342 research outputs found

    Waves III-V Multi-year Air Pollution Exposure Estimates

    Get PDF
    There is a growing body of evidence indicating that cumulative, long-term exposure to air pollution affects health and development. This air pollution data described here provides longer-term estimates of air pollution exposure that can be used to address a broad range of research questions related to how air pollution exposure over time may relate to a variety of health outcomes

    GAWMerge expands GWAS sample size and diversity by combining array-based genotyping and whole-genome sequencing

    Get PDF
    Genome-wide association studies (GWAS) have made impactful discoveries for complex diseases, often by amassing very large sample sizes. Yet, GWAS of many diseases remain underpowered, especially for non-European ancestries. One cost-effective approach to increase sample size is to combine existing cohorts, which may have limited sample size or be case-only, with public controls, but this approach is limited by the need for a large overlap in variants across genotyping arrays and the scarcity of non-European controls. We developed and validated a protocol, Genotyping Array-WGS Merge (GAWMerge), for combining genotypes from arrays and whole-genome sequencing, ensuring complete variant overlap, and allowing for diverse samples like Trans-Omics for Precision Medicine to be used. Our protocol involves phasing, imputation, and filtering. We illustrated its ability to control technology driven artifacts and type-I error, as well as recover known disease-associated signals across technologies, independent datasets, and ancestries in smoking-related cohorts. GAWMerge enables genetic studies to leverage existing cohorts to validly increase sample size and enhance discovery for understudied traits and ancestries

    Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function.

    Get PDF
    BACKGROUND: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function. METHODS: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis. RESULTS: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10(-7)). In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively. CONCLUSIONS: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function

    Clinical, environmental, and genetic risk factors for substance use disorders : characterizing combined effects across multiple cohorts

    Get PDF
    Substance use disorders (SUDs) incur serious social and personal costs. The risk for SUDs is complex, with risk factors ranging from social conditions to individual genetic variation. We examined whether models that include a clinical/environmental risk index (CERI) and polygenic scores (PGS) are able to identify individuals at increased risk of SUD in young adulthood across four longitudinal cohorts for a combined sample of N = 15,134. Our analyses included participants of European (N-EUR = 12,659) and African (N-AFR = 2475) ancestries. SUD outcomes included: (1) alcohol dependence, (2) nicotine dependence; (3) drug dependence, and (4) any substance dependence. In the models containing the PGS and CERI, the CERI was associated with all three outcomes (ORs = 01.37-1.67). PGS for problematic alcohol use, externalizing, and smoking quantity were associated with alcohol dependence, drug dependence, and nicotine dependence, respectively (OR = 1.11-1.33). PGS for problematic alcohol use and externalizing were also associated with any substance dependence (ORs = 1.09-1.18). The full model explained 6-13% of the variance in SUDs. Those in the top 10% of CERI and PGS had relative risk ratios of 3.86-8.04 for each SUD relative to the bottom 90%. Overall, the combined measures of clinical, environmental, and genetic risk demonstrated modest ability to distinguish between affected and unaffected individuals in young adulthood. PGS were significant but added little in addition to the clinical/environmental risk index. Results from our analysis demonstrate there is still considerable work to be done before tools such as these are ready for clinical applications.Peer reviewe

    Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations.

    Get PDF
    Asthma is a common disease with a complex risk architecture including both genetic and environmental factors. We performed a meta-analysis of North American genome-wide association studies of asthma in 5,416 individuals with asthma (cases) including individuals of European American, African American or African Caribbean, and Latino ancestry, with replication in an additional 12,649 individuals from the same ethnic groups. We identified five susceptibility loci. Four were at previously reported loci on 17q21, near IL1RL1, TSLP and IL33, but we report for the first time, to our knowledge, that these loci are associated with asthma risk in three ethnic groups. In addition, we identified a new asthma susceptibility locus at PYHIN1, with the association being specific to individuals of African descent (P = 3.9 × 10(-9)). These results suggest that some asthma susceptibility loci are robust to differences in ancestry when sufficiently large samples sizes are investigated, and that ancestry-specific associations also contribute to the complex genetic architecture of asthma

    ADAM19 and HTR4 Variants and Pulmonary Function: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study

    Get PDF
    The pulmonary function measures of forced expiratory volume in one second (FEV1) and its ratio to forced vital capacity (FVC) are used in the diagnosis and monitoring of lung diseases and predict cardiovascular mortality in the general population. Genome wide association studies (GWAS) have identified numerous loci associated with FEV1 and FEV1/FVC but the causal variants remain uncertain. We hypothesized that novel or rare variants poorly tagged by GWAS may explain the significant associations between FEV1/FVC and two genes: ADAM19 and HTR4

    Meta-analysis across Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium provides evidence for an association of serum vitamin D with pulmonary function

    Get PDF
    The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for serum 25-hydroxyvitamin D (25(OH)D)-pulmonary function association. We conducted the largest cross-sectional meta-analysis of the 25(OH)D-pulmonary function association to date, based on nine European ancestry (EA) cohorts (n 22 838) and five African ancestry (AA) cohorts (n 4290) in the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. Data were analysed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean serum 25(OH)D was 68 (SD 29) nmol/l for EA and 49 (SD 21) nmol/l for AA. For each 1 nmol/l higher 25(OH)D, forced expiratory volume in the 1st second (FEV1) was higher by 1.1 ml in EA (95 % CI 0.9, 1.3; P< 0.0001) and 1.8 ml (95 % CI 1.1, 2.5; P< 0.0001) in AA (P-race (difference) = 0.06), and forced vital capacity (FVC) was higher by 1.3 ml in EA (95 % CI 1.0, 1.6; P <0.0001) and 1.5 ml (95 % CI 0.8, 2.3; P= 0.0001) in AA (P-race difference = 0.56). Among EA, the 25(OH)D-FVC association was stronger in smokers: per 1 nmol/l higher 25(OH) D, FVC was higher by 1.7 ml (95 % CI 1.1, 2.3) for current smokers and 1.7 ml (95 % CI 1.2, 2.1) for former smokers, compared with 0.8 ml (95 % CI 0.4, 1.2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EA, a stronger association was observed for smokers compared with never smokers, which supports the importance of vitamin D in vulnerable populations

    Integration of evidence across human and model organism studies: A meeting report.

    Get PDF
    The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting\u27s objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and \u27omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration-particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs

    Integrative pathway genomics of lung function and airflow obstruction

    Get PDF
    Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10's role in influencing lung's susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung diseas
    • …
    corecore