Evaluation of the timing and regional distribution of 18 psychoactive drugs and metabolites in a Chinese city by wastewater analysis Open Access

In recent years, mental disorders have become a serious health problem and are receiving increasing attention. As a result, psychoactive drugs have become the most common prescription drugs globally, with over 30 billion doses prescribed daily in 2008 (Subedi & Kannan 2015). One meta-analysis study revealed that 25% of respondents had suffered from a mental disorder in the past year, and 29.2% had experienced a common mental disorder during their lifetimes (Steel et al. 2014). In China, which is one of the fastest developing countries, the production and use of psychoactive drugs are also increasing every year (Wang et al. 2015). The Chinese Epidemiological Survey on Mental Disorders reported the prevalence of mental disorders in China as 9.32% and the lifetime prevalence of schizophrenia and other mental disorders as 0.61%. These data, which confirm that mental disorders have become a major public health and social problem (Wittchen et al. 2011), emphasize the importance of monitoring and investigating substance dependence and mental disorders in the Chinese population.

Monitoring the use of psychotropic drugs can reflect the mental disorders in a population. In fact, most psychoactive drugs are metabolized in the human body and excreted either unchanged or as metabolites or conjugates (Calisto & Esteves 2009). The parent compounds and their metabolites then enter wastewater and are treated in wastewater treatment plants (WWTPs). This means that wastewater analysis is an effective method for monitoring psychoactive pharmaceutical use. Furthermore, wastewater analysis can also provide real-time, objective, and continuous information about and comparisons of the differences in psychoactive pharmaceutical consumption trends across time and space. Currently, wastewater analysis plays an important role in the monitoring of many psychoactive pharmaceuticals and illicit drugs, and it is currently undergoing comprehensive worldwide promotion.

Many studies have incorporated wastewater analysis to monitor the use of psychoactive drugs, but these have been conducted mainly in Europe, America, and Australia. Subedi & Kannan (2015) studied the occurrence of psychoactive drugs in wastewater in New York State, USA. Causanilles et al. (2017) researched the occurrence of pharmaceuticals in wastewater in Costa Rica. Kosjek et al. (2012) researched the occurrence of benzodiazepines in wastewater in Slovenia. Gurke et al. (2015) studied the occurrence of frequently prescribed pharmaceuticals and corresponding metabolites in wastewater in Germany. Several articles have been published regarding the occurrence of psychoactive drugs in wastewater in China (Zhou et al. 2010; Yuan et al. 2013; Sun et al. 2014; Sui et al. 2015; Wang et al. 2017). Nevertheless, most articles have focused only on Beijing (the capital of China), or only on a few psychoactive pharmaceuticals. In fact, the patterns of use of some psychoactive drugs differ from region to region (Du et al. 2019). In addition, information on regional and time variations in pharmaceuticals in wastewater is scarce.

In our study, we chose 18 frequently prescribed psychoactive drugs and their corresponding metabolites to investigate the occurrence of psychoactive pharmaceuticals and their corresponding metabolites in four suburban WWTPs, seven urban WWTPs, and one school WWTP on working days and weekends in a city in China. The selected psychoactive drugs included two antidepressants (venlafaxine and paroxetine), eight antipsychotic drugs (quetiapine, 7-hydroxyquetiapine, aripiprazole, dehydroaripiprazole, clozapine, risperidone, OH-risperidone, and sulpiride), and eight sedative-hypnotic drugs (promethazine, alprazolam, diazepam, nordiazepam, estazolam, flurazepam, midazolam, and hydroxymidazolam).

Promethazine, venlafaxine, quetiapine, 7-hydroxyquetiapine, alprazolam, aripiprazole, dehydroaripiprazole, clozapine, diazepam, nordiazepam, estazolam, flurazepam, midazolam, hydroxymidazolam, risperidone, OH-risperidone, paroxetine, sulpiride, and diazepam-d5 were purchased from Cerilliant (Round Rock, TX, USA). The mixed-stock standard solution (1 μg/mL) and internal standard solution (10 μg/mL) were diluted with methanol. Working standard solutions at concentrations of 100 and 5 ng/mL in methanol were prepared by serial dilutions of the stock standard solutions. A working internal standard solution at 20 ng/mL was generated by dilution in methanol.

High-performance liquid chromatography-grade methanol and acetonitrile were obtained from Chem Service (USA). Hydrochloric acid (analytical grade) was obtained from Yonghua Chemistry Co. (Jiangsu, China). Formic acid (98%) and ammonium acetate were obtained from Fluka (Buchs, Switzerland). An ammonium hydroxide solution (50%) was purchased from Aladdin Chemistry Co. (Shanghai, China). Ultrapure water was purified using a Milli-Q water system (Millipore, MA, USA). Glass microfiber filter papers (GF/C, 1.2 μm) were acquired from Whatman (Kent, UK).

The blank wastewater used for optimizing and validating the method was obtained from the inlet of a WWTP located in a small town in China. The blank sample was acidified with hydrochloric acid to pH 2, transported to the laboratory, and stored in the dark at −20 °C until analysis.

Authentic wastewater samples were collected every 2 hours from various WWTPs using automatic sampling devices. Twelve wastewater samples from the same day were combined and stored in 600 mL polyethylene terephthalate (PET) bottles as a 24 h composite sample. In our study, all 12 WWTPs were sampled for 4–6 days on working days and weekends (a total of 58 wastewater samples). In these WWTPs, Sj is located near some schools and mainly reflects the situation of the schools; ZHB, XS, SS, and CJZ are located in suburban districts; and DDH, KX, HC, WN, ZJB, XCP, and JXZ are located in the central part of the urban area. Further details about the sampling are included in Supplementary Table S1. The service population was provided by the corresponding WWTPs. After collection, the wastewater samples were acidified with hydrochloric acid to pH 2 and then transported to the laboratory for analysis. Samples were stored at −20 °C until pretreatment.

Sample pretreatment followed the procedure described in a previous paper (Yuan et al. 2020), with minor modifications. Briefly, 50 mL of wastewater was filtered through glass microfiber filter papers, and an internal standard (100 μL of 20 ng/mL) was added to samples prior to solid-phase extraction (SPE). Oasis MCX cartridges were conditioned with methanol (4 mL) and acidified water (4 mL, pH 2 with hydrochloric acid). The wastewater samples were then loaded onto the cartridges at a flow rate of 2 mL/min. Before elution, the cartridges were washed with water (4 mL) and methanol (4 mL) at a flow rate of 2 mL/min and dried under vacuum. Analytes were eluted from the cartridges using 4 mL of 3% ammonium hydroxide in methanol at a flow rate of 1 mL/min. The eluate was then evaporated to dryness at 50 °C and redissolved in 200 μL mobile phase A/mobile phase B (60/40, v/v). Analyses were performed by injecting 20 μL into the ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) system.

Chromatographic separation was performed using an Acquity^TM Ultra Performance LC (Waters, USA) with an Allure PFPP column (100 mm × 2.1 mm, 5 μm) at a flow rate of 0.5 mL/min. Twenty mmol/L ammonium acetate, 5% acetonitrile, and 0.1% formic acid in water was mobile phase A. Acetonitrile was mobile phase B. The gradient was programed as follows: 0–1 min, from 40 to 45% B; 1–6.5 min, from 45 to 90% B; 6.5–12 min, 90%B; 12–12.5 min, from 90%B to 40%B; 12.5–15 min, 40%B.

Mass spectrometry analysis was performed using a Sciex 6500 Plus Q-trap^™ quadrupole mass spectrometer (AB Sciex, USA). The analytes were analyzed in positive mode using multiple reaction monitoring (MRM) mode. The MRM parameters are shown in Supplementary Table S2. The data were evaluated using MultiQuant 3.0.2.

Method validation included determinations of selectivity, linearity, limits of detection (LODs), lower limits of quantitation (LLOQs), extraction recovery, matrix effect, precision, and accuracy.

Selectivity was evaluated by analyzing six different blank wastewater samples. This evaluation was intended to demonstrate the potential interference of endogenous substances with the analyte or IS signals.

Linearity was determined by linear regression with 1/x weighting. The LODs and LLOQs were defined as the concentrations giving a signal-to-noise ratio (S/N) of at least 3 and 10, respectively. The LLOQs were also required to exhibit a relative standard deviation (RSD) of less than 20% and an accuracy ranging between 80 and 120%.

The method extraction recovery, matrix effect, accuracy, and precision were calculated by analyzing three concentrations of samples (5, 20, and 80 ng/L) with six replicates of each sample. The accuracy was expressed as the percentage ratio of the measured concentration to the nominal concentration. The precision was evaluated by the RSD. The extraction recovery was calculated by dividing the pre-extraction spiked sample areas by the post-extraction spiked sample areas. The matrix effect was calculated by dividing the post-extraction spiked sample areas by the standard solution.

The results of method validation are shown in Supplementary Table S3. The correlation coefficients (r²) of linearity were all greater than 0.99. The LODs ranged from 0.2 to 2 ng/L and the LLOQs ranged from 0.5 to 5 ng/L. The accuracy and precision of the target compounds ranged from 88.2 to 111.6% and from 1.1 to 12.5%, respectively. The recovery and matrix effects of the target compounds ranged from 40.1 to 105.7% and from 60.3 to 99.7%, respectively.

The most abundant compounds in wastewater were diazepam, sulpiride, clozapine, venlafaxine, and quetiapine, which had a detection frequency close to 100%. The mean concentration of diazepam ranged from 1.0 ± 0.1 to 8.7 ± 0.6 ng/L, sulpiride from 9 ± 14.5 to 72.3 ± 14.0 ng/L, clozapine from 1.6 ± 3.6 to 24.5 ± 8.1 ng/L, venlafaxine from 3.2 ± 5.2 to 56.3 ± 18.6 ng/L, and quetiapine from 1.2 ± 1.5 to 17.8 ± 8.4 ng/L (Table 1). Nordiazepam is one of the metabolites of diazepam, but the nordiazepam concentration was below the LLOQ for most WWTPs (Table 1). The low frequency of nordiazepam may be related to its low excretion rate (Causanilles et al. 2017). By contrast, 7-hydroxyquetiapine, which is the major active metabolite of quetiapine (Hasselstrom & Linnet 2006), was detected in most WWTPs with mean concentrations ranging from 0.2 ± 0.3 to 1.3 ± 0.3 ng/L (Table 1). The detection frequency of estazolam was close to 75%, and its concentration was lower than 3 ng/L. Promethazine, alprazolam, and paroxetine had low detection frequencies. Other compounds, including aripiprazole, dehydroaripiprazole, flurazepam, midazolam, hydroxymidazolam, risperidone, and OH-Resperidone, were not detected in all WWTPs.

The mass loads of targets are shown in Table 2. Sulpiride had the highest average load (8.7 mg/1,000 inh/day), followed by venlafaxine (4.9 mg/1,000 inh/day), clozapine (3.6 mg/1,000 inh/day), quetiapine (1.5 mg/1,000 inh/day), and diazepam (0.8 mg/1,000 inh/day). In addition to being an antipsychotic, sulpiride has some effects on depression, and venlafaxine is also an antidepressant. These findings reflect the fact that depression has become one of the important components of mental disorders and has gradually become a major public health and social problem. The mean load of venlafaxine and quetiapine estimated in our study was lower than that reported in New York (Subedi & Kannan 2015). Diazepam loads reported previously in Beijing were similar to those of our study (Wang et al. 2017).

Monitoring the use of psychotropic drugs can reflect the mental disorders in a population. Currently, wastewater analysis is considered an effective method for monitoring the use of psychoactive pharmaceuticals. This study investigated the occurrence of 18 psychoactive drugs and their corresponding metabolites in 12 WWTPs in a southern city in China. For most compounds, lower loads of target compounds were found in the WWTPs in the suburbs than in the urban areas. On the contrary, diazepam showed higher loads in suburban WWTPs than in urban WWTPs, and school areas showed high loads of diazepam. In addition, a correlation analysis of the targets revealed a correlation between venlafaxine, sulpiride, and clozapine. These results may be associated with depression in patients with schizophrenia. Overall, wastewater analysis is expected to be a significant tool for monitoring the consumption of psychoactive pharmaceuticals.

The authors are grateful to the Shanghai Science and Technology Commission (24DZ3001800), the Opening Foundation of the Key Laboratory of Forensic Medicine of the Ministry of Justice (GY2025C-3), the Shanghai Forensic Service Platform (19DZ2292700), the Shanghai Key Laboratory of Forensic Medicine (21DZ2270800) and the Shanghai Association of Forensic Science (SHSFJD2023-009) for their financial support of this study.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.