A New Strategy for Efficient Retrospective Data Analyses for Designer Benzodiazepines in Large LC-HRMS Datasets - Pan, Meiru; Rasmussen, Brian Schou; Dalsgaard, Petur Weihe; Mollerup, Christian Brinch; Nielsen, Marie Katrine Klose; Nedahl, Michael; Linnet, Kristian; Mardal, Marie (Frontiers in Chemistry, 2022)
The expanding and dynamic market of new psychoactive substances (NPS) poses challenges for laboratories worldwide. Retrospective data analysis (RDA) of previously analyzed samples for new targets can be used to investigate analytes missed in the first data analysis. However, RDA has historically been unsuitable for routine evaluation, because reprocessing and reevaluating large numbers of forensic samples are highly work and time demanding. In this project, we developed an efficient and scalable retrospective data analysis workflow that can easily be tailored and optimized for groups of NPS. The objectives of the study were to establish a retrospective data analysis workflow for benzodiazepines in whole blood samples and apply it on previously analyzed driving-under-the-influence-of-drugs (DUID) cases. The RDA workflow was based on a training set of hits in ultra-high performance liquid chromatography – quadrupole time-of-flight – mass spectrometry (UHPLC-QTOF-MS) data files, corresponding to common benzodiazepines that also had been analyzed with a complementary UHPLC- tandem mass spectrometry (MS/MS) method. Quantitative results in the training set were used as the true condition to evaluate whether a hit in the UHPLC-QTOF-MS data file was true or false positive. The training set was used to evaluate and set filters. The RDA was used to extract information from 47 DBZD in 13514 UHPLC-QTOF-MS data files from DUID cases analysed from 2014 to 2020, with filters on retention time window, count level, and mass error. Sixteen designer and uncommon benzodiazepines (DBZD) were detected, where 47 identifications had been confirmed by complementary methods when the case was open (confirmed positive finding), and 43 targets were not reported, when the case was open (tentative positive finding). The most common tentative and confirmed findings were etizolam (n=26), phenazepam (n=13), lorazepam (n=9), and flualprazolam (n=8). This method efficiently found DBZD in previously acquired UHPLC-QTOF-MS data files, with only 9 false positive hits. When the standard of an emerging DBZD becomes available, all previously acquired DUID data files can be screened in less than one minute. Being able to perform a fast and accurate retrospective data analysis across previously acquired data files, is a major technological advancement in monitoring NPS abuse.