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 遗传变异 生物化学 基因型 基因
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:10
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
ccm应助baobaoxiong采纳,获得10
2秒前
一笑而过完成签到 ,获得积分10
3秒前
xiaobai123456完成签到,获得积分10
4秒前
火星上白羊完成签到,获得积分10
4秒前
UHPC发布了新的文献求助10
4秒前
深情安青应助刘铭晨采纳,获得10
6秒前
张平一完成签到 ,获得积分10
6秒前
JamesPei应助yuquan采纳,获得10
6秒前
小曹医生完成签到,获得积分10
8秒前
downdown完成签到,获得积分10
10秒前
wentao完成签到,获得积分10
13秒前
chen完成签到,获得积分10
14秒前
宇宙尽头完成签到,获得积分10
14秒前
欣慰的书本完成签到 ,获得积分10
17秒前
郑皓文完成签到,获得积分10
17秒前
17秒前
充电宝应助伶俐的千凡采纳,获得10
17秒前
ts完成签到,获得积分10
18秒前
yuquan完成签到,获得积分10
18秒前
frankyeah完成签到,获得积分10
18秒前
18秒前
干饭选手又困了完成签到,获得积分10
18秒前
番茄鱼完成签到 ,获得积分10
19秒前
zehua309完成签到,获得积分10
19秒前
chenzao完成签到,获得积分10
19秒前
REYU完成签到,获得积分10
20秒前
俭朴的世界完成签到 ,获得积分0
22秒前
Jason完成签到,获得积分10
22秒前
Jane完成签到,获得积分10
22秒前
跳跳完成签到,获得积分10
23秒前
SSD完成签到 ,获得积分10
23秒前
caoyulongchn完成签到,获得积分10
24秒前
BAEK完成签到,获得积分10
28秒前
传统的衬衫完成签到 ,获得积分10
28秒前
Fang Xianxin完成签到,获得积分10
29秒前
addi111完成签到,获得积分0
30秒前
风趣霆完成签到,获得积分10
30秒前
学不懂的云完成签到,获得积分10
31秒前
辛勤谷雪完成签到,获得积分0
31秒前
Erinzz发布了新的文献求助10
32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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
CLSI M100 Performance Standards for Antimicrobial Susceptibility Testing 36th edition 400
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6362286
求助须知:如何正确求助?哪些是违规求助? 8176007
关于积分的说明 17224813
捐赠科研通 5416998
什么是DOI,文献DOI怎么找? 2866674
邀请新用户注册赠送积分活动 1843775
关于科研通互助平台的介绍 1691614