E-cigarette use results in suppression of immune and inflammatory-response genes in nasal epithelial cells similar to cigarette smoke

Exposure to cigarette smoke is known to result in impaired host defense responses and immune suppressive effects. However, the effects of new and emerging tobacco products, such as e-cigarettes, on the immune status of the respiratory epithelium are largely unknown. We conducted a clinical study collecting superficial nasal scrape biopsies, nasal lavage, urine, and serum from nonsmokers, cigarette smokers, and e-cigarette users and assessed them for changes in immune gene expression profiles. Smoking status was determined based on a smoking history and a 3-to 4-wk smoking diary and confirmed using serum cotinine and urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) levels. Total RNA from nasal scrape biopsies was analyzed using the nCounter Human Immunology v2 Expression panel. Smoking cigarettes or vaping e-cigarettes resulted in decreased expression of immunerelated genes. All genes with decreased expression in cigarette smokers (n = 53) were also decreased in e-cigarette smokers. Additionally, vaping e-cigarettes was associated with suppression of a large number of unique genes (n = 305). Furthermore, the e-cigarette users showed a greater suppression of genes common with those changed in cigarette smokers. This was particularly apparent for suppressed expression of transcription factors, such as EGR1, which was functionally associated with decreased expression of 5 target genes in cigarette smokers and 18 target genes in e-cigarette users. Taken together, these data indicate that vaping e-cigarettes is associated with decreased expression of a large number of immune-related genes, which are consistent with immune suppression at the level of the nasal mucosa

The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109975/1/cpt6100087.pd

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 tobaccoderived 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

Sources of variability in nicotine and cotinine levels with use of nicotine nasal spray, transdermal nicotine, and cigarette smoking

Aims Nicotine nasal spray and transdermal nicotine are effective aids to smoking cessation, and are being evaluated for treatment of other medical diseases. Wide variation in levels of nicotine and its metabolite, cotinine, have been observed with such therapies. This study aimed primarily to assess sources of individual variability in nicotine and metabolite plasma levels from these dosing systems and from cigarette smoking

Analyses of nicotine metabolism biomarker genetics stratified by sex in African and European Americans

Nicotine is inactivated by the polymorphic CYP2A6 enzyme to cotinine and then to 3′hydroxycotinine. The Nicotine Metabolite Ratio (NMR; 3′hydroxycotinine/cotinine) is a heritable nicotine metabolism biomarker, varies with sex and ancestry, and influences smoking cessation and disease risk. We conducted sex-stratified genome-wide association studies of the NMR in European American (EA) and African American (AA) smokers (NCT01314001, NCT00666978). In EA females (n = 389) and males (n = 541), one significant (P < 5e−8) chromosome 19 locus was found (top variant: rs56113850, CYP2A6 (intronic), for C vs. T: females: beta = 0.67, P = 7.5e−22, 21.8% variation explained; males: beta = 0.75, P = 1.2e−37, 26.1% variation explained). In AA females (n = 503) and males (n = 352), the top variant was found on chromosome 19 but differed by sex (females: rs11878604, CYP2A6 (~ 16 kb 3′), for C vs. T: beta = − 0.71, P = 6.6e−26, 16.2% variation explained; males: rs3865454, CYP2A6 (~ 7 kb 3′), for G vs. T: beta = 0.64, P = 1.9e−19, 18.9% variation explained). In AA females, a significant region was found on chromosome 12 (top variant: rs12425845: P = 5.0e−9, TMEM132C (~ 1 Mb 5′), 6.1% variation explained) which was not significant in AA males. In AA males, significant regions were found on chromosomes 6 (top variant: rs9379805: P = 4.8e−9, SLC17A2 (~ 8 kb 5′), 8.0% variation explained) and 16 (top variant: rs77368288: P = 3.5e−8, ZNF469 (~ 92 kb 5′), 7.1% variation explained) which were not significant in AA females. Further investigation of these associations outside of chromosome 19 is required, as they did not replicate. Understanding how sex and ancestry influence nicotine metabolism genetics may improve personalized approaches for smoking cessation and risk prediction for tobacco-related diseases