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Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus

OBJECTIVE: To explore metabolic biomarkers related to erosive and reticulated oral lichen planus (OLP) by non-targeted metabolomics methods and correlate metabolites with gene expression, and to investigate the pathological network pathways of OLP from the perspective of metabolism. METHODS: A total...

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Autores principales: Xin, Ming-zhe, Shi, Ying-ying, Li, Chun-shen, Zuo, Li-hua, Li, Na, Liu, Li-wei, Ma, He-xin, Du, Qiu-zheng, Xue, Peng, Sun, Zhi, Zhao, Hong-yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8560742/
https://www.ncbi.nlm.nih.gov/pubmed/34737967
http://dx.doi.org/10.3389/fonc.2021.769163
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author Xin, Ming-zhe
Shi, Ying-ying
Li, Chun-shen
Zuo, Li-hua
Li, Na
Liu, Li-wei
Ma, He-xin
Du, Qiu-zheng
Xue, Peng
Sun, Zhi
Zhao, Hong-yu
author_facet Xin, Ming-zhe
Shi, Ying-ying
Li, Chun-shen
Zuo, Li-hua
Li, Na
Liu, Li-wei
Ma, He-xin
Du, Qiu-zheng
Xue, Peng
Sun, Zhi
Zhao, Hong-yu
author_sort Xin, Ming-zhe
collection PubMed
description OBJECTIVE: To explore metabolic biomarkers related to erosive and reticulated oral lichen planus (OLP) by non-targeted metabolomics methods and correlate metabolites with gene expression, and to investigate the pathological network pathways of OLP from the perspective of metabolism. METHODS: A total of 153 individuals were enrolled in this study, including 50 patients with erosive oral lichen planus (EOLP), 51 patients with reticulated oral lichen planus (ROLP), and 52 healthy controls (HC). The ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry (UHPLC/Q-Orbitrap HRMS) was used to analyze the metabolites of 40 EOLP, 40 ROLP, and 40 HC samples, and the differential metabolic biomarkers were screened and identified. The regulatory genes were further screened through the shared metabolites between EOLP and ROLP, and cross-correlated with the OLP-related differential genes in the network database. A “gene-metabolite” network was constructed after finding the key differential genes. Finally, the diagnostic efficiency of the biomarkers was verified in the validation set and a diagnostic model was constructed. RESULT: Compared with HC group, a total of 19 and 25 differential metabolites were identified in the EOLP group and the ROLP group, respectively. A total of 14 different metabolites were identified between EOLP and ROLP. Two diagnostic models were constructed based on these differential metabolites. There are 14 differential metabolites shared by EOLP and ROLP. The transcriptomics data showed 756 differentially expressed genes, and the final crossover network showed that 19 differential genes were associated with 12 metabolites. Enrichment analysis showed that alanine, aspartate and glutamate metabolism were closely associated with the pathogenesis of OLP. CONCLUSION: The metabolic change of different types of OLP were clarified. The potential gene perturbation of OLP was provided. This study provided a strong support for further exploration of the pathogenic mechanism of OLP.
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spelling pubmed-85607422021-11-03 Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus Xin, Ming-zhe Shi, Ying-ying Li, Chun-shen Zuo, Li-hua Li, Na Liu, Li-wei Ma, He-xin Du, Qiu-zheng Xue, Peng Sun, Zhi Zhao, Hong-yu Front Oncol Oncology OBJECTIVE: To explore metabolic biomarkers related to erosive and reticulated oral lichen planus (OLP) by non-targeted metabolomics methods and correlate metabolites with gene expression, and to investigate the pathological network pathways of OLP from the perspective of metabolism. METHODS: A total of 153 individuals were enrolled in this study, including 50 patients with erosive oral lichen planus (EOLP), 51 patients with reticulated oral lichen planus (ROLP), and 52 healthy controls (HC). The ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry (UHPLC/Q-Orbitrap HRMS) was used to analyze the metabolites of 40 EOLP, 40 ROLP, and 40 HC samples, and the differential metabolic biomarkers were screened and identified. The regulatory genes were further screened through the shared metabolites between EOLP and ROLP, and cross-correlated with the OLP-related differential genes in the network database. A “gene-metabolite” network was constructed after finding the key differential genes. Finally, the diagnostic efficiency of the biomarkers was verified in the validation set and a diagnostic model was constructed. RESULT: Compared with HC group, a total of 19 and 25 differential metabolites were identified in the EOLP group and the ROLP group, respectively. A total of 14 different metabolites were identified between EOLP and ROLP. Two diagnostic models were constructed based on these differential metabolites. There are 14 differential metabolites shared by EOLP and ROLP. The transcriptomics data showed 756 differentially expressed genes, and the final crossover network showed that 19 differential genes were associated with 12 metabolites. Enrichment analysis showed that alanine, aspartate and glutamate metabolism were closely associated with the pathogenesis of OLP. CONCLUSION: The metabolic change of different types of OLP were clarified. The potential gene perturbation of OLP was provided. This study provided a strong support for further exploration of the pathogenic mechanism of OLP. Frontiers Media S.A. 2021-10-19 /pmc/articles/PMC8560742/ /pubmed/34737967 http://dx.doi.org/10.3389/fonc.2021.769163 Text en Copyright © 2021 Xin, Shi, Li, Zuo, Li, Liu, Ma, Du, Xue, Sun and Zhao https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Xin, Ming-zhe
Shi, Ying-ying
Li, Chun-shen
Zuo, Li-hua
Li, Na
Liu, Li-wei
Ma, He-xin
Du, Qiu-zheng
Xue, Peng
Sun, Zhi
Zhao, Hong-yu
Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus
title Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus
title_full Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus
title_fullStr Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus
title_full_unstemmed Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus
title_short Metabolomics and Transcriptomics Analysis on Metabolic Characteristics of Oral Lichen Planus
title_sort metabolomics and transcriptomics analysis on metabolic characteristics of oral lichen planus
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8560742/
https://www.ncbi.nlm.nih.gov/pubmed/34737967
http://dx.doi.org/10.3389/fonc.2021.769163
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