亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Large-scale plasma proteomics for predicting future cardiovascular and all-cause mortality among individuals with cardiovascular-kidney-metabolic syndrome stage 0–3

医学 阶段(地层学) 疾病 内科学 人口 蛋白质组学 梅德林 重症监护医学 生物信息学 流行病学 死亡率 肿瘤科 入射(几何) 风险评估 血压
作者
Bingtao Weng,Jiahe Wei,Han Chen,Yuyan Zhao,Ningjian Wang,Hongliang Feng,Sizhi Ai,Xiao Tan
出处
期刊:Metabolism-clinical and Experimental [Elsevier BV]
卷期号:179: 156600-156600 被引量:3
标识
DOI:10.1016/j.metabol.2026.156600
摘要

BACKGROUND: Identifying high-risk individuals for cardiovascular and all-cause mortality among individuals with cardiovascular-kidney-metabolic (CKM) syndrome stage 0-3 can guide the implementation of targeted interventions. This study aimed to evaluate the predictive value of plasma proteins for future cardiovascular and all-cause mortality. METHODS: This study included 39,007 participants from the UK Biobank (UKB) with CKM stage 0-3 and available proteomic data. Associations between plasma proteins and future risks of cardiovascular and all-cause mortality were assessed using Cox proportional hazards models. Key proteins were identified through an ensemble machine learning approach integrating support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) algorithms. Subsequently, Cox models were applied to evaluate the incremental predictive value of these key proteins and their ability to enhance risk stratification for mortality outcomes. Furthermore, temporal trajectories of protein levels were examined in the years preceding death. RESULTS: During a median follow-up of 15.2 years, 505 participants died from cardiovascular causes and 3368 from any cause. 56 and 269 out of 2911 plasma proteins were significantly associated with cardiovascular and all-cause mortality, respectively (Bonferroni-adjusted P < 0.05). Incorporating seven and eight key proteins into conventional model significantly improved long-term predictive performance (C-statistics: 0.812 versus 0.782 for cardiovascular mortality; 0.772 versus 0.739 for all-cause mortality; both P < 0.001), and also provided incremental predictive value for 5- and 10-year mortality risks. Notably, participants died during follow-up exhibited markedly elevated certain protein levels over a decade before deaths, with progressively increasing trajectories over time. Stratification based on optimal predicted risk thresholds further revealed distinct cumulative mortality risks across groups. CONCLUSIONS: In individuals with CKM stage 0-3, plasma proteins combined with traditional risk factors may predict future cardiovascular and all-cause mortality.
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
刚刚
慈祥的映阳完成签到 ,获得积分10
5秒前
5秒前
ZZZ发布了新的文献求助10
6秒前
geqian完成签到 ,获得积分10
6秒前
沉静的迎荷完成签到 ,获得积分10
8秒前
8秒前
酷炫绮琴完成签到,获得积分10
9秒前
小栗子完成签到,获得积分10
10秒前
思柔完成签到 ,获得积分10
12秒前
菜咿咿呀呀完成签到 ,获得积分20
16秒前
Garry完成签到,获得积分10
16秒前
紧张的雅柏完成签到 ,获得积分10
16秒前
晚风完成签到,获得积分10
17秒前
21秒前
独特元蝶的应助被神勇的雅容采纳,获得10
25秒前
27秒前
光亮的成败完成签到,获得积分10
27秒前
28秒前
30秒前
失眠书双发布了新的文献求助30
33秒前
33秒前
拼搏愚志发布了新的文献求助10
37秒前
失眠书双完成签到,获得积分10
40秒前
45秒前
科研达人完成签到,获得积分20
47秒前
49秒前
sadsa发布了新的文献求助10
50秒前
清飏发布了新的文献求助10
53秒前
54秒前
MySun完成签到 ,获得积分10
57秒前
小二郎的应助被拼搏愚志采纳,获得10
58秒前
安详过客发布了新的文献求助10
59秒前
1分钟前
1分钟前
w1x2123完成签到,获得积分0
1分钟前
科研狗完成签到,获得积分10
1分钟前
李shuashua发布了新的文献求助10
1分钟前
1分钟前
xinyige发布了新的文献求助10
1分钟前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
The Dawn of Philology 520
Organizational Behavior 510
Production Logging: Theoretical and Interpretive Elements 400
A primer on partial least squares structural equation modeling (PLS-SEM) (4th ed.) 310
中国器官捐献和移植发展报告(2024) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7820088
求助须知:如何正确求助?哪些是违规求助? 9347734
关于积分的说明 20542774
捐赠科研通 7412660
什么是DOI,文献DOI怎么找? 3332549
关于科研通互助平台的介绍 2478500
邀请新用户注册赠送积分活动 2352587