检索结果-南通市图书馆

Machine Learning to Detect Alzheimer’s Disease from Circulating Non-coding RNAs

Genomics, Proteomics & Bioinformatics 2019年第4期17卷 430-440页

作者： Nicole Ludwig Tobias Fehlmann Fabian Kern Manfred Gogol Walter Maetzler Stephanie Deutscher simone gurlit Claudia Schulte Anna-Katharina von Thaler Christian Deuschle Florian Metzger Daniela Berg Ulrike Suenkel Verena Keller Christina Backes Hans-Peter Lenhof Eckart Meese Andreas Keller Department of Human Genetics Saarland University66421 Homburg/SaarGermany Chair for Clinical Bioinformatics Saarland University66123 Saarbru¨ckenGermany Institut fur Gerontologie Universitat Heidelberg69047 HeidelbergGermany Department of Neurology Christian-Albrechts-University of Kiel24118 KielGermany Center for Neurology and Hertie Institute for Clinical Brain Research Department of NeurodegenerationUniversity of Tuebingen72074 TuebingenGermany German Center for Neurodegenerative Diseases(DZNE) 72076 TuebingenGermany Department of Anesthesiology and Intensive Care St.Franziskus Hospital Muenster48145 MuensterGermany Department of Psychiatry and Psychotherapy University Hospital Tuebingen72016 TuebingenGermany Department of Medicine II Saarland University Medical Center66421 Homburg/SaarGermany Center for Bioinformatics Saarland Informatics Campus66123 SaarbruckenGermany

Blood-borne small non-coding(snc RNAs)are among the prominent candidates for blood-based diagnostic ***,high-throughput approaches are applied to discover biomarker *** have to be validated in larger cohorts and evaluated by adequate statistical learning ***,we published high-throughput sequencing based microRNA(miRNA)signatures in Alzheimer’s disease(AD)patients in the United States(US)and ***,we determined abundance levels of 21 known circulating miRNAs in 465 individuals encompassing AD patients and controls by *** computed models to assess the relation between miRNA expression and phenotypes,gender,age,or disease severity(Mini-Mental State Examination;MMSE).Of the 21 miRNAs,expression levels of 20 miRNAs were consistently de-regulated in the US and German cohorts.18 miRNAs were significantly correlated with neurodegeneration(Benjamini-Hochberg adjusted P<0.05)with highest significance for miR-532-5 p(BenjaminiHochberg adjusted P=4.8×10^-30).Machine learning models reached an area under the curve(AUC)value of 87.6%in differentiating AD patients from ***,ten miRNAs were significantly correlated with MMSE,in particular miR-26a/26b-5p(adjusted P=0.0002).Interestingly,the miRNAs with lower abundance in AD were enriched in monocytes and T-helper cells,while those up-regulated in AD were enriched in serum,exosomes,cytotoxic t-cells,and *** study represents the next important step in translational research for a miRNA-based AD test.

关键词： miRNAs Neurodegeneration Alzheimer’s disease Biomarker Non-coding RNAs Gene regulation

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：