title: Multidimensional statistical analysis applied to electron ionization mass spectra to determine steroid stereochemistry.
abstract: The differentiation of stereoisomers on the basis of their mass spectra only is usually a difficult challenge even when an informative ionization technique such as electron ionization is used; this is particularly the case for steroids. In this study, multivariate statistical techniques have been applied to the mass spectra of derivatized 5xi-androstane-3xi,17xi-diols (xi = alpha,beta) in order to investigate the possibility of discrimination among the different isomers. After collection of the data from the mass spectra (20 replicates for each of the 8 isomers), each ion was considered as a statistical variable and each mass spectrum as an observation. The more discriminative variables (42 out of the 160 initial ones) were selected using the analysis of variance technique (ANOVA). Thereafter, a linear discriminant analysis (LDA) allowed us to set up a predictive model for stereochemistry determination. The two-dimensional graphical display of the 160 observations on the basis of the canonical variables derived from LDA made it possible to separate the eight isomers. The discrimination of 5alpha and 5beta isomers as well as 3alpha and 3beta was unambiguous, whereas, the discrimination of 17alpha and 17beta epimers was less obvious. The robustness of the model was checked with 40 mass spectra recorded over a 6-month period on different quadrupole mass spectrometers and under different signal acquisition conditions. The percentage of correct assignment of these 'unknown' stereoisomers was 92%; only three 17alpha and 17beta epimers were not correctly plotted in the expected zone. Nevertheless, the performance score was better than those observed with traditional mass spectral libraries. Furthermore, this statistical approach allowed us to identify the main fragment ions involved in the discrimination between isomers: m/z 256 and 421 for isomers 5a-5b; m/z 241 and 331 for isomers 5alpha3alpha-5alpha3beta; m/z 143 and 162 for isomers 5beta3alpha-5beta3beta; and m/z 255 for epimers 17alpha-17beta.
authors.affiliation: Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), Ecole Nationale Vétérinaire de Nantes (ENVN), Atlanpôle La Chantrerie, BP 50707, F-40307 Nantes Cedex 3, France. laberca@vet-nantes.fr
authors.forename: Bruno
authors.initials: B
authors.lastname: Le Bizec
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Antignac
authors.forename: Dominique
authors.initials: D
authors.lastname: Bertrand
authors.forename: El Mostafa
authors.initials: el M
authors.lastname: Qannari
authors.forename: François
authors.initials: F
authors.lastname: Andre
mesh_terms: D000734:Androstenediols / Q000737:chemistry* / Q000145:classification*; D000818:Animals; D003627:Data Interpretation, Statistical; D016002:Discriminant Analysis; D015999:Multivariate Analysis; D021241:Spectrometry, Mass, Electrospray Ionization / Q000379:methods*; D013237:Stereoisomerism; D013256:Steroids / Q000737:chemistry* / Q000145:classification
chemical_list: D000734:Androstenediols; D013256:Steroids