Evidence map›Paper›PMID 35393522›Full record

ArticleScientific reports2022

Integrated bioinformatic analysis of gene expression profiling data to identify combinatorial biomarkers in inflammatory skin disease.

Heejin Bang, Ja Eun Kim, Hyun Su Lee, Sang Man Park, Dong-Joon Park, Eun Jung Lee

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. AlternativeExpert reviews in molecular medicine · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Heejin BangDepartment of Pathology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Republic of Korea.
Ja Eun KimYonsei University Wonju College of Medicine, Wonju, Republic of Korea.
Hyun Su LeeDepartment of Otorhinolaryngology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
Sang Man ParkDepartment of Otorhinolaryngology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
Dong-Joon ParkDepartment of Otorhinolaryngology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
Eun Jung LeeDepartment of Otorhinolaryngology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea. starlej@yonsei.ac.kr.
Yonsei University · KRKonkuk University Medical Center · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Selection of appropriate biomarker to identify inflammatory skin diseases is complicated by the involvement of thousands of differentially expressed genes (DEGs) across multiple cell types and organs. This study aimed to identify combinatorial biomarkers in inflammatory skin diseases. From one gene expression microarray profiling dataset, we performed bioinformatic analyses on dataset from lesional skin biopsies of patients with inflammatory skin diseases (atopic dermatitis [AD], contact eczema [KE], lichen planus [Li], psoriasis vulgaris [Pso]) and healthy controls to identify the involved pathways, predict upstream regulators, and potential measurable extracellular biomarkers. Overall, 434, 629, 581, and 738 DEGs were mapped in AD, KE, Li, and Pso, respectively; 238 identified DEGs were shared among four different inflammatory skin diseases. Bioinformatic analysis on four inflammatory skin diseases showed significant activation of pathways with known pathogenic relevance. Common upstream regulators, with upregulated predicted activity, identified were CNR1 and BMP4. We found the following common serum biomarkers: ACR, APOE, ASIP, CRISP1, DKK1, IL12B, IL9, MANF, MDK, NRTN, PCSK5, and VEGFC. Considerable differences of gene expression changes, involved pathways, upstream regulators, and biomarkers were found in different inflammatory skin diseases. Integrated bioinformatic analysis identified 12 potential common biomarkers of inflammatory skin diseases requiring further evaluation.

Indexed as

Dermatitis, AtopicSkin DiseasesBiomarkersComputational BiologyGene Expression ProfilingHumansSkinBiomarkers

Identifiers

PMID35393522
PMCPMC8989986
OpenAlexW4223510700

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.