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pmid:36859608

Identification and verification of feature biomarkers associated in heart failure by bioinformatics analysis.

Yi-Ding Yu · Yi-Tao Xue · Yan Li

Scientific reports · 2023 doi:10.1038/s41598-023-30666-0

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Identification and verification of feature biomarkers associated in heart failure by bioinformatics analysis.
doi
10.1038/s41598-023-30666-0
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36859608
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[0]
Yi-Ding Yu
[1]
Yi-Tao Xue
[2]
Yan Li
journal
Scientific reports
year
2023
abstract
Heart failure is the final destination of most cardiovascular diseases, and its complex molecular mechanisms remain largely uncertain. This study aimed to systematically investigate the underlying molecular mechanisms and diagnostic and therapeutic targets of heart failure using bioinformatics. We obtained 8 healthy samples and 8 heart failure samples from GSE8331 and GSE76701. After removing the batch effect, we performed a differential analysis on it and obtained 185 differentially expressed ID. The results of enrichment analysis showed that the molecular mechanisms of heart failure were mostly related to immune, inflammation, and metabolism-related pathways. Immune cell infiltration analysis showed that the degree of infiltration of Tgd cells and Neurons was significantly enriched in heart failure samples, whereas pDCs and NKTs were in healthy tissue samples. We obtained Hub genes including EGR1, EGR2, FOS and FOSB by PPI network analysis. We established a 4-gene diagnostic model with Hub gene, and validated it in GSE21610 and GSE57338, and evaluated the discriminative ability of Hub gene by ROC curve. The 4-gene diagnostic model has an AUC value of 0.775 in GSE21610 and 0.877 in GSE57338. In conclusion, we explored the underlying molecular mechanisms of heart failure and the immune cell infiltration environment of failing myocardium by performing bioinformatic analysis of the GEO dataset. In addition, we identified EGR1, EGR2, FOS and FOSB as potential diagnostic biomarkers and therapeutic targets for heart failure. More importantly, a diagnostic model of heart failure based on these 4 genes was developed, which leads to a new understanding of the pathogenesis of heart failure and may be an interesting target for future in-depth research.
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We used the limma package for differential analysis of heart failure samples and normal samples, and selected genes with p-value < 0.05 and |log2(FC)|≥ 1 as differential genes.
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We used the limma package for differential analysis of heart failure samples and normal samples, and selected genes with p-value < 0.05 and |log2(FC)|≥ 1 as differential genes.
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GEO
access_route
GEO accession URL
access_statement_verbatim
Publicly available datasets were analyzed in this study. This data can be found here: GSE8331; GSE76701; GSE21610; GSE57338.
access_statement_kind
data_availability_statement
sample_accessions array · 8 items
[0]
GSM206429
[1]
GSM206430
[2]
GSM206431
[3]
GSM206432
[4]
GSM206433
[5]
GSM206434
[6]
GSM206435
[7]
GSM206436
sample_count
8
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
mRNA quantitation of human heart left ventricles
resolution_checked_at
2026-11-01T18:06:44Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 8 items
[0]
asset:data:geo:GSE21610 not downloaded
[1]
asset:data:geo:GSE21610 licence not read
[2]
asset:data:geo:GSE57338 not downloaded
[3]
asset:data:geo:GSE57338 licence not read
[4]
asset:data:geo:GSE76701 not downloaded
[5]
asset:data:geo:GSE76701 licence not read
[6]
asset:data:geo:GSE8331 not downloaded
[7]
asset:data:geo:GSE8331 licence not read
analysis object · 4 fields
state
complete
methods array · 3 items
[0] object · 10 fields
id
method-1
family
differential_expression
specific
limma_voom
label
Differential expression analysis
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
band
verbatim
quote
We used the limma package for differential analysis of heart failure samples and normal samples, and selected genes with p-value < 0.05 and |log2(FC)|≥ 1 as differential genes.
[1] object · 10 fields
id
method-2
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
PPI
[2] object · 10 fields
id
method-3
family
diagnostic_evaluation
specific
roc
label
Diagnostic test evaluation
dsl_operations array · 6 items
[0]
confusion_counts
[1]
roc_curve
[2]
sensitivity_specificity
[3]
solve_confusion_matrix
[4]
classification_metrics
[5]
published_precision_envelope
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
reference_standard_and_test
evidence object · 3 fields
score
0.7
band
medium
quote
ROC curve
targets array · 0 items
gaps array · 0 items
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[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
expressible
true
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
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
R1
capability_id
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 · 4 items
[0]
GSE8331
[1]
GSE76701
[2]
GSE21610
[3]
GSE57338
resolved_accessions array · 4 items
[0]
GSE8331
[1]
GSE76701
[2]
GSE21610
[3]
GSE57338
statements array · 1 item
[0]
Publicly available datasets were analyzed in this study. This data can be found here: GSE8331; GSE76701; GSE21610; GSE57338.
basis
The paper names GSE8331, GSE76701, GSE21610, GSE57338 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 2 items
[0]
source:pmid:36859608
[1]
data:geo:GSE21610
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE21610
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T18:32:16Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
11982
completion_tokens
1499
cached_tokens
128
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:36859608
type
paper
label
pmid:36859608
[1] object · 3 fields
id
source:pmid:36859608
type
manuscript
label
PMID 36859608 full text
[2] object · 3 fields
id
data:geo:GSE21610
type
dataset
label
GEO GSE21610
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:36859608
type
paper
label
pmid:36859608
[1] object · 3 fields
id
source:pmid:36859608
type
manuscript
label
PMID 36859608 full text
[2] object · 3 fields
id
data:geo:GSE21610
type
dataset
label
GEO GSE21610
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-36859608
type
extraction
used array · 1 item
[0]
source:pmid:36859608
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE21610
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE21610
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
software
label
Corpus assay engine
[1] object · 3 fields
id
agent:minimax-reader
type
software
label
MiniMax literature reader
source_run_id
reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:36859608
parent_hash
sha256:69f54c285ac717a5a18c005fd5566a261f3d0be1ed5110ec597f84cd9f176ddd
fork_of
null
gaps array · 12 items
[0]
asset:data:geo:GSE21610 licence not read
[1]
asset:data:geo:GSE21610 not downloaded
[2]
asset:data:geo:GSE57338 licence not read
[3]
asset:data:geo:GSE57338 not downloaded
[4]
asset:data:geo:GSE76701 licence not read
[5]
asset:data:geo:GSE76701 not downloaded
[6]
asset:data:geo:GSE8331 licence not read
[7]
asset:data:geo:GSE8331 not downloaded
[8]
execution.not_run
[9]
review.human_critique
[10]
review.independent_reader
[11]
review.machine_critique
assays array · 1 item
[0] object · 11 fields
role
analysis
definition_id
differential_expression
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
We used the limma package for differential analysis of heart failure samples and normal samples, and selected genes with p-value < 0.05 and |log2(FC)|≥ 1 as differential genes.
order_basis
analysis_only
id
assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36859608", "kind": "science-record", "revision": 4, "content_hash": "sha256:6c7177b059ec2873b20cb63d24556acb12dfebeb87247a9118576ffff999fb03", "created_at": "2026-11-01T19:01:29Z", "updated_at": "2026-11-01T22:51:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and verification of feature biomarkers associated in heart failure by bioinformatics analysis.", "doi": "10.1038/s41598-023-30666-0", "pmid": "36859608", "authors": ["Yi-Ding Yu", "Yi-Tao Xue", "Yan Li"], "journal": "Scientific reports", "year": 2023, "abstract": "Heart failure is the final destination of most cardiovascular diseases, and its complex molecular mechanisms remain largely uncertain. This study aimed to systematically investigate the underlying molecular mechanisms and diagnostic and therapeutic targets of heart failure using bioinformatics. We obtained 8 healthy samples and 8 heart failure samples from GSE8331 and GSE76701. After removing the batch effect, we performed a differential analysis on it and obtained 185 differentially expressed ID. The results of enrichment analysis showed that the molecular mechanisms of heart failure were mostly related to immune, inflammation, and metabolism-related pathways. Immune cell infiltration analysis showed that the degree of infiltration of Tgd cells and Neurons was significantly enriched in heart failure samples, whereas pDCs and NKTs were in healthy tissue samples. We obtained Hub genes including EGR1, EGR2, FOS and FOSB by PPI network analysis. We established a 4-gene diagnostic model with Hub gene, and validated it in GSE21610 and GSE57338, and evaluated the discriminative ability of Hub gene by ROC curve. The 4-gene diagnostic model has an AUC value of 0.775 in GSE21610 and 0.877 in GSE57338. In conclusion, we explored the underlying molecular mechanisms of heart failure and the immune cell infiltration environment of failing myocardium by performing bioinformatic analysis of the GEO dataset. In addition, we identified EGR1, EGR2, FOS and FOSB as potential diagnostic biomarkers and therapeutic targets for heart failure. More importantly, a diagnostic model of heart failure based on these 4 genes was developed, which leads to a new understanding of the pathogenesis of heart failure and may be an interesting target for future in-depth research.", "claims": [{"id": "claim-method", "statement": "We used the limma package for differential analysis of heart failure samples and normal samples, and selected genes with p-value < 0.05 and |log2(FC)|≥ 1 as differential genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36859608", "locator": "sections[4] \"Data preprocessing and DEGs identification\" paragraph 2", "quote": "We used the limma package for differential analysis of heart failure samples and normal samples, and selected genes with p-value < 0.05 and |log2(FC)|≥ 1 as differential genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: GSE8331; GSE76701; GSE21610; GSE57338.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36859608", "locator": "sections[21] \"Data availability\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: GSE8331; GSE76701; GSE21610; GSE57338."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The 4-gene diagnostic model has an AUC value of 0.775 in GSE21610 and 0.877 in GSE57338.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36859608", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The 4-gene diagnostic model has an AUC value of 0.775 in GSE21610 and 0.877 in GSE57338."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The 4-gene diagnostic model has an AUC value of 0.775 in GSE21610 and 0.877 in GSE57338.", "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:36859608"], "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:GSE21610"], "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:GSE21610"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36859608", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-023-30666-0", "sha256": "sha256:76d11d1b64e92ca7471d5fce7880c3f1fa63c2090ac134daaa5926ac9a093538", "bytes": 40699, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-023-30666-0", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9977868", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE21610", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21610", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE21610", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: GSE8331; GSE76701; GSE21610; GSE57338.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: GSE8331; GSE76701; GSE21610; GSE57338.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM545657", "GSM545658", "GSM545659", "GSM545660", "GSM545661", "GSM545662", "GSM545663", "GSM545664", "GSM545665", "GSM545666", "GSM545667", "GSM545668", "GSM545669", "GSM545670", "GSM545671", "GSM545672", "GSM545673", "GSM545674", "GSM545675", "GSM545676", "GSM545677", "GSM545678", "GSM545679", "GSM545680", "GSM545681", "GSM545682", "GSM545683", "GSM545684", "GSM545685", "GSM545686", "GSM545687", "GSM545688", "GSM545689", "GSM545690", "GSM545691", "GSM545692", "GSM545693", "GSM545694", "GSM545695", "GSM545696", "GSM545697", "GSM545698", "GSM545699", "GSM545700", "GSM545701", "GSM545702", "GSM545703", "GSM545704", "GSM545705", "GSM545706", "GSM545707", "GSM545708", "GSM545709", "GSM545710", "GSM545711", "GSM545712", "GSM545713", "GSM545714", "GSM545715", "GSM545716", "GSM545717", "GSM545718", "GSM545719", "GSM545720", "GSM545721", "GSM545722", "GSM545723", "GSM545724"], "sample_count": 68, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene expression analysis in non-failing and failing myocardium pre and post pulsatile and non-pulsatile VAD support", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE57338", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE57338", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE57338", "version": null, "note": "Publicly available datasets were analyzed in this study. 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