INTRODUCTION
Interindividual and intraindividual variability in drug response can
lead to insufficient therapeutic efficacy or life-threatening adverse
events (Kaddurah-Daouk et al., 2014). In this context, precision
medicine aims to improve therapeutic outcomes by integrating the entire
genetic and phenotypic knowledge specifically related to an individual.
Pharmacogenomics and pharmacometabolomics are both major and
complementary approaches to precision medicine (Beger et al., 2016).
Pharmacogenomics is the use of patient-specific information associated
with the genome to study individual response to drugs, while
pharmacometabolomics focuses on the metabolome (profile of low molecular
weight molecules within a biological system) (Schrimpe-Rutledge et al.,
2016; Pang et al., 2019; Wake et al., 2019). Metabolomics allows
identification and understanding of pathways involved in drug-response
variation (Kaddurah-Daouk et al., 2014). It is also an important tool in
the discovery of biomarkers that can be applied to personalized medicine
(Villaseñor et al., 2014; Jensen et al., 2017; Ivanisevic and Thomas,
2018; Yeung, 2018). Biomarkers help monitor the evolution of a disease
and the corresponding response to drugs, as well as better predict the
clinical outcomes (Kohler et al., 2017). For instance, testosterone
glucuronide, when normalized by androsterone glucuronide, can be used as
a urinary biomarker of an androgen- and drug-metabolizing enzyme (i.e.
UGT2B17), as recently shown through targeted metabolomics analysis
(Zhang et al., 2020). Five ω- and (ω-1)-hydroxylated medium-chain
acylcarnitines have also been identified as novel CYP3A biomarkers using
an untargeted metabolomics approach (Kim et al., 2018).
The cytochrome P450 2D6 (CYP2D6) is responsible for the metabolism of
around 25% of all drugs used in clinical practice including
antidepressants, analgesics, β-blocking agents and antipsychotics
(Gaedigk, 2013). Prescribing CYP2D6 drug substrates is often challenging
for physicians because of the large variability in the activity of this
enzyme. CYP2D6 is a highly polymorphic gene locus and genotyping assays
can be used to predict enzyme activity (Nofziger et al., 2020). However,
relying only on genotyping has several limitations. First, it does not
take into account environmental factors such as concomitant medications,
food intake and disease-related factors (Gaedigk et al., 2018). Second,
depending on the technology and database used, some of the rare variants
may not be screened or even identified, and an allele may be erroneously
categorized as functional (Gaedigk et al., 2018). And third, when
duplication or multiplication is detected, a majority of copy number
tests do not distinguish which of the two allele has several copies
(Langaee et al., 2015; Shah et al., 2016). Therefore, in clinical
practice, precision medicine must rely on both real-time phenotyping and
genotyping in order to provide the best possible recommendations.
Currently, CYP2D6 phenotyping requires the administration of an
exogenous probe drug specifically metabolised by this isoenzyme (Samer
et al., 2013; Magliocco et al., 2019). Microdosing of the probe drug and
enhanced detection capacities of mass spectrometry have lowered the risk
of probe-related side effects. However, potential iatrogenic harm
(allergic reaction, dosing errors) would only be totally eliminated if
endogenous probes were available (Magliocco et al., 2019; Magliocco and
Daali, 2020). A recent review summarized human endogenous compounds that
have been tagged as potential CYP2D6 markers (Magliocco et al., 2019).
One of them stands out. It is a very promising urinary biomarker named
M1 (m/z 444.3102). It was characterised, but not yet structurally
identified in a non-targeted metabolomics study (Tay-Sontheimer et al.,
2014). Some in vitro and animal studies have also demonstrated
that CYP2D6 metabolizes the endocannabinoid anandamide (Snider et al.,
2008).
Our main objective in this study was to explore the presence of CYP2D6
biomarkers in human urine and plasma, using an untargeted metabolomics
approach. For this purpose, healthy volunteers were invited to two
sessions (control vs inhibitory). Prior to the inhibitory session,
volunteers received over 7 days, a daily dose (10 or 20 mg) of the
strong CYP2D6 inhibitor paroxetine. The CYP2D6 genotype and phenotype
were also integrated in the data analysis.