovery samples (UK Biobank and 23andMe), 5 autosomal loci were statistically-significantly associated with same-sex sexual behavior. Follow-up of these loci suggested links to biological pathways that involve sex hormone regulation and olfaction. 3 of the loci were statistically-significant in a meta-analysis of smaller, independent replication samples. Although only a few loci passed the stringent statistical corrections for genome-wide multiple testing and were replicated in other samples, our analyses show that many loci underlie same-sex sexual behavior in both sexes. In aggregate, all tested genetic variants accounted for 8 to 25% of variation in male and female same-sex sexual behavior, and the genetic influences were positively but imperfectly correlated between the sexes [genetic correlation coefficient (rg)= 0.63; 95% confidence intervals, 0.48 to 0.78]. These aggregate genetic influences partly overlapped with those on a variety of other traits, including externalizing behaviors such as smoking, cannabis use, risk-taking, and the personality trait “openness to experience.” Additional analyses suggested that sexual behavior, attraction, identity, and fantasies are influenced by a similar set of genetic variants (rg > 0.83); however, the genetic effects that differentiate heterosexual from same-sex sexual behavior are not the same as those that differ among nonheterosexuals with lower versus higher proportions of same-sex partners, which suggests that there is no single continuum from opposite-sex to same-sex preference.

Conclusion: Same-sex sexual behavior is influenced by not one or a few genes but many. Overlap with genetic influences on other traits provides insights into the underlying biology of same-sex sexual behavior, and analysis of different aspects of sexual preference underscore its complexity and call into question the validity of bipolar continuum measures such as the Kinsey scale. Nevertheless, many uncertainties remain to be explored, including how sociocultural influences on sexual preference might interact with genetic influences. To help communicate our study to the broader public, we organized workshops in which representatives of the public, activists, and researchers discussed the rationale, results, and implications of our study.

“Cannabis Prices on the Dark Web”, Cerveny & Ours 2019

“Cannabis Prices on the Dark Web”⁠, Jakub Cerveny, Jan C. van Ours (2019-08-13; ; backlinks; similar):

This paper examines prices of cannabis sold over the anonymous internet marketplace AlphaBay. We analyze cannabis prices of 500 listings from about 140 sellers, originating from 18 countries. We find that both listing characteristics and country characteristics matter. Cannabis prices are lower if sold in larger quantities, so there is a clear quantity discount. Cannabis prices increase with perceived quality. Cannabis prices are also higher when the seller is from a country with a higher GDP per capita or higher electricity prices. The internet based cannabis market seems to be characterized by monopolistic competition where many sellers offer differentiated products with quality variation causing a dispersion of cannabis prices and sellers have some control over the cannabis prices.

“Cannabis Use, Depression and Self-harm: Phenotypic and Genetic Relationships”, Hodgson et al 2019

“Cannabis use, depression and self-harm: phenotypic and genetic relationships”⁠, K. Hodgson, J. R. I. Coleman, S. P. Hagenaars, K. L. Purves, K. Glanville, S. W. Choi, P. O’Reilly, G. Breen et al (2019-02-14; similar):

Background and Aims

The use of cannabis has previously been linked to both depression and self-harm, however the role of genetics in this relationship are unclear. We aimed to examine the phenotypic and genetic relationships between these traits.

Design: Genetic and cross-sectional phenotypic data collected through UK Biobank, together with consortia genome-wide association study summary statistics. These data were used to assess the phenotypic and genetic relationship between cannabis use, depression and self harm.

Setting: UK, with additional international consortia data

Participants: N = 126,291 British adults aged between 40 and 70 years, recruited into UK Biobank

Measurements: Genome-wide genetic data, phenotypic data on lifetime history of cannabis use, depression and self-harm.


In UK Biobank, cannabis use is associated with increased likelihood of depression (OR = 1.64, 95% CI = 1.59–1.70, p = 1.19×10−213) and self-harm (OR = 2.85, 95% CI = 2.69–3.01, p = 3.46×10−304). The strength of this phenotypic association is stronger when more severe trait definitions of cannabis use and depression are considered. Additionally, statistically-significant genetic correlations are seen between cannabis use and depression using consortia summary statistics (rg = 0.289, SE = 0.036, p = 1.45×10−15). Polygenic risk scores for cannabis use and depression both explain a small but significant proportion of variance in cannabis use, depression and self harm within a UK Biobank target sample. However, two-sample Mendelian randomisation analyses were not significant.

Conclusion: Cannabis use is both phenotypically and genetically associated with depression and self harm. Future work dissecting the causal mechanism linking these traits may have implications for cannabis users.

“Rationality on the Fringes”, Hardy 2019

2019-hardy.pdf: “Rationality on the Fringes”⁠, Robert Augustus Hardy (2019-01-01; ; backlinks)

“Genetic Predisposition vs Individual-Specific Processes in the Association Between Psychotic-like Experiences and Cannabis Use”, Karcher et al 2019

“Genetic Predisposition vs Individual-Specific Processes in the Association Between Psychotic-like Experiences and Cannabis Use”⁠, Nicole R. Karcher, Deanna M. Barch, Catherine H. Demers, David A. A Baranger, Andrew C. Heath, Michael T. Lynskey et al (2019; ; backlinks; similar):

Importance: Previous research indicates that cannabis use is associated with psychotic-like experiences (PLEs). However, it is unclear whether this association results from predispositional (ie. shared genetic) factors or individual-specific factors (eg. causal processes, such as cannabis use leading to PLEs).

Objectives: To estimate genetic and environmental correlations between cannabis use and PLEs, and to examine PLEs in twin and nontwin sibling pairs discordant for exposure to cannabis use to disentangle predispositional from individual-specific effects.

Design, Setting, and Participants: In this cross-sectional analysis, diagnostic interviews and self-reported data were collected from 2 separate population-based samples of twin and nontwin sibling pairs. Data from the Human Connectome Project were collected between August 10, 2012, and September 29, 2015, and data from the Australian Twin Registry Cohort 3 (ATR3) were collected between August 1, 2005, and August 31, 2010. Data were analyzed between August 17, 2017, and July 6, 2018. The study included data from 1188 Human Connectome Project participants and 3486 ATR3 participants, totaling 4674 participants.

Main Outcomes and Measures: Three cannabis-involvement variables were examined: frequent use (ie. ≥100×), a DSM-IV lifetime cannabis use disorder diagnosis, and current cannabis use. Genetic and environmental correlations between cannabis involvement and PLEs were estimated. Generalized linear mixed models examined PLE differences in twin and nontwin sibling pairs discordant for cannabis use.

Results: Among the 4674 participants, the mean (SD) age was 30.5 (3.2) years, and 2923 (62.5%) were female. Data on race/​ethnicity were not included as a covariate owing to lack of variability within the ATR3 sample; among the 1188 participants in the Human Connectome Project, 875 (73.7%) were white. Psychotic-like experiences were associated with frequent cannabis use (β = 0.11; 95% CI, 0.08–0.14), cannabis use disorder (β = 0.13; 95% CI, 0.09–0.16), and current cannabis use (β = 0.07; 95% CI, 0.04–0.10) even after adjustment for covariates. Correlated genetic factors explained between 69.2% and 84.1% of this observed association. Within discordant pairs of twins/​siblings (N~pairs~, 308–324), Psychotic-like experiences were more common in cannabis-exposed individuals compared with their relative who used cannabis to a lesser degree (β ≥ .23, p < 0.05; eg, frequent and infrequent cannabis-using relatives significantly differed, z = -5.41; p < 0.001).

Conclusions and Relevance: Despite the strong contribution of shared genetic factors, frequent and problem cannabis use also appears to be associated with PLEs via person-specific pathways. This study’s findings suggest that policy discussions surrounding legalization should consider the influence of escalations in cannabis use on trait-like indices of vulnerability, such as PLEs, which could contribute to pervasive psychological and interpersonal burden.

“Drogues Sur Internet: Etat Des Lieuxsur La Situation En Suisse”, Rossy et al 2018

“Drogues sur Internet: Etat des lieuxsur la situation en Suisse”⁠, Quentin Rossy, Ludovic Staehli, Damien Rhumorbarbe, Pierre Esseiva, Frank Zobel, Christian Schneider et al (2018-11; ; backlinks; similar):

[Google Translate of French abstract] Where do you find drugs on the Internet, how are they sold, what is the size of the market and what is Switzerland’s place in it? To try to answer these questions, Addiction Switzerland and the School of Criminal Sciences at UNIL have collected and analyzed a set of relevant data on behalf of the Federal Office of Public Health.

The Internet is made up of three basic components: a transmission network (cables or waves), a system for recognizing interconnected devices (the IP protocol) and data transport protocols. Together, they allow the use of applications (web, e-mail, messaging) for communication and information sharing. It is possible to find and buy drugs on many applications including websites, whether concealed or not, but also social networks and messaging applications. You can come across different promotion strategies, different sales spaces but also evaluation of the drugs offered. Other products such as drugs, narcotics, and new psychoactive substances (NPS) are also on sale.

Knowledge about the sale of narcotics on the various applications present on the Internet is still in its infancy, with the exception of crypto-markets which are often specialized in this field. These are sales platforms that allow for some anonymity. The use of specific infrastructures (called darknets), web spaces that are not or not very regulated (dark webs), encrypted communications and cryptocurrencies like Bitcoin allow this anonymity. The dark webs, and the crypto-markets they host, however, are tiny compared to all the spaces on the web.

The sale of narcotic drugs on crypto-markets has been revealed by the Silk Road website. Since then, many similar sites have appeared but with often relatively short lifespans, due to internal fraud or the intervention of the police. The sites are based on management by administrators and on advertisements that describe the product, its price and the conditions of its acquisition. They also rely on the assessment of products and sellers by buyers. They are thus, in their form, similar to many sites known as eBay.

To understand Switzerland’s place in this market, downloads of data from one of the main crypto-narcotics markets (AlphaBay, active from the end of 2014 to July 2017) were carried out. They show that the most cited countries of origin are the Anglo-Saxon countries (United States, Canada, Australia, United Kingdom), the Netherlands and Germany. Switzerland occupies a less important place but, if we consider its size, its role is not negligible in terms of sales. Thus, 57 seller accounts declaring to be located in Switzerland carried out just over ten thousand transactions for a turnover of ~1.3 million francs on AlphaBay. The sale of stimulants concerns 85% of these transactions, especially with small quantities and prices close to those of the physical market. These sales represent in fact only a very small part of the narcotics market in Switzerland, but some sellers make substantial sales of up to almost $30,000 a month.

There is little data on people in Switzerland who order drugs online. Analysis of data from the Global Drug Survey suggests that shopping on the web and on dark webs remains limited, but with an increasing trend. Older data shows that cannabis and stimulants are the products most ordered by Swiss buyers. They order from sellers in Switzerland but also abroad, especially in Germany, the Netherlands, the United Kingdom and Belgium. Overseas orders are generally associated with larger quantities but remain relatively small. On average, apart from cannabis, purchases rarely exceed 5–10 grams on average.

A small survey of cantonal police has shown that surveys of online drug purchases have so far been relatively rare. They often result from information provided by an informant or from the discovery of a computer turned on during a search. The most frequent case concerns parcels intercepted by customs with small quantities ordered on the Internet, most often cannabis, stimulants or hallucinogens.

We will retain from this exploration of the data on the Internet drug markets, that these are found in different spaces of the web, in particular the dark webs, but that they seem so far to constitute only a very small part of the drug market for narcotic drugs, at least in Switzerland. There are, however, some indications that the phenomenon is tending to spread, even if it is happening at a slower pace than one might have thought. Like other innovations, the sale and purchase of psychoactive substances on the Internet probably follows an adoption phase in a small group of individuals before, perhaps, becoming a wider phenomenon.

“Forensic Drug Intelligence and the Rise of Cryptomarkets. Part II: Combination of Data from the Physical and Virtual Markets”, Morelato et al 2018

2018-morelato.pdf: “Forensic drug intelligence and the rise of cryptomarkets. Part II: Combination of data from the physical and virtual markets”⁠, Marie Morelato, Julian Broséus, Adrian De Grazia, Mark Tahtouh, Pierre Esseiva, Claude Roux (2018-07; ; backlinks):

  • Online data were compared to data related to traditional market descriptors.
  • The results highlighted a link between the virtual and physical markets.
  • Forensic drug intelligence processes rely on the combination of different information.

Technology provides new ways to access customers and suppliers while enhancing the security of off-line criminal activity. Since the first cryptomarket, Silk Road, in 2011, cryptomarkets have transformed the traditional drug sale by facilitating the creation of a global network of vendors and buyers. Due to the fragmented nature of traces that result from illegal activities, combining the results of concurrent processes based on traces of different nature should provide supplementary benefit to understand the drug market.

This article compares the data of the Australian virtual market (in particular data extracted from cryptomarkets) to the data related to traditional market descriptors, namely national seizures and arrests, prevalence data, shipping countries of seized post shipments as well as outcomes of specific surveys targeting users’ behaviour online. Results revealed the domestic nature of the online illicit drug trade in Australia which is dominated by amphetamine-type substances (ATS), in particular methylamphetamine and cannabis. These illicit drugs were also the most seized drugs on the physical market.

This article shows that the combination of different information offers a broader perspective of the illicit drug market in Australia and thus provides stronger arguments for policy makers. It also highlights the links between the virtual and physical markets.

[Keywords: darknet, illicit drug market, problem-oriented approach, National Forensic Rapid Laboratory (Australia)] [part I]

“Genetic Tools Weed out Misconceptions of Strain Reliability in Cannabis Sativa: Implications for a Budding Industry”, Schwabe & McGlaughlin 2018

“Genetic tools weed out misconceptions of strain reliability in Cannabis sativa: Implications for a budding industry”⁠, Anna L. Schwabe, Mitchell E. McGlaughlin (2018-05-28; similar):

Cannabis sativa is listed as a Schedule I substance by the United States Drug Enforcement Agency and has been federally illegal in the United States since 1937. However, the majority of states in the United States, as well as several countries, now have various levels of legal Cannabis. Products are labeled with identifying strain names but there is no official mechanism to register Cannabis strains, therefore the potential exists for incorrect identification or labeling. This study uses genetic analyses to investigate strain reliability from the consumer point of view. Ten microsatellite regions were used to examine samples from strains obtained from dispensaries in three states. Samples were examined for genetic similarity within strains, and also a possible genetic distinction between Sativa, Indica, or Hybrid types. The analyses revealed genetic inconsistencies within strains. Additionally, although there was strong statistical support dividing the samples into two genetic groups, the groups did not correspond to commonly reported Sativa/​Hybrid/​Indica types. Genetic differences have the potential to lead to phenotypic differences and unexpected effects, which could be surprising for the recreational user, but have more serious implications for patients relying on strains that alleviate specific medical symptoms.

“Genome-wide Study Identifies 611 Loci Associated With Risk Tolerance and Risky Behaviors”, Linnér et al 2018

“Genome-wide study identifies 611 loci associated with risk tolerance and risky behaviors”⁠, Richard Karlsson Linnér, Pietro Biroli, Edward Kong, S. Fleur W. Meddens, Robbee Wedow, Mark Alan Fontana et al (2018-02-08; ⁠, ⁠, ; similar):

Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 ~independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated (|̂rg| ~ 0.25–0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

“Genome-wide Association Analysis of Lifetime Cannabis Use (N=184,765) Identifies New Risk Loci, Genetic Overlap With Mental Health, and a Causal Influence of Schizophrenia on Cannabis Use”, Pasman et al 2018

“Genome-wide association analysis of lifetime cannabis use (N=184,765) identifies new risk loci, genetic overlap with mental health, and a causal influence of schizophrenia on cannabis use”⁠, Joëlle A. Pasman, Karin J. H. Verweij, Zachary Gerring, Sven Stringer, Sandra Sanchez-Roige, Jorien L. Treur et al (2018-01-08; ; similar):

Cannabis use is a heritable trait [1] that has been associated with adverse mental health outcomes. To identify risk variants and improve our knowledge of the genetic etiology of cannabis use, we performed the largest genome-wide association study (GWAS) meta-analysis for lifetime cannabis use (n = 184,765) to date. We identified 4 independent loci containing genome-wide statistically-significant SNP associations. Gene-based tests revealed 29 genome-wide statistically-significant genes located in these 4 loci and 8 additional regions. All SNPs combined explained 10% of the variance in lifetime cannabis use. The most statistically-significantly associated gene, CADM2, has previously been associated with substance use and risk-taking phenotypes [2–4]. We used S-PrediXcan to explore gene expression levels and found 11 unique eGenes. LD-score regression uncovered genetic correlations with smoking, alcohol use and mental health outcomes, including schizophrenia and bipolar disorder. Mendelian randomisation analysis provided evidence for a causal positive influence of schizophrenia risk on lifetime cannabis use.

“Exploring the Relationship between Polygenic Risk for Cannabis Use, Peer Cannabis Use and the Longitudinal Course of Cannabis Involvement”, Johnson et al 2018

2018-johnson.pdf: “Exploring the relationship between polygenic risk for cannabis use, peer cannabis use and the longitudinal course of cannabis involvement”⁠, Emma C. Johnson, Rebecca Tillman, Fazil Aliev, Jacquelyn L. Meyers, Jessica E. Salvatore, Andrey P. Anokhin et al (2018-01-01; )

“Genetic and Environmental Overlap Between Substance Use and Delinquency in Adolescence”, Boisvert et al 2018

2018-boisvert.pdf: “Genetic and Environmental Overlap Between Substance Use and Delinquency in Adolescence”⁠, Danielle L. Boisvert, Eric J. Connolly, Jamie C. Vaske, Todd A. Armstrong, Brian B. Boutwell (2018; ; similar):

During adolescence, many teens begin to experiment with substances and engage in delinquent behavior. The current study seeks to examine whether and to what extent genetic and environmental factors contribute to the association between substance use (ie. marijuana and alcohol) and different forms of delinquent offending (ie. violent and nonviolent) across males and females. Analyses were based on same-sex twins (n = 1,072) from the sibling subsample of the National Longitudinal Study of Adolescent to Adult Health (Add Health). The results revealed moderate to large genetic overlap between substance use and delinquent behavior for males. Much of the covariation between alcohol use and offending behavior for females was attributable to common environmental factors, while common genetic factors explained a large portion of the overlap between marijuana use and offending in males and females. The implications of these findings for sex differences in prevention and intervention efforts are discussed from a biosocial perspective.

“Instantly Hooked? Freebies and Samples of Opioids, Cannabis, MDMA, and Other Drugs in an Illicit E-Commerce Market”, Ladegaard 2018

2018-ladegaard.pdf: “Instantly Hooked? Freebies and Samples of Opioids, Cannabis, MDMA, and Other Drugs in an Illicit E-Commerce Market”⁠, Isak Ladegaard (2018; ⁠, ; backlinks):

Do drug dealers entice nonusers with free samples? Police, the popular press, and social media users say so, but crime researchers have found little support for this theory and argue instead that sample distribution is an unsound strategy for illegal market business. But what about in digital drug markets, where operational logics are based on sophisticated anonymization technology and reputation systems? The author collected data from a large e-commerce website for drugs over 305 days in 2014 and 2015 and documents that (a) drug dealers give away samples of all major substance categories and (b) sample distribution increases vendor sales for prescription drugs and opioid-based painkillers. To explore possible explanations of these findings, the author collected data from the market’s online forum and analyzed 175 discussions (2,218 posts) about samples. Among the findings is that samples are preferably given to reputable review writers, or “drug critics.”

“Six Years Later”, Décary-Hétu et al 2018

2018-decaryhetu.pdf: “Six Years Later”⁠, David Décary-Hétu, Vincent Mousseau, Sabrina Vidal (2018; ):

Cryptomarkets are online illicit marketplaces where drug dealers advertise the sale of illicit drugs. Anonymizing technologies such as the Tor network and virtual currencies are used to hide cryptomarket participants’ identity and to limit the ability of law enforcement agencies to make arrests. In this paper, our aim is to describe how herbal cannabis dealers and buyers in the United States have adapted to the online sale of herbal cannabis through cryptomarkets. To achieve this goal, we evaluate the size and scope of the American herbal cannabis market on cryptomarkets and compare it to other drug markets from other countries, evaluate the impact of cryptomarkets on offline sales of herbal cannabis, and evaluate the ties between the now licit herbal cannabis markets in some States and cryptomarkets. Our results suggest that only a small fraction of herbal cannabis dealers and drug users have transitioned to cryptomarkets. This can be explained by the need for technical skills to buy and sell herbal cannabis online and by the need to have access to computers that are not accessible to all. The slow rate of adoption may also be explained by the higher price of herbal cannabis relative to street prices. If cryptomarkets were to be adopted by a larger portion of the herbal cannabis market actors, our results suggest that wholesale and regional distributors who are not active on cryptomarkets would be the most affected market’s participants.

“Marijuana Intoxication in a Cat”, Janeczek et al 2018

“Marijuana intoxication in a cat”⁠, Agnieszka Janeczek, Marcin Zawadzki, Pawel Szpot, Artur Niedzwiedz (2018; ⁠, ; similar):

Background: Cannabis from hemp (Cannabis sativa and C. indica) is one of the most common illegal drugs used by drug abusers. Indian cannabis contains around 70 alkaloids, and delta-9-tetrahydrocannabinol (delta-9-THC) is the most psychoactive substance. Animal intoxications occur rarely and are mostly accidental. According to the US Animal Poison Control Center, cannabis intoxication mostly affects dogs (96%). The most common cause of such intoxication is unintentional ingestion of a cannabis product, but it may also occur after the exposure to marijuana smoke.

Case Presentation: A 6-year-old Persian cat was brought to the veterinary clinic due to strong psychomotor agitation turning into aggression. During hospitalisation for 14 days, the cat behaved normally and had no further attacks of unwanted behaviour. It was returned to its home but shortly after it developed neurological signs again and was re-hospitalized. On presentation, the patient showed no neurological abnormalities except for symmetric mydriasis and scleral congestion. During the examination, the behaviour of the cat changed dramatically. It developed alternate states of agitation and apathy, each lasting several minutes. On interview it turned out that the cat had been exposed to marijuana smoke. Blood toxicology tests by gas chromatography tandem mass spectrometry revealed the presence of delta-9-tetrahydrocannabinol (THC) at 5.5 ng/​mL, 11-hydroxy-delta-9-THC at 1.2 ng/​mL, and 11-carboxy-delta-9-THC at 13.8 ng/​mL. The cat was given an isotonic solution of NaCl 2.5 and 2.5% glucose at a dose of 40 mL/​kg/​day parenterally and was hospitalized. After complete recovery, the cat was returned to it’s owner and future isolation of the animal from marijuana smoke was advised.

Conclusions: This is the first case of a delta-9-tetrahydrocannabinol intoxication in a cat with both description of the clinical findings and the blood concentration of delta-9-THC and its main metabolites.

“Platform Criminalism: The 'Last-Mile' Geography of the Darknet Market Supply Chain”, Dittus et al 2017

“Platform Criminalism: The 'Last-Mile' Geography of the Darknet Market Supply Chain”⁠, Martin Dittus, Joss Wright, Mark Graham (2017-12-28; ; backlinks; similar):

Does recent growth of darknet markets signify a slow reorganisation of the illicit drug trade? Where are darknet markets situated in the global drug supply chain? In principle, these platforms allow producers to sell directly to end users, bypassing traditional trafficking routes. And yet, there is evidence that many offerings originate from a small number of highly active consumer countries, rather than from countries that are primarily known for drug production. In a large-scale empirical study, we determine the darknet trading geography of three plant-based drugs across four of the largest darknet markets, and compare it to the global footprint of production and consumption for these drugs. We present strong evidence that cannabis and cocaine vendors are primarily located in a small number of consumer countries, rather than producer countries, suggesting that darknet trading happens at the ‘last mile’, possibly leaving old trafficking routes intact. A model to explain trading volumes of opiates is inconclusive. We cannot find evidence for significant production-side offerings across any of the drug types or marketplaces. Our evidence further suggests that the geography of darknet market trades is primarily driven by existing consumer demand, rather than new demand fostered by individual markets.

“Forensic Drug Intelligence and the Rise of Cryptomarkets. Part I: Studying the Australian Virtual Market”, Broséus et al 2017b

2017-broseus-2.pdf: “Forensic drug intelligence and the rise of cryptomarkets. Part I: Studying the Australian virtual market”⁠, Julian Broséus, Marie Morelato, Mark Tahtouh, Claude Roux (2017-10-01; ⁠, ; backlinks):

  • Results revealed the domestic nature of the virtual Australian illicit drug trade.
  • The virtual Australian illicit drug trade is dominated by amphetamine-type substances (ATS).
  • The online price fixed by Australian sellers for the considered illicit drugs is higher than for any other shipping countries.
  • Understanding the link between virtual and physical drug market necessitates the integration of different perspective.

Analysing and understanding cryptomarkets is essential to become proactive in the fight against the illicit drug trade. Such research seeks to combine a diversity of indicators related to the virtual (darknet markets) and physical (the traditional “offline” market) aspects of the illicit drug trade to provide information on the distribution and consumption as well as to assess similarities/​differences between the virtual and physical markets.

This study analysed data that had previously been collected on cryptomarkets from December 2013 to March 2015. In this article, the data was extracted from 2 marketplaces, Evolution and Silk Road 2, and analysed to evaluate the illicit drug trade of the Australian virtual market (eg. information about the supply and demand, trafficking flows, prices of illicit drugs and market share) and highlight its specificities.

The results revealed the domestic nature of the virtual Australian illicit drug trade (ie. Australian sellers essentially ship their products to local customers). This may explain the coherence between supply and demand. Particularly, the virtual Australian illicit drug trade is dominated by amphetamine-type substances (ATS), mainly methamphetamine and 3,4-Methylenedioxymethamphetamine (MDMA), and cannabis. Australia, as a shipping country, accounts for half of the methamphetamine offered and purchased on Silk Road 2. Moreover, it was observed that the online price fixed by Australian sellers for the considered illicit drugs is higher than for any other shipping countries, which is in line with previous studies.

Understanding the virtual and physical drug market necessitates the integration and fusion of different perspectives to capture the dynamic nature of drug trafficking, monitor its evolution and finally improve our understanding of the phenomenon so policy makers can make informed decisions.

[Keywords: cryptomarkets, supply & demand, illicit drug market, Australian perspective, darknet] [part 2]

“Genetic and Environmental Contributions to the Association Between Cannabis Use and Psychotic-Like Experiences in Young Adult Twins”, Nesvåg et al 2017

“Genetic and Environmental Contributions to the Association Between Cannabis Use and Psychotic-Like Experiences in Young Adult Twins”⁠, Ragnar Nesvåg, Ted Reichborn-Kjennerud, Nathan A. Gillespie, Gun Peggy Knudsen, Jørgen G. Bramness, Kenneth S. Kendler et al (2017; ; backlinks; similar):

To investigate contributions of genetic and environmental risk factors and possible direction of causation for the relationship between symptoms of cannabis use disorders (CUD) and psychotic-like experiences (PLEs), a population-based sample of 2793 young adult twins (63.5% female, mean [range] age 28.2 [19–36] y) were assessed for symptoms of CUD and PLEs using the Composite International Diagnostic Interview. Latent risk of having symptoms of CUD or PLEs was modeled using Item Response Theory. Co-twin control analysis was performed to investigate effect of familiar confounding for the association between symptoms of CUD and PLEs. Biometric twin models were fitted to estimate the heritability, genetic and environmental correlations, and direction for the association. Lifetime use of cannabis was reported by 10.4% of the twins, and prevalence of PLEs ranged from 0.1% to 2.2%. The incidence rate ratio of PLEs due to symptoms of CUD was 6.3 (95% CI, 3.9, 10.2) in the total sample and 3.5 (95% CI, 1.5, 8.2) within twin pairs. Heritability estimates for symptoms of CUD were 88% in men and women, and for PLEs 77% in men and 43% in women. The genetic and environmental correlations between symptoms of CUD and PLEs were 0.55 and 0.52, respectively. The model allowing symptoms of CUD to cause PLEs had a better fit than models specifying opposite or reciprocal directions of causation. The association between symptoms of CUD and PLEs is explained by shared genetic and environmental factors and direct effects from CUD to risk for PLEs.

“Buying Drugs on a Darknet Market: A Better Deal? Studying the Online Illicit Drug Market through the Analysis of Digital, Physical and Chemical Data”, Rhumorbarbe et al 2016

2016-damien.pdf: “Buying drugs on a Darknet market: A better deal? Studying the online illicit drug market through the analysis of digital, physical and chemical data”⁠, Damien Rhumorbarbe, Ludovic Staehli, Julian Broséus, Quentin Rossy, Pierre Esseiva (2016-10-01; ⁠, ; backlinks):

  • The Evolution cryptomarket is described through the analysis of source code files.
  • Illicit drug orders on Evolution and chemical analyses are performed.
  • The study of packaging reveals concealment techniques used to avoid detection.
  • Products purity does not correspond with information provided on listings.
  • Chemical profiling reveals a relationship between purchases and police seizures.

Darknet markets, also known as cryptomarkets, are websites located on the Darknet and designed to allow the trafficking of illicit products, mainly drugs. This study aims at presenting the added value of combining digital, chemical and physical information to reconstruct sellers’ activities. In particular, this research focuses on Evolution, one of the most popular cryptomarkets active from January 2014 to March 2015.

Evolution source code files were analysed using Python scripts based on regular expressions to extract information about listings (ie. sales proposals) and sellers. The results revealed more than 48,000 listings and around 2700 vendors claiming to send illicit drug products from 70 countries. The most frequent categories of illicit drugs offered by vendors were cannabis-related products (around 25%) followed by ecstasy (MDA, MDMA) and stimulants (cocaine, speed). The cryptomarket was then especially studied from a Swiss point of view. Illicit drugs were purchased from 3 sellers located in Switzerland. The purchases were carried out to confront digital information (eg. the type of drug, the purity, the shipping country and the concealment methods mentioned on listings) with the physical analysis of the shipment packaging and the chemical analysis of the received product (purity, cutting agents, chemical profile based on minor and major alkaloids, chemical class). The results show that digital information, such as concealment methods and shipping country, seems accurate. But the illicit drugs purity is found to be different from the information indicated on their respective listings. Moreover, chemical profiling highlighted links between cocaine sold online and specimens seized in Western Switzerland.

This study highlights that (1) the forensic analysis of the received products allows the evaluation of the accuracy of digital data collected on the website, and (2) the information from digital and physical/​chemical traces are complementary to evaluate the practices of the online selling of illicit drugs on cryptomarkets.

[Keywords: cryptomarket, cocaine, drug profiling, Evolution market, concealment techniques, source codes]

“Results of an International Drug Testing Service for Cryptomarket Users”, Caudevilla 2016b

2016-caudevilla-2.pdf: “Results of an international drug testing service for cryptomarket users”⁠, Fernando Caudevilla (2016-09-01; ⁠, ⁠, ; backlinks):

Introduction: User surveys indicate that expectations of higher drug purity are a key reason for cryptomarket use. In 2014–2015, Spain’s NGO Energy Control conducted a 1-year pilot project to provide a testing service to cryptomarket drug users using the Transnational European Drug Information (TEDI) guidelines. In this paper, we present content and purity data from the trial.

Methods: 219 samples were analyzed by gas chromatography associated with mass spectrometry (GC⁠/​MS). Users were asked to report what substance they allegedly purchased.

Results: 40 different advertised substances were reported, although 77.6% were common recreational drugs (cocaine, MDMA, amphetamines, LSD, ketamine, cannabis). In 200 samples (91.3%), the main result of analysis matched the advertised substance. Where the advertised compound was detected, purity levels (m ± SD) were: cocaine 71.6 ± 19.4%; MDMA (crystal) 88.3 ± 1.4%; MDMA (pills) 133.3 ± 38.4 mg; Amphetamine (speed) 51.3 ± 33.9%; LSD 123.6 ± 40.5 μg; Cannabis resin THC: 16.5 ± 7.5% CBD: 3.4 ± 1.5%; Ketamine 71.3 ± 38.4%. 39.8% of cocaine samples contained the adulterant levamisole (11.6 ± 8%). No adulterants were found in MDMA and LSD samples.

Discussion: The largest collection of test results from drug samples delivered from cryptomarkets are reported in this study. Most substances contained the advertised ingredient and most samples were of high purity. The representativeness of these results is unknown.

[Keywords: cryptomarkets, drug markets, purity, adulterants, drug checking, drug trend monitoring]

[See also Arce 2020⁠.]

Table 1: Advertised substance and purities in samples from International Drug Testing Service (March 2014–March 2015).

“Declining Prevalence of Marijuana Use Disorders Among Adolescents in the United States, 2002 to 2013”, Grucza et al 2016

“Declining Prevalence of Marijuana Use Disorders Among Adolescents in the United States, 2002 to 2013”⁠, Richard A. Grucza, Arpana Agrawal, Melissa J. Krauss, Jahnavi Bongu, Andrew D. Plunk, Patricia A. Cavazos-Rehg et al (2016; similar):

Objective: Little is known about recent trends in marijuana use disorders among adolescents in the United States. We analyzed trends in the past-year prevalence of DSM-IV marijuana use disorders among adolescents, both overall and conditioned on past-year marijuana use. Potential explanatory factors for trends in prevalence were explored.

Method: We assembled data from the adolescent samples of the 2002 to 2013 administrations of the National Survey on Drug Use and Health (n = 216,852; aged 12–17 years). The main outcome measures were odds ratios describing the average annual change in prevalence and conditional prevalence of marijuana use disorders, estimated from models of marijuana use disorder as a function of year. Post hoc analyses incorporated measures of potentially explanatory risk and protective factors into the trend analyses.

Results: A decline in the past-year prevalence of marijuana use disorders was observed (odds ratio = 0.976 per year; 95% CI = 0.968, 0.984; p < 0.001). This was due to both a net decline in past-year prevalence of use and a decline in the conditional prevalence of marijuana use disorders. The trend in marijuana use disorders was accounted for by a decrease in the rate of conduct problems among adolescents (eg. fighting, stealing).

Conclusion: Past-year prevalence of marijuana use disorders among US adolescents declined by an estimated 24% over the 2002 to 2013 period. The decline may be related to trends toward lower rates of conduct problems. Identification of factors responsible for the reduction in conduct problems could inform interventions targeting both conduct problems and marijuana use disorders.

“The Genetic and Environmental Contributions to Internet Use and Associations With Psychopathology: A Twin Study”, Long et al 2016

“The Genetic and Environmental Contributions to Internet Use and Associations With Psychopathology: A Twin Study”⁠, Elizabeth C. Long, Brad Verhulst, Michael C. Neale, Penelope A. Lind, Ian B. Hickie, Nicholas G. Martin et al (2016; backlinks; similar):

Excessive internet use has been linked to psychopathology. Therefore, understanding the genetic and environmental risks underpinning internet use and their relation to psychopathology is important. This study aims to explore the genetic and environmental etiology of internet use measures and their associations with internalizing disorders and substance use disorders. The sample included 2,059 monozygotic (MZ) and dizygotic (DZ) young adult twins from the Brisbane Longitudinal Twin Study (BLTS). Younger participants reported more frequent internet use, while women were more likely to use the internet for interpersonal communication. Familial aggregation in ‘frequency of internet use’ was entirely explained by additive genetic factors accounting for 41% of the variance. Familial aggregation in ‘frequency of use after 11 pm’, ‘using the internet to contact peers’, and ‘using the internet primarily to access social networking sites’ was attributable to varying combinations of additive genetic and shared environmental factors. In terms of psychopathology, there were no statistically-significant associations between internet use measures and major depression (MD), but there were positive statistically-significant associations between ‘frequency of internet use’ and ‘frequency of use after 11 pm’ with social phobia (SP). ‘Using the internet to contact peers’ was positively associated with alcohol abuse, whereas ‘using the internet to contact peers’ and ‘using the internet primarily to access social networking sites’ were negatively associated with cannabis use disorders and nicotine symptoms. Individual differences in internet use can be attributable to varying degrees of genetic and environmental risks. Despite some statistically-significant associations of small effect, variation in internet use appears mostly unrelated to psychopathology.

“Genetic Predisposition to Schizophrenia Associated With Increased Use of Cannabis”, Power et al 2014

“Genetic predisposition to schizophrenia associated with increased use of cannabis”⁠, R A. Power, K. J H. Verweij, M. Zuhair, G. W Montgomery, A. K Henders, A. C Heath, P. A F. Madden, S. E Medland et al (2014; ; similar):

Cannabis is the most commonly used illicit drug worldwide. With debate surrounding the legalization and control of use, investigating its health risks has become a pressing area of research. One established association is that between cannabis use and schizophrenia, a debilitating psychiatric disorder affecting ~1% of the population over their lifetime. Although considerable evidence implicates cannabis use as a component cause of schizophrenia, it remains unclear whether this is entirely due to cannabis directly raising risk of psychosis, or whether the same genes that increases psychosis risk may also increase risk of cannabis use. In a sample of 2082 healthy individuals, we show an association between an individual’s burden of schizophrenia risk alleles and use of cannabis. This was significant both for comparing those who have ever versus never used cannabis (p = 2.6 × 10−4), and for quantity of use within users (p = 3.0 × 10−3). Although directly predicting only a small amount of the variance in cannabis use, these findings suggest that part of the association between schizophrenia and cannabis is due to a shared genetic aetiology. This form of gene-environment correlation is an important consideration when calculating the impact of environmental risk factors, including cannabis use.

“Polygenic Risk Scores for Smoking: Predictors for Alcohol and Cannabis Use?”, Vink et al 2014

“Polygenic risk scores for smoking: predictors for alcohol and cannabis use?”⁠, Jacqueline M. Vink, Jouke Jan Hottenga, Eco J. C de Geus, Gonneke Willemsen, Michael C. Neale, Helena Furberg et al (2014; backlinks; similar):

Background and Aims: A strong correlation exists between smoking and the use of alcohol and cannabis. This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors. Those scores reflect a combined effect of selected risk alleles for smoking.

Methods: Summary-level p-values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (n between 22,000 and 70,000 subjects). Using different p-value thresholds (0.1, 0.2 and 0.5) from the meta-analysis, sets of ‘risk alleles’ were defined and used to generate a polygenic risk score (weighted sum of the alleles) for each subject in an independent target sample from the Netherlands Twin Register (n = 1583). The association between polygenic smoking scores and alcohol/​cannabis use was investigated with regression analysis.

Results: The polygenic scores for ‘cigarettes per day’ were associated significantly with the number of glasses alcohol per week (p = 0.005, R2 = 0.4–0.5%) and cannabis initiation (p = 0.004, R2 = 0.6–0.9%). The polygenic scores for ‘age at onset of smoking’ were associated significantly with ‘age at regular drinking’ (p = 0.001, R2 = 1.1–1.5%), while the scores for ‘smoking initiation’ and ‘smoking cessation’ did not significantly predict alcohol or cannabis use.

Conclusions: Smoking, alcohol and cannabis use are influenced by aggregated genetic risk factors shared between these substances. The many common genetic variants each have a very small individual effect size.

“The Draft Genome and Transcriptome of Cannabis Sativa”, Bakel et al 2011

“The draft genome and transcriptome of Cannabis sativa”⁠, Harm van Bakel, Jake M. Stout, Atina G. Cote, Carling M. Tallon, Andrew G. Sharpe, Timothy R. Hughes et al (2011; similar):

Background: Cannabis sativa has been cultivated throughout human history as a source of fiber, oil and food, and for its medicinal and intoxicating properties. Selective breeding has produced cannabis plants for specific uses, including high-potency marijuana strains and hemp cultivars for fiber and seed production. The molecular biology underlying cannabinoid biosynthesis and other traits of interest is largely unexplored.

Results: We sequenced genomic DNA and RNA from the marijuana strain Purple Kush using short read approaches. We report a draft haploid genome sequence of 534 Mb and a transcriptome of 30,000 genes. Comparison of the transcriptome of Purple Kush with that of the hemp cultivar ‘Finola’ revealed that many genes encoding proteins involved in cannabinoid and precursor pathways are more highly expressed in Purple Kush than in ‘Finola’. The exclusive occurrence of Δ9-tetrahydrocannabinolic acid synthase in the Purple Kush transcriptome, and its replacement by cannabidiolic acid synthase in ‘Finola’, may explain why the psychoactive cannabinoid Δ9-tetrahydrocannabinol (THC) is produced in marijuana but not in hemp. Resequencing the hemp cultivars ‘Finola’ and ‘USO-31’ showed little difference in gene copy numbers of cannabinoid pathway enzymes. However, single nucleotide variant analysis uncovered a relatively high level of variation among four cannabis types, and supported a separation of marijuana and hemp.

Conclusions: The availability of the Cannabis sativa genome enables the study of a multifunctional plant that occupies an unique role in human culture. Its availability will aid the development of therapeutic marijuana strains with tailored cannabinoid profiles and provide a basis for the breeding of hemp with improved agronomic characteristics.

“Intelligence and Semen Quality Are Positively Correlated”, Arden et al 2008

“Intelligence and semen quality are positively correlated”⁠, Rosalind Arden, Linda S. Gottfredson, Geoffrey Miller, Arand Pierce (2008; backlinks; similar):

Human cognitive abilities intercorrelate to form a positive matrix, from which a large first factor, called ‘Spearman’s g’ or general intelligence, can be extracted. General intelligence itself is correlated with many important health outcomes including cardiovascular function and longevity. However, the important evolutionary question of whether intelligence is a fitness-related trait has not been tested directly, let alone answered. If the correlations among cognitive abilities are part of a larger matrix of positive associations among fitness-related traits, then intelligence ought to correlate with seemingly unrelated traits that affect fitness—such as semen quality. We found statistically-significant positive correlations between intelligence and 3 key indices of semen quality: log sperm concentration (r = 0.15, p = 0.002), log sperm count (r = 0.19, p < 0.001), and sperm motility (r = 0.14, p = 0.002) in a large sample of US Army Veterans. None was mediated by age, body mass index⁠, days of sexual abstinence, service in Vietnam, or use of alcohol, tobacco, marijuana, or hard drugs. These results suggest that a phenotype-wide fitness factor may contribute to the association between intelligence and health. Clarifying whether a fitness factor exists is important theoretically for understanding the genomic architecture of fitness-related traits, and practically for understanding patterns of human physical and psychological health.

“Testing Hypotheses about the Relationship between Cannabis Use and Psychosis”, Degenhardt et al 2003

2002-degenhardt.pdf: “Testing hypotheses about the relationship between cannabis use and psychosis”⁠, Louisa Degenhardt, Wayne Hall, Michael Lynskey (2003-01-01; ⁠, ; backlinks)

“Psychedelic-Induced Social Behavior in Mice: A Preliminary Report”, Siegel & Poole 1969

1969-siegel.pdf: “Psychedelic-Induced Social Behavior in Mice: A Preliminary Report”⁠, Ronald K. Siegel, Jean Poole (1969-12-01; ; similar):

When large populations of mice were treated with LSD (2mcg/​kg to 30mcg/​kg), bufotenine (5mg/​kg to 30mg/​kg), a cannabis sativa extract (50mg/​kg to 100mg/​kg), or tetrahydrocannabinol (2mg/​kg to 10mg/​kg), there was a dramatic change in social behavior. Such treatment produced a statistically-significant reduction in aggression, group aggregation, and temporary disruptions of social hierarchies. Hallucinogenic-treated mice placed in normal untreated colonies were hypersensitive to auditory and tactile stimulation and aggregated in small groups apart from the rest of the population. Treatment with saline or BOL-148 produced no statistically-significant changes in behavior.

…When strangers were introduced into the drugged colonies, they were relatively ignored by the inhabitants. This was true whether the strangers were introduced in a drugged or undrugged state. If the strangers were undrugged, however, they moved about the colony investigating mice and inducing squealing and flight behavior in the inhabitants. And, if the strangers were dominant mice to begin with, they would often establish dominance over the entire colony, exploiting the food supplies and territories of the inhabitants.

Vaping-associated pulmonary injury


Legal history of cannabis in the United States


Kush (Cannabis)


Intravenous marijuana syndrome


Effects of cannabis




Adolfo Constanzo