Variational graph autoencoder for reconstructed transcriptomic data associated with NLRP3 mediated pyroptosis in periodontitis

The NLRP3 inflammasome, regulated by TLR4, plays a pivotal role in periodontitis by mediating inflammatory cytokine release and bone loss induced by Porphyromonas gingivalis . Periodontal disease creates a hypoxic environment, favoring anaerobic bacteria survival and exacerbating inflammation. The N...

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Bibliographic Details
Published in:Scientific reports Vol. 15; no. 1; pp. 1962 - 11
Main Authors: Yadalam, Pradeep K., Natarajan, Prabhu Manickam, Ardila, Carlos M.
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 14.01.2025
Nature Publishing Group
Nature Portfolio
Subjects:
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692/308
Anaerobic bacteria
Apoptosis
Autoencoder
Bone loss
Cell death
Cell survival
Deep learning
Gene expression
Gene Expression Profiling
Gum disease
Humanities and Social Sciences
Humans
Hypoxia
Inflammasome
Inflammasomes
Inflammasomes - genetics
Inflammasomes - metabolism
K means clustering
multidisciplinary
NLR Family, Pyrin Domain-Containing 3 Protein - genetics
NLR Family, Pyrin Domain-Containing 3 Protein - metabolism
Periodontal diseases
Periodontitis
Periodontitis - genetics
Periodontitis - metabolism
Periodontitis - microbiology
Periodontitis - pathology
Porphyromonas gingivalis
Pyroptosis
Pyroptosis - genetics
Science
Science (multidisciplinary)
TLR4 protein
Toll-like receptors
Transcriptome
Transcriptomics
Variational autoencoders
Variational autoencoders
Inflammasome
Periodontitis
K means clustering
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:The NLRP3 inflammasome, regulated by TLR4, plays a pivotal role in periodontitis by mediating inflammatory cytokine release and bone loss induced by Porphyromonas gingivalis . Periodontal disease creates a hypoxic environment, favoring anaerobic bacteria survival and exacerbating inflammation. The NLRP3 inflammasome triggers pyroptosis, a programmed cell death that amplifies inflammation and tissue damage. This study evaluates the efficacy of Variational Graph Autoencoders (VGAEs) in reconstructing gene data related to NLRP3-mediated pyroptosis in periodontitis. The NCBI GEO dataset GSE262663, containing three samples with and without hypoxia exposure, was analyzed using unsupervised K-means clustering. This method identifies natural groupings within biological data without prior labels. VGAE, a deep learning model, captures complex graph relationships for tasks like link prediction and edge detection. The VGAE model demonstrated exceptional performance with an accuracy of 99.42% and perfect precision. While it identified 5,820 false negatives, indicating a conservative approach, it accurately predicted 4,080 out of 9,900 positive samples. The model’s latent space distribution differed significantly from the original data, suggesting a tightly clustered representation of the gene expression patterns. K-means clustering and VGAE show promise in gene expression analysis and graph structure reconstruction for periodontitis research.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-86455-4