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pmid:32669126

Identification of candidate biomarkers and pathways associated with psoriasis using bioinformatics analysis.

Yongqi Luo · Yangyang Luo · Jing Chang · Zhenghui Xiao · Bin Zhou

Hereditas · 2020 doi:10.1186/s41065-020-00141-1

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:32669126
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2026-11-01T15:41:06Z
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title
Identification of candidate biomarkers and pathways associated with psoriasis using bioinformatics analysis.
doi
10.1186/s41065-020-00141-1
pmid
32669126
authors array · 5 items
[0]
Yongqi Luo
[1]
Yangyang Luo
[2]
Jing Chang
[3]
Zhenghui Xiao
[4]
Bin Zhou
journal
Hereditas
year
2020
abstract
BACKGROUND: The aim of this study was to identify the candidate biomarkers and pathways associated with psoriasis. GSE13355 and GSE14905 were extracted from the Gene Expression Omnibus (GEO) database. Then the differentially expressed genes (DEGs) with |logFC| > 2 and adjusted P < 0.05 were chosen. In addition, the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for DEGs were performed. Then, the GO terms with P < 0.05 and overlap coefficient greater than 0.5 were integrated by EnrichmentMap. Additionally, risk subpathways analysis for DEGs was also conducted by using the iSubpathwayMiner package to obtain more psoriasis-related DEGs and pathways. Finally, protein-protein interaction (PPI) network analysis was performed to identify the hub genes, and the DGIdb database was utilized to search for the candidate drugs for psoriasis. RESULTS: A total of 127 DEGs which were mostly associated with keratinization, keratinocyte differentiation, and epidermal cell differentiation biological processes were identified. Based on these GO terms, 3 modules (human skin, epidermis and cuticle differentiation, and enzyme activity) were constructed. Moreover, 9 risk subpathways such as steroid hormone biosynthesis, folate biosynthesis, and pyrimidine metabolism were screened. Finally, PPI network analysis demonstrated that CXCL10 was the hub gene with the highest degree, and CXCR2, CXCL10, IVL, OASL, and ISG15 were the potential gene targets of the drugs for treating psoriasis. CONCLUSION: Psoriasis may be mostly caused by keratinization, keratinocyte differentiation, and epidermal cell differentiation; the pathogeneses were more related with pathways such as steroid hormone biosynthesis, folate biosynthesis, and pyrimidine metabolism. Besides, some psoriasis-related genes such as SPRR genes, HSD11B1, GGH, CXCR2, IVL, OASL, ISG15, and CXCL10 may be important targets in psoriatic therapy.
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After data preprocessing, the limma package [31] of R language was utilized to screen DEGs. The false discovery rate (FDR) of Benjamini and Hochberg (BH) method was applied to adjust p-values for multiple comparisons.
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sections[13] "Data preprocessing and screening of differentially expressed genes" paragraph 3
quote
After data preprocessing, the limma package [31] of R language was utilized to screen DEGs. The false discovery rate (FDR) of Benjamini and Hochberg (BH) method was applied to adjust p-values for multiple comparisons.
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sections[27] "notes" paragraph 1
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All data generated or analysed during this study are included in this published article.
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Gene expression data of skin from psoriatic patients and normal controls
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All data generated or analysed during this study are included in this published article.
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Homo sapiens
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Type I Interferon: Potential Therapeutic Target for Psoriasis?
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Top 10 GO terms in biological process for differentially expressed genes (DEGs) in gene expression profile of psoriatic patients (P < 0.05)
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Functional enrichment analysis of differentially expressed genes
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Top 10 GO terms in biological process for differentially expressed genes (DEGs) in gene expression profile of psoriatic patients (P < 0.05)
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[1]
Keratinization
[2]
6.15E-10
[3]
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GO:0009913
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2.01E-09
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GO:0007398
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Defense response
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GO:0008544
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7.87E-08
[3]
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[0]
GO:0060429
[1]
Epithelium development
[2]
6.53E-07
[3]
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[0]
GO:0006935
[1]
Chemotaxis
[2]
2.12E-06
[3]
CXCL1, IL8, CCL20, CXCL13, S100A9, CXCL9, CXCR2, CCL27, CCL18, CXCL10
[10] array · 4 items
[0]
GO:0042330
[1]
Taxis
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2.12E-06
[3]
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KEGG pathway enrichment analysis of differentially expressed genes (DEGs) in gene expression profile of psoriatic patients (P < 0.05)
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Functional enrichment analysis of differentially expressed genes
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KEGG pathway enrichment analysis of differentially expressed genes (DEGs) in gene expression profile of psoriatic patients (P < 0.05)
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[1]
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5.17E-06
[3]
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7.37E-04
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Risk subpathway enrichment analysis of differentially expressed genes (DEGs) in psoriatic patients (P < 0.05)
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Risk subpathway enrichment analysis of differentially expressed genes
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Table 3
caption
Risk subpathway enrichment analysis of differentially expressed genes (DEGs) in psoriatic patients (P < 0.05)
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[0]
ID
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Name
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Pvalue
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DEGs
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[0]
Path:00140_13
[1]
Steroid hormone biosynthesis
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0.01561
[3]
HSD11B1
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Path:00790_4
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Folate biosynthesis
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0.01561
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GGH
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Path:00240_21
[1]
Pyrimidine metabolism
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0.019471
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CMPK2, RRM2
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Path:00240_16
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0.030339
[3]
CMPK2, RRM2
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Path:00531_3
[1]
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0.041091
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HYAL4
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Path:00240_12
[1]
Pyrimidine metabolism
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0.044307
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CMPK2, RRM2
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Steroid hormone biosynthesis
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0.046108
[3]
HSD11B1
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Path:00380_10
[1]
Tryptophan metabolism
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0.046108
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KYNU
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[0]
Path:00480_6
[1]
Glutathione metabolism
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0.046108
[3]
RRM2
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section[6]/table-wrap[1]#Tab3
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Top 16 proteins of the higher degrees in protein-protein interaction (PPI) network of differentially expressed genes (DEGs)
structure object · 5 fields
pmcid
PMC7364515
section_index
7
section_title
Construction of protein-protein interaction network based on differentially expressed genes
row_count
17
column_count
2
table object · 8 fields
label
Table 4
caption
Top 16 proteins of the higher degrees in protein-protein interaction (PPI) network of differentially expressed genes (DEGs)
rows array · 17 items
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Degree
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CXCL10
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STAT1
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CXCL1
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CXCL9
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IRF7
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IVL
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12
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MX1
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S100A9
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CXCR2
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11
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ISG15
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11
[11] array · 2 items
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OAS1
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11
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[0]
OASL
[1]
11
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[0]
RSAD2
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11
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RTP4
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11
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SPRR1B
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11
[16] array · 2 items
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CMPK2
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10
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section[7]/table-wrap[1]#Tab4
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Candidate drugs targeting hub genes
structure object · 5 fields
pmcid
PMC7364515
section_index
8
section_title
Drug-hub gene interaction
row_count
37
column_count
5
table object · 8 fields
label
Table 5
caption
Candidate drugs targeting hub genes
rows array · 37 items
[0] array · 5 items
[0]
gene
[1]
drug
[2]
interaction_types
[3]
sources
[4]
pmids
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CXCR2
[1]
PROPOFOL
[2]
agonist
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GuideToPharmacologyInteractions
[4]
–
[2] array · 5 items
[0]
CXCR2
[1]
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agonist
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GuideToPharmacologyInteractions
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–
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CXCR2
[1]
CHEMBL411250
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agonist
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GuideToPharmacologyInteractions
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CXCR2
[1]
MEPHENTERMINE
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agonist
[3]
GuideToPharmacologyInteractions
[4]
–
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[0]
CXCR2
[1]
REPARIXIN
[2]
allosteric modulator|modulator|antagonist
[3]
GuideToPharmacologyInteractions|ChemblInteractions|TTD
[4]
–
[6] array · 5 items
[0]
CXCR2
[1]
DANIRIXIN
[2]
antagonist
[3]
GuideToPharmacologyInteractions|ChemblInteractions
[4]
–
[7] array · 5 items
[0]
CXCR2
[1]
NAVARIXIN
[2]
antagonist
[3]
GuideToPharmacologyInteractions|ChemblInteractions|TTD
[4]
–
[8] array · 5 items
[0]
CXCR2
[1]
CHEMBL239767
[2]
antagonist
[3]
GuideToPharmacologyInteractions
[4]
–
[9] array · 5 items
[0]
CXCR2
[1]
NAVARIXIN HYDRATE
[2]
antagonist
[3]
ChemblInteractions
[4]
–
[10] array · 5 items
[0]
CXCR2
[1]
ELUBRIXIN
[2]
antagonist
[3]
ChemblInteractions|TTD
[4]
–
[11] array · 5 items
[0]
CXCR2
[1]
Ladarixin
[2]
modulator
[3]
ChemblInteractions
[4]
–
[12] array · 5 items
[0]
CXCR2
[1]
BEVACIZUMAB
[2]
–
[3]
PharmGKB
[4]
–
[13] array · 5 items
[0]
CXCR2
[1]
CYCLOPHOSPHAMIDE
[2]
–
[3]
PharmGKB
[4]
–
[14] array · 5 items
[0]
CXCR2
[1]
ACETYLCYSTEINE
[2]
–
[3]
NCI
[4]
10,716,998
[15] array · 5 items
[0]
CXCR2
[1]
MECHLORETHAMINE HYDROCHLORIDE
[2]
–
[3]
NCI
[4]
12,753,603
[16] array · 5 items
[0]
CXCR2
[1]
VITAMIN E
[2]
–
[3]
NCI
[4]
16,679,868
[17] array · 5 items
[0]
CXCR2
[1]
GENISTEIN
[2]
–
[3]
NCI
[4]
9,712,063
[18] array · 5 items
[0]
ISG15
[1]
IRINOTECAN
[2]
inhibitor
[3]
MyCancerGenomeClinicalTrial
[4]
–
[19] array · 5 items
[0]
OASL
[1]
PEGINTERFERON ALFA-2B
[2]
–
[3]
PharmGKB
[4]
–
[20] array · 5 items
[0]
OASL
[1]
RIBAVIRIN
[2]
–
[3]
PharmGKB
[4]
–
[21] array · 5 items
[0]
IVL
[1]
ETRETINATE
[2]
–
[3]
NCI
[4]
12,445,200|8,381,448
[22] array · 5 items
[0]
IVL
[1]
RETINYL ACETATE
[2]
–
[3]
NCI
[4]
6,189,593
[23] array · 5 items
[0]
IVL
[1]
PERILLYL ALCOHOL
[2]
–
[3]
NCI
[4]
10,769,631
[24] array · 5 items
[0]
CXCL10
[1]
NI-0801
[2]
inhibitor
[3]
ChemblInteractions
[4]
–
[25] array · 5 items
[0]
CXCL10
[1]
METHYLPREDNISOLONE
[2]
–
[3]
NCI
[4]
17,220,550
[26] array · 5 items
[0]
CXCL10
[1]
TESTOSTERONE
[2]
–
[3]
NCI
[4]
9,681,518
[27] array · 5 items
[0]
CXCL10
[1]
REGRAMOSTIM
[2]
–
[3]
NCI
[4]
11,591,765
[28] array · 5 items
[0]
CXCL10
[1]
OXALIPLATIN
[2]
–
[3]
NCI
[4]
16,101,140
[29] array · 5 items
[0]
CXCL10
[1]
ANTIBIOTIC
[2]
–
[3]
NCI
[4]
10,634,213
[30] array · 5 items
[0]
CXCL10
[1]
ZIDOVUDINE
[2]
–
[3]
NCI
[4]
11,141,242
[31] array · 5 items
[0]
CXCL10
[1]
ATROPINE
[2]
–
[3]
NCI
[4]
15,315,164
[32] array · 5 items
[0]
CXCL10
[1]
ELDELUMAB
[2]
–
[3]
TdgClinicalTrial
[4]
–
[33] array · 5 items
[0]
CXCL10
[1]
STAVUDINE
[2]
–
[3]
NCI
[4]
11,141,242
[34] array · 5 items
[0]
CXCL10
[1]
GONADOTROPIN, CHORIONIC
[2]
–
[3]
NCI
[4]
15,590,984
[35] array · 5 items
[0]
CXCL10
[1]
RITONAVIR
[2]
–
[3]
NCI
[4]
11,141,242
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[0]
CXCL10
[1]
ATORVASTATIN
[2]
–
[3]
NCI
[4]
10,559,511
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section[8]/table-wrap[1]#Tab5
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Candidate drugs targeting hub genes
structure object · 5 fields
pmcid
PMC7364515
section_index
18
section_title
Drug-hub gene interaction
row_count
37
column_count
5
table object · 8 fields
label
Table 5
caption
Candidate drugs targeting hub genes
rows array · 37 items
[0] array · 5 items
[0]
gene
[1]
drug
[2]
interaction_types
[3]
sources
[4]
pmids
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[0]
CXCR2
[1]
PROPOFOL
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agonist
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GuideToPharmacologyInteractions
[4]
–
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[0]
CXCR2
[1]
BENZPIPERYLON
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agonist
[3]
GuideToPharmacologyInteractions
[4]
–
[3] array · 5 items
[0]
CXCR2
[1]
CHEMBL411250
[2]
agonist
[3]
GuideToPharmacologyInteractions
[4]
–
[4] array · 5 items
[0]
CXCR2
[1]
MEPHENTERMINE
[2]
agonist
[3]
GuideToPharmacologyInteractions
[4]
–
[5] array · 5 items
[0]
CXCR2
[1]
REPARIXIN
[2]
allosteric modulator|modulator|antagonist
[3]
GuideToPharmacologyInteractions|ChemblInteractions|TTD
[4]
–
[6] array · 5 items
[0]
CXCR2
[1]
DANIRIXIN
[2]
antagonist
[3]
GuideToPharmacologyInteractions|ChemblInteractions
[4]
–
[7] array · 5 items
[0]
CXCR2
[1]
NAVARIXIN
[2]
antagonist
[3]
GuideToPharmacologyInteractions|ChemblInteractions|TTD
[4]
–
[8] array · 5 items
[0]
CXCR2
[1]
CHEMBL239767
[2]
antagonist
[3]
GuideToPharmacologyInteractions
[4]
–
[9] array · 5 items
[0]
CXCR2
[1]
NAVARIXIN HYDRATE
[2]
antagonist
[3]
ChemblInteractions
[4]
–
[10] array · 5 items
[0]
CXCR2
[1]
ELUBRIXIN
[2]
antagonist
[3]
ChemblInteractions|TTD
[4]
–
[11] array · 5 items
[0]
CXCR2
[1]
Ladarixin
[2]
modulator
[3]
ChemblInteractions
[4]
–
[12] array · 5 items
[0]
CXCR2
[1]
BEVACIZUMAB
[2]
–
[3]
PharmGKB
[4]
–
[13] array · 5 items
[0]
CXCR2
[1]
CYCLOPHOSPHAMIDE
[2]
–
[3]
PharmGKB
[4]
–
[14] array · 5 items
[0]
CXCR2
[1]
ACETYLCYSTEINE
[2]
–
[3]
NCI
[4]
10,716,998
[15] array · 5 items
[0]
CXCR2
[1]
MECHLORETHAMINE HYDROCHLORIDE
[2]
–
[3]
NCI
[4]
12,753,603
[16] array · 5 items
[0]
CXCR2
[1]
VITAMIN E
[2]
–
[3]
NCI
[4]
16,679,868
[17] array · 5 items
[0]
CXCR2
[1]
GENISTEIN
[2]
–
[3]
NCI
[4]
9,712,063
[18] array · 5 items
[0]
ISG15
[1]
IRINOTECAN
[2]
inhibitor
[3]
MyCancerGenomeClinicalTrial
[4]
–
[19] array · 5 items
[0]
OASL
[1]
PEGINTERFERON ALFA-2B
[2]
–
[3]
PharmGKB
[4]
–
[20] array · 5 items
[0]
OASL
[1]
RIBAVIRIN
[2]
–
[3]
PharmGKB
[4]
–
[21] array · 5 items
[0]
IVL
[1]
ETRETINATE
[2]
–
[3]
NCI
[4]
12,445,200|8,381,448
[22] array · 5 items
[0]
IVL
[1]
RETINYL ACETATE
[2]
–
[3]
NCI
[4]
6,189,593
[23] array · 5 items
[0]
IVL
[1]
PERILLYL ALCOHOL
[2]
–
[3]
NCI
[4]
10,769,631
[24] array · 5 items
[0]
CXCL10
[1]
NI-0801
[2]
inhibitor
[3]
ChemblInteractions
[4]
–
[25] array · 5 items
[0]
CXCL10
[1]
METHYLPREDNISOLONE
[2]
–
[3]
NCI
[4]
17,220,550
[26] array · 5 items
[0]
CXCL10
[1]
TESTOSTERONE
[2]
–
[3]
NCI
[4]
9,681,518
[27] array · 5 items
[0]
CXCL10
[1]
REGRAMOSTIM
[2]
–
[3]
NCI
[4]
11,591,765
[28] array · 5 items
[0]
CXCL10
[1]
OXALIPLATIN
[2]
–
[3]
NCI
[4]
16,101,140
[29] array · 5 items
[0]
CXCL10
[1]
ANTIBIOTIC
[2]
–
[3]
NCI
[4]
10,634,213
[30] array · 5 items
[0]
CXCL10
[1]
ZIDOVUDINE
[2]
–
[3]
NCI
[4]
11,141,242
[31] array · 5 items
[0]
CXCL10
[1]
ATROPINE
[2]
–
[3]
NCI
[4]
15,315,164
[32] array · 5 items
[0]
CXCL10
[1]
ELDELUMAB
[2]
–
[3]
TdgClinicalTrial
[4]
–
[33] array · 5 items
[0]
CXCL10
[1]
STAVUDINE
[2]
–
[3]
NCI
[4]
11,141,242
[34] array · 5 items
[0]
CXCL10
[1]
GONADOTROPIN, CHORIONIC
[2]
–
[3]
NCI
[4]
15,590,984
[35] array · 5 items
[0]
CXCL10
[1]
RITONAVIR
[2]
–
[3]
NCI
[4]
11,141,242
[36] array · 5 items
[0]
CXCL10
[1]
ATORVASTATIN
[2]
–
[3]
NCI
[4]
10,559,511
locator
section[8]/table-wrap[1]#Tab5
gaps array · 4 items
[0]
asset:data:geo:GSE13355 not downloaded
[1]
asset:data:geo:GSE13355 licence not read
[2]
asset:data:geo:GSE14905 not downloaded
[3]
asset:data:geo:GSE14905 licence not read
analysis object · 4 fields
state
partial
methods array · 4 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 · 1 field
fdr_threshold
with Benjamini–Hochberg false discovery rate adjustment
data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
band
verbatim
quote
After data preprocessing, the limma package [31] of R language was utilized to screen DEGs. The false discovery rate (FDR) of Benjamini and Hochberg (BH) method was applied to adjust p-values for multiple comparisons.
[1] object · 10 fields
id
method-2
family
principal_component_analysis
specific
pca
label
Principal component analysis
dsl_operations array · 1 item
[0]
pca_fit
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
wide_numeric_matrix
evidence object · 3 fields
score
0.8
band
high
quote
Principal component analysis
[2] object · 10 fields
id
method-3
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
[3] object · 10 fields
id
method-4
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
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
pathway enrichment
targets array · 0 items
gaps array · 1 item
[0]
method.reader_differs_from_extractor
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 · 2 items
[0]
GSE13355
[1]
GSE14905
resolved_accessions array · 2 items
[0]
GSE13355
[1]
GSE14905
statements array · 1 item
[0]
All data generated or analysed during this study are included in this published article.
basis
The paper names GSE13355, GSE14905 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]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 8 items
[0]
source:pmid:32669126
[1]
data:geo:GSE13355
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asset:table:pmid:32669126:1
[3]
asset:table:pmid:32669126:2
[4]
asset:table:pmid:32669126:3
[5]
asset:table:pmid:32669126:4
[6]
asset:table:pmid:32669126:5
[7]
asset:table:pmid:32669126:6
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
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After data preprocessing, the limma package [31] of R language was utilized to screen DEGs. The false discovery rate (FDR) of Benjamini and Hochberg (BH) method was applied to adjust p-values for multiple comparisons.
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32669126", "kind": "science-record", "revision": 8, "content_hash": "sha256:1cd50bc2f3722d746e869a9a654023b98447d99099288e0ce0eecefa2c73f048", "created_at": "2026-11-01T15:41:06Z", "updated_at": "2026-11-01T22:45:06Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of candidate biomarkers and pathways associated with psoriasis using bioinformatics analysis.", "doi": "10.1186/s41065-020-00141-1", "pmid": "32669126", "authors": ["Yongqi Luo", "Yangyang Luo", "Jing Chang", "Zhenghui Xiao", "Bin Zhou"], "journal": "Hereditas", "year": 2020, "abstract": "BACKGROUND: The aim of this study was to identify the candidate biomarkers and pathways associated with psoriasis. GSE13355 and GSE14905 were extracted from the Gene Expression Omnibus (GEO) database. Then the differentially expressed genes (DEGs) with |logFC| > 2 and adjusted P < 0.05 were chosen. In addition, the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for DEGs were performed. Then, the GO terms with P < 0.05 and overlap coefficient greater than 0.5 were integrated by EnrichmentMap. Additionally, risk subpathways analysis for DEGs was also conducted by using the iSubpathwayMiner package to obtain more psoriasis-related DEGs and pathways. Finally, protein-protein interaction (PPI) network analysis was performed to identify the hub genes, and the DGIdb database was utilized to search for the candidate drugs for psoriasis.\nRESULTS: A total of 127 DEGs which were mostly associated with keratinization, keratinocyte differentiation, and epidermal cell differentiation biological processes were identified. Based on these GO terms, 3 modules (human skin, epidermis and cuticle differentiation, and enzyme activity) were constructed. Moreover, 9 risk subpathways such as steroid hormone biosynthesis, folate biosynthesis, and pyrimidine metabolism were screened. Finally, PPI network analysis demonstrated that CXCL10 was the hub gene with the highest degree, and CXCR2, CXCL10, IVL, OASL, and ISG15 were the potential gene targets of the drugs for treating psoriasis.\nCONCLUSION: Psoriasis may be mostly caused by keratinization, keratinocyte differentiation, and epidermal cell differentiation; the pathogeneses were more related with pathways such as steroid hormone biosynthesis, folate biosynthesis, and pyrimidine metabolism. Besides, some psoriasis-related genes such as SPRR genes, HSD11B1, GGH, CXCR2, IVL, OASL, ISG15, and CXCL10 may be important targets in psoriatic therapy.", "claims": [{"id": "claim-method", "statement": "After data preprocessing, the limma package [31] of R language was utilized to screen DEGs. 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The false discovery rate (FDR) of Benjamini and Hochberg (BH) method was applied to adjust p-values for multiple comparisons."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data generated or analysed during this study are included in this published article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32669126", "locator": "sections[27] \"notes\" paragraph 1", "quote": "All data generated or analysed during this study are included in this published article."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:32669126"], "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:GSE13355"], "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": {"fdr_threshold": "with Benjamini–Hochberg false discovery rate adjustment"}, "inputs": ["data:geo:GSE13355"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32669126", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": 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differentially expressed genes (DEGs) in gene expression profile of psoriatic patients (P < 0.05)", "rows": [["ID", "Name", "Pvalue", "DEGs"], ["GO:0031424", "Keratinization", "6.15E-10", "SPRR2C, SPRR1A, SPRR1B, LCE3D, TGM1, CNFN, SPRR3, TGM3, SPRR2G, IVL"], ["GO:0030216", "Keratinocyte differentiation", "9.07E-10", "SPRR2C, S100A7, SPRR1A, SPRR1B, LCE3D, TGM1, CNFN, SPRR3, TGM3, SPRR2G, IVL"], ["GO:0009913", "Epidermal cell differentiation", "2.01E-09", "SPRR2C, S100A7, SPRR1A, SPRR1B, LCE3D, TGM1, CNFN, SPRR3, TGM3, SPRR2G, IVL"], ["GO:0007398", "Ectoderm development", "1.76E-08", "KRT6A, S100A7, LCE3D, SPRR2G, SPRR2C, KRT16, SPRR1A, SPRR1B, CNFN, TGM1, SPRR3, TGM3, ALOX12B, IVL"], ["GO:0030855", "Epithelial cell differentiation", "4.85E-08", "RHCG, SPRR2C, S100A7, SPRR1A, SPRR1B, LCE3D, TGM1, CNFN, SPRR3, TGM3, SPRR2G, IVL"], ["GO:0006952", "Defense response", "5.96E-08", "CXCL1, DCD, KYNU, IL8, S100A8, S100A7, S100A9, CXCL9, RSAD2, CXCR2, CCL18, S100A12, CXCL10, WFDC12, FOS, 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