Identification of molecular subtypes of chronic obstructive pulmonary disease by gene expression profiling
Abstract Background: Chronic obstructive pulmonary disease (COPD) has become the fourth most lethal disease in the world and is expected to rise to the third most lethal disease in the world after 2030.COPD is complex and has clinical heterogeneity. However, identifying the subgroup characteristics of chronic obstructive pulmonary disease has become a challenge.Objectives: In order to delay the progress of COPD patients and improve their quality of life, we can find patients with different treatment goals and formulate different targeted treatment schemes by studying the differences between different subgroups.Methods: We obtained the relevant gene chip by searching the gene expression omnibus (GEO) database. 151 patients with COPD obtained from GEO database were divided into three subgroups by consensus clustering. In order to study the differential gene expression patterns between different subgroups, five subgroup specific weighted gene coexpression analysis modules were determined by weighted gene coexpression analysis (WGCNA).Results: The characteristics of WGCNA module showed that subjects in subgroup I showed airway remodeling characteristics; Subjects in subgroup II showed metabolic activity; Subjects in subgroup III showed inflammatory characteristics.Conclusions: This study obtained the clinical subgroup classification of chronic obstructive pulmonary disease through consensus clustering, and found that patients in different subgroups may have unique gene expression patterns, which can help researchers explore new treatment strategies for COPD according to the characteristics of clinical subgroups..
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Preprint| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
ResearchSquare.com - (2022) vom: 04. Juli Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Pingan, 张平安 Zhang [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.21203/rs.3.rs-1540944/v2 |
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| funding: |
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XRA035959126 |
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| 520 | |a Abstract Background: Chronic obstructive pulmonary disease (COPD) has become the fourth most lethal disease in the world and is expected to rise to the third most lethal disease in the world after 2030.COPD is complex and has clinical heterogeneity. However, identifying the subgroup characteristics of chronic obstructive pulmonary disease has become a challenge.Objectives: In order to delay the progress of COPD patients and improve their quality of life, we can find patients with different treatment goals and formulate different targeted treatment schemes by studying the differences between different subgroups.Methods: We obtained the relevant gene chip by searching the gene expression omnibus (GEO) database. 151 patients with COPD obtained from GEO database were divided into three subgroups by consensus clustering. In order to study the differential gene expression patterns between different subgroups, five subgroup specific weighted gene coexpression analysis modules were determined by weighted gene coexpression analysis (WGCNA).Results: The characteristics of WGCNA module showed that subjects in subgroup I showed airway remodeling characteristics; Subjects in subgroup II showed metabolic activity; Subjects in subgroup III showed inflammatory characteristics.Conclusions: This study obtained the clinical subgroup classification of chronic obstructive pulmonary disease through consensus clustering, and found that patients in different subgroups may have unique gene expression patterns, which can help researchers explore new treatment strategies for COPD according to the characteristics of clinical subgroups. | ||
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