An untargeted serum and urine lipidomics research based on UPLC–MS revealed the lipid alterations on adjuvant‐induced arthritis rats

脂类学 脂质代谢 脂质体 化学 代谢组学 新陈代谢 尿 脂肪酸代谢 色谱法 生物化学
作者
Wei Shi,Yue Han
出处
期刊:Biomedical Chromatography [Wiley]
卷期号:37 (11) 被引量:3
标识
DOI:10.1002/bmc.5736
摘要

Rheumatoid arthritis (RA) is a systemic autoimmune disease dominated by chronic inflammatory lesions of peripheral synovial joints. Growing evidence suggests that abnormal lipid metabolism levels contribute to the progression of RA. Although several metabolomics studies have shown abnormality in the RA lipidome, the relationship between the overall lipid metabolites and RA has not been systematically evaluated. In this study, an untargeted lipidomics method based on ultra performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze the serum and urine lipidomes of adjuvant-induced arthritis rats to study the characteristics of lipid metabolism changes in the rats and search lipid markers for diagnosing RA. By combining with orthogonal partial least squares discriminant analysis, a total of 52 potential lipid markers were identified, mainly involved in sphingolipid metabolism, glycerophospholipid metabolism, sterol lipid metabolism, glycerolipid metabolism and fatty acid metabolism, which provided crucial insight into lipid metabolism disturbances in RA. Further receiver operating characteristic analysis revealed that the areas under the curve of PC(22:4/16:0), PI(18:1/16:0) and LacCer(d18:1/12:0) from serum and 25-hydroxycholesterol from urine were 0.94, 1.00, 1.00 and 1.00, respectively, indicating the high predictive ability of this method for RA. In this study, our results indicated that a combination of serum and urine analysis can provide a more comprehensive and reliable assessment of RA, and a UPLC-MS-based lipidomics strategy is a powerful tool to search for potential lipid markers associated with RA and explore the pathogenesis of RA.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
刚刚
小熊有鳗鱼完成签到 ,获得积分10
1秒前
yu完成签到,获得积分10
1秒前
qjy发布了新的文献求助10
1秒前
搞科研的纽曼完成签到,获得积分20
1秒前
JackW发布了新的文献求助10
1秒前
2秒前
善学以致用应助wxz1998采纳,获得10
2秒前
sunchuanliang完成签到,获得积分10
2秒前
3秒前
无心发布了新的文献求助10
5秒前
6秒前
Apple发布了新的文献求助10
6秒前
6秒前
7秒前
kuikui1100发布了新的文献求助10
7秒前
KIVA完成签到,获得积分10
8秒前
8秒前
8秒前
9秒前
姜丝罐罐n发布了新的文献求助10
10秒前
luye应助干净的士萧采纳,获得10
10秒前
淡定自中发布了新的文献求助10
10秒前
思念需要什么完成签到,获得积分10
11秒前
领导范儿应助jin采纳,获得10
11秒前
11秒前
11秒前
赘婿应助AAA房地产小王采纳,获得10
12秒前
13秒前
眠不觉发布了新的文献求助10
13秒前
乌云完成签到,获得积分10
14秒前
hoyden发布了新的文献求助10
14秒前
orixero应助鉴鉴采纳,获得10
14秒前
文sdiw发布了新的文献求助10
15秒前
lei发布了新的文献求助10
15秒前
打打应助dddd采纳,获得10
16秒前
whr完成签到,获得积分10
16秒前
16秒前
闪闪的思柔完成签到 ,获得积分10
16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
Pipeline and riser loss of containment 2001 - 2020 (PARLOC 2020) 1000
Artificial Intelligence driven Materials Design 600
Comparing natural with chemical additive production 500
Investigation the picking techniques for developing and improving the mechanical harvesting of citrus 500
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 500
A Manual for the Identification of Plant Seeds and Fruits : Second revised edition 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5193830
求助须知:如何正确求助?哪些是违规求助? 4376175
关于积分的说明 13628611
捐赠科研通 4231092
什么是DOI,文献DOI怎么找? 2320710
邀请新用户注册赠送积分活动 1319080
关于科研通互助平台的介绍 1269416