EESI-MS Detection and Statistical Analysis of Multi-batch of Exhaled Breath Metabolomics Data of Liver Failure Patients

doi:10.7503/cjcu20150826

Abstract

Abstract:

In metabolomics studies, the number of samples should be enough to guarantee the reliability of data statistical analysis. The effective storage time of exhaled breath is short, and it is difficult to collect and detect a large number of breath samples in a short time. Combining multi batches of samples may obtain a large data, but usually there is a large variance between batches induced by ambient air varying. In this paper, the exhaled breath data of liver failure patients and healthy volunteers were obtained by high resolution extractive electrospray ionization mass spectrometry(EESI-MS) and then analyzed by multi-block partial least square(MB-PLS). The results were compared with traditional PLS method and showed its strength of removing the variance of batches for modeling. Moreover, we provided a variable selection strategy that based on variable importance in the projection(VIP) of MB-PLS to reduce the redundancy of data and eliminate the effect of non-information variables for modeling, and the performance of MB-PLS model had a great improvement.

Key words: Exhaled breath, Metabolomics, Extractive electrospray ionization mass spectrometry, Multi-block partial least square analysis

CLC Number:

O657.6

TrendMD:

LI Penghui, DENG Lingli, LUO Jiao, LI Wei, NING Jing, DING Jianhua, WU Xiaoping. EESI-MS Detection and Statistical Analysis of Multi-batch of Exhaled Breath Metabolomics Data of Liver Failure Patients[J]. Chem. J. Chinese Universities, 2016, 37(4): 626.

Figures/Tables 8

Fig.1 Two typical multi-block problems(A) The objects are in common, but the variables measured on these objects are different; (B) the variables are in common, but the objects are different.

Table 1 Four batches of exhaled breath sample

Batch	Date of collection	Liver failure patient	Healthy volunteer	Batch	Date of collection	Liver failure patient	Healthy volunteer
1	2014-07-08	9	4	3	2014-08-25	8	11
2	2014-08-14	9	4	4	2014-09-11	9	16

Fig.2 EESI-MS spectra of exhaled breath from liver failure patients and healthy volunteers (A)—(D) MS data of exhaled breath from liver failure patients; (E)—(H) MS data of exhaled breath from healthy volunteers. Each row represents a batch.

Fig.3 Scores plot of MB-PLS model(A) and PLS model(B) by the four batches of data respectivelyThe batches labeled by different graphics, the hollow red graphics and solid blue graphics for the disease group and control group respectively.

Fig.4 Model validation results of MB-PLS(○) and PLS(△) respectively

Fig.5 VIP scores of MB-PLS model

Fig.6 Variation of the mean CAMCCV of MB-PLS model with the threshold of VIP

Fig.7 MS/MS spectrum and proposed structure of m/z 90 from the data of liver failure patients and healthy volunteers breath samples

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