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pmid:36765431

Exploration of the underlying comorbidity mechanism in psoriasis and periodontitis: a bioinformatics analysis.

Hao Lei · Xin Chen · Ziyang Wang · Zixuan Xing · Wenqian Du · Ruimin Bai · Ke He · Wen Zhang · Yan Wang · Yan Zheng

Hereditas · 2023 doi:10.1186/s41065-023-00266-z

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title
Exploration of the underlying comorbidity mechanism in psoriasis and periodontitis: a bioinformatics analysis.
doi
10.1186/s41065-023-00266-z
pmid
36765431
authors array · 10 items
[0]
Hao Lei
[1]
Xin Chen
[2]
Ziyang Wang
[3]
Zixuan Xing
[4]
Wenqian Du
[5]
Ruimin Bai
[6]
Ke He
[7]
Wen Zhang
[8]
Yan Wang
[9]
Yan Zheng
journal
Hereditas
year
2023
abstract
BACKGROUND: Increasing evidence indicates that psoriasis (PSO) and periodontitis (PD) are likely to occur together, however, the underlying mechanism remains unclear. MATERIALS AND METHODS: The expression profiles of PSO (lesion vs non-lesion, GSE30999, GSE14905) and PD (affected vs unaffected gingival tissue, GSE16134, GSE10334) were downloaded from the GEO database. First, we investigated the common differentially expressed genes (DEGs) of PSO and PD. Then, GO and KEGG enrichment analysis, protein interaction network (PPI) construction, and hub gene identification analysis were carried out. Finally, GO and KEGG enrichment analysis, miRNA interaction analysis, and transcription factors (TFs) interaction analysis for hub genes were performed. RESULTS: Eighteen DEGs were identified for further analysis, including 15 up-regulated genes and 3 down-regulated genes. 9 hub genes were then identified via Cytohubba, including IL1B, CXCL1, CXCL8, MMP12, CCL18, SELL, CXCL13, FCGR3B, and SELE. Their functions are mainly enriched in two aspects: neutrophil chemotaxis and migration, chemokine activation and interaction. The enriched signaling pathways includes three categories: host defense, inflammation-related signaling pathways, and disease-related pathways. 9 common miRNAs based on experimental evidence and 10 common TFs were further identified in both PSO and PD. CONCLUSION: Our study revealed possible comorbidity mechanisms in PSO and PD from the perspective of bioinformatics tentatively. The data can present new insight for joint prevention and treatment of in PSO and PD, as well as provide data support for further prospective studies.
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Eighteen DEGs were identified for further analysis, including 15 up-regulated genes and 3 down-regulated genes.
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[110]
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[111]
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[112]
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[113]
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[115]
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[116]
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[117]
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[118]
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[119]
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[120]
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[121]
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[122]
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[123]
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[124]
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[125]
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[126]
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[127]
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[128]
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[129]
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[130]
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[131]
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[132]
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[133]
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[134]
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[135]
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[136]
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[137]
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[138]
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[139]
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[140]
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[141]
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[142]
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[143]
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[144]
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[146]
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[147]
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[148]
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[149]
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[150]
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[151]
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[152]
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[153]
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[154]
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[155]
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[156]
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[157]
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[158]
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[159]
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[160]
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[161]
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[162]
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[163]
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[164]
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[165]
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[166]
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[167]
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[168]
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[169]
GSM404174
[170]
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[171]
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[172]
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[173]
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[174]
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[175]
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[176]
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[177]
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[178]
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[180]
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[181]
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[182]
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[183]
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[184]
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[185]
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[187]
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[188]
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[189]
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[191]
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[192]
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[193]
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[194]
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[196]
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[197]
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[198]
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[199]
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[200]
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[201]
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[202]
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[203]
GSM404208
[204]
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[205]
GSM404210
[206]
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[207]
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[208]
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[209]
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[210]
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[211]
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[212]
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[213]
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[214]
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[215]
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[216]
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[217]
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[218]
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[219]
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[220]
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[221]
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[222]
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[223]
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[224]
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[225]
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[227]
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[228]
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[230]
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[233]
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[235]
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[236]
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[238]
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[239]
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[240]
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[242]
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[243]
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[244]
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[245]
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[246]
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[247]
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[248]
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[249]
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[250]
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[251]
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[252]
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[253]
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[254]
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[255]
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[256]
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[257]
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[258]
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[259]
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[260]
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[261]
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[262]
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[263]
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[264]
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[265]
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[266]
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[267]
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[268]
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[269]
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[270]
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[271]
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[272]
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[273]
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[275]
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[276]
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[277]
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[294]
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[298]
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[301]
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[304]
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[305]
GSM404310
[306]
GSM404311
[307]
GSM404312
[308]
GSM404313
[309]
GSM404314
sample_count
310
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Bacterial Correlates of Gingival Gene Expression
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE30999
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=GSE30999
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE30999
version
null
note
There is no new datasets and materials.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
There is no new datasets and materials.
access_statement_kind
data_availability_statement
sample_accessions array · 170 items
[0]
GSM767976
[1]
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[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[30]
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[56]
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[65]
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[66]
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[68]
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[69]
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[70]
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[71]
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[72]
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[73]
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[74]
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[75]
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[76]
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[77]
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[78]
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[79]
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[80]
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[81]
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[82]
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[83]
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[84]
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[85]
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[86]
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[87]
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[93]
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[113]
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[114]
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[116]
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[117]
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[120]
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[125]
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[126]
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[168]
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[169]
GSM768145
sample_count
170
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Expression data from skin biopsy samples from patients with moderate-to-severe psoriasis
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 8 items
[0]
asset:data:geo:GSE10334 not downloaded
[1]
asset:data:geo:GSE10334 licence not read
[2]
asset:data:geo:GSE14905 not downloaded
[3]
asset:data:geo:GSE14905 licence not read
[4]
asset:data:geo:GSE16134 not downloaded
[5]
asset:data:geo:GSE16134 licence not read
[6]
asset:data:geo:GSE30999 not downloaded
[7]
asset:data:geo:GSE30999 licence not read
analysis object · 4 fields
state
complete
methods array · 3 items
[0] object · 10 fields
id
method-1
family
differential_expression
specific
limma_voom
label
Differential expression analysis
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
1
band
verbatim
quote
R package “limma” was used to identify DEGs.
[1] object · 10 fields
id
method-2
family
network_analysis
specific
ppi_network
label
Network / pathway analysis
dsl_operations array · 3 items
[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
PPI
[2] object · 10 fields
id
method-3
family
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
0.8
band
high
quote
pathway enrichment
targets array · 0 items
gaps array · 0 items
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 4 items
[0]
GSE30999
[1]
GSE14905
[2]
GSE16134
[3]
GSE10334
resolved_accessions array · 4 items
[0]
GSE30999
[1]
GSE14905
[2]
GSE16134
[3]
GSE10334
statements array · 1 item
[0]
There is no new datasets and materials.
basis
The paper names GSE30999, GSE14905, GSE16134, GSE10334 in GEO database and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
assets array · 2 items
[0]
source:pmid:36765431
[1]
data:geo:GSE10334
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:GSE10334
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
2026-11-01T18:26:51Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
8169
completion_tokens
1774
cached_tokens
256
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:36765431
type
paper
label
pmid:36765431
[1] object · 3 fields
id
source:pmid:36765431
type
manuscript
label
PMID 36765431 full text
[2] object · 3 fields
id
data:geo:GSE10334
type
dataset
label
GEO GSE10334
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:36765431
type
paper
label
pmid:36765431
[1] object · 3 fields
id
source:pmid:36765431
type
manuscript
label
PMID 36765431 full text
[2] object · 3 fields
id
data:geo:GSE10334
type
dataset
label
GEO GSE10334
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-36765431
type
extraction
used array · 1 item
[0]
source:pmid:36765431
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE10334
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE10334
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:36765431
parent_hash
sha256:e3d0e312e3626a1950f4fc608910877cf4ab2db9b49d518374f6445a6f3c38a2
fork_of
null
gaps array · 12 items
[0]
asset:data:geo:GSE10334 licence not read
[1]
asset:data:geo:GSE10334 not downloaded
[2]
asset:data:geo:GSE14905 licence not read
[3]
asset:data:geo:GSE14905 not downloaded
[4]
asset:data:geo:GSE16134 licence not read
[5]
asset:data:geo:GSE16134 not downloaded
[6]
asset:data:geo:GSE30999 licence not read
[7]
asset:data:geo:GSE30999 not downloaded
[8]
execution.not_run
[9]
review.human_critique
[10]
review.independent_reader
[11]
review.machine_critique
assays array · 1 item
[0] object · 11 fields
role
analysis
definition_id
differential_expression
definition_version
f2132e96ae6c7a4e
required_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
R package “limma” was used to identify DEGs.
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:36765431", "kind": "science-record", "revision": 4, "content_hash": "sha256:4d477c64275b1e57294bcfd94db3e8debb7cc57499c457be37f8588722dfec06", "created_at": "2026-11-01T19:01:20Z", "updated_at": "2026-11-01T22:51:14Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploration of the underlying comorbidity mechanism in psoriasis and periodontitis: a bioinformatics analysis.", "doi": "10.1186/s41065-023-00266-z", "pmid": "36765431", "authors": ["Hao Lei", "Xin Chen", "Ziyang Wang", "Zixuan Xing", "Wenqian Du", "Ruimin Bai", "Ke He", "Wen Zhang", "Yan Wang", "Yan Zheng"], "journal": "Hereditas", "year": 2023, "abstract": "BACKGROUND: Increasing evidence indicates that psoriasis (PSO) and periodontitis (PD) are likely to occur together, however, the underlying mechanism remains unclear.\nMATERIALS AND METHODS: The expression profiles of PSO (lesion vs non-lesion, GSE30999, GSE14905) and PD (affected vs unaffected gingival tissue, GSE16134, GSE10334) were downloaded from the GEO database. First, we investigated the common differentially expressed genes (DEGs) of PSO and PD. Then, GO and KEGG enrichment analysis, protein interaction network (PPI) construction, and hub gene identification analysis were carried out. Finally, GO and KEGG enrichment analysis, miRNA interaction analysis, and transcription factors (TFs) interaction analysis for hub genes were performed.\nRESULTS: Eighteen DEGs were identified for further analysis, including 15 up-regulated genes and 3 down-regulated genes. 9 hub genes were then identified via Cytohubba, including IL1B, CXCL1, CXCL8, MMP12, CCL18, SELL, CXCL13, FCGR3B, and SELE. Their functions are mainly enriched in two aspects: neutrophil chemotaxis and migration, chemokine activation and interaction. The enriched signaling pathways includes three categories: host defense, inflammation-related signaling pathways, and disease-related pathways. 9 common miRNAs based on experimental evidence and 10 common TFs were further identified in both PSO and PD.\nCONCLUSION: Our study revealed possible comorbidity mechanisms in PSO and PD from the perspective of bioinformatics tentatively. The data can present new insight for joint prevention and treatment of in PSO and PD, as well as provide data support for further prospective studies.", "claims": [{"id": "claim-method", "statement": "R package “limma” was used to identify DEGs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36765431", "locator": "sections[15] \"Identification of DEGs\" paragraph 2", "quote": "R package “limma” was used to identify DEGs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "There is no new datasets and materials.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36765431", "locator": "sections[29] \"notes\" paragraph 1", "quote": "There is no new datasets and materials."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Eighteen DEGs were identified for further analysis, including 15 up-regulated genes and 3 down-regulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36765431", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Eighteen DEGs were identified for further analysis, including 15 up-regulated genes and 3 down-regulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Eighteen DEGs were identified for further analysis, including 15 up-regulated genes and 3 down-regulated genes.", "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:36765431"], "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:GSE10334"], "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:GSE10334"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36765431", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s41065-023-00266-z", "sha256": 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