Compartmental Analysis of Metabolite Profiles Associated With Disease Phenotype in Smokers With and Without Chronic Obstructive Pulmonary Disease
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 167
- 试验地点
- 1
- 主要终点
- Metabolites that can predict the progress of lung function
研究概览
简要总结
Despite the high prevalence of chronic obstructive pulmonary disease (COPD), there continues to be a large gap in our understanding of disease pathogenesis and mechanisms accounting for large variability in disease phenotype. Untargeted metabolomics is an ideal approach to uncover the metabolic basis of disease, as well as discover unique drug target opportunities aimed at these nodal metabolic drivers of disease. There are very limited data from metabolomics studies from plasma/serum and exhaled breath condensate that suggest certain metabolic pathways or metabolites might predict the presence and/or severity of COPD phenotypes.
Here, the investigators hope to generate comprehensive, compartment specific (blood and lung) metabolite profiles that will be correlated with various clinical phenotypes of COPD, using a complementary approach of untargeted nuclear magnetic resonance (NMR) and liquid chromatography (LC)- mass spectroscopy (MS) -based metabolomics.
详细描述
Despite the high prevalence of chronic obstructive pulmonary disease (COPD), there continues to be a large gap in our understanding of disease pathogenesis and mechanisms accounting for large variability in disease phenotype. Untargeted metabolomics is an ideal approach to uncover the metabolic basis of disease, as well as discover unique drug target opportunities aimed at these nodal metabolic drivers of disease. There are very limited data from metabolomics studies from plasma/serum and exhaled breath condensate that suggest certain metabolic pathways or metabolites might predict the presence and/or severity of COPD phenotypes.
The investigators hypothesize that: 1) smokers with COPD will have a metabolomics signature that is distinct from healthy non-COPD smokers; 2) this signature will be associated with clinically relevant manifestations of disease (e.g., GOLD classification, PFT).
The availability of biosamples from a well-characterized population of smokers with and without COPD, combined with our established in-house metabolomics expertise, will robustly allow to test these novel hypotheses. The investigators hope to generate comprehensive, compartment specific (blood and lung) metabolite profiles that will be correlated with various clinical phenotypes of COPD, using a complementary approach of untargeted nuclear magnetic resonance (NMR) and liquid chromatography (LC)- mass spectroscopy (MS) -based metabolomics. Moreover, this strategy may identify previously unrecognized metabolic pathways that are dysregulated in COPD. Collectively, these data will be used to direct a prospective clinical study to determine the association between metabolomics signatures and clinical outcomes.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Prospective
入排标准
- 年龄范围
- 40 Years 至 80 Years(Adult, Older Adult)
- 性别
- Male
- 接受健康志愿者
- 否
入选标准
- •males aged 40-80;
- •diagnosed with COPD according to the GOLD guidelines;
- •clinically stable patients without medication changes or exacerbation in two months;
- •smoking history of more than 10 pack years
排除标准
- •diagnosed with unstable cardiovascular diseases, significant renal or hepatic dysfunction or mental incompetence;
- •diagnosed with asthma, active pulmonary tuberculosis, diffuse panbronchiolitis, cystic fibrosis, clinically significant bronchiectasis, exacerbation of COPD or pneumonia in two months;
- •prescribed immunosuppressive medications.
结局指标
主要结局
Metabolites that can predict the progress of lung function
时间窗: 3 months
The study is aimed to investigate the relationship between the metabolites and the progress of lung function in COPD
次要结局
- Metabolites that are associated with inflammatory mediators(3 months)
- Metabolites that can predict the severity of emphysema(3 months)
研究者
Bei He
Professor and Chief in Department of Respiratory Medicine
Peking University Third Hospital
