Therapeutic and Prognostic Significance of Arachidonic Acid in Heart Failure.

医学 心力衰竭 危险系数 内科学 心脏病学 急性失代偿性心力衰竭 比例危险模型 队列 花生四烯酸 曲线下面积
作者
Ke Ma,Jie Yang,Yihui Shao,Ping Li,Hongchang Guo,Jianing Wu,Yi Zhu,Hui Zhang,Xu Zhang,Jie Du,Jie Lu
出处
期刊:Circulation Research [Ovid Technologies (Wolters Kluwer)]
卷期号:130 (7): 1056-1071
标识
DOI:10.1161/circresaha.121.320548
摘要

Accurate prediction of death is an unmet need in patients with acute decompensated heart failure (HF). Arachidonic acid (AA) metabolites play an important role in the multiple pathophysiological processes. We aimed to develop an AA score to accurately predict mortality in patients with acute decompensated HF and explore the causal relationship between the AA predictors and HF.The serum AA metabolites was measured in patients with acute decompensated HF (discovery cohort n=419; validation cohort n=386) by mass spectroscopy. We assessed the prognostic importance of AA metabolites for 1-year death using Cox regression and machine learning approaches. A machine learning-based AA score for predicting 1-year death was created and validated. We explored the mechanisms using transcriptome and functional experiments in a mouse model of early ischemic cardiomyopathy.Among the 27 AA metabolites, elevated 14,15-DHET/14,15-EET ratio was the strongest predictor of 1-year death (hazard ratio, 2.10, P=3.1×10-6). Machine learning-based AA score using a combination of the 14,15-DHET/14,15-EET ratio, 14,15-DHET, PGD2, and 9-HETE performed best (area under the curve [AUC]: 0.85). The machine learning-based AA score provided incremental information to predict mortality beyond BNP (B-type natriuretic peptide; ΔAUC: 0.19), clinical score (ΔAUC: 0.09), and preexisting Acute Decompensated Heart Failure National Registry, Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure, and Get With The Guidelines Heart Failure scores (ΔAUC: 0.17, 0.17, 0.15, respectively). In the validation cohort, the AA score accurately predicted mortality (AUC:0.81). False-negative and false-positive findings, as classified by the BNP threshold, were correctly reclassified by the AA score (46.2% of false-negative and 84.5% of false-positive). In a murine model, the expression and enzymatic activity of sEH (soluble epoxide hydrolase) increased after myocardial infarction. Genetic deletion of sEH improved HF and the blockade of 14,15-EET abolished this cardioprotection. We mechanistically revealed the beneficial effect of 14,15-EET by impairing the activation of monocytes/macrophages.Our studies propose that the AA score predicts death in patients with acute decompensated HF and inhibiting sEH serves as a therapeutic target for treating HF.URL: https://www.gov; Unique identifier: NCT04108182.
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
刚刚
大模型应助HD采纳,获得10
刚刚
aa完成签到,获得积分10
刚刚
kkyy完成签到,获得积分10
1秒前
1秒前
独特的夜阑完成签到 ,获得积分10
1秒前
1秒前
null完成签到,获得积分10
2秒前
科研通AI6应助呦吼。。。采纳,获得10
3秒前
3秒前
小耿发布了新的文献求助10
4秒前
5秒前
D33sama完成签到,获得积分10
5秒前
kkyy发布了新的文献求助10
5秒前
小华安完成签到,获得积分10
6秒前
ifhaceoiv发布了新的文献求助10
6秒前
柔弱的老三完成签到 ,获得积分10
7秒前
MrRaBB发布了新的文献求助10
7秒前
虾米完成签到,获得积分20
8秒前
雪白的白桃完成签到,获得积分10
8秒前
馅饼完成签到,获得积分10
8秒前
9秒前
王涛发布了新的文献求助10
9秒前
春江发布了新的文献求助10
9秒前
Owen应助悦耳蜜粉采纳,获得10
10秒前
自然的夏兰完成签到 ,获得积分10
11秒前
12秒前
量子星尘发布了新的文献求助10
12秒前
12秒前
满当当完成签到 ,获得积分10
12秒前
SciGPT应助xxx采纳,获得10
13秒前
上官若男应助南风采纳,获得10
13秒前
14秒前
多情的续完成签到,获得积分10
15秒前
自觉的绮烟完成签到,获得积分10
15秒前
阿文完成签到,获得积分10
15秒前
在逃板砖完成签到,获得积分10
16秒前
666驳回了华仔应助
16秒前
17秒前
JamesPei应助疯狂的寻绿采纳,获得10
18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
Iron toxicity and hematopoietic cell transplantation: do we understand why iron affects transplant outcome? 2000
List of 1,091 Public Pension Profiles by Region 1021
Teacher Wellbeing: Noticing, Nurturing, Sustaining, and Flourishing in Schools 800
Efficacy of sirolimus in Klippel-Trenaunay syndrome 500
上海破产法庭破产实务案例精选(2019-2024) 500
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
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 5478171
求助须知:如何正确求助?哪些是违规求助? 4579955
关于积分的说明 14371401
捐赠科研通 4508224
什么是DOI,文献DOI怎么找? 2470523
邀请新用户注册赠送积分活动 1457329
关于科研通互助平台的介绍 1431287