ArticleScientific reports2025
Identification and validation of endoplasmic reticulum autophagy-related potential biomarkers in periodontitis.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Identification and Experimental Validation of Key Genes Related to Neuroendocrine in Periodontitis Based on Single-Cell and Bulk Transcriptome Data.Journal of cellular and molecular medicine · 2026Article
- MZB1 Drives Periodontitis via ER Stress-Mediated Inflammation and Osteogenic Differentiation.International dental journal · 2026Article
- Biological Performance and Molecular Mechanisms of Mesyl MicroRNA-Targeted Oligonucleotides in Colorectal Cancer Cells.International journal of molecular sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Periodontitis is a chronic inflammatory disease that mainly occurs in the dental supporting tissues. Endoplasmic reticulum autophagy (ER-phagy) is a new type of selective autophagy. The main function of ER-phagy is to degrade excess ER membranes or toxic protein aggregates, control the volume of ER, and maintain cell homeostasis. This study utilized bioinformatics to identify and validate potential ER-phagy-related biomarkers for periodontitis. The relationship between immune cell infiltration and periodontitis as well as potential biomarkers was analyzed, to identify new targets for the diagnosis and treatment of periodontitis. Data from GeneCards and Gene Expression Omnibus (GEO) databases were utilized to identify differentially-expressed ER-phagy-related genes, and to conduct functional enrichment and pathway analyses. Random forest, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature removal (SVM-RFE) algorithms were used to identify hub genes. Receiver operating characteristic (ROC) curves and areas under the curve (AUCs) were calculated to assess diagnostic performance and identify potential biomarkers for periodontitis. The CIBERSORT deconvolution algorithm was used to study the link between potential biomarkers and distinct types of immune cells. In addition, clinical samples were examined using Real-time quantitative polymerase chain reaction (RT-qPCR) to verify the expression of genes related to ER-phagy in periodontitis and identify a signature which may better predict this disease. Bioinformatics analysis identified 88 differentially-expressed ER-phagy-related genes (DE-ERGs). 6 hub genes were found using LASSO, SVM-RFE and Random forest, namely ATP1A1, CD69, DNAJB11, GANAB, IL7, and PSME2. ATP1A1 and GANAB exhibited robust diagnostic efficacy in both the training set and validation set. The results of immune cell infiltration analysis revealed a significantly greater abundance of plasma cells in periodontitis tissue samples compared to healthy periodontal tissue samples (P < 0.05). Correlation analysis between potential biomarkers and immune cells demonstrated that the expression levels of ATP1A1 and GANAB were correlated with plasma cells and resting dendritic cells. Clinical samples examined by RT-qPCR verified that these ER-phagy-related signature genes in periodontitis may better predict the development of periodontitis.ER-phagy is closely related to the pathological process of periodontitis. The infiltration of immune cells differs between tissues affected by periodontitis and healthy periodontal tissues, and a variety of immune cell subsets are significantly correlated with ATP1A1 and GANAB, thus ATP1A1 and GANAB have good diagnostic efficiency for periodontitis and can be used as potential biomarkers for early diagnosis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.