Untargeted Metabolome Atlas for Sleep Phenotypes in the Hispanic Community Health Study/Study of Latinos.

Sleep is essential to maintaining health and wellbeing of individuals, influencing a variety of outcomes from mental health to cardiometabolic disease. This study aims to assess the relationships between various sleep phenotypes and blood metabolites. Utilizing data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep phenotypes, grouped in several domains (i.e., sleep disordered breathing (SDB), sleep duration, timing, insomnia symptoms, and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualize and interpret the associations between sleep phenotypes and metabolites. The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, some xenobiotic metabolites were associated with sleep duration and heart rate phenotypes (e.g. 1H-indole-7-acetic acid, 4-allylphenol sulfate), while ketone bodies and fatty acid metabolism metabolites were associated with sleep timing measures (e.g. 3-hydroxybutyrate (BHBA), 3-hydroxyhexanoylcarnitine (1)). Heart rate phenotypes had the overall largest number of detected metabolite associations. Many of these associations were shared with both SDB and with sleep timing phenotypes, while SDB phenotypes shared relatively few metabolite associations with sleep duration measures. A number of metabolites were associated with multiple sleep phenotypes, from a few domains. The amino acids vanillylmandelate (VMA) and 1-carboxyethylisoleucine were associated with the greatest number of sleep phenotypes, from all domains other than insomnia. This atlas of sleep-metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health.

Thyroid-related Hormones and Hypertension Incidence in Middle-Aged and Older Hispanic/Latino Adults: The HCHS/SOL Study.

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.

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

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

Association of Acculturation and Hispanic/Latino Background with Endogenous Sex and Thyroid-Related Hormones Among Middle-Aged and Older Hispanic/Latino Adults: the HCHS/SOL Study.

BACKGROUND: Hormones are linked to cardiometabolic diseases and may be impacted by acculturation though multiple mechanisms. We evaluated associations of Hispanic/Latino background and acculturation with levels of sex- and thyroid-related hormones and the potential mediating effect of adiposity, lifestyle factors, and sleep apnea syndrome on these associations. METHODS: We studied 1789 adults, aged 45-74, from a sub-cohort of the Hispanic Community Health Survey/Study of Latinos. Peri/pre-menopausal women and individuals on medications related to hormones were excluded. Our study assessed eleven sex- and thyroid-related hormones, Hispanic/Latino background, and five acculturation measures. Associations were assessed using multivariable linear and logistic regression adjusted for survey design and confounding variables. We explored potential mediation using a path analysis. RESULTS: In postmenopausal women, acculturation score-MESA was associated with decreased thyroid-stimulating hormone (ß = - 0.13;95%CI = - 0.22, - 0.03) while age at immigration greater than the median (vs US-born) was associated with decreased (ß = - 14.6; 95%CI = - 28.2, - 0.99) triiodothyronine (T3). In men, language acculturation and acculturation score-MESA were associated with increased estradiol and sex hormone-binding globulin (SHBG) while age at immigration greater and lesser than the median (vs US-born) was associated with decreased SHBG. Hispanic/Latino background (Mexicans as reference) were selectively associated with sex- and thyroid-related hormone levels in both sexes. Current smoking and sleep apnea syndrome partially mediated the association of Cuban and Puerto Rican heritage (vs Mexican) with T3 levels in men and postmenopausal women, respectively. CONCLUSION: Selected acculturation measures were associated with thyroid-related hormones in postmenopausal women and sex-related hormones in men. Understanding the mechanisms involved in the relationship of acculturation and Hispanic/Latino background with hormones warrants additional investigation.

Arsenic metabolism, diabetes prevalence, and insulin resistance among Mexican Americans: A mendelian randomization approach.

Background: Differences in arsenic metabolism capacity may influence risk for type 2 diabetes, but the mechanistic drivers are unclear. We evaluated the associations between arsenic metabolism with overall diabetes prevalence and with static and dynamic measures of insulin resistance among Mexican Americans living in Starr County, Texas. Methods: We utilized data from cross-sectional studies conducted in Starr County, Texas, from 2010-2014. A Mendelian randomization approach was utilized to evaluate the associations between arsenic metabolism and type 2 diabetes prevalence using the intronic variant in the arsenic methylating gene, rs9527, as the instrumental variable for arsenic metabolism. To further assess mechanisms for diabetes pathogenesis, proportions of the urinary arsenic metabolites were employed to assess the association between arsenic metabolism and insulin resistance among participants without diabetes. Urinary biomarkers of arsenic metabolites were modeled as individual proportions of the total. Arsenic metabolism was evaluated both with a static outcome of insulin resistance, homeostatic measure of assessment (HOMA-IR), and a dynamic measure of insulin sensitivity, Matsuda Index. Results: Among 475 Mexican American participants from Starr County, higher metabolism capacity for arsenic is associated with higher diabetes prevalence driven by worse insulin resistance. Presence of the minor T allele of rs9527 is independently associated with an increase in the proportion of monomethylated arsenic (MMA%) and is associated with an odds ratio of 0.50 (95% CI: 0.24, 0.90) for type 2 diabetes. This association was conserved after potential covariate adjustment. Furthermore, among participants without type 2 diabetes, the highest quartile of MMA% was associated with 22% (95% CI: -33.5%, -9.07%) lower HOMA-IR and 56% (95% CI: 28.3%, 91.3%) higher Matsuda Index for insulin sensitivity. Conclusions: Arsenic metabolism capacity, indicated by a lower proportion of monomethylated arsenic, is associated with increased diabetes prevalence driven by an insulin resistant phenotype among Mexican Americans living in Starr County, Texas.

Association between adverse childhood experiences and later-life allostatic load in UK Biobank female participants.

BACKGROUND: Adverse childhood experiences during key developmental periods have been shown to impact long-term health outcomes. Adverse childhood experiences may include psychological, physical, or sexual abuse; neglect; or socioeconomic factors. Adverse childhood experiences are linked with an increase in poor health behavior such as smoking and alcohol consumption, and may also influence epigenetic changes, inflammatory response, metabolic changes, and allostatic load. OBJECTIVE: We sought to explore associations between adverse childhood experiences and allostatic load in adult female participants in the UK Biobank. DESIGN: The UK Biobank is a multisite cohort study established to capture lifestyle, environment, exposure, health history, and genotype data on individuals in the United Kingdom. METHODS: Adverse childhood experiences were assessed from the Childhood Trauma Screener, which measures abuse and neglect across five items. Biological measures at enrollment were used to construct allostatic load, including measures of metabolic, inflammatory, and cardiovascular function. Females with a cancer diagnosis prior to enrollment were removed as it may influence allostatic load. Poisson regression models were used to assess the association between adverse childhood experiences and allostatic load, accounting for a priori confounders. RESULTS: A total of 33,466 females with complete data were analyzed, with a median age at enrollment of 54 (range = 40-70) years. Among the study sample, the mean allostatic load ranged from 1.85 in those who reported no adverse childhood experiences to 2.45 in those with all adverse childhood experiences reported. In multivariable analysis, there was a 4% increase in average allostatic load among females for every additional adverse childhood experience reported (incidence rate ratio = 1.04, 95% confidence interval = 1.03-1.05). Similar results were observed when assessing individual adverse childhood experience components. CONCLUSION: This analysis supports a growing body of evidence suggesting that increased exposure to early life abuse or neglect is associated with increased allostatic load in females.

Interaction analysis of ancestry-enriched variants with APOE-ɛ4 on MCI in the Study of Latinos-Investigation of Neurocognitive Aging.

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.

Relationships Between Urinary Metals and Diabetes Traits Among Mexican Americans in Starr County, Texas, USA.

Hispanics/Latinos have higher rates of type 2 diabetes (T2D), and the origins of these disparities are poorly understood. Environmental endocrine-disrupting chemicals (EDCs), including some metals and metalloids, are implicated as diabetes risk factors. Data indicate that Hispanics/Latinos may be disproportionately exposed to EDCs, yet they remain understudied with respect to environmental exposures and diabetes. The objective of this study is to determine how metal exposures contribute to T2D progression by evaluating the associations between 8 urinary metals and measures of glycemic status in 414 normoglycemic or prediabetic adults living in Starr County, Texas, a Hispanic/Latino community with high rates of diabetes and diabetes-associated mortality. We used multivariable linear regression to quantify the differences in homeostatic model assessments for pancreatic ß-cell function, insulin resistance, and insulin sensitivity (HOMA-ß, HOMA-IR, HOMA-S, respectively), plasma insulin, plasma glucose, and hemoglobin A1c (HbA1c) associated with increasing urinary metal concentrations. Quantile-based g-computation was utilized to assess mixture effects. After multivariable adjustment, urinary arsenic and molybdenum were associated with lower HOMA-ß, HOMA-IR, and plasma insulin levels and higher HOMA-S. Additionally, higher urinary copper levels were associated with a reduced HOMA-ß. Lastly, a higher concentration of the 8 metal mixtures was associated with lower HOMA-ß, HOMA-IR, and plasma insulin levels as well as higher HOMA-S. Our data indicate that arsenic, molybdenum, copper, and this metal mixture are associated with alterations in measures of glucose homeostasis among non-diabetics in Starr County. This study is one of the first to comprehensively evaluate associations of urinary metals with glycemic measures in a high-risk Mexican American population.

Awareness and utilization of genetic testing among Hispanic and Latino adults living in the US: The Hispanic Community Health Study/Study of Latinos.

We investigated the awareness, perceived usefulness, and use of genetic testing among Hispanic and Latino individuals. Annual follow-up surveys for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) from 2019 to April 2020 assessed participants' level of awareness and use of genetic tests to determine disease risks, likelihood of passing disease to children, disease treatment, or drug selection. They also were asked to rate the usefulness of the tests for managing a person's health on a 1 (not at all useful) to 10 (extremely useful) scale. There were 5,769 HCHS/SOL participants who completed at least one survey question. Of the target population, 55.2% was aware of at least one type of genetic test. Awareness varied between HCHS/SOL enrollment sites and was higher among individuals who had higher educational attainment and had higher incomes. Only 3.3% of the target population reported receiving one or more of the tests described. HCHS/SOL individuals rated the usefulness as 8.4, on average, with lower scores observed among U.S.-born individuals compared to individuals born outside the United States, with differences by HCHS/SOL enrollment sites. In conclusion, while awareness of genetic testing among Hispanic and Latino individuals varies by location, education, and income, perceptions about its usefulness are high while experiences with testing are rare. Results identify groups and locations that may benefit from greater outreach about the capabilities of genetic testing and precision medicine.

Interaction of Arsenic Exposure and Transcriptomic Profile in Basal Cell Carcinoma.

Exposure to inorganic arsenic (As) is recognized as risk factor for basal cell carcinoma (BCC). We have followed-up 7000 adults for 6 years who were exposed to As and had manifest As skin toxicity. Of them, 1.7% developed BCC (males = 2.2%, females = 1.3%). In this study, we compared transcriptome-wide RNA sequencing data from the very first 26 BCC cases and healthy skin tissue from independent 16 individuals. Genes in " cell carcinoma pathway", "Hedgehog signaling pathway", and "Notch signaling pathway" were overexpressed in BCC, confirming the findings from earlier studies in BCC in other populations known to be exposed to As. However, we found that the overexpression of these known pathways was less pronounced in patients with high As exposure (urinary As creatinine ratio (UACR) > 192 µg/gm creatinine) than patients with low UACR. We also found that high UACR was associated with impaired DNA replication pathway, cellular response to different DNA damage repair mechanisms, and immune response. Transcriptomic data were not strongly suggestive of great potential for immune checkpoint inhibitors; however, it suggested lower chance of platinum drug resistance in BCC patients with high UACR compared high platinum drug resistance potential in patients with lower UACR.

An Overview of Cancer in the First 315,000 All of Us Participants.

INTRODUCTION: The 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 METHODS: This 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 DISCUSSION: Data 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. CONCLUSIONS: This 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.

The All of Us Research Program: Data quality, utility, and diversity.

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.

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

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

Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures.

Exposures to environmental pollutants are often composed of mixtures of chemicals that can be highly correlated because of similar sources and/or chemical structures. The effect of an individual chemical on a health outcome can be weak and difficult to detect because of the relatively low level of exposures to many environmental pollutants. To tackle the challenging problem of assessing the health risk of exposure to a mixture of environmental pollutants, we propose a statistical approach to assessing the proportion of the variation of an outcome explained by a mixture of pollutants. The proposed approach avoids the difficult task of identifying specific pollutants that are responsible for the effects and may also be used to assess interactions among exposures. Extensive simulation results demonstrate that the proposed approach has very good performance. Application of the proposed approach is illustrated by investigating the main and interaction effects of the chemical pollutants on systolic and diastolic blood pressure in participants from the National Health and Nutrition Examination Survey.

Arsenic in private well water and birth outcomes in the United States.

BACKGROUND: Prenatal 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. METHODS: Using 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. RESULTS: We 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. CONCLUSION: In 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.

AFA: Ancestry-specific allele frequency estimation in admixed populations: The Hispanic Community Health Study/Study of Latinos.

Allele frequency estimates in admixed populations, such as Hispanics and Latinos, rely on the sample's specific admixture composition and thus may differ between two seemingly similar populations. However, ancestry-specific allele frequencies, i.e., pertaining to the ancestral populations of an admixed group, may be particularly useful for prioritizing genetic variants for genetic discovery and personalized genomic health. We developed a method, ancestry-specific allele frequency estimation in admixed populations (AFA), to estimate the frequencies of biallelic variants in admixed populations with an unlimited number of ancestries. AFA uses maximum-likelihood estimation by modeling the conditional probability of having an allele given proportions of genetic ancestries. It can be applied using either local ancestry interval proportions encompassing the variant (local-ancestry-specific allele frequency estimations in admixed populations [LAFAs]) or global proportions of genetic ancestries (global-ancestry-specific allele frequency estimations in admixed populations [GAFAs]), which are easier to compute and are more widely available. Simulations and comparisons to existing software demonstrated the high accuracy of the method. We implemented AFA on high-quality imputed data of ∼9,000 Hispanics and Latinos from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), an understudied, admixed population with three predominant continental ancestries: Amerindian, European, and African. Comparison of the European and African estimated frequencies to the respective gnomAD frequencies demonstrated high correlations (Pearson R2 = 0.97-0.99). We provide a genome-wide dataset of the estimated ancestry-specific allele frequencies for available variants with allele frequency between 5% and 95% in at least one of the three ancestral populations. Association analysis of Amerindian-enriched variants with cardiometabolic traits identified five loci associated with lipid traits in Hispanics and Latinos, demonstrating the utility of ancestry-specific allele frequencies in admixed populations.

Association of Accelerometer-Measured Physical Activity and Cardiovascular Health in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

INTRODUCTION: Evidence regarding the associations between accelerometer-measured moderate-vigorous physical activity (MVPA) and cardiovascular health (CVH) indicators among Hispanic/Latino adults are unavailable. METHODS: Examined cross-sectional data from 12,008 Hispanic/Latino adults aged 18-74 years participating in the Hispanic Community Health Study/Study of Latinos. Accelerometer-measured MVPA was assessed categorically and dichotomously per 2008 PA guidelines. Adverse and ideal CVH indicators were determined by standard cut-points for blood glucose, total cholesterol, blood pressure, body mass index (BMI), and smoking. A composite of low CV risk, defined as achieving all ideal CVH indicators, was included. Adjusted Poisson regression models and complex survey design methods were used for all analyses. RESULTS: Compared to high MVPA, lower MVPA categories were associated with higher prevalence of all adverse CVH indicators, except hypertension, and with lower prevalence of low CV risk and ideal blood glucose, blood pressure, and BMI. Similarly, non-adherence to PA guidelines was associated with a higher prevalence of diabetes (16%), hypercholesterolemia (9%), obesity (28%), and smoking (9%); and lower prevalence of low CV risk (24%), ideal blood glucose (6%), ideal blood pressure (6%), and ideal BMI (22%). CONCLUSION: Overall, high accelerometer-measured MVPA and meeting PA guidelines were associated with favorable CVH in Hispanic/Latino adults.

A mass-balance model to assess arsenic exposure from multiple wells in Bangladesh.

BACKGROUND: Water arsenic (As) sources beyond a rural household's primary well may be a significant source for certain individuals, including schoolchildren and men working elsewhere. OBJECTIVE: To improve exposure assessment by estimating the fraction of drinking water that comes from wells other than the household's primary well in a densely populated area. METHODS: We use well water and urinary As data collected in 2000-2001 within a 25 km2 area of Araihazar upazila, Bangladesh, for 11,197 participants in the Health Effects of Arsenic Longitudinal Study (HEALS). We estimate the fraction of water that participants drink from different wells by imposing a long-term mass-balance constraint for both As and water. RESULTS: The mass-balance model suggest that, on average, HEALS participants obtain 60-75% of their drinking water from their primary household wells and 25-40% from other wells, in addition to water from food and cellular respiration. Because of this newly quantified contribution from other wells, As in drinking water rather than rice was identified as the largest source of As exposure at baseline for HEALS participants with a primary household well containing ≤50 µg/L As. SIGNIFICANCE: Dose-response relationships for As based on water As should take into account other wells. The mass-balance approach could be applied to study other toxicants.

Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations.

BACKGROUND: Thousands 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. METHODS: To 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. RESULTS: Our 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. CONCLUSIONS: These 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.