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APOE-ɛ4 risk on Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD) differs between race/ethnic groups, presumably due to ancestral genomic background surrounding the APOE locus. We studied whether African and Amerindian ancestry-enriched genetic variants in the APOE region modify the effect of the APOE-ɛ4 alleles on Mild Cognitive Impairment (MCI) in Hispanics/Latinos. We defined African and Amerindian ancestry-enriched variants as those common in one Hispanic/Latino parental ancestry and rare in the other two. We identified such variants in the APOE region with a predicted moderate impact based on the SnpEff tool. We tested their interaction with APOE-ɛ4 on MCI in the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) population and African Americans from the Atherosclerosis Risk In Communities (ARIC) study. We identified 5 Amerindian and 14 African enriched variants with an expected moderate effect. A suggestive significant interaction (p-value = 0.01) was found for one African-enriched variant, rs8112679, located in the ZNF222 gene fourth exon. Our results suggest there are no ancestry-enriched variants with large effect sizes of interaction effects with APOE-ɛ4 on MCI in the APOE region in the Hispanic/Latino population. Further studies are needed in larger datasets to identify potential interactions with smaller effect sizes.

The All of Us Research Program seeks to engage at least one million diverse participants to advance precision medicine and improve human health. We describe here the cloud-based Researcher Workbench that uses a data passport model to democratize access to analytical tools and participant information including survey, physical measurement, and electronic health record (EHR) data. We also present validation study findings for several common complex diseases to demonstrate use of this novel platform in 315,000 participants, 78% of whom are from groups historically underrepresented in biomedical research, including 49% self-reporting non-White races. Replication findings include medication usage pattern differences by race in depression and type 2 diabetes, validation of known cancer associations with smoking, and calculation of cardiovascular risk scores by reported race effects. The cloud-based Researcher Workbench represents an important advance in enabling secure access for a broad range of researchers to this large resource and analytical tools.

BackgroundPrenatal exposure to drinking water with arsenic concentrations >50 μg/L is associated with adverse birth outcomes, with inconclusive evidence for concentrations ≤50 μg/L. In a collaborative effort by public health experts, hydrologists, and geologists, we used published machine learning model estimates to characterize arsenic concentrations in private wells-federally unregulated for drinking water contaminants-and evaluated associations with birth outcomes throughout the conterminous U.S.MethodsUsing several machine learning models, including boosted regression trees (BRT) and random forest classification (RFC), developed from measured groundwater arsenic concentrations of ∼20,000 private wells, we characterized the probability that arsenic concentrations occurred within specific ranges in groundwater. Probabilistic model estimates and private well usage data were linked by county to all live birth certificates from 2016 (n = 3.6 million). We evaluated associations with gestational age and term birth weight using mixed-effects models, adjusted for potential confounders and incorporated random intercepts for spatial clustering.ResultsWe generally observed inverse associations with term birth weight. For instance, when using BRT estimates, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 5 μg/L was associated with a -1.83 g (95% CI: -3.30, -0.38) lower term birth weight after adjusting for covariates. Similarly, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 10 μg/L was associated with a -2.79 g (95% CI: -4.99, -0.58) lower term birth weight. Associations with gestational age were null.ConclusionIn this largest epidemiologic study of arsenic and birth outcomes to date, we did not observe associations of modeled arsenic estimates in private wells with gestational age and found modest inverse associations with term birth weight. Study limitations may have obscured true associations, including measurement error stemming from a lack of individual-level information on primary water sources, water arsenic concentrations, and water consumption patterns.

IntroductionThe NIH All of Us Research Program will have the scale and scope to enable research for a wide range of diseases, including cancer. The program's focus on diversity and inclusion promises a better understanding of the unequal burden of cancer. Preliminary cancer ascertainment in the All of Us cohort from two data sources (self-reported versus electronic health records (EHR)) is considered.Materials and methodsThis work was performed on data collected from the All of Us Research Program's 315,297 enrolled participants to date using the Researcher Workbench, where approved researchers can access and analyze All of Us data on cancer and other diseases. Cancer case ascertainment was performed using data from EHR and self-reported surveys across key factors. Distribution of cancer types and concordance of data sources by cancer site and demographics is analyzed.Results and discussionData collected from 315,297 participants resulted in 13,298 cancer cases detected in the survey (in 89,261 participants), 23,520 cancer cases detected in the EHR (in 203,813 participants), and 7,123 cancer cases detected across both sources (in 62,497 participants). Key differences in survey completion by race/ethnicity impacted the makeup of cohorts when compared to cancer in the EHR and national NCI SEER data.ConclusionsThis study provides key insight into cancer detection in the All of Us Research Program and points to the existing strengths and limitations of All of Us as a platform for cancer research now and in the future.

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.

BackgroundThousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed.MethodsTo derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants.ResultsOur results revealed 24 suggestive signals (p < 1 × 10-4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN.ConclusionsThese analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

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 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.

BackgroundPhysical activity is a modifiable healthy behavior that has been shown to positively influence health-related quality of life. However, research examining the link between physical activity and health-related quality of life among Hispanic/Latino adults is limited and inconsistent. The purpose of this study is to assess whether accelerometer-measured moderate-vigorous physical activity (MVPA) is associated with self-reported (a) mental health-related quality of life, and (b) physical health-related quality of life among diverse Hispanic/Latino adults in the US.MethodsCross-sectional data from 12,379 adults ages 18-74 years in 2008-2011, who participated in HCHS/SOL and had complete data were analyzed using complex survey design methods. Accelerometer data were categorized into no MVPA, low, moderate, and high MVPA. Health-related quality of life was assessed with the Short-Form 12 and we used the mental and physical component subscales where higher scores indicate better health-related quality of life. Multivariate linear regression models were used to derive adjusted means with 95% confidence intervals and linear trends.ResultsWe observed no significant linear trend between accelerometer-measured MVPA and mental health-related quality of life (ptrend = 0.73). There was a significant positive association between MVPA and physical health-related quality of life (ptrend

Arsenic (As) is a risk factor for non-melanoma skin cancer (NMSC). From a six-year follow-up study on 7000 adults exposed to As, we reported the associations of single-nucleotide variation in tumor tissue and gene expression. Here, we identify the associations of small deletions (DELs) and transcriptomic profiles in NMSC. Comparing the (a) NMSC tissue (n = 32) and corresponding blood samples from each patient, and (b) an independent set of non-lesional, healthy skin (n = 16) and paired blood, we identified NMSC-associated DELs. Differential expressions of certain gene pathways (TGF-β signaling pathway, IL-17 pathway, PD-L1 pathway, etc.) showed significant interactions with these somatic DELs and As exposure. In low-As-exposure cases, the DELs in APC were associated with the up-regulation of inflamed T-Cell-associated genes by a fold change (FC) of 8.9 (95% CI 4.5–17.6), compared to 5.7 (95% CI 2.9–10.8) without APC DELs; in high-As-exposure cases, the APC DELs were associated with an FC of 5.8 (95% CI 3.5–9.8) compared to 1.2 (95% CI −1.3 to 1.8) without APC DELs. We report, for the first time, the significant associations of somatic DELs (many in STR regions) in NMSC tissue and As exposure with many dysregulated gene pathways. These findings may help in selecting groups of patients for potential targeted therapy like PD-L1 inhibitors, IL-17 inhibitors, and TGF-β inhibitors in the future. [ABSTRACT FROM AUTHOR]

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 5- to 7-year-old children enrolled in the Bangladesh Environmental Research in Children's Health (BiRCH) cohortIn 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 to −0.010; P  = .0005) and −0.017 (95% CI, −0.029 to −0.004; P  = .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. [ABSTRACT FROM AUTHOR]

Although genome-wide association studies (GWAS) have identified several variants linked to depression, few GWAS of non-European populations have been performed. We conducted a genome-wide analysis of depression in a large, population-based sample of Hispanics/Latinos. Data came from 12,310 adults in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Past-week depressive symptoms were assessed using the 10-item Center for Epidemiological Studies of Depression Scale. Three phenotypes were examined: a total depression score, a total score modified to account for psychiatric medication use, and a score excluding anti-depressant medication users. We estimated heritability due to common variants (h2SNP), and performed a GWAS of the three phenotypes. Replication was attempted in three independent Hispanic/Latino cohorts. We also performed sex-stratified analyses, analyzed a binary trait indicating probable depression, and conducted three trans-ethnic analyses. The three phenotypes exhibited significant heritability (h2SNP = 6.3-6.9%; p = .002) in the total sample. No SNPs were genome-wide significant in analyses of the three phenotypes or the binary indicator of probable depression. In sex-stratified analyses, seven genome-wide significant SNPs (one in females; six in males) were identified, though none were supported through replication. Four out of 24 loci identified in prior GWAS were nominally associated in HCHS/SOL. There was no evidence of overlap in genetic risk factors across ancestry groups, though this may have been due to low power. We conducted the largest GWAS of depression-related phenotypes in Hispanic/Latino adults. Results underscore the genetic complexity of depressive symptoms as a phenotype in this population and suggest the need for much larger samples.

Although generalized anxiety disorder (GAD) is heritable and aggregates in families, no genomic loci associated with GAD have been reported. We aimed to discover potential loci by conducting a genome-wide analysis of GAD symptoms in a large, population-based sample of Hispanic/Latino adults. Data came from 12,282 participants (aged 18-74) in the Hispanic Community Health Study/Study of Latinos. Using a shortened Spielberger Trait Anxiety measure, we analyzed the following: (i) a GAD symptoms score restricted to the three items tapping diagnostic features of GAD as defined by DSM-V; and (ii) a total trait anxiety score based on summing responses to all ten items. We first calculated the heritability due to common variants (h2SNP ) and then conducted a genome-wide association study (GWAS) of GAD symptoms. Replication was attempted in three independent Hispanic cohorts (Multi-Ethnic Study of Atherosclerosis, Women's Health Initiative, Army STARRS). The GAD symptoms score showed evidence of modest heritability (7.2%; P = 0.03), while the total trait anxiety score did not (4.97%; P = 0.20). One genotyped SNP (rs78602344) intronic to thrombospondin 2 (THBS2) was nominally associated (P = 5.28 × 10-8 ) in the primary analysis adjusting for psychiatric medication use and significantly associated with the GAD symptoms score in the analysis excluding medication users (P = 4.18 × 10-8 ). However, meta-analysis of the replication samples did not support this association. Although we identified a genome-wide significant locus in this sample, we were unable to replicate this finding. Evidence for heritability was also only detected for GAD symptoms, and not the trait anxiety measure, suggesting differential genetic influences within the domain of trait anxiety. © 2016 Wiley Periodicals, Inc.

OBJECTIVE: Metal and metalloid exposures (hereafter "metals") are associated with adverse health outcomes, including type 2 diabetes; however, previous studies were largely cross-sectional or underpowered. Furthermore, underserved racial and ethnic groups are underrepresented in environmental health research despite having higher rates of type 2 diabetes and a greater risk of metal exposures. Consequently, we evaluated continuous glycemic traits in relation to baseline urinary toxic metal, essential metal, and metal mixtures in a cohort of Mexican American adults. RESEARCH DESIGN AND METHODS: A total of 510 participants were selected based upon self-reported diabetes status and followed over 3 years. Urinary metals were assessed at baseline. Linear mixed-effects models were used to estimate per-month changes in hemoglobin A1c, fasting plasma glucose, and postload glucose in relation to urinary metal levels. Multiple statistical approaches were used to assess the associations between glycemic traits and metal mixtures. RESULTS: After adjustment, higher urinary levels of arsenic, selenium, copper, molybdenum, nickel, and tin were associated with faster increases in measures of glycemia. The toxic metal mixture composed of arsenic, lead, cadmium, nickel, and tin was associated with faster increases in postload glucose. Using postload glucose criteria, highest versus lowest arsenic was predicted to accelerate conversion of normoglycemia to prediabetes and diabetes by 23 and 65 months, respectively. CONCLUSIONS: In this underrepresented, high-risk Mexican American population, exposure to toxic metals and alterations in essential metal homeostasis were associated with faster increases in glycemia over time that may accelerate type 2 diabetes development. [ABSTRACT FROM AUTHOR]

Exposure to inorganic arsenic (As) is recognized as a risk factor for non-melanoma skin cancer (NMSC). We followed up with 7000 adults for 6 years who were exposed to As. During follow-up, 2.2% of the males and 1.3% of the females developed basal cell carcinoma (BCC), while 0.4% of the male and 0.2% of the female participants developed squamous cell carcinoma (SCC). Using a panel of more than 400 cancer-related genes, we detected somatic mutations (SMs) in the first 32 NMSC samples (BCC = 26 and SCC = 6) by comparing paired (tissue–blood) samples from the same individual and then comparing them to the SM in healthy skin tissue from 16 participants. We identified (a) a list of NMSC-associated SMs, (b) SMs present in both NMSC and healthy skin, and (c) SMs found only in healthy skin. We also demonstrate that the presence of non-synonymous SMs in the top mutated genes (like PTCH1, NOTCH1, SYNE1, PKHD1 in BCC and TP53 in SCC) significantly affects the magnitude of differential expressions of major genes and gene pathways (basal cell carcinoma pathways, NOTCH signaling, IL-17 signaling, p53 signaling, Wnt signaling pathway). These findings may help select groups of patients for targeted therapy, like hedgehog signaling inhibitors, IL17 inhibitors, etc., in the future. [ABSTRACT FROM AUTHOR]

Background Thyroid-related hormones act to regulate metabolic pathways and blood pressure (BP). However, the relationship of TSH and peripheral thyroid hormones and the role of the hypothalamic-pituitary-thyroid axis on hypertension development is not fully understood. We assessed sex-specific associations of thyroid-related hormones with BP and hypertension in Hispanic/Latino adults followed for 6 years. Methods We studied 1789 adults, ages 45 to 74, free of diabetes at baseline from a subcohort of the Hispanic Community Health Study/Study of Latinos. We assessed TSH, free T4 (FT4), T3, and various indicators of thyroid axis. Using multivariable linear and Poisson regression adjusted for survey design and confounding variables, we estimated a priori sex-specific associations of thyroid-related hormones with changes in BP and hypertension development. Results In men and women, TSH and TSH/FT4 ratios were associated with changes in diastolic BP and T3 with changes in pulse pressure and the development of hypertension from prehypertension. In men, a 1-SD increase in TSH [incident rate ratio (IRR) = 1.42; 95% confidence interval (CI): 1.15, 1.75] and TSH/FT4 ratio (IRR = 1.20; 95% CI: 1.07, 1.35) were positively associated with the development of hypertension from prehypertension while the TSH/FT4 ratio (IRR = 0.85; 95% CI:.72, 1.00) was protective in women. We observed sex-specific differences in associations of the T3/FT4 ratio and indices of pituitary sensitivity to thyroid hormones with changes in pulse pressure and hypertension development. Conclusion Thyroid-related hormones are associated with sex-specific changes in BP and hypertension among Hispanic/Latino adults consistent with selected studies conducted in other populations. Mechanisms underlying associations of pituitary sensitivity to thyroid hormones with BP and hypertension development warrant further study. [ABSTRACT FROM AUTHOR]