Patterns of Tobacco Product Use in the US Population using the Population Assessment of Tobacco and Health Study

The U.S. Centers for Disease Control and Prevention (CDC) reported that, in the United States, tobacco product use is the prominent cause of avoidable disease, disability, and death in the year 2017.While tobacco use has severe public health consequences, it has been difficult to fully understand the behaviors surrounding this preventable public health challenge. Introduced in 2011, the Population Assessment of Tobacco and Health (PATH) Study’s purpose is to influence the Food and Drug Administration\u27s regulatory activities via the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH study is a longitudinal cohort study examining tobacco use and behavior in adolescents and adults. The purpose of this dissertation is to examine use and behavior for tobacco products over time and examine both initiation and switching of products. In our analysis, we found that demographically, those who initiated or consistently used smokeless products over time were white and male while those who used traditional combustible products varied more in terms of racial makeup. With smokeless and traditional combustible products, most participants chose to use tobacco products with moderate nicotine levels, regardless of previous exposure in a prior study wave. There was very little evidence of product switching that resulted in increased tar/nicotine content differences among the population we studied. Younger participants were using electronic cigarettes in greater proportions than adults and as opposed to traditional combustible products. We also found that the rate of nicotine metabolism was not related to frequency of e-cigarette use or type of product. These results provide insight into ways in which prevention strategies can be targeted to groups that are more likely to initiate and stay using tobacco products

Association of selenoprotein and selenium pathway gnotypes with risk of colorectal cancer and interaction with selenium status

Selenoprotein genetic variations and suboptimal selenium (Se) levels may contribute to the risk of colorectal cancer (CRC) development. We examined the association between CRC risk and genotype for single nucleotide polymorphisms (SNPs) in selenoprotein and Se metabolic pathway genes. Illumina Goldengate assays were designed and resulted in the genotyping of 1040 variants in 154 genes from 1420 cases and 1421 controls within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Multivariable logistic regression revealed an association of 144 individual SNPs from 63 Se pathway genes with CRC risk. However, regarding the selenoprotein genes, only TXNRD1 rs11111979 retained borderline statistical significance after adjustment for correlated tests (PACT = 0.10; PACT significance threshold was P < 0.1). SNPs in Wingless/Integrated (Wnt) and Transforming growth factor (TGF) beta-signaling genes (FRZB, SMAD3, SMAD7) from pathways affected by Se intake were also associated with CRC risk after multiple testing adjustments. Interactions with Se status (using existing serum Se and Selenoprotein P data) were tested at the SNP, gene, and pathway levels. Pathway analyses using the modified Adaptive Rank Truncated Product method suggested that genes and gene x Se status interactions in antioxidant, apoptosis, and TGF-beta signaling pathways may be associated with CRC risk. This study suggests that SNPs in the Se pathway alone or in combination with suboptimal Se status may contribute to CRC development

Association of Selenoprotein and Selenium Pathway Genotypes with Risk of Colorectal Cancer and Interaction with Selenium Status

Selenoprotein genetic variations and suboptimal selenium (Se) levels may contribute to the risk of colorectal cancer (CRC) development. We examined the association between CRC risk and genotype for single nucleotide polymorphisms (SNPs) in selenoprotein and Se metabolic pathway genes. Illumina Goldengate assays were designed and resulted in the genotyping of 1040 variants in 154 genes from 1420 cases and 1421 controls within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Multivariable logistic regression revealed an association of 144 individual SNPs from 63 Se pathway genes with CRC risk. However, regarding the selenoprotein genes, only TXNRD1 rs11111979 retained borderline statistical significance after adjustment for correlated tests (P-ACT = 0.10; P-ACT significance threshold was P <0.1). SNPs in Wingless/Integrated (Wnt) and Transforming growth factor (TGF) beta-signaling genes (FRZB, SMAD3, SMAD7) from pathways affected by Se intake were also associated with CRC risk after multiple testing adjustments. Interactions with Se status (using existing serum Se and Selenoprotein P data) were tested at the SNP, gene, and pathway levels. Pathway analyses using the modified Adaptive Rank Truncated Product method suggested that genes and gene x Se status interactions in antioxidant, apoptosis, and TGF-beta signaling pathways may be associated with CRC risk. This study suggests that SNPs in the Se pathway alone or in combination with suboptimal Se status may contribute to CRC development.Peer reviewe

Vitamin D-Related Genes, Blood Vitamin D Levels and Colorectal Cancer Risk in Western European Populations

Higher circulating 25-hydroxyvitamin D levels (25(OH)D) have been found to be associated with lower risk for colorectal cancer (CRC) in prospective studies. Whether this association is modified by genetic variation in genes related to vitamin D metabolism and action has not been well studied in humans. We investigated 1307 functional and tagging single-nucleotide polymorphisms (SNPs; individually, and by gene/pathway) in 86 vitamin D-related genes in 1420 incident CRC cases matched to controls from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. We also evaluated the association between these SNPs and circulating 25(OH)D in a subset of controls. We confirmed previously reported CRC risk associations between SNPs in the VDR, GC, and CYP27B1 genes. We also identified additional associations with 25(OH)D, as well as CRC risk, and several potentially novel SNPs in genes related to vitamin D transport and action (LRP2, CUBN, NCOA7, and HDAC9). However, none of these SNPs were statistically significant after Benjamini-Hochberg (BH) multiple testing correction. When assessed by a priori defined functional pathways, tumor growth factor beta (TGF beta) signaling was associated with CRC risk (P <= 0.001), with most statistically significant genes being SMAD7 (P-BH = 0.008) and SMAD3 (P-BH = 0.008), and 18 SNPs in the vitamin D receptor (VDR) binding sites (P = 0.036). The 25(OH)D-gene pathway analysis suggested that genetic variants in the genes related to VDR complex formation and transcriptional activity are associated with CRC depending on 25(OH)D levels (interaction P = 0.041). Additional studies in large populations and consortia, especially with measured circulating 25(OH)D, are needed to confirm our findings

Supplementary Table S24 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study

Supplementary Table S24 shows the results of weighted multiple linear regression analysis of log-transformed urinary 3,4-methylhippuric acid (34MHA) with study covariates</p

Supplementary Table S41 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study

Supplementary Table S41 shows scaled variance components and intra-class correlation coefficients resulting from mixed model analysis for all analytes</p

Supplementary Table S12 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study

Supplementary Table S12 shows the results of weighted multiple linear regression analysis of log-transformed urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) with study covariates</p

Supplementary Table S35 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study

Supplementary Table S35 shows the results of weighted multiple linear regression analysis of log-transformed urinary N‐acetyl‐S‐(4‐hydroxy‐2‐methyl‐2‐buten‐1‐yl)‐L‐cysteine (4HMBeMA) with study covariates</p

Supplementary Table S2 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study

Supplementary Table S2 shows the reference biomarker half-lives used in the analysis</p

Supplementary Table S22 from Influence of Half-life and Smoking/Nonsmoking Ratio on Biomarker Consistency between Waves 1 and 2 of the Population Assessment of Tobacco and Health Study

Supplementary Table S22 shows the results of weighted multiple linear regression analysis of log-transformed urinary N‐acetyl‐S‐(1‐cyano‐2‐hydroxyethyl)‐L‐cysteine (1CyHEMA) with study covariates</p