Keywords
heart
transplantation, tacrolimus, voriconazole,
CYP2C19,
CYP3A5
1. Introduction
Fungal infections (FIs), especially invasive aspergillosis (IA) is one
of the common complications in heart transplant (HT) recipients and
cause significant morbidity and mortality. The incidence of IA is 3.5%
to 26.7% in HT patients,1,2 and with risk factors
including isolation of aspergillus fumigatus from bronchoalveolar
lavage, re-operation, cytomegalovirus infection and post-transplant
hemodialysis, et al.3 Patients who receiving
immunosuppressive therapy after solid organ transplantation are
particularly vulnerable to severe infections. Triazole antifungal drugs
such as voriconazole (VRC),
posaconazole and itraconazole are the first or second line for IA
treatment.3,4 These agents are inhibitors of
cytochrome P450 3A4 (CYP3A4), which plays an important role in
metabolizing immunosuppressants such as cyclosporine A, tacrolimus (TAC)
and sirolimus. Thus, drug-drug interactions (DDIs) are inevitable
between azole antifungals and these immunosuppressants in patients
received transplantation. Since changes in immunosuppressants exposure
put patients at a high risk of rejection or toxicity, and the DDIs
cannot be precisely predicted, it is really a complex task for
clinicians to maintain immunosuppressants concentrations within the
therapeutic window when concomitant with azole antifungals.
Among the triazole antifungal drugs, VRC is recommended as a first-line
option for prophylaxis and treatment of IA and also commonly used after
HT.4,5 According to the VRC package insert, when
initiation with VRC in patients already receiving TAC, the TAC dose
should be reduced to one-third of the original dose and followed with
frequent monitoring of TAC blood levels.6 Despite this
recommendation, the magnitude of DDI differs among patients and the
pre-emptive dose modification can still result in TAC overexposure or
even severe toxicity. In a retrospective analysis of renal and lung
recipients, the change of TAC dose-adjusted concentration
(C0/D) between baseline and VRC co-therapy was 5.0±2.7
(range 1.0–20.2) and TAC dose decreased more than fourfold in 64% of
patients.7 These results suggested that VRC metabolism
is complex in vivo and usually affected by clinical and genetic
factors. Identification of predictors for TAC dose adjustment is
extremely important for individualized therapy, however, little
information is available for HT patients at present.
TAC is predominantly metabolized by
hepatic and intestinal CYP3A4/5 enzymes.8Single-nucleotide polymorphism in CYP3A5*3 (rs776746;
6985A>G ) causes alternative splicing and protein
truncation result in the absence of CYP3A5 , contributing to
inter-individual and inter-racial differences in CYP3A-dependent drug
clearance.9 It is well recognized that patients
carrying at least one functional CYP3A5 allele (CYP3A5*1 ) require
approximately two folds higher TAC dose than patients withCYP3A5*3/*3 genotype.10 Moreover,CYP3A4*1G (rs2242480, 20239G>A ),CYP3A4*1B (rs2740574, -392A>G ) and a novelCYP3A4*22 (rs35599367, 15389C>T) are also
significantly associated with TAC
C0/D.11-13 While the frequencies ofCYP3A4*1B and CYP3A4*22 are less than 1% in Asian
patients,14 indicating a limited role in our study
population. With regard to VRC, CYP2C19 is the primarily responsible for
the metabolism of it into VRC N-oxide, though CYP3A4, CYP2C9 and members
of the flavin containing mono-oxygenase (FMO) family also contribute to
the metabolism.15 Also, VRC has the potential to be
both a substrate and an inhibitor of the CYP2C19, CYP3A4 and CYP2C9
enzymes. Of note, the CYP2C19 genotype is a significant
determinant of the wide pharmacokinetics variability for VRC.
Therapeutic recommendations for the use of VRC should be based onCYP2C19 genotype, subtherapeutic and supratherapeutic VRC
concentrations could be avoided by choosing alternative agents in
ultrarapid/rapid metabolizers (UMs *17/*17 or RMs, *1/*17 )
and poor metabolizers (PMs, *2/*2 or *2/*3 or*3/*3 ).16
Our previous study in HT patients using a population pharmacokinetic
(PopPK) approach revealed that TAC clearance was reduced by 63% inCYP3A5 expressers (*1/*1 or *1/*3 ) and 81% inCYP3A5 nonexpressers (*3/*3 ) when co-administrated with
VRC.17 Another study showed that CYP3A5genotype and several clinical variables should be taken into
considerations as modulators of the TAC–azole
interaction.7 A pharmacokinetic study from healthy
volunteers demonstrated that the AUC0-24 of TAC in
CYP2C19 intermediate metabolizers (IMs, *1/*2, *1/*3, *2/*17 ) and
PMs were significantly higher than that in extensive metabolizers (EMs,*1/*1 ) when co-administrated with VRC.18 This
finding indicated that CYP2C19 genotypes may be a potential
determinant for DDI between TAC and VRC. Previous study from
hematopoietic stem cell transplantation (HSCT) implied that the DDI
between TAC and VRC is affected by the genetic polymorphisms in bothCYP3A5 and CYP2C19 g enes.19 However, the
influences of CYP3A4/5 and CYP2C19 genotypes on TAC dose
adjustment with VRC are poorly understood. Therefore, the present study
was conducted to evaluate the potential factors that can elucidate and
predict the magnitude of DDIs between TAC and VRC in HT recipients so as
to help TAC individualized therapy.
2. Methods
2.1 Study design and population
This is a retrospective study investigating the characteristics of DDI
between TAC (Prograf, FK-506; Astellas Ireland Co., Ltd, Kerry, Ireland)
and VRC (Pfizer, Karlsruhe, Germany) in HT patients. Patients were
enrolled into the control group and the VRC group according to whether
VRC was used or not. The study was carried out in accordance with the
Declaration of Helsinki and with approval from the Ethics Committee of
Tongji Medical College, Huazhong University of Science and Technology
(Ethical code: [2018]S331). None of the heart donors came from
executed prisoners. Informed consent was obtained from the enrolled
patients.
Eligible recipients were adults (≥18 years) who received first HT at
Union hospital, Tongji Medical College, Huazhong University of Science
and Technology from February 2015 to November 2020. The exclusion
criteria were as follows: (1) pregnancy or lactation; (2) hepatic or
renal dysfunction; (3) incomplete dose information and clinical data;
(4) receiving concomitant drugs that could interact with TAC (such as
fluconazole, posaconazole, diltiazem, etc.) but except VRC. Moreover,
the inclusion criteria of VRC group were the following: (1) concomitant
administration of TAC and VRC for at least 7 days, (2) availability of
at least 2 TAC trough concentrations (C0) before and
after VRC concomitant therapy. The demographic and clinical data were
collected by reviewing electronic medical records.
2.2 Administration of immunosuppressants and VRC
All of patients received a triple immunosuppressive therapy, which
included TAC, mycophenolate mofetil (CellCept, MMF; Roche, Shanghai,
China) and corticosteroids according to the local clinical protocol as
previously reported.20 Briefly, oral TAC initiation
was given approximately 48 h after transplantation surgery at a dose of
0.02–0.12 mg/kg/day and continued twice daily to achieve individualized
target range (10–15 ng/mL, in the early postoperative days [0–60])
under standard of care of therapeutic drug monitoring
(TDM).21 MMF was initiated at a dose of 1 g every 12 h
with dose adjustment for toxicity or allograft rejection. Oral
prednisone was started 3 days after transplantation with an initial dose
of 1 mg/kg/day (twice daily), and decreased 5 mg every 3 days to a
maintenance dose of 10 mg/day. In Co-VRC group, patients with suspected
or confirmed fungal infection was orally administrated VRC at the dose
of 200 mg every 12 h.
2.3 TAC sampling and measurement
Blood samples were collected 2–3 times a week for C0measurement during hospitalization and whenever deemed necessary by the
attending physician (but not before day 3). The whole blood TAC
C0 was measured using an automated
electrochemiluminescence immunoassay (ECLIA) by the Cobas e411 analyzer
series (Roche, Switzerland), according to the manufacturer’s protocol.
Linearity was verified from 1.1 to 27.1 ng/mL for TAC, with total
imprecision ranged from 3.9 to 9.4% for TAC.22
2.4 Genotyping of CYP3A4 /5 and CYP2C19
Genomic DNA was extracted from 200 μL ethylenediaminetetraacetic
acid-treated peripheral bloods using the QIAampR DNA Blood Mini Kit
(Qiagen, Hilden, Germany). DNA was quantified using a spectrophotometer
(Thermo, Inc., DE, USA) to determine the concentration and purity and
stored at -80◦C until detection. CYP3A4*1G(rs2242480, 20239G>A) , CYP3A5*3 (rs776746,
6986A>G), CYP2C19*2 (rs4244285, 681G>A) andCYP2C19*3 (rs4986893, 636G>A) genotyping were
performed by Sanger sequencing using ABI3730xl analyzer (Applied
Biosystems, CA, USA). All samples were analyzed in triplicate and both
negative and positive controls were included to ensure authenticity of
the results.
2.5 Statistical Analysis
All TAC concentrations were corrected for daily TAC dose (using the dose
ingested the day before trough concentration measurement). Creatinine
clearance (Ccr) was estimated using
the
Cockcroft-Gault formula.23 All continuous variables
were described as median (25th to 75th percentiles) or mean ± standard
deviation.
Continuous
data were tested for normality using the Kolmogorov-Smirnov test. TAC
C0/D were not normally distributed. The nonparametric
Mann–Whitney U and Fisher exact test or χ2 test were
used, respectively, to assess the quantitative and categorical
differences between data from the 2 groups. These statistical analyses
were carried out using GraphPad Prism 9 (version 9.0.0 121; GraphPad
Software, Inc., La Jolla, CA). Univariate and multivariate logistic
regression analyses were carried out using SPSS Statistics version 20.0
(IBM Corp., Armonk, NY, USA). All reported P values were
two-tailed, and aPvalue <0.05 was considered statistically significant.
3. Results
3.1 Patient characteristics
A total number of 137 HT patients were enrolled for analysis, with 69
patients in the control group and the others in the VRC group (before
VRC concomitant were named as Pre-VRC group, concomitant with VRC were
named as Co-VRC group). Demographics of
the study populations when
reaching the TAC target concentration range were summarized in Table 1.
There were no significant differences between the three groups with
respect to age, sex, body weight, hematocrit, creatinine clearance,CYP3A5 genotype and CYP2C19 genotype. The frequencies ofCYP3A4*1G , CYP3A5*3 , CYP2C19*2 and CYP2C19*3alleles were distributed in concordance with Hardy–Weinberg
equilibrium. No patient was found to carry with CYP2C19*3/*3genotype.
3.2 Effects of VRC on the dose and C0/D of TAC
As showed in Table 1 and Figure 1, to maintain therapeutic concentration
level of TAC, the requirements of TAC dose were significantly lower and
the C0/D of TAC were significant higher in
Co-VRC group than those in Pre-VRC
and control groups. Compared to Pre-VRC group, the TAC dose reduced
4.75±2.42 folds and the TAC C0/D increased 5.00±2.27
folds in Co-VRC group. The magnitude of DDI between TAC and VRC showed
large individual variabilities with more than ten-fold changes in TAC
dose (range 1.28–13.00) and TAC C0/D (range
1.43–13.75). In detail, a fourfold reduction of TAC dose was needed for
63.24% patients (43/68) to obtain the same TAC concentration level
before co-therapy with VRC (Figure 2).
3.3 Effects of CYP3A4/5 genotypes on the dose and
C0/D of TAC
To investigate the influence of CYP3A4/5 genotypes on this DDI,
recipients were divided into different groups based on different
genotypes. In the present study, the requirement of TAC dose was
significantly lower in CYP3A5 nonexpressers than that ofCYP3A5 expressers in control group (p<0.001), Pre-VRC
group (p <0.001) and Co-VRC group (p =0.0028)
(Figure 3A). Likewise, significant differences in TAC
C0/D between CYP3A5 expressers and nonexpressers
were
observed
in these three groups (Figure 3B). While there was no significant
difference in TAC dose and C0/D between CYP3A4*1Gallele and CYP3A4*1/*1 genotype in all groups (Figure 1S A and
B). Besides, to reach similar target concentrations, no significant
difference in fold changes of TAC dose and C0/D were
observed before and after VRC co-therapy both in different CYP3A5genotypes (Figure 3C and D) andCYP3A4 genotypes (Figure 1S C and D). Moreover, according toCYP3A4/5 genotypes, we divided CYP3A into CYP3A EMs
(CYP3A5*1 allele and CYP3A4*1G allele), CYP3A IMs
(CYP3A5*1 allele and CYP3A4*1/*1 , or CYP3A5*3/*3and CYP3A4*1G allele) and CYP3A PMs (CYP3A4*1/*1 andCYP3A5*3/*3 ). There was also no significant difference in fold
changes of TAC dose and C0/D before and after VRC
co-therapy in all groups (Figure 2S).
3.4 Effect of CYP2C19 genotype on the dose and
C0/D of TAC
Due to the small number of CYP2C19 PMs, we put CYP2C19 PMs together with
IMs for further analysis. As showed in Figure 4, the requirement of TAC
dose in CYP2C19 IMs/PMs were significant lower than that of EMs in
Co-VRC group (p =0.0395) (Figure 4A). The TAC C0/D
in CYP2C19 IMs/PMs were obviously higher than that of EMs
(p =0.0417) (Figure 4B). CYP2C19 genotypes were not
associated with the changes of TAC dose and C0/D in both
control and Pre-VRC groups (Figure 4A and B). Furthermore, both the fold
changes of TAC dose (4.06±1.85 vs 5.49±2.47, p =0.0031) and
C0/D (4.14±1.91 vs 5.91±2.59, p =0.0019)
before and after VRC co-therapy in CYP2C19 EMs were significantly lower
than these in CYP2C19 IMs/PMs (Figure 4C and D).
3.5 Combined effects of CYP3A5 and CYP2C19 genotypes on
the dose and C0/D of TAC concomitant with VRC
To further investigate the interpreted effects of CYP2C19 andCYP3A5 genotypes on the DDI between VRC and TAC, we subdivided
the Co-VRC group into four groups based on
genotypes.
In CYP2C19 EMs, the TAC dosage needed to achieve target concentration
were significantly lower in CYP3A5 nonexpressers than those inCYP3A5 expressers (p =0.0286). And TAC C0/D
was significantly higher in CYP3A5 nonexpressers than expressers
(p =0.0018). However, in CYP2C19 IMs/PMs, only TAC
C0/D showed significant difference between patients
carried CYP3A5*1 allele and CYP3A5*3/*3 genotype
(p =0.0341). Interestingly, both in CYP3A5 expressers and
nonexpressers, there were no significant difference in TAC dose and
C0/D between CYP2C19 EMs and IMs/PMs (Figure 5A and B).
Moreover, we analyzed the fold changes of TAC dose and
C0/D before and after VRC initiation in different
genotypes. Both in CYP2C19 EMs and IMs/PMs group, there were no
significant difference in the fold changes of TAC dose and
C0/D between CYP3A5 expressers and nonexpressers.
Similarly, in CYP3A5 expressers group, there were no significant
difference in the fold changes of TAC dose and C0/D
between CYP2C19 EMs and IMs/PMs. However, in CYP3A5 nonexpressers
group, the fold changes of TAC dose (4.02±1.44 vs 5.50±2.42,p =0.0173) and C0/D (4.21±1.64 vs5.88±2.37, p =0.0076) in CYP2C19 EMs were significantly lower than
those in CYP2C19 IMs/PMs (Figure 5C and D).
3.6 Predicted factors for the TAC dose adjustment with VRC co-therapy
Although CYP2C19 genotype had an effect of on TAC dose adjustment
in combination with VRC, we further investigated whether other factors
from characteristics of HT recipients may also affect the TAC dose
adjustment. The median fold change of TAC dose was 4.17, which defined
as the cut-off value for further analysis. Risk factors for TAC dose
adjustment, such as age, gender, steroid dose, days after
transplantation, CYP3A4 , CYP3A5 and CYP2C19genotypes were first analyzed by univariate analysis. Covariates that
showed significant correlations (p <0.10) were further
evaluated in the multivariate analysis. CYP2C19 IM/PM (OR 4.592, 95% CI
1.417–14.879; p =0.011) and hematocrit (OR 1.192, 95% CI
1.053–1.35; p =0.006) were associated with the fold changes of
TAC dose in both univariate and multivariate analysis, indicating that
they were independent factors for TAC dose reduction in concomitant with
VRC (Table 2).
Moreover,
the fold changes of TAC dose
when
co-treated with VRC were positively correlated
with the levels of hematocrit
(R=0.2681, p =0.027, Figure 6)
4. Discussion
Precise dose adjustment of TAC is crucial to avoid graft rejection and
toxicities after organ transplantation.24 The DDI
between VRC and TAC is inevitable and highly variable in solid organ
transplantation, which is a challenge for TAC dose modification. To the
best of our knowledge, this is the first study to assess the magnitude
of DDI between VRC and TAC in HT patients during the early stage of
transplantation. The present study demonstrated that TAC dose adjustment
was in a large inter-individual variability after VRC initiation and TAC
dose could be approximately reduced to 1/4-1/5 of the original dose to
maintain the same level. Moreover, it was CYP2C19 but notCYP3A4 and CYP3A5 genotypes that significantly correlated
with the adjustment of TAC dose. In multivariate analysis,CYP2C19 genotype and hematocrit were independent factors
affecting TAC dose modification after VRC combination.
Currently, the recommendation of TAC dose reduction in VRC package
insert was arose from the results of pharmacokinetics study in healthy
volunteers,6 which didn’t consider the potential
factors from hematocrit, hepatic and renal function, DDIs as well as the
genetic polymorphisms of metabolic enzymes and
transporters.25-28 Our results indicated that TAC dose
adjustment due to DDI with VRC was complex and largely variable in organ
transplant patients, which was in line with some previous studies. A
retrospective study in HSCT patients demonstrated that the TAC dose
should be reduced to one-fifth after VRC
co-administered.29 Other studies from renal and liver
transplant patients reported that the rule-of-thumb reduction of the TAC
dose by one-third may not be satisfactory.30,31A
reduction of 75% TAC dosage might be more appropriate for TAC dose when
co-treated with VRC from a cohort of renal and lung
recipients.7 Therefore, TAC dose should not be reduced
based on a fixed ratio when considering DDI, but should be individually
modified according to patient characteristics.
As is commonly known, TAC is mainly metabolized by hepatic and
intestinal CYP3A4/5 enzymes. Although CYP3A4 was the basis of DDI
between TAC and VRC, the CYP3A4*1G was not found to be associated
with the fold changes of TAC dose and C0/D after VRC
co-therapy. As expected, the requirements of TAC dose in patients
carried CYP3A5*1allele
were about 1.5–2 fold higher than those carried with CYP3A5*3/*3genotype in all groups, which was in line with previous
studies.10,32 Nevertheless, CYP3A5*3 also
didn’t affect TAC dose modification and C0/D changes in
concomitant with VRC. Perhaps this could be explained by that VRC was a
stronger suppressor of CYP3A enzyme and weakened the effect ofCYP3A5 genetic variants on TAC metabolism. Although CYP3A5genotype significantly affect TAC metabolism, genotype-based TAC dose
adjustment may sometimes be inappropriate, especially in combination
with drugs that strongly interact with TAC.
CYP2C19 is the primary enzyme responsible for VRC metabolism and the
genetic polymorphism may affect the DDIs of VRC. Consistent with
previous studies,18,33 in Co-VRC group, the
requirement of TAC dose was significant lower and TAC
C0/D was significant higher in CYP2C19 IMs/PMs compared
to CYP2C19 EMs. More importantly, the fold changes of TAC dose to
achieve therapeutic concentration range in CYP2C19 IMs/PMs were
significantly higher than that of
CYP2C19 EMs. In CYP2C19 EMs and CYP2C19 IMs/PMs, the TAC dose was
reduced to approximately a quarter and one fifth of the initial dose,
respectively. Besides, both univariate and multiple regression analysis
revealed that CYP2C19 IMs/PMs was independent factors significantly
contributing to the changes of TAC dose modification before and after
VRC co-therapy. These illustrated that CYP2C19 genotype played a
more prominent role in TAC dose adjustment after VRC initiation,
although TAC is mainly metabolized by CYP3A. When co-administered with
VRC, CYP2C19 genotype-dependent changes of TAC dose and
C0/D was a result of CYP2C19 genotype-related VRC
exposures. Previous study in liver transplant patients indicated that
VRC trough levels were significantly higher in CYP2C19 IMs/PMs and lower
in CYP2C19 EMs.34,35 Experiments in vitro also
demonstrated that the magnitude of inhibition of the metabolism of TAC
by CYP3A was dependent on VRC concentration within a specific
range.31,36 However, this speculation needs to be
further validated in HT patients and we will continue to pay attention
to it.
Additionally, we also found that hematocrit was another determinant for
dose adjustment of TAC when co-administrated with VRC. TAC almost
extensively binds to red blood cells, as a consequence, the TAC
concentrations are measured in whole blood instead of plasma and
strongly affected by hematocrit.8 Lower hematocrit
level was previously identified as a covariate enhancing TAC
clearance.37 In renal transplant recipients, a 10%
absolute decrease in hematocrit may increase TAC clearance by more than
50–100%.38,39 Another study in liver transplant
recipients showed a significant positive correlation between hematocrit
and TAC ratio.40 Of note, our study may be responsible
for the fact that changes of TAC dose adjustment was positively
correlated with levels of hematocrit. This indicated that TAC
concentration fluctuation was insensitive in the low hematocrit level
but more sensitive with the increased hematocrit level. Consequently, we
need to realize that the combination of high whole-blood TAC
concentrations with low hematocrit levels may result in extremely high
unbound plasma concentrations and further lead to toxicity.
Although DDIs between VRC and TAC is inevitable, some strategies can be
used to help dose adjustment. Many PopPK studies regarding TAC in organ
transplantation had been published, TAC dose when concomitant with VRC
can be recommended with model simulation or Bayesian
estimation.17,41,42 Besides, prolonged-release (PR)
TAC formulations had been gradually applied in clinical practice, due to
the advantages in improved medication compliance and less concentration
fluctuations. Interestingly, the effects of VRC on TAC exposure were
substantially smaller and less variable after administrated with PR-TAC
formulation than that in conventional formulation.43Because the absorption of PR-TAC is mainly in the distal small intestine
or in the colon,44 where CYP3A plays a minor
role,45,46 presumably decreasing the magnitude of DDI.
Therefore, PR-TAC may be an optimal choice when considering the DDI
between TAC and VRC, if the above findings could be further validated in
organ transplant patients. Although these findings can provide some
options, TDM of TAC is still essential and really an effective means to
guide dose adjustment.
Some limitations exist in this study. Firstly, VRC trough concentrations
were not routinely monitored, thus it’s difficult to confirm whether DDI
between TAC and VRC is associated with VRC metabolism. Secondly, TAC
concentrations after eliminating VRC were not obtained so that we can’t
evaluate the TAC dose increment. Thirdly, the present study was
performed in a single center with a relatively small sample size and the
results should be further validated in a large population. In future,
prospective studies with multi-center and larger scales should be
encouraged to investigate DDIs between TAC and VRC in HT patients.
Regardless of the limitations described above, our study demonstrated
that CYP2C19 genotype and hematocrit were predictors for TAC dose
optimization after VRC combination. These results may potentially have
clinical implications and will provide some references for TAC dose
modification when combined with VRC.
Acknowledgments : We are grateful to the staff in the Department
of Cardiovascular Surgery, Union Hospital, Tongji Medical College,
Huazhong University of Science and Technology providing patient
information.
Funding : This study was funded by the Hubei Provincial Key
Research and Development Program (No.2020BCA060), the National Key
Research and Development Program (No.2017YFC0909900), and the National
Natural Science Foundation of China (No.81903723, No. 81703630).
Conflict of Interest : There are no conflicts of interest to
disclose.
Author contributions : X.H., Y.Z., H.Z. and Y.Z. designed the
research and wrote the manuscript. J.Z., H.X, H.M., L.L. and L.T.
performed the research. X.H., Y.Z., F.Z., and Y.H. analyzed the data.
H.Z. and Y.Z. contributed analytical tools.