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pmid:32460303

Bioinformatics Analysis and Identification of Underlying Biomarkers Potentially Linking Allergic Rhinitis and Asthma.

Zhanfeng Yan · Lili Liu · Lulu Jiao · Xiaohui Wen · Jianhua Liu · Ningyu Wang

Medical science monitor : international medical journal of experimental and clinical research · 2020 doi:10.12659/MSM.924934

Paper

complete

Experiment

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Data

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Analysis

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pmid:32460303
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science-record
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sha256:4baa8a7cf46ca54cc8c3b3e3a369256ba9b4bcd8a394452937d0990334539899
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created_at
2026-11-01T15:41:02Z
updated_at
2026-11-01T22:44:53Z
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paper object · 10 fields
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title
Bioinformatics Analysis and Identification of Underlying Biomarkers Potentially Linking Allergic Rhinitis and Asthma.
doi
10.12659/MSM.924934
pmid
32460303
authors array · 6 items
[0]
Zhanfeng Yan
[1]
Lili Liu
[2]
Lulu Jiao
[3]
Xiaohui Wen
[4]
Jianhua Liu
[5]
Ningyu Wang
journal
Medical science monitor : international medical journal of experimental and clinical research
year
2020
abstract
BACKGROUND Rhinitis is the most common clinical manifestation of allergy, affecting more than 400 million people around the world. Rhinitis increases the risk of developing bronchial hyper-responsiveness and asthma. Previous studies have shown that rhinitis is closely related with the physiology, pathology, and pathogenesis of asthma. We analyzed co-expressed genes to explore the relationships between rhinitis and asthma and to find biomarkers of comorbid rhinitis and asthma. MATERIAL AND METHODS Asthma- and rhinitis-related differentially-expressed genes (DEGs) were identified by bioinformatic analysis of GSE104468 and GSE46171 datasets from the Gene Expression Omnibus (GEO) database. After assessment of Gene Ontology (GO) terms and pathway enrichment for DEGs, a protein-protein interaction (PPI) network was conducted via comprehensive target prediction and network analyses. We also evaluated co-expressed DEGs and corresponding predicted miRNAs involved in the developing process of rhinitis and asthma. RESULTS We identified 687 and 1001 DEGs in bronchial and nasal epithelia samples of asthma patients, respectively. For patients with rhinitis, we found 245 DEGs. The hub-genes of PAX6, NMU, NTS, NMUR1, PMCH, and KRT6A may be associated with rhinitis, while CPA3, CTSG, POSTN, CLCA1, HDC, and MUC5B may be involved in asthma. The co-expressed DEGs of BPIFA1, CCL26, CPA3, and CST1, together with corresponding predicted miRNAs (e.g., miR-195-5p and miR-125a-3p) were found to be significantly correlated with rhinitis and asthma. CONCLUSIONS Rhinitis and asthma are related, and there are significant correlations of BPIFA1, CCL26, CPA3, and CST1 genes with novel biomarkers involved in the comorbidity of rhinitis and asthma.
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The Bioconductor R packages “limma” [19], was applied to analyze GSE104468 and GSE46171 RAW datasets. Original p-values were corrected using the Benjamini-Hochberg method.
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sections[3] "Data processing" paragraph 2
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The Bioconductor R packages “limma” [19], was applied to analyze GSE104468 and GSE46171 RAW datasets. Original p-values were corrected using the Benjamini-Hochberg method.
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Additionally, the GSE104468 dataset, including collected nasal epithelia and bronchial epithelia sample from 12 subjects with allergic asthma and 12 control subjects, was used to identify differentially-expressed genes and molecular mechanisms of asthma [17].
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sections[2] "Material and Methods" paragraph 2
quote
Additionally, the GSE104468 dataset, including collected nasal epithelia and bronchial epithelia sample from 12 subjects with allergic asthma and 12 control subjects, was used to identify differentially-expressed genes and molecular mechanisms of asthma [17].
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The Nasal Methylome: A Key to Understanding Allergic Asthma [Agilent]
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Additionally, the GSE104468 dataset, including collected nasal epithelia and bronchial epithelia sample from 12 subjects with allergic asthma and 12 control subjects, was used to identify differentially-expressed genes and molecular mechanisms of asthma [17].
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Asthmatics with exacerbation during acute respiratory illness exhibit unique transcriptional signatures.
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The Gene Ontology (GO) terms enrichment for the co-expressed genes of rhinitis and asthma.
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Functional enrichment in co-DEGs
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Table 1
caption
The Gene Ontology (GO) terms enrichment for the co-expressed genes of rhinitis and asthma.
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[0] array · 4 items
[0]
Gene/product
[1]
GO class (direct)
[2]
Evidence
[3]
Reference
[1] array · 4 items
[0]
BPIFA1
[1]
Protein binding
[2]
IPI
[3]
PMID: 25416956
[2] array · 3 items
[0]
Extracellular region
[1]
IDA
[2]
PMID: 11425234
[3] array · 3 items
[0]
Extracellular space
[1]
IDA
[2]
PMID: 21805676
[4] array · 3 items
[0]
Lipid binding
[1]
IEA
[2]
GO_REF: 0000037
[5] array · 3 items
[0]
Antimicrobial humoral response
[1]
TAS
[2]
Reactome: R-HSA-6803157
[6] array · 3 items
[0]
Antibacterial humoral response
[1]
IDA
[2]
PMID: 23499554
[7] array · 3 items
[0]
Innate immune response
[1]
IDA
[2]
PMID: 23499554
[8] array · 3 items
[0]
Regulation of liquid surface tension
[1]
IDA
[2]
PMID: 23499554
[9] array · 3 items
[0]
Multicellular organismal water homeostasis
[1]
IDA
[2]
PMID: 24124190
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[0]
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[1]
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[2]
PMID: 21805676
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[0]
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[1]
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[2]
PMID: 21805676
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[0]
Negative regulation of single-species biofilm formation in or on host organism
[1]
IMP
[2]
PMID: 23499554
[13] array · 3 items
[0]
Regulation of sodium ion transmembrane transport
[1]
IDA
[2]
PMID: 24124190
[14] array · 4 items
[0]
CCL26
[1]
Positive regulation of endothelial cell proliferation
[2]
IDA
[3]
PMID: 19525930
[15] array · 3 items
[0]
Monocyte chemotaxis
[1]
IDA
[2]
PMID: 10373330
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[0]
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[1]
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[2]
PMID: 28381538
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[0]
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[2]
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[0]
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[1]
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[2]
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[0]
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[1]
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[2]
PMID: 10373330
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[0]
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[1]
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[2]
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[1]
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[2]
PMID: 10373330
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[0]
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[1]
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[2]
PMID: 19525930
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[1]
IDA
[2]
PMID: 19525930
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PMID: 11425309
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G protein-coupled receptor signaling pathway
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PMID: 21873635
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Cellular response to interferon-gamma
[1]
IBA
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PMID: 21873635
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CPA3
[1]
Angiotensin maturation
[2]
TAS
[3]
Reactome: R-HSA-2028294
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[0]
Metallocarboxypeptidase activity
[1]
TAS
[2]
PMID: 1629626
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TAS
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TAS
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PMID: 2708524
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[0]
Zinc ion binding
[1]
IEA
[2]
GO_REF: 0000002
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[0]
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[1]
IEA
[2]
GO_REF: 0000039
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[1]
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IDA
[3]
PMID: 24248522
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[0]
Cysteine-type endopeptidase inhibitor activity
[1]
IEA
[2]
GO_REF: 0000037
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PMID: 25416956
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PMID: 22664934
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PMID: 21873635
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Detection of chemical stimulus involved in sensory perception of bitter taste
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IDA
[3]
PMID: 24248522
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Cysteine-type endopeptidase inhibitor activity
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GO_REF: 0000037
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PMID: 25416956
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PMID: 22664934
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IEA
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GO_REF: 0000108
[66] array · 3 items
[0]
Extracellular space
[1]
IBA
[2]
PMID: 21873635
[67] array · 4 items
[0]
FETUB
[1]
Cysteine-type endopeptidase inhibitor activity
[2]
IEA
[3]
GO_REF: 0000002
[68] array · 3 items
[0]
Single fertilization
[1]
ISS
[2]
GO_REF: 0000024
[69] array · 3 items
[0]
Binding of sperm to zona pellucida
[1]
ISS
[2]
GO_REF: 0000024
[70] array · 3 items
[0]
Metalloendopeptidase inhibitor activity
[1]
ISS
[2]
GO_REF: 0000024
[71] array · 3 items
[0]
Negative regulation of endopeptidase activity
[1]
ISS
[2]
GO_REF: 0000024
[72] array · 3 items
[0]
Extracellular exosome
[1]
HDA
[2]
PMID: 23533145
[73] array · 3 items
[0]
Binding of sperm to zona pellucida
[1]
IBA
[2]
PMID: 21873635
[74] array · 3 items
[0]
Negative regulation of endopeptidase activity
[1]
IBA
[2]
PMID: 21873635
[75] array · 3 items
[0]
Metalloendopeptidase inhibitor activity
[1]
IBA
[2]
PMID: 21873635
[76] array · 3 items
[0]
Extracellular region
[1]
IBA
[2]
PMID: 21873635
[77] array · 3 items
[0]
Endopeptidase inhibitor activity
[1]
IBA
[2]
PMID: 21873635
locator
section[9]/table-wrap[1]#t1-medscimonit-26-e924934
[4] object · 16 fields
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asset:table:pmid:32460303:2
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table
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jats-table
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application/vnd.jats.table+json
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sha256:057272956e5a19bcaa8989df646273e22af8fee13ce6e420ec8ccc722246bc79
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read_table
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note
The Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment among predicted miRNAs and co-DEGs.
structure object · 5 fields
pmcid
PMC7278529
section_index
11
section_title
Identification of functional and pathway enrichment among predicted miRNAs and co-DEGs
row_count
45
column_count
5
table object · 8 fields
label
Table 2
caption
The Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment among predicted miRNAs and co-DEGs.
rows array · 45 items
[0] array · 5 items
[0]
Genes
[1]
Predicted miRNAs
[2]
Category
[3]
[4]
P value
[1] array · 5 items
[0]
BPIFA1
[1]
hsa-miR-195-5p
[2]
KEGG pathway
[3]
Fatty acid biosynthesis
[4]
1.04E-07
[2] array · 3 items
[0]
hsa-miR-16-5p
[1]
Adherens junction
[2]
1.70E-07
[3] array · 3 items
[0]
hsa-miR-424-5p
[1]
TGF-beta signaling pathway
[2]
3.28E-05
[4] array · 4 items
[0]
hsa-miR-497-5p
[1]
GO terms
[2]
Neurotrophin TRK receptor signaling pathway
[3]
1.79E-31
[5] array · 3 items
[0]
hsa-miR-15b-5p
[1]
cell death
[2]
1.41E-28
[6] array · 2 items
[0]
Response to stress
[1]
1.41E-28
[7] array · 2 items
[0]
Blood coagulation
[1]
1.84E-25
[8] array · 2 items
[0]
Fc-epsilon receptor signaling pathway
[1]
5.45E-19
[9] array · 2 items
[0]
Immune system process
[1]
3.87E-15
[10] array · 2 items
[0]
Activation of signaling protein activity involved in unfolded protein response
[1]
3.77E-14
[11] array · 2 items
[0]
Toll-like receptor 10 signaling pathway
[1]
1.22E-13
[12] array · 2 items
[0]
Epidermal growth factor receptor signaling pathway
[1]
1.82E-13
[13] array · 2 items
[0]
Toll-like receptor TLR1: TLR2 signaling pathway
[1]
1.06E-12
[14] array · 2 items
[0]
Toll-like receptor TLR6: TLR2 signaling pathway
[1]
1.06E-12
[15] array · 5 items
[0]
CCL26
[1]
hsa-miR-326
[2]
KEGG pathway
[3]
Steroid biosynthesis
[4]
8.04E-10
[16] array · 3 items
[0]
hsa-miR-615-5p
[1]
ECM-receptor interaction
[2]
3.39E-08
[17] array · 4 items
[0]
hsa-miR-559
[1]
GO terms
[2]
Neurotrophin TRK receptor signaling pathway
[3]
5.30E-26
[18] array · 3 items
[0]
hsa-miR-335-5p
[1]
Small molecule metabolic process
[2]
5.89E-21
[19] array · 3 items
[0]
hsa-miR-548d-5p
[1]
Blood coagulation
[2]
8.06E-18
[20] array · 2 items
[0]
Cellular protein modification process
[1]
4.43E-15
[21] array · 2 items
[0]
Fc-epsilon receptor signaling pathway
[1]
3.94E-13
[22] array · 2 items
[0]
Cellular nitrogen compound metabolic process
[1]
3.94E-13
[23] array · 2 items
[0]
Immune system process
[1]
7.59E-11
[24] array · 5 items
[0]
CPA3
[1]
hsa-miR-125a-3p
[2]
KEGG pathway
[3]
Adherens junction
[4]
2.60E-07
[25] array · 3 items
[0]
hsa-miR-155-5p
[1]
Hippo signaling pathway
[2]
1.21E-05
[26] array · 3 items
[0]
hsa-miR-196a-5p
[1]
TGF-beta signaling pathway
[2]
1.96E-05
[27] array · 3 items
[0]
hsa-miR-196b-5p
[1]
Lysine degradation
[2]
4.43E-05
[28] array · 3 items
[0]
GO terms
[1]
cellular nitrogen compound metabolic process
[2]
6.05E-108
[29] array · 2 items
[0]
gene expression
[1]
7.55E-68
[30] array · 2 items
[0]
biosynthetic process
[1]
8.95E-64
[31] array · 2 items
[0]
cellular protein modification process
[1]
8.70E-52
[32] array · 5 items
[0]
CST1
[1]
hsa-miR-452-5p
[2]
KEGG pathway
[3]
ECM-receptor interaction
[4]
0.000132
[33] array · 3 items
[0]
hsa-miR-608
[1]
Hippo signaling pathway
[2]
0.00019
[34] array · 3 items
[0]
hsa-miR-138-5p
[1]
Adherens junction
[2]
0.00019
[35] array · 3 items
[0]
hsa-miR-4685-5p
[1]
Apoptosis
[2]
0.005037
[36] array · 3 items
[0]
hsa-miR-1321
[1]
Focal adhesion
[2]
0.005037
[37] array · 3 items
[0]
GO terms
[1]
Cellular nitrogen compound metabolic process
[2]
2.81E-42
[38] array · 2 items
[0]
Gene expression
[1]
2.91E-40
[39] array · 2 items
[0]
Biosynthetic process
[1]
7.87E-34
[40] array · 2 items
[0]
mRNA metabolic process
[1]
8.00E-21
[41] array · 2 items
[0]
Response to stress
[1]
8.00E-21
[42] array · 2 items
[0]
RNA metabolic process
[1]
1.38E-17
[43] array · 2 items
[0]
Symbiosis, encompassing mutualism through parasitism
[1]
1.97E-17
[44] array · 2 items
[0]
Cellular component assembly
[1]
2.11E-17
locator
section[11]/table-wrap[1]#t2-medscimonit-26-e924934
[5] object · 16 fields
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asset:table:pmid:32460303:3
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section[14]/table-wrap[1]#t3-medscimonit-26-e924934
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note
The relationship between co-expressed genes and respiratory system diseases based on the CTD database.
structure object · 5 fields
pmcid
PMC7278529
section_index
14
section_title
Supplementary Data
row_count
27
column_count
8
table object · 8 fields
label
Supplementary Table 1
caption
The relationship between co-expressed genes and respiratory system diseases based on the CTD database.
rows array · 27 items
[0] array · 8 items
[0]
Gene symbol
[1]
Gene ID
[2]
Disease name
[3]
Disease ID
[4]
Direct evidence
[5]
Inference network
[6]
Inference score
[7]
Reference count
[1] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Particulate Matter | Tobacco Smoke Pollution | Vehicle Emissions
[6]
12.67
[7]
3
[2] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Rhinitis, allergic
[3]
MESH: D065631
[4]
[5]
Particulate Matter | Soot
[6]
8.45
[7]
2
[3] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Rhinitis, allergic, seasonal
[3]
MESH: D006255
[4]
[5]
Particulate Matter
[6]
3.57
[7]
1
[4] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Asthma
[3]
MESH: D001249
[4]
[5]
Acetaminophen | Arsenic | Particulate Matter | Soot | Tobacco Smoke Pollution | Vehicle Emissions
[6]
21.02
[7]
29
[5] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Asthma, occupational
[3]
MESH: D059366
[4]
[5]
Silicon Dioxide
[6]
3.35
[7]
1
[6] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Nose diseases
[3]
MESH: D009668
[4]
[5]
Propylthiouracil | Tobacco Smoke Pollution
[6]
9.59
[7]
4
[7] array · 8 items
[0]
CCL26
[1]
10344
[2]
Asthma
[3]
MESH: D001249
[4]
[5]
Aerosols | Antigens, Dermatophagoides | Arsenic | Cadmium | Dexamethasone | Ozone | Resveratrol | Tobacco Smoke Pollution | Zinc
[6]
27.99
[7]
28
[8] array · 8 items
[0]
CCL26
[1]
10344
[2]
Rhinitis, allergic, perennial
[3]
MESH: D012221
[4]
[5]
Ozone
[6]
3.73
[7]
1
[9] array · 8 items
[0]
CCL26
[1]
10344
[2]
Rhinitis, allergic
[3]
MESH: D065631
[4]
[5]
Atrazine
[6]
2.83
[7]
1
[10] array · 8 items
[0]
CCL26
[1]
10344
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Tobacco Smoke Pollution
[6]
2.6
[7]
1
[11] array · 8 items
[0]
CCL26
[1]
10344
[2]
Nose diseases
[3]
MESH: D009668
[4]
[5]
Lipopolysaccharides | Propylthiouracil | Tobacco Smoke Pollution
[6]
14.31
[7]
5
[12] array · 8 items
[0]
CCL26
[1]
10344
[2]
Sinusitis
[3]
MESH: D012852
[4]
[5]
Tobacco Smoke Pollution
[6]
2.9
[7]
1
[13] array · 8 items
[0]
CPA3
[1]
1359
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Tobacco Smoke Pollution | Vehicle Emissions
[6]
6.86
[7]
2
[14] array · 8 items
[0]
CPA3
[1]
1359
[2]
Asthma
[3]
MESH: D001249
[4]
[5]
Acetaminophen | Decitabine | epigallocatechin gallate | Tobacco Smoke Pollution | trimellitic anhydride | Vehicle Emissions
[6]
18.84
[7]
19
[15] array · 8 items
[0]
CPA3
[1]
1359
[2]
Nose diseases
[3]
MESH: D009668
[4]
[5]
Tobacco Smoke Pollution
[6]
3.4
[7]
2
[16] array · 8 items
[0]
CPA3
[1]
1359
[2]
Sinusitis
[3]
MESH: D012852
[4]
[5]
Acetaminophen | Tobacco Smoke Pollution
[6]
7.83
[7]
2
[17] array · 7 items
[0]
CST1
[1]
1469
[2]
Rhinitis, allergic, seasonal
[3]
MESH: D006255
[4]
Marker/mechanism
[5]
[6]
1
[18] array · 8 items
[0]
CST1
[1]
1469
[2]
Rhinitis, allergic
[3]
MESH: D065631
[4]
[5]
Air Pollutants
[6]
3.83
[7]
1
[19] array · 8 items
[0]
CST1
[1]
1469
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Air Pollutants
[6]
3.6
[7]
1
[20] array · 8 items
[0]
CST1
[1]
1469
[2]
Asthma
[3]
MESH: D001249
[4]
[5]
Air Pollutants | Methotrexate | Tretinoin
[6]
9.41
[7]
14
[21] array · 8 items
[0]
CST1
[1]
1469
[2]
Asthma, occupational
[3]
MESH: D059366
[4]
[5]
Silicon Dioxide
[6]
3.45
[7]
1
[22] array · 8 items
[0]
CST2
[1]
1470
[2]
Asthma, occupational
[3]
MESH: D059366
[4]
[5]
Silicon Dioxide
[6]
3.85
[7]
1
[23] array · 8 items
[0]
FETUB
[1]
26998
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Tobacco Smoke Pollution | Vehicle Emissions
[6]
5.71
[7]
2
[24] array · 8 items
[0]
FETUB
[1]
26998
[2]
Rhinitis, allergic
[3]
MESH: D065631
[4]
[5]
Atrazine
[6]
2.66
[7]
1
[25] array · 8 items
[0]
FETUB
[1]
26998
[2]
Nose diseases
[3]
MESH: D009668
[4]
[5]
cobaltous chloride | Tobacco Smoke Pollution
[6]
7.86
[7]
3
[26] array · 8 items
[0]
FETUB
[1]
26998
[2]
Sinusitis
[3]
MESH: D012852
[4]
[5]
Acetaminophen | Tobacco Smoke Pollution
[6]
6.66
[7]
2
locator
section[14]/table-wrap[1]#t3-medscimonit-26-e924934
[6] object · 16 fields
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asset:table:pmid:32460303:4
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jats-table
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note
The relationship between co-expressed genes and respiratory system diseases based on the CTD database.
structure object · 5 fields
pmcid
PMC7278529
section_index
19
section_title
Supplementary Materials
row_count
27
column_count
8
table object · 8 fields
label
Supplementary Table 1
caption
The relationship between co-expressed genes and respiratory system diseases based on the CTD database.
rows array · 27 items
[0] array · 8 items
[0]
Gene symbol
[1]
Gene ID
[2]
Disease name
[3]
Disease ID
[4]
Direct evidence
[5]
Inference network
[6]
Inference score
[7]
Reference count
[1] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Particulate Matter | Tobacco Smoke Pollution | Vehicle Emissions
[6]
12.67
[7]
3
[2] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Rhinitis, allergic
[3]
MESH: D065631
[4]
[5]
Particulate Matter | Soot
[6]
8.45
[7]
2
[3] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Rhinitis, allergic, seasonal
[3]
MESH: D006255
[4]
[5]
Particulate Matter
[6]
3.57
[7]
1
[4] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Asthma
[3]
MESH: D001249
[4]
[5]
Acetaminophen | Arsenic | Particulate Matter | Soot | Tobacco Smoke Pollution | Vehicle Emissions
[6]
21.02
[7]
29
[5] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Asthma, occupational
[3]
MESH: D059366
[4]
[5]
Silicon Dioxide
[6]
3.35
[7]
1
[6] array · 8 items
[0]
BPIFA1
[1]
51297
[2]
Nose diseases
[3]
MESH: D009668
[4]
[5]
Propylthiouracil | Tobacco Smoke Pollution
[6]
9.59
[7]
4
[7] array · 8 items
[0]
CCL26
[1]
10344
[2]
Asthma
[3]
MESH: D001249
[4]
[5]
Aerosols | Antigens, Dermatophagoides | Arsenic | Cadmium | Dexamethasone | Ozone | Resveratrol | Tobacco Smoke Pollution | Zinc
[6]
27.99
[7]
28
[8] array · 8 items
[0]
CCL26
[1]
10344
[2]
Rhinitis, allergic, perennial
[3]
MESH: D012221
[4]
[5]
Ozone
[6]
3.73
[7]
1
[9] array · 8 items
[0]
CCL26
[1]
10344
[2]
Rhinitis, allergic
[3]
MESH: D065631
[4]
[5]
Atrazine
[6]
2.83
[7]
1
[10] array · 8 items
[0]
CCL26
[1]
10344
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Tobacco Smoke Pollution
[6]
2.6
[7]
1
[11] array · 8 items
[0]
CCL26
[1]
10344
[2]
Nose diseases
[3]
MESH: D009668
[4]
[5]
Lipopolysaccharides | Propylthiouracil | Tobacco Smoke Pollution
[6]
14.31
[7]
5
[12] array · 8 items
[0]
CCL26
[1]
10344
[2]
Sinusitis
[3]
MESH: D012852
[4]
[5]
Tobacco Smoke Pollution
[6]
2.9
[7]
1
[13] array · 8 items
[0]
CPA3
[1]
1359
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Tobacco Smoke Pollution | Vehicle Emissions
[6]
6.86
[7]
2
[14] array · 8 items
[0]
CPA3
[1]
1359
[2]
Asthma
[3]
MESH: D001249
[4]
[5]
Acetaminophen | Decitabine | epigallocatechin gallate | Tobacco Smoke Pollution | trimellitic anhydride | Vehicle Emissions
[6]
18.84
[7]
19
[15] array · 8 items
[0]
CPA3
[1]
1359
[2]
Nose diseases
[3]
MESH: D009668
[4]
[5]
Tobacco Smoke Pollution
[6]
3.4
[7]
2
[16] array · 8 items
[0]
CPA3
[1]
1359
[2]
Sinusitis
[3]
MESH: D012852
[4]
[5]
Acetaminophen | Tobacco Smoke Pollution
[6]
7.83
[7]
2
[17] array · 7 items
[0]
CST1
[1]
1469
[2]
Rhinitis, allergic, seasonal
[3]
MESH: D006255
[4]
Marker/mechanism
[5]
[6]
1
[18] array · 8 items
[0]
CST1
[1]
1469
[2]
Rhinitis, allergic
[3]
MESH: D065631
[4]
[5]
Air Pollutants
[6]
3.83
[7]
1
[19] array · 8 items
[0]
CST1
[1]
1469
[2]
Rhinitis
[3]
MESH: D012220
[4]
[5]
Air Pollutants
[6]
3.6
[7]
1
[20] array · 8 items
[0]
CST1
[1]
1469
[2]
Asthma
[3]
MESH: D001249
[4]
[5]
Air Pollutants | Methotrexate | Tretinoin
[6]
9.41
[7]
14
[21] array · 8 items
[0]
CST1
[1]
1469
[2]
Asthma, occupational
[3]
MESH: D059366
[4]
[5]
Silicon Dioxide
[6]
3.45
[7]
1
[22] array · 8 items
[0]
CST2
[1]
1470
[2]
Asthma, occupational
[3]
MESH: D059366
[4]
[5]
Silicon Dioxide
[6]
3.85
[7]
1
[23] array · 8 items
[0]
FETUB
[1]
26998
[2]
Rhinitis
[3]
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26998
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MESH: D012852
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Additionally, the GSE104468 dataset, including collected nasal epithelia and bronchial epithelia sample from 12 subjects with allergic asthma and 12 control subjects, was used to identify differentially-expressed genes and molecular mechanisms of asthma [17].
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32460303", "kind": "science-record", "revision": 9, "content_hash": "sha256:4baa8a7cf46ca54cc8c3b3e3a369256ba9b4bcd8a394452937d0990334539899", "created_at": "2026-11-01T15:41:02Z", "updated_at": "2026-11-01T22:44:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics Analysis and Identification of Underlying Biomarkers Potentially Linking Allergic Rhinitis and Asthma.", "doi": "10.12659/MSM.924934", "pmid": "32460303", "authors": ["Zhanfeng Yan", "Lili Liu", "Lulu Jiao", "Xiaohui Wen", "Jianhua Liu", "Ningyu Wang"], "journal": "Medical science monitor : international medical journal of experimental and clinical research", "year": 2020, "abstract": "BACKGROUND Rhinitis is the most common clinical manifestation of allergy, affecting more than 400 million people around the world. Rhinitis increases the risk of developing bronchial hyper-responsiveness and asthma. Previous studies have shown that rhinitis is closely related with the physiology, pathology, and pathogenesis of asthma. We analyzed co-expressed genes to explore the relationships between rhinitis and asthma and to find biomarkers of comorbid rhinitis and asthma. MATERIAL AND METHODS Asthma- and rhinitis-related differentially-expressed genes (DEGs) were identified by bioinformatic analysis of GSE104468 and GSE46171 datasets from the Gene Expression Omnibus (GEO) database. After assessment of Gene Ontology (GO) terms and pathway enrichment for DEGs, a protein-protein interaction (PPI) network was conducted via comprehensive target prediction and network analyses. We also evaluated co-expressed DEGs and corresponding predicted miRNAs involved in the developing process of rhinitis and asthma. RESULTS We identified 687 and 1001 DEGs in bronchial and nasal epithelia samples of asthma patients, respectively. For patients with rhinitis, we found 245 DEGs. The hub-genes of PAX6, NMU, NTS, NMUR1, PMCH, and KRT6A may be associated with rhinitis, while CPA3, CTSG, POSTN, CLCA1, HDC, and MUC5B may be involved in asthma. The co-expressed DEGs of BPIFA1, CCL26, CPA3, and CST1, together with corresponding predicted miRNAs (e.g., miR-195-5p and miR-125a-3p) were found to be significantly correlated with rhinitis and asthma. CONCLUSIONS Rhinitis and asthma are related, and there are significant correlations of BPIFA1, CCL26, CPA3, and CST1 genes with novel biomarkers involved in the comorbidity of rhinitis and asthma.", "claims": [{"id": "claim-method", "statement": "The Bioconductor R packages “limma” [19], was applied to analyze GSE104468 and GSE46171 RAW datasets. 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"section_index": 19, "section_title": "Supplementary Materials", "row_count": 27, "column_count": 8}, "table": {"label": "Supplementary Table 1", "caption": "The relationship between co-expressed genes and respiratory system diseases based on the CTD database.", "rows": [["Gene symbol", "Gene ID", "Disease name", "Disease ID", "Direct evidence", "Inference network", "Inference score", "Reference count"], ["BPIFA1", "51297", "Rhinitis", "MESH: D012220", "", "Particulate Matter | Tobacco Smoke Pollution | Vehicle Emissions", "12.67", "3"], ["BPIFA1", "51297", "Rhinitis, allergic", "MESH: D065631", "", "Particulate Matter | Soot", "8.45", "2"], ["BPIFA1", "51297", "Rhinitis, allergic, seasonal", "MESH: D006255", "", "Particulate Matter", "3.57", "1"], ["BPIFA1", "51297", "Asthma", "MESH: D001249", "", "Acetaminophen | Arsenic | Particulate Matter | Soot | Tobacco Smoke Pollution | Vehicle Emissions", "21.02", "29"], ["BPIFA1", "51297", "Asthma, occupational", "MESH: D059366", "", "Silicon Dioxide", "3.35", "1"], ["BPIFA1", "51297", "Nose diseases", "MESH: D009668", "", "Propylthiouracil | Tobacco Smoke Pollution", "9.59", "4"], ["CCL26", "10344", "Asthma", "MESH: D001249", "", "Aerosols | Antigens, Dermatophagoides | Arsenic | Cadmium | Dexamethasone | Ozone | Resveratrol | Tobacco Smoke Pollution | Zinc", "27.99", "28"], ["CCL26", "10344", "Rhinitis, allergic, perennial", "MESH: D012221", "", "Ozone", "3.73", "1"], ["CCL26", "10344", "Rhinitis, allergic", "MESH: D065631", "", "Atrazine", "2.83", "1"], ["CCL26", "10344", "Rhinitis", "MESH: D012220", "", "Tobacco Smoke Pollution", "2.6", "1"], ["CCL26", "10344", "Nose diseases", "MESH: D009668", "", "Lipopolysaccharides | Propylthiouracil | Tobacco Smoke Pollution", "14.31", "5"], ["CCL26", "10344", "Sinusitis", "MESH: D012852", "", "Tobacco Smoke Pollution", "2.9", "1"], ["CPA3", "1359", "Rhinitis", "MESH: D012220", "", "Tobacco Smoke Pollution | Vehicle Emissions", "6.86", "2"], ["CPA3", "1359", "Asthma", "MESH: D001249", "", "Acetaminophen | Decitabine | epigallocatechin gallate | Tobacco Smoke Pollution | trimellitic anhydride | Vehicle Emissions", "18.84", "19"], ["CPA3", "1359", "Nose diseases", "MESH: D009668", "", "Tobacco Smoke Pollution", "3.4", "2"], ["CPA3", "1359", "Sinusitis", "MESH: D012852", "", "Acetaminophen | Tobacco Smoke Pollution", "7.83", "2"], ["CST1", "1469", "Rhinitis, allergic, seasonal", "MESH: D006255", "Marker/mechanism", "", "1"], ["CST1", "1469", "Rhinitis, allergic", "MESH: D065631", "", "Air Pollutants", "3.83", "1"], ["CST1", "1469", "Rhinitis", "MESH: D012220", "", "Air Pollutants", "3.6", "1"], ["CST1", "1469", "Asthma", "MESH: D001249", "", "Air Pollutants | Methotrexate | Tretinoin", "9.41", "14"], ["CST1", "1469", "Asthma, occupational", "MESH: D059366", "", "Silicon Dioxide", "3.45", "1"], ["CST2", "1470", "Asthma, occupational", "MESH: D059366", "", "Silicon Dioxide", "3.85", "1"], ["FETUB", "26998", "Rhinitis", "MESH: D012220", "", "Tobacco Smoke Pollution | Vehicle Emissions", "5.71", "2"], ["FETUB", "26998", "Rhinitis, allergic", "MESH: D065631", "", "Atrazine", "2.66", "1"], ["FETUB", "26998", "Nose diseases", "MESH: D009668", "", "cobaltous chloride | Tobacco Smoke Pollution", "7.86", "3"], ["FETUB", "26998", "Sinusitis", "MESH: D012852", "", "Acetaminophen | Tobacco Smoke Pollution", "6.66", "2"]], "row_count": 27, "column_count": 8, "numeric_cells": 109, "header_rows": 1, "locator": "section[19]/table-wrap[1]#db_ds_table-wrap1_reqid_"}}], "gaps": ["asset:data:geo:GSE104468 not downloaded", "asset:data:geo:GSE104468 licence not read", "asset:data:geo:GSE46171 not downloaded", "asset:data:geo:GSE46171 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The Bioconductor R packages “limma” [19], was applied to analyze GSE104468 and GSE46171 RAW datasets. Original p-values were corrected using the Benjamini-Hochberg method."}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "pathway enrichment"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"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": {"tier": "R1", "reachable": true, "accessions": ["GSE104468", "GSE46171"], "resolved_accessions": ["GSE104468", "GSE46171"], "statements": ["Additionally, the GSE104468 dataset, including collected nasal epithelia and bronchial epithelia sample from 12 subjects with allergic asthma and 12 control subjects, was used to identify differentially-expressed genes and molecular mechanisms of asthma [17]."], "basis": "The paper names GSE104468, GSE46171 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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