Identification of key gene associated with periodontitis and prediction of therapeutic drugs using machine learning in combination with LIME model explainer

Qilong Huang; Zhaohua Wang; Jiayu Han

doi:10.23977/medsc.2023.040518

Identification of key gene associated with periodontitis and prediction of therapeutic drugs using machine learning in combination with LIME model explainer

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DOI: 10.23977/medsc.2023.040518 | Downloads: 13 | Views: 430

Author(s)

Qilong Huang ¹, Zhaohua Wang ², Jiayu Han ³

Affiliation(s)

¹ Department of Biomedical Engineering, China Medical University, Shenyang, 110122, China
² Department of Otorhinolaryngology & Head and Neck Surgery Dalian Friendship Hospital of Dalian Medical University, Dalian, Liaoning, 116000, China
³ Yantai Research Institute, Harbin Engineering University, Yantai, Shandong, 264000, China

Corresponding Author

Qilong Huang

ABSTRACT

Periodontitis is an immune-inflammatory disease characterized by irreversible periodontal attachment loss and bone destruction. In this study, we downloaded two microarray datasets, GSE10334 and GSE16134, from the Gene Expression Omnibus (GEO) database to identify molecular biomarkers and potential mechanisms associated with periodontitis. We performed differential gene expression analysis using the Limma package and co-expression network analysis. Additionally, we used machine learning with L1 regularization and LIME model explainer to identify the most relevant gene, ISL1. Finally, we validated molecular docking experiments using AutoDockTool and PyMOL. GO and KEGG enrichment analyses showed that periodontitis may affect various biological processes, including transcription, gene expression, apoptosis, and proliferation regulation. We found that periodontitis may influence cytokine-cytokine receptor interaction, lipid and atherosclerosis, and IL-17 signaling pathway. Our molecular docking results demonstrated that all of the major targets selected could be stably bound by the active components we chose. In summary, this study provides the hub gene, ISL1. We also identified 9 active components that may play a role in regulating ISL1 in periodontitis.

KEYWORDS

Periodontitis, LIME, hub gene, molecular docking

CITE THIS PAPER

Qilong Huang, Zhaohua Wang, Jiayu Han, Identification of key gene associated with periodontitis and prediction of therapeutic drugs using machine learning in combination with LIME model explainer. MEDS Clinical Medicine (2023) Vol. 4: 133-142. DOI: http://dx.doi.org/10.23977/medsc.2023.040518.

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Identification of key gene associated with periodontitis and prediction of therapeutic drugs using machine learning in combination with LIME model explainer

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Affiliation(s)

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ABSTRACT

KEYWORDS

CITE THIS PAPER

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