Exposure to metal mixtures and telomere length in Bangladeshi children.

Telomere length is associated with chronic diseases and in younger populations, may represent a biomarker of disease susceptibility. As growing evidence suggests that environmental factors, including metals, may impact telomere length, we investigated the association between 17 metals measured in toenail samples and leukocyte relative telomere length (RTL), among 472 five- to seven-year-old children enrolled in the Bangladesh Environmental Research in Children's Health (BiRCH) cohort. In single exposure linear regression models, a doubling of arsenic (As) and mercury (Hg) (µg/g) were associated with a -0.21 (95%CI: -0.032, -0.010; p=0.0005) and -0.017 (95%CI: -0.029, -0.004; p=0.006) difference in RTL, respectively. In Bayesian Kernel Machine Regression (BKMR) mixture models, the overall metal mixture was inversely associated with RTL (P-for-trend <0.001). Negative associations with RTL were observed with both log2-As and log2-Hg, while an inverted U-shaped association was observed for log2-zinc (Zn) with RTL. We found little evidence of interaction among metals. Sex-stratification identified stronger associations of the overall mixture and log2-As with RTL among females, compared to males. Our study suggests that As and Hg may independently influence RTL in mid-childhood. Further studies are needed to investigate potential long-term impacts of metal-associated telomere shortening in childhood on health outcomes in adult life.

Air quality and cancer risk in the All of Us Research Program.

INTRODUCTION: The NIH All of Us Research Program has enrolled over 544,000 participants across the US with unprecedented racial/ethnic diversity, offering opportunities to investigate myriad exposures and diseases. This paper aims to investigate the association between PM2.5 exposure and cancer risks. MATERIALS AND METHODS: This work was performed on data from 409,876 All of Us Research Program participants using the All of Us Researcher Workbench. Cancer case ascertainment was performed using data from electronic health records and the self-reported Personal Medical History questionnaire. PM2.5 exposure was retrieved from NASA's Earth Observing System Data and Information Center and assigned using participants' 3-digit zip code prefixes. Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Generalized additive models (GAMs) were used to investigate non-linear relationships. RESULTS: A total of 33,387 participants and 46,176 prevalent cancer cases were ascertained from participant EHR data, while 20,297 cases were ascertained from self-reported survey data from 18,133 participants; 9,502 cancer cases were captured in both the EHR and survey data. Average PM2.5 level from 2007 to 2016 was 8.90 µg/m3 (min 2.56, max 15.05). In analysis of cancer cases from EHR, an increased odds for breast cancer (OR 1.17, 95% CI 1.09-1.25), endometrial cancer (OR 1.33, 95% CI 1.09-1.62) and ovarian cancer (OR 1.20, 95% CI 1.01-1.42) in the 4th quartile of exposure compared to the 1st. In GAM, higher PM2.5 concentration was associated with increased odds for blood cancer, bone cancer, brain cancer, breast cancer, colon and rectum cancer, endocrine system cancer, lung cancer, pancreatic cancer, prostate cancer, and thyroid cancer. CONCLUSIONS: We found evidence of an association of PM2.5 with breast, ovarian, and endometrial cancers. There is little to no prior evidence in the literature on the impact of PM2.5 on risk of these cancers, warranting further investigation.

Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits.

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E-04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E-03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E-06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.

Associations of exposure to metal and metal mixtures with thyroid hormones: Results from the NHANES 2007-2012.

BACKGROUND: Disrupted thyroid homeostasis plays a role in neurocognitive dysfunction and metabolic disorders. Since individuals are exposed to multiple metals simultaneously, it is important to assess the effects of metal mixtures on thyroid hormone status. This study aimed to investigate the associations of metal mixtures and individual metals with thyroid hormone levels. METHODS: Data included 2399 men and 1988 women from the 2007-2012 National Health and Nutrition Examination Survey (2007-2012). Thyroid hormones measured included total triiodothyronine (T3), total thyroxine (T4), free forms of T3 (FT3) and T4 (FT4), and thyroid stimulating hormone (TSH). We included twelve metals (arsenic, barium, cobalt, cesium, molybdenum, antimony, thallium, tungsten, and uranium from urine; cadmium, lead, and mercury from blood) in traditional linear regression models controlling for 12 metals simultaneously and in quantile-based g-computation (QGC) to assess the relative contribution of each metal as well as the overall association with thyroid hormones as a metal mixture. RESULTS: There were associations of the total metal mixture with thyroid hormones for T3 (beta: -0.023, 95% CI: -0.04, -0.01, in women), T4 (beta: -0.03, 95% CI: -0.05, -0.01, in men; beta: -0.026, 95% CI: -0.04, -0.01, in women), and the T3:T4 ratio (beta: 0.026, 95% CI: 0.01, 0.05, in men). Arsenic had negative contributions to T3 and T4. Cadmium had a positive contribution to T4 but negative contributions to T3 and T3:T4. Lead had a positive contribution to T3 and T3:T4, but a negative contribution to T4. CONCLUSION: Multiple metals as a mixture were associated with thyroid hormone levels. Arsenic, cadmium, and lead were individually associated with multiple thyroid hormones. Examination of associations of metal mixtures and individual metals with thyroid hormones can contribute to an understanding of thyroid hormone homeostasis and provide evidence for developing intervention and guidance for health promotion.

A missense variant in FTCD is associated with arsenic metabolism and toxicity phenotypes in Bangladesh.

Inorganic arsenic (iAs) is a carcinogen, and exposure to iAs via food and water is a global public health problem. iAs-contaminated drinking water alone affects >100 million people worldwide, including ~50 million in Bangladesh. Once absorbed into the blood stream, most iAs is converted to mono-methylated (MMA) and then di-methylated (DMA) forms, facilitating excretion in urine. Arsenic metabolism efficiency varies among individuals, in part due to genetic variation near AS3MT (arsenite methyltransferase; 10q24.32). To identify additional arsenic metabolism loci, we measured protein-coding variants across the human exome for 1,660 Bangladeshi individuals participating in the Health Effects of Arsenic Longitudinal Study (HEALS). Among the 19,992 coding variants analyzed exome-wide, the minor allele (A) of rs61735836 (p.Val101Met) in exon 3 of FTCD (formiminotransferase cyclodeaminase) was associated with increased urinary iAs% (P = 8x10-13), increased MMA% (P = 2x10-16) and decreased DMA% (P = 6x10-23). Among 2,401 individuals with arsenic-induced skin lesions (an indicator of arsenic toxicity and cancer risk) and 2,472 controls, carrying the low-efficiency A allele (frequency = 7%) was associated with increased skin lesion risk (odds ratio = 1.35; P = 1x10-5). rs61735836 is in weak linkage disequilibrium with all nearby variants. The high-efficiency/major allele (G/Valine) is human-specific and eliminates a start codon at the first 5´-proximal Kozak sequence in FTCD, suggesting selection against an alternative translation start site. FTCD is critical for catabolism of histidine, a process that generates one-carbon units that can enter the one-carbon/folate cycle, which provides methyl groups for arsenic metabolism. In our study population, FTCD and AS3MT SNPs together explain ~10% of the variation in DMA% and support a causal effect of arsenic metabolism efficiency on arsenic toxicity (i.e., skin lesions). In summary, this work identifies a coding variant in FTCD associated with arsenic metabolism efficiency, providing new evidence supporting the established link between one-carbon/folate metabolism and arsenic toxicity.

Correction: A missense variant in FTCD is associated with arsenic metabolism and toxicity phenotypes in Bangladesh.

[This corrects the article DOI: 10.1371/journal.pgen.1007984.].

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

Machine Learning Models of Arsenic in Private Wells Throughout the Conterminous United States As a Tool for Exposure Assessment in Human Health Studies.

Arsenic from geologic sources is widespread in groundwater within the United States (U.S.). In several areas, groundwater arsenic concentrations exceed the U.S. Environmental Protection Agency maximum contaminant level of 10 µg per liter (µg/L). However, this standard applies only to public-supply drinking water and not to private-supply, which is not federally regulated and is rarely monitored. As a result, arsenic exposure from private wells is a potentially substantial, but largely hidden, public health concern. Machine learning models using boosted regression trees (BRT) and random forest classification (RFC) techniques were developed to estimate probabilities and concentration ranges of arsenic in private wells throughout the conterminous U.S. Three BRT models were fit separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, or 10 µg/L whereas the RFC model estimates the most probable category (≤5, >5 to ≤10, or >10 µg/L). Overall, the models perform best at identifying areas with low concentrations of arsenic in private wells. The BRT 10 µg/L model estimates for testing data have an overall accuracy of 91.2%, sensitivity of 33.9%, and specificity of 98.2%. Influential variables identified across all models included average annual precipitation and soil geochemistry. Models were developed in collaboration with public health experts to support U.S.-based studies focused on health effects from arsenic exposure.

Association between prenatal arsenic exposure, birth outcomes, and pregnancy complications: An observational study within the National Children's Study cohort.

BACKGROUND: Chronic arsenic exposure has been associated with pregnancy complications and reduced fetal growth in populations where total arsenic exposure exceeds 50 µg/L. However, the potential effect on pregnancy outcomes remains unclear at lower levels of arsenic exposure, such as those most commonly observed in the United States. OBJECTIVES: We evaluated the associations between arsenic exposure during pregnancy with fetal growth and risk of pregnancy complications using data from mother-infant pairs participating in the National Children's Study. METHODS: Prenatal arsenic exposure was measured using maternal urine collected during the third trimester. Information about pregnancy complications was abstracted from medical records. Fetal growth, including gestational age, birth weight, birth length, head circumference, and ponderal index, was ascertained through physical measurement at birth and extracted from medical records. RESULTS: Medians [interquartile range (IQR)] of maternal urinary total arsenic and dimethylarsinic acid (DMA) were 7.77 µg/L (7.98) and 3.44 µg/L (3.13), respectively. Each increase in IQR of prenatal total arsenic level was associated with greater birth length (+0.28 cm; 95% CI: 0.14, 0.42), greater head circumference (+0.12 cm; 95% CI: 0.04, 0.21), and lower ponderal index (-0.37 kg/m3; 95% CI: -0.58, -0.17). Similar results were obtained for levels of prenatal DMA. Tests for multiplicative interaction indicate that prenatal urinary DMA was negatively associated with gestational age among female infants (-0.44 week decrease in gestational age estimated for each IQR increase in DMA; 95% CI: -0.84, -0.05), while no association was observed among male infants (pinteraction = 0.02). No significant associations were detected between arsenic and birth weight or pregnancy complications. CONCLUSIONS: Higher prenatal arsenic exposure was associated with longer birth length, greater head circumference, and lower ponderal index. Associations between arsenic and gestational age may be modified by infant sex.

The effect of age on DNA methylation in whole blood among Bangladeshi men and women.

BACKGROUND: It is well-known that methylation changes occur as humans age, however, understanding how age-related changes in DNA methylation vary by sex is lacking. In this study, we characterize the effect of age on DNA methylation in a sex-specific manner and determine if these effects vary by genomic context. We used the Illumina HumanMethylation 450 K array and DNA derived from whole blood for 400 adult participants (189 males and 211 females) from Bangladesh to identify age-associated CpG sites and regions and characterize the location of these age-associated sites with respect to CpG islands (vs. shore, shelf, or open sea) and gene regions (vs. intergenic). We conducted a genome-wide search for age-associated CpG sites (among 423,604 sites) using a reference-free approach to adjust for cell type composition (the R package RefFreeEWAS) and performed an independent replication analysis of age-associated CpGs. RESULTS: The number of age-associated CpGs (p < 5 x 10- 8) were 986 among men and 3479 among women of which 2027(63.8%) and 572 (64.1%) replicated (using Bonferroni adjusted p < 1.2 × 10- 5). For both sexes, age-associated CpG sites were more likely to be hyper-methylated with increasing age (compared to hypo-methylated) and were enriched in CpG islands and promoter regions compared with other locations and all CpGs on the array. Although we observed strong correlation between chronological age and previously-developed epigenetic age models (r ≈ 0.8), among our top (based on lowest p-value) age-associated CpG sites only 12 for males and 44 for females are included in these prediction models, and the median chronological age compared to predicted age was 44 vs. 51.7 in males and 45 vs. 52.1 in females. CONCLUSIONS: Our results describe genome-wide features of age-related changes in DNA methylation. The observed associations between age and methylation were generally consistent for both sexes, although the associations tended to be stronger among women. Our population may have unique age-related methylation changes that are not captured in the established methylation-based age prediction model we used, which was developed to be non-tissue-specific.

The contribution of parent-to-offspring transmission of telomeres to the heritability of telomere length in humans.

Leukocyte telomere length (LTL) is a heritable trait with two potential sources of heritability (h2): inherited variation in non-telomeric regions (e.g., SNPs that influence telomere maintenance) and variability in the lengths of telomeres in gametes that produce offspring zygotes (i.e., "direct" inheritance). Prior studies of LTL h2 have not attempted to disentangle these two sources. Here, we use a novel approach for detecting the direct inheritance of telomeres by studying the association between identity-by-descent (IBD) sharing at chromosome ends and phenotypic similarity in LTL. We measured genome-wide SNPs and LTL for a sample of 5069 Bangladeshi adults with substantial relatedness. For each of the 6318 relative pairs identified, we used SNPs near the telomeres to estimate the number of chromosome ends shared IBD, a proxy for the number of telomeres shared IBD (Tshared). We then estimated the association between Tshared and the squared pairwise difference in LTL ((ΔLTL)2) within various classes of relatives (siblings, avuncular, cousins, and distant), adjusting for overall genetic relatedness (ϕ). The association between Tshared and (ΔLTL)2 was inverse among all relative pair types. In a meta-analysis including all relative pairs (ϕ > 0.05), the association between Tshared and (ΔLTL)2 (P = 0.01) was stronger than the association between ϕ and (ΔLTL)2 (P = 0.43). Our results provide strong evidence that telomere length (TL) in parental germ cells impacts TL in offspring cells and contributes to LTL h2 despite telomere "reprogramming" during embryonic development. Applying our method to larger studies will enable robust estimation of LTL h2 attributable to direct transmission of telomeres.

Urinary arsenic concentration, airway inflammation, and lung function in the U.S. adult population.

BACKGROUND: Inorganic arsenic (iAs) is ubiquitous in the environment and has been linked to lung cancer and a number of non-malignant lung disease in both adults and children. However, most studies were conducted in populations with higher arsenic exposure levels in drinking water and relatively little epidemiologic research evaluated the impacts of low levels iAs exposure on non-malignant lung disease among populations that are not primarily exposed to arsenic through drinking water. OBJECTIVES: We assessed the associations of arsenic exposure with airway inflammation and lung function among U.S. adults aged 20-79 years using data from the National Health and Nutrition Examination Survey 2007-2012 cycles. METHODS: Two measures of arsenic exposure, urinary total arsenic and dimethylarsonic acid (DMA), were used. We calibrated these two exposure measures by regressing their concentrations by arsenobetaine and extracting the residuals to calculate estimated total arsenic and estimated DMA. Arsenic exposures were modeled as log-transformed continuous variables as well as quartile categories. Fractional exhaled nitric oxide (FENO), an indicator of respiratory inflammation, was available for participants. For lung function, the best forced expiratory volume in the first one second (FEV1), forced vital capacity (FVC), forced expiratory flow rate (FEF) 25-75%, their percent estimated values, ratios of FEV1 to FVC, and FEF 25-75% to FVC were used (i.e. FEV1/FVC and FEF/FVC). Weighted multivariable linear regression models, adjusted for potential confounders, were used to evaluate the association of arsenic exposure with airway inflammation and lung function overall, and among males and females. RESULTS: Significant associations between arsenic exposure and increased airway inflammation were found. A two-fold increase in urinary total arsenic and DMA was associated with 23.87% (95% CI: 2.66, 49.46) and 14.05% (95% CI: 1.77, 27.81) higher levels of FENO, respectively. In addition, participants in the highest quartile of urinary total arsenic had FENO levels 8.49% (95% CI: 1.13, 16.39) higher than those in the lowest quartile. These associations were similar between males and females. Limited evidence was found for the association with respect to lung function and potential modification effect of sex. CONCLUSIONS: Arsenic exposure was related to increased risk of airway inflammation but there is limited evidence of an association in relation to lung function. Future research conducted in populations with relatively lower exposure levels that are not primarily exposed to arsenic through drinking water is needed to confirm our findings.

Multiple metal exposures and metabolic syndrome: A cross-sectional analysis of the National Health and Nutrition Examination Survey 2011-2014.

BACKGROUND: Epidemiologic studies suggest toxic metals are linked with diabetes and cardiovascular disease, while experimental studies indicate nutritionally essential metals are involved in the metabolism of macronutrients and defense against oxidative stress. OBJECTIVES: We sought to evaluate how essential and toxic metals are cross-sectionally related to metabolic syndrome, a clustering of cardiometabolic conditions. METHODS: Using data from the 2011-2014 National Health and Nutrition Examination Survey (n = 1088), we characterized metal concentrations as measured in spot urine (arsenic, cadmium, and inorganic/elemental mercury), whole blood (manganese, lead, methylmercury, and selenium), and serum (copper and zinc) samples. Principal component analysis was performed to derive patterns of exposures. Metabolic syndrome was defined according to the 2009 Joint Scientific Statement as the presence of ≥ 3 of the following conditions: high blood pressure, high triglycerides, low HDL cholesterol, high fasting glucose, and abdominal obesity. RESULTS: After adjustment for potential confounders, prevalence ratios for metabolic syndrome comparing the highest to the lowest quartiles were 1.41 (95% CI: 1.18-1.67) for the arsenic-inorganic/elemental mercury pattern, 0.95 (0.78-1.16) for the methylmercury-manganese pattern, 0.73 (0.57-0.94) for the cadmium-lead pattern, 0.91 (0.76-1.10) for the copper pattern, and 1.36 (1.13-1.63) for the selenium-zinc pattern. The positive associations observed for the arsenic-inorganic/elemental mercury pattern were due to an elevated prevalence of high blood pressure, low HDL cholesterol, and high triglycerides among those with greater exposures. Associations for the selenium-zinc pattern were driven by a positive relationship with high triglycerides. Greater lead-cadmium co-exposures were related to a lower prevalence of dyslipidemia and abdominal obesity. CONCLUSIONS: These cross-sectional findings suggest both toxic and essential metal exposures may contribute to cardiometabolic health, but need to be confirmed with prospective data.

Metallic air pollutants and breast cancer heterogeneity.

BACKGROUND: Emerging evidence suggests airborne metals may be associated with breast cancer risk. However, breast cancer is heterogenous and associations with heavy metals vary by subtype. Heavy metals possess both carcinogenic and xenoestrogenic properties which may be related to different tumor etiologies. Therefore, we tested for etiologic heterogeneity, using a case-series approach, to determine whether associations between residential airborne metal concentrations and breast cancer differed by tumor subtype. METHODS: Between 2005 and 2008, we enrolled incident breast cancer cases into the Breast Cancer Care in Chicago study. Tumor estrogen and progesterone receptors status was determined by medical record abstraction and confirmed immunohistochemically (N = 696; 147 ER/PR-negative). The 2002 USEPA's National Air Toxics Assessment census-tract estimates of metal concentrations (antimony, arsenic, beryllium, cadmium, chromium, cobalt, lead, manganese, mercury, nickel and selenium) were matched to participants' residences of the same year. Adjusted logistic regression models were used to examine whether the airborne heavy metal associations differed by tumor ER/PR status. Principal component analysis was performed to assess associations by metal co-exposures. RESULTS: Comparing the highest and lowest quintiles, higher concentrations of antimony (odds ratio[OR]: 1.8, 95% confidence interval[CI]: 0.9, 3.7, P-trend: 0.05), cadmium (OR: 2.3, 95% CI: 1.2, 4.4, P-trend: 0.04) and cobalt (OR: 2.0, 95% CI: 0.9, 4.4, P-trend: 0.04) were associated with ER/PR-negative breast cancer. Mixture analysis using principal components suggested co-exposures to multiple airborne heavy metals may drive associations with tumor receptor status. CONCLUSIONS: Among women diagnosed with breast cancer, metallic air pollutants were associated with increased odds of developing ER/PR-negative breast cancer.

Lack of Association between Opioid-Receptor Genotypes and Smoking Cessation Outcomes in a Randomized, Controlled Naltrexone Trial.

AIMS: The present study examined how variation in mu- (OPRM1), kappa- (OPRK), and delta- (OPRD) opioid receptor genes may influence the efficacy of naltrexone in the context of a smoking cessation trial. METHODS: The study's primary objective was to examine the association of the Asn40Asp OPRM1 single nucleotide polymorphism (SNP) with naltrexone's effects on smoking quit rate, weight gain, and heavy drinking behavior during a double-blind, randomized clinical trial in 280 adult DSM-IV nicotine-dependent participants. The secondary goal of the study was to examine the relationship of 20 additional SNPs of OPRM1, OPRK, and OPRD with the aforementioned outcomes. RESULTS: Results indicated a null association between any opioid-receptor gene SNP and naltrexone's effects on smoking quit rate, weight gain, and heavy drinking behavior in this sample of nicotine dependent participants. CONCLUSIONS: In sum, these results do not suggest that genetic variation in opioid-receptors is related to treatment responses to naltrexone in a smoking cessation trial.

Genome-wide association study of telomere length among South Asians identifies a second RTEL1 association signal.

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.

Screening for gene-environment (G×E) interaction using omics data from exposed individuals: an application to gene-arsenic interaction.

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.

Limited influence of germline genetic variation on all-cause mortality in women with early onset breast cancer: evidence from gene-based tests, single-marker regression, and whole-genome prediction.

PURPOSE: Women diagnosed with breast cancer have heterogeneous survival outcomes that cannot be fully explained by known prognostic factors, and germline variation is a plausible but unconfirmed risk factor. METHODS: We used three approaches to test the hypothesis that germline variation drives some differences in survival: mortality loci identification, tumor aggressiveness loci identification, and whole-genome prediction. The 2954 study participants were women diagnosed with breast cancer before age 50, with a median follow-up of 15 years who were genotyped on an exome array. We first searched for loci in gene regions that were associated with all-cause mortality. We next searched for loci in gene regions associated with five histopathological characteristics related to tumor aggressiveness. Last, we also predicted 10-year all-cause mortality on a subset of 1903 participants (3,245,343 variants after imputation) using whole-genome prediction methods. RESULTS: No risk loci for mortality or tumor aggressiveness were identified. This null result persisted when restricting to women with estrogen receptor-positive tumors, when examining suggestive loci in an independent study, and when restricting to previously published risk loci. Additionally, the whole-genome prediction model also found no evidence to support an association. CONCLUSION: Despite multiple complementary approaches, our study found no evidence that mortality in women with early onset breast cancer is influenced by germline variation.

Associations between prenatal arsenic exposure with adverse pregnancy outcome and child mortality.

BACKGROUND: Chronic arsenic exposure is a public health concern in many parts of the world, with elevated concentrations in groundwater posing a threat to millions of people. Arsenic is associated with various cancers and an array of chronic diseases; however, the relationship with adverse pregnancy outcomes and child mortality is less established. OBJECTIVES: We evaluated associations between individual-level prenatal arsenic exposure with adverse pregnancy outcomes and child mortality in a pregnancy study among 498 women nested in a larger population-based cohort in rural Bangladesh. METHODS: Creatinine-adjusted urinary total arsenic concentration, a comprehensive measure of exposure from water, food, and air sources, reflective of the prenatal period was available for participants. Self-reported pregnancy outcomes (livebirth, stillbirth, spontaneous/elective abortion) were ascertained. Generalized estimating equations, accounting for multiple pregnancies of participants, were used to estimate odds ratios and 95% confidence intervals in relation to adverse pregnancy outcomes. Vital status of livebirths was subsequently ascertained through November 2015. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals in relation to child mortality. RESULTS: We observed a significant association between prenatal arsenic exposure and the risk of stillbirth (greater than median; adjusted OR = 2.50; 95% CI = 1.04, 6.01). We also observed elevated risk of child mortality (greater than median; adjusted HR = 1.92; 95% CI = 0.78, 4.68) in relation to prenatal arsenic exposure. CONCLUSIONS: Prospective studies should continue to evaluate prenatal and early life health effects of arsenic exposure and arsenic remediation strategies for women of child-bearing age.

Association between genome-wide copy number variation and arsenic-induced skin lesions: a prospective study.

BACKGROUND: Exposure to arsenic in drinking water is a global health problem and arsenic-induced skin lesions are hallmark of chronic arsenic toxicity. We and others have reported germline genetic variations as risk factors for such skin lesions. The role of copy number variation (CNV) in the germline DNA in this regard is unknown. METHODS: From a large prospectively followed-up cohort, exposed to arsenic, we randomly selected 2171 subjects without arsenic-induced skin lesions at enrollment and genotyped their whole blood DNA samples on Illumina Cyto12v2.1 SNP chips to generate DNA copy number. Participants were followed up every 2 years for a total of 8 years, especially for the development of skin lesions. In Cox regression models, each CNV segment was used as a predictor, accounting for other potential covariates, for incidence of skin lesions. RESULT: The presence of genomic deletion(s) in a number of genes (OR5J2, GOLGA6L7P, APBA2, GALNTL5, VN1R31P, PHKG1P2, SGCZ, ZNF658) and lincRNA genes (RP11-76I14.1, CTC-535 M15.2, RP11-73B2.2) were associated with higher risk [HR between 1.67 (CI 1.3-2.1) and 2.15 (CI 1.5-2.9) for different CNVs] for development of skin lesions independent of gender, age, and arsenic exposure. Some deletions had stronger effect in a specific gender (ZNF658 in males, SGCZ in females) and some had stronger effect in higher arsenic exposure (lincRNA CTD-3179P9.1) suggesting a possible gene-environment interaction. CONCLUSION: This first genome-wide CNV study in a prospectively followed-up large cohort, exposed to arsenic, suggests that DNA deletion in several genes and lincRNA genes may predispose an individual to a higher risk of development of arsenic-induced skin lesions.