Lipidomic identification of urinary extracellular vesicles for non-alcoholic steatohepatitis diagnosis

doi:10.1186/s12951-022-01540-4

科研成果详情

题名	Lipidomic identification of urinary extracellular vesicles for non-alcoholic steatohepatitis diagnosis
作者	Zhu, Qingfu1; Li, Hengrui1; Ao, Zheng 6; Xu, Hao 1; luo, Jiaxin1; Kaurich, Connor 6; Yang, Rui1; Zhu, Pei-Wu7; Chen, Sui-Dan8; Wang, Xiao-Dong 5; Tang, Liang-Jie 3; Li, Gang3; Huang, Ou-Yang3; Zheng, Ming-Hua3,4,5; Li, Hui-Ping2; Liu, Fei2
发表日期	2022-07-27
发表期刊	Journal of Nanobiotechnology 影响因子和分区
语种	英语
原始文献类型	Journal article (JA)
关键词	Decision trees Diagnosis Diseases Lipids Machine learning Nucleic acids Chronic liver disease Clinical diagnosis Extracellular Lipid molecules Lipidomics Machine-learning Non-alcoholic fatty liver Non-alcoholic fatty liver disease Non-alcoholic steatohepatitis Urinary extracellular vesicle
其他关键词	LIVER ; EXOSOMES ; CANCER ; TISSUE ; NASH
摘要	Background and Aims: Non-alcoholic fatty liver disease (NAFLD) is a usual chronic liver disease and lacks non-invasive biomarkers for the clinical diagnosis and prognosis. Extracellular vesicles (EVs), a group of heterogeneous small membrane-bound vesicles, carry proteins and nucleic acids as promising biomarkers for clinical applications, but it has not been well explored on their lipid compositions related to NAFLD studies. Here, we investigate the lipid molecular function of urinary EVs and their potential as biomarkers for non-alcoholic steatohepatitis (NASH) detection. Methods: This work includes 43 patients with non-alcoholic fatty liver (NAFL) and 40 patients with NASH. The EVs of urine were isolated and purified using the EXODUS method. The EV lipidomics was performed by LC-MS/MS. We then systematically compare the EV lipidomic profiles of NAFL and NASH patients and reveal the lipid signatures of NASH with the assistance of machine learning. Results: By lipidomic profiling of urinary EVs, we identify 422 lipids mainly including sterol lipids, fatty acyl lipids, glycerides, glycerophospholipids, and sphingolipids. Via the machine learning and random forest modeling, we obtain a biomarker panel composed of 4 lipid molecules including FFA (18:0), LPC (22:6/0:0), FFA (18:1), and PI (16:0/18:1), that can distinguish NASH with an AUC of 92.3%. These lipid molecules are closely associated with the occurrence and development of NASH. Conclusion: The lack of non-invasive means for diagnosing NASH causes increasing morbidity. We investigate the NAFLD biomarkers from the insights of urinary EVs, and systematically compare the EV lipidomic profiles of NAFL and NASH, which holds the promise to expand the current knowledge of disease pathogenesis and evaluate their role as non-invasive biomarkers for NASH diagnosis and progression. © 2022, The Author(s).
资助项目	Zhejiang Provincial Natural Science Foundation [LY22H120002]; Zhejiang Provincial and Ministry of Health Research Fund for Medical Sciences [WKJ-ZJ-1910]; Wenzhou Medical University [89218012]; Wenzhou Basic Research Projects [Y2020916]
出版者	BioMed Central Ltd
出版地	LONDON
ISSN	1477-3155
EISSN	1477-3155
卷号	20 期号:1 页码:349
DOI	10.1186/s12951-022-01540-4
页数	11
WOS类目	Biotechnology & Applied Microbiology ; Nanoscience & Nanotechnology
WOS研究方向	Biotechnology & Applied Microbiology ; Science & Technology - Other Topics
WOS记录号	WOS:000831205500001
收录类别	EI ; SCIE ; PUBMED ; SCOPUS
EI入藏号	20223112450707
EI主题词	Biomarkers
EI分类号	461.2 Biological Materials and Tissue Engineering ; 461.6 Medicine and Pharmacology ; 723.4 Artificial Intelligence ; 801.2 Biochemistry ; 804.1 Organic Compounds ; 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory ; 961 Systems Science
URL	查看原文
PubMed ID	35897102
SCOPUSEID	2-s2.0-85134881933
通讯作者地址	[Li, Hui-Ping]The First Affiliated Hospital of Wenzhou Medical University,Zhejiang,Wenzhou,325035,China ; [Liu, Fei]The First Affiliated Hospital of Wenzhou Medical University,Zhejiang,Wenzhou,325035,China ; [Zheng, Ming-Hua]Department of Hepatology,NAFLD Research Center,the First Affiliated Hospital of Wenzhou Medical University,Wenzhou,China
Scopus学科分类	Bioengineering;Medicine (miscellaneous);Molecular Medicine;Biomedical Engineering;Applied Microbiology and Biotechnology;Pharmaceutical Science
TOP期刊	TOP期刊
引用统计	被引频次[WOS]：0 [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://kms.wmu.edu.cn/handle/3ETUA0LF/153528
专题	眼视光学院（生物医学工程学院）、附属眼视光医院温州医科大学附属第一医院附属第一医院_感染内科
通讯作者	Zheng, Ming-Hua; Li, Hui-Ping; Liu, Fei
作者单位	1.Eye Hospital,School of Ophthalmology & Optometry,School of Biomedical Engineering,Wenzhou Medical University,Zhejiang,Wenzhou,325035,China; 2.The First Affiliated Hospital of Wenzhou Medical University,Zhejiang,Wenzhou,325035,China; 3.Department of Hepatology,NAFLD Research Center,the First Affiliated Hospital of Wenzhou Medical University,Wenzhou,China; 4.Institute of Hepatology,Wenzhou Medical University,Wenzhou,China; 5.Key Laboratory of Diagnosis and Treatment for the Development of Chronic Liver Disease in Zhejiang Province,Wenzhou,China; 6.Department of Intelligent Systems Engineering,Indiana University,Bloomington,47405,United States; 7.Department of Laboratory Medicine,the First Affiliated Hospital of Wenzhou Medical University,Wenzhou,China; 8.Department of Pathology,the First Affiliated Hospital of Wenzhou Medical University,Wenzhou,China
第一作者单位	眼视光学院（生物医学工程学院）、附属眼视光医院
通讯作者单位	附属第一医院
第一作者的第一单位	眼视光学院（生物医学工程学院）、附属眼视光医院
推荐引用方式 GB/T 7714	Zhu, Qingfu,Li, Hengrui,Ao, Zheng,et al. Lipidomic identification of urinary extracellular vesicles for non-alcoholic steatohepatitis diagnosis[J]. Journal of Nanobiotechnology,2022,20(1):349.
APA	Zhu, Qingfu., Li, Hengrui., Ao, Zheng., Xu, Hao., luo, Jiaxin., ... & Liu, Fei. (2022). Lipidomic identification of urinary extracellular vesicles for non-alcoholic steatohepatitis diagnosis. Journal of Nanobiotechnology, 20(1), 349.
MLA	Zhu, Qingfu,et al."Lipidomic identification of urinary extracellular vesicles for non-alcoholic steatohepatitis diagnosis".Journal of Nanobiotechnology 20.1(2022):349.