Genetic Epidemiology of COPD (COPDGene) Genetic Analysis
Ontology highlight
ABSTRACT:
SECONDARY ACCESSION(S): PRJNA253345
REPOSITORIES: dbGaP
Similar Datasets
Project description:COPDGene is a multicenter observational study designed to identify genetic factors associated with COPD. It will also characterize chest CT phenotypes in COPD subjects, including assessment of emphysema, gas trapping, and airway wall thickening. Finally, subtypes of COPD based on these phenotypes will be used in a comprehensive genome-wide study to identify COPD susceptibility genes.COPDGene will enroll 10,000 smokers with and without COPD across the GOLD stages. Both Non-Hispanic white and African-American subjects are included in the cohort. Inspiratory and expiratory chest CT scans will be obtained on all participants. In addition to the cross-sectional enrollment process, these subjects will be followed regularly for longitudinal studies. A genome-wide association study (GWAS) will be done on an initial group of 4000 subjects to identify genetic variants associated with case-control status and several quantitative phenotypes related to COPD. The initial findings will be verified in an additional 2000 COPD cases and 2000 smoking control subjects, and further validation association studies will be carried out.COPDGene will provide important new information about genetic factors in COPD, and will characterize the disease process using high resolution CT scans. Understanding genetic factors and CT phenotypes that define COPD will potentially permit earlier diagnosis of this disease and may lead to the development of treatments to modify progression.
| S-EPMC2924193 | biostudies-literature
Project description:NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene)
| PRJNA289174 | ENA
Project description:Various comorbidities and multimorbidity frequently occur in chronic obstructive pulmonary disease (COPD), leading to the overload of health care systems and increased mortality. We aimed to assess the impact of COPD on the probability and clustering of comorbidities. The cross-sectional analysis of the nationwide Lithuanian database was performed based on the entries of the codes of chronic diseases. COPD was defined on the code J44.8 entry and six-month consumption of bronchodilators. Descriptive statistics and odds ratios (ORs) for associations and agglomerative hierarchical clustering were carried out. 321,297 patients aged 40-79 years were included; 4834 of them had COPD. A significantly higher prevalence of cardiovascular diseases (CVD), lung cancer, kidney diseases, and the association of COPD with six-fold higher odds of lung cancer (OR 6.66; p < 0.0001), a two-fold of heart failure (OR 2.61; p < 0.0001), and CVD (OR 1.83; p < 0.0001) was found. Six clusters in COPD males and five in females were pointed out, in patients without COPD-five and four clusters accordingly. The most prevalent cardiovascular cluster had no significant difference according to sex or COPD presence, but a different linkage of dyslipidemia was found. The study raises the need to elaborate adjusted multimorbidity case management and screening tools enabling better outcomes.
| S-EPMC8775709 | biostudies-literature
Project description:Airflow limitation in COPD patients is not fully reversible. However, there may be large variability in bronchodilator responsiveness (BDR) among COPD patients, and familial aggregation of BDR suggests a genetic component. Therefore, we investigated the association between six candidate genes and BDR in subjects with severe COPD. A total of 389 subjects from the National Emphysema Treatment Trial (NETT) were analyzed. Bronchodilator responsiveness to albuterol was expressed in three ways: absolute change in FEV(1), change in FEV(1) as a percent of baseline FEV(1), and change in FEV(1) as a percent of predicted FEV(1). Genotyping was completed for 122 single nucleotide polymorphisms (SNPs) in six candidate genes (EPHX1, SFTPB, TGFB1, SERPINE2, GSTP1, ADRB2). Associations between BDR phenotypes and SNP genotypes were tested using linear regression, adjusting for age, sex, pack-years of smoking, and height. Genes associated with BDR phenotypes in the NETT subjects were assessed for replication in 127 pedigrees from the Boston Early-Onset COPD (EOCOPD) Study. Three SNPs in EPHX1 (p=0.009-0.04), three SNPs in SERPINE2 (p=0.004-0.05) and two SNPs in ADRB2 (0.04-0.05) were significantly associated with BDR phenotypes in NETT subjects. One SNP in EPHX1 (rs1009668, p=0.04) was significantly replicated in EOCOPD subjects. SNPs in SFTPB, TGFB1, and GSTP1 genes were not associated with BDR. In conclusion, a polymorphism of EPHX1 was associated with bronchodilator responsiveness phenotypes in subjects with severe COPD.
| S-EPMC2745950 | biostudies-literature
Project description:Cigarette smoking is the principal environmental risk factor for developing COPD, and nicotine dependence strongly influences smoking behavior. This study was performed to elucidate the relationship between nicotine dependence, genetic susceptibility to nicotine dependence, and volumetric CT findings in smokers.Current smokers with COPD (GOLD stage ? 2) or normal spirometry were analyzed from the COPDGene Study, a prospective observational study. Nicotine dependence was determined by the Fagerstrom test for nicotine dependence (FTND). Volumetric CT acquisitions measuring the percent of emphysema on inspiratory CT (% of lung <-950 HU) and gas trapping on expiratory CT (% of lung <-856 HU) were obtained. Genotypes for two SNPs in the CHRNA3/5 region (rs8034191, rs1051730) previously associated with nicotine dependence and COPD were analyzed for association to COPD and nicotine dependence phenotypes.Among 842 currently smoking subjects (335 COPD cases and 507 controls), 329 subjects (39.1%) showed high nicotine dependence. Subjects with high nicotine dependence had greater cumulative and current amounts of smoking. However, emphysema severity was negatively correlated with the FTND score in controls (? = -0.19, p < .0001) as well as in COPD cases (? = -0.18, p = 0.0008). Lower FTND score, male gender, lower body mass index, and lower FEV1 were independent risk factors for emphysema severity in COPD cases. Both CHRNA3/5 SNPs were associated with FTND in current smokers. An association of genetic variants in CHRNA3/5 with severity of emphysema was only found in former smokers, but not in current smokers.Nicotine dependence was a negative predictor for emphysema on CT in COPD and control smokers. Increased inflammation in more highly addicted current smokers could influence the CT lung density distribution, which may influence genetic association studies of emphysema phenotypes.
| S-EPMC3033825 | biostudies-literature
Project description:Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. COPD is thought to arise from the interaction of environmental exposures and genetic susceptibility, and major research efforts are underway to identify genetic determinants of COPD susceptibility. With the exception of SERPINA1, genetic associations with COPD identified by candidate gene studies have been inconsistently replicated, and this literature is difficult to interpret. We conducted a systematic review and meta-analysis of all population-based, case-control candidate gene COPD studies indexed in PubMed before 16 July 2008. We stored our findings in an online database, which serves as an up-to-date compendium of COPD genetic associations and cumulative meta-analysis estimates. On the basis of our systematic review, the vast majority of COPD candidate gene era studies are underpowered to detect genetic effect odds ratios of 1.2-1.5. We identified 27 genetic variants with adequate data for quantitative meta-analysis. Of these variants, four were significantly associated with COPD susceptibility in random effects meta-analysis, the GSTM1 null variant (OR 1.45, CI 1.09-1.92), rs1800470 in TGFB1 (0.73, CI 0.64-0.83), rs1800629 in TNF (OR 1.19, CI 1.01-1.40) and rs1799896 in SOD3 (OR 1.97, CI 1.24-3.13). In summary, most COPD candidate gene era studies are underpowered to detect moderate-sized genetic effects. Quantitative meta-analysis identified four variants in GSTM1, TGFB1, TNF and SOD3 that show statistically significant evidence of association with COPD susceptibility.
| S-EPMC2798725 | biostudies-literature
Project description:Psoriasis is a chronic, inflammatory, immune-mediated skin condition with a prevalence of 0-11.8% across the world. It is associated with a number of cardiovascular, metabolic, and autoimmune disease co-morbidities. Psoriasis is a multifactorial disorder, influenced by both genetic and environmental factors. Its genetic basis has long been established through twin studies and familial clustering. The association of psoriasis with the HLA-Cw6 allele has been shown in many studies. Recent genome-wide association studies have identified a large number of other genes associated with psoriasis. Many of these genes regulate the innate and adaptive immune system. These findings indicate that a dysregulated immune system may play a major role in the pathogenesis of psoriasis. In this article, we review the clinical and genetic epidemiology of psoriasis with a brief description of the pathogenesis of disease.
| S-EPMC4285384 | biostudies-literature
Project description:<p>Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. <b>The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease.</b> The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity.</p> <p><b>The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies.</b> To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000179 COPDGene_v6 Cohort. <ul> <li><a href="./study.cgi?study_id=phs000296">phs000296</a> ESP LungGO COPDGene</li> <li><a href="./study.cgi?study_id=phs000765">phs000765</a> COPDGene_Geno</li> </ul> </p>
| phs000179 | dbGaP
Project description:While much attention has been paid to the vulnerability of computer networks to node and link failure, there is limited systematic understanding of the factors that determine the likelihood that a node (computer) is compromised. We therefore collect threat log data in a university network to study the patterns of threat activity for individual hosts. We relate this information to the properties of each host as observed through network-wide scans, establishing associations between the network services a host is running and the kinds of threats to which it is susceptible. We propose a methodology to associate services to threats inspired by the tools used in genetics to identify statistical associations between mutations and diseases. The proposed approach allows us to determine probabilities of infection directly from observation, offering an automated high-throughput strategy to develop comprehensive metrics for cyber-security.
| S-EPMC4100021 | biostudies-other