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]
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
光坠星海完成签到 ,获得积分10
刚刚
无限尔云发布了新的文献求助10
刚刚
仲侣弥月发布了新的文献求助10
1秒前
1秒前
温曈发布了新的文献求助10
1秒前
火星上笑蓝完成签到,获得积分10
2秒前
2秒前
丘比特应助漂亮的孤风采纳,获得10
2秒前
cc完成签到 ,获得积分10
3秒前
3秒前
3秒前
张小哥12发布了新的文献求助10
3秒前
3秒前
天天快乐应助aaaaa12346采纳,获得10
3秒前
4秒前
小马甲应助Yu采纳,获得10
4秒前
Maruko_0_发布了新的文献求助10
4秒前
图图应助安详的从波采纳,获得10
4秒前
醉意拥桃枝完成签到 ,获得积分10
4秒前
Frank发布了新的文献求助30
4秒前
4秒前
4秒前
5秒前
CipherSage应助瞬间de回眸采纳,获得10
5秒前
完美世界应助jj采纳,获得10
5秒前
潇洒的凌雪完成签到,获得积分20
5秒前
5秒前
彭于彦祖应助Yyyyyy11采纳,获得30
6秒前
6秒前
7秒前
AiQi发布了新的文献求助10
7秒前
7秒前
SireTD完成签到,获得积分10
7秒前
7秒前
学霸扬完成签到,获得积分10
8秒前
nkcyn发布了新的文献求助30
8秒前
8秒前
丘比特应助森距离采纳,获得10
8秒前
8秒前
9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
List of 1,091 Public Pension Profiles by Region 1561
Binary Alloy Phase Diagrams, 2nd Edition 1200
Holistic Discourse Analysis 600
Atlas of Liver Pathology: A Pattern-Based Approach 500
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
Using Genomics to Understand How Invaders May Adapt: A Marine Perspective 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5505994
求助须知:如何正确求助?哪些是违规求助? 4601482
关于积分的说明 14476730
捐赠科研通 4535445
什么是DOI,文献DOI怎么找? 2485408
邀请新用户注册赠送积分活动 1468357
关于科研通互助平台的介绍 1440869