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pmid:39085362

The immune-inflammation factor is associated with diabetic nephropathy: evidence from NHANES 2013-2018 and GEO database.

Yan Wang · Shu-Yan Zhao · Yong-Chun Wang · Jia Xu · Jie Wang

Scientific reports · 2024 doi:10.1038/s41598-024-68347-1

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:39085362
kind
science-record
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sha256:2440a53a4a7ca04fcc8a158752ae05d610e05eb76b4cb2e5ed380c243d839802
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T20:29:09Z
updated_at
2026-11-01T22:12:20Z
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paper object · 10 fields
state
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title
The immune-inflammation factor is associated with diabetic nephropathy: evidence from NHANES 2013-2018 and GEO database.
doi
10.1038/s41598-024-68347-1
pmid
39085362
authors array · 5 items
[0]
Yan Wang
[1]
Shu-Yan Zhao
[2]
Yong-Chun Wang
[3]
Jia Xu
[4]
Jie Wang
journal
Scientific reports
year
2024
abstract
Diabetic nephropathy (DN) is a common secondary kidney disease. Immune and inflammatory responses play an influential role in the development of DN. This study aims to explore the role and mechanisms of immune- and inflammatory-related factors in DN. Participants from the NHANES 2013-2018 were included to evaluate the association between the SII and DN. Considering the skewed distribution of SII, log SII was used for subsequent analysis. Then, the DEGs were extracted from the GSE96804 dataset by the "limma" package of R, which were further screened out genes in the key module based on WGCNA. The intersection genes between DEGs and key module genes were the key genes for the following mechanism exploration. The CyTargetlinker plug-in of Cytoscape software was used to construct the drug-genes network. Molecular docking was used to calculate the binding affinity between potential drugs and the hub genes. Among the 8236 participants from NHANES 2013-2018, Log SII was significantly associated with DN (p < 0.05). DEG and WGCNA revealed 30 DN-related genes, which mainly regulated immune- and inflammation pathways, and the NOD-like receptor signaling pathway was the core pathway highly involved in the DN occurrence. Moreover, NAIP, ZFP36, and DUSP1 were identified as hub genes in DN progression and there was a strong binding interaction between resveratrol and DUSP1.In conclusion, immune inflammation plays an influential role in the occurrence and development of DN. SII is an effective diagnostic marker for DN and resveratrol might have potential value in treating DN.
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The non-linear association between logSII and DN was investigated using the restricted cubic spline (RCS) analysis. Then, three generalized linear models were used to further evaluate the correlation between SII and DN.
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sections[17] "Statistical analysis" paragraph 2
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The non-linear association between logSII and DN was investigated using the restricted cubic spline (RCS) analysis. Then, three generalized linear models were used to further evaluate the correlation between SII and DN.
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sections[32] "Data availability" paragraph 2
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The data and material supporting the findings of this study are available from the corresponding author upon request.
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Higher log SII was independently associated with diabetic nephropathy.
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When all the covariates were adjusted in model 3, logSII was an independent predictor for DN (P < 0.05).
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sections[21] "The association between Log SII and DN" paragraph 4
quote
When all the covariates were adjusted in model 3, logSII was an independent predictor for DN (P < 0.05).
[1] object · 3 fields
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sections[21] "The association between Log SII and DN" paragraph 4
quote
PAF analysis showed that 23.41% (16.18%-30.64%) of DN cases could be attributed to the increase in LogSII level (Table 3).
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Higher log SII was independently associated with diabetic nephropathy.
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Human Regulatory T cells from Umbilical Cord Blood Display Increased Repertoire Diversity and Lineage Stability Relative to Adult Peripheral Blood
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Expression data from isolated endothelial cells from glioblastoma and normal brain cultured as monolayer on gelatin and on Matrigel
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571
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Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Glomeruli vs. Control Glomeruli)
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571
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Homo sapiens
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Transcriptome Analysis of Human Diabetic Kidney Disease (DKD Tubuli vs. Control Tubuli)
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2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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The data and material supporting the findings of this study are available from the corresponding author upon request.
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title
Exon Level Expression Profiling of Diabetic Nephropathy
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data:geo:GSE137301
type
dataset
label
GEO GSE137301
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-39085362
type
extraction
used array · 1 item
[0]
source:pmid:39085362
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE137301
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE137301
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:39085362
parent_hash
sha256:81a0f88301cc7ee48529b8ae899dfa08a47bf06d6c333f80445e849afc75e37f
fork_of
null
gaps array · 15 items
[0]
asset:data:geo:GSE137301 licence not read
[1]
asset:data:geo:GSE137301 not downloaded
[2]
asset:data:geo:GSE137902 licence not read
[3]
asset:data:geo:GSE137902 not downloaded
[4]
asset:data:geo:GSE30528 licence not read
[5]
asset:data:geo:GSE30528 not downloaded
[6]
asset:data:geo:GSE30529 licence not read
[7]
asset:data:geo:GSE30529 not downloaded
[8]
asset:data:geo:GSE96804 licence not read
[9]
asset:data:geo:GSE96804 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
principal_component_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
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pca_fit
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Principal Component Analysis
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:39085362", "kind": "science-record", "revision": 3, "content_hash": "sha256:2440a53a4a7ca04fcc8a158752ae05d610e05eb76b4cb2e5ed380c243d839802", "created_at": "2026-11-01T20:29:09Z", "updated_at": "2026-11-01T22:12:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The immune-inflammation factor is associated with diabetic nephropathy: evidence from NHANES 2013-2018 and GEO database.", "doi": "10.1038/s41598-024-68347-1", "pmid": "39085362", "authors": ["Yan Wang", "Shu-Yan Zhao", "Yong-Chun Wang", "Jia Xu", "Jie Wang"], "journal": "Scientific reports", "year": 2024, "abstract": "Diabetic nephropathy (DN) is a common secondary kidney disease. Immune and inflammatory responses play an influential role in the development of DN. This study aims to explore the role and mechanisms of immune- and inflammatory-related factors in DN. Participants from the NHANES 2013-2018 were included to evaluate the association between the SII and DN. Considering the skewed distribution of SII, log SII was used for subsequent analysis. Then, the DEGs were extracted from the GSE96804 dataset by the \"limma\" package of R, which were further screened out genes in the key module based on WGCNA. The intersection genes between DEGs and key module genes were the key genes for the following mechanism exploration. The CyTargetlinker plug-in of Cytoscape software was used to construct the drug-genes network. Molecular docking was used to calculate the binding affinity between potential drugs and the hub genes. Among the 8236 participants from NHANES 2013-2018, Log SII was significantly associated with DN (p < 0.05). DEG and WGCNA revealed 30 DN-related genes, which mainly regulated immune- and inflammation pathways, and the NOD-like receptor signaling pathway was the core pathway highly involved in the DN occurrence. Moreover, NAIP, ZFP36, and DUSP1 were identified as hub genes in DN progression and there was a strong binding interaction between resveratrol and DUSP1.In conclusion, immune inflammation plays an influential role in the occurrence and development of DN. SII is an effective diagnostic marker for DN and resveratrol might have potential value in treating DN.", "claims": [{"id": "claim-method", "statement": "The non-linear association between logSII and DN was investigated using the restricted cubic spline (RCS) analysis. 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