Geotemporospatial and causal inferential epidemiological overview and survey of USA cannabis, cannabidiol and cannabinoid genotoxicity expressed in cancer incidence 2003-2017: part 1 - continuous bivariate analysis

Abstract

Background: The genotoxic and cancerogenic impacts of population-wide cannabinoid exposure remains an open but highly salient question. The present report examines these issues from a continuous bivariate perspective with subsequent reports continuing categorical and detailed analyses.

Methods: Age-standardized state census incidence of 28 cancer types (including "All (non-skin) Cancer") was sourced using SEER*Stat software from Centres for Disease Control and National Cancer Institute across US states 2001-2017. It was joined with drug exposure data from the nationally representative National Survey of Drug Use and Health conducted annually by the Substance Abuse and Mental Health Services Administration 2003-2017, response rate 74.1%. Cannabinoid data was from Federal seizure data. Income and ethnicity data sourced from the US Census Bureau. Data was processed in R.

Results: Nineteen thousand eight hundred seventy-seven age-standardized cancer rates were returned. Based on these rates and state populations this equated to 51,623,922 cancer cases over an aggregated population 2003-2017 of 124,896,418,350. Regression lines were charted for cancer-substance exposures for cigarettes, alcohol use disorder (AUD), cannabis, THC, cannabidiol, cannabichromene, cannabinol and cannabigerol. In this substance series positive trends were found for 14, 9, 6, 9, 12, 6, 9 and 7 cancers; with largest minimum E-Values (mEV) of 1.76 × 10⁹, 4.67 × 10⁸, 2.74 × 10⁴, 4.72, 2.34 × 10¹⁸, 2.74 × 10¹⁷, 1.90 × 10⁷, 5.05 × 10⁹; and total sum of exponents of mEV of 34, 32, 13, 0, 103, 58, 25, 31 indicating that cannabidiol followed by cannabichromene are the most strongly implicated in environmental carcinogenesis. Breast cancer was associated with tobacco and all cannabinoids (from mEV = 3.53 × 10⁹); "All Cancer" (non-skin) linked with cannabidiol (mEV = 1.43 × 10¹¹); pediatric AML linked with cannabis (mEV = 19.61); testicular cancer linked with THC (mEV = 1.33). Cancers demonstrating elevated mEV in association with THC were: thyroid, liver, pancreas, AML, breast, oropharynx, CML, testis and kidney. Cancers demonstrating elevated mEV in relation to cannabidiol: prostate, bladder, ovary, all cancers, colorectum, Hodgkins, brain, Non-Hodgkins lymphoma, esophagus, breast and stomach.

Conclusion: Data suggest that cannabinoids including THC and cannabidiol are important community carcinogens exceeding the effects of tobacco or alcohol. Testicular, (prostatic) and ovarian tumours indicate mutagenic corruption of the germline in both sexes; pediatric tumourigenesis confirms transgenerational oncogenesis; quantitative criteria implying causality are fulfilled.

Keywords: Cannabidiol; Cannabigerol; Cannabinoid; Cannabis; Chromosomal toxicity; Congenital anomalies; Dose–response relationship; Epigenotoxicity; Genotoxicity; Mechanisms; Multigenerational genotoxicity; Oncogenesis; Sigmoidal dose–response; Supra-linear dose response; Transgenerational teratogenicity; Δ9-tetrahydrocannabinol.

Fig. 1

Time trends of A common, B intermediate frequency and C rarer cancers in USA 2003–2017

Fig. 2

Trends in various substance use rates at state level across USA 2003–2017

Fig. 3

State level cannabinoid exposure estimates across USA 2003 – 2017

Fig. 4

Incidence of 28 cancer types by tobacco exposure across USA

Fig. 5

Incidence of 28 cancer types by Alcohol Use Disorder incidence across USA

Fig. 6

Incidence of 28 cancer types by estimates of Styate level Δ9-Tetrahydrocannabinol exposure across USA

Fig. 7

Incidence of 28 cancer types by estimates of Styate level Cannabidiol exposure across USA

Fig. 8

Comparative Minimum E-values regression models tumour incidence against various substances

Fig. 9

Comparative Minimum E-values regression models tumour incidence against estimates of various cannabinoid exposures

Fig. 10

Comparative cumulative sum of the regression model minimum E-value exponents by substance