Chemometric analysis of Fourier transform infrared spectra for the detection of cotinine in fingernails of e-cigarette users

Nicotine exposure from e-cigarette use remains a growing public health concern, necessitating reliable biomarkers and analytical approaches for long-term exposure assessment. This study aimed to investigate the feasibility of detecting and classifying cotinine, the primary metabolite of nicotine, in fingernails of e-cigarette users using Fourier transform infrared (FTIR) spectroscopy coupled with chemometric analysis. Fingernail samples were collected and extracted from 30 e-cigarette users and 30 non-smokers. Infrared spectra were acquired in attenuated total reflectance mode and analysed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) for classification and prediction. Distinct spectral features associated with cotinine were observed in smoker samples, particularly an absorption band near 1277 cm−1 corresponding to C–N stretching vibrations. Quantitative analysis revealed significantly higher cotinine concentrations in smokers compared with non-smokers (p < 0.05, Mann–Whitney U test). Chemometric modelling achieved complete discrimination between groups, with the PLS-DA model demonstrating excellent predictive performance and an area under the receiver operating characteristic (ROC) curve of 1.0. These findings indicate that FTIR spectroscopy combined with chemometric tools provides a rapid and effective approach for cotinine detection in fingernails, supporting its potential application in nicotine exposure assessment.

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