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pmid:36309899

Identification and validation of genetic signature associated with aging in chronic obstructive pulmonary disease.

Shanshan Chen · Yuan Zhan · Jinkun Chen · Jixing Wu · Yiya Gu · Qian Huang · Zhesong Deng · Xiaojie Wu · Yongman Lv · Jungang Xie

Aging · 2022 doi:10.18632/aging.204358

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complete

Experiment

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Data

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Analysis

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title
Identification and validation of genetic signature associated with aging in chronic obstructive pulmonary disease.
doi
10.18632/aging.204358
pmid
36309899
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[0]
Shanshan Chen
[1]
Yuan Zhan
[2]
Jinkun Chen
[3]
Jixing Wu
[4]
Yiya Gu
[5]
Qian Huang
[6]
Zhesong Deng
[7]
Xiaojie Wu
[8]
Yongman Lv
[9]
Jungang Xie
journal
Aging
year
2022
abstract
Aging plays an essential role in the development for chronic obstructive pulmonary disease (COPD). The aim of this study was to identify and validate the potential aging-related genes of COPD through bioinformatics analysis and experimental validation. Firstly, we compared the gene expression profiles of aged and young COPD patients using two datasets (GSE76925 and GSE47460) from Gene Expression Omnibus (GEO), and identified 244 aging-related different expressed genes (DEGs), with 132 up-regulated and 112 down-regulated. Then, by analyzing the data for cigarette smoke-induced COPD mouse model (GSE125521), a total of 783 DEGs were identified between aged and young COPD mice, with 402 genes increased and 381 genes decreased. Additionally, functional enrichment analysis revealed that these DEGs were actively involved in COPD-related biological processes and function pathways. Meanwhile, six genes were identified as the core aging-related genes in COPD after combining the human DEGs and mouse DEGs. Eventually, five out of six core genes were validated to be up-regulated in the lung tissues collected from aged COPD patients than young COPD patients, namely NKG7, CKLF, LRP4, GDPD3 and CXCL9. Thereinto, the expressions of NKG7 and CKLF were negatively associated with lung function. These results may expand the understanding for aging in COPD.
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In order to identify the DEGs between the young and aged groups, the limma R packages (http://www.bioconductor.org/packages) was used to perform the negative binomial distribution method according to the two standard deviations where the absolute value of FC was greater than the median of FC.
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In order to identify the DEGs between the young and aged groups, the limma R packages (http://www.bioconductor.org/packages) was used to perform the negative binomial distribution method according to the two standard deviations where the absolute value of FC was greater than the median of FC.
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To identify the genes associated with aging in COPD patients, two microarray datasets (GSE76925 and GSE47460) were downloaded from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) [50, 51].
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sections[10] "Microarray data acquisition and process" paragraph 2
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To identify the genes associated with aging in COPD patients, two microarray datasets (GSE76925 and GSE47460) were downloaded from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) [50, 51].
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Eventually, five out of six core genes were validated to be up-regulated in the lung tissues collected from aged COPD patients than young COPD patients, namely NKG7, CKLF, LRP4, GDPD3 and CXCL9.
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Eventually, five out of six core genes were validated to be up-regulated in the lung tissues collected from aged COPD patients than young COPD patients, namely NKG7, CKLF, LRP4, GDPD3 and CXCL9.
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Eventually, five out of six core genes were validated to be up-regulated in the lung tissues collected from aged COPD patients than young COPD patients, namely NKG7, CKLF, LRP4, GDPD3 and CXCL9.
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Inhibition of LTβR-signalling blocks epithelial apoptosis and activates endogenous Wnt-induced regeneration
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[581]
GSM1150547
sample_count
582
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null
group_sizes_basis
null
platform
6480;14550
taxon
Homo sapiens
title
Gene expression profiling of chronic lung disease for the Lung Genomics Research Consortium
resolution_checked_at
2026-11-01T17:30:42Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 15 fields
id
data:geo:GSE76925
role
raw
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geo-series
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application/vnd.ncbi.geo-series+json
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE76925
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE76925
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null
note
To identify the genes associated with aging in COPD patients, two microarray datasets (GSE76925 and GSE47460) were downloaded from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) [50, 51].
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
To identify the genes associated with aging in COPD patients, two microarray datasets (GSE76925 and GSE47460) were downloaded from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) [50, 51].
access_statement_kind
repository_route_statement
sample_accessions array · 151 items
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sample_count
151
group_sizes
null
group_sizes_basis
null
platform
10558
taxon
Homo sapiens
title
Functional interactors of genomewide association study genes are differentially expressed in severe chronic obstructive pulmonary disease lung tissue
resolution_checked_at
2026-11-01T17:30:42Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 6 items
[0]
asset:data:geo:GSE125521 not downloaded
[1]
asset:data:geo:GSE125521 licence not read
[2]
asset:data:geo:GSE47460 not downloaded
[3]
asset:data:geo:GSE47460 licence not read
[4]
asset:data:geo:GSE76925 not downloaded
[5]
asset:data:geo:GSE76925 licence not read
analysis object · 4 fields
state
complete
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[0] object · 10 fields
id
method-1
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differential_expression
specific
limma_voom
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Differential expression analysis
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[0]
normalise_counts
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differential_expression_fit
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fdr_bh
missing_operations array · 0 items
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[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
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verbatim
quote
In order to identify the DEGs between the young and aged groups, the limma R packages (http://www.bioconductor.org/packages) was used to perform the negative binomial distribution method according to the two standard deviations where the absolute value of FC was greater than the median of FC.
[1] object · 10 fields
id
method-2
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correlation_analysis
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Correlation analysis
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[0]
pearson_r
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[0]
paired_numeric_columns
evidence object · 3 fields
score
0.8
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high
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Pearson correlation
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id
method-3
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network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
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[0]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
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[0]
edge_list
evidence object · 3 fields
score
0.8
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high
quote
GO enrichment
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capability object · 3 fields
state
complete
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[0] object · 6 fields
capability_id
capability:computational_analysis
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assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
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[5]
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[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
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true
required_operations array · 3 items
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normalise_counts
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differential_expression_fit
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fdr_bh
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom.
capability object · 4 fields
tier
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capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 3 items
[0]
GSE76925
[1]
GSE47460
[2]
GSE125521
resolved_accessions array · 3 items
[0]
GSE76925
[1]
GSE47460
[2]
GSE125521
statements array · 1 item
[0]
To identify the genes associated with aging in COPD patients, two microarray datasets (GSE76925 and GSE47460) were downloaded from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) [50, 51].
basis
The paper names GSE76925, GSE47460, GSE125521 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
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[0]
normalise_counts
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differential_expression_fit
[2]
fdr_bh
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[0]
source:pmid:36309899
[1]
data:geo:GSE125521
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[0]
run_analysis
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readers array · 0 items
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[0]
data:geo:GSE125521
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review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
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MiniMax-M3.1-Flash
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minimax
provider_family
minimax
read_at
2026-11-01T18:13:26Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
null
calls
5
usage object · 3 fields
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11708
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1697
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256
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[0] object · 4 fields
id
extraction
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complete
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MiniMax-M3.1-Flash
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minimax
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execution object · 5 fields
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absent
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not_run
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null
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[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
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pmid:36309899
type
paper
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pmid:36309899
[1] object · 3 fields
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source:pmid:36309899
type
manuscript
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PMID 36309899 full text
[2] object · 3 fields
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data:geo:GSE125521
type
dataset
label
GEO GSE125521
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[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
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id
pmid:36309899
type
paper
label
pmid:36309899
[1] object · 3 fields
id
source:pmid:36309899
type
manuscript
label
PMID 36309899 full text
[2] object · 3 fields
id
data:geo:GSE125521
type
dataset
label
GEO GSE125521
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agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-36309899
type
extraction
used array · 1 item
[0]
source:pmid:36309899
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE125521
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accession_resolution
used array · 1 item
[0]
data:geo:GSE125521
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agent:corpus-assay-engine
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[0] object · 3 fields
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agent:corpus-assay-engine
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agent:minimax-reader
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reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
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ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:36309899
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sha256:8f472fd53a15e8873547b936639800bfd04917614701bb227214bbeff3aa4f24
fork_of
null
gaps array · 10 items
[0]
asset:data:geo:GSE125521 licence not read
[1]
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[2]
asset:data:geo:GSE47460 licence not read
[3]
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[4]
asset:data:geo:GSE76925 licence not read
[5]
asset:data:geo:GSE76925 not downloaded
[6]
execution.not_run
[7]
review.human_critique
[8]
review.independent_reader
[9]
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assays array · 3 items
[0] object · 11 fields
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data_generation
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animal_model
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99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
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0.99
evidence array · 3 items
[0]
ng the data for cigarette smoke-induced COPD mouse model (GSE125521), a total of 783 DEGs were identi
[1]
ng the data for cigarette smoke-induced COPD mouse model (GSE125521), a total of 783 DEGs were
[2]
s in COPD after combining the human DEGs and mouse DEGs. Eventually, five out of six core genes
order_basis
paper_text_order:658
id
assay:1
[1] object · 11 fields
role
data_generation
definition_id
microarray
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99e1195c7d6f
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support_state
partial
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assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 3 items
[0]
ted core gene profiles of COPD patients, two microarray datasets were obtained from GEO. The informa
[1]
al adhesion” (Figure 1E). Characteristics of microarray datasets included. DEGs associated with agin
[2]
Software, San Diego, CA, United States). The microarray data were analyzed by different R packages.
order_basis
paper_text_order:1544
id
assay:2
[2] object · 11 fields
role
analysis
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differential_expression
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f2132e96ae6c7a4e
required_operations array · 3 items
[0]
normalise_counts
[1]
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[2]
fdr_bh
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supported
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dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
In order to identify the DEGs between the young and aged groups, the limma R packages (http://www.bioconductor.org/packages) was used to perform the negative binomial distribution method according to the two standard deviations where the absolute value of FC was greater than the median of FC.
order_basis
consumes_earlier_output
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assay:3
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36309899", "kind": "science-record", "revision": 5, "content_hash": "sha256:ec29822c99efebea320cd9c857abd4cd785f3d7a48250a68a48c46319782d603", "created_at": "2026-11-01T18:15:43Z", "updated_at": "2026-11-01T22:50:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of genetic signature associated with aging in chronic obstructive pulmonary disease.", "doi": "10.18632/aging.204358", "pmid": "36309899", "authors": ["Shanshan Chen", "Yuan Zhan", "Jinkun Chen", "Jixing Wu", "Yiya Gu", "Qian Huang", "Zhesong Deng", "Xiaojie Wu", "Yongman Lv", "Jungang Xie"], "journal": "Aging", "year": 2022, "abstract": "Aging plays an essential role in the development for chronic obstructive pulmonary disease (COPD). The aim of this study was to identify and validate the potential aging-related genes of COPD through bioinformatics analysis and experimental validation. Firstly, we compared the gene expression profiles of aged and young COPD patients using two datasets (GSE76925 and GSE47460) from Gene Expression Omnibus (GEO), and identified 244 aging-related different expressed genes (DEGs), with 132 up-regulated and 112 down-regulated. Then, by analyzing the data for cigarette smoke-induced COPD mouse model (GSE125521), a total of 783 DEGs were identified between aged and young COPD mice, with 402 genes increased and 381 genes decreased. Additionally, functional enrichment analysis revealed that these DEGs were actively involved in COPD-related biological processes and function pathways. Meanwhile, six genes were identified as the core aging-related genes in COPD after combining the human DEGs and mouse DEGs. Eventually, five out of six core genes were validated to be up-regulated in the lung tissues collected from aged COPD patients than young COPD patients, namely NKG7, CKLF, LRP4, GDPD3 and CXCL9. Thereinto, the expressions of NKG7 and CKLF were negatively associated with lung function. These results may expand the understanding for aging in COPD.", "claims": [{"id": "claim-method", "statement": "In order to identify the DEGs between the young and aged groups, the limma R packages (http://www.bioconductor.org/packages) was used to perform the negative binomial distribution method according to the two standard deviations where the absolute value of FC was greater than the median of FC.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36309899", "locator": "sections[10] \"Microarray data acquisition and process\" paragraph 2", "quote": "In order to identify the DEGs between the young and aged groups, the limma R packages (http://www.bioconductor.org/packages) was used to perform the negative binomial distribution method according to the two standard deviations where the absolute value of FC was greater than the median of FC."}], "state": "complete"}, {"id": "claim-data-access", "statement": "To identify the genes associated with aging in COPD patients, two microarray datasets (GSE76925 and GSE47460) were downloaded from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) [50, 51].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36309899", "locator": "sections[10] \"Microarray data acquisition and process\" paragraph 2", "quote": "To identify the genes associated with aging in COPD patients, two microarray datasets (GSE76925 and GSE47460) were downloaded from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo) [50, 51]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Eventually, five out of six core genes were validated to be up-regulated in the lung tissues collected from aged COPD patients than young COPD patients, namely NKG7, CKLF, LRP4, GDPD3 and CXCL9.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36309899", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Eventually, five out of six core genes were validated to be up-regulated in the lung tissues collected from aged COPD patients than young COPD patients, namely NKG7, CKLF, LRP4, GDPD3 and CXCL9."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Eventually, five out of six core genes were validated to be up-regulated in the lung tissues collected from aged COPD patients than young COPD patients, namely NKG7, CKLF, LRP4, GDPD3 and CXCL9.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36309899"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE125521"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE125521"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36309899", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.18632/aging.204358", "sha256": 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