分析化学
分析化學
분석화학
Chinese Journal of Analytical Chemistry
2015年
11期
1766-1771
,共6页
庞博%越晧%王恩鹏%尉海涛%戴雨霖%刘淑莹%吴绥生
龐博%越晧%王恩鵬%尉海濤%戴雨霖%劉淑瑩%吳綏生
방박%월호%왕은붕%위해도%대우림%류숙형%오수생
动脉粥样硬化%快速高分辨液相色谱/质谱%尿酸%胍基乙酸%代谢组学
動脈粥樣硬化%快速高分辨液相色譜/質譜%尿痠%胍基乙痠%代謝組學
동맥죽양경화%쾌속고분변액상색보/질보%뇨산%고기을산%대사조학
Atherosclerosis%Rapid resolution liquid chromatography quadrupole time-of-flight mass spectrometry%Uric acid%Guanidineacetic acid%Metabonomics
利用基于液相色谱-质谱联用的方法对动脉粥样硬化( atherosclerosis, AS)患者和正常对照( Control)人群的尿液进行分析,寻找动脉粥样硬化患者尿液中的差异代谢物,为其发病机制及早期筛查提供科学依据。使用VaSera VS-1000无创动脉血管弹性测定仪筛选15名动脉粥样硬化患者(46.84依2.41)及15名健康者(45.72依1.93),采用高分离度快速液相色谱与四极杆-飞行时间串联质谱(RRLC-QTOF/MS)技术对其尿液代谢物进行分析,采用主成分分析( Principal component analysis, PCA)对两组代谢物进行分类,并寻找潜在生物标记物。 RRLC-QTOF/MS检测结果表明,动脉粥样硬化组和对照组尿液代谢物谱能得到很好的区分,发现并鉴定了2种生物标记物尿酸及胍基乙酸,从而提示嘌呤代谢、氨基酸代谢及氧化应激可能在动脉粥样硬化发生发展中有重要作用。
利用基于液相色譜-質譜聯用的方法對動脈粥樣硬化( atherosclerosis, AS)患者和正常對照( Control)人群的尿液進行分析,尋找動脈粥樣硬化患者尿液中的差異代謝物,為其髮病機製及早期篩查提供科學依據。使用VaSera VS-1000無創動脈血管彈性測定儀篩選15名動脈粥樣硬化患者(46.84依2.41)及15名健康者(45.72依1.93),採用高分離度快速液相色譜與四極桿-飛行時間串聯質譜(RRLC-QTOF/MS)技術對其尿液代謝物進行分析,採用主成分分析( Principal component analysis, PCA)對兩組代謝物進行分類,併尋找潛在生物標記物。 RRLC-QTOF/MS檢測結果錶明,動脈粥樣硬化組和對照組尿液代謝物譜能得到很好的區分,髮現併鑒定瞭2種生物標記物尿痠及胍基乙痠,從而提示嘌呤代謝、氨基痠代謝及氧化應激可能在動脈粥樣硬化髮生髮展中有重要作用。
이용기우액상색보-질보련용적방법대동맥죽양경화( atherosclerosis, AS)환자화정상대조( Control)인군적뇨액진행분석,심조동맥죽양경화환자뇨액중적차이대사물,위기발병궤제급조기사사제공과학의거。사용VaSera VS-1000무창동맥혈관탄성측정의사선15명동맥죽양경화환자(46.84의2.41)급15명건강자(45.72의1.93),채용고분리도쾌속액상색보여사겁간-비행시간천련질보(RRLC-QTOF/MS)기술대기뇨액대사물진행분석,채용주성분분석( Principal component analysis, PCA)대량조대사물진행분류,병심조잠재생물표기물。 RRLC-QTOF/MS검측결과표명,동맥죽양경화조화대조조뇨액대사물보능득도흔호적구분,발현병감정료2충생물표기물뇨산급고기을산,종이제시표령대사、안기산대사급양화응격가능재동맥죽양경화발생발전중유중요작용。
A rapid resolution liquid chromatography quadrupole time-of-flight mass spectrometric ( RRLC-QTOF/MS) method was used to profile the metabolites of urine samples from atherosclerosis ( AS) patients and healthy controls and find the differential metabolites which could provide the scientific evidence to explain the pathogenesis and early disease diagnose. In the study, 15 AS patients ( age46. 84±2. 41 years) and 15 healthy controls ( age45 . 72±1 . 93 years ) was screened out by VaSera VS-1000 . The urine samples were analyzed by RRLC-QTOF/MS and the resulting data matrices were analyzed by multivariate statistical analysis ( Principal Component Analysis, PCA ) to find the potential biomarkers. The results showed that the urine samples of AS patients were successfully distinguished from those of healthy controls. Besides, a total of two significantly changed metabolites, uric acid and Guanidineacetic acid, had been found and identified as potential biomarkers, which suggested that the disorder of purine metabolism and amino acid metabolism played an important role in the mechanism of AS.