Evidence map›Paper›PMID 42634206›Full record

ArticleJournal of cellular and molecular medicine2026

Identification and Experimental Validation of Key Genes Related to Neuroendocrine in Periodontitis Based on Single-Cell and Bulk Transcriptome Data.

Jiaguan Zhang, Ziyan Liu, Jianqing Deng, Peishan Huang, Huijuan Liu

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Jiaguan ZhangThe Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhe, China.ORCID 0009-0002-9521-2542
Ziyan LiuThe Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhe, China.
Jianqing DengThe Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhe, China.
Peishan HuangThe Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhe, China.
Huijuan LiuThe Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhe, China.

Funding

Shenzhen Clinical Research Center for Oral Diseases 20210617170745001
6 · The paper itself

Abstract

Periodontitis is a chronic inflammatory condition linked to systemic diseases, yet the neuroendocrine mechanisms underlying its pathogenesis remain unclear. This study aimed to elucidate neuroendocrine-related molecular pathways involved in periodontitis. Transcriptomic data and neuroendocrine-related genes (NRGs) were integrated to identify candidate genes from the overlap between differentially expressed genes (DEGs) and NRGs. Machine learning, ROC analysis and expression validation were used to screen key genes and construct a diagnostic nomogram. Functional enrichment, immune infiltration, drug prediction, molecular docking and single-cell analyses were performed. Key gene expression was further validated using clinical samples. Nine candidate genes were obtained from the intersection of 210 DEGs and 1441 NRGs. Five key genes-FOXN1, XBP1, HCLS1, IRF4 and RORA-were identified and used to develop an effective diagnostic model. These genes showed distinct tissue and cellular distributions and were enriched in pathways such as Ribosome and Protein processing in the ER. Sixteen immune cell types differed between groups, and 24 potential drugs, including melatonin, were predicted. Single-cell analysis highlighted T cells and Endothelial cells as central cell populations. PCR results aligned with bioinformatic findings. Five neuroendocrine-related genes were identified as potential diagnostic biomarkers and therapeutic targets, offering new insights into the neuroendocrine mechanisms of periodontitis.

Indexed as

PeriodontitisSingle-Cell AnalysisTranscriptomeBiomarkersComputational BiologyGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHumansSingle-Cell Gene Expression AnalysisBiomarkersimmune infiltrationkey geneneuroendocrineperiodontitis

Identifiers

PMID42634206
PMCPMC13500899

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