Urine metabolite analysis as a function of deoxynivalenol exposure: an NMR-based metabolomics investigation

作者
Richard P. Hopton,Elizabeth Turner,V. J. Burley,Paul C. Turner,Julie Fisher
出处
期刊:Food Additives & Contaminants: Part A [Taylor & Francis]
卷期号:27 (2): 255-261 被引量:27
标识
DOI:10.1080/19440040903314015
摘要

Deoxynivalenol (DON) is a toxic fungal metabolite that frequently contaminates cereal crops including wheat, maize and barley. Despite knowledge of frequent exposure through diet, our understanding of the potential consequences of human exposure remains limited, in part due to the lack of validated exposure biomarkers. In this study, we interrogated the urinary metabolome using nuclear magnetic resonance (NMR) spectroscopy to compare individuals with known low and high DON exposure through consumption of their normal diet. Urine samples from 22 adults from the UK (seven males, 15 females; age range = 21-59 years) had previously determined urinary DON levels using an established liquid chromatography-mass spectrometry (LC-MS) assay. Urine samples were subsequently analysed using an NMR-based metabolomics approach coupled with multivariate statistical analysis. Metabolic profiling suggested that hippurate levels could be used to distinguish between groups with low (3.6 ng DON mg(-1) creatinine: 95% CI = 2.6, 5.0 ng mg(-1)) and high (11.1 ng mg(-1): 95% CI = 8.1, 15.5 ng mg(-1)) DON exposure, with the concentration of hippurate being significantly (1.5 times) higher for people with high DON exposure than for those with low DON exposure (p = 0.047). This, to our knowledge, is the first report of a metabolomics-derived biomarker of DON exposure in humans.

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
1秒前
若一应助fang采纳,获得30
4秒前
kk发布了新的文献求助10
5秒前
可靠诗蕊发布了新的文献求助10
5秒前
Orange应助绝逝采纳,获得10
6秒前
渡人舟应助乐乐宝采纳,获得10
6秒前
aajhajkahna应助禾之采纳,获得10
6秒前
nxy完成签到 ,获得积分10
6秒前
fu完成签到,获得积分10
6秒前
梅狸猫不读博完成签到 ,获得积分10
7秒前
7秒前
口腔飞飞完成签到 ,获得积分10
7秒前
8秒前
ralph_liu完成签到,获得积分10
8秒前
闭着眼数星星完成签到,获得积分20
11秒前
liubai完成签到,获得积分10
12秒前
13秒前
13秒前
16秒前
16秒前
17秒前
18秒前
务实的以松完成签到,获得积分10
18秒前
顾矜应助dodo采纳,获得10
19秒前
勿明发布了新的文献求助10
19秒前
stone发布了新的文献求助10
20秒前
22完成签到,获得积分10
20秒前
guochang完成签到,获得积分10
21秒前
wxw发布了新的文献求助10
21秒前
21秒前
22秒前
Yeeee发布了新的文献求助10
22秒前
22秒前
科研通AI6.2应助重要冷之采纳,获得10
22秒前
Hello应助采薇采纳,获得10
22秒前
XiaoShu发布了新的文献求助20
22秒前
24秒前
26秒前
RYY发布了新的文献求助10
26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
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
Comparative Elite Sport Development Systems, Structures and Public Policy 600
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
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 7637373
求助须知:如何正确求助?哪些是违规求助? 9210973
关于积分的说明 19757588
捐赠科研通 7204676
什么是DOI,文献DOI怎么找? 3275647
关于科研通互助平台的介绍 2437328
邀请新用户注册赠送积分活动 2272834