The differentiation of synthetic cathinone isomers using GC-EI-MS and multivariate analysis

Abstract

The emergence of highly similar compounds, such as synthetic cathinone constitutional and positional isomers, has created a growing need for the expansion of the standard analytical approaches used in forensic laboratories. This research develops a canonical discriminant analysis (CDA) approach for the differentiation of synthetic cathinone isomers using gas chromatography-electron ionization-mass spectrometry (GC-EI-MS). This study also investigates the use of multiple scans across the chromatographic peak and a reduction in the number of ions used to construct the CDA models to reduce the required number of replicate sample injections. The chloroethcathinone (CEC) and methoxymethcathinone (MeOMC) positional isomers, as well as the constitutional isomers dibutylone, eutylone, pentylone, and the positional isomer 2,3-pentylone were analyzed in this study.The CDA leave-one-out cross-validation (LOOCV) classification rates were 90.2% for the CEC isomers and 100.0% for the MeOMC and constitutional isomer sets when 15 ions and peak apex data were used to construct the CDA models. The reduction strategies resulted in LOOCV classification rates of at least 67.9%, 98.0%, and 98.1%, for the CEC, MeOMC, and constitutional isomers, respectively. The classification rates improved for all three isomer sets to 75.3%, 99.3%, and 99.4%, respectively, when the lowest concentration samples were removed from the reduction strategies dataset. Finally, a comparison of ion selection methods revealed that the CDA classification rates were similar between the most abundant ions and the ions with the highest principal component analysis (PCA) loadings, indicating the applicability of using relative ion abundance as an ion selection method for CDA classification.