Molecular classification reveals the sensitivity of lung adenocarcinoma to radiotherapy and immunotherapy: multi-omics clustering based on similarity network fusion.

BACKGROUND: Due to individual differences in tumors and immune systems, the response rate to immunotherapy is low in lung adenocarcinoma (LUAD) patients. Combinations with other therapeutic strategies improve the efficacy of immunotherapy in LUAD patients. Although radioimmunotherapy has been demonstrated to effectively suppress tumors, the underlying mechanisms still need to be investigated. METHODS: Total RNA from LUAD cells was sequenced before and after radiotherapy to identify differentially expressed radiation-associated genes. The similarity network fusion (SNF) algorithm was applied for molecular classification based on radiation-related genes, immune-related genes, methylation data, and somatic mutation data. The changes in gene expression, prognosis, immune cell infiltration, radiosensitivity, chemosensitivity, and sensitivity to immunotherapy were assessed for each subtype. RESULTS: We used the SNF algorithm and multi-omics data to divide TCGA-LUAD patients into three subtypes. Patients with the CS3 subtype had the best prognosis, while those with the CS1 and CS2 subtypes had poorer prognoses. Among the strains tested, CS2 exhibited the most elevated immune cell infiltration and expression of immune checkpoint genes, while CS1 exhibited the least. Patients in the CS2 subgroup were more likely to respond to PD-1 immunotherapy. The CS2 patients were most sensitive to docetaxel and cisplatin, while the CS1 patients were most sensitive to paclitaxel. Experimental validation of signature genes in the CS2 subtype showed that inhibiting the expression of RHCG and TRPA1 could enhance the sensitivity of lung cancer cells to radiation. CONCLUSIONS: In summary, this study identified a risk classifier based on multi-omics data that can guide treatment selection for LUAD patients.

Vitamin E Acetate in Bronchoalveolar-Lavage Fluid Associated with EVALI.

BACKGROUND: The causative agents for the current national outbreak of electronic-cigarette, or vaping, product use-associated lung injury (EVALI) have not been established. Detection of toxicants in bronchoalveolar-lavage (BAL) fluid from patients with EVALI can provide direct information on exposure within the lung. METHODS: BAL fluids were collected from 51 patients with EVALI in 16 states and from 99 healthy participants who were part of an ongoing study of smoking involving nonsmokers, exclusive users of e-cigarettes or vaping products, and exclusive cigarette smokers that was initiated in 2015. Using the BAL fluid, we performed isotope dilution mass spectrometry to measure several priority toxicants: vitamin E acetate, plant oils, medium-chain triglyceride oil, coconut oil, petroleum distillates, and diluent terpenes. RESULTS: State and local health departments assigned EVALI case status as confirmed for 25 patients and as probable for 26 patients. Vitamin E acetate was identified in BAL fluid obtained from 48 of 51 case patients (94%) in 16 states but not in such fluid obtained from the healthy comparator group. No other priority toxicants were found in BAL fluid from the case patients or the comparator group, except for coconut oil and limonene, which were found in 1 patient each. Among the case patients for whom laboratory or epidemiologic data were available, 47 of 50 (94%) had detectable tetrahydrocannabinol (THC) or its metabolites in BAL fluid or had reported vaping THC products in the 90 days before the onset of illness. Nicotine or its metabolites were detected in 30 of 47 of the case patients (64%). CONCLUSIONS: Vitamin E acetate was associated with EVALI in a convenience sample of 51 patients in 16 states across the United States. (Funded by the National Cancer Institute and others.).

KIAA1199 drives immune suppression to promote colorectal cancer liver metastasis by modulating neutrophil infiltration.

BACKGROUND AND AIMS: Metastasis is the primary cause of cancer mortality, and colorectal cancer (CRC) frequently metastasizes to the liver. Our previous studies demonstrated the critical role of KIAA1199 in tumor invasion and metastasis in CRC. In the present study, we described an immune regulatory effect of KIAA1199 that creates a permissive environment for metastasis. APPROACH AND RESULTS: Flow cytometry was used to examine the effects of KIAA1199 on the infiltration of tumor immune cells. Neutrophils and T cells were isolated, stimulated, and/or cultured for in vitro function assays. In the patients with CRC, high expression levels of KIAA1199 were associated with an increased neutrophil infiltration into the liver. This result was further validated in mouse metastasis models. The increased influx of neutrophils contributed to the KIAA1199-driven CRC liver metastasis. Mechanistically, KIAA1199 activated the TGFß signaling pathway by interacting with the TGFBR1/2 to stimulate CXCL1 and CXCL3 production, thereby driving the aggregation of immunosuppressive neutrophils. Genetic blockade or pharmacologic inhibition of KIAA1199 restored tumor immune infiltration, impeded tumor progression, and potentiated response to immune checkpoint blockade (ICB). CONCLUSIONS: These findings indicated that KIAA1199 could facilitate the liver infiltration of immunosuppressive neutrophils via the TGFß-chemokine (C-X-C motif) ligand (CXCL)3/1-CXCR2 axis, which might be clinically targeted for the treatment of hepatic metastasis.

Distinguishing Exposure to Secondhand and Thirdhand Tobacco Smoke among U.S. Children Using Machine Learning: NHANES 2013-2016.

While the thirdhand smoke (THS) residue from tobacco smoke has been recognized as a distinct public health hazard, there are currently no gold standard biomarkers to differentiate THS from secondhand smoke (SHS) exposure. This study used machine learning algorithms to assess which combinations of biomarkers and reported tobacco smoke exposure measures best differentiate children into three groups: no/minimal tobacco smoke exposure (NEG); predominant THS exposure (TEG); and mixed SHS and THS exposure (MEG). Participants were 4485 nonsmoking 3-17-year-olds from the National Health and Nutrition Examination Survey 2013-2016. We fitted and tested random forest models, and the majority (76%) of children were classified in NEG, 16% were classified in TEG, and 8% were classified in MEG. The final classification model based on reported exposure, biomarker, and biomarker ratio variables had a prediction accuracy of 95%. This final model had prediction accuracies of 100% for NEG, 88% for TEG, followed by 71% for MEG. The most important predictors were the reported number of household smokers, serum cotinine, serum hydroxycotinine, and urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). In the absence of validated biomarkers specific to THS, comprehensive biomarker and questionnaire data for tobacco smoke exposure can distinguish children exposed to SHS and THS with high accuracy.

Manipulation of Menthol and Nicotine Content in Cigarettes: Effects on Smoking Behavior and Toxicant Exposure in Women Menthol Smokers.

BACKGROUND: The purpose of this study was to determine the effects of smoking and other outcomes of assigning cigarettes with reduced nicotine and/or no menthol to female menthol smokers. AIMS AND METHODS: Nontreatment-seeking female menthol smokers (N = 263) participated in a randomized controlled trial in which levels of menthol and nicotine in cigarettes were manipulated using experimental cigarettes. After a baseline period, participants were assigned to the following conditions for 6 weeks: (1) their own brand of cigarette (conventional nicotine with menthol), (2) a conventional nicotine cigarette with no menthol, (3) a cigarette with reduced nicotine (RNC) with menthol, or (4) a RNC cigarette and no menthol. Participants then returned to using their own brand and were followed for another 6 weeks. Outcomes included cigarettes smoked, biomarkers of exposure, and dependence measures. RESULTS: Results indicated that, after an initial increase, rates of smoking of all three experimental cigarettes were at or below baseline rates of smoking of one's own brand. Levels of biomarkers also decreased during the experimental phase but rebounded somewhat after participants resumed smoking their own brand. There was evidence that the overall amount of smoking decreased similarly among women who switched to non-menthol and/or RNC cigarettes. CONCLUSIONS: These results suggest that no detrimental effect will occur in nicotine or toxicant exposure levels with a ban on characterizing menthol and/or a product standard on nicotine content in cigarettes. IMPLICATIONS: The implication of this work is that there would be no risk to women menthol smokers associated with regulations restricting nicotine and eliminating menthol in cigarettes.

Variability in Urinary Nicotine Exposure Biomarker Levels Between Waves 1 (2013-2014) and 2 (2014-2015) in the Population Assessment of Tobacco and Health Study.

INTRODUCTION: To date, no studies have evaluated the consistency of biomarker levels in people who smoke over a long-time period in real-world conditions with a large number of subjects and included use behavior and measures of nicotine metabolism. We evaluated the variability of biomarkers of nicotine exposure over approximately a 1-year period in people who exclusively smoke cigarettes, including intensity and recency of use and brand switching to assess impact on understanding associations with product characteristics. AIMS AND METHODS: Multivariate regression analysis of longitudinal repeated measures of urinary biomarkers of nicotine exposure from 916 adults in the Population Assessment of Tobacco and Health (PATH) Study with demographic characteristics and use behavior variables. Intraclass correlation coefficients (ICCs) were calculated to examine individual variation of nicotine biomarkers and the uncertainty of repeat measures at two time points (Waves 1 and 2). RESULTS: Age, race, and urinary creatinine were significant covariates of urinary cotinine. When including use behavior, recency, and intensity of use were highly significant and variance decreased to a higher extent between than within subjects. The ICC for urinary cotinine decreased from 0.7530 with no use behavior variables in the model to 0.5763 when included. Similar results were found for total nicotine equivalents. CONCLUSIONS: Urinary nicotine biomarkers in the PATH Study showed good consistency between Waves 1 and 2. Use behavior measures such as time since last smoked a cigarette and number of cigarettes smoked in the past 30 days are important to include when assessing factors that may influence biomarker concentrations. IMPLICATIONS: The results of this study show that the consistency of the nicotine biomarkers cotinine and total nicotine equivalents in spot urine samples from Waves 1 to 2 of the PATH Study is high enough that these data are useful to evaluate the association of cigarette characteristics with biomarkers of exposure under real-world use conditions.

Validation of the Wave 1 and Wave 2 Population Assessment of Tobacco and Health (PATH) Study Indicators of Tobacco Dependence Using Biomarkers of Nicotine Exposure Across Tobacco Products.

INTRODUCTION: This study examined the predictive relationships between biomarkers of nicotine exposure and 16-item self-reported level of tobacco dependence (TD) and subsequent tobacco use outcomes. AIMS AND METHODS: The Population Assessment of Tobacco and Health (PATH) Study surveyed adult current established tobacco users who provided urine biospecimens at Wave 1 (September 2013-December 2014) and completed the Wave 2 (October 2014-October 2015) interview (n = 6872). Mutually exclusive user groups at Wave 1 included: Cigarette Only, E-cigarette Only, Cigar Only, Hookah Only, Smokeless Tobacco Only, Cigarette Plus E-cigarette, multiple tobacco product users who smoked cigarettes, and multiple tobacco product users who did not smoke cigarettes. Total Nicotine Equivalents (TNE-2) and TD were measured at Wave 1. Approximate one-year outcomes included frequency/quantity used, quitting, and adding/switching to different tobacco products. RESULTS: For Cigarette Only smokers and multiple tobacco product users who smoked cigarettes, higher TD and TNE-2 were associated with: a tendency to smoke more, smoking more frequently over time, decreased likelihood of switching away from cigarettes, and decreased probability of quitting after one year. For other product user groups, Wave 1 TD and/or TNE-2 were less consistently related to changes in quantity and frequency of product use, or for adding or switching products, but higher TNE-2 was more consistently predictive of decreased probability of quitting. CONCLUSIONS: Self-reported TD and nicotine exposure assess common and independent aspects of dependence in relation to tobacco use behaviors for cigarette smokers. For other product user groups, nicotine exposure is a more consistent predictor of quitting than self-reported TD. IMPLICATIONS: This study suggests that smoking cigarettes leads to the most coherent pattern of associations consistent with a syndrome of TD. Because cigarettes continue to be prevalent and harmful, efforts to decrease their use may be accelerated via conventional means (eg, smoking cessation interventions and treatments), but also perhaps by decreasing their dependence potential. The implications for noncombustible tobacco products are less clear as the stability of tobacco use patterns that include products such as e-cigarettes continue to evolve. TD, nicotine exposure measures, and consumption could be used in studies that attempt to understand and predict product-specific tobacco use behavioral outcomes.

Urinary Nicotine Metabolites and Self-Reported Tobacco Use Among Adults in the Population Assessment of Tobacco and Health (PATH) Study, 2013-2014.

INTRODUCTION: The Population Assessment of Tobacco and Health (PATH) Study is a longitudinal cohort study on tobacco use behavior, attitudes and beliefs, and tobacco-related health outcomes, including biomarkers of tobacco exposure in the U.S. population. In this report we provide a summary of urinary nicotine metabolite measurements among adult users and non-users of tobacco from Wave 1 (2013-2014) of the PATH Study. METHODS: Total nicotine and its metabolites including cotinine, trans-3'-hydroxycotinine (HCTT), and other minor metabolites were measured in more than 11 500 adult participants by liquid chromatography tandem mass spectrometry methods. Weighted geometric means (GM) and least square means from statistical modeling were calculated for non-users and users of various tobacco products. RESULTS: Among daily users, the highest GM concentrations of nicotine, cotinine and HCTT were found in exclusive smokeless tobacco users, and the lowest in exclusive e-cigarette users. Exclusive combustible product users had intermediate concentrations, similar to those found in users of multiple products (polyusers). Concentrations increased with age within the categories of tobacco users, and differences associated with gender, race/ethnicity and educational attainment were also noted among user categories. Recent (past 12 months) former users had GM cotinine concentrations that were more than threefold greater than never users. CONCLUSIONS: These urinary nicotine metabolite data provide quantification of nicotine exposure representative of the entire US adult population during 2013-2014 and may serve as a reference for similar analyses in future measurements within this study. IMPLICATIONS: Nicotine and its metabolites in urine provide perhaps the most fundamental biomarkers of recent nicotine exposure. This report, based on Wave 1 of the Population Assessment of Tobacco and Health (PATH) Study, provides the first nationally representative data describing urinary nicotine biomarker concentrations in both non-users, and users of a variety of tobacco products including combustible, e-cigarette and smokeless products. These data provide a urinary biomarker concentration snapshot in time for the entire US population during 2013-2014, and will provide a basis for comparison with future results from continuing, periodic evaluations in the PATH Study.

Serum Concentrations of Cotinine and Trans-3'-Hydroxycotinine in US Adults: Results From Wave 1 (2013-2014) of the Population Assessment of Tobacco and Health Study.

INTRODUCTION: The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative cohort of tobacco product users and nonusers. The study's main purpose is to obtain longitudinal epidemiologic data on tobacco use and exposure among the US population. AIMS AND METHODS: Nicotine biomarkers-cotinine (COT) and trans-3'-hydroxycotinine (HCT)-were measured in blood samples collected from adult daily tobacco users and nonusers during Wave 1 of the PATH Study (2013-2014; n = 5012; one sample per participant). Participants' tobacco product use and exposure to secondhand smoke were categorized based on questionnaire responses. Nonusers were subdivided into never users and recent former users. Daily tobacco users were classified into seven tobacco product use categories: exclusive users of cigarette, smokeless tobacco, electronic cigarette, cigar, pipe, and hookah, as well as polyusers. We calculated sample-weighted geometric mean (GM) concentrations of cotinine, HCT, and the nicotine metabolite ratio (NMR) and evaluated their associations with tobacco use with adjustment for potential confounders. RESULTS: The GMs (95% confidence intervals) of COT and HCT concentrations for daily tobacco users were 196 (184 to 208) and 72.5 (67.8 to 77.4) ng/mL, and for nonusers they were 0.033 (0.028 to 0.037) and 0.021 (0.018 to 0.023) ng/mL. Exclusive smokeless tobacco users had the highest COT concentrations of all user groups examined. The GM NMR in daily users was 0.339 (95% confidence interval: 0.330 to 0.350). CONCLUSIONS: These nationally representative estimates of serum nicotine biomarkers could be the basis for reference ranges characterizing nicotine exposure for daily tobacco users and nonusers in the US adult population. IMPLICATIONS: This report summarizes the serum nicotine biomarker measurements in Wave 1 of the PATH Study. We are reporting the first estimates of HCT in serum for daily tobacco users and nonusers in the noninstitutionalized, civilian US adult population; the first nationally representative serum COT estimates for daily exclusive users of different tobacco products and daily polyusers; and the first nationally representative estimate of the serum NMR in daily tobacco users by age, race/ethnicity, and sex.

Secondhand marijuana exposure in a convenience sample of young children in New York City.

BACKGROUND: Biomarkers of exposure to marijuana smoke can be detected in the urine of children with exposure to secondhand marijuana smoke, but the prevalence is unclear. METHODS: We studied children between the ages of 0 to 3 years who were coming in for well-child visits or hospitalized on the inpatient general pediatric unit between 2017 and 2018 at Kravis Children's Hospital at Mount Sinai. Parents completed an anonymous survey, and urine samples were analyzed for cotinine and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (COOH-THC), a metabolite of Δ9-tetrahydrocannabinol. RESULTS: Fifty-three children had urine samples available for analysis. COOH-THC was detectable in 20.8% of the samples analyzed and urinary cotinine was detectable in 90.2%. High levels of tobacco exposure (defined as cotinine ≥2.0 ng/ml) were significantly associated with COOH-THC detection (p < 0.01). We found that 34.8% of children who lived in attached housing where smoking was allowed within the property had detectable COOH-THC compared to 13.0% of children who lived in housing where smoking was not allowed at all. CONCLUSIONS: This study adds to the growing evidence that children are being exposed to marijuana smoke, even in places where recreational marijuana use is illegal. It is critical that more research be done on the impact of marijuana smoke exposure on children's health and development. IMPACT: We found that 20.8% of the 53 children recruited from Mount Sinai Hospital had detectable marijuana metabolites in their urine. Children with household tobacco smoke exposure and children who lived in attached housing where smoking was allowed on the premises were more likely to have detectable marijuana smoke metabolites. This study adds to the growing evidence that children are being exposed to marijuana smoke, even in places where marijuana remains illegal by state law. As states consider marijuana legalization, it is critical that the potential adverse health effects from marijuana exposure in children be taken into account.

Exposure to Nicotine and Toxicants Among Dual Users of Tobacco Cigarettes and E-Cigarettes: Population Assessment of Tobacco and Health (PATH) Study, 2013-2014.

INTRODUCTION: Concurrent use of tobacco cigarettes and e-cigarettes ("dual use") is common among tobacco users. Little is known about differences in demographics and toxicant exposure among subsets of dual users. AIMS AND METHODS: We analyzed data from adult dual users (current every/some day users of tobacco cigarettes and e-cigarettes, n = 792) included in the PATH Study Wave 1 (2013-2014) and provided urine samples. Samples were analyzed for biomarkers of exposure to nicotine and selected toxicants (tobacco-specific nitrosamine NNK [NNAL], lead, cadmium, naphthalene [2-naphthol], pyrene [1-hydroxypyrene], acrylonitrile [CYMA], acrolein [CEMA], and acrylamide [AAMA]). Subsets of dual users were compared on demographic, behavioral, and biomarker measures to exclusive cigarette smokers (n = 2411) and exclusive e-cigarette users (n = 247). RESULTS: Most dual users were predominant cigarette smokers (70%), followed by daily dual users (13%), non-daily concurrent dual users (10%), and predominant vapers (7%). Dual users who smoked daily showed significantly higher biomarker concentrations compared with those who did not smoke daily. Patterns of e-cigarette use had little effect on toxicant exposure. Dual users with high toxicant exposure were generally older, female, and smoked more cigarettes per day. Dual users who had low levels of biomarkers of exposure were generally younger, male, and smoked non-daily. CONCLUSIONS: In 2013-2014, most dual users smoked cigarettes daily and used e-cigarettes occasionally. Cigarette smoking appears to be the primary driver of toxicant exposure among dual users, with little-to-no effect of e-cigarette use on biomarker levels. Results reinforce the need for dual users to stop smoking tobacco cigarettes to reduce toxicant exposure. IMPLICATIONS: With considerable dual use of tobacco cigarettes and e-cigarettes in the United States, it is important to understand differences in toxicant exposure among subsets of dual users, and how these differences align with user demographics. Findings suggest most dual users smoke daily and use e-cigarettes intermittently. Low exposure to toxicants was most common among younger users, males, and intermittent smokers; high exposure to toxicants was most common among older users, females, and heavier cigarette smokers. Results underscore the heterogeneity occurring within dual users, and the need to quit smoking cigarettes completely in order to reduce toxicant exposure.

Tobacco-Specific Nitrosamines (NNAL, NNN, NAT, and NAB) Exposures in the US Population Assessment of Tobacco and Health (PATH) Study Wave 1 (2013-2014).

INTRODUCTION: The tobacco-specific nitrosamines (TSNAs) are an important group of carcinogens found in tobacco and tobacco smoke. To describe and characterize the levels of TSNAs in the Population Assessment of Tobacco and Health (PATH) Study Wave 1 (2013-2014), we present four biomarkers of TSNA exposure: N'-nitrosonornicotine, N'-nitrosoanabasine, N'-nitrosoanatabine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) which is the primary urinary metabolite of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone. METHODS: We measured total TSNAs in 11 522 adults who provided urine using automated solid-phase extraction coupled to isotope dilution liquid chromatography-tandem mass spectrometry. After exclusions in this current analysis, we selected 11 004 NNAL results, 10 753 N'-nitrosonornicotine results, 10 919 N'-nitrosoanatabine results, and 10 996 N'-nitrosoanabasine results for data analysis. Geometric means and correlations were calculated using SAS and SUDAAN. RESULTS: TSNA concentrations were associated with choice of tobacco product and frequency of use. Among established, every day, exclusive tobacco product users, the geometric mean urinary NNAL concentration was highest for smokeless tobacco users (993.3; 95% confidence interval [CI: 839.2, 1147.3] ng/g creatinine), followed by all types of combustible tobacco product users (285.4; 95% CI: [267.9, 303.0] ng/g creatinine), poly tobacco users (278.6; 95% CI: [254.9, 302.2] ng/g creatinine), and e-cigarette product users (6.3; 95% CI: [4.7, 7.9] ng/g creatinine). TSNA concentrations were higher in every day users than in intermittent users for all the tobacco product groups. Among single product users, exposure to TSNAs differed by sex, age, race/ethnicity, and education. Urinary TSNAs and nicotine metabolite biomarkers were also highly correlated. CONCLUSIONS: We have provided PATH Study estimates of TSNA exposure among US adult users of a variety of tobacco products. These data can inform future tobacco product and human exposure evaluations and related regulatory activities.

Long noncoding RNA TCL6 binds to miR-106a-5p to regulate hepatocellular carcinoma cells through PI3K/AKT signaling pathway.

Long noncoding RNAs (lncRNAs) have been reported to dysregulate and involve in the pathology of hepatocellular carcinoma (HCC). Nonetheless, the functional role of lncRNA T cell leukemia/lymphoma 6 (TCL6) and its underlying mechanism in HCC remain unclear. Herein, we analyzed the expression of TCL6 and elucidated its mechanistic involvement in HCC. Bioinformatics analyses indicated TCL6 was evidently downregulated in HCC tissues compared with normal controls. TCL6 was downregulated while microRNA-106a-5p (miR-106a-5p) was upregulated in HCC cell lines. Moreover, knockdown or overexpression of TCL6 significantly raised or diminished the expression level of miR-106a-5p in HCC cells, similar to the effect of miR-106a-5p on TCL6 expression. Functionally, TCL6 inhibited the proliferative, migratory, and invasive potentials of HCC cells as analyzed by cell counting kit-8, scratch wound healing, and transwell assays, respectively. Conversely, miR-106a-5p exerted an opposite effect on the proliferative, migratory, and invasive potentials of HCC. RNA immune precipitation and luciferase reporter assays revealed TCL6 directly bound to miR-106a-5p and luciferase reporter assay verified phosphatase and tensin homolog (PTEN) was a target gene of miR-106a-5p. Mechanistically, TCL6 knockdown evidently reduced PTEN expression at both messenger RNA and protein levels, and miR-106a-5p inhibitor partially rescued this reduction effect in HCC cells. Additionally, western blot assays demonstrated miR-106a-5p downregulation or TCL6 overexpression promoted the protein level of PTEN, and suppressed the phosphorylation level of AKT, the protein level of phosphatidylinositol 3-kinase (PI3K). Collectively, these results revealed TCL6 as a tumor-suppressive lncRNA regulates PI3K/AKT signaling pathway via directly binding to miR-106a-5p in HCC. This mechanism provides a theoretical basis for HCC pathogenesis and a potential therapeutic strategy for HCC treatment.

Evaluation of Bronchoalveolar Lavage Fluid from Patients in an Outbreak of E-cigarette, or Vaping, Product Use-Associated Lung Injury - 10 States, August-October 2019.

CDC, the Food and Drug Administration (FDA), state and local health departments, and multiple public health and clinical partners are investigating a national outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). Based on data collected as of October 15, 2019, 86% of 867 EVALI patients reported using tetrahydrocannabinol (THC)-containing products in the 3 months preceding symptom onset (1). Analyses of THC-containing product samples by FDA and state public health laboratories have identified potentially harmful constituents in these products, such as vitamin E acetate, medium chain triglyceride oil (MCT oil), and other lipids (2,3) (personal communication, D.T. Heitkemper, FDA Forensic Chemistry Center, November 2019). Vitamin E acetate, in particular, might be used as an additive in the production of e-cigarette, or vaping, products; it also can be used as a thickening agent in THC products (4). Inhalation of vitamin E acetate might impair lung function (5-7).

Exposure to Secondhand Smoke Among Nonsmokers - United States, 1988-2014.

Exposure to secondhand smoke from burning tobacco products can cause sudden infant death syndrome, respiratory infections, ear infections, and asthma attacks in infants and children, and coronary heart disease, stroke, and lung cancer in adult nonsmokers (1). There is no risk-free level of secondhand smoke exposure (2). CDC analyzed questionnaire and laboratory data from the National Health and Nutrition Examination Survey (NHANES) to assess patterns of secondhand smoke exposure among U.S. nonsmokers. The prevalence of secondhand smoke exposure among U.S. nonsmokers declined substantially during 1988-2014, from 87.5% to 25.2%. However, no change in exposure occurred between 2011-2012 and 2013-2014, and an estimated one in four nonsmokers, or approximately 58 million persons, were still exposed to secondhand smoke during 2013-2014. Moreover, marked disparities persisted across population groups. Exposure prevalence was highest among nonsmokers aged 3-11 years (37.9%), non-Hispanic blacks (50.3%), and those who were living in poverty (47.9%), in rental housing (38.6%), or with someone who smoked inside the home (73.0%), or among persons who had less than a high school education (30.7%). Comprehensive smoke-free laws and policies for workplaces and public places and smoke-free rules for homes and vehicles can further reduce secondhand smoke exposure among all nonsmokers.

Nicotine, Carcinogen, and Toxin Exposure in Long-Term E-Cigarette and Nicotine Replacement Therapy Users: A Cross-sectional Study.

BACKGROUND: Given the rapid increase in the popularity of e-cigarettes and the paucity of associated longitudinal health-related data, the need to assess the potential risks of long-term use is essential. OBJECTIVE: To compare exposure to nicotine, tobacco-related carcinogens, and toxins among smokers of combustible cigarettes only, former smokers with long-term e-cigarette use only, former smokers with long-term nicotine replacement therapy (NRT) use only, long-term dual users of both combustible cigarettes and e-cigarettes, and long-term users of both combustible cigarettes and NRT. DESIGN: Cross-sectional study. SETTING: United Kingdom. PARTICIPANTS: The following 5 groups were purposively recruited: combustible cigarette-only users, former smokers with long-term (≥6 months) e-cigarette-only or NRT-only use, and long-term dual combustible cigarette-e-cigarette or combustible cigarette-NRT users (n = 36 to 37 per group; total n = 181). MEASUREMENTS: Sociodemographic and smoking characteristics were assessed. Participants provided urine and saliva samples and were analyzed for biomarkers of nicotine, tobacco-specific N-nitrosamines (TSNAs), and volatile organic compounds (VOCs). RESULTS: After confounders were controlled for, no clear between-group differences in salivary or urinary biomarkers of nicotine intake were found. The e-cigarette-only and NRT-only users had significantly lower metabolite levels for TSNAs (including the carcinogenic metabolite 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol [NNAL]) and VOCs (including metabolites of the toxins acrolein; acrylamide; acrylonitrile; 1,3-butadiene; and ethylene oxide) than combustible cigarette-only, dual combustible cigarette-e-cigarette, or dual combustible cigarette-NRT users. The e-cigarette-only users had significantly lower NNAL levels than all other groups. Combustible cigarette-only, dual combustible cigarette-NRT, and dual combustible cigarette-e-cigarette users had largely similar levels of TSNA and VOC metabolites. LIMITATION: Cross-sectional design with self-selected sample. CONCLUSION: Former smokers with long-term e-cigarette-only or NRT-only use may obtain roughly similar levels of nicotine compared with smokers of combustible cigarettes only, but results varied. Long-term NRT-only and e-cigarette-only use, but not dual use of NRTs or e-cigarettes with combustible cigarettes, is associated with substantially reduced levels of measured carcinogens and toxins relative to smoking only combustible cigarettes. PRIMARY FUNDING SOURCE: Cancer Research UK.

Biomarkers of exposure to new and emerging tobacco delivery products.

Accurate and reliable measurements of exposure to tobacco products are essential for identifying and confirming patterns of tobacco product use and for assessing their potential biological effects in both human populations and experimental systems. Due to the introduction of new tobacco-derived products and the development of novel ways to modify and use conventional tobacco products, precise and specific assessments of exposure to tobacco are now more important than ever. Biomarkers that were developed and validated to measure exposure to cigarettes are being evaluated to assess their use for measuring exposure to these new products. Here, we review current methods for measuring exposure to new and emerging tobacco products, such as electronic cigarettes, little cigars, water pipes, and cigarillos. Rigorously validated biomarkers specific to these new products have not yet been identified. Here, we discuss the strengths and limitations of current approaches, including whether they provide reliable exposure estimates for new and emerging products. We provide specific guidance for choosing practical and economical biomarkers for different study designs and experimental conditions. Our goal is to help both new and experienced investigators measure exposure to tobacco products accurately and avoid common experimental errors. With the identification of the capacity gaps in biomarker research on new and emerging tobacco products, we hope to provide researchers, policymakers, and funding agencies with a clear action plan for conducting and promoting research on the patterns of use and health effects of these products.

Detecting biomarkers of secondhand marijuana smoke in young children.

BACKGROUND: The impact of secondhand marijuana smoke exposure on children is unknown. New methods allow detection of secondhand marijuana smoke in children. METHODS: We studied children ages 1 mo to 2 y hospitalized with bronchiolitis in Colorado from 2013 to 2015. Parents completed a survey, and urine samples were analyzed for cotinine using LC/MS/MS (limits of detection 0.03 ng/ml) and marijuana metabolites including COOH-THC (limits of detection 0.015 ng/ml). RESULTS: A total of 43 subjects had urine samples available for analysis. Most (77%) of the subjects were male, and 52% were less than 1 y of age. COOH-THC was detectable in 16% of the samples analyzed (THC+); the range in COOH-THC concentration was 0.03-1.5 ng/ml. Two subjects had levels >1 ng/ml. Exposure did not differ by gender or age. Non-white children had more exposure than white children (44 vs. 9%; P < 0.05). 56% of children with cotinine >2.0 ng/ml were THC+, compared with 7% of those with lower cotinine (P < 0.01). CONCLUSION: Metabolites of marijuana smoke can be detected in children; in this cohort, 16% were exposed. Detectable COOH-THC is more common in children with tobacco smoke exposure. More research is needed to assess the health impacts of marijuana smoke exposure on children and inform public health policy.

High-throughput and sensitive analysis of urinary heterocyclic aromatic amines using isotope-dilution liquid chromatography-tandem mass spectrometry and robotic sample preparation system.

Heterocyclic aromatic amines (HCAA) are listed by the US Food and Drug Administration (FDA) as harmful or potentially harmful constituents of tobacco smoke. However, quantifying HCAA exposure is challenging. In this study, we developed a sensitive, precise, and accurate isotope dilution, liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify urinary HCAAs in smokers and nonsmokers. The high-throughput robotic sample preparation system could handle a throughput of over 300 samples per day, while maintaining intra-day and inter-day imprecision and bias ≤10 %. The limits of detection of carcinogenic HCAAs ranged from 0.31 to 0.83 pg/mL. The validated method was applied to measure HCAAs in urine collected from smokers and non-smokers. This sensitive and efficient analytical method is ideal to support large-scale biomonitoring studies of HCAA exposure. Graphical Abstract LC/MS/MS and robotic sample preparation system for urinary HCAA analysis.

Analysis of Cannabinoids and Their Metabolites in Human Urine.

Biologically monitoring marijuana exposure from active and passive use requires both a wide linear range and sensitive detection. We have developed and validated a multifunctional method using ultrahigh performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) for analysis of urinary Δ9-tetrahydrocannabinol (THC), cannabidiol and cannabinol, and two major metabolites of THC, 11-nor-9-carboxy-THC and 11-hydroxy-THC, in active users and particularly in people exposed to secondhand marijuana smoke (SHMS). The method used positive electrospray ionization (ESI) mode to reach the sensitivity needed to detect trace SHMS exposure with limits of detection (LOD) ranging from 0.002 to 0.008 nanograms per milliliter (ng/mL) and 0.005 to 0.017 ng/mL for "free" (unconjugated forms) and "total" (unconjugated plus conjugated forms) measurements, respectively. These LODs were approximately 10-100 times more sensitive than those reported in the literature. To reduce or avoid time-consuming repetitive sample preparation and analysis, the method simultaneously monitored multiple reaction monitoring transitions in negative ESI mode to quantify high analyte levels typically found in the urine of active marijuana users (linear dynamic range of 12.5-800 ng/mL). The validation results indicated this method was accurate (average inter/intra-day bias, <10%), precise (inter/intra-day imprecision, <10%), and fast (6 min run time). In addition, sample preparation throughput was greatly improved using an automation liquid-handling system, meeting the needs for potential large-scale population studies.