Empirical Type I error rates for all tests: with hidden stratification.

a<p>nominal α = 0.05.</p>b<p>nominal α = 0.0001.</p

Observed power to detect the true positive marker: with both hidden stratification and hidden relatedness between subjects.

<p>Observed power to detect the true positive marker: with both hidden stratification and hidden relatedness between subjects.</p

Deviations from uniformity under the null, 1% DNA differentiation.

<p>We show a plot of the distribution of the p-values of all non-causal SNPs for each of the four competing tests when 1% DNA differentiation between cases and controls is present. The straight broken line represents Uniform (0,1) distribution.</p

Observed type 1 error rates: with both hidden stratification and hidden relatedness between subjects.

<p>Observed type 1 error rates: with both hidden stratification and hidden relatedness between subjects.</p

Deviations from uniformity under the alternative, 1% DNA differentiation.

<p>We show a plot of the distribution of the p-values of all SNPs (20 of them are causal) for each of the four competing tests when 1% DNA differentiation between cases and controls is present. The straight broken line represents Uniform (0,1) distribution.</p

Power comparison among all tests: with hidden stratification.

a<p>α = 0.05.10⁻⁵.</p>b<p>α = 0.0001.</p

Deviations from uniformity under the alternative, no DNA differentiation.

<p>We show a plot of the distribution of the p-values of all SNPs (20 of them are causal) for each of the four competing tests when DNA differentiation between cases and controls is absent. The straight broken line represents Uniform (0,1) distribution.</p

Associations of biomarkers of nicotine uptake (TNE) and nicotine metabolism (CYP2A6 activity) with lung cancer incidence (92 cases).

<p>Associations of biomarkers of nicotine uptake (TNE) and nicotine metabolism (CYP2A6 activity) with lung cancer incidence (92 cases).</p

Association of CYP2A6 activity with lung cancer incidence in smokers: The multiethnic cohort study

<div><p>While smoking is the primary cause of lung cancer, only 11–24% of smokers develop the malignancy over their lifetime. The primary addictive agent in tobacco smoke is nicotine and variation in nicotine metabolism may influence the smoking levels of an individual. Therefore, inter-individual variation in lung cancer risk among smokers may be due in part to differences in the activity of enzymes involved in nicotine metabolism. In most smokers, cytochrome P450 2A6 (CYP2A6)-catalyzed C-oxidation accounts for >75% of nicotine metabolism, and the activity of this enzyme has been shown to correlate with the amount of nicotine and carcinogens drawn from cigarettes. We prospectively evaluated the association of urinary biomarkers of nicotine uptake (total nicotine equivalents [TNE]) and CYP2A6 activity (ratio of urinary total trans-3′-hydroxycotinine to cotinine) with lung cancer risk among 2,309 Multiethnic Cohort Study participants who were current smokers at time of urine collection; 92 cases were diagnosed during a mean follow-up of 9.5 years. We found that higher CYP2A6 activity and TNE was associated with increased lung cancer risk after adjusting for age, sex, race/ethnicity, body mass index, smoking duration, and urinary creatinine (p’s = 0.002). The association for CYP2A6 activity remained even after adjusting for self-reported cigarettes per day (CPD) (Hazard Ratio [HR] per unit increase in log-CYP2A6 activity = 1.52; p = 0.005) and after adjusting for TNE (HR = 1.46; p = 0.01). In contrast, the association between TNE and lung cancer risk was of borderline statistical significance when adjusted for CPD (HR = 1.53; p = 0.06) and not statistically significant when further adjusted for CYP2A6 activity (HR = 1.30; p = 0.22). These findings suggest that CYP2A6 activity provides information on lung cancer risk that is not captured by smoking history or a (short-term) biomarker of dose. CYP2A6 activity should be further studied as a risk biomarker for smoking-related lung cancer.</p></div

Association of Urinary N7-(1-hydroxyl-3-buten-1-yl) Guanine (EB-GII) Adducts and Butadiene-Mercapturic Acids with Lung Cancer Development in Cigarette Smokers

Approximately 10% of smokers will develop lung cancer. Sensitive predictive biomarkers are needed to identify susceptible individuals. 1,3-Butadiene (BD) is among the most abundant tobacco smoke carcinogens. BD is metabolically activated to 3,4-epoxy-1-butene (EB), which is detoxified via the glutathione conjugation/mercapturic acid pathway to form monohydroxybutenyl mercapturic acid (MHBMA) and dihydroxybutyl mercapturic acid (DHBMA). Alternatively, EB can react with guanine nucleobases of DNA to form N7-(1-hydroxyl-3-buten-1-yl) guanine (EB-GII) adducts. We employed isotope dilution LC/ESI-HRMS/MS methodologies to quantify MHBMA, DHBMA, and EB-GII in urine of smokers who developed lung cancer (N = 260) and matched smoking controls (N = 259) from the Southern Community Cohort (white and African American). The concentrations of all three biomarkers were significantly higher in smokers that subsequently developed lung cancer as compared to matched smoker controls after adjusting for age, sex, and race/ethnicity (p p p = 0.0007 for DHBMA). The odds ratio (OR) for lung cancer development was 1.63 for MHBMA, 1.37 for DHBMA, and 1.97 for EB-GII, with a higher OR in African American subjects than in whites. The association of urinary EB-GII, MHBMA, and DHBMA with lung cancer status did not remain upon adjustment for total nicotine equivalents. These findings reveal that urinary MHBMA, DHBMA, and EB-GII are directly correlated with the BD dose delivered via smoking and are associated with lung cancer risk