Habibul Ahsan

Arsenic exposure from drinking water is considered to be a risk factor for skin and internal cancers. Animal studies suggest a potential antagonism between arsenic and selenium in the body. We did a case-cohort analysis to prospectively evaluate the association between arsenic-related premalignant skin lesions and prediagnostic blood selenium levels in 303 cases of skin lesions newly diagnosed from November 2002 to April 2004 and 849 subcohort members randomly selected from the 8,092 participants in the Health Effects of Arsenic Longitudinal Study with available baseline blood and urine samples collected in 2000. Incidence rate ratios for skin lesions in increasing blood selenium quintiles were 1.00 (reference), 0.68 [95% confidence interval (95% CI), 0.39-1.18], 0.51 (95% CI, 0.29-0.87), 0.52 (95% CI, 0.30-0.91), and 0.53 (95% CI, 0.31-0.90). Effect estimates remained similar with adjustments for age, sex, body mass index, smoking status, excessive sunlight exposure (in men), well water arsenic concentration at baseline, and nutritional intakes of folate, iron, protein, vitamin E, and B vitamins. At any given arsenic exposure level, the risk of premalignant skin lesions was consistently greater among participants with blood selenium lower than the average level. The findings support the hypothesis that dietary selenium intake may reduce the incidence of arsenic-related premalignant skin lesions among populations exposed to arsenic exposure from drinking water. (Cancer Epidemiol Biomarkers Prev 2007;16(2):207–13)

Y Chen, P Factor-Litvak, G R Howe, F Parvez, H Ahsan; Nutritional Influence on Risk of High Blood Pressure in Bangladesh: A Population-Based Cross-Sectional St

Y Chen, M Hall, J Graziano, V Slavkovich, A van Geen, F Parvez, H Ahsan; A Prospective Study of Blood Selenium Levels and the Risk of Arsenic-Related Skin Lesi

We have developed a thirty-nine-item semi-quantitative food-frequency questionnaire (FFQ) to assess the dietary consumption of 11 746 men and women in a prospective cohort study that evaluates the health effects of As from drinking water in Bangladesh. In order to validate the FFQ, two 7 d food diaries (FD) were completed for 189 randomly selected cohort participants in two different seasons of the year. Nutrient values were converted based on both the United States Department of Agriculture's National Nutrient Database and a food composition table for the Indian subcontinent. Pearson product-moment and Spearman non-parametric rank correlation coefficients comparing food and nutrient consumptions estimated from FFQ and 7 d FD were calculated based on log-transformed consumption values with or without adjustment for total energy and correction for within-individual variation. Correlations of macronutrients and common micronutrients including total fat, monounsaturated fat, polyunsaturated fat, saturated fat, protein, carbohydrate, dietary fibre, Na, K, vitamin B₆, vitamin B₁₂, riboflavin, Mn, thiamin and Fe were moderately good, ranging from 0·30 to 0·76. However, correlations of other micronutrients were weak (<0·30). Large seasonal variations in intakes of retinol equivalents and vitamin C were observed. This analysis documents the degree of validity of the FFQ in measuring specific nutrient intakes in the study population. To our knowledge, the present study is the first to document the validity of a FFQ with the use of 7 d FD in a Bangladeshi population.

Prostate cancer is the most commonly diagnosed cancer in men and one of the leading causes of cancer deaths. There is strong genetic evidence indicating that a large proportion of prostate cancers are caused by heritable factors but the search for prostate cancer susceptibility genes has thus far remained elusive. TGFBR1*6A, a common hypomorphic variant of the type I Transforming Growth Factor Beta receptor, is emerging as a tumor susceptibility allele that predisposes to the development of breast, colon and ovarian cancer. The association with prostate cancer has not yet been explored. A total of 907 cases and controls from New York City were genotyped to test the hypothesis that TGFBR1*6A may contribute to the development of prostate cancer. TGFBR1*6A allelic frequency among cases (0.086) was slightly higher than among controls (0.080) but the differences in TGFBR1*6A genotype distribution between cases and controls did not reach statistical significance (p = 0.67). Our data suggest that TGFBR1*6A does not contribute to the development of prostate cancer.

Background The case-only study for investigating gene–environment interactions provides increased statistical efficiency over case-control analyses. This design has been criticized for being susceptible to bias arising from non-independence between the genetic and environmental factors in the population. Given that independence is critical to the validity of case-only estimates of interaction, researchers frequently use controls to evaluate whether the independence assumption is tenable, as advised in the literature. Our work investigates to what extent this approach is appropriate and how non-independence can be accounted for in case-only analyses. Methods We provide a formula in epidemiological terms that illustrates the relationship between the gene–environment association measured among controls and the gene–environment association in the source population. Using this formula, we conducted sensitivity analyses to describe the circumstances in which controls can be used as proxy for the source population when evaluating gene–environment independence. Lastly, we generated hypothetical cohort data to examine whether multivariable modelling approaches can be used to control for non-independence. Results Our sensitivity analyses show that controls should not be used to evaluate gene–environment independence in the population, even when the baseline risk of disease is low (i.e. 1%), and the interaction and independent effects are moderate (i.e. risk ratio = 2). When the factors are associated, it is possible to remove bias arising from non-independence using standard statistical multivariable techniques in case-only analyses. Conclusions Even when the disease risk is low, evaluation of gene–environment independence in controls does not provide a consistent test for bias in the case-only study. Given that control for non-independence is possible when the source of the non-independence can be conceptualized, the case-only design may still be a useful epidemiological tool for examining gene–environment interactions.