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RESEARCH
Clinical Oral Investigations (2025) 29:75
https://doi.org/10.1007/s00784-025-06164-0
Yongjie Tan and Ying He contributed equally to this work.
Extended author information available on the last page of the article
Abstract
Objectives We investigated the recently generated RNA-sequencing dataset of pulpitis to identify the potential pain-related
lncRNAs for pulpitis prediction.
Materials and methods Dierential analysis was performed on the gene expression prole between normal and pulpitis
samples to obtain pulpitis-related genes. The co-expressed gene modules were identied by weighted gene coexpression
network analysis (WGCNA). Then the hypergeometric test was utilized to screen pain-related core modules. The functional
enrichment analysis was performed on the up- and down-regulated genes in the core module of pulpitis pain to explore
the underlying mechanisms. A pain-related lncRNA-based classication model was constructed using LASSO. Consensus
clustering and gene set variation analysis (GSVA) on the inltrating immunocytes was used for pulpitis subtyping. miRanda
predicts miRNA-target relationship, which was ltered by expression correlation. Hallmark pathway and enrichment analy-
sis was performed to investigate the candidate target pathways of the lncRNAs.
Results A total of 1830 dierential RNAs were identied in pulpitis. WGCNA explored seven co-expressed modules,
among which the turquoise module is pain-related with hypergeometric test. The up-regulated genes were signicantly
enriched in immune response related pathways. Down-regulated genes were signicantly enriched in dierentiation path-
ways. Eight lncRNAs in the pain-related module were related to inammation. Among them, MIR181A2HG was downregu-
lated while other seven lncRNAs were upregulated in pulpitis. The LASSO classication model revealed that MIR181A2HG
and LINC00426 achieved outstanding predictive performances with perfect ROC-AUC score (AUC = 1). We dierentiated
the pulpitis samples into two progression subtypes and MIR181A2HG is a progressive marker for pulpitis. The miRNA-
mRNA-lncRNA regulatory network of pulpitis pain was constructed, with GATA3 as a key transcription factor. NF-kappa B
signaling pathway is a candidate pathway impacted by these lncRNAs.
Conclusions PCED1B-AS1, MIAT, MIR181A2HG, LINC00926, LINC00861, LINC00528, LINC00426 and ITGB2-AS1
may be potential markers of pulpitis pain. A two-lncRNA signature of LINC00426 and MIR181A2HG can accurately predict
pulpitis, which could facilitate the molecular diagnosis of pulpitis. GATA3 might regulate these lncRNAs and downstream
NF-kappa B signaling pathway.
Clinical relevance This study identied potential pain-related lncRNAs with underlying molecular mechanism analysis for
the prediction of pulpitis. The classication model based on lncRNAs will facilitate the early diagnosis of pulpitis.
Keywords Pulpitis · Pain · lncRNA · Prediction · Bioinformatic analysis
Received: 26 June 2024 / Accepted: 15 January 2025 / Published online: 22 January 2025
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025
Identication of pain-related long non-coding RNAs for pulpitis
prediction
YongjieTan1· YingHe2· YuexuanXu1· XilinQiu1· GuanruLiu1· LingxianLiu1· YeJiang2· MingyueLi1·
WeijunSun1,3· ZiqiangXie4· YonghuiHuang1· XinChen1· XuechaoYang2,5
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