European epidemiological patterns of cannabis- and substance-related congenital cardiovascular anomalies: geospatiotemporal and causal inferential study

Abstract

As prenatal and community cannabis exposures have recently been linked with congenital heart disease (CHD), it was of interest to explore these associations in Europe in a causal framework and space-time context. Congenital anomaly data from Eurocat, drug-use data from the European Monitoring Centre for Drugs and Drug Addiction, and income from the World Bank. Countries with rising daily cannabis use had in general higher congenital anomaly rates over time than those without (time: status interaction: β-Est. = 0.0267, P = 0.0059). At inverse probability-weighted panel regression, cannabis terms were positive and significant for CHD, severe CHD, atrial septal defect, ventricular septal defect, atrioventricular septal defect, patent ductus arteriosus, tetralogy of Fallot, vascular disruptions, double outlet right ventricle, transposition of the great vessels, hypoplastic right heart, and mitral valve anomalies from 1.75 × 10−19, 4.20 × 10−11, <2.2 × 10−16, <2.2 × 10−16, 1.58 × 10−12, 4.30 × 10−9, 4.36 × 10−16, 3.50 × 10−8, 5.35 × 10−12, <2.2 × 10−16, 5.65 × 10−5 and 6.06 × 10−10. At spatial regression, terms including cannabis were positive and significant for this same list of anomalies from 0.0038, 1.05 × 10−10, 0.0215, 8.94 × 10−6, 1.23 × 10−5, 2.05 × 10−5, 1.07 × 10−6, 8.77 × 10−5, 9.11 × 10−6, 0.0001, 3.10 × 10−7 and 2.17 × 10−7. 92.6% and 75.2% of 149 E-value estimates and minimum E-values were in high zone >9; 100.0% and 98.7% >1.25. Data show many congenital cardiac anomalies exhibit strong bivariate relationships with metrics of cannabis exposure. Causal inferential modelling for the twelve anomalies selected demonstrated convincing evidence of robust relationships to cannabis which survived adjustment and fulfilled epidemiological criteria for causal relationships. Space-time regression was similarly confirmatory. Epigenomic pathways constitute viable potential mechanisms. Given exponential genotoxic dose-response effects, careful and astute control of cannabinoid penetration is indicated.

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

“…Interestingly a companion paper to this one has shown that the VACTERL syndrome (Vertebral, anorectal, cardiac, tracheo-esophageal fistulae/esophageal atresia, renal and limb anomalies) [ 83 ] was strongly and causally linked with European cannabinoid exposure [ 15 , 84 ]. Since renal anomalies are part of the VACTERL syndrome this finding also imputes renal abnormalities in the overall pattern of uronephrological congenital anomalies (UCA’s).…”

Perturbation of 3D nuclear architecture, epigenomic dysregulation and aging, and cannabinoid synaptopathy reconfigures conceptualization of cannabinoid pathophysiology: part 1–aging and epigenomics

“…UHRF1 is also a key regulator of cell growth. Growth inhibition explains some of the growth-inhibitory actions of cannabis, as described in studies involving babies' heads, brains, and hearts ( 191 , 195 , 196 , 201 , 203 , 205 , 207 , 319 – 321 ).…”

Clinical Epigenomic Explanation of the Epidemiology of Cannabinoid Genotoxicity Manifesting as Transgenerational Teratogenesis, Cancerogenesis and Aging Acceleration

“…There are various strengths and limitations to the present conceptualization. The strengths include the remarkable consistency across the many epidemiological studies, which clearly demonstrates the genotoxic harms of cannabis exposure in several different international jurisdictions, in relation to both the congenital anomalies [ 28 , 36 , 37 , 40 , 45 , 46 , 49 , 51 , 71 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 ] and cancer [ 22 , 23 , 24 , 25 , 26 , 30 , 41 , 232 ], and, indeed, now also in aging [ 53 , 54 ]. Similar results in many different studies are clearly mutually supportive and strengthen the overall quality of the body of evidence.…”

“…For the reader who is unfamiliar with this epidemiological literature, it should be pointed out that most of the modern epidemiological studies referred to are not just observational ecological studies of convenience which happen to show a particular association. Many of the best studies used a formal space–time analysis and the quantitative tools of causal inference to introduce a pseudo-randomized quasi-experimental paradigm from which it is entirely appropriate to invoke causal associations [ 28 , 36 , 37 , 40 , 45 , 51 , 71 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 ].…”