Cited by 19Spondyloarthritis Studies and TreatmentsRheumatoid Arthritis Research and TherapiesCancer-related molecular mechanisms research

Comprehensive analyses of long non-coding RNA expression profiles by RNA sequencing and exploration of their potency as biomarkers in psoriatic arthritis patients

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Yue, Tao, Ji, Mei, Qu, Huanru, Guo, Mengru, Bai, Fengmin, Zhang, Zhanming, Wang, Weifeng, Gong, Xuming +1 more·2019·BMC Immunology

Abstract

BACKGROUND: The aim of the current study was to investigate the long non-coding RNA (lncRNA) expression profiles in psoriatic arthritis (PSA) patients by RNA sequencing, and to further explore potential biomarkers that were able to predict PSA risk and activity. METHODS: LncRNA and mRNA expression profiles in peripheral blood mononuclear cells (PBMC) of 4 PSA patients and 4 normal controls (NCs) were detected by RNA sequencing, followed by comprehensive bioinformatic analyses. Subsequently, 3 top upregulated and 2 top downregulated lncRNAs were chosen for further validation in 93 PSA patients and 93 NCs by quantitative polymerase chain reaction (qPCR) assay. RESULTS: Totally 76 upregulated and 54 downregulated lncRNAs, as well as 231 upregulated and 102 downregulated mRNAs were discovered in PSA patients compared with NCs. Enrichment analyses revealed that they were mostly associated with nucleosome, extracellular exosome and extracellular matrix, and the top enriched pathways were systemic lupus erythematosus (SLE), alcoholism and viral carcinogenesis. qPCR assay showed that lnc-RP11-701H24.7 and lnc-RNU12 were upregulated in PSA patients compared with NCs, and they could predict PSA risk with high area under curves. Besides, lnc-RP11-701H24.7 was positively associated with ESR, SJC, TJC and pain VAS score while lnc-RNU12 was positively correlated with PASI score, CRP and PGA score, implying that both of them were positively correlated with disease activity. CONCLUSION: Our study facilitates comprehensive understanding of lncRNA expression profiles in PSA pathogenesis, and discovers that lnc-RP11-701H24.7 and lnc-RNU12 might be served as novel biomarkers for PSA risk and activity.

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Authors
Yue, T., Ji, M., Qu, H., Guo, M., Bai, F., Zhang, Z., Wang, W., Gong, X., & Zhang, Z.
Affiliations
  • Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine (CN)
  • Shanghai Skin Disease Hospital (CN)
  • Shanghai University of Traditional Chinese Medicine (CN)
  • Fudan University (CN)
Corresponding author
  • Yue, Tao
  • Zhang, Zhanming
  • Zhang, Zhenghua
Venue
BMC Immunology
Published
2019-08-07
Volume
20
Issue
1
Pages
28-28
ISSN
1471-2172 (ISSN-L)
OpenAlex
W2964655141
Cited by
19
References
34
Citations by year
2026: 1 · 2024: 2 · 2023: 2 · 2022: 7 · 2021: 2 · 2020: 4 · 2019: 1
FWCI
2.65
Type
journal article
Language
en
Open access
Locations
  • BMC Immunology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Prioyity Speciality for Changning District, Shanghai Municipal Commission of Health and Family Planning (20161003)
Topics
  • Health Sciences › Medicine › Rheumatology › Spondyloarthritis Studies and Treatments
  • Health Sciences › Medicine › Rheumatology › Rheumatoid Arthritis Research and Therapies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
Keywords
psoriatic arthritis, long non-coding RNA, lncRNA expression profiles, biomarkers, disease activity, disease risk prediction, peripheral blood mononuclear cells, exosomes, extracellular matrix
MeSH terms
Female, Humans, Male, RNA, Messenger, Sensitivity and Specificity, Biomarkers, Arthritis, Psoriatic, Computational Biology, Gene Expression Profiling, Gene Regulatory Networks, Workflow, High-Throughput Nucleotide Sequencing, Transcriptome, RNA, Long Noncoding, Gene Ontology

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