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.

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.

Inclusion Criteria:

1. Patient has signed informed consent.
2. Patients diagnosed with COPD or fully healthy participants.

Exclusion Criteria:

1. Tumor disease.
2. Heart disease.
3. Thyroid disease.

COPD patients and healthy people.