中华检验医学杂志
中華檢驗醫學雜誌
중화검험의학잡지
CHINESE JOURNAL OF LABORATORY MEDICINE
2015年
4期
262-266
,共5页
冯爽%刘树业%张立%张磊%杜岩青%冯冉冉
馮爽%劉樹業%張立%張磊%杜巖青%馮冉冉
풍상%류수업%장립%장뢰%두암청%풍염염
代谢组学%结核,胸膜%胸腔积液%生物学标记%最小二乘法分析
代謝組學%結覈,胸膜%胸腔積液%生物學標記%最小二乘法分析
대사조학%결핵,흉막%흉강적액%생물학표기%최소이승법분석
Metabolomics%Tuberculosis,pleural%Pleural effusion%Biological markers%Least-squares analysis
目的 采用超高效液相色谱-质谱联用分析技术(UPLC-MS)分析结核性胸膜炎患者胸腔积液,建立基于代谢物组的OPLS-DA模型,探讨潜在的代谢标志物.方法 收集2012年11月至2013年9月在天津市海河医院住院患者的胸腔积液标本166份(结核性胸腔积液83份,细菌性胸膜炎31份,肺癌30份,心力衰竭22份)进行代谢组学定量分析研究.通过模式识别方法构建正交偏最小二乘判别分析(OPLS-DA)模型,代谢物根据变量投影重要性值(VIP)值、VIP置信区间进行初步筛选,然后利用SPSS 17.0对所得变量进行非参数检验(Kruskal-Wallis H检验),进而筛选出潜在代谢标志物.结果 基于胸腔积液代谢物数据建立的OPLS-DA模型,验证模型的预测准确度达到100％(38/38),该模型能够很好地区分结核性胸膜炎组及对照组.基于代谢物筛查得到的46特征离子中有5个具有统计学差异,其中在结核性胸膜炎组17a,20a-二羟基胆甾醇(2 589 490.00),磷脂[20∶4(8Z,11Z,14z,17z)](1 188 670.00),生育三烯酚(1 051 760.00),磷脂(0-18:0) (434 394.00)与肺癌组(735 615.00、336 815.00、324 563.00、193 055.00)、细菌性胸膜炎组(1 678 805.00、598 256.50、699 384.00、343 866.00)、心力衰竭组(535 842.00、253 503.00、234 503.00、130 185.00)比较显著增高(H分别为26.787、18.680、26.193、21.024,P＜0.01),在结核性胸膜炎组L-苯丙氨酸(245 976.00)与肺癌组(753 033.50)、细菌性胸膜炎组(357 278.00)、心力衰竭组(586 678.00)显著下降(H=13.635,P＜0.01).结论 基于UPLC-MS分析技术平台构建的OPLS-DA模型可区分结核性胸膜炎与对照组,为寻找结核性胸膜炎的特征标志物及早期诊断提供了新的方法.
目的 採用超高效液相色譜-質譜聯用分析技術(UPLC-MS)分析結覈性胸膜炎患者胸腔積液,建立基于代謝物組的OPLS-DA模型,探討潛在的代謝標誌物.方法 收集2012年11月至2013年9月在天津市海河醫院住院患者的胸腔積液標本166份(結覈性胸腔積液83份,細菌性胸膜炎31份,肺癌30份,心力衰竭22份)進行代謝組學定量分析研究.通過模式識彆方法構建正交偏最小二乘判彆分析(OPLS-DA)模型,代謝物根據變量投影重要性值(VIP)值、VIP置信區間進行初步篩選,然後利用SPSS 17.0對所得變量進行非參數檢驗(Kruskal-Wallis H檢驗),進而篩選齣潛在代謝標誌物.結果 基于胸腔積液代謝物數據建立的OPLS-DA模型,驗證模型的預測準確度達到100％(38/38),該模型能夠很好地區分結覈性胸膜炎組及對照組.基于代謝物篩查得到的46特徵離子中有5箇具有統計學差異,其中在結覈性胸膜炎組17a,20a-二羥基膽甾醇(2 589 490.00),燐脂[20∶4(8Z,11Z,14z,17z)](1 188 670.00),生育三烯酚(1 051 760.00),燐脂(0-18:0) (434 394.00)與肺癌組(735 615.00、336 815.00、324 563.00、193 055.00)、細菌性胸膜炎組(1 678 805.00、598 256.50、699 384.00、343 866.00)、心力衰竭組(535 842.00、253 503.00、234 503.00、130 185.00)比較顯著增高(H分彆為26.787、18.680、26.193、21.024,P＜0.01),在結覈性胸膜炎組L-苯丙氨痠(245 976.00)與肺癌組(753 033.50)、細菌性胸膜炎組(357 278.00)、心力衰竭組(586 678.00)顯著下降(H=13.635,P＜0.01).結論 基于UPLC-MS分析技術平檯構建的OPLS-DA模型可區分結覈性胸膜炎與對照組,為尋找結覈性胸膜炎的特徵標誌物及早期診斷提供瞭新的方法.
목적 채용초고효액상색보-질보련용분석기술(UPLC-MS)분석결핵성흉막염환자흉강적액,건립기우대사물조적OPLS-DA모형,탐토잠재적대사표지물.방법 수집2012년11월지2013년9월재천진시해하의원주원환자적흉강적액표본166빈(결핵성흉강적액83빈,세균성흉막염31빈,폐암30빈,심력쇠갈22빈)진행대사조학정량분석연구.통과모식식별방법구건정교편최소이승판별분석(OPLS-DA)모형,대사물근거변량투영중요성치(VIP)치、VIP치신구간진행초보사선,연후이용SPSS 17.0대소득변량진행비삼수검험(Kruskal-Wallis H검험),진이사선출잠재대사표지물.결과 기우흉강적액대사물수거건립적OPLS-DA모형,험증모형적예측준학도체도100％(38/38),해모형능구흔호지구분결핵성흉막염조급대조조.기우대사물사사득도적46특정리자중유5개구유통계학차이,기중재결핵성흉막염조17a,20a-이간기담치순(2 589 490.00),린지[20∶4(8Z,11Z,14z,17z)](1 188 670.00),생육삼희분(1 051 760.00),린지(0-18:0) (434 394.00)여폐암조(735 615.00、336 815.00、324 563.00、193 055.00)、세균성흉막염조(1 678 805.00、598 256.50、699 384.00、343 866.00)、심력쇠갈조(535 842.00、253 503.00、234 503.00、130 185.00)비교현저증고(H분별위26.787、18.680、26.193、21.024,P＜0.01),재결핵성흉막염조L-분병안산(245 976.00)여폐암조(753 033.50)、세균성흉막염조(357 278.00)、심력쇠갈조(586 678.00)현저하강(H=13.635,P＜0.01).결론 기우UPLC-MS분석기술평태구건적OPLS-DA모형가구분결핵성흉막염여대조조,위심조결핵성흉막염적특정표지물급조기진단제공료신적방법.
Objective Pleural effusion of patients with tuberculous pleurisy was analyzed by ultra high performance liquid chromatography-mass spectrometry (UPLC-MS).Orthogonal partial least squares discriminant analysis (OPLS-DA) model was established for searching and analyzing the potential metabolic biomarkers to provide new ideas for the early diagnosis of tuberculosis pleurisy.Methods Totally 166 cases of pleural samples were collected from November 2012 to September 2013 in Tianjin Haihe Hospital (tuberculosis pleurisy 83 cases,bacterial pleurisy 31 cases,lung cancer 30 cases and heart failure 22 cases)and metabonomics quantitative analysis was conducted.Quantitative analysis of metabolic methods was enrolled.Orthogonal partial least squares discriminant analysis (OPLS-DA) model was constructed by the pattern recognition method.Based on the OPLS-DA model,potential biomarkers was filtered preliminary by variable importance in the projection (VIP) and VIP confidence interval value.The specific metabolites were determined by applying non-parametric test(Kruskal-Wallis H test)by using SPSS 17.0,and potential metabolic biomarkers were screened.Results The prediction accuracy of OPLS-DA model was 100％ (38/38),which illustrated that the model could verify the tuberculous pleurisy group and the control group accurately.Based on the data of metabolites,46 potential metabolites were finally screened and 5 metabolites were identified with statistically significant differences (P ＜ 0.05).The data of tuberculosis pleurisy group showed a significant increase in 17a,20a-Dihydroxy cholesteryl,phospholipid [20∶4 (8Z,11Z,14z,17Z)] (1 188 670.00),tocotrienols (1 051 760.00) and phospholipid(O-18:0) (434 394.00) compared with the lung cancer group(735 615.00,336 815.00,324 563.00,193 055.00),bacterial pleurisy group (1 678 805.00,598 256.50,699 384.00,343 866.00),and heart failure group(535 842.00,253 503.00,234 503.00,130 185.00) (H =26.787,18.680,26.193,21.024,P ＜0.01),and a significant decrease in L-phenylalanine(245 976.00)compared with the lung cancer group(753 033.50),bacterial pleurisy group (357 278.00),and heart failure group(586 678.00) (H =13.635,P ＜ 0.01).Conclusions The OPLSDA model constructed on the basic of UPLC-MS technology platform can verify the tuberculous pleurisy group and the control group accurately,and the study provides new ideas and methods for identifying features of tuberculous pleurisy markers and early diagnosis.
