A large study of metabolomics reveals common and distinct metabolic biomarkers for type 2 diabetes, coronary heart disease, and stroke

危险系数 医学 冲程(发动机) 内科学 2型糖尿病 糖尿病 比例危险模型 代谢组学 代谢物 脂蛋白 内分泌学 心脏病学 生物信息学 胆固醇 置信区间 生物 机械工程 工程类
作者
Yanqiang Lu,Guochen Li,Vivian Viallon,Pietro Ferrari,Heinz Freisling,Yanan Qiao,Liping Shao,Luying Wu,Yi Ding,Chaofu Ke
出处
期刊:American Journal of Epidemiology [Oxford University Press]
被引量:1
标识
DOI:10.1093/aje/kwae167
摘要

Abstract We aimed at examining the shared and unique associations of metabolites with multiple cardiometabolic diseases, including type 2 diabetes (T2D), coronary heart disease (CHD), and stroke. In this study, a total of 168 plasma metabolites were measured by high-throughput nuclear magnetic resonance spectroscopy among 98 162 participants free of T2D, CHD, and stroke at baseline. Cox proportional hazard models estimated hazard ratios for a 1-SD increase in metabolite concentration levels, and false discovery rate (at 10%) was used to correct for multiple comparisons. Over 12.1 years of follow-up on average, 3463 T2D, 6186 CHD, and 1892 stroke events were recorded. Most lipoprotein metabolites were associated with risks of T2D and CHD but not with the risk of stroke, with stronger associations for T2D than for CHD. Phospholipids within intermediate-density lipoprotein or large low-density lipoprotein particles showed positive associations with CHD and inverse associations with T2D. Metabolites indicating very small very low-density lipoprotein, histidine, creatinine, albumin, and glycoprotein acetyls were associated with risks of all 3 conditions. This large-scale metabolomics study revealed common and distinct metabolic biomarkers for T2D, CHD, and stroke, providing instrumental information to possibly implement precision medicine for preventing and treating these conditions.
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
思洁WAIT发布了新的文献求助10
刚刚
1秒前
echasl73完成签到,获得积分10
1秒前
Natalie发布了新的文献求助10
1秒前
leotao完成签到,获得积分10
1秒前
CodeCraft应助十三采纳,获得10
1秒前
Silence发布了新的文献求助10
2秒前
烂漫皮皮虾完成签到,获得积分10
2秒前
4秒前
joker发布了新的文献求助10
4秒前
稳重诗珊发布了新的文献求助10
4秒前
Owen应助TTTTTT采纳,获得30
4秒前
结实向真发布了新的文献求助10
5秒前
wangyuhao发布了新的文献求助10
5秒前
5秒前
5秒前
江凡儿发布了新的文献求助10
6秒前
王秋婷发布了新的文献求助10
6秒前
221完成签到,获得积分20
6秒前
wjx发布了新的文献求助10
6秒前
7秒前
Kw发布了新的文献求助80
7秒前
大模型应助randomname采纳,获得10
8秒前
NexusExplorer应助拂晓采纳,获得10
8秒前
9秒前
茶色玻璃发布了新的文献求助10
10秒前
科研通AI5应助L龙采纳,获得30
10秒前
10秒前
10秒前
11秒前
11秒前
zyx发布了新的文献求助30
11秒前
11秒前
12秒前
12秒前
不知道发布了新的文献求助10
13秒前
欣喜的香彤完成签到,获得积分10
13秒前
LIDOC完成签到,获得积分20
13秒前
13秒前
高分求助中
Continuum thermodynamics and material modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 2000
Applications of Emerging Nanomaterials and Nanotechnology 1111
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Les Mantodea de Guyane Insecta, Polyneoptera 1000
Theory of Block Polymer Self-Assembly 750
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3488497
求助须知:如何正确求助?哪些是违规求助? 3076158
关于积分的说明 9143934
捐赠科研通 2768523
什么是DOI,文献DOI怎么找? 1519179
邀请新用户注册赠送积分活动 703643
科研通“疑难数据库(出版商)”最低求助积分说明 701932