Original Article
Discovery of the biomarkers from tuberculosis pleural effusion by metabolomic analytical techniques
Shuang Feng, Shuye Liu, Li Zhang, Lei Zhang, Yanqing Du, Ranran Feng
Published 2015-04-11
Cite as Chin J Lab Med, 2015, 38(4): 262-266. DOI: 10.3760/cma.j.issn.1009-9158.2015.04.012
Abstract
ObjectivePleural 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.
MethodsTotally 166 cases of pleural samples were collected from November 2012 to September 2013 in Tianjin Haihe Hospital (tuberculosis pleurisy 83 cases, bacterial pleurisy 31cases, 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.
ResultsThe 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).
ConclusionsThe OPLS-DA 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.(Chin J Lab Med, 2015, 38: 262-266)
Key words:
Metabolomics; Tuberculosis, pleural; Pleural effusion; Biological markers; Least-squares analysis
Contributor Information
Shuang Feng
Department of Clinical laboratory, Haihe Hospital, Tianjin 300350, China
Shuye Liu
Li Zhang
Lei Zhang
Yanqing Du
Ranran Feng
