UPLC-MS/MS method for the simultaneous quantification of caffeine and illicit psychoactive drugs in hair using a single-step high-speed grinding extraction – Insights into a cut-off value for caffeine abuse

Abstract

Caffeine is a commonly consumed psychoactive substance whose addictive potential has long been reported. Excessive caffeine intake may lead to severe health damage or drug addiction problems; however, studies on the surveillance of caffeine abuse by the Chinese population are lacking. This study aimed to propose a concentration value for caffeine based on hair analysis to distinguish excessive intake from normal consumption, and provide an analytical tool for forensic toxicology investigations of caffeine and other frequently abused drugs. A sensitive and accurate ultra-high performance liquid chromatography-tandem mass spectrometry method was developed to detect caffeine and 13 illicit drugs and their metabolites in hair. Thereafter, this method was employed to test 479 real samples. Briefly, the hair samples were washed with water and acetone, and subsequently extracted by one-step high-speed grinding with acetonitrile-buffer solution. The lower limit of quantifications of 0.05 ng/mg for caffeine and THC, and 0.005 ng/mg for others, were achieved for all substances. The results revealed a mean caffeine concentration of 0.78 (range 0.008–3.5 ng/mg) based on 24 healthy volunteers, 55.0 (range 3.07–292.2 ng/mg) based on 52 self-reported caffeine abuse participants, and 5.78 (range 0–140.34 ng/mg) based on 403 drug addicts. The mean caffeine concentration in hair from self-reported caffeine abusers was 70-fold higher than that in hair from healthy volunteers. A tentative cut-off level of 5.5 ng/mg as an indicator of excessive caffeine consumption was developed based on receiver operating characteristic analysis. Additionally, the assessment of 403 hair samples from drug addicts indicated that illicit drug abusers had potential for caffeine abuse, especially polydrug users. This hair analysis method serves as a useful tool for the large-scale surveillance of caffeine and illicit drug abuse.