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Purpose of Review: In this paper, we summarize prior studies that have used Mendelian Randomization (MR) methods to study the effects of exposures, lifestyle factors, physical traits, and/or biomarkers on cancer risk in humans. Many such risk factors have been associated with cancer risk in observational studies, and the MR approach can be used to provide evidence as to whether these associations represent causal relationships. MR methods require a risk factor of interest to have known genetic determinants that can be used as proxies for the risk factor (i.e., "instrumental variables" or IVs), and these can be used to obtain an effect estimate that, under certain assumptions, is not prone to bias caused by unobserved confounding or reverse causality. This review seeks to describe how MR studies have contributed to our understanding of cancer causation., Recent Findings: We searched the published literature and identified 76 MR studies of cancer risk published prior to October 31, 2017. Risk factors commonly studied included alcohol consumption, Vitamin D, anthropometric traits, telomere length, lipid traits, glycemic traits, and markers of inflammation. Risk factors showing compelling evidence of a causal association with risk for at least one cancer type include alcohol consumption (for head/neck and colorectal), adult body mass index (increases risk for multiple cancers, but decreases risk for breast), height (increases risk for breast, colorectal, and lung; decreases risk for esophageal), telomere length (increases risk for lung adenocarcinoma, melanoma, renal cell carcinoma, glioma, B-cell lymphoma subtypes, chronic lymphocytic leukemia, and neuroblastoma), and hormonal factors (affects risk for sex-steroid sensitive cancers)., Summary: This review highlights alcohol consumption, body mass index, height, telomere length, and the hormonal exposures as factors likely to contribute to cancer causation. This review also highlights the need to study specific cancer types, ideally subtypes, as the effects of risk factors can be heterogeneous across cancer types. As consortia-based genome-wide association studies increase in sample size and analytical methods for MR continue to become more sophisticated, MR will become an increasingly powerful tool for understanding cancer causation.

Inherited genetic variation affects local gene expression and DNA methylation in humans. Most expression quantitative trait loci (cis-eQTLs) occur at the same genomic location as a methylation QTL (cis-meQTL), suggesting a common causal variant and shared mechanism. Using DNA and RNA from peripheral blood of Bangladeshi individuals, here we use co-localization methods to identify eQTL-meQTL pairs likely to share a causal variant. We use partial correlation and mediation analyses to identify >400 of these pairs showing evidence of a causal relationship between expression and methylation (i.e., shared mechanism) with many additional pairs we are underpowered to detect. These co-localized pairs are enriched for SNPs showing opposite associations with expression and methylation, although many SNPs affect multiple CpGs in opposite directions. This work demonstrates the pervasiveness of co-regulated expression and methylation in the human genome. Applying this approach to other types of molecular QTLs can enhance our understanding of regulatory mechanisms.

Identifying gene-environment interactions is a central challenge in the quest to understand susceptibility to complex, multi-factorial diseases. Developing an understanding of how inter-individual variability in inherited genetic variation alters the effects of environmental exposures will enhance our knowledge of disease mechanisms and improve our ability to predict disease and target interventions to high-risk sub-populations. Limited progress has been made identifying gene-environment interactions in the epidemiological setting using existing statistical approaches for genome-wide searches for interaction. In this paper, we describe a novel two-step approach using omics data to conduct genome-wide searches for gene-environment interactions. Using existing genome-wide SNP data from a large Bangladeshi cohort study specifically designed to assess the effect of arsenic exposure on health, we evaluated gene-arsenic interactions by first conducting genome-wide searches for SNPs that modify the effect of arsenic on molecular phenotypes (gene expression and DNA methylation features). Using this set of SNPs showing evidence of interaction with arsenic in relation to molecular phenotypes, we then tested SNP-arsenic interactions in relation to skin lesions, a hallmark characteristic of arsenic toxicity. With the emergence of additional omics data in the epidemiologic setting, our approach may have the potential to boost power for genome-wide interaction research, enabling the identification of interactions that will enhance our understanding of disease etiology and our ability to develop interventions targeted at susceptible sub-populations.

Background: Leucocyte telomere length (TL) is a potential biomarker of ageing and risk for age-related disease. Leucocyte TL is heritable and shows substantial differences by race/ethnicity. Recent genome-wide association studies (GWAS) report ~10 loci harbouring SNPs associated with leucocyte TL, but these studies focus primarily on populations of European ancestry., Objective: This study aims to enhance our understanding of genetic determinants of TL across populations., Methods: We performed a GWAS of TL using data on 5075 Bangladeshi adults. We measured TL using one of two technologies (qPCR or a Luminex-based method) and used standardised variables as TL phenotypes., Results: Our results replicate previously reported associations in the TERC and TERT regions (P=2.2×10 -8 and P=6.4×10 -6 , respectively). We observed a novel association signal in the RTEL1 gene (intronic SNP rs2297439; P=2.82×10 -7 ) that is independent of previously reported TL-associated SNPs in this region. The minor allele for rs2297439 is common in South Asian populations (≥0.25) but at lower frequencies in other populations (eg, 0.07 in Northern Europeans). Among the eight other previously reported association signals, all were directionally consistent with our study, but only rs8105767 ( ZNF208 ) was nominally significant (P=0.003). SNP-based heritability estimates were as high as 44% when analysing close relatives but much lower when analysing distant relatives only., Conclusions: In this first GWAS of TL in a South Asian population, we replicate some, but not all, of the loci reported in prior GWAS of individuals of European ancestry, and we identify a novel second association signal at the RTEL1 locus., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes ( cis -eQTLs). More research is needed to identify effects of genetic variation on distant genes ( trans -eQTLs) and understand their biological mechanisms. One common trans -eQTLs mechanism is "mediation" by a local ( cis ) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are " cis -mediators" of trans -eQTLs, including those " cis -hubs" involved in regulation of many trans -genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans -eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis -mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis -hubs and trans -eQTL regulation across tissue types., (© 2017 Yang et al.; Published by Cold Spring Harbor Laboratory Press.)

A growing knowledge base of genetic and environmental information has greatly enabled the study of disease risk factors. However, the computational complexity and statistical burden of testing all variants by all environments has required novel study designs and hypothesis-driven approaches. We discuss how incorporating biological knowledge from model organisms, functional genomics, and integrative approaches can empower the discovery of novel gene-environment interactions and discuss specific methodological considerations with each approach. We consider specific examples where the application of these approaches has uncovered effects of gene-environment interactions relevant to drug response and immunity, and we highlight how such improvements enable a greater understanding of the pathogenesis of disease and the realization of precision medicine., (© The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

Genetic and environmental factors are both known to contribute to susceptibility to complex diseases. Therefore, the study of gene-environment interaction (G×E) has been a focus of research for several years. In this article, select examples of G×E from the literature are described to highlight different approaches and underlying principles related to the success of these studies. These examples can be broadly categorized as studies of single metabolism genes, genes in complex metabolism pathways, ranges of exposure levels, functional approaches and model systems, and pharmacogenomics. Some studies illustrated the success of studying exposure metabolism for which candidate genes can be identified. Moreover, some G×E successes depended on the availability of high-quality exposure assessment and longitudinal measures, study populations with a wide range of exposure levels, and the inclusion of ethnically and geographically diverse populations. In several examples, large population sizes were required to detect G×Es. Other examples illustrated the impact of accurately defining scale of the interactions (i.e., additive or multiplicative). Last, model systems and functional approaches provided insights into G×E in several examples. Future studies may benefit from these lessons learned., (© The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Genome-wide association studies (GWAS) have identified more than 90 susceptibility loci for breast cancer, but the underlying biology of those associations needs to be further elucidated. More genetic factors for breast cancer are yet to be identified but sample size constraints preclude the identification of individual genetic variants with weak effects using traditional GWAS methods. To address this challenge, we utilized a gene-level expression-based method, implemented in the MetaXcan software, to predict gene expression levels for 11,536 genes using expression quantitative trait loci and examine the genetically-predicted expression of specific genes for association with overall breast cancer risk and estrogen receptor (ER)-negative breast cancer risk. Using GWAS datasets from a Challenge launched by National Cancer Institute, we identified TP53INP2 (tumor protein p53-inducible nuclear protein 2) at 20q11.22 to be significantly associated with ER-negative breast cancer (Z = -5.013, p = 5.35×10-7, Bonferroni threshold = 4.33×10-6). The association was consistent across four GWAS datasets, representing European, African and Asian ancestry populations. There are 6 single nucleotide polymorphisms (SNPs) included in the prediction of TP53INP2 expression and five of them were associated with estrogen-receptor negative breast cancer, although none of the SNP-level associations reached genome-wide significance. We conducted a replication study using a dataset outside of the Challenge, and found the association between TP53INP2 and ER-negative breast cancer was significant (p = 5.07x10-3). Expression of HP (16q22.2) showed a suggestive association with ER-negative breast cancer in the discovery phase (Z = 4.30, p = 1.70x10-5) although the association was not significant after Bonferroni adjustment. Of the 249 genes that are 250 kb within known breast cancer susceptibility loci identified from previous GWAS, 20 genes (8.0%) were statistically significant associated with ER-negative breast cancer (p<0.05), compared to 582 (5.2%) of 11,287 genes that are not close to previous GWAS loci. This study demonstrated that expression-based gene mapping is a promising approach for identifying cancer susceptibility genes.

Ecologists have long recognized the influence that environmental conditions have on abundance and range extent of animal species. We used the northern bobwhite ( Colinus virginianus ; hereafter bobwhite) as a model species for studying how microclimates serve as refuge against severe weather conditions. This species serves as an indicator or umbrella species for other sensitive ground-nesting, grassland obligate species. We conducted a mensurative field experiment in the rolling plains of Texas, USA, a semi-arid ecosystem on the southwestern periphery of bobwhite range, to determine whether native bunch grasses, apparently suitable for bobwhite nesting, could reduce ambient temperature below levels harmful for eggs. During the nesting season, we compared temperature and relative humidity readings at daily heat maxima (i.e., the 3 h during each day with highest temperatures) during the nesting season over the course of two years at 63 suitable nest sites paired with 63 random locations ( n = 126) using two sensors at ∼10 and ∼60 cm above ground level. Mean temperature at nest height was 2.3% cooler at nest sites (35.99 °C ± 0.07 SE) compared to random locations (36.81 °C ± 0.07 SE); at ambient height, nest sites were slightly cooler (32.78 °C ± 0.06 SE) than random location (32.99 °C ± 0.06 SE). Mean relative humidity at nest sites was greater at nest height (34.53% ± 0.112 SE) and ambient height (36.22% ± 0.10 SE) compared to random locations at nest (33.35% ± 0.12 SE) and ambient height (35.75% ± 0.10 SE). Based on these results, cover at sites that appear visually suitable for nesting by bobwhites and other ground nesting birds provided adequate thermal refuge in the rolling plains by maintaining cooler, moister microclimates than surrounding non-nesting locations. Post-hoc analyses of data revealed that habitat conditions surrounding suitable nest sites strongly influenced thermal suitability of the substrate. Given that eggs of bobwhites and probably other species would experience lethal temperatures without these thermal refuges in the context of proper habitat condition, nesting vegetation is a critical component of niche space for bobwhites and other ground nesting birds in semi-arid regions. Many contemporary land uses, however, degrade or destroy bunch grasses and grassland systems, and thus decrease landscape inhabitability. Conservationists working with obligate grassland species that require bunch grasses in semi-arid regions should develop land management strategies that maximize the availability of these thermal refuges across space and time., Competing Interests: The authors declare that they have no competing interests.

Telomeres are tandem repeat sequences at the end of chromosomes that bind proteins to protect chromosome ends. Telomeres shorten with age, and shorter leukocyte telomere length (TL) has been associated with overall mortality in numerous studies. However, this association has not been tested in populations outside of Europe and the U.S. We assessed the association between TL and subsequent mortality using data on 744 mortality cases and 761 age-/sex-matched controls sampled from >27,000 participants from three longitudinal Bangladeshi cohorts: Health Effects of Arsenic Longitudinal Study (HEALS), HEALS Expansion (HEALS-E), and Bangladesh Vitamin E and Selenium Trial (BEST). We used conditional logistic regression to estimate odds ratios (ORs) for the association between a standardized TL variable and overall mortality, as well as mortality from chronic diseases, respiratory diseases, circulatory diseases, and cancer. In HEALS and BEST, we observed an association between shorter TL and increased overall mortality (P=0.03 and P=0.03), mortality from chronic disease (P=0.01 and P=0.03) and mortality from circulatory disease (P=0.03 and P=0.04). Results from pooled analyses of all cohorts were consistent with HEALS and BEST. This is the first study demonstrating an association between short TL and increased mortality in a population of non-European ancestry.

Inconsistent associations between smoking and telomere length (TL) have been reported in epidemiologic studies, perhaps because of the time-varying nature of smoking behaviors. We estimated the associations of TL, which was measured by quantitative polymerase chain reaction using saliva DNA, with concurrent and past smoking status reported biennially for up to 16 years before TL measurement in 5,624 participants in the Health and Retirement Study (1992-2008). Smoking was associated with reduced TL when we used prospective data on smoking statuses among men and women, but the association was strongly attenuated among men in cross-sectional analyses. This attenuation was largely due to a higher rate of smoking cessation during the study period among men with shorter TL than among men with longer TL. Short TL was also associated with poorer overall health in men, which suggests that male smokers with short TL were more likely to quit smoking because of poor health. Analyses of years since cessation, smoking duration, and pack-years of smoking all support the hypothesis that increased cigarette use shortens TL. Our results provide a potential explanation for the inconsistent associations between smoking and TL reported in previous cross-sectional studies. Time-varying associations should be considered in future studies of smoking behavior, TL, aging, and disease risk., (© The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Telomeres cap chromosome ends, protecting them from degradation, double-strand breaks, and end-to-end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset-based meta-analyses of 204,993 directly-measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene-level p value cutoffs ≤3.08 × 10 -5 ). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere-related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk., Competing Interests: Author’s disclosures of potential conflicts of interest: non for all authors., (© 2016 UICC.)

Background: Observational studies examining associations between adult height and risk of colorectal, prostate, and lung cancers have generated mixed results. We conducted meta-analyses using data from prospective cohort studies and further carried out Mendelian randomization analyses, using height-associated genetic variants identified in a genome-wide association study (GWAS), to evaluate the association of adult height with these cancers., Methods and Findings: A systematic review of prospective studies was conducted using the PubMed, Embase, and Web of Science databases. Using meta-analyses, results obtained from 62 studies were summarized for the association of a 10-cm increase in height with cancer risk. Mendelian randomization analyses were conducted using summary statistics obtained for 423 genetic variants identified from a recent GWAS of adult height and from a cancer genetics consortium study of multiple cancers that included 47,800 cases and 81,353 controls. For a 10-cm increase in height, the summary relative risks derived from the meta-analyses of prospective studies were 1.12 (95% CI 1.10, 1.15), 1.07 (95% CI 1.05, 1.10), and 1.06 (95% CI 1.02, 1.11) for colorectal, prostate, and lung cancers, respectively. Mendelian randomization analyses showed increased risks of colorectal (odds ratio [OR] = 1.58, 95% CI 1.14, 2.18) and lung cancer (OR = 1.10, 95% CI 1.00, 1.22) associated with each 10-cm increase in genetically predicted height. No association was observed for prostate cancer (OR = 1.03, 95% CI 0.92, 1.15). Our meta-analysis was limited to published studies. The sample size for the Mendelian randomization analysis of colorectal cancer was relatively small, thus affecting the precision of the point estimate., Conclusions: Our study provides evidence for a potential causal association of adult height with the risk of colorectal and lung cancers and suggests that certain genetic factors and biological pathways affecting adult height may also affect the risk of these cancers., Competing Interests: The authors have declared that no competing interests exist.

Background: Adiposity traits have been associated with risk of many cancers in observational studies, but whether these associations are causal is unclear. Mendelian randomization (MR) uses genetic predictors of risk factors as instrumental variables to eliminate reverse causation and reduce confounding bias. We performed MR analyses to assess the possible causal relationship of birthweight, childhood and adult body mass index (BMI), and waist-hip ratio (WHR) on the risks of breast, ovarian, prostate, colorectal and lung cancers., Methods: We tested the association between genetic risk scores and each trait using summary statistics from published genome-wide association studies (GWAS) and from 51 537 cancer cases and 61 600 controls in the Genetic Associations and Mechanisms in Oncology (GAME-ON) Consortium., Results: We found an inverse association between the genetic score for childhood BMI and risk of breast cancer [odds ratio (OR) = 0.71 per standard deviation (s.d.) increase in childhood BMI; 95% confidence interval (CI): 0.60, 0.80; P = 6.5 × 10(-5)). We also found the genetic score for adult BMI to be inversely associated with breast cancer risk (OR = 0.66 per s.d. increase in BMI; 95% CI: 0.57, 0.77; P = 2.5 × 10(-7)), and positively associated with ovarian cancer (OR = 1.35; 95% CI: 1.05, 1.72; P = 0.017), lung cancer (OR = 1.27; 95% CI: 1.09, 1.49; P = 2.9 × 10(-3)) and colorectal cancer (OR = 1.39; 95% CI: 1.06, 1.82, P = 0.016). The inverse association between genetically predicted adult BMI and breast cancer risk remained even after adjusting for directional pleiotropy via MR-Egger regression., Conclusions: Findings from this study provide additional understandings of the complex relationship between adiposity and cancer risks. Our results for breast and lung cancer are particularly interesting, given previous reports of effect heterogeneity by menopausal status and smoking status., (© The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

In genome-wide gene-environment interaction (GxE) studies, a common strategy to improve power is to first conduct a filtering test and retain only the SNPs that pass the filtering in the subsequent GxE analyses. Inspired by two-stage tests and gene-based tests in GxE analysis, we consider the general problem of jointly testing a set of parameters when only a few are truly from the alternative hypothesis and when filtering information is available. We propose a unified set-based test that simultaneously considers filtering on individual parameters and testing on the set. We derive the exact distribution and approximate the power function of the proposed unified statistic in simplified settings, and use them to adaptively calculate the optimal filtering threshold for each set. In the context of gene-based GxE analysis, we show that although the empirical power function may be affected by many factors, the optimal filtering threshold corresponding to the peak of the power curve primarily depends on the size of the gene. We further propose a resampling algorithm to calculate P-values for each gene given the estimated optimal filtering threshold. The performance of the method is evaluated in simulation studies and illustrated via a genome-wide gene-gender interaction analysis using pancreatic cancer genome-wide association data., (© 2015, The International Biometric Society.)

Telomere length is a potential biomarker of aging and risk for age-related diseases. For measurement of relative telomere repeat mass (TRM), qPCR is typically used primarily due to its low cost and low DNA input. But the position of the sample on a plate often impacts the qPCR-based TRM measurement. Recently we developed a novel, probe-based Luminex assay for TRM that requires ~50ng DNA and involves no DNA amplification. Here we report, for the first time, a comparison among TRM measurements obtained from (a) two singleplex qPCR assays (using two different primer sets), (b) a multiplex qPCR assay, and (c) our novel Luminex assay. Our comparison is focused on characterizing the effects of sample positioning on TRM measurement. For qPCR, DNA samples from two individuals (K and F) were placed in 48 wells of a 96-well plate. For each singleplex qPCR assay, we used two plates (one for Telomere and one for Reference gene). For the multiplex qPCR and the Luminex assay, the telomere and the reference genes were assayed from the same well. The coefficient of variation (CV) of the TRM for Luminex (7.2 to 8.4%) was consistently lower than singleplex qPCR (11.4 to 14.9%) and multiplex qPCR (19.7 to 24.3%). In all three qPCR assays the DNA samples in the left- and right-most columns showed significantly lower TRM than the samples towards the center, which was not the case for the Luminex assay (p = 0.83). For singleplex qPCR, 30.5% of the variation in TL was explained by column-to-column variation and 0.82 to 27.9% was explained by sample-to-sample variation. In contrast, only 5.8% of the variation in TRM for the Luminex assay was explained by column-to column variation and 50.4% was explained by sample-to-sample variation. Our novel Luminex assay for TRM had good precision and did not show the well position effects of the sample that were seen in all three of the qPCR assays that were tested.

Gene expression and its regulation can vary substantially across tissue types. In order to generate knowledge about gene expression in human tissues, the Genotype-Tissue Expression (GTEx) program has collected transcriptome data in a wide variety of tissue types from post-mortem donors. However, many tissue types are difficult to access and are not collected in every GTEx individual. Furthermore, in non-GTEx studies, the accessibility of certain tissue types greatly limits the feasibility and scale of studies of multi-tissue expression. In this work, we developed multi-tissue imputation methods to impute gene expression in uncollected or inaccessible tissues. Via simulation studies, we showed that the proposed methods outperform existing imputation methods in multi-tissue expression imputation and that incorporating imputed expression data can improve power to detect phenotype-expression correlations. By analyzing data from nine selected tissue types in the GTEx pilot project, we demonstrated that harnessing expression quantitative trait loci (eQTLs) and tissue-tissue expression-level correlations can aid imputation of transcriptome data from uncollected GTEx tissues. More importantly, we showed that by using GTEx data as a reference, one can impute expression levels in inaccessible tissues in non-GTEx expression studies., (Copyright © 2016 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Telomere length (TL) is a potential biomarker of aging and age-related disease risk. We recently published a novel Luminex-based method for high-throughput, low-cost TL measurement. Here we describe a blinded comparison of the Luminex method to Southern blot, the most precise TL measurement method. Luminex and Southern blot measurements for the same 50 DNA samples were taken in two independent laboratories; each sample was measured twice, several months apart. The inter-assay CV for Luminex ranged from 5.5 to 9.1 (depending on CV estimation method), and Southern blot CV from 1.0 to 1.7. Both measures were inversely associated with age. The correlation between the repeated measurements was 0.66 for Luminex and 0.97 for Southern blot. The correlation between Southern blot and Luminex was 0.65 in round 1 and 0.75 in round 2, and the relationship showed no evidence of non-linearity. Our results demonstrate that the Luminex assay is a valid and reproducible method for high-throughput TL measurement. The Luminex assay involves no DNA amplification, which may make Luminex an attractive alternative to PCR-based TL measurement.

Background: Exposure to inorganic arsenic (iAs), a class I carcinogen, affects several hundred million people worldwide. Once absorbed, iAs is converted to monomethylated (MMA) and then dimethylated forms (DMA), with methylation facilitating urinary excretion. The abundance of each species in urine relative to their sum (iAs%, MMA%, and DMA%) varies across individuals, reflecting differences in arsenic metabolism capacity., Methods: The association of arsenic metabolism phenotypes with participant characteristics and arsenical skin lesions was characterized among 4,794 participants in the Health Effects of Arsenic Longitudinal Study (Araihazar, Bangladesh). Metabolism phenotypes include those obtained from principal component (PC) analysis of arsenic species., Results: Two independent PCs were identified: PC1 appears to represent capacity to produce DMA (second methylation step), and PC2 appears to represent capacity to convert iAs to MMA (first methylation step). PC1 was positively associated (P <0.05) with age, female sex, and BMI, while negatively associated with smoking, arsenic exposure, education, and land ownership. PC2 was positively associated with age and education but negatively associated with female sex and BMI. PC2 was positively associated with skin lesion status, while PC1 was not. 10q24.32/AS3MT region polymorphisms were strongly associated with PC1, but not PC2. Patterns of association for most variables were similar for PC1 and DMA%, and for PC2 and MMA% with the exception of arsenic exposure and SNP associations., Conclusions: Two distinct arsenic metabolism phenotypes show unique associations with age, sex, BMI, 10q24.32 polymorphisms, and skin lesions., Impact: This work enhances our understanding of arsenic metabolism kinetics and toxicity risk profiles., (©2015 American Association for Cancer Research.)

Background: Consumption of arsenic-contaminated drinking water adversely affects health. There is interindividual variation in arsenic metabolism efficiency, partially due to genetic variation in the arsenic methyltransferase (AS3MT) gene region., Objectives: The goal of this study was to assess the overall contribution of genetic factors to variation in arsenic metabolism efficiency, as measured by the relative concentration of dimethylarsinic acid (DMA%) in urine., Methods: Using data on genome-wide single nucleotide polymorphisms (SNPs) and urinary DMA% for 2,053 arsenic-exposed Bangladeshi individuals, we employed various SNP-based approaches for heritability estimation and polygenic modeling., Results: Using data on all participants, the percent variance explained (PVE) for DMA% by all measured and imputed SNPs was 16% (p = 0.08), which was reduced to 5% (p = 0.34) after adjusting for AS3MT SNPs. Using information on close relatives only, the PVE was 63% (p = 0.0002), but decreased to 41% (p = 0.01) after adjusting for AS3MT SNPs. Regional heritability analysis confirmed 10q24.32 (AS3MT) as a major arsenic metabolism locus (PVE = 7%, p = 4.4 × 10(-10)), but revealed no additional regions. We observed a moderate association between a polygenic score reflecting elevated DMA% (composed of thousands of non-AS3MT SNPs) and reduced skin lesion risk in an independent sample (p < 0.05). We observed no associations for SNPs reported in prior candidate gene studies of arsenic metabolism., Conclusions: Our results suggest that there are common variants outside of the AS3MT region that influence arsenic metabolism in Bangladeshi individuals, but the effects of these variants are very weak compared with variants near AS3MT. The high heritability estimates observed using family-based heritability approaches suggest substantial effects for rare variants and/or unmeasured environmental factors.

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., (© The Author 2015. Published by Oxford University Press.)

Background: Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear., Methods: We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients., Results: The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor-positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10(-8)., Conclusions: Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Background: Epidemiologic data on genetic susceptibility to cardiovascular effects of arsenic exposure from drinking water are limited., Objective: We investigated whether the association between well-water arsenic and cardiovascular disease (CVD) differed by 170 single nucleotide polymorphisms (SNPs) in 17 genes related to arsenic metabolism, oxidative stress, inflammation, and endothelial dysfunction., Method: We conducted a prospective case-cohort study nested in the Health Effects of Arsenic Longitudinal Study, with a random subcohort of 1,375 subjects and 447 incident fatal and nonfatal cases of CVD. Well-water arsenic was measured in 2000 at baseline. The CVD cases, 56 of which occurred in the subcohort, included 238 coronary heart disease cases, 165 stroke cases, and 44 deaths due to other CVD identified during follow-up from 2000 to 2012., Results: Of the 170 SNPs tested, multiplicative interactions between well-water arsenic and two SNPs, rs281432 in ICAM1 (padj = 0.0002) and rs3176867 in VCAM1 (padj = 0.035), were significant for CVD after adjustment for multiple testing. Compared with those with GC or CC genotype in rs281432 and lower well-water arsenic, the adjusted hazard ratio (aHR) for CVD was 1.82 (95% CI: 1.31, 2.54) for a 1-SD increase in well-water arsenic combined with the GG genotype, which was greater than expected given aHRs of 1.08 and 0.96 for separate effects of arsenic and the genotype alone, respectively. Similarly, the joint aHR for arsenic and the rs3176867 CC genotype was 1.34 (95% CI: 0.95, 1.87), greater than expected given aHRs for their separate effects of 1.02 and 0.84, respectively., Conclusions: Associations between CVD and arsenic exposure may be modified by genetic variants related to endothelial dysfunction.

Human fertility is a complex trait determined by gene-environment interactions in which genetic factors represent a significant component. To better understand inter-individual variability in fertility, we performed one of the first genome-wide association studies (GWAS) of common fertility phenotypes, lifetime number of pregnancies and number of children in a developing country population. The fertility phenotype data and DNA samples were obtained at baseline recruitment from individuals participating in a large prospective cohort study in Bangladesh. GWAS analyses of fertility phenotypes were conducted among 1,686 married women. One SNP on chromosome 4 was non-significantly associated with number of children at P <10(-7) and number of pregnancies at P <10(-6). This SNP is located in a region without a gene within 1 Mb. One SNP on chromosome 6 was non-significantly associated with extreme number of children at P <10(-6). The closest gene to this SNP is HDGFL1, a hepatoma-derived growth factor. When we excluded hormonal contraceptive users, a SNP on chromosome 5 was non-significantly associated at P <10(-5) for number of children and number of pregnancies. This SNP is located near C5orf64, an open reading frame, and ZSWIM6, a zinc ion binding gene. We also estimated the heritability of these phenotypes from our genotype data using GCTA (Genome-wide Complex Trait Analysis) for number of children (hg2 = 0.149, SE = 0.24, p-value = 0.265) and number of pregnancies (hg2 = 0.007, SE = 0.22, p-value = 0.487). Our genome-wide association study and heritability estimates of number of pregnancies and number of children in Bangladesh did not confer strong evidence of common variants for parity variation. However, our results suggest that future studies may want to consider the role of 3 notable SNPs in their analysis.

Background: Inorganic arsenic is one of the most common naturally occurring contaminants found in the environment. Arsenic is associated with a number of health outcomes, with epigenetic modification suggested as a potential mechanism of toxicity., Objective: Among a sample of 400 adult participants, we evaluated the association between arsenic exposure, as measured by blood and urinary total arsenic concentrations, and epigenome-wide white blood cell DNA methylation., Methods: We used linear regression models to examine the associations between arsenic exposure and methylation at each CpG site, adjusted for sex, age, and batch. Differentially methylated loci were subsequently examined in relation to corresponding gene expression for functional evidence of gene regulation., Results: In adjusted analyses, we observed four differentially methylated CpG sites with urinary total arsenic concentration and three differentially methylated CpG sites with blood arsenic concentration, based on the Bonferroni-corrected significance threshold of p < 1 × 10(-7). Methylation of PLA2G2C (probe cg04605617) was the most significantly associated locus in relation to both urinary (p = 3.40 × 10(-11)) and blood arsenic concentrations (p = 1.48 × 10(-11)). Three additional novel methylation loci-SQSTM1 (cg01225779), SLC4A4 (cg06121226), and IGH (cg13651690)--were also significantly associated with arsenic exposure. Further, there was evidence of methylation-related gene regulation based on gene expression for a subset of differentially methylated loci., Conclusions: We observed significant associations between arsenic exposure and gene-specific differential white blood cell DNA methylation, suggesting that epigenetic modifications may be an important pathway underlying arsenic toxicity. The specific differentially methylated loci identified may inform potential pathways for future interventions.

Background: Inorganic arsenic is a carcinogen whose mode of action may involve telomere dysfunction. Recent epidemiological studies suggest that chronic arsenic exposure is associated with longer telomeres and altered expression of telomere-related genes in peripheral blood. In this study, we evaluated the association of urinary arsenic concentration with expression of telomere-related genes and telomere length in Bangladeshi individuals with a wide range of arsenic exposure through naturally contaminated drinking water., Methods: We used linear regression models to estimate associations between urinary arsenic and array-based expression measures for 69 telomere related genes using mononuclear cell RNA samples from 1799 individuals. Association between arsenic exposure and a qPCR-based telomere length measure was assessed among 167 individuals., Results: Urinary arsenic was positively associated with expression of WRN, and negatively associated with TERF2, DKC1, TERF2IP and OBFC1 (all P<0.00035, Bonferroni-corrected threshold). We detected interaction between urinary arsenic and arsenic metabolism efficiency in relation to expression of WRN (P for interaction =0.00008). In addition, we observed that very high arsenic exposure was associated with longer telomeres compared to very low exposure (P=0.02)., Discussion: Our findings suggest that arsenic's carcinogenic mode of action may involve alteration of telomere maintenance and/or telomere damage. This study extends our knowledge regarding the effect of arsenic on telomere length and expression of telomere-related genes., (Copyright © 2014 Elsevier Inc. All rights reserved.)

A large fraction of human genes are regulated by genetic variation near the transcribed sequence (cis-eQTL, expression quantitative trait locus), and many cis-eQTLs have implications for human disease. Less is known regarding the effects of genetic variation on expression of distant genes (trans-eQTLs) and their biological mechanisms. In this work, we use genome-wide data on SNPs and array-based expression measures from mononuclear cells obtained from a population-based cohort of 1,799 Bangladeshi individuals to characterize cis- and trans-eQTLs and determine if observed trans-eQTL associations are mediated by expression of transcripts in cis with the SNPs showing trans-association, using Sobel tests of mediation. We observed 434 independent trans-eQTL associations at a false-discovery rate of 0.05, and 189 of these trans-eQTLs were also cis-eQTLs (enrichment P<0.0001). Among these 189 trans-eQTL associations, 39 were significantly attenuated after adjusting for a cis-mediator based on Sobel P<10-5. We attempted to replicate 21 of these mediation signals in two European cohorts, and while only 7 trans-eQTL associations were present in one or both cohorts, 6 showed evidence of cis-mediation. Analyses of simulated data show that complete mediation will be observed as partial mediation in the presence of mediator measurement error or imperfect LD between measured and causal variants. Our data demonstrates that trans-associations can become significantly stronger or switch directions after adjusting for a potential mediator. Using simulated data, we demonstrate that this phenomenon is expected in the presence of strong cis-trans confounding and when the measured cis-transcript is correlated with the true (unmeasured) mediator. In conclusion, by applying mediation analysis to eQTL data, we show that a substantial fraction of observed trans-eQTL associations can be explained by cis-mediation. Future studies should focus on understanding the mechanisms underlying widespread cis-mediation and their relevance to disease biology, as well as using mediation analysis to improve eQTL discovery.

Background: Chronic arsenic exposure through drinking water is a public health problem affecting millions of people worldwide, including at least 30 million in Bangladesh. We prospectively investigated the associations of arsenic exposure and arsenical skin lesion status with lung disease mortality in Bangladeshi adults., Methods: Data were collected from a population-based sample of 26,043 adults, with an average of 8.5 years of follow-up (220,157 total person-years). There were 156 nonmalignant lung disease deaths and 90 lung cancer deaths ascertained through October 2013. We used Cox proportional hazards models to estimate adjusted hazard ratios and 95% confidence intervals (CIs) for lung disease mortality., Results: Creatinine-adjusted urinary total arsenic was associated with nonmalignant lung disease mortality, with persons in the highest tertile of exposure having a 75% increased risk for mortality (95% CI = 1.15-2.66) compared with those in the lowest tertile of exposure. Persons with arsenical skin lesions were at increased risk of lung cancer mortality (hazard ratio = 4.53 [95% CI = 2.82-7.29]) compared with those without skin lesions., Conclusions: This prospective investigation of lung disease mortality, using individual-level arsenic measures and skin lesion status, confirms a deleterious effect of ingested arsenic on mortality from lung disease. Further investigations should evaluate effects on the incidence of specific lung diseases, more fully characterize dose-response, and evaluate screening and biomedical interventions to prevent premature death among arsenic-exposed populations, particularly among those who may be most susceptible to arsenic toxicity.

Age-related cognitive decline is a major public health concern facing a large segment of the US population. To identify genetic risk factors related to cognitive decline, we used nationally representative longitudinal data from the US Health and Retirement Study to conduct genome-wide association studies with 5765 participants of European ancestry, and 890 participants of African ancestry. Mixed effects models were used to derive cognitive decline phenotypes from data on repeated cognitive assessments and to perform single nucleotide polymorphism-based heritability estimation. We found 2 independent associations among European-Americans in the 19q13.32 region: rs769449 (APOE intron; p = 3.1 × 10(-20)) and rs115881343 (TOMM40 intron; p = 6.6 × 10(-11)). rs769449 was also associated with cognitive decline among African-Americans (p = 0.005), but rs115881343 was not. Cross-sectional cognitive function showed moderate heritability (15%-32%) across several age strata (50-59, 60-69, 70-79 years), but the cognitive decline heritability estimate was low (∼5%). These results indicate that despite multiple association signals for cognitive decline in the 19q13.32 region, inter-individual variation is likely influenced substantially by environmental factors., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Background: The high prevalence of tobacco use in some developing nations, including Bangladesh, poses several public health challenges for these populations. Smoking behaviour is determined by genetic and environmental factors; however, the genetic determinants of smoking behaviour have not been previously examined in a Bangladeshi or South Asian population. We performed a genome-wide association study (GWAS) of tobacco smoking behaviour among a population-based sample of 5354 (2035 ever smokers and 3319 never smokers) men and women in Bangladesh., Methods: Genome-wide association analyses were conducted for smoking initiation (ever vs never smokers), smoking quantity (cigarettes per day), age of smoking initiation, and smoking cessation (former vs current smokers). Sex-stratified associations were performed for smoking initiation., Results: We observed associations for smoking initiation in the SLC39A11 region at 17q21.31 (rs2567519, p=1.33×10⁻⁷) among men and in the SLCO3A1 region at 15q26 (rs12912184, p=9.32×10⁻⁸) among women., Conclusions: These findings suggest possible underlying mechanisms related to solute carrier transporter genes, which transport neurotransmitters, nutrients, heavy metals and other substrates into cells, for smoking initiation in a South Asian population in a sex-specific pattern. Genetic markers could have potential translational implications for the prevention or treatment of tobacco use and addiction in South Asian populations and warrant further exploration.

Early-onset breast cancer (EOBC) causes substantial loss of life and productivity, creating a major burden among women worldwide. We analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 population control women ages ≤ 51 years. The SNPs with smallest P values were examined in a replication set of 3,470 EOBC cases and 5,475 control women. We also tested EOBC association with 19,684 genes by annotating each gene with putative functional SNPs, and then combining their P values to obtain a gene-based P value. We examined the gene with smallest P value for replication in 1,145 breast cancer cases and 1,142 control women. The combined discovery and replication sets identified 72 new SNPs associated with EOBC (P < 4 × 10(-8)) located in six genomic regions previously reported to contain SNPs associated largely with later-onset breast cancer (LOBC). SNP rs2229882 and 10 other SNPs on chromosome 5q11.2 remained associated (P < 6 × 10(-4)) after adjustment for the strongest published SNPs in the region. Thirty-two of the 82 currently known LOBC SNPs were associated with EOBC (P < 0.05). Low power is likely responsible for the remaining 50 unassociated known LOBC SNPs. The gene-based analysis identified an association between breast cancer and the phosphofructokinase-muscle (PFKM) gene on chromosome 12q13.11 that met the genome-wide gene-based threshold of 2.5 × 10(-6). In conclusion, EOBC and LOBC seem to have similar genetic etiologies; the 5q11.2 region may contain multiple distinct breast cancer loci; and the PFKM gene region is worthy of further investigation. These findings should enhance our understanding of the etiology of breast cancer.

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.

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.

A large body of epidemiologic evidence provides strong support for the notion that type-2 diabetics are at decreased risk for prostate cancer. In this review article, we summarize the epidemiologic literature that explores the role of diabetes mellitus and related biomarkers in prostate cancer risk and detection, in order to create a better understanding of the potential mechanisms that underlie this inverse association. The bulk of the data supporting this association comes from the USA, as evidence for this association is less consistent in many other regions of the world. The relationship between diabetes and prostate cancer is suspected to be causal due to evidence of decreasing prostate cancer risk with increasing diabetes duration and lack of evidence for any confounding of this association. Hypothesized mechanisms for decreased prostate cancer risk among diabetics include (1) decreased levels of hormones and other cancer-related growth factors among diabetics, (2) the impact of diabetes on detection-related factors, such as prostate size, circulating prostate-specific antigen (PSA), and health-care seeking behaviors, (3) protective effects of diabetes medications, and (4) a protective effect of diabetes-induced vascular damage in the prostate. The evidence for screening-related factors is compelling, as diabetics appear to have reduced PSA and lower levels of health-care seeking behavior compared with nondiabetics. Furthermore, the inverse association between diabetes and prostate cancer is much less apparent in populations that do not perform biopsies based on PSA levels and in studies restricted to biopsied individuals. The inverse association appears to be stronger for low-grade disease, as compared with high-grade (Gleason >7), which is consistent with the observation that among patients receiving biopsy or prostate cancer treatment, diabetics are more likely to have high-grade disease as compared to nondiabetics, potentially resulting in worse outcomes for diabetics. Epidemiological research has reveals a great deal regarding the relationship between diabetes and prostate cancer risk, but additional research is needed to further clarify the mechanisms underlying this inverse association., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Genome-wide association (GWA) studies have identified several pancreatic cancer (PanCa) susceptibility loci. Methods for assessment of polygenic susceptibility can be employed to detect the collective effect of additional association signals for PanCa. Using data on 492,651 autosomal single nucleotide polymorphisms (SNPs) from the PanScan GWA study (2,857 cases, 2,967 controls), we employed polygenic risk score (PRS) cross-validation (CV) methods to (a) confirm the existence of unidentified association signals, (b) assess the predictive value of PRSs, and (c) assess evidence for polygenic effects in specific genomic locations (genic vs. intergenic). After excluding SNPs in known PanCa susceptibility regions, we constructed PRS models using a training GWA dataset and then tested the model in an independent testing dataset using fourfold CV. We also employed a "power-replication" approach, where power to detect SNP associations was calculated using a training dataset, and power was tested for association with "replication status" in a testing dataset. PRS scores constructed using ≥ 10% of genome-wide SNPs showed significant association with PanCa (P< 0.05) across the majority of CV analyses. Associations were stronger for PRSs restricted to genic SNPs compared to intergenic PRSs. The power-replications approach produced weaker associations that were not significant when restricting to SNPs with low pairwise linkage disequilibrium, whereas PRS results were robust to such restrictions. Although the PRS approach will not dramatically improve PanCa prediction, it provides strong evidence for unidentified association signals for PanCa. Our results suggest that focusing association studies on genic regions and conducting larger GWA studies can reveal additional PanCa susceptibility loci., (© 2012 Wiley Periodicals, Inc.)

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 individual's 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., Competing Interests: The authors have declared that no competing interests exist.

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).

In genome-wide association (GWA) studies, hundreds of thousands of single-nucleotide polymorphisms (SNP) are tested for association with a disease trait. Typically, GWA studies give equal consideration to all SNPs tested, regardless of existing knowledge of an SNP's functionality or biological plausibility of association. Because many tests are conducted, very low statistical significance thresholds (P < 5 × 10(-8)) are required to identify true associations with confidence. By restricting GWA analyses to SNPs with enhanced prior probabilities of association, we can reduce the number of tests conducted and relax the required significance threshold, increasing power to detect association. In this analysis of existing GWA data on pancreatic cancer cases (n = 1,736) and controls (n = 1,802) of European descent (the PanScan study), we conduct a GWA scan restricted to SNPs that have been reported to associate with human phenotypes in previous GWA studies (with P < 5 × 10(-8)). Using this method, we drastically reduce the number of tests conducted (from ~550,000 to 1,087) and test only SNPs that are known to be (or tag) variants that influence human biological processes. Of the 1,087 SNPs tested, the strongest association observed was for HNF1A SNP rs7310409 (P = 3 × 10(-5); P(Bonferroni) = 0.03), an SNP known to associate with circulating C-reactive protein. This association was replicated in an independent sample of 1,094 cases and 1,165 controls (P = 0.02), producing a highly significant association in the combined data sets (P = 2 × 10(-6); P(Bonferroni) = 0.002). The HNF1A region also harbors variants that influence several human traits, including maturity-onset diabetes of the young, type 2 diabetes, low-density lipoprotein cholesterol, and N-glycan levels. This novel "pleiotropy scan" method may be useful for identifying susceptibility loci for other cancer phenotypes., (©2011 AACR.)

Objective: To examine associations between recently identified common type 2 diabetes (T2D) susceptibility genetic variants and pancreatic cancer risk., Methods: Using data on individuals of European ancestry from the Cancer Genetic Markers of Susceptibility PanScan-I study (1,763 pancreatic cancer cases and 1,802 controls), we tested associations for 37 T2D susceptibility variants with pancreatic cancer risk. Associations with pancreatic cancer were also tested for three composite T2D susceptibility measures, incorporating data on all 37 variants, and for ten additional variants related to T2D-related phenotypes, including fasting glucose and beta-cell function., Results: Of the 37 T2D risk alleles, two showed nominally significant positive associations with pancreatic cancer risk (FTO rs8050136 per-allele OR = 1.12; CI: 1.02-1.23; MTNR1B rs1387153 OR = 1.11; CI: 1.00-1.23) and one showed an inverse association (BCL11A rs243021 OR = 0.88; CI: 0.80-0.97). The composite T2D susceptibility measures were not associated with pancreatic cancer. The glucose-raising allele of MADD rs11039149 was associated with increased risk of pancreatic cancer (OR = 1.14; CI: 1.03-1.27)., Conclusions: Overall, these results do not provide strong evidence that common variants underling T2D or related phenotypes also affect pancreatic cancer risk; however, associations for FTO, MTNR1B, BCL11A, and MADD variants warrant further investigation in larger studies. Hypothesis-driven analyses of existing genome-wide genetic data can be cost-efficient and promising approaches for investigating genetic susceptibility to complex diseases.

Background: Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored., Methods: We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic., Results: Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure., Conclusions: The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.

Dietary factors are believed to modulate arsenic toxicity, potentially influencing risk of arsenical skin lesions. The authors evaluated associations among dietary patterns, arsenic exposure, and skin lesion risk using baseline food frequency questionnaire data collected in the Health Effects of Arsenic Longitudinal Study (HEALS) in Araihazar, Bangladesh (2000-2009). They identified dietary patterns and estimated dietary pattern scores using factor analysis. Scores were tested for association with incident skin lesion risk and interaction with water arsenic exposure by using ∼6 years of follow-up data (814 events among 9,677 individuals) and discrete time hazards models (adjusting for key covariates). The authors identified 3 clear dietary patterns: the "gourd and root," "vegetable," and "animal protein" patterns. The gourd and root pattern score was inversely associated with skin lesion risk (P(trend) = 0.001), with hazard ratios of 0.86, 0.73, and 0.69 for the second, third, and fourth highest quartiles. Furthermore, the association between water arsenic and skin lesion incidence was stronger among participants with low gourd and root scores (multiplicative P(interaction) < 0.001; additive P(interaction) = 0.05). The vegetable pattern and animal protein pattern showed similar but weaker associations and interactions. Eating a diet rich in gourds and root vegetables and increasing dietary diversity may reduce arsenical skin lesion risk in Bangladesh.

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.

Purpose: The objective of this analysis was to evaluate the effects of dietary B vitamin intakes on creatinine-adjusted urinary total arsenic concentration among individuals participating in the Health Effects of Arsenic Longitudinal Study (HEALS) cohort in Araihazar, Bangladesh. Arsenic exposure is a major public health problem in Bangladesh, where nearly 77 million people have been chronically exposed to arsenic through the consumption of naturally contaminated groundwater. Dietary factors influencing the metabolism of ingested arsenic may potentially be important modifiers of the health effects of arsenic in this population., Methods: Daily average B vitamin intakes from a validated food frequency questionnaire and laboratory data on drinking water and urinary arsenic concentrations among 9,833 HEALS cohort participants were utilized. Statistical analyses were conducted using generalized estimating equations incorporating knotted spline linear regression., Results: Increasing dietary intakes of thiamin, niacin, pantothenic acid, and pyridoxine were found to significantly increase urinary total arsenic excretion, adjusted for daily arsenic intake from drinking water and other potential confounders., Conclusions: These results suggest that higher intakes of certain B vitamins may enhance the excretion of arsenic from the body. This study offers new insights into modifiable dietary factors that relate to arsenic excretion and thus provides potential avenues for the prevention of arsenic-related health effects.

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.

Objective: To examine the collective effects of type 1 (T1D) and type 2 diabetes (T2D) risk alleles on prostate cancer (PCa) risk., Methods: Using data on 14 and 18 single nucleotide polymorphisms (SNPs) that effect T1D and T2D risk, respectively, we generated risk scores (a 'risk allele count' and a 'genetic relative risk') for both T1D and T2D for 1,171 non-Hispanic white, PSA-screened PCa cases and 1,101 matched controls from the Cancer Genetic Markers of Susceptibility study. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between the diabetes risk scores and PCa risk., Results: Both T2D risk scores, but neither T1D score, showed an inverse association with PCa (p < 0.01). These associations remained significant after excluding HNF1B SNP rs4430796 (a known PCa risk factor) from the analysis. The highest quartile of the T2D allele count (>20 risk alleles) was associated with reduced PCa risk (OR = 0.77; CI: 0.60-0.99) compared to the lowest category (<17 risk alleles)., Conclusions: These results suggest that individuals with increased genetic susceptibility to T2D have decreased risk for PCa. This association is consistent with the observation that individuals with T2D are at decreased risk for PCa; however, data on T2D status was not available for this analysis., (Copyright 2010 S. Karger AG, Basel.)

Case-control genome-wide association (GWA) studies have facilitated the identification of susceptibility loci for many complex diseases; however, these studies are often not adequately powered to detect gene-environment (G x E) and gene-gene (G x G) interactions. Case-only studies are more efficient than case-control studies for detecting interactions and require no data on control subjects. In this article, we discuss the concept and utility of the case-only genome-wide interaction (COGWI) study, in which common genetic variants, measured genome-wide, are screened for association with environmental exposures or genetic variants of interest. An observed G-E (or G-G) association, as measured by the case-only odds ratio (OR), suggests interaction, but only if the interacting factors are unassociated in the population from which the cases were drawn. The case-only OR is equivalent to the interaction risk ratio. In addition to risk-related interactions, we discuss how the COGWI design can be used to efficiently detect G x G, G x E and pharmacogenetic interactions related to disease outcomes in the context of observational clinical studies or randomized clinical trials. Such studies can be conducted using only data on individuals experiencing an outcome of interest or individuals not experiencing the outcome of interest. Sharing data among GWA and COGWI studies of disease risk and outcome can further enhance efficiency. Sample size requirements for COGWI studies, as compared to case-control GWA studies, are provided. In the current era of genome-wide analyses, the COGWI design is an efficient and straightforward method for detecting G x G, G x E and pharmacogenetic interactions related to disease risk, prognosis and treatment response.

Inflammation is believed to play a role in prostate cancer (PCa) etiology, but it is unclear whether inflammatory markers C-reactive protein (CRP) and interleukin-6 (IL-6) associate with PCa risk in older men. Using Cox regression, we assessed the relationship between baseline concentrations of CRP and IL-6 and the subsequent PCa risk in the Cardiovascular Health Study, a population-based cohort study of mostly European American men of ages >64 years (n = 2,234; mean follow-up = 8.7 years; 215 incident PCa cases). We also tested associations between CRP and IL-6 tagSNPs and PCa risk, focusing on SNPs that are known to associate with circulating CRP and/or IL-6. Neither CRP nor IL-6 blood concentrations was associated with PCa risk. The C allele of IL-6 SNP rs1800795 (-174), a known functional variant, was associated with increased risk in a dominant model (HR = 1.44; 95% CI = 1.03-2.01; p = 0.03), but was not statistically significant after accounting for multiple tests (permutation p = 0.21). Our results suggest that circulating CRP and IL-6 do not influence PCa risk. SNPs at the CRP locus are not associated with PCa risk in this cohort, while the association between rs1800795 and PCa risk warrants further investigation.

Purpose: Fragmented ownership of diagnostic gene patents has the potential to create an "anticommons" in the area of genomic diagnostics, making it difficult and expensive to assemble the patent rights necessary to develop a panel of genetic tests. The objectives of this study were to identify US patents that protect existing panels of genetic tests, describe how (or if) test providers acquired rights to these patents, and determine if fragmented patent ownership has inhibited the commercialization of these panels., Methods: As case studies, we selected four clinical applications of genetic testing (cystic fibrosis, maturity-onset diabetes of the young, long QT syndrome, and hereditary breast cancer) that use tests protected by > or =3 US patents. We summarized publically available information on relevant patents, test providers, licenses, and litigation., Results: For each case study, all tests of major genes/mutations were patented, and at least one party held the collective rights to conduct all relevant tests, often as a result of licensing agreements., Conclusions: We did not find evidence that fragmentation of patent rights has inhibited commercialization of genetic testing services. However, as knowledge of genetic susceptibility increases, it will be important to consider the potential consequences of fragmented ownership of diagnostic gene patents.

Introduction: Inflammatory status may be an important prognostic factor for breast cancer. Correlates of markers of inflammation in breast cancer survivors have not been thoroughly evaluated., Methods: Using data from, the Health, Eating, Activity, and Lifestyle (HEAL) Study (a population-based, multiethnic prospective cohort study of female breast cancer patients) we evaluated the associations between circulating markers of inflammation (C-reactive protein [CRP] and serum amyloid A [SAA], measured approximately 31 months after diagnosis) and several demographic, lifestyle, and clinical characteristics in 741 disease-free breast cancer survivors. Analysis of variance and regression methods were used for statistical analyses of log-transformed values of CRP and SAA., Results: After adjusting for age, BMI, ethnicity, and study site, higher concentrations of CRP were associated with increasing concentration of SAA (P-trend < 0.0001), increasing age (P-trend < 0.0001), increasing BMI (P-trend < 0.0001), increasing waist circumference (P-trend < 0.0001), positive history of heart failure (P = 0.0007), decreasing physical activity (P-trend = 0.005), Hispanic ethnicity (P = 0.05 vs. non-Hispanic white), and current smoking (P = 0.03 vs. never smoking). Vitamin E supplementation (P = 0.0005), tamoxifen use (P = 0.008), and radiation treatment (compared to no chemotherapy or radiation; P = 0.04) were associated with reduced CRP. Associations of CRP with clinical characteristics were not significant in the adjusted models. In a multivariate analysis, CRP showed significant associations with waist circumference, BMI, age, history of heart failure, tamoxifen use, and vitamin E supplementation (R (2) = 0.35). Similar, yet fewer, associations were observed for SAA (R (2) = 0.19)., Conclusions: This study highlights important correlates of inflammatory status in breast cancer patients. Our results are consistent with those from similar studies of healthy women.