Metabolomic analysis reveals the metabolic disturbance in aortic dissection: Subtype difference and accurate diagnosis

代谢组学 医学 冠状动脉疾病 内科学 发病机制 主动脉夹层 疾病 代谢控制分析 病例对照研究 生物信息学 生物 主动脉 胰岛素
作者
Jinghui Zhang,Lu Han,Hongchuan Liu,Hongjia Zhang,Zhuoling An
出处
期刊:Nutrition Metabolism and Cardiovascular Diseases [Elsevier BV]
卷期号:33 (8): 1556-1564 被引量:3
标识
DOI:10.1016/j.numecd.2023.05.006
摘要

Aortic dissection (AD), a severe clinical emergency with high mortality, is easily misdiagnosed as are other cardiovascular diseases. This study aimed at discovering plasma metabolic markers with the potential to diagnose AD and clarifying the metabolic differences between two subtypes of AD.To facilitate the diagnosis of AD, we investigated the plasma metabolic profile by metabolomic approach. A total 482 human subjects were enrolled in the study: 80 patients with AD (50 with Stanford type A and 30 with Stanford type B), 198 coronary artery disease (CAD) patients, and 204 healthy individuals. Plasma samples were submitted to targeted metabolomic analysis. The partial least-squares discriminant analysis models were constructed to illustrate clear discrimination of AD patients with CAD patients and healthy control. Subsequently, the metabolites that were clinically relevant to the disturbances in AD were identified. Twenty metabolites induced the separation of AD patients and healthy control, 9 of which caused the separation of CAD patients and healthy control. There are 11 metabolites specifically down-regulated in AD group. Subgroup analysis showed that the levels of glycerol and uridine were dramatically lower in the plasma of patients with Stanford type A AD than those in the healthy control or Stanford type B AD groups.This study characterized metabolomic profiles specifically associated with the pathogenesis and development of AD. The findings of this research may potentially lead to earlier diagnosis and treatment of AD.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
Korai完成签到 ,获得积分10
1秒前
斐乐完成签到,获得积分10
1秒前
暖暖的禾日完成签到,获得积分10
3秒前
花花完成签到,获得积分10
3秒前
3秒前
大大怪完成签到,获得积分10
3秒前
可问春风完成签到,获得积分0
3秒前
wweq完成签到,获得积分10
5秒前
六芒星bling完成签到,获得积分10
6秒前
要减肥的湘云完成签到,获得积分10
6秒前
123完成签到,获得积分10
6秒前
精明的彩虹完成签到,获得积分10
6秒前
唠叨的逍遥完成签到,获得积分10
7秒前
大大怪发布了新的文献求助10
7秒前
Jane完成签到 ,获得积分10
9秒前
乐乐应助雪山冰川采纳,获得10
10秒前
朱哥永正完成签到,获得积分10
10秒前
10秒前
拉稀摆带完成签到 ,获得积分10
11秒前
Eurus完成签到 ,获得积分10
12秒前
12秒前
淡定的幼晴完成签到,获得积分10
13秒前
浩然完成签到 ,获得积分10
14秒前
xwj完成签到,获得积分10
14秒前
身体健康完成签到 ,获得积分10
14秒前
none完成签到,获得积分10
14秒前
珂珂完成签到 ,获得积分10
15秒前
landolu完成签到,获得积分10
16秒前
一篮子青柠檬完成签到,获得积分10
16秒前
17秒前
Muhebbet完成签到,获得积分10
17秒前
慈祥的元珊完成签到,获得积分10
18秒前
Yewen完成签到,获得积分10
18秒前
star完成签到,获得积分10
19秒前
21秒前
tfsn20完成签到,获得积分10
21秒前
zhu2026完成签到,获得积分10
22秒前
chen完成签到,获得积分10
22秒前
雪山冰川发布了新的文献求助10
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Rosenblum, Global Change Biology 800
自動車の空力技術 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7778504
求助须知:如何正确求助?哪些是违规求助? 9318853
关于积分的说明 20366411
捐赠科研通 7365581
什么是DOI,文献DOI怎么找? 3319214
关于科研通互助平台的介绍 2467181
邀请新用户注册赠送积分活动 2334693