Introduction

Synthetic cathinones (SCs) represent one of the main new psychoactive substance (NPS) classes, along with synthetic cannabinoids and opioids. Generally marketed as legal alternative to illicit drugs, SCs are often sold labeled as “bath salts” and as replacements of popular stimulants, like amphetamines and analogues. SCs such as 3-methylmethcathinone (3-MMC), 3-chloromethylcathinone (3-CMC), and 4-CMC (clephedrone) constitute a large portion of total NPS seizures in the European drug market. Notably, in 2021, SC seizures represented more than 50% of the seized material, 3-CMC and 4-CMC accounting for 34 and 6%, respectively (1, 2). As amphetamine analogues, they have stimulant and euphoric properties similar to those of 3,4-methylenedioxymethamphetamine (MDMA) or cocaine. However, they can also cause several adverse effects such as agitation, accelerated heart rate, high blood pressure, unconsciousness, and hallucination (3, 4). These effects are attributed to the SC affinity for dopamine, norepinephrine, and serotonin transporters, increasing the concentration of catecholamines in the central nervous system (1, 5).

Since their appearance in the 2000s, many different SCs emerged onto the illicit drug market with minor modifications at the backbone structure to circumvent legal controls and analytical detection while inducing similar or more potent effects (6). Notably, para- and meta-substituted methcathinones appeared to be highly potent alternatives to the classic cathinones (Fig. 1). In particular, in vivo investigations in rats demonstrated that halogenated derivatives exhibit dose- and time-dependent modulation of dopamine brain levels, with 4-CMC being more potent than 4-fluoromethcathinone (4-FMC) and 4-bromomethcathinone (4-BMC, brephedrone) (6, 7). Further studies are necessary to understand the differences in their pharmaco-toxicological profiles (4, 6,7,8). However, despite the health risks associated with their consumption, SCs have gained great popularity and several intoxications and fatalities related to halogenated SCs have been recently reported (1, 6, 9,10,11,12,13,14,15). Particularly, many cases involved 4-CMC consumption along with other NPSs. 3-CMC fatal cases were also reported (11,12,13, 15, 16).

Fig. 1
figure 1

Synthetic cathinone scaffold

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Due to their extensive metabolic degradation, detection of new emerging SCs challenges analytical toxicologists (5, 17). The detection of metabolites is therefore a go-to to prove consumption in clinical and forensic casework. 4-FMC human metabolism was previously assessed (17). 3- and 4-CMC metabolic transformations have been recently studied, although the investigations were partial (5, 16, 18). To the best of our knowledge, 4-BMC metabolism has not been studied. Our investigation of the metabolism of SCs and search for alternative markers of consumption included the assessment of the human metabolism of 3-CMC, 4-CMC, and 4-BMC using in silico metabolite predictions, ten-donor-pooled human hepatocytes incubations, and 3-CMC- and 4-CMC-postive samples from authentic clinical and forensic cases. Incubates and samples were analyzed by liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS) with positive and negative electrospray ionization, and data were automatically and manually mined for an exhaustive screening of phase I and phase II metabolites.

Experimental

In Silico Metabolite Prediction

Phase I and phase II putative metabolites of 3-CMC, 4-CMC, and 4-BMC were predicted using a machine-learning based tool, GLORYx freeware (19, 20). All the phase I and II first-generation metabolites generated with a prediction score equal or higher than 25% were reprocessed to simulate second-generation metabolism; the score threshold was established based on previous experiments evaluating several metabolite prediction software (3). Second-generation metabolites scores was multiplied to the score of the corresponding first-generation metabolite to calculate a final score (adjusted score).

Chemicals and Reagents

3-CMC, 4-CMC, and 4-BMC reference standards were obtained from Cayman Chemical (Ann Harbor, MI, USA), and diclofenac was purchased from Sigma Aldrich (Milan, Italy). Standard solutions were solubilized in methanol to 1 mg/mL and stored at −20 °C until the analysis.

Carlo Erba (Cornaredo, Italy) provided LC-MS grade water, acetonitrile, and methanol. LC-MS grade formic acid was purchased from Sigma Aldrich.

Williams’ medium E, HEPES buffer (2-[4-(2-hydroxyethyl)-1-piperazinyl]ethanesulfonic acid), and l-glutamine were supplied by Sigma Aldrich. Supplemented Williams’ Medium E (sWME) was prepared dissolving HEPES and l-glutamine at 2 and 20 mmol/L, respectively, in Williams’ medium E. The solution was prepared extemporaneously. Thawing medium and cryopreserved ten-donor-pooled human hepatocytes were purchased from Lonza (Basel, Switzerland).

Human Hepatocyte Incubations

As previously described, incubations were conducted following our in-house protocol (21). Briefly, hepatocytes were thawed in thawing medium at 37 °C, then resuspended in sWME. After assessing cell viability with the trypan blue exclusion method, sWME volume was adjusted to 2 × 106 viable cells/mL. The cathinones were diluted to 20 μmol/L in sWME and 250 μL was incubated with 250 μL hepatocytes for 0 or 3 h at 37 °C. Reactions were quenched with an equal volume of ice-cold acetonitrile and centrifugation for 10 min, 15,000 g, at room temperature. The incubates were stored at −80 °C until analysis.

Authentic Samples

Biological samples from three positive cases were analyzed to confirm in vitro results. Case #1 was a suicide and was found positive for 3-CMC (70 ng/mL in blood); postmortem blood and urine were collected at the autopsy. Case #2 was an offense of driving under the influence; oral fluid was collected for roadside drug testing positive for both 3- and 4-CMC (non-quantitative). Case #3 was a patient admitted to the hospital and was found positive for 4-CMC (non-quantitative); urine was collected allegedly 3 h after consumption.

Sample Preparation

Hepatocyte Incubations

Incubates were thawed at room temperature, and 100 μL was mixed with 100 μL acetonitrile and centrifuged for 10 min, 15,000 g, at room temperature. The supernatant was dried at 37 °C under a nitrogen stream, reconstituted with 100 μL mobile phases A:B 90:10 (v/v), and centrifuged for 10 min, 15,000 g, at room temperature. The supernatants were transferred into vials with glass inserts and 10 μL was injected onto the chromatographic system.

Authentic Samples

For case #1, 400 μL blood or urine were mixed with 1 mL acetonitrile and centrifuged for 5 min, 15,000 g, at room temperature. The supernatants were evaporated to dryness under nitrogen at 37 °C. The residues were reconstituted with 200 μL mobile phases A:B 90:10 (v/v), and centrifuged for 10 min, 15,000 g, at room temperature. The supernatants were transferred into vials with glass inserts and 10 μL was injected onto the chromatographic system.

For cases #2 (oral fluid) and #3 (urine), samples were thawed at room temperature, and 50 μL was mixed with 150 μL acetonitrile and centrifuged for 10 min, 15,000 g, at room temperature. The supernatants were evaporated to dryness under nitrogen at 37 °C and then followed the same preparative steps as case #1.

Instrumental Conditions

LC-HRMS/MS analysis was performed with a Dionex UltiMate 3000 chromatographic system coupled with a Thermo Scientific (Waltham, MA, USA) Q Exactive mass spectrometer equipped with heated electrospray ionization source. Each sample was injected once in positive- and once in negative-ionization mode.

Liquid Chromatography

Analyte separation was performed through a Kinetex Biphenyl column (150 × 2.1 mm, 2.6 μm) from Phenomenex (Castel Maggiore, Italy) with a mobile phase gradient at 0.4 mL/min composed of 0.1% formic acid in water (A), and 0.1% formic acid in acetonitrile (B). The gradient started with 2% B held for 2 min, increased to 25% B within 12 min, increased to 95% within 2 min, and held for 4 min; initial conditions were restored within 0.1 min and maintained for 3.9 min. The chromatographic run lasted 24 min. The column oven was set at 37 ± 1 °C and the autosampler temperature was 10 ± 1 °C.

High-Resolution Tandem Mass Spectrometry

Source settings were: spray voltage, ±3.5 kV; sheath gas flow rate, 50 arbitrary units (a.u.); auxiliary gas flow rate, 5 a.u.; auxiliary gas temperature, 300 °C; capillary temperature, 300 °C; S-lens radio frequency level, 50 a.u.

The mass spectrometer acquired from 1 to 20 min of the chromatographic run in full-scan HRMS (FullMS)/data dependent MS/MS (ddMS2) mode. FullMS settings were: range, m/z 100–500; resolution at full width at half maximum at m/z 200, 70,000; automatic gain control (AGC) target, 106; and maximum injection time (IT), 200 ms. ddMS2 settings were: AGC target, 2 × 105; maximum IT, 64 ms; isolation window, m/z 1.2; resolution, 17,500; and stepped normalized collision energy (NCE), 20, 80, and 100 a.u. A maximum number of five ddMS2 scans were triggered for each FullMS scan (minimum intensity, 104; dynamic exclusion, 2.0 s) depending on an inclusion list of putative metabolites based on in silico predictions and postulation (Supplementary Table S1) (5, 16, 18). Due to 4-BMC isotopic distribution, the 3-h incubate with hepatocytes was reinjected with two different inclusion lists using 79Br or 81Br isotope to increase the chances to obtain non-interfered HRMS/MS spectra. Ions that were not included in the inclusion list also triggered ddMS2 scans, although they were not priority (“pick others if idle” option). In addition, an exclusion list was compiled based on background noise, as evaluated during the injection of blank control samples (A:B 90:10, v/v). The Orbitrap was calibrated prior to analysis and a lock mass list with previously identified background ions was compiled in positive-ionization mode and used throughout the analysis for better accuracy (22).

Data Mining

LC-HRMS/MS data mining was performed with Compound Discoverer™ (Thermo Scientific, v. 3.2.0.421), applying a mixed targeted/untargeted workflow as previously described, with minor modifications (3, 23). Briefly, after spectrum selection and retention time alignment between raw data files, the ions were compared to a list of theoretical metabolites generated using combinations of selected transformations. The potential metabolites were then compared to mzCloud, ChemSpider and HighResNPS libraries. Besides, the HRMS/MS spectra and theoretical elemental composition of all ions with an intensity higher than 105 were compared to the same databases. For each sample, signals with an intensity lower than 1% of the most intense metabolite identified were not considered.

Results

In Silico Metabolite Prediction

Predictions of 3-CMC, 4-CMC, and 4-BMC phase I and phase II metabolites in humans are displayed in Supplementary Table S2. A total of 9 first-generation (pA1-pA9) and 64 second-generation (pAX-1 to pAX-13, pAX representing the corresponding first-generation metabolite) metabolites were predicted for 3-CMC; 20 metabolites were duplicates. A total of 9 first-generation (pB1-pB9) and 48 second-generation (pBX-1-pBX-13) metabolites were predicted for 4-CMC, 12 being duplicates. A total of 10 first-generation (pC1-pC10) and 54 second-generation (pCX-1 to pCX-13) metabolites were predicted for 4-BMC, 13 being duplicates. The principal phase I transformations shared by all three analogues were N-acetylation, hydroxylation (phenyl ring or alkyl chain), β-ketoreduction, N-demethylation, and oxidative deamination.

To favor the acquisition of their product-ion spectra over other compounds during the LC-HRMS/MS analysis, all predicted metabolites were compiled in inclusion lists (Supplementary Table S1). All predicted metabolic reactions and combinations were included in the lists of possible transformations for data mining with Compound Discoverer™.

In Vitro Metabolite Identification

The three analogues were only detected in positive-ionization mode: 3-CMC and 4-CMC eluted at 8.72 and 9.14 min, respectively, with a base peak at m/z 198.0678, while 4-BMC was detected at 10.02 min ([M + H]+, m/z 242.0173). As expected from structural analogues, 3-CMC, 4-CMC, and 4-BMC displayed similar fragmentation pattern (Figs. 2, 3 and 4), the only significant difference being the relative intensity of the fragment produced by water loss, which was high in 3- and 4-CMC (m/z 180.0574), consistent with the literature (5, 18), and low in 4-BMC (m/z 224.0067). Subsequent hydrochloric or hydrobromic acid loss produced major fragments at m/z 144.0808/145.0886 in all three compounds. Minor fragment at m/z 103.0542 corresponded to the phenylethyl moiety.

Fig. 2
figure 2

HRMS/MS spectra of 3-CMC and major metabolites identified in human hepatocyte incubates and authentic samples and suggested fragmentation pattern. Unless stated otherwise, spectra were produced after positive electrospray ionization. Gluc, glucuronide; NEG, negative-ionization mode

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Fig. 3
figure 3

HRMS/MS spectra of 4-CMC and major metabolites identified in human hepatocyte incubates and authentic samples and suggested fragmentation pattern. Unless stated otherwise, spectra were produced after positive electrospray ionization. Gluc, glucuronide; NEG, negative-ionization mode

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Fig. 4
figure 4

HRMS/MS spectra of 4-BMC and major metabolites identified in human hepatocyte incubates and suggested fragmentation pattern. Unless stated otherwise, spectra were produced after positive electrospray ionization. Gluc, glucuronide; NEG, negative-ionization mode

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3- and 4-CMC LC-HRMS area were 70% and 15% lower from 0 to 3 h of incubation, respectively. Nine 3-CMC metabolites (A1-A9, by ascending retention time) and nine 4-CMC metabolites (B1-B9) were identified. 4-BMC LC-HRMS signal was 40% less intense from 0 h to 3 h of incubation, and ten metabolites (C1-C10) were identified. Considering that the three molecules were incubated simultaneously and analyzed under the same conditions, the discrepancy observed in the metabolic degradation rates might be explained by a different interaction with metabolic enzymes, cofactors, and transporters based on the halogen nature and position. However, no major differences were observed in the metabolites produced after incubation. β-Ketoreduction and N-demethylation were prominent reactions for all three molecules, and metabolites with ω-hydroxylation, ω-carboxylation, O-glucuronidation, and/or N-acetylation were also detected; metabolites with oxidative deamination were only detected in combination with β-ketoreduction and O-glucuronidation. Although the reactions were the same between the three cathinones, beside N-acetylation being only identified with 3-CMC, the relative intensity of the metabolites with the same transformation showed better resemblance between 4-CMC and 4-BMC than between 3- and 4-CMC.

In vitro results are reported in Tables II, I, and III. Extracted-ion chromatograms of 3-CMC, 4-CMC, 4-BMC, and their metabolites after positive and negative ionization after incubation are displayed in Fig. 5. Structure elucidation of major metabolites is described below.

Table I Metabolic Transformation, Elemental Composition, Retention time (RT), Accurate Mass of Protonated ([M + H]+) and Deprotonated ([M-H]−) Ion, Deviation from Exact Mass, and Liquid Chromatography-High-Resolution Mass Spectrometry Peak Area of 3-CMC and Metabolites after 3-h Incubation with Human Hepatocytes and in Authentic Samples. Mass Tolerance, 5 ppm
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Table II Metabolic Transformation, Elemental Composition, Retention Time (RT), Accurate Mass of Protonated ([M + H]+) and Deprotonated ([M-H]−) Ion, Deviation from Exact Mass, and Liquid Chromatography-High-Resolution Mass Spectrometry Peak Area of 4-CMC and Metabolites after 3-h Incubation with Human Hepatocytes and in Authentic Samples. Mass Tolerance, 5 ppm
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Table III Metabolic Transformation, Elemental Composition, Retention Time (RT), Accurate Mass Of Protonated ([M + H]+) and Deprotonated ([M-H]−) Ion, Deviation from Exact Mass, and Liquid Chromatography-High-Resolution Mass Spectrometry Peak Area of 4-BMC and Metabolites after 3-h Incubation with Human Hepatocytes. Mass Tolerance, 5 ppm
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Fig. 5
figure 5

Extracted-ion chromatograms of 3-CMC, 4-CMC, 4-BMC, and metabolites identified in human hepatocyte incubates. Mass tolerance, 5 ppm

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β-Ketoreduction

Reduction of the carbonyl group (+2H) generated the most intense metabolites for 3-CMC (A3), 4-CMC (B4), and 4-BMC (C4) after positive ionization. The transformation was suggested by a + 2.0156 Da ±5 ppm mass shift from the corresponding parent and a substantial in-source water loss, typical of synthetic cathinones with a β-ketoreduction in similar instrumental and analytical conditions (3,24); for B4, the signal of the in-source fragment was even 20% higher than that of the precursor ion. The water loss was also the most intense fragment in A3, B4, and C4 HRMS/MS spectra, which also contained minor fragments at m/z 125.0153 ± 5 ppm (A3 and B4) or 168.9646 (C4) and 115.0542/116.0621 ± 5 ppm, indicating loss of water and methylamine, and further hydrochloric or hydrobromic acid, respectively. Under the present chromatographic conditions, B4 and C4 LC-HRMS peaks, from 4-CMC and 4-BMC metabolism, respectively, presented a shoulder, suggesting the coelution of diastereoisomers due to the formation of a chiral center; A3 from 3-CMC did not present a shoulder.

N-Demethylation

Another major transformation was the dealkylation of the N-methyl group (-CH2), which was suggested by a − 14.0157 Da ±5 ppm mass shift from the corresponding parent (A2, B3, and C3 from 3-CMC, 4-CMC, and 4-BMC, respectively). The three metabolites had a fragmentation pattern similar to that of their respective parent in positive-ionization mode with major water loss in 3- and 4-CMC spectra at m/z 166.0418 and further hydrochloric or hydrobromic loss at m/z 130.0651/131.0730, and fragment at m/z 103.0542 corresponding to the phenylethyl moiety for all three compounds.

β-Ketoreduction and N-Demethylation

Combination of the two major reactions β-ketoreduction (+2H) and N-demethylation (-CH2) produced another metabolite in 3-CMC (A1), and two other diastereoisomer metabolites in 4-CMC (B1 and B2), and 4-BMC (C1 and C2) incubates. The metabolites’ structure was elucidated through their −12.0000 Da ±5 ppm mass shift from the corresponding parent, their substantial in-source water loss, and their HRMS/MS spectra displaying previously described fragments at m/z 115.0542/116.0621 ± 5 ppm and 168.0575 ± 5 ppm (A1, B1, and B2) or 212.0069 (C1 and C2) due to water loss. Under the chromatographic conditions of the analysis, B1/B2 and C1/C2 diastereoisomers, due to 4-CMC and 4-BMC ketoreduction, respectively, were completely resolved; A1 from 3-CMC only presented one peak.

N-Demethylation and ω-Carboxylation

Although ω-carboxylation (-2H + 2O) alone was not detected with a signal higher than the established threshold, it was found in combination with N-demethylation (-CH2) in 3-CMC (A4), 4-CMC (B5), and 4-BMC (C6) incubates in both positive- and negative-ionization modes. Elemental composition change was indicated by a + 15.9586 Da ±5 ppm mass shift from the respective parent. In negative mode, C6 fragmentation generated the bromide ion at m/z 78.9192; the corresponding fragment was not detected in A4 and B5 spectra, the chloride ion having a mass lower than 50 Da. Other intense fragments were found at m/z 168.0222 ± 5 ppm (A4 and B5) or 211.9722 (C6) due to formic acid loss, and 111.0007 ± 5 ppm (A4 and B5) or 154.9507 (C6) formed by the chlorophenyl or bromophenyl ions, respectively. In positive-ionization mode, characteristic fragments were produced by α-cleavage on either side of the carbonyl group at m/z 110.9995 and 138.9944 for A4 and B5, and 154.9492 and 182.9431 for C6, indicating that the transformation occurred at the methyl. Fragments at m/z 129.0102 for A4 and B5 and 172.9597 for C6 were produced by the chloro/bromobenzyl ring after rearrangement to include an oxygen atom, likely from the carboxylic acid group. A4, B5, and C6 ranked first, second, and second most intense metabolites in 3-CMC, 4-CMC, and 4-BMC, respectively, due to their high intensity in negative-ionization mode entailed by the presence of a carboxyl group.

β-Ketoreduction, Oxidative Deamination, and O-Glucuronidation

Three metabolites with the same mass and fragmentation pattern were only detected in negative-ionization mode, although with a relatively intense signal, in 3-CMC (A5, A6, and A8), 4-CMC (B6, B8, and B9), and 4-BMC (C7, C9, and C10) incubates. These metabolites were produced by oxidative deamination (-NH2 + OH), O-glucuronidation (+C6H8O6), and β-ketoreduction (+2H), as suggested by their +163.0016 Da ±5 ppm mass shift from their respective parent; they are the only phase II metabolites detected in vitro. The lack of signal in positive-ionization mode, despite their intensity after negative ionization, may be explained be the substitution of the amine group, which is much more prone to carry a positive charge during electrospray ionization. The spectra of the metabolites contained the glucuronide loss at m/z 167.0269 ± 5 ppm for 3- and 4-CMC metabolites or 210.9767 ± 5 ppm for 4-BMC and typical ions from the glucuronide fragmentation at m/z 71.0139 ± 5 ppm, 75.0087 ± 5 ppm, 85.0295 ± 5 ppm, and 113.0244 ± 5 ppm under similar instrumental and analytical conditions (25,26), C7, C9, and C10 spectra also contained the bromide ion at m/z 78.9189 ± 5 ppm.

A fourth peak with the same m/z and fragmentation pattern was manually found with an intensity below the intensity threshold at 12.08, 11.87, and 12.67 min for 3-CMC, 4-CMC, and 4-BMC, respectively (one of these peaks was detected with an intensity above the threshold in the blood and urine of the 3-CMC-positive case #1 and named AC – see below). Considering that β-ketoreduction may generate two diastereoisomers and, either for 3-CMC, 4-CMC, and 4-BMC, the four metabolites had similar HRMS/MS spectra, it may be hypothesized that two sets of diastereoisomers (R/S) were produced with O-glucuronidation at either one or the other hydroxyl group formed by β-ketoreduction, producing two diastereoisomers (R/S) depending on the configuration of the newly formed asymmetric carbon, and oxidative deamination. The exact position of the glucuronides might be determined with further studies with nuclear magnetic resonance or comparison to analytical standards.

3- and 4-CMC in Vivo Metabolite Identification

In vivo results are compiled in Tables I and II. Extracted-ion chromatograms of 3-CMC, 4-CMC, and their metabolites after positive and negative ionization in authentic samples are displayed in Fig. 6.

Fig. 6
figure 6

Extracted-ion chromatograms of 3-CMC, 4-CMC, and metabolites identified in authentic samples. Mass tolerance, 5 ppm

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Case #1: 3-CMC-Positive Blood and Urine

Except for A2, A7, and A9, all 3-CMC metabolites identified in human hepatocyte incubations were also detected in the autoptic blood from case #1; 3-CMC itself was not detected. Except for A7 and A9, all metabolites identified in vitro were also detected in the urine. Two additional diastereoisomer metabolites (AA and AB by ascending retention time) produced by β-ketoreduction (+2H) and glucuronidation (+C6H8O6) were identified both in blood and urine, as suggested by their +178.0478 Da mass shift from 3-CMC and their fragmentation spectra that are similar to that of the corresponding non-conjugated metabolite A3. Another additional metabolite (AC) produced by β-ketoreduction, oxidative deamination, and O-glucuronidation was also identified in blood and urine, as suggested by the +163.0016 Da ±5 ppm mass shift from the parent and the fragmentation similar to that of A4, A5, and A8, which underwent the same transformations; AC was retrospectively identified in human hepatocyte incubates. A3 (β-ketoreduction) was the metabolite with the most intense signal in positive-ionization mode in blood, and A4 (N-demethylation and ω-carboxylation) and A8 (β-ketoreduction, oxidative deamination, and O-glucuronidation) were intense only in negative-ionization mode. Similarly, A3 was detected with a high intensity in positive-ionization mode in urine, but A4, A5 (β-ketoreduction, oxidative deamination, and O-glucuronidation), and A8 were detected with a high intensity after negative ionization, A8 signal being the most intense among the metabolites when considering both ionization modes. Although A5, A6, and A8 were not detected when re-extracting the urine samples after β-glucuronidase hydrolysis along with controls, the corresponding non-conjugated metabolites were not detected.

Case #2: 3- and 4-CMC-Positive Oral Fluid

3-CMC metabolites A1, A2, A3, A4, A7, and A8 were detected in the oral fluid of case #2, along with the parent; no additional metabolite was identified. 3-CMC, A1 (β-ketoreduction and N-demethylation), and A3 (β-ketoreduction) had the most intense signals. 4-CMC metabolites B1, B2, B3, and B4 were detected, along with the parent, and B4 (β-ketoreduction) was preponderant.

Case #3: 4-CMC-Positive Urine

Except for B7, all 4-CMC metabolites identified in human hepatocyte incubations were also detected in the urine of case #3, along with the parent. An additional minor metabolite (BA) produced by hydroxylation (+O) and glucuronidation (+C6H8O6) was identified in urine, as suggested by the +192.0272 Da mass shift from 4-CMC and its fragmentation that is similar to that of the corresponding non-conjugated metabolite B7. BA was retrospectively detected in human hepatocyte incubates, although with an intensity below the established threshold. 4-CMC and B4 (β-ketoreduction) had the most intense signal in positive-ionization mode, and B5 (N-demethylation and ω-carboxylation), B6 (β-ketoreduction, oxidative deamination, and O-glucuronidation), B8 (β-ketoreduction, oxidative deamination, and O-glucuronidation), and B9 (β-ketoreduction, oxidative deamination, and O-glucuronidation) were major after negative ionization, B5 signal being the most intense among the metabolites when considering both ionization modes. B6, B8, and B9 corresponding non-conjugated forms were not detected after glucuronide hydrolysis in urine.

Discussion

The abundance of the metabolites cannot be accurately determined under the present analytical conditions due to the lack of analytical standards for the metabolites identified. UV detection might have more accurately reflected the relative amount of the metabolites, although its sensitivity might have been a limiting parameter. The comparison can therefore only be based on the relative signal intensity of the analytes, which can be affected by sample preparation, matrix effect, and susceptibility to electrospray ionization. This latter bias is particularly critical in the present study as major metabolites detected in negative-ionization mode, and produced by combination of β-ketoreduction, oxidative deamination, and O-glucuronidation, are not ionized in positive mode and therefore not detected. Additionally, the ionization of these major metabolites in negative-ionization mode being due to the carboxylic acid group of the glucuronide, the corresponding non-conjugated metabolites (β-ketoreduction and oxidative deamination) and all metabolites that undergo oxidative deamination might have been produced, but were not detected under the present analytical conditions. This hypothesis is corroborated by the non-detection of the corresponding non-conjugated metabolites (and the conjugated ones) in hydrolyzed urine.

The three cathinones displayed a similar metabolic fate, as shown in Fig. 7.

Fig. 7
figure 7

3-CMC, 4-CMC, and 4-BMC metabolic fate in humans. Gluc, glucuronide; bold arrows indicate major pathways

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In Vitro Versus in Vivo

Hepatocyte incubations are a good model to predict in vivo metabolism, although they do not reproduce all processes such as extrahepatic metabolism, reabsorption, and enterohepatic circulation. However, good correlation between 3-CMC incubation with human hepatocytes and authentic samples from cases #1 and #2 was found, as the same metabolites were identified except for AA and AB (β-ketoreduction and glucuronidation), which were only detected in the urine of case #1, albeit with a low intensity compared to the other metabolites, and A9 (β-ketoreduction and N-acetylation), which was only detected in vitro. In postmortem case #1, 3-CMC was not detected in blood and its signal was low in urine compared to that of the main metabolites, which may indicate that a long time elapsed between consumption and death. Consistent with in vitro results, the metabolites with the most intense signal in urine and blood were produced through β-ketoreduction (A3) in positive-ionization mode; β-ketoreduction, oxidative deamination, and further O-glucuronidation (A5, A6, and A8), and N-demethylation and ω-carboxylation (A4), when considering the signal in negative-ionization mode. In case #2 oral fluid, 3-CMC was intense, pointing towards a recent consumption, and A3 (β-ketoreduction) was the only major metabolite.

Good correlation was also found between 4-CMC in vitro versus in vivo samples, despite B7 (ω-hydroxylation) being major in incubates but not detected in authentic samples. Conversely, 4-CMC was intense in case #3 urine, and metabolites B4 (β-ketoreduction) in positive-ionization mode and B8 and B9 (β-ketoreduction, oxidative deamination, and O-glucuronidation) after negative ionization, were predominant. Of note, in case #2, the distinction between 3- and 4-CMC metabolites with the same transformations was only possible through their retention times as determined in vitro, considering that they yield the same fragments with similar relative intensities.

Comparison to the Literature

In the present study, 3-CMC, 4-CMC, and 4-BMC human metabolism was investigated with in silico metabolite prediction, human hepatocyte incubations, and authentic positive samples for a comprehensive overview. The samples were analyzed by LC-HRMS/MS and targeted and untargeted data mining strategy for an exhaustive screening. 3-CMC metabolism was previously studied using human liver microsomes by Lopes et al. (5) and in a case report by Romańczuk et al. (16). 4-CMC metabolism also was recently assessed by Massano et al. during a clinical study with several participants (18). Consistent with our results, the authors found that β-ketoreduction and N-demethylation were major 3- and 4-CMC metabolic pathways. However, none of the studies reported the detection of metabolites formed through N-demethylation and ω-carboxylation (A4 and B5), or β-ketoreduction, oxidative deamination, and O-glucuronidation (A5, A6, A8, AC, B6, B8, and B9), although A4, A8, B6, B8, and B9 were major in our study, especially in urine where A8 and B5 were the main metabolites in cases #1 and #3, respectively. In the study by Lopes et al., 3-CMC metabolism was assessed using human liver microsome incubations without authentic samples, which are a good first approach in identifying the metabolites of specific molecules but do not contain all hepatic enzymes and endogenous cofactors and do not provide the natural orientation of membrane enzymes (5). In the studies by Romańczuk et al. and Massano et al., the analyses were conducted by LC-MS/MS in after electrospray ionization in positive mode only (16,18), which may explain why A4 and B5 (higher signal in negative-ionization mode) and A5, A6, A8, AC, B6, B8, and B9 (no signal in positive-ionization mode) were not detected. In the three articles, the approach used for data mining was not described and the metabolites might have been not detected because they were simply not expected and therefore not searched. Noteworthy, the corresponding metabolites were never reported in the metabolism of other popular SCs such as 3- and 4-MMC, although the same transformation can theoretically occur (27,28,29). This highlights the need for a comprehensive screening of the data with targeted and untargeted strategies for metabolic identification studies, in general. Further comparison is complicated by the lack of detailed information regarding metabolite intensities.

Markers of Consumption

β-Ketoreduction was a major metabolic transformation in all the biological matrices analyzed, consistent with the metabolism of cathinones in general (30). Phase I metabolites with a combination of N-demethylation and ω-carboxylation and phase II metabolites with a combination of β-ketoreduction, oxidative deamination, and O-glucuronidation also had an intense signal, especially in negative-ionization mode. Based on our in vitro and in vivo findings, we suggest A3, A4, and A8 in blood; A3, A4, A5, and A8 in urine; and A3 in oral fluid; as specific metabolite marker of 3-CMC consumption. Similarly, we suggest B4 and B5 in blood; B4, B5, B6, B8, and B9 in urine; and B4 in oral fluid; as metabolite markers of 4-CMC use. Due to the similar metabolic profile in vitro, we suggest the corresponding metabolites C4 and C6 in blood; C4, C6, C7, C9, and C10 in urine; and C4 in oral fluid; as markers of 4-BMC use. The parent signal should also be monitored in cases or recent consumption. Careful attention should be taken to separate position isomers 3-CMC, 4-CMC, and their metabolites to avoid misidentification. Glucuronide hydrolysis of urine samples is not recommended, as the corresponding non-conjugated compounds were not detected with present analytical conditions.

Conclusions

We identified alternative major metabolites markers for documenting 3- and 4-CMC intake in clinical and forensic casework, and we investigated 4-BMC metabolism for the first time. Several major metabolites were poorly or even not detected after positive electrospray ionization, which is often the only ionization mode used in metabolite identification studies. Additionally, several major urinary metabolites were glucuronides whose non-conjugated forms are unlikely to be detected after electrospray ionization, although the analysis of urine samples only after glucuronide hydrolysis is often performed in this kind of studies. We therefore recommend toxicologists being cautious when interpreting data from hydrolyzed samples during routine drug screening, as major metabolites might have become undetectable.

Moreover, our results strongly support the need for comprehensive screening strategies in metabolite identification studies, to avoid overlooking important metabolites. Orthogonal data obtained from different types of analysis, i.e., different analytical columns, ionization modes, or even technologies, are especially paramount. Further investigation in the metabolism of other popular methcathinone analogues such as 3- and 4-MMC is needed, as the corresponding metabolites might be produced.