Evidence map›Paper›PMID 39758938›Full record

ArticleJournal of inflammation research2024

Novel Insights from Comprehensive Bioinformatics Analysis Utilizing Large-Scale Human Transcriptomes and Experimental Validation: The Role of Autophagy in Periodontitis.

Fen Liu, Zhipeng Zhu, Huaxi Zou, Zhen Huang, Shengkai Xiao, Zhihua Li

Abstract read
In one paragraph

Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. IL-6Journal of translational medicine · 2025
    Article
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.

Fen LiuSchool of Stomatology, Jiangxi Medical College, Nanchang University, Jiangxi Provincial Key Laboratory of Oral Diseases, Jiangxi Provincial Clinical Research Center for Oral Disease, Nanchang, Jiangxi, People's Republic of China.ORCID 0009-0005-2469-7513
Zhipeng ZhuSchool of Stomatology, Jiangxi Medical College, Nanchang University, Jiangxi Provincial Key Laboratory of Oral Diseases, Jiangxi Provincial Clinical Research Center for Oral Disease, Nanchang, Jiangxi, People's Republic of China.
Huaxi ZouDepartment of Cardiovascular Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People's Republic of China.
Zhen HuangSchool of Stomatology, Jiangxi Medical College, Nanchang University, Jiangxi Provincial Key Laboratory of Oral Diseases, Jiangxi Provincial Clinical Research Center for Oral Disease, Nanchang, Jiangxi, People's Republic of China.
Shengkai XiaoSchool of Stomatology, Jiangxi Medical College, Nanchang University, Jiangxi Provincial Key Laboratory of Oral Diseases, Jiangxi Provincial Clinical Research Center for Oral Disease, Nanchang, Jiangxi, People's Republic of China.
Zhihua LiSchool of Stomatology, Jiangxi Medical College, Nanchang University, Jiangxi Provincial Key Laboratory of Oral Diseases, Jiangxi Provincial Clinical Research Center for Oral Disease, Nanchang, Jiangxi, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Autophagy plays a crucial role in the pathophysiology of periodontitis, yet its precise involvement in the disease process remains elusive. The aim of the present study was thus to investigate the involvement of autophagy in the pathology of periodontitis. This investigation involved transcriptomic analysis of a broad range of human samples and complemented by in vitro experimentation. Materials and Methods: We analyzed the transcriptomes of human gingival tissues from individuals with periodontitis and health controls to identify the differential expression of autophagy-related genes (DEARGs) and to investigate their potential interactions and functional pathways. Additionally, protein-protein interaction (PPI) networks were constructed to identify key functional modules and hub genes. Experimental validation of autophagy regulation in periodontitis and identification of key autophagy-regulating genes was accomplished through in vitro cellular experiments. Subsequently, a comprehensive analysis of immune cell infiltrate utilizing the CIBERSORT algorithm was performed. Finally, leveraging the DSigDB database, potential candidate drugs for periodontitis treatment targeting autophagy were predicted. Results: A total of 79 genes have been identified as DEARGs in periodontitis. An intricate interplay among the DEARGs and their impact on the regulatory mechanisms of autophagy within the context of periodontitis was observed. Subsequently, 10 hub genes were discerned through the establishment of a PPI network. Furthermore, dysregulated autophagic activity in periodontitis was validated, and 9 key genes (APP, KDR, IL1B, CXCL12, CXCR4, IL6, FOS, LCK, and SHC1) were identified through in vitro experiments. Our analysis unveiled an association between these genes and altered immune cell infiltration in periodontitis. Additionally, we predicted potential therapeutic agents such as curcumin, 27-hydroxycholesterol, and Trolox, showing promise in the treatment of periodontitis by modulating the autophagic process. Conclusion: This study identified nine key genes for autophagy regulation and potential therapeutic agents in periodontitis. These findings not only enhance our comprehension of the pathological mechanisms of periodontitis but also provide substantial evidence for the advancement of novel therapeutic strategies.

Indexed as

autophagydatabasediagnosiskey genesperiodontitistranscriptome

Identifiers

PMID39758938
PMCPMC11697667

What Socratic holds

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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 Socratic graph.