Abstract
E-cigarette or vaping use-associated lung injury (EVALI) was identified with the incidents of a multi-state outbreak of acute lung injuries associated with the use of electronic cigarettes (e-cigs) and attributed to vitamin E acetate in off-market cannabis-based e-liquids. Aside from EVALI, hypersecretion of mucus, irritated nasal passages, and watery, red eyes have been defined as complaints associated with vaping standard nicotine-based e-liquids. The chemical composition of e-liquids varies between manufacturers and robust oversight of ingredients is lacking. Manufacturers use chemicals deemed “generally recognized as safe” (GRAS) by the FDA, a designation for chemicals used in foodstuffs to be ingested. Most “GRAS” chemicals are associated with at least one Global Harmonization System (GHS) warning class, ranging from irritant to toxic. Untargeted chemical analysis is critical to evaluate e-liquid products to determine chemical composition; equally important is the quantitation of components to help elucidate the potential harms from exceeding recommended exposure limits. Untargeted screening of e-liquids was accomplished using gas chromatography-mass spectrometry (GC-MS) and Direct Analysis in Real Time-AccuTOF™ mass spectrometry (DART-ToF-MS) and has identified 350 chemical constituents from 241 products analyzed. Nicotine, caffeine, menthol, and vitamin E were confirmed and quantitated by GC-MS, ethanol was confirmed and quantitated by headspace-gas chromatography-dual flame ionization detection (HS-GC-FID), and olivetol and cannabinoids were confirmed and quantitated by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Maximum identified concentrations of nicotine, caffeine, menthol, vitamin E, ethanol, olivetol, Δ9-tetrahydrocannabinol, and cannabidiol were 56.4, 26.9, 4.28, 307.9, 217.2, 399.6, 497.7, and 332.6 mg/ml, respectively. Evaluation of untargeted analysis and quantitation of unlabeled chemical components of e-liquids is essential to improving etiology of acute lung injury and less severe impacts of vaping, both short-term and long-term. The historical documentation of unlabeled ingredients can provide some insight for a retrospective analysis of health consequences and inform policy discussions.
Highlights
The modern electronic cigarette evolved rapidly after its introduction in 2003 in the United States
A fifth class of e-cigarette devices that facilitate the consumption of drugs other than nicotine (DOTN) and drug formulations that include waxes, dabs, crystals, and plant materials emerged from the highly customizable third generation device (Poklis et al, 2017a; Harrell and Eissenberg, 2018)
This study identified cannabinoids (CBD, Δ9-THC, Δ8THC, CBG, cannabidiolic acid (CBDA), CBN, CBC, THCV, and Tetrahydrocannabinolic acid (THCA)), caffeine, dextromethorphan, kratom alkaloids, the blue lotus alkaloids apomorphine and nuciferine, gamma-Butyrolactone (GBL), a variety of synthetic cannabinoids (5F-ADB, MDMB-FUBINACA, FUBAMB, EMB-FUBINACA, MFUBINAC, MMB-FUBICA, 4FMDMB-BINACA, 5F-EDMB-PINACA) and the synthetic cathinone 4-fluoroisocathinone in products
Summary
The modern electronic cigarette evolved rapidly after its introduction in 2003 in the United States. Four device types are recognized by the Centers for Disease Control and Prevention (CDC). The first-generation device, the “cig-alike”, was low voltage and disposable and the second generation was re-fillable while the third generation enabled a user to select power, wicking material, and coil type. The fourth generation, called the “pod mod” allowed the user discreet vaping with small concealable devices and lack of associated aerosol cloud (Centers for Disease Control and Prevention, 2020a). Each type of e-cigarette allowed the consumer to make choices in line with their preferences. A fifth class of e-cigarette devices that facilitate the consumption of drugs other than nicotine (DOTN) and drug formulations that include waxes, dabs, crystals, and plant materials emerged from the highly customizable third generation device (Poklis et al, 2017a; Harrell and Eissenberg, 2018)
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