Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies

Background and purpose: Diagnosis of dementia with Lewy bodies (DLB) is highly challenging, primarily due to a lack of valid and reliable diagnostic tools. To date, there is no report of qualitative signature for the diagnosis of DLB. We aimed to develop a blood-based qualitative signature for diffe...

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Autores principales:	Shu Zhou, Qingchun Meng, Lingyu Li, Luo Hai, Zexuan Wang, Zhicheng Li, Yingli Sun
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	dementia with Lewy bodies microRNA relative expression ordering signature feature selection Genetics QH426-470
Acceso en línea:	https://doaj.org/article/3a950632ed6842b78ae0b050208e9320
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spelling	oai:doaj.org-article:3a950632ed6842b78ae0b050208e93202021-11-19T05:52:57ZIdentification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies1664-802110.3389/fgene.2021.758103https://doaj.org/article/3a950632ed6842b78ae0b050208e93202021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fgene.2021.758103/fullhttps://doaj.org/toc/1664-8021Background and purpose: Diagnosis of dementia with Lewy bodies (DLB) is highly challenging, primarily due to a lack of valid and reliable diagnostic tools. To date, there is no report of qualitative signature for the diagnosis of DLB. We aimed to develop a blood-based qualitative signature for differentiating DLB patients from healthy controls.Methods: The GSE120584 dataset was downloaded from the public database Gene Expression Omnibus (GEO). We combined multiple methods to select features based on the within-sample relative expression orderings (REOs) of microRNA (miRNA) pairs. Specifically, we first quickly selected miRNA pairs related to DLB by identifying reversal stable miRNA pairs. Then, an optimal miRNA pair subset was extracted by random forest (RF) and support vector machine-recursive feature elimination (SVM-RFE) methods. Furthermore, we applied logistic regression (LR) and SVM to build several prediction models. The model performance was assessed using the receiver operating characteristic curve (ROC) analysis. Lastly, we conducted bioinformatics analyses to explore the molecular mechanisms of the discovered miRNAs.Results: A qualitative signature consisted of 17 miRNA pairs and two clinical factors was identified for discriminating DLB patients from healthy controls. The signature is robust against experimental batch effects and applicable at the individual levels. The accuracies of the-signature-based models on the test set are 82.61 and 79.35%, respectively, indicating that the signature has acceptable discrimination performance. Moreover, bioinformatics analyses revealed that predicted target genes were enriched in 11 Go terms and 2 KEGG pathways. Moreover, five potential hub genes were found for DLB, including SRF, MAPK1, YWHAE, RPS6KA3, and KDM7A.Conclusion: This study provided a blood-based qualitative signature with the potential to be used as an effective tool to improve the accuracy of DLB diagnosis.Shu ZhouShu ZhouQingchun MengLingyu LiLuo HaiZexuan WangZhicheng LiYingli SunFrontiers Media S.A.articledementia with Lewy bodiesmicroRNArelative expression orderingsignaturefeature selectionGeneticsQH426-470ENFrontiers in Genetics, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	dementia with Lewy bodies microRNA relative expression ordering signature feature selection Genetics QH426-470
spellingShingle	dementia with Lewy bodies microRNA relative expression ordering signature feature selection Genetics QH426-470 Shu Zhou Shu Zhou Qingchun Meng Lingyu Li Luo Hai Zexuan Wang Zhicheng Li Yingli Sun Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies
description	Background and purpose: Diagnosis of dementia with Lewy bodies (DLB) is highly challenging, primarily due to a lack of valid and reliable diagnostic tools. To date, there is no report of qualitative signature for the diagnosis of DLB. We aimed to develop a blood-based qualitative signature for differentiating DLB patients from healthy controls.Methods: The GSE120584 dataset was downloaded from the public database Gene Expression Omnibus (GEO). We combined multiple methods to select features based on the within-sample relative expression orderings (REOs) of microRNA (miRNA) pairs. Specifically, we first quickly selected miRNA pairs related to DLB by identifying reversal stable miRNA pairs. Then, an optimal miRNA pair subset was extracted by random forest (RF) and support vector machine-recursive feature elimination (SVM-RFE) methods. Furthermore, we applied logistic regression (LR) and SVM to build several prediction models. The model performance was assessed using the receiver operating characteristic curve (ROC) analysis. Lastly, we conducted bioinformatics analyses to explore the molecular mechanisms of the discovered miRNAs.Results: A qualitative signature consisted of 17 miRNA pairs and two clinical factors was identified for discriminating DLB patients from healthy controls. The signature is robust against experimental batch effects and applicable at the individual levels. The accuracies of the-signature-based models on the test set are 82.61 and 79.35%, respectively, indicating that the signature has acceptable discrimination performance. Moreover, bioinformatics analyses revealed that predicted target genes were enriched in 11 Go terms and 2 KEGG pathways. Moreover, five potential hub genes were found for DLB, including SRF, MAPK1, YWHAE, RPS6KA3, and KDM7A.Conclusion: This study provided a blood-based qualitative signature with the potential to be used as an effective tool to improve the accuracy of DLB diagnosis.
format	article
author	Shu Zhou Shu Zhou Qingchun Meng Lingyu Li Luo Hai Zexuan Wang Zhicheng Li Yingli Sun
author_facet	Shu Zhou Shu Zhou Qingchun Meng Lingyu Li Luo Hai Zexuan Wang Zhicheng Li Yingli Sun
author_sort	Shu Zhou
title	Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies
title_short	Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies
title_full	Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies
title_fullStr	Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies
title_full_unstemmed	Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies
title_sort	identification of a qualitative signature for the diagnosis of dementia with lewy bodies
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/3a950632ed6842b78ae0b050208e9320
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Identification of a Qualitative Signature for the Diagnosis of Dementia With Lewy Bodies

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