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pmid:36568106

Bioinformatics analysis identifies immune-related gene signatures and subtypes in diabetic nephropathy.

Kunna Lu · Li Wang · Yan Fu · Guanghong Li · Xinhuan Zhang · Mingfeng Cao

Frontiers in endocrinology · 2022 doi:10.3389/fendo.2022.1048139

Paper

complete

Experiment

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Data

partial

Analysis

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pmid:36568106
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title
Bioinformatics analysis identifies immune-related gene signatures and subtypes in diabetic nephropathy.
doi
10.3389/fendo.2022.1048139
pmid
36568106
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[0]
Kunna Lu
[1]
Li Wang
[2]
Yan Fu
[3]
Guanghong Li
[4]
Xinhuan Zhang
[5]
Mingfeng Cao
journal
Frontiers in endocrinology
year
2022
abstract
Background: Systemic inflammation and immune response are involved in the pathogenesis of diabetic nephropathy (DN). However, the specific immune-associated signature during DN development is unclear. Our study aimed to reveal the roles of immune-related genes during DN progression. Methods: The GSE30529 and GSE30528 datasets were acquired from the Gene Expression Omnibus (GEO) database. Then, the intersection between differentially expressed genes (DEGs) and immune score-related genes (ISRGs) was screened. Subsequently, functional enrichment analyses were performed. The different immune phenotype-related subgroups were finally divided using unsupervised clustering. The core genes were identified by WGCNA and the protein-protein interaction (PPI) network. xCell algorithm was applied to assess the proportion of immune cell infiltration. Results: 92 immune score-related DEGs (ISRDEGs) were identified, and these genes were enriched in inflammation- and immune-associated pathways. Furthermore, two distinct immune-associated subgroups (C1 and C2) were identified, and the C1 subgroup exhibited activated immune pathways and a higher percentage of immune cells compared to the C2 subgroup. Two core genes (LCK and HCK) were identified and all up-regulated in DN, and the expressions were verified using GSE30122, GSE142025, and GSE104954 datasets. GSEA indicated the core genes were mainly enriched in immune-related pathways. Correlation analysis indicated LCK and HCK expressions were positively correlated with aDC, CD4+ Tem, CD8+T cells, CD8+ Tem, and mast cells. Conclusions: We identified two immune-related genes and two immune-associated subgroups, which might help to design more precise tailored immunotherapy for DN patients.
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WGCNA was used to establish potential modules associated with different subgroups of DN samples (29).
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Two core genes (LCK and HCK) were identified and all up-regulated in DN, and the expressions were verified using GSE30122, GSE142025, and GSE104954 datasets.
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asset:data:geo:GSE104954 not downloaded
[1]
asset:data:geo:GSE104954 licence not read
[2]
asset:data:geo:GSE142025 not downloaded
[3]
asset:data:geo:GSE142025 licence not read
[4]
asset:data:geo:GSE30122 not downloaded
[5]
asset:data:geo:GSE30122 licence not read
[6]
asset:data:geo:GSE30528 not downloaded
[7]
asset:data:geo:GSE30528 licence not read
[8]
asset:data:geo:GSE30529 not downloaded
[9]
asset:data:geo:GSE30529 licence not read
analysis object · 4 fields
state
partial
methods array · 2 items
[0] object · 10 fields
id
method-1
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
protein-protein interaction
[1] object · 10 fields
id
method-2
family
null
specific
null
label
Weighted gene coexpression network analysis (WGCNA)
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
WGCNA was used to establish potential modules associated with different subgroups of DN samples (29).
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
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]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
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: ppi_network.
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 · 5 items
[0]
GSE30529
[1]
GSE30528
[2]
GSE104954
[3]
GSE142025
[4]
GSE30122
resolved_accessions array · 5 items
[0]
GSE30529
[1]
GSE30528
[2]
GSE104954
[3]
GSE142025
[4]
GSE30122
statements array · 1 item
[0]
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
basis
The paper names GSE30529, GSE30528, GSE104954, GSE142025, GSE30122 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
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
assets array · 2 items
[0]
source:pmid:36568106
[1]
data:geo:GSE104954
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:GSE104954
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
2026-11-01T18:21:43Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
9101
completion_tokens
2098
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:36568106
type
paper
label
pmid:36568106
[1] object · 3 fields
id
source:pmid:36568106
type
manuscript
label
PMID 36568106 full text
[2] object · 3 fields
id
data:geo:GSE104954
type
dataset
label
GEO GSE104954
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:36568106
type
paper
label
pmid:36568106
[1] object · 3 fields
id
source:pmid:36568106
type
manuscript
label
PMID 36568106 full text
[2] object · 3 fields
id
data:geo:GSE104954
type
dataset
label
GEO GSE104954
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-36568106
type
extraction
used array · 1 item
[0]
source:pmid:36568106
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE104954
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE104954
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:36568106
parent_hash
sha256:8814384ed906439f8dd22f84b0756dd783a15a262b4c0fb9363244ae5eb4d0da
fork_of
null
gaps array · 15 items
[0]
asset:data:geo:GSE104954 licence not read
[1]
asset:data:geo:GSE104954 not downloaded
[2]
asset:data:geo:GSE142025 licence not read
[3]
asset:data:geo:GSE142025 not downloaded
[4]
asset:data:geo:GSE30122 licence not read
[5]
asset:data:geo:GSE30122 not downloaded
[6]
asset:data:geo:GSE30528 licence not read
[7]
asset:data:geo:GSE30528 not downloaded
[8]
asset:data:geo:GSE30529 licence not read
[9]
asset:data:geo:GSE30529 not downloaded
[10]
execution.not_run
[11]
method.reader_named_unmapped
[12]
review.human_critique
[13]
review.independent_reader
[14]
review.machine_critique
assays array · 1 item
[0] object · 11 fields
role
analysis
definition_id
network_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
protein-protein interaction
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:36568106", "kind": "science-record", "revision": 3, "content_hash": "sha256:7a0c5e574498cfd5834867ef64646cf49aa1e9e7ad0679df9e7022818ceaba86", "created_at": "2026-11-01T19:01:07Z", "updated_at": "2026-11-01T22:08:26Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics analysis identifies immune-related gene signatures and subtypes in diabetic nephropathy.", "doi": "10.3389/fendo.2022.1048139", "pmid": "36568106", "authors": ["Kunna Lu", "Li Wang", "Yan Fu", "Guanghong Li", "Xinhuan Zhang", "Mingfeng Cao"], "journal": "Frontiers in endocrinology", "year": 2022, "abstract": "Background: Systemic inflammation and immune response are involved in the pathogenesis of diabetic nephropathy (DN). However, the specific immune-associated signature during DN development is unclear. Our study aimed to reveal the roles of immune-related genes during DN progression.\nMethods: The GSE30529 and GSE30528 datasets were acquired from the Gene Expression Omnibus (GEO) database. Then, the intersection between differentially expressed genes (DEGs) and immune score-related genes (ISRGs) was screened. Subsequently, functional enrichment analyses were performed. The different immune phenotype-related subgroups were finally divided using unsupervised clustering. The core genes were identified by WGCNA and the protein-protein interaction (PPI) network. xCell algorithm was applied to assess the proportion of immune cell infiltration.\nResults: 92 immune score-related DEGs (ISRDEGs) were identified, and these genes were enriched in inflammation- and immune-associated pathways. Furthermore, two distinct immune-associated subgroups (C1 and C2) were identified, and the C1 subgroup exhibited activated immune pathways and a higher percentage of immune cells compared to the C2 subgroup. Two core genes (LCK and HCK) were identified and all up-regulated in DN, and the expressions were verified using GSE30122, GSE142025, and GSE104954 datasets. GSEA indicated the core genes were mainly enriched in immune-related pathways. Correlation analysis indicated LCK and HCK expressions were positively correlated with aDC, CD4+ Tem, CD8+T cells, CD8+ Tem, and mast cells.\nConclusions: We identified two immune-related genes and two immune-associated subgroups, which might help to design more precise tailored immunotherapy for DN patients.", "claims": [{"id": "claim-method", "statement": "WGCNA was used to establish potential modules associated with different subgroups of DN samples (29).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36568106", "locator": "sections[6] \"Weighted gene coexpression network analysis\" paragraph 2", "quote": "WGCNA was used to establish potential modules associated with different subgroups of DN samples (29)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36568106", "locator": "sections[23] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The paper identified LCK and HCK as two immune-related core genes that were up-regulated in diabetic nephropathy.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36568106", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Two core genes (LCK and HCK) were identified and all up-regulated in DN, and the expressions were verified using GSE30122, GSE142025, and GSE104954 datasets."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The paper identified LCK and HCK as two immune-related core genes that were up-regulated in diabetic nephropathy.", "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:36568106"], "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:GSE104954"], "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:GSE104954"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36568106", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fendo.2022.1048139", "sha256": "sha256:6f2e60f6626be02ed095a714f93ce16969956d4c74f1d7264891af3575570b13", "bytes": 31138, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fendo.2022.1048139", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9768367", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE104954", "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=GSE104954", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE104954", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2810894", "GSM2810895", "GSM2810896", "GSM2810897", "GSM2810898", "GSM2810899", "GSM2810900", "GSM2810901", "GSM2810902", "GSM2810903", "GSM2810904", "GSM2810905", "GSM2810906", "GSM2810907", "GSM2810908", "GSM2810909", "GSM2810910", "GSM2810911", "GSM2810912", "GSM2810913", "GSM2810914", "GSM2810915", "GSM2810916", "GSM2810917", "GSM2810918", "GSM2810919", "GSM2810920", "GSM2810921", "GSM2810922", "GSM2810923", "GSM2810924", "GSM2810925", "GSM2810926", "GSM2810927", "GSM2810928", "GSM2810929", "GSM2810930", "GSM2810931", "GSM2810932", "GSM2810933", "GSM2810934", "GSM2810935", "GSM2810936", "GSM2810937", "GSM2810938", "GSM2810939", "GSM2810940", "GSM2810941", "GSM2810942", "GSM2810943", "GSM2810944", "GSM2810945", "GSM2810946", "GSM2810947", "GSM2810948", "GSM2810949", "GSM2810950", "GSM2810951", "GSM2810952", "GSM2810953", "GSM2810954", "GSM2810955", "GSM2810956", "GSM2810957", "GSM2810958", "GSM2810959", "GSM2810960", "GSM2810961", "GSM2810962", "GSM2810963", "GSM2810964", "GSM2810965", "GSM2810966", "GSM2810967", "GSM2810968", "GSM2810969", "GSM2810970", "GSM2810971", "GSM2810972", "GSM2810973", "GSM2810974", "GSM2810975", "GSM2810976", "GSM2810977", "GSM2810978", "GSM2810979", "GSM2810980", "GSM2810981", "GSM2810982", "GSM2810983", "GSM2810984", "GSM2810985", "GSM2810986", "GSM2810987", "GSM2810988", "GSM2810989", "GSM2810990", "GSM2810991", "GSM2810992", "GSM2810993", "GSM2810994", "GSM2810995", "GSM2810996", "GSM2810997", "GSM2810998", "GSM2810999", "GSM2811000", "GSM2811001", "GSM2811002", "GSM2811003", "GSM2811004", "GSM2811005", "GSM2811006", "GSM2811007", "GSM2811008", "GSM2811009", "GSM2811010", "GSM2811011", "GSM2811012", "GSM2811013", "GSM2811014", "GSM2811015", "GSM2811016", "GSM2811017", "GSM2811018", "GSM2811019", "GSM2811020", "GSM2811021", "GSM2811022", "GSM2811023", "GSM2811024", "GSM2811025", "GSM2811026", "GSM2811027", "GSM2811028", "GSM2811029", "GSM2811030", "GSM2811031", "GSM2811032", "GSM2811033", "GSM2811034", "GSM2811035", "GSM2811036", "GSM2811037", "GSM2811038", "GSM2811039", "GSM2811040", "GSM2811041", "GSM2811042", "GSM2811043", "GSM2811044", "GSM2811045", "GSM2811046", "GSM2811047", "GSM2811048", "GSM2811049", "GSM2811050", "GSM2811051", "GSM2811052", "GSM2811053", "GSM2811054", "GSM2811055", "GSM2811056", "GSM2811057", "GSM2811058", "GSM2811059", "GSM2811060", "GSM2811061", "GSM2811062", "GSM2811063", "GSM2811064", "GSM2811065", "GSM2811066", "GSM2811067", "GSM2811068", "GSM2811069", "GSM2811070", "GSM2811071", "GSM2811072", "GSM2811073", "GSM2811074", "GSM2811075", "GSM2811076", "GSM2811077", "GSM2811078", "GSM2811079", "GSM2811080", "GSM2811081", "GSM2811082", "GSM2811083", "GSM2811084", "GSM2811085", "GSM2811086", "GSM2811087", "GSM2811088"], "sample_count": 195, "group_sizes": null, "group_sizes_basis": null, "platform": "22945;24120", "taxon": "Homo sapiens", "title": "Tubulointerstitial transcriptome from ERCB subjects with chronic kidney disease and living donor biopsies.", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE142025", "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=GSE142025", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE142025", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4217781", "GSM4217782", "GSM4217783", "GSM4217784", "GSM4217785", "GSM4217786", "GSM4217787", "GSM4217788", "GSM4217789", "GSM4217790", "GSM4217791", "GSM4217792", "GSM4217793", "GSM4217794", "GSM4217795", "GSM4217796", "GSM4217797", "GSM4217798", "GSM4217799", "GSM4217800", "GSM4217801", "GSM4217802", "GSM4217803", "GSM4217804", "GSM4217805", "GSM4217806", "GSM4217807", "GSM4217808", "GSM4217809", "GSM4217810", "GSM4217811", "GSM4217812", "GSM4217813", "GSM4217814", "GSM4217815", "GSM4217816"], "sample_count": 36, "group_sizes": null, "group_sizes_basis": null, "platform": "20301", "taxon": "Homo sapiens", "title": "Comparison of Kidney Transcriptomic Profiles of Early and Advanced Diabetic Nephropathy Reveals Potential New Mechanisms for Disease Progression", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE30122", "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=GSE30122", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE30122", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/ Supplementary Material . 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