6 research outputs found

    State-of-the-art methods for exposure-health studies: Results from the exposome data challenge event

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    The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological factors for disease. However, challenges arise when trying to quantify the health effects of complex exposure mixtures. Analytical challenges include dealing with high dimensionality, studying the combined effects of these exposures and their interactions, integrating causal pathways, and integrating high-throughput omics layers. To tackle these challenges, the Barcelona Institute for Global Health (ISGlobal) held a data challenge event open to researchers from all over the world and from all expertises. Analysts had a chance to compete and apply state-of-the-art methods on a common partially simulated exposome dataset (based on real case data from the HELIX project) with multiple correlated exposure variables (P > 100 exposure variables) arising from general and personal environments at different time points, biological molecular data (multi-omics: DNA methylation, gene expression, proteins, metabolomics) and multiple clinical phenotypes in 1301 mother–child pairs. Most of the methods presented included feature selection or feature reduction to deal with the high dimensionality of the exposome dataset. Several approaches explicitly searched for combined effects of exposures and/or their interactions using linear index models or response surface methods, including Bayesian methods. Other methods dealt with the multi-omics dataset in mediation analyses using multiple-step approaches. Here we discuss features of the statistical models used and provide the data and codes used, so that analysts have examples of implementation and can learn how to use these methods. Overall, the exposome data challenge presented a unique opportunity for researchers from different disciplines to create and share state-of-the-art analytical methods, setting a new standard for open science in the exposome and environmental health field

    Development of a global urban greenness indicator dataset for 1,000+ cities

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    Global climate change has sparked efforts to adapt to increasing temperatures, especially in urban areas that experience increased day and nighttime temperatures due to the urban heat island effect. The addition of greenspace has been suggested as a possible means for urban centers to respond to increasing urban temperatures. Thus, it is important for urban planning and policymakers to have access to data on greenspace specific at a fine spatial resolution. This dataset consists of information on peak and annual average 1 × 1 km Normalized Difference Vegetation Index (NDVI) for over 1,000 global urban centers, which is an objective satellite-based measure of vegetation. Population-weighted values for both peak and annual average NDVI and include an indicator of greenness, with seven levels ranging from extremely low to extremely high are provided. Additional information regarding the climate zone (using the Köppen-Geiger climate classification) and level of development (using the Human Development Index or HDI) for each city is included. Analyses were repeated in 2010, 2015, and 2020 to provide the ability to track urban greenness over time. Data are provided in tabular format with summaries presented in both tables and graphics. These data can be used to inform policy and planning and can be used as an indicator for a variety of climate and health investigations

    Diversity of Studies on Neighborhood Greenspace and Brain Health by Racialized/Ethnic Group and Geographic Region: A Rapid Review

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    Studies examining associations between greenspace and Alzheimer’s disease and related dementia (ADRD) outcomes are rapidly on the rise, yet no known literature reviews have summarized the racialized/ethnic group and geographic variation of those published studies. This is a significant gap given the known disparities in both greenspace access and ADRD risk between racialized/ethnic groups and between developed versus developing countries. In this rapid literature review, we (1) describe the diversity of published greenspace–brain health studies with respect to racialized/ethnic groups and geographic regions; (2) determine the extent to which published studies have investigated racialized/ethnic group differences in associations; and (3) review methodological issues surrounding studies of racialized/ethnic group disparities in greenspace and brain health associations. Of the 57 papers meeting our inclusion criteria as of 4 March 2022, 21% (n = 12) explicitly identified and included individuals who were Black, Hispanic/Latinx, and/or Asian. Twenty-one percent of studies (n = 12) were conducted in developing countries (e.g., China, Dominican Republic, Mexico), and 7% (n = 4) examined racialized/ethnic group differences in greenspace–brain health associations. None of the studies were framed by health disparities, social/structural determinants of health, or related frameworks, despite the known differences in both greenspace availability/quality and dementia risk by racialized/ethnic group and geography. Studies are needed in developing countries and that directly investigate racialized/ethnic group disparities in greenspace—brain health associations to target and promote health equity

    Expression quantitative trait locus fine mapping of the 17q12–21 asthma locus in African American children: a genetic association and gene expression study

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    Background: African ancestry is associated with a higher prevalence and greater severity of asthma than European ancestries, yet genetic studies of the most common locus associated with childhood-onset asthma, 17q12–21, in African Americans have been inconclusive. The aim of this study was to leverage both the phenotyping of the Children's Respiratory and Environmental Workgroup (CREW) birth cohort consortium, and the reduced linkage disequilibrium in African Americans, to fine map the 17q12–21 locus. Methods: We first did a genetic association study and meta-analysis using 17q12–21 tag single-nucleotide polymorphisms (SNPs) for childhood-onset asthma in 1613 European American and 870 African American children from the CREW consortium. Nine tag SNPs were selected based on linkage disequilibrium patterns at 17q12–21 and their association with asthma, considering the effect allele under an additive model (0, 1, or 2 effect alleles). Results were meta-analysed with publicly available summary data from the EVE consortium (on 4303 European American and 3034 African American individuals) for seven of the nine SNPs of interest. Subsequently, we tested for expression quantitative trait loci (eQTLs) among the SNPs associated with childhood-onset asthma and the expression of 17q12–21 genes in resting peripheral blood mononuclear cells (PBMCs) from 85 African American CREW children and in upper airway epithelial cells from 246 African American CREW children; and in lower airway epithelial cells from 44 European American and 72 African American adults from a case-control study of asthma genetic risk in Chicago (IL, USA). Findings: 17q12–21 SNPs were broadly associated with asthma in European Americans. Only two SNPs (rs2305480 in gasdermin-B [GSDMB] and rs8076131 in ORMDL sphingolipid biosynthesis regulator 3 [ORMDL3]) were associated with asthma in African Americans, at a Bonferroni-corrected threshold of p<0·0055 (for rs2305480_G, odds ratio [OR] 1·36 [95% CI 1·12–1·65], p=0·0014; and for rs8076131_A, OR 1·37 [1·13–1·67], p=0·0010). In upper airway epithelial cells from African American children, genotype at rs2305480 was the most significant eQTL for GSDMB (eQTL effect size [β] 1·35 [95% CI 1·25–1·46], p<0·0001), and to a lesser extent showed an eQTL effect for post-GPI attachment to proteins phospholipase 3 (β 1·15 [1·08–1·22], p<0·0001). No SNPs were eQTLs for ORMDL3. By contrast, in PBMCs, the five core SNPs were associated only with expression of GSDMB and ORMDL3. Genotype at rs12936231 (in zona pellucida binding protein 2) showed the strongest associations across both genes (for GSDMB, eQTLβ 1·24 [1·15–1·32], p<0·0001; and for ORMDL3 (β 1·19 [1·12–1·24], p<0·0001). The eQTL effects of rs2305480 on GSDMB expression were replicated in lower airway cells from African American adults (β 1·29 [1·15–1·44], p<0·0001). Interpretation: Our study suggests that SNPs regulating GSDMB expression in airway epithelial cells have a major role in childhood-onset asthma, whereas SNPs regulating the expression levels of 17q12–21 genes in resting blood cells are not central to asthma risk. Our genetic and gene expression data in African Americans and European Americans indicated GSDMB to be the leading candidate gene at this important asthma locus.6 month embargo; published: 01 May 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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