Principal component analysis metabolites

Principal component analysis enables reduction of a large data matrix into two or three main components that include orthogonally relevant information. In such a way, changes in metabolic profiles, described by many variables, can be measurably determined and compared. Subsequently, using other calculation procedures for the reduced data matrix, the importance of variables (metabolites) can be determined and assessed. Discrimination or regression calculation methods are of great importance in this step of the analysis. 

The authors also combined metabolomics results with results obtained from AFP determinations. The model was created using linear discriminant analysis. Principal component analysis was also carried out. Thanks to the created model, it was possible to detect metabolites of potential diagnostic value. Moreover, analysis of metabolomic profiles decreased the number of patients that were incorrectly classified with the use of AFP marker [21]. 

The authors used two deletion mutants in the glycolysis pathway to demonstrate this powerful technique. The two mutants without growth-rate phenotypes showed metabolic phenotypes when concentrations of six metabolites were measured (Raamsdonk et al., 2001). To analyze all the metabolites in the cell at the same time, they used NMR spectroscopy and found that changes in the concentrations of metabolites were similar in these two mutants. The authors concluded that mutant strains containing defective genes involved in similar pathways displayed metabolite profiles that could be clustered together using principal component analysis. 

Pan, Z. et al., Principal component analysis of urine metabolites detected by NMR and DESI-MS in patients with inborn errors of metabolism, Anal. Bioanal. Chem., 387, 539, 2006. 

D /-resolved NMR has been applied to metabolomics to enhance resolution of the overlapping resonances and facilitate identification of the sample compo-nents. Viant used this approach to achieve quantitative ID F2-projections which were analysed using principal component analysis to evaluate metabolites citrate, taurine and alanine in embryogenesis of fish Oryzias latipes. In comparison to conventional NMR quantification the author stated that the likelihood that a... 

These studies use proton NMR spectroscopy to measure amino acids and other metabolites. The changes of the individual components of the NMR profile can yield information on the regional effects in the kidney (Holmes, Bonner, and Nicholson 1997 Holmes et al. 1998 Lindon, Holmes, and Nicholson 2004 Robertson et al. 2005). Several investigators have applied principal component analysis to improve the identification of affected regions of the nephron. As for other renal tests, the timing and collection procedures are critical to the application in addition, several of the measured metabolites are affected by other organ toxicities, particularly hepatotoxicity. 

In this chapter, we will show altered composition of metabolites in the cancerous tissue revealed by IMS, with both manual data processing and statistic data management. In particular, as a statistical strategy, an unsupervised multivariate data analysis technique that enables us to sort the data sets without any reference information is described. A major method that is related to IMS, namely principal component analysis (PCA), will be described in detail. 

Figure 3.41 shows the result of imaging mass spectrometry-principal component analysis (IMS-PCA) for the colon cancer tissue. In this case, this unsupervised analysis revealed that the largest spectral difference (i.e., the largest difference in metabolite composition) was observed between the normal and the other tissue areas (i.e., normal vs. stroma/cancer area), and the second largest difference was observed between the stroma and normal/cancer area. The overall interpretation of PCA was shown in Table 3.6. 

A NMR-based metabonomic study of transgenic maize sets an example of discrimination possible using multivariate techniques (principal component analysis and partial-least squares-discriminant analysis) to NMR data on unfractionated metabolites. Other metabonomics studies are reviewed under... 

Szirmai M (1995) Total synthesis and analysis of major human urinary metabolites of dl-tetrahydrocannabinol, the principal psychoactive component of Cannabis sativa L. Dissertation, Uppsala University, Sweden... 

Although considerable progress has been made in the metabolic profile approach, a number of problems remain to be overcome. Many of these centre around the fluctuations in component composition, not from metabolic disorders, but brought about by other influences. These are principally due to diet and the metabolic variations in individuals in relation to activity. Drugs can also affect the excretion levels of compounds, in addition to the production of their own metabolites. These factors all make quantitative data difficult to obtain and evaluate. Careful statistical analysis of the results are necessary and a population of 500 subjects, grouped in age and sex, has been studied with a view to obtaining a suitable data base for urinary organic acids [370]. 

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