The Individualized Accurate Diagnosis and Treatment of Chronic Objective Pulmonary Disease(COPD) Patients Based on Multidimensional Data

Study Overview
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Brief Summary
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Chronic obstructive pulmonary disease (COPD) is known as progressive lung disease and the fourth leading cause of death worldwide. Despite valuable efforts, there is still no Individualized accurate diagnostic and prognostic tool for COPD. Hence, the investigators' research integrated multi-dimensional data of COPD patients, which may provide an invaluable bioinformatic resource for understanding the underlying molecular alterations that drive disease progression, with the goal of developing individualized accurate diagnostic and therapeutic inventions.

Detailed Description
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Chronic obstructive pulmonary disease (COPD) is known as progressive lung disease and the fourth leading cause of death worldwide. Acute exacerbations of COPD (AECOPD) is an important event of disease progression worsening in airway function and respiratory symptoms, bringing about respiratory failure, and increasing the rates of mortality. Despite valuable efforts, there is still no Individualized accurate diagnostic and prognostic tool for COPD. In this context, the investigators are to perform comprehensive transcriptomic, proteomic, metabonomic and exosome characterization of COPD patients and healthy controls. Biological samples of COPD participants, including blood, urine, stool, saliva, bronchoalveolar lavage fluid and clinical characteristics are going to be collected from the remaining materials of the routine clinical examination. And samples of healthy controls will be collected from the rest of the healthy examination practice. By integrating the multi-dimensional data, the investigators aim to elucidate the impact of molecular alterations driving phenotypic variation and to delineate the mechanisms of AECOPD for prospective exploration of personalized, precision-based clinical care.

Official Title
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The Individualized Accurate Diagnosis and Treatment, as Well as the Prevention of Acute Exacerbation of Chronic Objective Pulmonary Disease(COPD) Based on Multidimensional Data

Conditions
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Copd, Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patient has signed informed consent. Patients diagnosed with COPD or fully healthy participants. Exclusion Criteria: Tumor disease. Heart disease. Thyroid disease.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 90 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| SCOPD<br>Participants with stable COPD diagnosed according to GOLD criteria and hasn't encountered acute exacerbations in the past six months, generally include outpatient clinical patient and community patients. | |
| AECOPD<br>Participants with COPD diagnosed according to GOLD criteria and suffered from acute exacerbations, characterized by worsening clinical symptoms(such as acute worsening of dyspnea, and/or cough and sputum production, and/or increased sputum purulence) and positive laboratory biomarkers suggesting AECOPD (such as serum CRP and serum neutrophilia or eosinophilia) at the time of registering into the group, particularly include inpatient. | |
| Smoking healthy controls<br>Participants with a smoking history of more than ten years and was in good health, characterized by negative chest radiograph and negative laboratory tests for cardiac, pulmonary or hematologic disorders, and so on. | |
| Non smoking healthy controls<br>Participants without a smoking history and was in good health, characterized by negative chest radiograph and negative laboratory tests for cardiac, pulmonary or hematologic disorders, and so on. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The transcriptome analysis of participates' serum or plasma | Include the transcriptome data of serum，plasma or exosomes inside | through study completion, an average of 1 year | 
| The metabolomics analysis of participates' urine or stool | Predominately include metabolic target analysis, metabolic profiling analysis | through study completion, an average of 1 year | 
| The proteomics analysis of bronchoalveolar lavage fluid and saliva | Differentially expressed proteins between SCOPD and AECOPD which associated with disease progression were analyesd | through study completion, an average of 1 year |