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Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing

BACKGROUND: The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are different. This study aims to discover some specific and sensitive biomarkers to distinguish AE from IE at early stage to give specific treatment...

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Autores principales: Fan, Siyuan, He, Xiangyan, Zhu, Zhongyi, Chen, Lu, Zou, Yijun, Chen, Zhonglin, Yu, Jialin, Chen, Weijun, Guan, Hongzhi, Ma, Jinmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278324/
https://www.ncbi.nlm.nih.gov/pubmed/37332019
http://dx.doi.org/10.1186/s13578-023-01047-x
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author Fan, Siyuan
He, Xiangyan
Zhu, Zhongyi
Chen, Lu
Zou, Yijun
Chen, Zhonglin
Yu, Jialin
Chen, Weijun
Guan, Hongzhi
Ma, Jinmin
author_facet Fan, Siyuan
He, Xiangyan
Zhu, Zhongyi
Chen, Lu
Zou, Yijun
Chen, Zhonglin
Yu, Jialin
Chen, Weijun
Guan, Hongzhi
Ma, Jinmin
author_sort Fan, Siyuan
collection PubMed
description BACKGROUND: The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are different. This study aims to discover some specific and sensitive biomarkers to distinguish AE from IE at early stage to give specific treatments for good outcomes. RESULTS: We compared the host gene expression profiles and microbial diversities of cerebrospinal fluid (CSF) from 41 patients with IE and 18 patients with AE through meta-transcriptomic sequencing. Significant differences were found in host gene expression profiles and microbial diversities in CSF between patients with AE and patients with IE. The most significantly upregulated genes in patients with IE were enriched in pathways related with immune response such as neutrophil degranulation, antigen processing and presentation and adaptive immune system. In contrast, those upregulated genes in patients with AE were mainly involved in sensory organ development such as olfactory transduction, as well as synaptic transmission and signaling. Based on the differentially expressed genes, a classifier consisting of 5 host genes showed outstanding performance with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95. CONCLUSIONS: This study provides a promising classifier and is the first to investigate transcriptomic signatures for differentiating AE from IE by using meta-transcriptomic next-generation sequencing technology. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-023-01047-x.
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spelling pubmed-102783242023-06-20 Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing Fan, Siyuan He, Xiangyan Zhu, Zhongyi Chen, Lu Zou, Yijun Chen, Zhonglin Yu, Jialin Chen, Weijun Guan, Hongzhi Ma, Jinmin Cell Biosci Research BACKGROUND: The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are different. This study aims to discover some specific and sensitive biomarkers to distinguish AE from IE at early stage to give specific treatments for good outcomes. RESULTS: We compared the host gene expression profiles and microbial diversities of cerebrospinal fluid (CSF) from 41 patients with IE and 18 patients with AE through meta-transcriptomic sequencing. Significant differences were found in host gene expression profiles and microbial diversities in CSF between patients with AE and patients with IE. The most significantly upregulated genes in patients with IE were enriched in pathways related with immune response such as neutrophil degranulation, antigen processing and presentation and adaptive immune system. In contrast, those upregulated genes in patients with AE were mainly involved in sensory organ development such as olfactory transduction, as well as synaptic transmission and signaling. Based on the differentially expressed genes, a classifier consisting of 5 host genes showed outstanding performance with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95. CONCLUSIONS: This study provides a promising classifier and is the first to investigate transcriptomic signatures for differentiating AE from IE by using meta-transcriptomic next-generation sequencing technology. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-023-01047-x. BioMed Central 2023-06-19 /pmc/articles/PMC10278324/ /pubmed/37332019 http://dx.doi.org/10.1186/s13578-023-01047-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Fan, Siyuan
He, Xiangyan
Zhu, Zhongyi
Chen, Lu
Zou, Yijun
Chen, Zhonglin
Yu, Jialin
Chen, Weijun
Guan, Hongzhi
Ma, Jinmin
Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing
title Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing
title_full Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing
title_fullStr Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing
title_full_unstemmed Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing
title_short Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing
title_sort integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278324/
https://www.ncbi.nlm.nih.gov/pubmed/37332019
http://dx.doi.org/10.1186/s13578-023-01047-x
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