COPD subtypes identified by network-based clustering of blood gene expression

Chang, Yale; Glass, Kimberly; Liu, Yang‐Yu; Silverman, Edwin K.; Crapo, James D.; Tal‐Singer, Ruth; Bowler, R.P.; Dy, Jennifer G.; Cho, Michael; Castaldi, Peter J.

doi:10.1016/j.ygeno.2016.01.004

Cited by 55 publications

(64 citation statements)

References 43 publications

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“…Genetic variations in the cluster on chromosome 15, encoding the nicotinic acetylcholine receptor subunits (CHRNA5-CHRNA3-CHRNB4), are correlated with tobacco addiction and increased risk of COPD, peripheral artery disease, lung cancer and obesity [6,7,8]. Different studies on lung tissue and peripheral blood identified increased expression of genes related to inflammatory pathways and immune regulation [9]. More studies are warranted to recognize those genes and pathways occurring in COPD.…”

Section: Introductionmentioning

confidence: 99%

Metabolic Disorder in Chronic Obstructive Pulmonary Disease (COPD) Patients: Towards a Personalized Approach Using Marine Drug Derivatives

et al. 2017

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Metabolic disorder has been frequently observed in chronic obstructive pulmonary disease (COPD) patients. However, the exact correlation between obesity, which is a complex metabolic disorder, and COPD remains controversial. The current study summarizes a variety of drugs from marine sources that have anti-obesity effects and proposed potential mechanisms by which lung function can be modulated with the anti-obesity activity. Considering the similar mechanism, such as inflammation, shared between obesity and COPD, the study suggests that marine derivatives that act on the adipose tissues to reduce inflammation may provide beneficial therapeutic effects in COPD subjects with high body mass index (BMI).

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Section: Introductionmentioning

confidence: 99%

Metabolic Disorder in Chronic Obstructive Pulmonary Disease (COPD) Patients: Towards a Personalized Approach Using Marine Drug Derivatives

et al. 2017

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“…In some studies, a higher BMI was associated with a cluster that had higher mortality and inflammation [25] as well as overall comorbidity burden [26]. Yet, another study using gene interaction networks to define COPD clusters based on inflammation-influenced genetic profiles showed no significant difference in BMI across groups [27]. Our path analysis also shows conflicting data with BMI having both a negative and an indirect positive relationship with emphysema progression.…”

Section: Discussionmentioning

confidence: 62%

Mediastinal and Subcutaneous Chest Fat Are Differentially Associated with Emphysema Progression and Clinical Outcomes in Smokers

Grace¹,

Leader²,

Nouraie³

et al. 2017

Respiration

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Background: Studies have demonstrated both positive and negative effects of obesity on clinical outcomes in chronic obstructive pulmonary disease (COPD). In other chronic diseases, fat location is differentially associated with disease outcomes; however, this relationship has not been well studied in COPD. Objective: To determine if fat location explains the differential association of body mass index (BMI) with clinical outcome measures in smokers. Methods: Baseline and 6-year chest computed tomography scans from 68 current and former smokers were used to quantify mediastinal and subcutaneous fat. The relationships of BMI, mediastinal fat, and subcutaneous fat with cross-sectional and 6-year changes in pulmonary function, incremental shuttle walk distance (ISWD), quantitative emphysema, and circulating interleukin-6 (IL-6) and C-reactive protein (CRP) levels were assessed using generalized linear models adjusted for clinically relevant covariates. Results: Baseline subcutaneous fat was negatively associated with emphysema progression over 6 years (p < 0.01). BMI and mediastinal fat volume were inversely associated with baseline ISWD (p < 0.01 and p = 0.043, respectively) as well as 6-year change in ISWD (p = 0.020 and p = 0.028, respectively). IL-6 was directly associated with BMI and mediastinal fat (p < 0.01) and CRP was directly associated with BMI only (p = 0.033). Conclusions: Increased subcutaneous chest fat is associated with less emphysema progression over time in smokers, while increased mediastinal fat volume is associated with decreased walk distance and increased IL-6 levels. These findings suggest a complex interaction between fat, inflammation, and emphysema that should be considered when phenotyping patients with COPD and provide new evidence of an inverse association between emphysema progression and chest subcutaneous fat.

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“…The resulting contingency table is subsequently used to quantify the enrichment level (by computing the log odds ratio) and testing enrichment (by a chi-squared test or a Fisher's exact test) for a particular gene set. This method has also been widely applied in the recent literature of genomics and complex disease studies (Richiardi et al, 2015;Walter et al, 2015;Chang et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

BAGSE: a Bayesian hierarchical model approach for gene set enrichment analysis

Hukku

Quick

Luca

et al. 2019

Preprint

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Gene set enrichment analysis has been shown to be effective in identifying relevant biological pathways underlying complex diseases. Existing approaches lack the ability to quantify the enrichment levels accurately, hence preventing the enrichment information to be further utilized in both upstream and downstream analyses. A modernized and rigorous approach for gene set enrichment analysis that emphasizes both hypothesis testing and enrichment estimation is much needed. We propose a novel computational method, Bayesian Analysis of Gene Set Enrichment (BAGSE), for gene set enrichment analysis. BAGSE is built on a Bayesian hierarchical model and fully accounts for the uncertainty embedded in the association evidence of individual genes. We adopt an empirical Bayes inference framework to fit the proposed hierarchical model by implementing an efficient EM algorithm. Through simulation studies, we illustrate that BAGSE yields accurate enrichment quantification while achieving similar power as the state-of-the-art methods. Further simulation studies show that BAGSE can effectively utilize the enrichment information to improve the power in gene discovery. Finally, we demonstrate the application of BAGSE in analyzing real data from a differential expression experiment and a Transcriptome-wide Association Study (TWAS). Our results indicate that the proposed statistical framework is effective in aiding the discovery of potentially causal pathways and gene networks. BAGSE is implemented using the C++ programming language and is freely available from https://github.com/xqwen/bagse/.

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COPD subtypes identified by network-based clustering of blood gene expression

Cited by 55 publications

References 43 publications

Metabolic Disorder in Chronic Obstructive Pulmonary Disease (COPD) Patients: Towards a Personalized Approach Using Marine Drug Derivatives

Metabolic Disorder in Chronic Obstructive Pulmonary Disease (COPD) Patients: Towards a Personalized Approach Using Marine Drug Derivatives

Mediastinal and Subcutaneous Chest Fat Are Differentially Associated with Emphysema Progression and Clinical Outcomes in Smokers

BAGSE: a Bayesian hierarchical model approach for gene set enrichment analysis

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