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 β-cell function, insulin resistance, and insulin sensitivity (HOMA-β, 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-β, HOMA-IR, and plasma insulin levels and higher HOMA-S. Additionally, higher urinary copper levels were associated with a reduced HOMA-β. Lastly, a higher concentration of the 8 metal mixtures was associated with lower HOMA-β, 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

A RESTful API for Accessing Microbial Community Data for MG-RAST

Many health outcomes are influenced by a person's body mass index, as well as by the trajectory of body mass index through a lifetime. Although previous research has established that body mass index related traits are influenced by genetics, the relationship between these traits and genetics has not been well characterized in people of South Asian ancestry. To begin to characterize this relationship, we analyzed the association between common genetic variation and five phenotypes related to body mass index in a population-based sample of 5,354 Bangladeshi adults. We discovered a significant association between SNV rs347313 (intron of NOS1AP) and change in body mass index in women over two years. In a linear mixed-model, the G allele was associated with an increase of 0.25 kg/m2 in body mass index over two years (p-value of 2.3·10−8). We also estimated the heritability of these phenotypes from our genotype data. We found significant estimates of heritability for all of the body mass index-related phenotypes. Our study evaluated the genetic determinants of body mass index related phenotypes for the first time in South Asians. The results suggest that these phenotypes are heritable and some of this heritability is driven by variation that differs from those previously reported. We also provide evidence that the genetic etiology of body mass index related traits may differ by ancestry, sex, and environment, and consequently that these factors should be considered when assessing the genetic determinants of the risk of body mass index-related disease

Association between Arsenic Exposure from Drinking Water and Longitudinal Change in Blood Pressure among HEALS Cohort Participants

Background: Cross-sectional studies have shown associations between arsenic exposure and prevalence of high blood pressure; however, studies examining the relationship of arsenic exposure with longitudinal changes in blood pressure are lacking. Method: We evaluated associations of arsenic exposure in relation to longitudinal change in blood pressure in 10,853 participants in the Health Effects of Arsenic Longitudinal Study (HEALS). Arsenic was measured in well water and in urine samples at baseline and in urine samples every 2 years after baseline. Mixed-effect models were used to estimate the association of baseline well and urinary creatinine-adjusted arsenic with annual change in blood pressure during follow-up (median, 6.7 years). Result: In the HEALS population, the median water arsenic concentration at baseline was 62 μg/L. Individuals in the highest quartile of baseline water arsenic or urinary creatinine-adjusted arsenic had a greater annual increase in systolic blood pressure compared with those in the reference group (β = 0.48 mmHg/year; 95% CI: 0.35, 0.61, and β = 0.43 mmHg/year; 95% CI: 0.29, 0.56 for water arsenic and urinary creatinine-adjusted arsenic, respectively) in fully adjusted models. Likewise, individuals in the highest quartile of baseline arsenic exposure had a greater annual increase in diastolic blood pressure for water arsenic and urinary creatinine-adjusted arsenic, (β = 0.39 mmHg/year; 95% CI: 0.30, 0.49, and β = 0.45 mmHg/year; 95% CI: 0.36, 0.55, respectively) compared with those in the lowest quartile. Conclusion: Our findings suggest that long-term arsenic exposure may accelerate age-related increases in blood pressure. These findings may help explain associations between arsenic exposure and cardiovascular disease

The Influence of Germline Genetic Variation on Early Onset Breast Cancer Incidence and Mortality

In the United States, breast cancer is the most frequently diagnosed non-skin cancer in women, and one in five women who are diagnosed develop breast cancer before age 50. Germline genetic variation is a known risk factor for breast cancer risk, and a suspected risk factor for breast cancer mortality, but previous investigations have not comprehensively identified all of the genetic variation that is expected to be associated with breast cancer. One possible explanation for this gap in knowledge is the only relatively recent ability to investigate the effect of rare germline genetic variation, which up until recently has been too expensive and technically challenging to measure in the a large number of participants that are necessary for genetic epidemiologic studies, and the methodological challenges of identifying rare variants. This thesis uses three complementary methods (single marker regression analysis, SKAT-O gene-based tests, and candidate gene) to identify individual risk loci and three additional complementary methods (Kriging whole genome prediction, polygenic risk scores, and whole genome heritability estimates) to predict breast cancer risk and breast cancer mortality using a population of women who were diagnosed with breast cancer before the age of 50. Suggestively associated risk loci were examined for evidence of replication using an independent sample. For breast cancer risk, the identification analyses find three genes in which variation is associated with risk of breast cancer: FGFR2 (discovery p=2.18e-5; replication p<1e-30), NEK10 (discovery p=1.20e-3; replication p<1e-30), and MKL1 (discovery p=2.62e-4; replication p<p<1e-30). Previous studies had identified loci near each of these genes as being associated with breast cancer risk, but conditional analyses indicate that the associations in the MKL1 and NEK10 genes are driven by risk loci distinct from those previously reported, and are driven by risk loci that would not have been identified using a single variant regression. The genetic data alone is able to predict breast cancer risk with an AUC of 0.618 (95% CI 0.610-0.629). When the influence of a limited set of non-genetic predictors is also incorporated, the combined model is able to predict breast cancer risk with an AUC of 0.655 (95% CI: 0.649-0.660). This combined model is a significant improvement over models that include only the genetic information or only the non-genetic risk factors. In contrast to the analyses of the genetic determinants of breast cancer development, this analysis does not find any compelling evidence that breast cancer mortality is strongly driven by germline genetics that could be measured by our study. The identified genes all represent possible pharmacological targets for cancer chemoprevention. The prediction model for breast cancer risk improves upon existing methods of prediction, and is strong enough to be useful at the population level. From a clinical perspective, the model still has low levels of discrimination, but may be strong enough to be used in very specific scenarios, such as interpretation of ambiguous screening results, or to help individuals to understand their personal risk when considering other medical treatments that may increase the risk of breast cancer such as hormone replacement therapy or hormone-assisted reproductive therapy. In the context of breast cancer prognosis, these investigations support other lines of evidence that suggest that for many women who are diagnosed with breast cancer, germline genetic variation does not strongly influence the risk of mortality

Retinal Ganglion Cell and Inner Plexiform Layer Loss Correlate with Visual Acuity Loss in LHON: A Longitudinal, Segmentation OCT Analysis.

PURPOSE: Describe changes in the retina as vision loss progresses in Leber\u27s Hereditary Optic Neuropathy (LHON) using spectral-domain optical coherence tomography (SD-OCT) autosegmentation, and determine if relationship exists between retinal changes and vision loss. METHODS: From patient records we identified nine LHON patients who underwent periodic neuro-ophthalmologic examinations and high-resolution SD-OCT as part of their care. We describe the impact of LHON progression on each retinal layer, and the relationship between these structural changes and visual acuity using generalized estimating equations and nonparametric tests. RESULTS: The thickness of the ganglion cell layer (GCL) and inner plexiform layer (IPL) decreased immediately or soon after symptom onset, and this decrease was associated with worsening vision: in the GCL a 1-mm3 volume loss was associated with a 3.2 increase in logMAR visual acuity (95% confidence interval [CI]: 2.1-4.1); in the IPL a 1-mm3 volume loss was associated with a 4.9 increase in visual acuity (95%CI: 6.5-3.2). The retinal nerve fiber layer (RNFL) also thinned, but not until after the GCL and IPL, and only in the papillomacular bundle (PMB) and temporal layers was thinning associated with vision loss. CONCLUSIONS: For the first time these analyses describe a structure-function relationship between the retinal changes that occur in LHON patients as their disease progresses and vision worsens. The structural changes in the GCL, IPL, and RNFL preceded structural changes in the other retinal layers. This analysis suggests that the first 6 months after diagnosis define a target for therapeutic intervention, and this can inform treatment guidelines for ongoing therapeutic trials

Mendelian randomization analysis of arsenic metabolism and pulmonary function within the Hispanic Community Health Study/Study of Latinos

Arsenic exposure has been linked to poor pulmonary function, and inefficient arsenic metabolizers may be at increased risk. Dietary rice has recently been identified as a possible substantial route of exposure to arsenic, and it remains unknown whether it can provide a sufficient level of exposure to affect pulmonary function in inefficient metabolizers. Within 12,609 participants of HCHS/SOL, asthma diagnoses and spirometry-based measures of pulmonary function were assessed, and rice consumption was inferred from grain intake via a food frequency questionnaire. After stratifying by smoking history, the relationship between arsenic metabolism efficiency [percentages of inorganic arsenic (%iAs), monomethylarsenate (%MMA), and dimethylarsinate (%DMA) species in urine] and the measures of pulmonary function were estimated in a two-sample Mendelian randomization approach (genotype information from an Illumina HumanOmni2.5-8v1-1 array), focusing on participants with high inferred rice consumption. Among never-smoking high inferred consumers of rice (n = 1395), inefficient metabolism was associated with past asthma diagnosis and forced vital capacity below the lower limit of normal (LLN) (OR 1.40, p = 0.0212 and OR 1.42, p = 0.0072, respectively, for each percentage-point increase in %iAs; OR 1.26, p = 0.0240 and OR 1.24, p = 0.0193 for %MMA; OR 0.87, p = 0.0209 and OR 0.87, p = 0.0123 for the marker of efficient metabolism, %DMA). Among ever-smoking high inferred consumers of rice (n = 1127), inefficient metabolism was associated with peak expiratory flow below LLN (OR 1.54, p = 0.0108/percentage-point increase in %iAs, OR 1.37, p = 0.0097 for %MMA, and OR 0.83, p = 0.0093 for %DMA). Less efficient arsenic metabolism was associated with indicators of pulmonary dysfunction among those with high inferred rice consumption, suggesting that reductions in dietary arsenic could improve respiratory health

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

Genome-wide association studies and heritability estimates of body mass index related phenotypes in Bangladeshi adults.

Many health outcomes are influenced by a person's body mass index, as well as by the trajectory of body mass index through a lifetime. Although previous research has established that body mass index related traits are influenced by genetics, the relationship between these traits and genetics has not been well characterized in people of South Asian ancestry. To begin to characterize this relationship, we analyzed the association between common genetic variation and five phenotypes related to body mass index in a population-based sample of 5,354 Bangladeshi adults. We discovered a significant association between SNV rs347313 (intron of NOS1AP) and change in body mass index in women over two years. In a linear mixed-model, the G allele was associated with an increase of 0.25 kg/m2 in body mass index over two years (p-value of 2.3·10-8). We also estimated the heritability of these phenotypes from our genotype data. We found significant estimates of heritability for all of the body mass index-related phenotypes. Our study evaluated the genetic determinants of body mass index related phenotypes for the first time in South Asians. The results suggest that these phenotypes are heritable and some of this heritability is driven by variation that differs from those previously reported. We also provide evidence that the genetic etiology of body mass index related traits may differ by ancestry, sex, and environment, and consequently that these factors should be considered when assessing the genetic determinants of the risk of body mass index-related disease

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

BackgroundPrenatal exposure to drinking water with arsenic concentrations &gt;50&nbsp;μg/L is associated with adverse birth outcomes, with inconclusive evidence for concentrations ≤50&nbsp;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&nbsp;=&nbsp;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&nbsp;μg/L was associated with a -1.83&nbsp;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&nbsp;μg/L was associated with a -2.79&nbsp;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