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时间:2020-04-06
《尿液代谢组学研究中质控样本的制备方法研究_陈文才.pdf》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、华南预防医学2014年10月第40卷第5期SouthChinaJPrevMed,October2014,Vol.40,No.5·401··论著·尿液代谢组学研究中质控样本的制备方法研究1,22232陈文才,高燕红,王晶,汤柳英,杨杏芬【摘要】目的初步探索代谢组学研究中尿液质控样本的制备方法。方法运用液质联用技术对健康志愿者、镉暴露者尿样和质控样本检测分析,并对获得的总离子流图、内源性代谢物含量及主成分进行比较。结果该研究样本为40名女性健康志愿者晨尿、40名女性镉暴露者晨尿及来自于80份样本等体积混匀配
2、置成的18份质控样本。随机选取的6份健康志愿者和6份镉暴露者尿样在正、负离子检测模式条件下总离子流图不能完全重叠,6份质控样本总离子流图几乎完全重合。内源性代谢物log2转化的归一化丰度值的四分位数间距比较结果显示,质控样本与健康志愿者和镉暴露者样本代谢物log2转化的归一化丰度值分布之间差异均有统计学意义(均P<0.05);主成分分析(PCA)得分图显示健康志愿者及镉暴露者样本散在分布,而质控样相对集中;进一步对质控样本分析发现,除平衡系统时使用的5个质控样本之外,其他13个质控样本变化均保持在2SD
3、之间。结论该研究配置的质控样本能够反映研究样本基本信息及系统的受控情况,建立了适用于尿液代谢组学研究的质控样本制备方法。【关键词】代谢组学;尿;质控样本;主成分分析中图分类号:R446;O658文献标识码:A文章编号:1671-5039(2014)05-0401-081,2StudyonpreparingqualitycontrolsamplesforurinemetabonomicsresearchCHENWen-cai,2232GAOYan-hong,WANGJing,TANGLiu-ying,YA
4、NGXing-fen.1.SchoolofPublicHealth,SunYat-senUniversity,Guangzhou510080,China;2.GuangdongProvincialCenterforDiseaseControlandPreven-tion;3.MedicalCollegeofJinanUniversity【Abstract】ObjectiveToexplorethemethodofpreparingurinequalitycontrolsamplesinmeta-bono
5、micsresearch.MethodsUrinesamplescollectedfromhealthyvolunteersandcadmiumexposurein-dividuals,andqualitycontrolsampleswereanalyzedbyLC/MStechniques.Then,thetotalioncurrents,thecontentofendogenousmetabolitesandprincipalcomponentswerecompared.ResultsStudysa
6、mplesconsistedof40morningurinesamplesfromfemalehealthyvolunteers,40morningurinesamplesfromcad-miumexposurefemales,and18qualitycontrolsamplespreparedbymixing80urineresearchsamplesate-qualvolumefrom40morningurinesamplesoffemalehealthyvolunteersand40morning
7、urinesamplesofcadmiumexposurefemales.Thetotalioncurrentsof6samplesrandomlyselectedfromhealthyvolunteersand6morningurinesamplesrandomlyfromcadmiumexposurefemalesweredisordered,but6qualitycon-trolsamplesnearlyoverlappedinEST+/-conditions.Theinter-quartiler
8、angeofendogenousmetabolitesindicatedthatcontentsofqualitycontrolsamplesweresignificantlydifferentfromthoseofhealthyvolunteersandcadmiumexposurefemales(bothP<0.05).Thescoreplotsofprincipalcomponentanalysis(PCA)showedthaturi
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