Geotemporospatial and causal inferential epidemiological overview and survey of USA cannabis, cannabidiol and cannabinoid genotoxicity expressed in cancer incidence 2003–2017: part 2 – categorical bivariate analysis and attributable fractions

2022

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The use of Δ8THC is increasing at present across the USA in association with widespread cannabis legalization and the common notion that it is “legal weed”. As genotoxic actions have been described for many cannabinoids, we studied the cancer epidemiology of Δ8THC. Data on 34 cancer types was from the Centers for Disease Control Atlanta Georgia, substance abuse data from the Substance Abuse and Mental Health Services Administration, ethnicity and income data from the U.S. Census Bureau, and cannabinoid concentration data from the Drug Enforcement Agency, were combined and processed in R. Eight cancers (corpus uteri, liver, gastric cardia, breast and post-menopausal breast, anorectum, pancreas, and thyroid) were related to Δ8THC exposure on bivariate testing, and 18 (additionally, stomach, Hodgkins, and Non-Hodgkins lymphomas, ovary, cervix uteri, gall bladder, oropharynx, bladder, lung, esophagus, colorectal cancer, and all cancers (excluding non-melanoma skin cancer)) demonstrated positive average marginal effects on fully adjusted inverse probability weighted interactive panel regression. Many minimum E-Values (mEVs) were infinite. p-values rose from 8.04 × 10−78. Marginal effect calculations revealed that 18 Δ8THC-related cancers are predicted to lead to a further 8.58 cases/100,000 compared to 7.93 for alcoholism and −8.48 for tobacco. Results indicate that between 8 and 20/34 cancer types were associated with Δ8THC exposure, with very high effect sizes (mEVs) and marginal effects after adjustment exceeding tobacco and alcohol, fulfilling the epidemiological criteria of causality and suggesting a cannabinoid class effect. The inclusion of pediatric leukemias and testicular cancer herein demonstrates heritable malignant teratogenesis.

Section: Recent Dna Methylation Studiessupporting

confidence: 92%

Section: Mechanisms Of Cannabinoid Carcinogenesismentioning

confidence: 99%

Epidemiology of Δ8THC-Related Carcinogenesis in USA: A Panel Regression and Causal Inferential Study

2022

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“…There are indications that in these areas large crops of cannabis are being cultivated and food chain contamination seems likely. Since epidemiological studies have confirmed that the exponentiation of cannabinoid genotoxicity seen in the laboratory is also reflected in patterns of congenital anomaly incidence [ 1 , 3 , 4 , 8 , 22 , 23 , 24 , 25 ] a relatively abrupt rise in community cannabinoid exposure would be expected to be associated with a relatively sudden and abrupt step-wise rise in congenital anomaly rates. This issue seems to not be well understood in the public health community.…”

Section: Introductionmentioning

confidence: 99%

Cannabis- and Substance-Related Epidemiological Patterns of Chromosomal Congenital Anomalies in Europe: Geospatiotemporal and Causal Inferential Study

2022

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Introduction: Laboratory data link cannabinoid exposure to chromosomal mis-segregation errors. Recent epidemiological reports confirm this link and raise concern that elevated chromosomal congenital anomaly rates (CCAR) may be occurring in Europe which is experiencing increased cannabis use, daily intensity of use and cannabinoid potency. Methods: CCAR data from Eurocat. Drug use data from the European Monitoring Centre for Drugs and Drug Addiction. Income from World Bank. Bivariate, multivariate, panel and geotemporospatial regressions analyzed. Inverse probability weighting of panel models and E-values used as major quantitative causal inferential methodologies. Results: In countries where daily cannabis use was rising the trend for CCA’s was upwards whereas in those where daily use was declining it was usually downwards (p = 0.0002). In inverse probability weighted panel models terms for cannabis metrics were significant for chromosomal disorders, trisomies 21 and 13 and Klinefelters syndrome from p < 2.2 × 10−16. In spatiotemporal models cannabis terms were positive and significant for chromosomal disorders, genetic disorders, trisomies 21, 18 and 13, Turners and Klinefelters syndromes from 4.28 × 10−6, 5.79 × 10−12, 1.26 × 10−11, 1.12 × 10−7, 7.52 × 10−9, 7.19 × 10−7 and 7.27 × 10−7. 83.7% of E-value estimates and 74.4% of minimum E-values (mEV) > 9 including four values each at infinity. Considering E-values: the sensitivity of the individual disorders was trisomy 13 > trisomy 21 > Klinefelters > chromosomal disorders > Turners > genetic syndromes > trisomy 18 with mEV’s 1.91 × 1025 to 59.31; and daily cannabis use was the most powerful covariate (median mEV = 1.91 × 1025). Conclusion: Data indicate that, consistent with reports from Hawaii, Canada, Colorado, Australia and USA, CCARs are causally and spatiotemporally related to metrics and intensity of cannabis exposure, directly impact 645 MB (21.5%) of the human genome and may implicate epigenomic-centrosomal mechanisms.

“…The concern is that this relatively abrupt launching of parts of the continent into higher cannabinoid exposure zones will continue to see an increasing number of severe genotoxic outcomes such as those described above for amelia. Particularly when this report is read in conjunction with other reports on cannabinoid teratogenicity [ 4 , 5 , 6 , 7 , 11 , 16 , 108 , 130 , 131 ], cannabinoid cancerogenicity [ 95 , 96 , 97 , 99 , 100 , 102 , 103 , 104 , 106 , 108 ], cannabinoid accelerated aging [ 102 , 132 , 133 ], heritable mutagenic and carcinogenic disease [ 98 , 99 , 100 , 108 , 134 , 135 , 136 ], and heritable neurotoxicity [ 107 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 ], it becomes clear that rational policies in this area would tightly restrict and control community exposure to genotoxic and neurotoxic cannabinoids for multiple public health indications as has always been the community’s response to known serious genotoxic xenobiotics. The prospect of continued contamination of the food chain and increasing population exposure, incurring avoidable genetic and epigenetic damage to the heritable material of the population for multiple generations to come, is most serious indeed.…”

Section: Discussionmentioning

confidence: 94%

“…As outlined in the introduction, the mechanisms of cannabis genotoxicity are many and complex and have been reviewed elsewhere [ 4 , 5 , 6 , 7 , 16 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 ]. For our present purposes, we wish to focus on two pathways of particular importance, these being the disruption of key morphogen gradients and the epigenomic perturbations.…”

Section: Discussionmentioning

confidence: 99%

European Epidemiological Patterns of Cannabis- and Substance-Related Body Wall Congenital Anomalies: Geospatiotemporal and Causal Inferential Study

2022

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As body wall congenital anomalies (BWCAs) have a long history of being associated with prenatal or community cannabis exposure (CCE), it was of interest to investigate these epidemiological relationships in Europe given the recent increases in cannabis use prevalence, daily intensity, and Δ9-tetrahydrocannabinol (THC) potency. Methods: This study makes use of BWCA data from Eurocat, drug exposure data from the European Monitoring Centre for Drugs and Drug Addiction, and income from the World Bank. Results: The mapping analysis showed that BWCARs increased in France, Spain, and the Netherlands. The bivariate mapping analysis showed that the BWCA rates (BWCAR) and the cannabis resin THC concentration rose simultaneously in France, the Netherlands, Bulgaria, Sweden, and Norway. The bivariate ranking of the BWCARs by median minimum E-value (mEV) was omphalocele > diaphragmatic hernia > abdominal wall defects > gastroschisis. With inverse probability weighted multivariable panel regression, the series of BWCAs, including gastroschisis, omphalocele, and diaphragmatic hernia, was positively related to various metrics of cannabis use from p = 2.45 × 10−14, 4.77 × 10−7 and <2.2 × 10−16. With geospatial regression, the same series of BWCAs was related to cannabis metrics from p = 0.0016, 5.28 × 10−6 and 4.88 × 10−9. Seventeen out of twenty-eight (60.7%) of the E-value estimates were >9 (high range), as were 14/28 (50.0%) of the mEVs. Conclusion: The data confirm the close relationship of the BWCARs with the metrics of CCE, fulfill the quantitative criteria of causal inference, and underscore the salience of the public health impacts of cannabinoid teratogenicity. Of major concern is the rising CCE impacting exponential cannabinoid genotoxic dose-response relationships. CCE should be carefully restricted to protect the food chain, the genome, and the epigenome of coming generations.