Alpha-1 antitrypsin gene polymorphism in Chronic Obstructive Pulmonary Disease (COPD).
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ABSTRACT:
SUBMITTER: Denden S
PROVIDER: S-EPMC3036098 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Chronic obstructive pulmonary disease (COPD) Metagenome
| PRJNA647843 | ENA
Project description:Measuring genome-wide changes in transcript abundance in circulating peripheral whole blood cells is a useful way to study disease pathobiology and may help elucidate biomarkers and molecular mechanisms of disease. The sensitivity and interpretability of analyses carried out in this complex tissue, however, are significantly affected by its heterogeneity. It is therefore desirable to quantify this heterogeneity, either to account for it or to better model interactions that may be present between the abundance of certain transcripts, some cell types and some indication. Accurate enumeration of the many component cell types that make up peripheral whole blood can be costly, however, and may further complicate the sample collection process. Many approaches have been developed to infer the composition of a sample from high-dimensional transcriptomic and, more recently, epigenetic data. These approaches rely on the availability of isolated expression profiles for the cell types to be enumerated. These profiles are platform-specific, suitable datasets are rare, and generating them is expensive. No such dataset exists on the Affymetrix Gene ST platform. We present a freely-available, and open-source, multiresponse Gaussian model capable of accurately inferring the composition of peripheral whole blood samples from Affymetrix Gene ST expression profiles. The model was developed on a cohort of patients with chronic obstructive pulmonary disease (COPD) and tested in chronic heart failure patients.
2016-05-25 | GSE77344 | GEO
Project description:Chronic Obstructive Pulmonary Disease (COPD) patient microbiome
| PRJEB46960 | ENA
Project description:RationaleAlpha-1 antitrypsin deficiency, caused primarily by homozygosity for the Z allele of the SERPINA1 gene, is a well-established genetic cause of chronic obstructive pulmonary disease (COPD). Whether the heterozygous PiMZ genotype for alpha-1 antitrypsin confers increased risk for COPD has been debated.ObjectivesWe analyzed 8,271 subjects in the Genetic Epidemiology of COPD (COPDGene) Study, hypothesizing that PiMZ would independently associate with COPD and COPD-related phenotypes.MethodsThe COPDGene Study comprises a multiethnic, cross-sectional, observational cohort of non-Hispanic white and African American current and former smokers with at least 10 pack-years of smoking who were enrolled for detailed clinical and genetic studies of COPD and COPD-related traits. We performed multivariate logistic regression analysis for moderate to severe COPD and assessed Pi genotype with other relevant covariates in models stratified by race. We analyzed quantitative characteristics on the basis of volumetric computed tomography with generalized linear models controlling for genotype, scanner type, and similar covariates.ResultsWhite PiMZ COPDGene subjects had significantly lower lung function, FEV1 percent predicted (68 ± 28 vs. 75 ± 27; P = 0.0005), and FEV1/FVC ratio (0.59 ± 0.18 vs. 0.63 ± 0.17; P = 0.0008), as well as more radiographic emphysema (P = 0.001), than subjects without alpha-1 antitrypsin Z risk alleles. Similarly, African American PiMZ subjects had lower lung function, FEV1 percent predicted (65 ± 33 vs. 84 ± 25; P = 0.009) and FEV1/FVC (0.61 ± 0.21 vs. 0.71 ± 0.15; P = 0.03).ConclusionsIn the COPDGene Study, we demonstrate that PiMZ heterozygous individuals who smoke are at increased risk for COPD and obstructive lung function impairment compared with Z-allele noncarriers, regardless of race. Although severe alpha-1 antitrypsin deficiency is uncommon in African Americans, our study adds further support for initial targeted detection of all subjects with COPD for alpha-1 antitrypsin deficiency, including African Americans. Clinical trial registered with www.clinicaltrials.gov (NCT00608784).
| S-EPMC5566271 | biostudies-literature
Project description:Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disease with complex pathological features and largely unknown etiologies. Identification and validation of biomarkers for this disease could facilitate earlier diagnosis, appreciation of disease subtypes and/or determination of response to therapeutic intervention. To identify gene expression markers for COPD, we performed genome-wide expression profiling of lung tissue from 56 subjects using the Affymetrix U133 Plus 2.0 array. Lung function measurements from these subjects ranged from normal, un-obstructed to severely obstructed. Analysis of differential expression between cases (FEV1<70%, FEV1/FVC<0.7) and controls (FEV1>80%, FEV1/FVC>0.7) identified a set of 65 probe sets representing discrete markers associated with COPD. Correlation of gene expression with quantitative measures of airflow obstruction (FEV1 or FEV1/FVC) identified a set of 220 probe sets. A total of 31 probe sets were identified that showed evidence of significant correlation with quantitative traits and differential expression between cases and controls. Keywords: Disease state marker
2008-05-31 | GSE8581 | GEO
Project description:Chronic obstructive pulmonary disease (COPD) is a common chronic disease, and its morbidity and mortality are increasing. There are many studies that have tried to explain the pathogenesis of COPD from genetic susceptibility, to identify the susceptibility of COPD factors, which play a role in early prevention, early detection and the early treatment. However, it is well known that COPD is an inflammatory disease characterized by incomplete reversible airflow limitation in which genes interact with the environment. In recent years, many studies have proved gene polymorphisms and COPD correlation. However, there is less research on the relationship between COPD and genome-wide association study (GWAS), epigenetics and apoptosis. In this paper, we summarized the correlation between gene level and COPD from the following four aspects: the GWAS, the gene polymorphism, the epigenetics and the apoptosis, and the relationship between COPD and gene is summarized comprehensively.
| S-EPMC5436778 | biostudies-literature
Project description:BackgroundAlpha-1 Antitrypsin (AAT) deficiency (AATD), the most common genetic cause of emphysema presents with unexplained phenotypic heterogeneity in affected subjects. Our objectives to identify unique and shared AATD plasma biomarkers with chronic obstructive pulmonary disease (COPD) may explain AATD phenotypic heterogeneity.MethodsThe plasma or serum of 5,924 subjects from four AATD and COPD cohorts were analyzed on SomaScan V4.0 platform. Using multivariable linear regression, inverse variance random-effects meta-analysis, and Least Absolute Shrinkage and Selection Operator (LASSO) regression we tested the association between 4,720 individual proteins or combined in a protein score with emphysema measured by 15th percentile lung density (PD15) or diffusion capacity (DLCO) in distinct AATD genotypes (Pi*ZZ, Pi*SZ, Pi*MZ) and non-AATD, PiMM COPD subjects. AAT SOMAmer accuracy for identifying AATD was tested using receiver operating characteristic curve analysis.FindingsIn PiZZ AATD subjects, 2 unique proteins were associated with PD15 and 98 proteins with DLCO. Of those, 68 were also associated with DLCO in COPD also and enriched for three cellular component pathways: insulin-like growth factor, lipid droplet, and myosin complex. PiMZ AATD subjects shared similar proteins associated with DLCO as COPD subjects. Our emphysema protein score included 262 SOMAmers and predicted emphysema in AATD and COPD subjects. SOMAmer AAT level <7.99 relative fluorescence unit (RFU) had 100% sensitivity and specificity for identifying Pi*ZZ, but it was lower for other AATD genotypes.InterpretationUsing SomaScan, we identified unique and shared plasma biomarkers between AATD and COPD subjects and generated a protein score that strongly associates with emphysema in COPD and AATD. Furthermore, we discovered unique biomarkers associated with DLCO and emphysema in PiZZ AATD.FundingThis work was supported by a grant from the Alpha-1 Foundation to RPB. COPDGene was supported by Award U01 HL089897 and U01 HL089856 from the National Heart, Lung, and Blood Institute. Proteomics for COPDGene was supported by NIH 1R01HL137995. GRADS was supported by Award U01HL112707, U01 HL112695 from the National Heart, Lung, and Blood Institute, and UL1TRR002535 to CCTSI; QUANTUM-1 was supported by the National Heart Lung and Blood Institute, the Office of Rare Diseases through the Rare Lung Disease Clinical Research Network (1 U54 RR019498-01, Trapnell PI), and the Alpha-1 Foundation. COPDGene is also supported by the COPD Foundation through contributions made to an Industry Advisory Board that has included AstraZeneca, Bayer Pharmaceuticals, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer, and Sunovion.
| S-EPMC9507992 | biostudies-literature
Project description:BackgroundAlpha-1 antitrypsin deficiency (AATD) is an often-overlooked genetic condition that makes individuals susceptible to early onset of chronic obstructive pulmonary disease (COPD). The established benefits of exercise-based pulmonary rehabilitation (PR) for usual COPD patients are unclear for those with underlying AATD, especially given potentially differing muscle adaptations to exercise. This review seeks to compare PR outcomes between AATD and usual COPD patients and to consolidate current knowledge on exercise intervention outcomes for the AATD population.MethodsA thorough search of 4 databases (Ovid, Medline, CINAHL, CENTRAL) was conducted based on 3 search concepts: (1) alpha-1 antitrypsin deficiency, (2) pulmonary rehabilitation OR exercise, and (3) muscle morphology. A dual review process and quality assessment were independently implemented throughout all stages of the review.ResultsFour studies highlighted modest exercise capacity and quality of life in AATD patients undergoing PR. However, one study reported unique muscle and mitochondrial responses compared to usual COPD patients. Additionally, a moderate exercise session did not alter pro-inflammatory cytokine levels in AATD patients, despite higher levels of tumor necrosis factor-α levels in muscle biopsies compared to usual COPD patients.ConclusionsThe current literature base insufficiently addresses the efficacy of PR on AATD, with indications that exercise adaptation may deviate from that of usual COPD patients. Further research is needed to optimize PR, particularly in identifying the most suitable exercise intensity, and delivery setting, and addressing specific educational needs for individuals with AATD.
| S-EPMC10913928 | biostudies-literature
Project description:Diaphragm muscles in Chronic Obstructive Pulmonary Disease (COPD) patients undergo an adaptive fast to slow transformation that includes cellular adaptations. This project studies the signaling mechanisms responsible for this transformation. Keywords: other
2003-07-16 | GSE475 | GEO
Project description:Background: Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD, thus the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Methods: Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Results: Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, Random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. Conclusion: We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.
2022-10-17 | PXD035120 | Pride