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Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence – a vulnerable time for developing mental health difficulties. This study examines how annual average PM2.5and NO2exposure at ages 9-10 years relates to internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at baseline and annually for two follow-up sessions for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Overall, the pollution effects moderated the main effects of age with higher levels of PM2.5and NO2leading to an even greater likelihood of having no behavioral problems (i.e., score of zero) with age over time, as well as fewer problems when problems are present as the child ages. Albeit this was on the order equal to or less than a 1-point change. Thus, one year of annual exposure at 9-10 years is linked with very small change in emotional behaviors in early adolescence, which may be of little clinical relevance.

Supplementary Data from Transcriptomic Response to Calcium in Normal Colon Organoids is Impacted by Colon Location and Sex

Supplementary Table 1. Association between 139 dietary nutrients and ethnicity (n = 1829)*. Supplementary Table 2. The top ten nutrient measurements in correlation with principal component 2 in either positive or negative direction. Supplementary Table 3. Association between dietary folate intake and risk for methylation (n = 1426)*. Supplementary Table 4. Individual nutrients associated with risk for methylation (n = 1426)*. Supplementary Figure S1. Principal component analysis was conducted based on 101 nutrients with no missing values in 1829 cohort members and identified four principal components that explained 59% of the total variance of nutrients with each one explaining >5% of the variance. This figure included the top nine principal components with each one explaining >2% of the variance. PC = principal component.

Supplementary Figure from Transcriptomic Response to Calcium in Normal Colon Organoids is Impacted by Colon Location and Sex

Lung cancer gene methylation detected in sputum assesses field cancerization and predicts lung cancer incidence. Hispanic smokers have higher lung cancer susceptibility compared with non-Hispanic whites (NHW). We aimed to identify novel dietary nutrients affecting lung cancer gene methylation and determine the degree of ethnic disparity in methylation explained by diet. Dietary intakes of 139 nutrients were assessed using a validated Harvard food frequency questionnaire in 327 Hispanics and 1,502 NHWs from the Lovelace Smokers Cohort. Promoter methylation of 12 lung cancer genes was assessed in sputum DNA. A global association was identified between dietary intake and gene methylation (Ppermutation = 0.003). Seventeen nutrient measurements were identified with magnitude of association with methylation greater than that seen for folate. A stepwise approach identified B12, manganese, sodium, and saturated fat as the minimally correlated set of nutrients whose optimal intakes could reduce the methylation by 36% (Ppermutation < 0.001). Six protective nutrients included vitamin D, B12, manganese, magnesium, niacin, and folate. Approximately 42% of ethnic disparity in methylation was explained by insufficient intake of protective nutrients in Hispanics compared with NHWs. Functional validation of protective nutrients showed an enhanced DNA repair capacity toward double-strand DNA breaks, a mechanistic biomarker strongly linked to acquisition of lung cancer gene methylation in smokers. Dietary intake is a major modifiable factor for preventing promoter methylation of lung cancer genes in smokers' lungs. Complex dietary supplements could be developed on the basis of these protective nutrients for lung cancer chemoprevention in smokers. Hispanic smokers may benefit the most from this complex for reducing their lung cancer susceptibility. Cancer Prev Res; 11(2); 93–102. ©2017 AACR.

Biomarkers such as exhaled nitric oxide (FeNO), a marker of airway inflammation, have applications in the study of chronic respiratory disease where longitudinal studies of within-participant changes in the biomarker are particularly relevant. A cutting-edge approach to assessing FeNO, called multiple flow FeNO, repeatedly assesses FeNO across a range of expiratory flow rates at a single visit and combines these data with a deterministic model of lower respiratory tract NO to estimate parameters quantifying airway wall and alveolar NO sources. Previous methodological work for multiple flow FeNO has focused on methods for data from a single participant or from cross-sectional studies. Performance of existingad hoctwo-stage methods for longitudinal multiple flow FeNO in cohort or panel studies has not been evaluated. In this paper, we present a novel longitudinal extension to a unified hierarchical Bayesian (L_U_HB) model relating longitudinally assessed multiple flow FeNO to covariates. In several simulation study scenarios, we compare the L_U_HB method to other unified and two-stage frequentist methods. In general, L_U_HB produced unbiased estimates, had good power, and its performance was not sensitive to the magnitude of the association with a covariate and correlations between NO parameters. In an application relating height to longitudinal multiple flow FeNO in schoolchildren without asthma, unified analysis methods estimated positive, statistically significant associations of height with airway and alveolar NO concentrations and negative associations with airway wall diffusivity while estimates from two-stage methods were smaller in magnitude and sometimes non-significant.

Diabetes is an established risk factor for colorectal cancer; however, the mechanisms underlying this relationship are not fully understood and the role of genetic variation is unclear. We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes and joint testing of Gxdiabetes, G-colorectal cancer association and/or G-diabetes correlation (2,3-degrees of freedom joint tests; d.f.). Based on the joint tests, variant rs3802177 inSLC30A8(p-value3-d.f.:5.46×10−11; regulates phosphorylation of the insulin receptor and phosphatidylinositol-3 kinase activity) and rs9526201 inLRCH1(p-value2-d.f.:7.84×10−09; regulates T cell migration and Natural Killer Cell cytotoxicity) were associated with colorectal cancer. These results suggest that variation in genes related to insulin signalling and immune function may modify the association of diabetes with colorectal cancer and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.

Although food allergies are considered common, relatively little is known about disparities in food allergy by race in the United States.To evaluate differences in reported food allergy and food-associated anaphylaxis among individuals enrolled in a longitudinal cohort study from metropolitan Detroit, Michigan.Participants in the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) were asked about food allergies, including the inciting food and associated symptoms. Individuals were considered to have food-associated anaphylaxis if symptoms coincided with established clinical criteria. Logistic regression was used to assess whether race difference persisted after adjusting for and stratifying by potential confounders. African genetic ancestry was individually estimated among African American SAPPHIRE participants to assess whether ancestry was associated with food allergy.Within the SAPPHIRE cohort, African American participants were significantly more likely to report food allergy (26.1% vs 17%; P = 3.47 × 10Compared with European Americans, African Americans appear to be at higher risk for developing food allergy and food-associated anaphylaxis, particularly with regard to seafood allergy. The lack of association with genetic ancestry suggests that socioenvironmental determinants may play a role in these disparities.

Two-step tests for gene-environment (G × E) interactions exploit marginal SNP effects to improve the power of a genome-wide interaction scan (GWIS). They combine a screening step based on marginal effects used to ‘bin’ SNPs for weighted hypothesis testing in the second step to deliver greater power over single-step tests while preserving the genome-wide type I error. However, the presence of many SNPs with detectable marginal effects on the trait of interest can reduce power by ‘displacing’ true interactions with weaker marginal effects and by adding to the number of tests that need to be corrected for multiple testing. We introduce a new significance-based allocation into bins for step 2 G × E testing that overcomes the displacement issue and propose a computationally efficient approach to account for multiple testing within bins. Simulation results demonstrate that these simple improvements can provide substantially greater power than current methods under several scenarios. An application to a multi-study collaboration for understanding colorectal cancer (CRC) reveals a G×Sex interaction located within the SMAD7 gene.

Though both genetic and lifestyle factors are known to influence cardiometabolic outcomes, less attention has been given to whether lifestyle exposures can alter the association between a genetic variant and these outcomes. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium’s Gene-Lifestyle Interactions Working Group has recently published investigations of genome-wide gene-environment interactions in large multi-ancestry meta-analyses with a focus on cigarette smoking and alcohol consumption as lifestyle factors and blood pressure and serum lipids as outcomes. Further description of the biological mechanisms underlying these statistical interactions would represent a significant advance in our understanding of gene-environment interactions, yet accessing and harmonizing individual-level genetic and ‘omics data is challenging. Here, we demonstrate the coordinated use of summary-level data for gene-lifestyle interaction associations on up to 600,000 individuals, differential methylation data, and gene expression data for the characterization and prioritization of loci for future follow-up analyses. Using this approach, we identify 48 genes for which there are multiple sources of functional support for the identified gene-lifestyle interaction. We also identified five genes for which differential expression was observed by the same lifestyle factor for which a gene-lifestyle interaction was found. For instance, in gene-lifestyle interaction analysis, the T allele of rs6490056 (ALDH2) was associated with higher systolic blood pressure, and a larger effect was observed in smokers compared to non-smokers. In gene expression studies, this allele is associated with decreased expression of ALDH2, which is part of a major oxidative pathway. Other results show increased expression of ALDH2 among smokers. Oxidative stress is known to contribute to worsening blood pressure. Together these data support the hypothesis that rs6490056 reduces expression of ALDH2, which raises oxidative stress, leading to an increase in blood pressure, with a stronger effect among smokers, in whom the burden of oxidative stress is greater. Other genes for which the aggregation of data types suggest a potential mechanism include: GCNT4×current smoking (HDL), PTPRZ1×ever-smoking (HDL), SYN2×current smoking (pulse pressure), and TMEM116×ever-smoking (mean arterial pressure). This work demonstrates the utility of careful curation of summary-level data from a variety of sources to prioritize gene-lifestyle interaction loci for follow-up analyses.

Lung function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry GWAS meta-analysis of lung function to date, comprising 580,869 participants, 1020 independent association signals identified 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score (GRS) showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies (PheWAS) for selected associated variants, and trait and pathway-specific GRS to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

Motivation While gene–environment (GxE) interactions contribute importantly to many different phenotypes, detecting such interactions requires well-powered studies and has proven difficult. To address this, we combine two approaches to improve GxE power: simultaneously evaluating multiple phenotypes and using a two-step analysis approach. Previous work shows that the power to identify a main genetic effect can be improved by simultaneously analyzing multiple related phenotypes. For a univariate phenotype, two-step methods produce higher power for detecting a GxE interaction compared to single step analysis. Therefore, we propose a two-step approach to test for an overall GxE effect for multiple phenotypes. Results Using simulations we demonstrate that, when more than one phenotype has GxE effect (i.e. GxE pleiotropy), our approach offers substantial gain in power (18–43%) to detect an aggregate-level GxE effect for a multivariate phenotype compared to an analogous two-step method to identify GxE effect for a univariate phenotype. We applied the proposed approach to simultaneously analyze three lipids, LDL, HDL and Triglyceride with the frequency of alcohol consumption as environmental factor in the UK Biobank. The method identified two loci with an overall GxE effect on the vector of lipids, one of which was missed by the competing approaches. Availability and implementation We provide an R package MPGE implementing the proposed approach which is available from CRAN: https://cran.r-project.org/web/packages/MPGE/index.html Supplementary information Supplementary data are available at Bioinformatics online.

Purpose The aim of the study was to determine the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in a university student population. Methods This was a cross-sectional survey study based on the World Health Organization population-based seroepidemiological investigational protocol for SARS-CoV-2 conducted between April 29, 2020, and May 8, 2020, examining SARS-CoV-2 antibody prevalence among 790 university students in Los Angeles, CA. Participants completed a questionnaire on potential risk factors before blood sampling. Samples were analyzed using the EUROIMMUN Anti-SARS-CoV-2 ELISA (IgG) for the qualitative detection of IgG class antibodies to SARS-CoV-2 in human serum or plasma. Results The estimated prevalence of SARS-CoV-2 antibody was 4.0% (3.0%, 5.1%). Factors associated with having a positive test included history of anosmia and/or loss of taste (95% CI: 1.4–9.6). A history of respiratory symptoms, with or without fever, was not associated with a positive antibody test. Conclusions Prevalence of SARS-CoV-2 antibodies in the undergraduate and graduate student university population was similar to community prevalence.

Rationale: Although elevated air pollution exposure impairs lung-function development in childhood, it remains a challenge to use this information to estimate the potential public health benefits of air pollution interventions in exposed populations. Objectives: Apply G-computation to estimate hypothetical effects of several realistic scenarios for future air pollution reductions on lung growth. Methods: Mixed-effects linear regression was used to estimate FEV(1) and FVC from age 11 to 15 years in 2,120 adolescents across 3 cohorts (1993–2001, 1997–2004, and 2007–2011). Models included regional pollutants (nitrogen dioxide [NO(2)] or particulate matter with an aerodynamic diameter ≤2.5 μm [PM(2.5)]) and other important covariates. Using G-computation, a causal inference–based method, we then estimated changes in mean lung growth in our population for hypothetical interventions on either NO(2) or PM(2.5). Confidence intervals (CIs) were computed by bootstrapping (N = 1,000). Measurements and Main Results: Compared with the effects of exposure from observed NO(2) concentrations during the study period, had communities remained at 1994 to 1997 NO(2) levels, FEV(1) and FVC growth were estimated to have been reduced by 2.7% (95% CI, −3.6 to −1.8) and 4.2% (95% CI, −5.2 to −3.4), respectively. If NO(2) concentrations had been reduced by 30%, we estimated a 4.4% increase in FEV(1) growth (95% CI, 2.8–5.9) and a 7.1% increase in FVC growth (95% CI, 5.7–8.6). Comparable results were observed for PM(2.5) interventions. Conclusions: We estimated that substantial increases in lung function would occur as a result of interventions that reduce NO(2) or PM(2.5) concentrations. These findings provide a quantification of potential health benefits of air quality improvement.

Defined by their genetic profile, individuals may exhibit differential clinical outcomes due to an environmental exposure. Identifying subgroups based on specific exposure-modifying genes can lead to targeted interventions and focused studies. Genome-wide interaction scans (GWIS) can be performed to identify such genes, but these scans typically suffer from low power due to the large multiple testing burden. We provide a novel framework for powerful two-step hypothesis tests for GWIS with a time-to-event endpoint under the Cox proportional hazards model. In the Cox regression setting, we develop an approach that prioritizes genes for Step-2 G × E testing based on a carefully constructed Step-1 screening procedure. Simulation results demonstrate this two-step approach can lead to substantially higher power for identifying gene-environment ( G × E ) interactions compared to the standard GWIS while preserving the family-wise error rate over a range of scenarios. In a taxane-anthracycline chemotherapy study for breast cancer patients, the two-step approach identifies several gene expression by treatment interactions that would not be detected using the standard GWIS.

Gene-lifestyle interaction analyses have identified genetic variants whose effect on cardiovascular risk-raising traits is modified by alcohol consumption and smoking behavior. The biological mechanisms of these interactions remain largely unknown, but may involve epigenetic modification linked to perturbation of gene expression. Diverse, individual-level datasets including genotypes, methylation and gene expression conditional on lifestyle factors, are ideally suited to study this hypothesis, yet are often unavailable for large numbers of individuals. Summary-level data, such as effect sizes of genetic variants on a phenotype, present an opportunity for multi-omic study of the biological mechanisms underlying gene-lifestyle interactions. We propose a method that unifies disparate, publicly available summary datasets to build mechanistic hypotheses in models of smoking behavior and alcohol consumption with blood lipid levels and blood pressure measures. Of 897 observed genetic interactions, discovered through genome-wide analysis in diverse multi-ethnic cohorts, 48 were identified with lifestyle-related differentially methylated sites within close proximity and linked to target genes. Smoking behavior and blood lipids account for 37 and 28 of these signals respectively. Five genes also showed differential expression conditional on lifestyle factors within these loci with mechanisms supported in the literature. Our analysis demonstrates the utility of summary data in characterizing observed gene-lifestyle interactions and prioritizes genetic loci for experimental follow up related to blood lipids, blood pressure, and cigarette smoking. We show concordance between multiple trait-or exposure-related associations from diverse assays, driving hypothesis generation for better understanding gene-lifestyle interactions.

BackgroundThe role of race/ethnicity in genetic predisposition of early-onset cancers can be estimated by comparing family-based cancer concordance rates among ethnic groups.MethodsWe used linked California health registries to evaluate the relative cancer risks for first degree relatives of patients diagnosed between ages 0-26, and the relative risks of developing distinct second primary malignancies (SPMs). From 1989-2015, we identified 29,631 cancer patients and 62,863 healthy family members. We calculated the standardized incident ratios (SIRs) of early-onset primary cancers diagnosed in proband siblings and mothers, as well as SPMs detected among early-onset patients. Analyses were stratified by self-identified race/ethnicity.ResultsGiven probands with cancer, there were increased relative risks of any cancer for siblings and mothers [SIR=3.32;95% confidence interval (CI):2.85-3.85)] and of SPMs (SIR=7.27;95%CI:6.56-8.03). Higher relative risk of any cancer in siblings and mothers given a proband with solid cancer (PConclusionsThe data support a need for increased attention to the genetics of early-onset cancer predisposition and environmental factors in race/ethnic minority families in the US.FundingThis work was supported by the V Foundation for funding this work (Grant FP067172).Key MessagesWe identified 29 631 cancer patients and their 62 863 healthy family members in California from 1989 to 2015.The risk of early-onset cancer in siblings and mothers was elevated by having a proband with cancer in the same family.The relative risk of early-onset cancers given a proband with solid cancer was higher for Latinos and Blacks when compared to non-Latino Whites.

BackgroundAsthma is a common but complex disease with racial/ethnic differences in prevalence, morbidity, and response to therapies.ObjectiveWe sought to perform an analysis of genetic ancestry to identify new loci that contribute to asthma susceptibility.MethodsWe leveraged the mixed ancestry of 3902 Latinos and performed an admixture mapping meta-analysis for asthma susceptibility. We replicated associations in an independent study of 3774 Latinos, performed targeted sequencing for fine mapping, and tested for disease correlations with gene expression in the whole blood of more than 500 subjects from 3 racial/ethnic groups.ResultsWe identified a genome-wide significant admixture mapping peak at 18q21 in Latinos (P=6.8×10-6), where Native American ancestry was associated with increased risk of asthma (odds ratio [OR], 1.20; 95% CI, 1.07-1.34; P=.002) and European ancestry was associated with protection (OR, 0.86; 95% CI, 0.77-0.96; P=.008). Our findings were replicated in an independent childhood asthma study in Latinos (P=5.3×10-3, combined P=2.6×10-7). Fine mapping of 18q21 in 1978 Latinos identified a significant association with multiple variants 5' of SMAD family member 2 (SMAD2) in Mexicans, whereas a single rare variant in the same window was the top association in Puerto Ricans. Low versus high SMAD2 blood expression was correlated with case status (13.4% lower expression; OR, 3.93; 95% CI, 2.12-7.28; P&nbsp

Gene-environment (G × E) interaction is important for many complex traits. In a case-control study of a disease trait, logistic regression is the standard approach used to model disease as a function of a gene (G), an environmental factor (E), G × E interaction, and adjustment covariates. We propose an alternative model with G as the outcome and show how it provides a unified framework for obtaining results from all of the common G × E tests. These include the 1–degree-of-freedom (df) test of G × E interaction, the 2-df joint test of G and G × E, the case-only and empirical Bayes tests, and several 2-step tests. In the context of this unified model, we propose a novel 3-df test and demonstrate that it provides robust power across a wide range of underlying G × E interaction models. We demonstrate the 3-df test in a genome-wide scan of G × sex interaction for childhood asthma using data from the Children’s Health Study (Southern California, 1993–2001). This scan identified a strong G × sex interaction at the phosphodiesterase gene 4D locus (PDE4D), a known asthma-related locus, with a strong effect in males (per-allele odds ratio = 1.70; P = 3.8 × 10(−8)) and virtually no effect in females. We describe a software program, G×EScan (University of Southern California, Los Angeles, California), which can be used to fit standard and unified models for genome-wide G × E studies.

To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P, Reporting Summary. Further information on experimental design is available in the Life Sciences Reporting Summary linked to this article.

ObjectiveAn understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for sporadic CRC differs by anatomical subsite of the primary tumor has not been examined.DesignTo identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48,214 CRC cases and 64,159 controls of European ancestry. We characterized effect heterogeneity at CRC risk loci using multinomial modeling.ResultsWe identified 13 loci that reached genome-wide significance (P−8) and that were not reported by previous GWAS for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer.ConclusionGenetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumor.Significance of this studyWhat is already known about this subject?Heterogeneity among colorectal cancer (CRC) tumors originating at different locations of the colorectum has been revealed in somatic genomes, epigenomes, and transcriptomes, and in some established environmental risk factors for CRC.Genome-wide association studies (GWAS) have identified over 100 genetic variants for overall CRC risk; however, a comprehensive analysis of the extent to which genetic risk factors differ by the anatomical sublocation of the primary tumor is lacking.What are the new findings?In this large consortium-based study, we analyzed clinical and genome-wide genotype data of 112,373 CRC cases and controls of European ancestry to comprehensively examine whether CRC case subgroups defined by anatomical sublocation have distinct germline genetic etiologies.We discovered 13 new loci at genome-wide significance (P−8) that were specific to certain anatomical sublocations and that were not reported by previous GWAS for overall CRC risk; multiple lines of evidence support strong candidate target genes at several of these loci, including PTGER3, LCT, MLH1, CDX1, KLF14, PYGL, BCL11B, and BMP7.Systematic heterogeneity analysis of genetic risk variants for CRC identified thus far, revealed that the genetic architectures of proximal and distal CRC are partly distinct.Taken together, our results further support the idea that tumors arising in different anatomical sublocations of the colorectum may have distinct etiologies.How might it impact on clinical practice in the foreseeable future?Our results provide an informative resource for understanding the differential role that genes and pathways may play in the mechanisms of proximal and distal CRC carcinogenesis.The new insights into the etiologies of proximal and distal CRC may inform the development of new precision prevention strategies, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention.Our findings suggest that future studies of etiological risk factors for CRC and molecular mechanisms of carcinogenesis should take into consideration the anatomical sublocation of the colorectal tumor.

Additional file 1.

Rationale: The 17q12-21.1 locus is one of the most highly replicated genetic associations with asthma. Individuals of African descent have lower linkage disequilibrium in this region, which could facilitate identifying causal variants.Objectives: To identify functional variants at 17q12-21.1 associated with early-onset asthma among African American individuals.Methods: We evaluated African American participants from SAPPHIRE (Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity) (n = 1,940), SAGE II (Study of African Americans, Asthma, Genes and Environment) (n = 885), and GCPD-A (Study of the Genetic Causes of Complex Pediatric Disorders-Asthma) (n = 2,805). Associations with asthma onset at ages under 5 years were meta-analyzed across cohorts. The lead signal was reevaluated considering haplotypes informed by genetic ancestry (i.e., African vs. European). Both an expression-quantitative trait locus analysis and a phenome-wide association study were performed on the lead variant.Measurements and Main Results: The meta-analyzed results from SAPPHIRE, SAGE II, and the GCPD-A identified rs11078928 as the top association for early-onset asthma. A haplotype analysis suggested that the asthma association partitioned most closely with the rs11078928 genotype. Genetic ancestry did not appear to influence the effect of this variant. In the expression-quantitative trait locus analysis, rs11078928 was related to alternative splicing of GSDMB (gasdermin-B) transcripts. The phenome-wide association study of rs11078928 suggested that this variant was predominantly associated with asthma and asthma-associated symptoms.Conclusions: A splice-acceptor polymorphism appears to be a causal variant for asthma at the 17q12-21.1 locus. This variant appears to have the same magnitude of effect in individuals of African and European descent.

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups using 1 degree of freedom (1df) interaction and 2df joint tests. Primary multi-ancestry analyses in 62,969 individuals in stage 1 identified 3 novel loci that were replicated in an additional 59,296 individuals in stage 2, including rs7955964 (FIGNL2/ANKRD33) showing significant 1df interactions with long sleep duration and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) showing significant 1df interactions with short sleep duration (Pint < 5×10−8). Secondary ancestry-specific two-stage analyses and combined stage 1 and 2 analyses additionally identified 23 novel loci that need external replication, including 3 and 5 loci showing significant 1df interactions with long and short sleep duration, respectively (Pint < 5×10−8). Multiple genes mapped to our 26 novel loci have known functions in sleep-wake regulation, nervous and cardiometabolic systems. We also identified new gene by long sleep interactions near five known BP loci (≤1Mb) including NME7, FAM208A, MKLN1, CEP164, and RGL3/ELAVL3 (Pint < 5×10−8). This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.

Background Body mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology. Methods To improve statistical power and interpretation for gene‐environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype‐Tissue Expression Project for all genes with heritability ≥1%. We used a mixed‐effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI‐CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR, Novel findings of this study include: the genetically predicted expressions of FOXA1, PSMC5 and CD33 modified the association of BMI on CRC risk for men; KIAA0753 and SCN1B modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes. These findings provide support for potential new biological insights that could help in understanding the underlying mechanisms of BMI and diabetes on CRC.

Author(s): Cocco, Maxwell P; White, Evan; Xiao, Shujie; Hu, Donglei; Mak, Angel; Sleiman, Patrick; Yang, Mao; Bobbitt, Kevin R; Gui, Hongsheng; Levin, Albert M; Hochstadt, Samantha; Whitehouse, Kyle; Rynkowski, Dean; Barczak, Andrea J; Abecasis, Goncalo; Blackwell, Thomas W; Kang, Hyun Min; Nickerson, Deborah A; Germer, Soren; Ding, Jun; Lanfear, David E; Gilliland, Frank; Gauderman, W James; Kumar, Rajesh; Erle, David J; Martinez, Fernando; Hakonarson, Hakon; Burchard, Esteban G; Williams, L Keoki | Abstract: BackgroundMitochondria support critical cellular functions, such as energy production through oxidative phosphorylation, regulation of reactive oxygen species, apoptosis, and calcium homeostasis.ObjectiveGiven the heightened level of cellular activity in patients with asthma, we sought to determine whether mitochondrial DNA (mtDNA) copy number measured in peripheral blood differed between individuals with and without asthma.MethodsWhole genome sequence data was generated as part of the Trans-Omics for Precision Medicine (TOPMed) Program on participants from the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) and the Study of African Americans, Asthma, Genes, a Environment II (SAGE II). We restricted our analysis to individuals who self-identified as African American (3,651 asthma cases and 1,344 controls). Mitochondrial copy number was estimated using the sequencing read depth ratio for the mitochondrial and nuclear genomes. Respiratory complex expression was assessed using RNA-sequencing.ResultsAverage mitochondrial copy number was significantly higher among individuals with asthma when compared with controls (SAPPHIRE: 218.60 vs. 200.47, Pl0.001; SAGE II: 235.99 vs. 223.07, Pl0.001). Asthma status was significantly associated with mitochondrial copy number after accounting for potential explanatory variables, such as participant age, sex, leukocyte counts, and mitochondrial haplogroup. Despite the consistent relationship between asthma status and mitochondrial copy number, the latter was not associated with time-to-exacerbation or patient-reported asthma control. Mitochondrial respiratory complex gene expression was disproportionately lower in individuals with asthma when compared with individuals without asthma and other protein-encoding genes.ConclusionsWe observed a robust association between asthma and higher mitochondrial copy number. Asthma having an effect on mitochondria function was also supported by lower respiratory complex gene expression in this group.

Objective To assess associations between age-related macular degeneration (AMD) and multiple factors comprising a conceptual model of AMD risk in a population of Chinese Americans, and to draw comparisons with a similar risk assessment of a Latino population. Design A cross-sectional population-based study. Participants We enrolled 4582 Chinese Americans aged ≥50 residing in Monterey Park, California. Methods Participants completed a comprehensive eye examination, including stereoscopic fundus photography and ocular biometric measurements. Fundus images were graded using a modified version of the Wisconsin Age-Related Maculopathy Grading System. Main Outcomes and Measures Odds ratios for factors significantly modifying the risk of AMD and its related retinal lesions. Results Of the eligible participants, 4172 (72%) had fundus photographs gradable for AMD. Early AMD was present in 375 eyes (4.6%), and late AMD was present in 17 (0.2%). Shorter axial length, male sex, older age, and family history of AMD were identified as independent risk factors for prevalent AMD and its characteristic retinal lesions using a conceptual model of potential AMD risk factors. Of 4 AMD risk factors identified for Latinos, 3 (older age, male sex, shorter axial length) overlapped with those identified for Chinese Americans, with an association similar in magnitude and direction. Lower levels of education were a risk factor specific to Latinos. Based on a multivariable logistic regression model, the predicted probability of early AMD was 31% lower among Chinese Americans relative to Latinos (95% confidence interval [CI], 17%–43%). Chinese Americans also had statistically significantly lower odds of any AMD and 2 types of early retinal lesions symptomatic of AMD. Conclusions Factors associated with prevalent AMD are similar for Chinese Americans and Latinos. Chinese Americans who were older, were male, had a family history of AMD, and had a shorter axial length were at an increased risk for AMD compared with those without these risk factors. We observed a significantly lower predicted prevalence of AMD among Chinese Americans compared with Latinos, even after controlling for all relevant covariates, suggesting that additional genetic or lifestyle differences may play an important role in determining AMD risk.

Objective To identify factors associated with prevalent diabetic retinopathy (DR) among Chinese American adults with type 2 diabetes mellitus (T2DM), and to compare these factors to ones previously described for a population-based sample of Latinos with a higher DR prevalence. Design Population-based cross-sectional study. Participants Total of 4582 Chinese Americans aged 50 or older residing in Monterey Park, California. Methods Participants completed an in-home questionnaire on sociodemographic status and medical history, and a comprehensive clinical eye examination, using the same protocol implemented in the Los Angeles Latino Eye Study. Fundus photographs from 7 Early Treatment Diabetic Retinopathy Study fields were graded in a masked manner using a modified Airlie House grading system to assess presence and severity of DR. Logistic regression analyses based on a conceptual model of DR risk identified factors associated with prevalent DR. Main Outcome Measures Odds ratios (ORs) and 95% confidence intervals (CIs) for factors associated with DR and vision-threatening DR (VTDR). Results In total, 238 participants were diagnosed with any DR; 27 of these were classified as having VTDR. Both any DR and VTDR showed statistically significant positive associations with T2DM duration (OR5–9 years = 1.24; OR10–14 years = 2.07; OR15+years = 3.99), glycosylated hemoglobin (HbA1c) (OR6.5%–6.9% = 1.33; OR7%–7.9% = 1.86; OR8%+ = 3.22), systolic blood pressure (SBP) (ORper 10 mmHg+ = 1.19), and insulin treatment (ORinsulin+ = 2.44). For VTDR, we also found novel associations with antihypertensive drugs (OR = 0.18; 95% CI = 0.06–0.61) and statins (OR: 4.96; 95% CI: 1.60–16.41). Chinese Americans and Latinos had a nearly identical DR probability based on HbA1c and SBP. However, Latinos had a higher DR probability at every year of duration of T2DM (≥5 years). Conclusions Although we observed an overall lower DR prevalence in Chinese Americans than in Latinos (35.8% of individuals with TD2M among Chinese Americans vs. 42.0% among Latinos), our data indicate that the impact of increasing HbA1c and SBP on DR probability is incrementally the same in both populations. However, increasing T2DM duration is associated with higher DR probability in Latinos than in Chinese Americans, even after controlling for other known predictors. Novel factors associated with VTDR include antihypertensive drugs and statins. However, to determine whether these drugs impact VTDR susceptibility, we need longitudinal data and more cases.

Lung cancer gene methylation detected in sputum assesses field cancerization and predicts lung cancer incidence. Hispanic smokers have higher lung cancer susceptibility compared with non-Hispanic whites (NHW). We aimed to identify novel dietary nutrients affecting lung cancer gene methylation and determine the degree of ethnic disparity in methylation explained by diet. Dietary intakes of 139 nutrients were assessed using a validated Harvard food frequency questionnaire in 327 Hispanics and 1,502 NHWs from the Lovelace Smokers Cohort. Promoter methylation of 12 lung cancer genes was assessed in sputum DNA. A global association was identified between dietary intake and gene methylation (Ppermutation = 0.003). Seventeen nutrient measurements were identified with magnitude of association with methylation greater than that seen for folate. A stepwise approach identified B12, manganese, sodium, and saturated fat as the minimally correlated set of nutrients whose optimal intakes could reduce the methylation by 36% (Ppermutation < 0.001). Six protective nutrients included vitamin D, B12, manganese, magnesium, niacin, and folate. Approximately 42% of ethnic disparity in methylation was explained by insufficient intake of protective nutrients in Hispanics compared with NHWs. Functional validation of protective nutrients showed an enhanced DNA repair capacity toward double-strand DNA breaks, a mechanistic biomarker strongly linked to acquisition of lung cancer gene methylation in smokers. Dietary intake is a major modifiable factor for preventing promoter methylation of lung cancer genes in smokers' lungs. Complex dietary supplements could be developed on the basis of these protective nutrients for lung cancer chemoprevention in smokers. Hispanic smokers may benefit the most from this complex for reducing their lung cancer susceptibility. Cancer Prev Res; 11(2); 93–102. ©2017 AACR.

Nonsteroidal anti-inflammatory drugs (NSAIDs) are consistently shown in epidemiological and clinical studies to exert chemo-preventive effects on colorectal cancer (CRC). Specifically, aspirin binds irreversibly to COX1/2 enzymes, attenuating pro-inflammatory signaling pathways, but it can also exert protective effects via Wnt-β-catenin signaling, circulating inflammatory cytokines, and platelet mediated mechanisms. In this analysis, we conduct genome-wide interaction scans on a large CRC dataset to expand upon previous work and identify novel G x NSAIDs interactions. We pooled epidemiological and imputed genetic data from 72,667 individuals (41,876 controls, and 30,806 cases) of European descent from 31 studies. Genotypes were imputed to the Haplotype Reference Consortium panel. Regular use of aspirin and combined aspirin/non-aspirin NSAIDs (henceforth termed ‘nsaidsALL') were harmonized across studies and measured as ever/never at reference time. We employed several statistical methods in our GWIS: traditional logistic regression with an interaction term, case-only analyses, joint tests (2df/3df), two-step methods. We also assessed interactions between CRC polygenic risk scores (PRS) and aspirin/nsaidsALL on additive and multiplicative scales. PRS was modeled categorically (quartiles) and continuously as a per 1 SD increase from the minimum value. All models were adjusted for age, sex, study, and ancestry. Aspirin (OR=0.789, 95% CI=0.753-0.826) and nsaidsALL (OR=0.760; 95% CI=0.726-0.793) use were inversely associated with CRC risk. Using standard logistic regression, we identified a genome-wide significant interaction between rs72833769 (chromosome 6 intergenic region upstream of PHACTR1) and both aspirin and nsaidsALL (p = 4.0e-09, p = 1.3e-08, respectively). An additional genome-wide interaction locus was identified for nsaidsALL only, on rs35118762 (p = 2.2e-08), located in the Major Histocompatibility Complex region and in close linkage with a previously identified marginal GWAS hit (rs9271695). We identified another region of interest using two-step methods tagged by SNP rs350047 (aspirin pgxe = 1.1e-05, nsaidsALL pgxe = 4.4e-05). This region also coincides with another previously identified marginal GWAS hit (rs12514517), and is notable for being upstream of PTGER4, an important receptor for aspirin mediated inflammatory response signaling. For interactions with PRS, we observed a significant super-additive interaction for both aspirin (RERI=0.102, p=7e-08) and nsaidsALL use (RERI=0.132, p=4.6e-12). Results were similar when modeling PRS categorically. There were no multiplicative scale interactions between PRS and any NSAID use. GWIS for aspirin and nsaidsALL use identified several loci of interest that warrant follow-up in functional studies. Citation Format: Andre E. Kim, David A. Drew, Yi Lin, Conghui Qu, John P. Morrison, Stephanie Bien, Victor Moreno, Graham Casey, Ulrike Peters, Andrew T. Chan, W James Gauderman. NSAIDs and colorectal cancer risk: Results from genome-wide interaction scans [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 820.

Background: Observational studies indicate that calcium, a micronutrient involved in numerous cell-signaling cascades, may protect against colon cancer. Stratified analyses suggest the protective effect of calcium may depend on sex and anatomic subsite, but these hypotheses have been difficult to test experimentally. Here, we employ human-derived normal colon 3D organoids as a model of the healthy colon crypt to interrogate the effect of calcium exposure on gene expression and the effect of donor sex and biopsy anatomic subsite on the response to calcium. Methods: A total of 39 3D colon organoid lines derived from colon biopsies (22 proximal, 17 distal) obtained from unrelated subjects (21 female, 18 male) during screening colonoscopy were grown under low (1.7 mM) calcium conditions, and a matching set of the same lines were grown under high (5.0 mM) calcium conditions. After 72 hours, total RNA was extracted from organoid lines, libraries were prepared with poly-A selection, and bulk RNA-sequencing was used to measure gene expression. DNA was extracted from the same lines and genotyped using the OncoArray 500K beadchip. Missing genotypes were imputed to the TOPMed reference panel using the TOPMed Imputation Server. Polygenic risk scores for colorectal cancer were calculated for each organoid line using Plink and 135 of 141 genome-wide significant SNPs associated with colorectal cancer in recent genome-wide association studies. Relative expression between low and high calcium conditions was tested using generalized linear models as implemented in DESeq2. Functional enrichment of gene ontologies among differentially expressed genes was performed with ToppFun. The effects of donor sex, biopsy subsite, and organoid polygenic risk score on response to calcium were tested using single and multiple linear regression as implemented in the base R lm function. Results: Exposure to calcium induced differential expression of 767 genes with a false discovery rate of 5%. Differentially expressed genes were enriched for biological processes including extracellular structure organization (Bonferroni p=1.6E-3) and positive regulation of apoptosis (Bonferroni p=2.2E-2). Although stratified analyses demonstrated more differentially expressed genes in 3D colon organoids derived from male subjects, no statistically significant effect of sex, subsite, or polygenic risk score on response to calcium was observed. Conclusion: We tested the effect of calcium exposure on gene expression in human-derived normal colon 3D organoids and found that calcium modulated processes related to differentiation and apoptosis, but the response to calcium was not affected by sex, anatomic subsite, or polygenic risk score. Citation Format: Christopher H. Dampier, Matthew Devall, Jennifer Bryant, Stephen D. Eaton, Jeroen R. Huyghe, Andre E. Kim, Virginia Diez-Obrero, Franzel J. van Duijnhoven, Duncan C. Thomas, Steven M. Powell, W James Gauderman, Ulrike Peters, Graham Casey. Calcium modulates apoptosis and differentiation in human normal colon 3D organoids irrespective of donor sex and biopsy site [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2578.

Background: Type 2 diabetes mellitus (T2D) is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship are unclear and it is not known if the association is modified by genetic variants. To provide insights into the molecular pathways potentially linking diabetes and colorectal cancer, we undertook a large-scale gene-environment interaction analysis (GxE). Methods: We tested multiplicative statistical interactions between approximately 7 million common (allele frequency >1%) genetic variants and T2D status in 31,529 colorectal cancer cases and 42,861 controls of European ancestry from 3 genetic consortia (GECCO/CCFR/CORECT). Statistical methods included traditional case-control logistic regression, case-only analyses, joint tests (2df/3df), and two-step approaches. We also explored additive and multiplicative interactions between polygenic risk score (PRS) of the known genome-wide significant loci for colorectal cancer and T2D. Results: Overall, T2D was positively associated with colorectal cancer risk [odds ratio [OR]: 1.25 (95% confidence interval [CI]: 1.14-1.36)]. A statistically significant interaction was identified between T2D status and an intronic variant in LRCH1 (rs9526201) and colorectal cancer risk using the 2-d.f. joint test (p-value:1.44x10-8). A statistically significant additive scale interaction between PRS for colorectal cancer and T2D was found (p-value: 1.8x10-10) such that the observed risk of developing colorectal cancer for individuals with T2D and a 1 standard deviation (SD) higher increment of PRS compared to non-diabetics with the lowest PRS was 0.184 more than if there was no interaction between T2D and PRS. Conclusion: These results suggest that variation in a gene related to immune function may modify the association of T2D with colorectal cancer and potentially provide novel insights into the biology underlying this relationship. Furthermore, our data show that genetic risk prediction models for CRC may need to consider non-genetic risk factors. Citation Format: Niki Dimou, Andre E. Kim, Orlagh Flanagan, Neil Murphy, Emmanouil Bouras, Peter T. Campbell, Graham Casey, Steven Gallinger, Stephen B. Gruber, Li Hsu, Mark A. Jenkins, Yi Lin, Victor Moreno, Conghui Qu, Edward Ruiz-Narvaez, Mariana C. Stern, Yu Tian, Kostas Tsilidis, W. James Gauderman, Marc J. Gunter, Ulrike Peters. Probing the diabetes - colorectal cancer link using gene - environment interaction analyses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 817.

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.

Incidence rates of childhood leukemia in the United States have steadily increased over the last several decades, but only recently have disparities in the increase in incidence been recognized. In the current analysis, Surveillance, Epidemiology and End Results (SEER) data were used to evaluate recent trends in the incidence of childhood leukemia diagnosed at age 0-19 years from 1992 to 2013, overall and by age, race/ethnicity, gender and histologic subtype. Hispanic White children were more likely than non-Hispanic White, non-Hispanic Black or non-Hispanic Asian children to be diagnosed with acute lymphocytic leukemia (ALL) from 2009 to 2013. From 1992 to 2013, a significant increase in ALL incidence was observed for Hispanic White children [annual percent change (APC)Hispanic = 1.08, 95% CI: 0.59, 1.58]; no significant increase was observed for non-Hispanic White, Black or Asian children. ALL incidence increased by about 3% per year from 1992 to 2013 for Hispanic White children diagnosed from 15 to 19 years (APC = 2.67; 95% CI: 0.88, 4.49) and by 2% for those 10-14 years (APC = 2.09; 95% CI: 0.57, 3.63), while no significant increases in incidence were observed in non-Hispanic White, Black, or Asian children of the same age. Acute myeloid leukemia (AML) incidence increased among non-Hispanic White children under 1 year at diagnosis, and among Hispanic White children diagnosed at age 1-4. The increase in incidence rates of childhood ALL appears to be driven by rising rates in older Hispanic children (10-14, and 15-19 years). Future studies are needed to evaluate reasons for the increase in ALL among older Hispanic children.

RationaleAdverse effects of exposures to ambient air pollution on lung function are well documented, but evidence in racial/ethnic minority children is lacking.ObjectivesTo assess the relationship between air pollution and lung function in minority children with asthma and possible modification by global genetic ancestry.MethodsThe study population consisted of 1,449 Latino and 519 African American children with asthma from five different geographical regions in the mainland United States and Puerto Rico. We examined five pollutants (particulate matter ≤10 μm and ≤2.5 μm in diameter, ozone, nitrogen dioxide, and sulfur dioxide), derived from participant residential history and ambient air monitoring data, and assessed over several time windows. We fit generalized additive models for associations between pollutant exposures and lung function parameters and tested for interaction terms between exposures and genetic ancestry.Measurements and main resultsA 5 μg/m(3) increase in average lifetime particulate matter less than or equal to 2.5 μm in diameter exposure was associated with a 7.7% decrease in FEV1 (95% confidence interval = -11.8 to -3.5%) in the overall study population. Global genetic ancestry did not appear to significantly modify these associations, but percent African ancestry was a significant predictor of lung function.ConclusionsEarly-life particulate exposures were associated with reduced lung function in Latino and African American children with asthma. This is the first study to report an association between exposure to particulates and reduced lung function in minority children in which racial/ethnic status was measured by ancestry-informative markers.

A genome-wide association study (GWAS) typically is focused on detecting marginal genetic effects. However, many complex traits are likely to be the result of the interplay of genes and environmental factors. These SNPs may have a weak marginal effect and thus unlikely to be detected from a scan of marginal effects, but may be detectable in a gene-environment (G × E) interaction analysis. However, a genome-wide interaction scan (GWIS) using a standard test of G × E interaction is known to have low power, particularly when one corrects for testing multiple SNPs. Two 2-step methods for GWIS have been previously proposed, aimed at improving efficiency by prioritizing SNPs most likely to be involved in a G × E interaction using a screening step. For a quantitative trait, these include a method that screens on marginal effects [Kooperberg and Leblanc, 2008] and a method that screens on variance heterogeneity by genotype [Pare et al., 2010] In this paper, we show that the Pare et al. approach has an inflated false-positive rate in the presence of an environmental marginal effect, and we propose an alternative that remains valid. We also propose a novel 2-step approach that combines the two screening approaches, and provide simulations demonstrating that the new method can outperform other GWIS approaches. Application of this method to a G × Hispanic-ethnicity scan for childhood lung function reveals a SNP near the MARCO locus that was not identified by previous marginal-effect scans.

Studying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions uses a single regression model that includes both the genetic main and G × E interaction effects (the “joint” framework). The alternative “stratified” framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.

Background: Menopausal hormone therapy (MHT) use has been consistently associated with a decreased risk of colorectal cancer (CRC) in women. Our aim was to use a genome-wide gene–environment interaction analysis to identify genetic modifiers of CRC risk associated with use of MHT. Methods: We included 10 835 postmenopausal women (5419 cases and 5416 controls) from 10 studies. We evaluated use of any MHT, oestrogen-only (E-only) and combined oestrogen–progestogen (E+P) hormone preparations. To test for multiplicative interactions, we applied the empirical Bayes (EB) test as well as the Wald test in conventional case–control logistic regression as primary tests. The Cocktail test was used as secondary test. Results: The EB test identified a significant interaction between rs964293 at 20q13.2/CYP24A1 and E+P (interaction OR (95% CIs)=0.61 (0.52–0.72), P=4.8 × 10−9). The secondary analysis also identified this interaction (Cocktail test OR=0.64 (0.52–0.78), P=1.2 × 10−5 (alpha threshold=3.1 × 10−4). The ORs for association between E+P and CRC risk by rs964293 genotype were as follows: C/C, 0.96 (0.61–1.50); A/C, 0.61 (0.39–0.95) and A/A, 0.40 (0.22–0.73), respectively. Conclusions: Our results indicate that rs964293 modifies the association between E+P and CRC risk. The variant is located near CYP24A1, which encodes an enzyme involved in vitamin D metabolism. This novel finding offers additional insight into downstream pathways of CRC etiopathogenesis.

Background:Previous studies associated night-shift work with melatonin disruption, with mixed evidence regarding the modulating effects of chronotype (i.e., diurnal preference).Methods:One hundred and thirty active nurses (84 rotating-shift and 46 day-shift workers) in the Nurses' Health Study II wore a head-mounted light meter and collected spontaneous urine voids over 3 days. 6-Sulfatoxymelatonin (aMT6s), the major urinary metabolite of melatonin, was assessed.Results:Rotating-shift workers on night shifts had more light exposure and lower urinary melatonin levels during the night, and urinary melatonin rhythms with smaller peaks [11.81 ng/mg-creatinine/h, 95% confidence interval (CI), 9.49–14.71 vs. 14.83 ng/mg-creatinine/h, 95% CI, 11.72–18.75] and later peak onset (5.71 hours, 95% CI, 4.76–6.85 vs. 4.10 hours, 95% CI, 3.37–4.99), compared with day-shift workers. Furthermore, evening chronotypes' melatonin rhythms had later peak onset compared with morning types (4.90 hours, 95% CI, 3.94–6.09 vs. 3.64 hours, 95% CI, 2.99–4.43). However, among day-shift workers, morning chronotypes had melatonin rhythms with greater mean levels, larger peaks, and earlier peak onset compared with evening chronotypes; patterns were similar comparing evening versus morning chronotypes among rotating-shift workers on night shifts. The interaction of rotating-shift work and chronotype was significant across all parameters (P < 0.05).Conclusions:As expected, rotating-shift workers on night shifts had greater light exposure and lower urinary melatonin levels during the night compared with day-shift workers. Intriguingly, melatonin rhythms were dependent on both chronotype and rotating-shift work type, and better alignment of rotating-shift work and chronotype appeared to produce less disrupted melatonin rhythms.Impact:The joint effects of shift-work type and chronotype require attention in future studies.

In the version of this article initially published, in Fig. 3, the y-axis numbering did not match the log scale indicated in the axis label. The error has been corrected in the HTML and PDF version of the article.

Background/Aim: The Pediatric Research using Integrated Sensor Monitoring Systems (PRISMS) program was launched by the US National Institute of Biomedical Imaging and Bioengineering to develop wear...

We tested for pleiotropy in European ancestry subjects (N>90K) via GWAS of systolic and diastolic blood pressure (BP), mean arterial pressure, and pulse pressure, using gene (G)-alcohol consumption (E) interactions. The approach was a correlated meta-analysis (PMCID-PMC3773990) that combined simultaneously the 4 BP traits genome-wide GxE interactions summary meta-P values. This approach adjusts for correlations among single traits at the genomic level. A variant was considered pleiotropic when the overall correlated meta-analysis yielded P ≤5E-08 and GxE meta- P ≤E-04 for at least two single traits. The novel pleiotropic variants localize in eight loci. TTLL7 (1p31.1) is a tubulin modifier. DYRK3 (1q32.1) is a transcription regulator. MAPKAPK2 (1q32.1) is a stress-activated serine/threonine-protein kinase involved in cytokine production especially for TNF , IL6 and phosphorylates (among others) LSP1 , identified in our GWAS GxE study for individual BP traits. FSTL5 (4q32.2) is annotated as calcium ion binding . A locus at 11q13.1 includes SNX32 , EFEMP2, and FOSL1 . FOSL1 variants may regulate expression of SNX32 . EFEMP2 is implicated in blood coagulation. CATSPER2 (15q15.3) is a cation channel. CCDC151 (19p13.2) is an outer dynein arm assembly. The functions of two other loci (17q22 and 18q22.3) are unknown. We also identified 4 pleiotropic loci ( SGK223 , TNKS , GATA4 , FTO ) that were found significant at our GxE meta-GWAS of single traits in 572K multi-ancestry individuals. In addition, we detected 24 pleiotropic BP-known loci. Some of these genes relate to alcohol consumption (e.g., BLK , GATA4 , FTO ). TNKS , MAPKAPK2 and FSTL5 interact with the Wnt/β-catenin signaling pathway, which contributes to hypertension. Several pleiotropic variants showed features of regulation by locating at promoter and enhancer histone marks, at DNAse, at proteins binding sites and being eQTL. The 36 novel and BP-known loci comprising 86 significant genes were enriched for Hypertension , Cardiac arrhythmias , Myocardial infarction , Atrial fibrillation, and Left ventricular hypertrophy . Our correlated meta-analysis of GxE interaction approach identified novel pleiotropic loci and validated known BP loci, thus providing insights into the mechanisms of hypertension.

BACKGROUND Use of electronic cigarettes (e-cigarettes) among adolescents has increased since their introduction into the US market in 2007. Little is known about the role of e-cigarette psychosocial factors on risk of e-cigarette or cigarette use in adolescence. METHODS Information on e-cigarette and cigarette psychosocial factors (use and attitudes about use in the home and among friends) was collected from 11th- and 12th-grade participants in the Southern California Children’s Health Study during the spring of 2014. RESULTS Of 2084 participants, 499 (24.0%) had used an e-cigarette, including 200 (9.6%) current users (past 30 days); 390 participants (18.7%) had smoked a combustible cigarette, and 119 (5.7%) were current cigarette smokers. Cigarette and e-cigarette use were correlated. Nevertheless, 40.5% (n = 81) of current e-cigarette users had never smoked a cigarette. Psychosocial factors (home use of each product, friends’ use of and positive attitudes toward e-cigarettes and cigarettes) and participant perception of the harm of e-cigarettes were strongly positively associated both with e-cigarette and cigarette use. Most youth who reported e-cigarette use had friends who used e-cigarettes, and almost half of current users reported that they did not believe there were health risks associated with e-cigarette use. CONCLUSIONS Longitudinal studies of adolescents are needed to determine whether the strong association of e-cigarette psychosocial factors with both e-cigarette and cigarette use will lead to increased cigarette use or dual use of cigarettes and e-cigarettes, or whether e-cigarettes will serve as a gateway to cigarette use.

To assess associations between age-related macular degeneration (AMD) and multiple factors comprising a conceptual model of AMD risk in a population of Chinese Americans, and to draw comparisons with a similar risk assessment of a Latino population.A cross-sectional population-based study.We enrolled 4582 Chinese Americans aged ≥50 residing in Monterey Park, California.Participants completed a comprehensive eye examination, including stereoscopic fundus photography and ocular biometric measurements. Fundus images were graded using a modified version of the Wisconsin Age-Related Maculopathy Grading System.Odds ratios for factors significantly modifying the risk of AMD and its related retinal lesions.Of the eligible participants, 4172 (72%) had fundus photographs gradable for AMD. Early AMD was present in 375 eyes (4.6%), and late AMD was present in 17 (0.2%). Shorter axial length, male sex, older age, and family history of AMD were identified as independent risk factors for prevalent AMD and its characteristic retinal lesions using a conceptual model of potential AMD risk factors. Of 4 AMD risk factors identified for Latinos, 3 (older age, male sex, shorter axial length) overlapped with those identified for Chinese Americans, with an association similar in magnitude and direction. Lower levels of education were a risk factor specific to Latinos. Based on a multivariable logistic regression model, the predicted probability of early AMD was 31% lower among Chinese Americans relative to Latinos (95% confidence interval [CI], 17%-43%). Chinese Americans also had statistically significantly lower odds of any AMD and 2 types of early retinal lesions symptomatic of AMD.Factors associated with prevalent AMD are similar for Chinese Americans and Latinos. Chinese Americans who were older, were male, had a family history of AMD, and had a shorter axial length were at an increased risk for AMD compared with those without these risk factors. We observed a significantly lower predicted prevalence of AMD among Chinese Americans compared with Latinos, even after controlling for all relevant covariates, suggesting that additional genetic or lifestyle differences may play an important role in determining AMD risk.

Background— Nitric oxide (NO) plays an important role in cardiovascular health by maintaining and regulating vascular tone and blood flow. Epigenetic regulation of NO synthase (NOS), the genes responsible for NO production, may affect cardiovascular disease, including the development of atherosclerosis in children. Methods and Results— We measured percentage DNA methylation using bisulfite conversion and pyrosequencing assays on DNA from buccal cells provided by 377 participants of the Children’s Health Study on whom carotid artery intima-media thickness (CIMT) measurements were also collected. We examined a total of 16 CpG loci located within NOS1 , NOS2A , NOS3 , ARG1 , and ARG2 genes responsible for NO production. CIMT was measured using high-resolution B-mode carotid ultrasound. The association between percentage DNA methylation in ARG and NOS genes with CIMT was evaluated using linear regression adjusted for sex, ethnicity, body mass index, age at CIMT, town of residence, and experimental plate for pyrosequencing reactions. Differences in the association by ethnicity and ancestral group were also evaluated. For a 1% increase in average DNA methylation of NOS1 , CIMT increased by 1.2 μm ( P =0.02). This association was greater in Hispanic children of Native American descent (β=2.3; P =0.004) than in non-Hispanic whites (β=0.3; P =0.71) or Hispanic whites (β=1.0; P =0.35). Conclusions— DNA methylation of NOS1 has a plausible role in atherogenesis through regulation of NO production, although ancestry may alter the magnitude of this association.

Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors.

In a genome-wide association study (GWAS), investigators typically focus their primary analysis on the direct (marginal) associations of each single nucleotide polymorphism (SNP) with the trait. Some SNPs that are truly associated with the trait may not be identified in this scan if they have a weak marginal effect and thus low power to be detected. However, these SNPs may be quite important in subgroups of the population defined by an environmental or personal factor, and may be detectable if such a factor is carefully considered in a gene-environment (G × E) interaction analysis. We address the question "Using a genome wide interaction scan (GWIS), can we find new genes that were not found in the primary GWAS scan?" We review commonly used approaches for conducting a GWIS in case-control studies, and propose a new two-step screening and testing method (EDG×E) that is optimized to find genes with a weak marginal effect. We simulate several scenarios in which our two-step method provides 70-80% power to detect a disease locus while a marginal scan provides less than 5% power. We also provide simulations demonstrating that the EDG×E method outperforms other GWIS approaches (including case only and previously proposed two-step methods) for finding genes with a weak marginal effect. Application of this method to a G × Sex scan for childhood asthma reveals two potentially interesting SNPs that were not identified in the marginal-association scan. We distribute a new software program (G×Escan, available at http://biostats.usc.edu/software) that implements this new method as well as several other GWIS approaches.