Foundry120 atlas

Single-cell transcriptomics reveal cell type-specific molecular changes and altered intercellular communications in chronic obstructive pulmonary disease

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Dataset overview

Participants None
Samples 9
Reuse readiness 6.3/10 evidence-backed score

Single-cell transcriptomics highlights immunological dysregulations of monocytes in the pathobiology of COPD.

Abstract

<h4>Background</h4>Chronic obstructive pulmonary disease (COPD) is a common respiratory disease, whose pathogenetic complexity was strongly associated with aging/smoking and poorly understood.<h4>Methods</h4>Here we performed single-cell RNA sequencing (scRNA-seq) analysis of 66,610 cells from COPD and age-stratified control lung tissues of donors with different smoking histories to prioritize cell types most perturbed in COPD lungs in aging/smoking dependent or independent manner. By performing an array of advanced bioinformatic analyses, such as gene set enrichment analysis, trajectory analysis, cell-cell interactions analysis, regulatory potential analysis, weighted correlation network analysis, functional interaction analysis, and gene set variation analysis, we integrated cell-type-level alterations into a system-level malfunction and provided a more clarified COPD pathological model containing specific mechanisms by which aging and smoking facilitate COPD development. Finally, we integrated the publicly available scRNA-seq data of 9 individuals, resulting in a total of 110,931 cells, and replicated the analyses to enhance the credibility of our findings.<h4>Results</h4>Our study pointed to enrichment of COPD molecular alteration in monocytes, which further induced a previously unrecognized pro-inflammatory effect on alveolar epithelial cells. In addition, aged monocytes and club cells facilitated COPD development via maintaining an autoimmune airway niche. Unexpectedly, macrophages, whose defect to resolve inflammation was long-recognized in COPD pathogenesis, primarily induced an imbalance of sphingolipids rheostat in a smoking-dependent way. These findings were validated in a meta-analysis including other public single-cell transcriptomic data.<h4>Conclusions</h4>In sum, our study provided a clarified view of COPD pathogenesis and demonstrated the potential of targeting monocytes in COPD diagnosis and treatment.

Study facts

Organism
Homo sapiens
Platform
BD Rhapsody
Age group
adult
Disease groups
Anatomical sites
lung

Data availability

  • Raw counts
  • Processed matrix

File types TXT

Files and samples

Strengths & limitations for reuse

Strengths

  • Raw reads are advertised
  • Raw counts are advertised
  • Processed matrices are advertised
  • Cell metadata are advertised

Limitations

  • Not documented: participant counts are documented
Extraction evidence & provenance

Each extracted field is shown with the source excerpt and location used to resolve it.

Assay

FieldValueEvidence
assay.assay_type single-cell RNA sequencing
single-cell RNA sequencing (scRNA-seq) analysis

Section abstract, offset —

assay.library_chemistry BD Rhapsody WTA Amplification Kit
scRNA-seq libraries were constructed using BD Rhapsody™ WTA Amplification Kit (BD, 633801)

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assay.platform BD Rhapsody
scRNA-seq libraries were constructed using BD Rhapsody™ WTA Amplification Kit (BD, 633801)

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assay.reference_genome GENCODE v29
Genome_build: GENCODE v29

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assay.sequencing_type scrna_seq
single-cell RNA-seq analysis for lung of COPD and age-stratified control lung tissues of donors with different smoking histories

Section , offset —

Cohort

FieldValueEvidence
cohort.age_group adult from source
GEO age characteristics: 63; 73; 50; 73; 71; 75; 28; 35; 27

Section GEO family SOFT, offset —

Data_Assets

FieldValueEvidence
data_assets.cell_metadata True
GSE171541_CellType_Metadata.txt.gz

Section , offset —

data_assets.open_access True
"ftplink": "ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE171nnn/GSE171541/"

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data_assets.participant_metadata True
"age": "63", "group": "smoker", "tissue": "lung", "disease": "COPD"

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data_assets.processed_matrix True
Supplementary_files_format_and_content: tab-delimited text files include expression matrix and cell type metadata

Section , offset —

data_assets.raw_counts True
GSE171541_UMI_count.txt.gz

Section , offset —

data_assets.raw_reads True
SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRP313634

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Processing

FieldValueEvidence
processing.quality_control_reported True
Cells filtered with < 301 expressed genes or > 30% UMIs originating from mitochondrial

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Specimens

FieldValueEvidence
specimens.anatomical_sites ['lung']
"tissue": "lung"

Section , offset —

specimens.number_of_cells 66610
analysis of 66,610 cells from COPD and age-stratified control lung tissues

Section abstract, offset —

specimens.number_of_samples 9
"n_samples": 9

Section , offset —