Genetic Susceptibility to Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in the West and is an incurable malignancy. No firmly established evidence exists for environmental risk factors in the etiology of CLL. However, CLL is estimated to have one of the highest familial risks for a hematologic malignancy; this along with other evidence strongly supports an inherited genetic component. In the past 5 years, genome-wide association studies (GWAS) have provided the foundation for new avenues in the investigation of pathogenesis of this disease with 22 susceptibility loci currently identified. We review here the advances made in identifying these loci, the potential to translate these findings into clinical practice, and future directions needed to advance our understanding of the genetic susceptibility of CLL. (C) 2013 Elsevier Inc. All rights reserved

Impact of changing US cigarette smoking patterns on incident cancer: Risks of 20 smoking-related cancers among the women and men of the NIH-AARP cohort

Background: Historically, US women started smoking at a later age than men and had lower relative risks for smoking-related cancers. However, more recent birth cohorts of women and men have similar smoking histories and have now reached the high-risk age for cancer. The impact of these changes on cancer incidence has not been systematically examined. Methods: Relative risks (RR), 95% confidence intervals (CI) and attributable fractions were calculated for cigarette smoking and incidence of 20 smoking-related cancers in 186 057 women and 266 074 men of the National Institutes of Health-AARP cohort, aged 50 to 71 years in 1995 and followed for 11 years. Results: In the cohort, which included participants born between 1924 and 1945, most women and men started smoking as teenagers. RRs for current vs never smoking were similar in women and men for the following cancers: lung squamous-cell (RR women: 121.4, 95% CI: 57.3–257.4; RR men:114.6, 95% CI: 61.2–214.4), lung adenocarcinoma (RR women: 11.7, 95% CI: 9.8–14.0; RR men: 15.6, 95% CI: 12.5–19.6), laryngeal (RR women: 37.0, 95% CI: 14.9–92.3; RR men: 13.8, 95% CI: 9.3–20.2), oral cavity-pharyngeal (RR women:4.4, 95% CI: 3.3–6.0; RR men: 3.8, 95% CI: 3.0–4.7), oesophageal squamous cell (RR women: 7.3, 95% CI: 3.5–15.5; RR men: 6.2, 95% CI: 2.8–13.7), bladder (RR women: 4.7, 95% CI: 3.7–5.8; RR men: 4.0, 95% CI: 3.5–4.5), colon (RR women: 1.3, 95% CI: 1.2–1.5; RR men: 1.3, 95% CI: 1.1–1.4), and at other sites, with similar attributable fractions. Conclusions: RRs for current smoking and incidence of many smoking-related cancers are now similar in US women and men, likely reflecting converging smoking patterns

A Flexible Bayesian Model for Studying Gene–Environment Interaction

An important follow-up step after genetic markers are found to be associated with a disease outcome is a more detailed analysis investigating how the implicated gene or chromosomal region and an established environment risk factor interact to influence the disease risk. The standard approach to this study of gene–environment interaction considers one genetic marker at a time and therefore could misrepresent and underestimate the genetic contribution to the joint effect when one or more functional loci, some of which might not be genotyped, exist in the region and interact with the environment risk factor in a complex way. We develop a more global approach based on a Bayesian model that uses a latent genetic profile variable to capture all of the genetic variation in the entire targeted region and allows the environment effect to vary across different genetic profile categories. We also propose a resampling-based test derived from the developed Bayesian model for the detection of gene–environment interaction. Using data collected in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study, we apply the Bayesian model to evaluate the joint effect of smoking intensity and genetic variants in the 15q25.1 region, which contains a cluster of nicotinic acetylcholine receptor genes and has been shown to be associated with both lung cancer and smoking behavior. We find evidence for gene–environment interaction (P-value = 0.016), with the smoking effect appearing to be stronger in subjects with a genetic profile associated with a higher lung cancer risk; the conventional test of gene–environment interaction based on the single-marker approach is far from significant

A regression model for risk difference estimation in population-based case-control studies clarifies gender differences in lung cancer risk of smokers and never smokers

BACKGROUND: Additive risk models are necessary for understanding the joint effects of exposures on individual and population disease risk. Yet technical challenges have limited the consideration of additive risk models in case-control studies. METHODS: Using a flexible risk regression model that allows additive and multiplicative components to estimate absolute risks and risk differences, we report a new analysis of data from the population-based case-control Environment And Genetics in Lung cancer Etiology study, conducted in Northern Italy between 2002-2005. The analysis provides estimates of the gender-specific absolute risk (cumulative risk) for non-smoking- and smoking-associated lung cancer, adjusted for demographic, occupational, and smoking history variables. RESULTS: In the multiple-variable lexpit regression, the adjusted 3-year absolute risk of lung cancer in never smokers was 4.6 per 100,000 persons higher in women than men. However, the absolute increase in 3-year risk of lung cancer for every 10 additional pack-years smoked was less for women than men, 13.6 versus 52.9 per 100,000 persons. CONCLUSIONS: In a Northern Italian population, the absolute risk of lung cancer among never smokers is higher in women than men but among smokers is lower in women than men. Lexpit regression is a novel approach to additive-multiplicative risk modeling that can contribute to clearer interpretation of population-based case-control studies

N-Acetylation phenotype and genotype and risk of bladder cancer in benzidine-exposed workers

Several studies in subjects occupationally exposed to arylamine carcinogens have shown increased risks for bladder cancer associated with the slow acetylator phenotype. To follow up these reports, a case-control study of N-acetylation and bladder cancer risk was carried out among subjects occupationally exposed to benzidine, in benzidine dye production and use facilities in China. Thirty-eight bladder cancer cases and 43 controls from these factories were included for study of acetylation phenotype, by dapsone administration, and for polymorphisms in the NAT2 gene, by a polymerase chain reaction (PCR)-based test. In contrast to previous studies, no increase in bladder cancer risk was found for the slow N-acetylation phenotype (OR= 0.3; 95% CI = 0.1-1.3) or for slow N-acetylation-associated double mutations in NAT2 (OR = 0.5; 95% CI = 0.1-1.8). Examination of specific mutations and adjustment for age, weight, city and tobacco use did not alter the results. When examined by level of benzidine exposure in the cases, the bladder cancer risks associated with low (OR = 0.3, 95% CI = 0.0-2.2), medium (OR = 0.7, 95% CI = 0.1-4.5) and high (OR = 0.6, 95% CI = 0.1-3.5) exposure showed no interaction between genotype and benzidine exposure, within the range of exposures experienced by subjects in this study. This study, which is the first to incorporate phenotypic and genotypic analyses, provides evidence that the NAT2-related slow N-acetylation polymorphism is not associated with an increased risk of bladder cancer in workers exposed to benzidine, and may have a protective effec

Lung Cancer and Occupation in a Population-based Case-Control Study

The authors examined the relation between occupation and lung cancer in the large, population-based Environment And Genetics in Lung cancer Etiology (EAGLE) case-control study. In 2002–2005 in the Lombardy region of northern Italy, 2,100 incident lung cancer cases and 2,120 randomly selected population controls were enrolled. Lifetime occupational histories (industry and job title) were coded by using standard international classifications and were translated into occupations known (list A) or suspected (list B) to be associated with lung cancer. Smoking-adjusted odds ratios and 95% confidence intervals were calculated with logistic regression. For men, an increased risk was found for list A (177 exposed cases and 100 controls; odds ratio = 1.74, 95% confidence interval: 1.27, 2.38) and most occupations therein. No overall excess was found for list B with the exception of filling station attendants and bus and truck drivers (men) and launderers and dry cleaners (women). The authors estimated that 4.9% (95% confidence interval: 2.0, 7.8) of lung cancers in men were attributable to occupation. Among those in other occupations, risk excesses were found for metal workers, barbers and hairdressers, and other motor vehicle drivers. These results indicate that past exposure to occupational carcinogens remains an important determinant of lung cancer occurrence

Pooled Analysis of Alcohol Dehydrogenase Genotypes and Head and Neck Cancer: A HuGE Review

Possession of the fast metabolizing alleles for alcohol dehydrogenase (ADH), ADH1B*2 and ADH1C*1, and the null allele for aldehyde dehydrogenase (ALDH), ALDH2*2, results in increased acetylaldehyde levels and is hypothesized to increase the risk of head and neck cancer. To examine this association, the authors undertook a Human Genome Epidemiology review on these three genes and a pooled analysis of published studies on ADH1C. The majority of Asians had the fast ADH1B*2 and ADH1C*1 alleles, while the majority of Caucasians had the slow ADH1B*1/1 and ADH1C*1/2 genotypes. The ALDH2*2 null allele was frequently observed among Asians, though it was rarely observed in other populations. In a pooled analysis of data from seven case-control studies with a total of 1,325 cases and 1,760 controls, an increased risk of head and neck cancer was not observed for the ADH1C*1/2 genotype (odds ratio = 1.00, 95% confidence interval: 0.81, 1.23) or the ADH1C*1/1 genotype (odds ratio = 1.14, 95% confidence interval: 0.92, 1.41). Increased relative risks of head and neck cancer were reported for the ADH1B*1/1 and ALDH2*1/2 genotypes in several studies. Recommendations for future studies include larger sample sizes and incorporation of relevant ADH and ALDH genes simultaneously, as well as other genes. These considerations suggest the potential for the organization of a consortium of investigators conducting studies in this fiel