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Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model
Background: Peanut allergy (PA) has become a clinical and public health problem, which is mainly regulated by genetics, immune responses, and environmental factors. Diagnosis and treatment for PA have always remained huge challenges due to its multiple triggers. Studies have shown that long non-codi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740276/ https://www.ncbi.nlm.nih.gov/pubmed/36496569 http://dx.doi.org/10.3390/foods11233760 |
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author | Liu, Manman Li, Sen Li, Boya Sun, Shanfeng Liu, Guirong Wang, Junjuan Hao, Mengzhen Che, Huilian |
author_facet | Liu, Manman Li, Sen Li, Boya Sun, Shanfeng Liu, Guirong Wang, Junjuan Hao, Mengzhen Che, Huilian |
author_sort | Liu, Manman |
collection | PubMed |
description | Background: Peanut allergy (PA) has become a clinical and public health problem, which is mainly regulated by genetics, immune responses, and environmental factors. Diagnosis and treatment for PA have always remained huge challenges due to its multiple triggers. Studies have shown that long non-coding RNAs (lncRNAs) play a critical role in the development of allergic diseases. Method and Results: In the current study, we examined the plasma lncRNA expression profiles of peanut allergy Brown Norway rats and healthy controls and 496 differently expressed lncRNAs were identified, including 411 up-regulated genes and 85 down-regulated genes. We screened 8 lncRNAs based on the candidate principle and the candidates were verified in individual samples by quantitative real-time PCR. Then, the four lncRNA-based diagnostic model was established by least absolute shrinkage and selection operator (LASSO) and logistic regression, which was proved by area under the receiver operating characteristic curve (AUC). Conclusions: In summary, we assessed the correlation between lncRNA expression levels and the diagnosis of peanut allergy, which may perform a vital role in guiding the management of peanut allergy. |
format | Online Article Text |
id | pubmed-9740276 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97402762022-12-11 Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model Liu, Manman Li, Sen Li, Boya Sun, Shanfeng Liu, Guirong Wang, Junjuan Hao, Mengzhen Che, Huilian Foods Article Background: Peanut allergy (PA) has become a clinical and public health problem, which is mainly regulated by genetics, immune responses, and environmental factors. Diagnosis and treatment for PA have always remained huge challenges due to its multiple triggers. Studies have shown that long non-coding RNAs (lncRNAs) play a critical role in the development of allergic diseases. Method and Results: In the current study, we examined the plasma lncRNA expression profiles of peanut allergy Brown Norway rats and healthy controls and 496 differently expressed lncRNAs were identified, including 411 up-regulated genes and 85 down-regulated genes. We screened 8 lncRNAs based on the candidate principle and the candidates were verified in individual samples by quantitative real-time PCR. Then, the four lncRNA-based diagnostic model was established by least absolute shrinkage and selection operator (LASSO) and logistic regression, which was proved by area under the receiver operating characteristic curve (AUC). Conclusions: In summary, we assessed the correlation between lncRNA expression levels and the diagnosis of peanut allergy, which may perform a vital role in guiding the management of peanut allergy. MDPI 2022-11-22 /pmc/articles/PMC9740276/ /pubmed/36496569 http://dx.doi.org/10.3390/foods11233760 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Manman Li, Sen Li, Boya Sun, Shanfeng Liu, Guirong Wang, Junjuan Hao, Mengzhen Che, Huilian Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model |
title | Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model |
title_full | Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model |
title_fullStr | Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model |
title_full_unstemmed | Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model |
title_short | Long Non-Coding RNAs Expressed in the Peanut Allergy for Understanding the Pathophysiology of Peanut Allergy Rat Model |
title_sort | long non-coding rnas expressed in the peanut allergy for understanding the pathophysiology of peanut allergy rat model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740276/ https://www.ncbi.nlm.nih.gov/pubmed/36496569 http://dx.doi.org/10.3390/foods11233760 |
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