Brandon L. Pierce

Elevated Biomarkers of Inflammation Are Associated With Reduced Survival Among Breast Cancer Patients

PURPOSE Chronic inflammation is believed to contribute to the development and progression of breast cancer. Systemic C-reactive protein (CRP) and serum amyloid A (SAA) are measures of low-grade chronic inflammation and potential predictors of cancer survival. PATIENTS AND METHODS We evaluated the relationship between circulating markers of inflammation and breast cancer survival using data from the Health, Eating, Activity, and Lifestyle (HEAL) Study (a multiethnic prospective cohort study of women diagnosed with stage 0 to IIIA breast cancer). Circulating concentrations of CRP and SAA were measured approximately 31 months after diagnosis and tested for associations with disease-free survival (approximately 4.1 years of follow-up) and overall survival (approximately 6.9 years of follow-up) in 734 disease-free breast cancer survivors. Cox proportional hazards models were used with adjustment for potential confounding factors to generate hazard ratios (HRs) and 95% CIs. Results Elevated SAA and CRP were associated with reduced overall survival, regardless of adjustment for age, tumor stage, race, and body mass index (SAA P trend < .0001; CRP P trend = .002). The HRs for SAA and CRP tertiles suggested a threshold effect on survival, rather than a dose-response relationship (highest v lowest tertile: SAA HR = 3.15; 95% CI, 1.73 to 5.65; CRP HR = 2.27; 95% CI, 1.27 to 4.08). Associations were similar and still significant after adjusting for self-reported history of cardiovascular events and censoring cardiovascular disease deaths. Elevated CRP and SAA were also associated with reduced disease-free survival, although these associations were of borderline significance (SAA P trend = .04; CRP P trend = .07). CONCLUSION Circulating SAA and CRP may be important prognostic markers for long-term survival in breast cancer patients, independent of race, tumor stage, and body mass index.

Arsenic exposure from drinking water, and all-cause and chronic-disease mortalities in Bangladesh (HEALS): a prospective cohort study

BACKGROUND Millions of people worldwide are chronically exposed to arsenic through drinking water, including 35-77 million people in Bangladesh. The association between arsenic exposure and mortality rate has not been prospectively investigated by use of individual-level data. We therefore prospectively assessed whether chronic and recent changes in arsenic exposure are associated with all-cause and chronic-disease mortalities in a Bangladeshi population. METHODS In the prospective cohort Health Effects of Arsenic Longitudinal Study (HEALS), trained physicians unaware of arsenic exposure interviewed in person and clinically assessed 11 746 population-based participants (aged 18-75 years) from Araihazar, Bangladesh. Participants were recruited from October, 2000, to May, 2002, and followed-up biennially. Data for mortality rates were available throughout February, 2009. We used Cox proportional hazards model to estimate hazard ratios (HRs) of mortality, with adjustment for potential confounders, at different doses of arsenic exposure. FINDINGS 407 deaths were ascertained between October, 2000, and February, 2009. Multivariate adjusted HRs for all-cause mortality in a comparison of arsenic at concentrations of 10.1-50.0 microg/L, 50.1-150.0 microg/L, and 150.1-864.0 microg/L with at least 10.0 microg/L in well water were 1.34 (95% CI 0.99-1.82), 1.09 (0.81-1.47), and 1.68 (1.26-2.23), respectively. Results were similar with daily arsenic dose and total arsenic concentration in urine. Recent change in exposure, measurement of total arsenic concentrations in urine repeated biennially, did not have much effect on the mortality rate. INTERPRETATION Chronic arsenic exposure through drinking water was associated with an increase in the mortality rate. Follow-up data from this cohort will be used to assess the long-term effects of arsenic exposure and how they might be affected by changes in exposure. However, solutions and resources are urgently needed to mitigate the resulting health effects of arsenic exposure. FUNDING US National Institutes of Health.

Efficient Design for Mendelian Randomization Studies: Subsample and 2-Sample Instrumental Variable Estimators

Mendelian randomization (MR) is a method for estimating the causal relationship between an exposure and an outcome using a genetic factor as an instrumental variable (IV) for the exposure. In the traditional MR setting, data on the IV, exposure, and outcome are available for all participants. However, obtaining complete exposure data may be difficult in some settings, due to high measurement costs or lack of appropriate biospecimens. We used simulated data sets to assess statistical power and bias for MR when exposure data are available for a subset (or an independent set) of participants. We show that obtaining exposure data for a subset of participants is a cost-efficient strategy, often having negligible effects on power in comparison with a traditional complete-data analysis. The size of the subset needed to achieve maximum power depends on IV strength, and maximum power is approximately equal to the power of traditional IV estimators. Weak IVs are shown to lead to bias towards the null when the subsample is small and towards the confounded association when the subset is relatively large. Various approaches for confidence interval calculation are considered. These results have important implications for reducing the costs and increasing the feasibility of MR studies.

Genome-Wide Association Study Identifies Chromosome 10q24.32 Variants Associated with Arsenic Metabolism and Toxicity Phenotypes in Bangladesh

Arsenic contamination of drinking water is a major public health issue in many countries, increasing risk for a wide array of diseases, including cancer. There is inter-individual variation in arsenic metabolism efficiency and susceptibility to arsenic toxicity; however, the basis of this variation is not well understood. Here, we have performed the first genome-wide association study (GWAS) of arsenic-related metabolism and toxicity phenotypes to improve our understanding of the mechanisms by which arsenic affects health. Using data on urinary arsenic metabolite concentrations and approximately 300,000 genome-wide single nucleotide polymorphisms (SNPs) for 1,313 arsenic-exposed Bangladeshi individuals, we identified genome-wide significant association signals (P<5×10−8) for percentages of both monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) near the AS3MT gene (arsenite methyltransferase; 10q24.32), with five genetic variants showing independent associations. In a follow-up analysis of 1,085 individuals with arsenic-induced premalignant skin lesions (the classical sign of arsenic toxicity) and 1,794 controls, we show that one of these five variants (rs9527) is also associated with skin lesion risk (P = 0.0005). Using a subset of individuals with prospectively measured arsenic (n = 769), we show that rs9527 interacts with arsenic to influence incident skin lesion risk (P = 0.01). Expression quantitative trait locus (eQTL) analyses of genome-wide expression data from 950 individuals lymphocyte RNA suggest that several of our lead SNPs represent cis-eQTLs for AS3MT (P = 10−12) and neighboring gene C10orf32 (P = 10−44), which are involved in C10orf32-AS3MT read-through transcription. This is the largest and most comprehensive genomic investigation of arsenic metabolism and toxicity to date, the only GWAS of any arsenic-related trait, and the first study to implicate 10q24.32 variants in both arsenic metabolism and arsenical skin lesion risk. The observed patterns of associations suggest that MMA% and DMA% have distinct genetic determinants and support the hypothesis that DMA is the less toxic of these two methylated arsenic species. These results have potential translational implications for the prevention and treatment of arsenic-associated toxicities worldwide.

A Prospective Study of Arsenic Exposure From Drinking Water and Incidence of Skin Lesions in Bangladesh

Elevated concentrations of arsenic in groundwater pose a public health threat to millions of people worldwide. The authors aimed to evaluate the association between arsenic exposure and skin lesion incidence among participants in the Health Effects of Arsenic Longitudinal Study (HEALS). The analyses used data on 10,182 adults free of skin lesions at baseline through the third biennial follow-up of the cohort (2000-2009). Discrete-time hazard regression models were used to estimate hazard ratios and 95% confidence intervals for incident skin lesions. Multivariate-adjusted hazard ratios for incident skin lesions comparing 10.1-50.0, 50.1-100.0, 100.1-200.0, and ≥200.1 μg/L with ≤10.0 μg/L of well water arsenic exposure were 1.17 (95% confidence interval (CI): 0.92, 1.49), 1.69 (95% CI: 1.33, 2.14), 1.97 (95% CI: 1.58, 2.46), and 2.98 (95% CI: 2.40, 3.71), respectively (P(trend) = 0.0001). Results were similar for the other measures of arsenic exposure, and the increased risks remained unchanged with changes in exposure in recent years. Dose-dependent associations were more pronounced in females, but the incidence of skin lesions was greater in males and older individuals. Chronic arsenic exposure from drinking water was associated with increased incidence of skin lesions, even at low levels of arsenic exposure (<100 μg/L).

Diabetes mellitus and prostate cancer risk

Epidemiological evidence suggests that diabetes mellitus (DM) is associated with a decrease in risk for prostate cancer (PCa). The objective of this study was to examine the association between PCa risk and several characteristics of DM (duration, age at diagnosis, treatment) in data from two population‐based, case‐control studies of PCa.

Genetic determinants of telomere length and risk of common cancers: a Mendelian randomization study

Epidemiological studies have reported inconsistent associations between telomere length (TL) and risk for various cancers. These inconsistencies are likely attributable, in part, to biases that arise due to post-diagnostic and post-treatment TL measurement. To avoid such biases, we used a Mendelian randomization approach and estimated associations between nine TL-associated SNPs and risk for five common cancer types (breast, lung, colorectal, ovarian and prostate cancer, including subtypes) using data on 51 725 cases and 62 035 controls. We then used an inverse-variance weighted average of the SNP-specific associations to estimate the association between a genetic score representing long TL and cancer risk. The long TL genetic score was significantly associated with increased risk of lung adenocarcinoma (P = 6.3 × 10−15), even after exclusion of a SNP residing in a known lung cancer susceptibility region (TERT-CLPTM1L) P = 6.6 × 10−6). Under Mendelian randomization assumptions, the association estimate [odds ratio (OR) = 2.78] is interpreted as the OR for lung adenocarcinoma corresponding to a 1000 bp increase in TL. The weighted TL SNP score was not associated with other cancer types or subtypes. Our finding that genetic determinants of long TL increase lung adenocarcinoma risk avoids issues with reverse causality and residual confounding that arise in observational studies of TL and disease risk. Under Mendelian randomization assumptions, our finding suggests that longer TL increases lung adenocarcinoma risk. However, caution regarding this causal interpretation is warranted in light of the potential issue of pleiotropy, and a more general interpretation is that SNPs influencing telomere biology are also implicated in lung adenocarcinoma risk.

A prospective study of body mass index and mortality in Bangladesh

BACKGROUND Body mass index (BMI) (kg/m(2)) has a U- or J-shaped relationship with all-cause mortality in Western and East Asian populations. However, this relationship is not well characterized in Bangladesh, where the BMI distribution is shifted towards lower values. METHODS Using data on 11,445 individuals (aged 18-75 years) participating in the Health Effects of Arsenic Longitudinal Study (HEALS) in Araihazar, Bangladesh, we prospectively examined associations of BMI (measured at baseline) with all-cause mortality during approximately 6 years of follow-up. We also examined this relationship within strata of key covariates (sex, age, smoking, education and arsenic exposure). Cox proportional hazards models adjusted for these covariates and BMI-related illnesses were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for BMI categories defined by the World Health Organization. RESULTS Low BMI was strongly associated with increased mortality in this cohort (P-trend < 0.0001). Severe underweight (BMI < 16 kg/m(2); HR 2.06, CI 1.53-2.77) and moderate underweight (16.0-16.9 kg/m(2); HR 1.39, CI 1.01-2.90) were associated with increased all-cause mortality compared with normal BMI (18.6-22.9 kg/m(2)). The highest BMI category (> or =23.0 kg/m(2)) did not show a clear association with mortality (HR 1.10, CI 0.77-1.53). The BMI-mortality association was stronger among individuals with <5 years of formal education (interaction P = 0.02). CONCLUSIONS Underweight (presumably due to malnutrition) is a major determinant of mortality in the rural Bangladeshi population.

Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction

BACKGROUND Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms(SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesions is likely to be causal. METHODS Using data on 2060 arsenic-exposed Bangladeshi individuals, we estimated associations for two 10q24.32 SNPs with relative concentrations of three urinary arsenic species (representing metabolism efficiency): inorganic arsenic (iAs), monomethylarsonic acid(MMA) and dimethylarsinic acid (DMA). SNP-based predictions of iAs%, MMA% and DMA% were tested for association with skin lesion status among 2483 cases and 2857 controls. RESULTS Causal odds ratios for skin lesions were 0.90 (95% confidence interval[CI]: 0.87, 0.95), 1.19 (CI: 1.10, 1.28) and 1.23 (CI: 1.12, 1.36)for a one standard deviation increase in DMA%, MMA% and iAs%,respectively. We demonstrated genotype-arsenic interaction, with metabolism-related variants showing stronger associations with skin lesion risk among individuals with high arsenic exposure (synergy index: 1.37; CI: 1.11, 1.62). CONCLUSIONS We provide strong evidence for a causal relationship between arsenic metabolism efficiency and skin lesion risk. Mendelian randomization can be used to assess the causal role of arsenic exposure and metabolism in a wide array of health conditions.exposure and metabolism in a wide array of health conditions.Developing interventions that increase arsenic metabolism efficiency are likely to reduce the impact of arsenic exposure on health.

A Prospective Study of the Synergistic Effects of Arsenic Exposure and Smoking, Sun Exposure, Fertilizer Use, and Pesticide Use on Risk of Premalignant Skin Lesions in Bangladeshi Men

Skin lesions are classic clinical signs of toxicity due to long-term exposure to arsenic, and they are considered precursors to arsenic-related skin cancer. The authors prospectively evaluated synergisms between effects of arsenic exposure and those of tobacco use, sun exposure, and pesticide and fertilizer use on incident skin lesions using risk factor data from 5,042 men from the Health Effects of Arsenic Longitudinal Study in Araihazar, Bangladesh, which recruited participants from October 2000 to May 2002. Discrete time hazard models were used to estimate measures of synergistic interactions on the additive scale. The authors observed significant synergistic effects between various measures of arsenic exposure and smoking and fertilizer use. The relative excess risks for the interactions between smoking status and arsenic exposure were 0.12 (95% confidence interval: 0.06, 0.19) for water arsenic and 0.11 (95% confidence interval: 0.05, 0.15) for urinary arsenic measures, respectively. Significant synergistic effects were also observed between fertilizer use and water arsenic (relative excess risk for the interaction = 0.06, 95% confidence interval: 0.01, 0.12). This is the first prospective study based on individual-level data that supports a role for smoking and certain occupational risk factors in modification of the effect of long-term arsenic exposure on skin lesions. Understanding differential arsenic susceptibility allows researchers to develop interventions to prevent the health consequences of this massive problem in the Bangladeshi population and beyond.