The Association Between Insulin Use and Asthma: An Epidemiological Observational Analysis and Mendelian Randomization Study

孟德尔随机化 哮喘 医学 队列 胰岛素 糖尿病 流行病学 队列研究 全国健康与营养检查调查 人口 内科学 环境卫生 内分泌学 生物 生物化学 遗传变异 基因 基因型
作者
Zikai Lin,Junfeng Huang,Shuojia Xie,Ziwen Zheng,Kailun Tang,Shiyue Li,Ruchong Chen
出处
期刊:Lung [Springer Science+Business Media]
卷期号:201 (2): 189-199 被引量:12
标识
DOI:10.1007/s00408-023-00611-z
摘要

Asthma is a common respiratory disease caused by genetic and environmental factors, but the contribution of insulin use to the risk of asthma remains unclear. This study aimed to investigate the association between insulin use and asthma in a large population-based cohort, and further explore their causal relationship by Mendelian randomization (MR) analysis. An epidemiological study including 85,887 participants from the National Health and Nutrition Examination Survey (NHANES) 2001–2018 was performed to evaluate the association between insulin use and asthma. Based on the inverse-variance weighted approach, MR analysis were conducted to estimate the causal effect of insulin use on asthma from the UKB and FinnGen datasets, respectively. In the NHANES cohort, we found that insulin use was associated with an increased risk of asthma [odd ratio (OR) 1.38; 95% CI 1.16–1.64; p < 0.001]. For the MR analysis, we found a causal relationship between insulin use and a higher risk of asthma in both Finn (OR 1.10; p < 0.001) and UK Biobank cohorts (OR 1.18; p < 0.001). Meanwhile, there was no causal association between diabetes and asthma. After multivariable adjustment for diabetes in UKB cohort, the insulin use remained significantly associated with an increased risk of asthma (OR 1.17, p < 0.001). An association between insulin use and an increased risk of asthma was found via the real-world data from the NHANES. In addition, the current study identified a causal effect and provided a genetic evidence of insulin use and asthma. More studies are needed to elucidate the mechanisms underlying the association between insulin use and asthma.
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
乐乐应助柚子采纳,获得10
1秒前
nana湘发布了新的文献求助10
2秒前
明亮衣发布了新的文献求助10
2秒前
2秒前
含蓄的小熊猫完成签到 ,获得积分10
6秒前
丁1完成签到 ,获得积分10
7秒前
7秒前
8秒前
youth应助请叫我女侠采纳,获得50
10秒前
11秒前
maf2007完成签到,获得积分10
12秒前
15秒前
田様应助明亮剑采纳,获得10
15秒前
棱镜发布了新的文献求助10
16秒前
自由曼冬完成签到 ,获得积分10
16秒前
17秒前
19秒前
19秒前
20秒前
21秒前
jielo发布了新的文献求助10
21秒前
端庄夏青完成签到,获得积分10
21秒前
22秒前
怡然新之完成签到 ,获得积分10
24秒前
24秒前
24秒前
学术小垃圾发布了新的文献求助100
24秒前
123发布了新的文献求助10
25秒前
彭于晏应助YOKO采纳,获得10
26秒前
科研通AI6.4应助火山书痴采纳,获得30
27秒前
Whisper发布了新的文献求助10
27秒前
lalalla发布了新的文献求助10
27秒前
28秒前
28秒前
清嘉发布了新的文献求助10
29秒前
30秒前
呼呼完成签到,获得积分10
31秒前
QQQ123完成签到,获得积分10
31秒前
刘刘球完成签到,获得积分10
33秒前
34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
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
适配Micro-LED色转换的高兼容性量子点负性光刻胶制备与工艺研究 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7316632
求助须知:如何正确求助?哪些是违规求助? 8932628
关于积分的说明 18936046
捐赠科研通 6976622
什么是DOI,文献DOI怎么找? 3214079
关于科研通互助平台的介绍 2382025
邀请新用户注册赠送积分活动 2192830