Association Between CYP3A4 and CYP3A5 Genotypes and Cyclosporine's Blood Level and Doses Among Jordanian Kidney Transplanted Patients

Abstract

BACKGROUND
Cyclosporine is used as an immunosuppressive agent in kidney transplantation. It has a narrow therapeutic window. Cyclosporine is predominantly metabolized by CYP3A4 and CYP3A5. The most common single nucleotide polymorphisms (SNPs) affecting cyclosporine metabolism (CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3) were investigated among Jordanian kidney transplanted patients to find out the genotypes and allele frequencies of these SNPs. Additionally, this study investigated whether genotypes of CYP3A4 and CYP3A5 affects C2 blood levels, dosing of cyclosporine and the prevalence of acute rejection.

METHODS
Blood samples of 109 adult patients taking cyclosporine as their primary immunosuppressant for kidney transplantation were collected from Prince Hamzah Hospital, Amman, Jordan. Patients’ first C2 blood levels and their first two given doses were collected. Patients were genotyped for the four SNPs using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) assay method.

RESULTS
Allele frequencies among Jordanian patients for CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3 were 0.037, 0.399, 0.037 and 0.271, respectively. There was a significant association between CYP3A4*22 and mean difference of the second and first given doses (P=0.034). There was a big difference between CYP3A4*22 and the mean of the first C2 blood levels (P=0.063).

CONCLUSION
There was a strong association between CYP3A4*22 and the mean difference of the second and first given doses. There was a trend of significant difference between the mean of the first C2 blood levels among heterozygous CYP3A4*22 patients. Pharmacogenomics may hold promise in assisting the prediction of the best cyclosporine dose and C2 blood level among Jordanian kidney transplanted patients.

Full text

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682 Current Drug Metabolism, 2019, 20, 682-694
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Association Between CYP3A4 and CYP3A5 Genotypes and Cyclosporine's Blood
Levels and Doses among Jordanian Kidney Transplanted Patients
Sahar El-Shair1,*, Mohammad Al Shhab1, Khaled Zayed2, Moaath Alsmady1 and Malek Zihlif1
1Department of Pharmacology, The University of Jordan, Amman, Jordan 2Department of Nephrology and Kidney Transplantation,
Prince Hamzah Hospital, Amman, Jordan
A R T I C L E H I S T O R Y
Received: June 06, 2019
Revised: July 16, 2019
Accepted: July 25, 2019
DOI:
10.2174/1389200220666190806141825
Abstract: Background: Cyclosporine is used as an immunosuppressive agent in kidney transplantation. It has a
narrow therapeutic window. Cyclosporine is predominantly metabolized by CYP3A4 and CYP3A5. The most com-
mon Single Nucleotide Polymorphisms (SNPs) affecting cyclosporine metabolism (CYP3A4*1B, CYP3A4*1G,
CYP3A4*22 and CYP3A5*3) were investigated among Jordanian kidney transplanted patients to find out the geno-
types and allele frequencies of these SNPs. Additionally, this study investigated whether genotypes of CYP3A4 and
CYP3A5 affect C2 blood levels, dosing of cyclosporine and the prevalence of acute rejection.
Methods: Blood samples of 109 adult patients taking cyclosporine as their primary immunosuppressant for kidney
transplantation were collected from the Prince Hamzah Hospital, Amman, Jordan. Patients’ first C2 blood levels and
their first two given doses were collected. Patients were genotyped for the four SNPs using Polymerase Chain Reac-
tion-restriction Fragment Length Polymorphism (PCR-RFLP) assay method.
Results: Allele frequencies among Jordanian patients for CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3
were 0.037, 0.399, 0.037 and 0.271, respectively. There was a significant association between CYP3A4*22 and mean
difference in the second and first given doses (P=0.034). There was a big difference between CYP3A4*22 and the
mean of the first C2 blood levels (P=0.063).
Conclusion: There was a strong association between CYP3A4*22 and the mean difference between the second and
first given doses. There was a trend of significant difference between the mean of the first C2 blood levels among
heterozygous CYP3A4*22 patients. Pharmacogenomics may hold promise in assisting the prediction of the best
cyclosporine dose and C2 blood level among Jordanian kidney transplant patients.
Keywords: Cyclosporine, kidney transplantation, CYP3A4*1B, CYP3A4*1G, CYP3A4*22, CYP3A5*3, Jordanian.
1. INTRODUCTION
Kidney transplantation is the optimal modality of Renal Re-
placement Therapy (RRT) for patients with end-stage renal disease
[1]. Much of the success of kidney transplantation seen nowadays is
due to the use of immunosuppressive medications [2, 3]. Immuno-
suppressive agents hav e a narrow therapeutic window and are asso-
ciated with great inter- and intra-individual response variations [4-
6]. Subtherapeutic blood concentrations are associated with an in-
creased risk of acute rejection. Whereas, overdosing is associated
with an increased risk of adverse events [7].
Cyclosporine (CsA) is one of the cornerstone immunosuppres-
sive agents used in kidney transplantation along with steroids and
antiproliferative drugs [3]. Many factors affect CsA metabolism
such as diet, age, drugs, genetics and others [8, 9]. Pharmacokinet-
ics (PK) and Pharmacodynamics (PD) are difficult to predict in all
transplanted patients [1]. The best clinical practice involves the use
of standard dosing based on body weight and Therapeutic Drug
Monitoring (TDM) by measuring cyclosporine blood levels [1, 9].
However, TDM cannot reflect drug concentration at its site of ac-
tion nor guarantee optimal organ suppression [1]. Some patients
may even develop acute rejection or drug-related adverse events
despite having the drug within the therapeutic window [10, 11].
Genetics was estimated to account for 20-95% of variability in drug
disposition and effect [5, 12-14]. Hence, the emergence of Pharma-
cogenomics (PG) science aims to aid and guide, along with TDM,
future prescription of immunosuppressants [1].
*Address correspondence to this author at the Department of Pharmacology,
University of Jordan, Amman, Jordan. Tel: +962795321521;
E-mail: pharm-d.sahar.elshair@hotmail.com
CsA is extensively metabolized by the isoenzyme CYP3A4 as it
is responsible for about 80% of CsA metabolism [15]. There are
more than 30 Single Nucleotide Polymorphism (SNPs) identified in
the CYP3A4 gene [14, 16]. The most frequent allele known to af-
fect cyclosporine is CYP3A4*1B. Other alleles may include
CYP3A4*22, CYP3A4*1G, CYP3A4*3, CYP3A4 rs 4646437C˃T
and 2 pseudogenes [17-19]. Table 1 [20-22] and Fig. (1) summarize
major CYP3A4 alleles.
CYP3A4*1B is an A- to G- mutation in the 5’ regulatory region
at 290 locus of CYP3A4 (A290G, rs2740574) [23, 24]. It was re-
ported with controversial assumptions regarding its mRNA tran-
scription and enzymatic activity [17, 25-27]. Some support the as-
sumption of an impaired or decreased CYP3A4 enzymatic activity
[23, 28, 29]. Others support the opposite assumption of increased
enzymatic activity and increased rate of drug metabolism as men-
tioned by Barbarino et al. (2013) and Crettol et al. (2008) [17, 18].
Whereas, others presume its in-vitro and in-vivo studies that do not
show any association between genotypes and phenotypes at all [26].
CYP3A4*1G is a highly frequent allele in intron 10 of the
CYP3A4 gene (rs2242480) involving a -G to -A substitution at posi-
tion 82266 [30]. This SNP is also associated with controversial as-
sumptions where some authors presume it is associated with reduced
enzymatic activity [31, 32]. Therefore, patients carrying the mutant
allele have higher CsA levels and consequently require lower doses.
While, others presume its association with a higher enzymatic activity
[25, 30, 33] and the resulting lower CsA levels which thus require
higher doses than patients possessing the wild allele.
CYP3A4*22 is a newly identified SNP in intron 6 found on
CYP3A4 gene that results from a substitution of C to T allele (522-

Association Between CYP3A4 and CYP3A5 Genotypes Current Drug Metabolism, 2019, Vol. 20, No. 8 683
191C>T; rs35599367) [34]. Some reported its association with
decreased CYP3A4 mRNA hepatic levels [18, 35, 36]. Thus, the T-
variant allele was correlated with a decreased CYP3A4 enzymatic
activity [34] when compared to both CT and CC genotypes.
CYP3A5 is considered the second most important CYP3A
isoenzyme in the human liver and intestine [9, 14]. CYP3A5 has a
similar protein sequence to CYP3A4 and similar substrate specific-
ity [1]. It may represent up to 50% of the total hepatic CYP3A con-
tent in people expressing it [17, 37]. Though CsA is oxidized by
CYP3A4, some of its metabolites are formed by CYP3A5, therefore
having a significant impact on CsA PK [36, 38]. There are at least 7
variant alleles of CYP3A5 identified to date. Fig. (2) summarizes
the major CYP3A5 alleles.
The expression of CYP3A5 is affected by a splicing mutation
(A6986G, rs776746) within intron 3 [5, 16, 37] o f the mentioned
gene. The replacement of nucleotide A (CYP3A5*1) by nucleotide G
(CYP3A5*3) at locus 6986 creates an mRNA splice defect with a
premature stop codon resulting in an inactive truncated protein [5, 16,
36]. Thus, CYP3A5*3 variant is a loss-of-function allele [16, 37].
The aim of this study was to examine the genotypes and allele
frequencies of CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and
CYP3A5*3 polymorphisms among Jordanian kidney transplanted
patients. Additionally, this study investigated any association be-
tween genotypes of CYP3A4 and CYP3A5 and all of the C2 blood
levels, dosing of CsA and the prevalence of acute rejection.
2. METHODS AND MATERIALS
A total of 160 kidney transplant patients who attended Neph-
rology and Kidney Transplant Clinics at Prince Hamzah Hospital,
Jordan, were interviewed after obtaining their consent. The study’s
informed consent and case report forms were both approved by the
Institutional Review Board of Prince Hamzah Hospital.
Patients were assigned and identified with a random number.
Around 3-5 ml venous whole blood samples were drawn and col-
lected in Ethylene Diamine Tetra-acetic Acid (EDTA) tubes identi-
fied with a random number for each patient. Tubes were stored at
4°C until analysis. The genomic DNA of each patient was exam-
ined for CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3
polymorphisms. A total of 51 patients were excluded from the
study.
2.1. Inclusion Criteria
Jordanian adult (18 years old and above) patients, including
both female and male population, who underwent kidney transplant
during 2009-2017 and who were prescribed cyclosporine as their
primary immunosuppressant agent.
Table 1. Major CYP3A4 alleles [20-22].
Allele
Nucleotide Change
Protein Effect
Change in Activity
CYP3A4*1B (rs2740574)
-392A<G
Promoter
Decreased
CYP3A4*1G (rs2242480)
20230G>A
Intronic
Decreased
CYP3A4*2 (rs55785340)
15713T>C
Ser222Pro
Decreased
CYP3A4*3 (rs4986910)
23171T>C
Met445Thr
None
CYP3A4*8 (rs72552799)
13908G>A
Arg130Gln
Decreased
CYP3A4*12 (rs12721629)
21896C>T
Leu373Phe
Both
CYP3A4*13 (rs4986909)
22026C>T
Pro416Leu
Decreased
CYP3A4*15A (rs4986907)
14269G>A
Arg162Gln
Nonfunctional
CYP3A4*17 (rs4987161)
15615T>C
Phe189Ser
Both
CYP3A4*18 (rs28371759)
20070T>C
Leu293Pro
Both
CYP3A4*22 (rs35599367)
15389C>T
Intronic
Decreased
Fig. (1). Different CYP3A4 alleles [21].

684 Current Drug Metabolism, 2019, Vol. 20, No. 8 El-Shair et al.
2.2. Exclusion Criteria
Any patient younger than 18 years, any patient prescribed tac-
rolimus as their primary immunosuppressive drug and any patient
prescribed cyclosporine for reasons other than kidney transplant.
2.3. Genome DNA Extraction
DNA was extracted from lymphocytes of peripheral whole
blood using DNA extraction kits (Wizard Genomic DNA Purifica-
tion Kit, Promega, USA) according to the manufacturer’s protocol.
2.4. Genotyping
In order to study the different genotypes o f the patients, a spe-
cific sequence containing the SNP of the gene of interest was am-
plified by Polymerase Chain Reaction (PCR), then through Restric-
tion Fragment Length Polymorphism-Polymerase Chain Reaction
(RFLPs-PCR) process. Specific restriction enzymes were used to
digest normal or mutant alleles at specific sites.
All primers were designed by Primer 3’- according to the Rs-
number of the SNP as shown in Table 2. PCR was performed using
PCR-Thermocycler (Bio-Rad, USA) as described in Table 3. The
resultant amplified sequences were confirmed on agarose gel elec-
trophoresis and visualized using Red Safe. The PCR products were
digested by specific restriction enzyme and RFLP mixture was
prepared as shown in Table 4. Digested products were mixed with
5µl loading dye and confirmed on agarose gel electrophoresis.
Genotypes and phenotypes were recorded according to the size of
the resulted fragments as described in Table 4.
2.5. Statistical Analysis
2.5.1. Prediction of Allele and Genotype Frequencies
Allele and genotype frequencies of 109 patients were estimated.
In addition, the Hardy-Weinberg Equilibrium (HWE) was used.
One for Chi-square value and the other for P-value of the Chi-
Square test. If the P value of the chi-square test is < 0.05, it is then
not consistent with HWE.
2.5.2. Statistical Tests
Normally distributed continuous variables such as age, weight,
C2 levels and doses given were all analyzed using ANOVA test.
Pearson Chi-square test was used to test discrete variables of inde-
pendence to determine the association between all different SNPs
(CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3) and
gender, the prevalence of adverse events and prevalence of acute
rejection. A P-value of 0.05 or less was considered significant. All
the statistical analyses were performed using Statistical Package for
Social Sciences (SPSS Inc., Chicago, Illinois) version 23.0.
2.5.3. Comparison of Allele Frequencies Between Jordanian
Population and other Ethnic Groups
In order to compare allele frequencies between the Jordanian
population and other ethnic populations, the statistical z-test was
Fig. (2). Different CYP3A5 alleles [27].
Arrow heads indicate mutated locations that result in amino acid changes, premature stop codon and alternative splicing.
CYP: Cytochrome P450; INS: Insertion; ORF: Open reading frame; SV: Splicing variant; UTR: Untranslated regions.
Table 2. Primers sequences and expected product size for CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3 PCR amplifica-
tion.
SNP
Primers
Sequence (5’ – 3’)
Rs Number
PCR Product S ize
CYP3A4*1B - F
ATCTGTGTGAGGAGTTTGGT
CYP3A4*1B
CYP3A4*1B - R
GTGAGGCTGTTGGATTGTTT
2740574
470
CYP3A4*1G - F
TCAGAGCCTTCCTACATAGAG
CYP3A4*1G
CYP3A4*1G - R
GTCTTTCCTCTCCTTTCAGC
2242480
315
CYP3A4*22 - F
ACTGTAGTTGTCTGATAGTGGG
CYP3A4*22
CYP3A4*22 - R
CGCTGAGTGGAGAAAGATGT
35599367
290
CYP3A5*3 - F
AAGTCCTCAGAATCCACAGCG
CYP3A5*3
CYP3A5*3 – R
CACACAGCAAGAGTCTCACAC
776746
416
*Primer sequences are designed by Primer 3’- according to rs-number and tested usin g NCBI website.

Association Between CYP3A4 and CYP3A5 Genotypes Current Drug Metabolism, 2019, Vol. 20, No. 8 685
used at 5% level of significance. If z-value is less than 1.96,
then the two proportions of allele frequencies are significantly
similar. On the other hand, if z-value is greater than 1.96, then
allele frequencies are significantly different between the two
groups.
3. RESULTS
3.1. Study Population Characteristics
This study included 109 kidney transplant recipients who vis-
ited the Nephrology and Kidney Transplant Clinics at Prince
Hamzah Hospital periodically and who underwent kidney transplant
from 2006 until early 2017. Patients who were taking cyclosporine
(CsA) drug as their primary immunosuppressant along with predni-
solone and mycophenolic acid as maintenance anti-rejection ther-
apy were included. Their data including C2 blood levels, first two
given doses, the prevalence of drug-related adverse events and
prevalence of acute rejection were reviewed.
Out of the 109 kidney transplant patients, 65% were male and
35% were female between the ages of 18-73 years. The demo-
graphic data included in this study (Table 5) are gender, age,
weight, year of transplant, donor type, Drug-drug Interactions
(DDI) found and the most common reported adverse events. The
most commonly reported drug-related adverse events among our
patient groups were gingival hyperplasia and hirsutism as shown in
Table 5.
All amplified sequences of all alleles tested were confirmed on
1.5% agarose gel electrophoresis and visualized using Red Safe.
The PCR-RFLP analysis of all SNPs was performed on all the 109
subjects. The PCR product was digested by MboII, RsaI, DraIII and
SspI enzymes for CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and
CYP3A5*3, respectively. They were visualized using 3.5 % aga-
rose gel after being stained by Ethidium Bromide. Summary of
gene and allele frequencies with their consistency with HWE is
shown in Table 6.
3.2. C2 Levels and Polymorphisms
The first C2 level was taken for each patient. The association
between the four SNPs and the mean for the first C2 levels are
shown in Table 7. The four polymorphisms showed no significant
association with the mean of the first C2 levels.
Table 3. PCR conditions used and agarose gel confirmations for CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3 genotypes.
PCR Conditions
SNP
Initial
Denaturation
Denaturation
Annealing
Extension
Number of
Cycles
Final
Extension
Confirmed on
Agarose Gel (%)
CYP3A4*1B
54 for 30 seconds
36 cycle
1.5
CYP3A4*1G
52 for 30 seconds
36 cycle
1.5
CYP3A4*22
51 for 30 seconds
36 cycle
2.5
CYP3A5*3
95ºC for 5
minutes
95ºC for 30
seconds
55.4 for 30 seconds
72ºC for 1
minute
39 cycle
72ºC for 7 min
1.5
Table 4. Genotypes and phenotypes of digested fragments for CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3.
SNP
Restriction
Enzyme
Alleles
Fragment Length
Genotypes
Phenotypes
References
AA
69, 104, 297 bp
Homozygous wild
Extensive metabolizers
AG
69, 104, 297, 470 bp
Heterozygous
Intermediate metabolizers
CYP3A4*1B
MboII
GG
470 bp
Homozygous mutant
Poor metabolizers
[23, 28]
GG
192, 123 bp
Homozygous wild
Extensive metabolizers
GA
315, 192, 123 bp
Heterozygous
Intermediate metabolizers
CYP3A4*1G
RsaI
AA
315 bp
Homozygous mutant
Poor metabolizers
[31, 32]
CC
290 bp
Homozygous wild
Extensive metabolizers
CT
97, 193, 290 bp
Heterozygous
Intermediate metabolizers
CYP3A4*22
DraIII
TT
97, 193 bp
Homozygous mutant
Poor metabolizers
[18, 35]
AA
190 + 226 bp
Homozygous wild
Extensive metabolizers
AG
190 + 226 + 416 bp
Heterozygous
Intermediate metabolizers
CYP3A5*3
SspI
GG
416 bp
Homozygous mutant
Non-functioning
[16, 39]
BP: Base pair.

686 Current Drug Metabolism, 2019, Vol. 20, No. 8 El-Shair et al.
Table 5. Demographic data of our study group.
Demographic Data
Variables
No.
%
Mean
Males
71
65
Gender
Females
38
35
-
Total
109
100
-
18-25
19
17
26-35
31
29
36-45
26
24
46-55
21
19
56-65
11
10
Age
66-75 or more
1
1
38.56
Total
109
100
-
≤35
0
0
36-45
10
9
46-55
15
14
56-65
19
17
66-75
25
23
76-85
17
16
86-95
17
16
96-105
6
6
Weight
≥106
0
0
69.72
Total
109
100
-
2010
2
2
2011
8
7
2012
10
9
2013
25
23
2014
24
22
2015
25
23
Year of Transplantation
2016
15
14
-
Total
109
100
-
LR
101
93
Donor Type
LNR
8
7
-
Total
109
100
-
No DDI
80
73
With CYP-450 Inhibitors
27
25
DDI
With CYP-450 Inducers
2
2
-
Total
109
100
-
Table (5) contd….

Association Between CYP3A4 and CYP3A5 Genotypes Current Drug Metabolism, 2019, Vol. 20, No. 8 687
Adverse Events
Reported AE
No AE
Gingival
Hyperplasia
Hirsutism
Increased
KFT
Increased LFT
Rash
Total
AA
83
(82%)
11
(11%)
5
(5%)
0
1
(1%)
1
(1%)
101
AG
5
(83%)
0
0
1
(17%)
0
0
6
CYP3A4*1B
GG
0
0
0
0
1
(100%)
0
1
Total
88
11
5
1
2
1
108
GG
29
(85%)
4
(12%)
0
0
0
1
(3%)
34
GA
48
(77%)
7
(11%)
4
(6%)
1
(2%)
2
(3%)
0
62
CYP3A4*1G
AA
11
(92%)
0
1
(8%)
0
0
0
12
Total
88
11
5
1
2
1
108
CYP3A4*22
CC
82
(82%)
10
(10%)
5
(5%)
1
(1%)
1
(1%)
1
(1%)
100
CT
6
(75%)
1
(12.5%)
0
0
1
(12.5%)
0
8
TT
0
0
0
0
0
0
0
Total
88
11
5
1
2
1
108
CYP3A5*3
AA
63
(83%)
7
(9%)
3
(4%)
1
(1.32%)
1
(1.32%)
1
(1.32%)
76
AG
3
(60%)
1
(20%)
1
(20%)
0
0
0
5
GG
22
(81%)
3
(11%)
1
(4%)
0
1
(4%)
0
27
Total
88
11
5
1
2
1
108
CYP-450: Cytochrome P-450.
DDI: Drug-Drug Interaction.
AE: Adverse Events.
Table 6. Gene and allele frequencies of CYP3A4*1B, CYP3A4*1G, CYP3A4*22 and CYP3A5*3 polymorphisms among Jordanian
patients and their consistency with Hardy-Weinberg Equilibriu m.
HWE
SNP
Number of Patients
Frequency
Chi Sq Value
P-Value of Chi-Sq
CYP3A4*1B
AA (wild)
102/109
0.94
AG
6/109
0.06
Gene Frequency
GG (mutant)
1/109
0.01
A allele
210/218
0.963
Allele Frequency
G allele
8/218
0.037
5.344
0.021
Table (6) contd….

688 Current Drug Metabolism, 2019, Vol. 20, No. 8 El-Shair et al.
HWE
SNP
Number of Patients
Frequency
Chi Sq Value
P-Value of Chi-Sq
CYP3A4*1G
GG (wild)
34/109
0.31
GA
63/109
0.58
Gene Frequency
AA (mutant)
12/109
0.11
G allele
131/218
0.601
Allele Frequency
A allele
87/218
0.399
4.583
0.032
CYP3A4*22
CC (wild)
101/109
0.93
CT
8/109
0.07
Gene Frequency
TT (mutant)
0/109
0
C allele
210/218
0.963
Allele Frequency
T allele
8/218
0.037
0.158
0.691
CYP3A5*3
AA (wild)
77/109
0.71
AG
5/109
0.05
Gene Frequency
GG (mutant)
27/109
0.25
A allele
159/218
0.729
Allele Frequency
G allele
59/218
0.271
85.142
0.000
Table 7. Associations between 1st C2 level and SNPs among Jordanian patients taking cyclosporine.
1st Level
N
Mean
SD
St.Err
F
Sig
AA
102
(93%)
1253.89
579.49
57.38
AG
6
(6%)
1274.83
631.45
257.79
CYP3A4*1B
GG
1
(1%)
1600.00
-
-
Total
109
1258.22
577.59
55.32
0.178
0.837
GG
34
(31%)
1281.35
653.58
112.09
GA
63
(58%)
1274.98
551.85
69.53
CYP3A4*1G
AA
12
(11%)
1104.67
498.51
143.91
Total
109
1258.22
577.59
55.32
0.473
0.624
CC
101
(93%)
1287.10
573.21
57.04
CT
8
(7%)
893.63
537.90
190.18
CYP3A4*22
TT
0
0
0
0
Total
109
1258.22
577.59
55.32
3.520
0.063
AA
77
(71%)
1268.58
578.56
65.93
AG
5
(4%)
1342.20
366.65
163.97
CYP3A5*3
GG
27
(25%)
1213.11
618.76
119.08
Total
109
1258.22
577.59
55.32
0.145
0.865
SD: Standard Deviation.
St.Err: Standard Error.

Association Between CYP3A4 and CYP3A5 Genotypes Current Drug Metabolism, 2019, Vol. 20, No. 8 689
Table 8. Associations between differences between 2nd and 1st given doses and SNPs among Jordanian patients taking cyclosporine.
2nd Given Dose
N
Mean
SD
St.Err
F
Sig
AA
102
(93%)
0.98
33.78
3.34
AG
6
(6%)
4.17
33.23
13.57
CYP3A4*1B
GG
1
(1%)
-25.00
-
-
Total
109
0.92
33.537
3.21
0.323
0.725
GG
34
(31%)
1.84
30.793
5.28
GA
63
(58%)
-1.59
35.89
4.52
CYP3A4*1G
AA
12
(11%)
11.46
27.93
8.06
Total
109
0.92
33.54
3.21
0.778
0.462
CC
101
(93%)
-0.99
32.44
3.23
CT
8
(7%)
25.00
40.09
14.17
CYP3A4*22
TT
0
0
0
0
Total
109
0.92
33.54
3.21
4.600
0.034
AA
77
(71%)
0.65
36.10
4.11
AG
5
(4%)
-15.00
13.69
6.12
CYP3A5*3
GG
27
(25%)
4.63
27.77
5.34
Total
109
0.92
33.54
3.21
0.727
0.486
SD: Standard Deviation
St.Err: Standard Error
3.3. Differences between Given Dose and Polymorphisms
The difference between the second and first given doses was
calculated for each patient. The association between the four SNPs
and the mean difference between the second and first given doses
are shown in Table 8. A statistically significant association was
only observed between CYP3A4*22 and the mean difference be-
tween the second and first given doses with a P -value of 0.034. The
rest of the polymorphisms showed no associations.
3.4. Prevalence of Acute Rejection and Polymorphisms
Prevalence of acute rejection was recorded for each patient. The
association between the prev alence of acute rejection and the four
SNPs is shown in Table 9. No significant association was observed
with any of the four SNPs and prevalence of acute rejection in the
study group.
3.5. Comparison of Allele Frequencies between Jordanian
Population and other Ethnic Groups
The allele frequencies among Jordanian population compared to
other ethnic groups are shown in Table 10.
4. DISCUSSION
CsA is extensively metabolized in the liver and small intestine
by both CYP3A4 and CYP3A5. Both the cytochromes are consid-
ered major reflectors of overall CYP3A activity [9, 50]. The most
common SNPs affecting cyclosporine’s PK include CYP3A4*1B,
CYP3A4*1G, CYP3A4*22 and CYP3A5*3.
The first SNP affecting CsA, CYP3A4*1B, is highly variable
among different racial populations. As Jordan population is consid-
ered, a mixed Caucasian population, this study found that the minor
allele frequency of CYP3A4*1B (G allele) is 0.037, which varies
from previous studies among Jordanians (P=0.107) as reported by
Yousef et al. (2016) [40], but it was consistent with another study
among Caucasian populations (P=0.000) [44]. Cattaneo et al.
(2004) also reported it to be around 4% among Caucasians and
66.7% among the black population [29]. Moreover, van Schaik
(2008) reported this SNP to be more common among African-
Americans when compared to Caucasians. As the case among Cau-
casians, this varian t was also considered rare among Asians [24].
The results of this study did not show any association between
CYP3A4*1B and any CsA PK parameters. Such results are similar
to the results observed by Rivory et al. (2001) [23] and Ashavaid et
al. (2010) [52].
Regarding CYP3A4*1G, which has not been studied among
Jordanian population, the minor allele frequency was 0.399. This
significantly differs from the frequencies among Caucasians
(P=0.000) [46] and Chinese (P=0.025) [47] populations. Regarding
this SNP and its effect on CsA PK parameters, there was no asso-
ciation with any significant effect on PK parameters. Such results
are in agreement with a study conducted at the early stage

690 Current Drug Metabolism, 2019, Vol. 20, No. 8 El-Shair et al.
Table 9. Associations between the prevalence of acute rejection and SNPs among Jordanian patients taking cyclosporine.
Incidence of Acute Rejection
No
Yes
Total
Pearson Chi Square
AA
74
(73%)
27
(27%)
101
AG
2
(33%)
4
(67%)
6
CYP3A4*1B
GG
1
(100%)
0
1
Total
77
31
108
0.090
GG
24
(73%)
9
(27%)
33
GA
42
(67%)
21
(33%)
63
CYP3A4*1G
AA
11
(92%)
1
(8%)
12
Total
77
31
108
0.210
CC
72
(72%)
28
(28%)
100
CT
5
(63%)
3
(37%)
8
CYP3A4*22
TT
0
0
0
Total
77
31
108
0.415
AA
57
(75%)
19
(25%)
76
AG
3
(60%)
2
(40%)
5
CYP3A5*3
GG
17
(63%)
10
(37%)
27
Total
77
31
108
0.419
Table 10. Comparisons of allele frequencies between Jordanian transplantation population and other ethnic transplantation groups
for the four polymorphisms.
Ethnic
References
Sample Size
Allele Frequency
Z-Score
P-Value
CYP3A4*1B
A Allele
G Allele
Jordanians
Present Study
109
0.963
0.037
---
---
Jordanians
[40]
137
0.912
0.088
1.61
0.107
Turkish
[41]
186
0.986
0.014
1.29
0.197
Spanish
[42]
177
0.96
0.04
0.13
0.897
British
[41]
200
0.935
0.065
1.03
0.303
Caucasians
[43]
135
0.93
0.07
1.12
0.263
Caucasians
[44]
241
0.689
0.311
5.68
0
Asians
[45]
151
0.42
0.58
9.04
0
African Americans
[45]
151
0.42
0.58
9.04
0
Table (10) contd….

Association Between CYP3A4 and CYP3A5 Genotypes Current Drug Metabolism, 2019, Vol. 20, No. 8 691
Ethnic
References
Sample Size
Allele Frequency
Z-Score
P-Value
CYP3A4*1B
A Allele
G Allele
CYP3A4*1G
G Allele
A Allele
Jordanians
Present Study
109
0.601
0.399
---
---
European Americans
[46]
48
0.917
0.083
3.97
0
Chinese
[5]
126
0.738
0.262
2.24
0.025
Chinese
[47]
91
0.75
0.25
2.23
0.026
African Americans
[46]
48
0.781
0.219
2.19
0.029
CYP3A4*22
C Allele
T Allele
Jordanians
Present Study
109
0.963
0.037
---
---
Caucasians
[36]
177
0.97
0.03
0.32
0.749
Caucasians
[44]
241
0.71
0.29
5.37
0
CYP3A5*3
A Allele
G Allele
Jordanians
Present Study
109
0.729
0.271
---
---
Jordanians
[40]
137
0.120
0.880
9.73
0.000
Caucasians
[44]
241
0.963
0.037
6.48
0.000
Caucasians
[48]
95
0.906
0.094
3.22
0.001
Koreans
[46]
92
0.745
0.255
0.26
0.795
Koreans
[49]
194
27.6
0.724
7.63
0.0000
African Americans
[46]
48
0.802
0.198
0.97
0.332
post-transplantation on 126 renal transplant patients who revealed
that the wild CYP3A4*1 allele and mutant CYP3A4*1G carriers do
not differ significantly in cyclosporine’s PK [5]. In addition, Zhang
et al. (2013) did not observe any significant influence of this SNP
on cyclosporine C0/Dose among 101 Chinese renal transplant pa-
tients [53].
Findings in this study differ from the study by Hu et al. (2007)
on 26 Chinese healthy subjects who showed a significantly higher
clearance rate in patients having the mutant allele, 50% reduction in
C2 concentration, a lower mean maximum plasma concentration
(Cmax) and a lower mean AUC0-4 [54]. Similarly, Qiu et al.
(2008) also observed in their study that homozygous wild patients
had a 40% higher dose-adjusted trough levels (C0/dose) on days
16-30 post-transplantation when compared to homozygous
CYP3A4*1G mutant patients and C2-post-dose-adjusted level
(C2/dose) for homozygous wild CYP3A4*1 was 35% higher on
days 16-30 and 19% higher on days 8-15 when compared to homo-
zygous mutant patients [55].
The second SNP that was also not investigated in Jordan before
is the CYP3A4*22. Our results revealed the minor allele frequency
to be 0.037, which is significantly different from the frequency
reported by Lunde et al. (2014) (P=0.749) among Caucasians [36].
Interestingly, in this study, there was a trend of significant dif-
ference between the mean of the first C2 blood levels among homo-
zygous wild patients and C2 blood levels among heterozygous
CYP3A4*22 patients (P= 0.063). Elens et al. (2011) also reported a
significant association between CYP3A4*22 and CsA trough levels
C0 (P=0.033) [56].
Additionally, a significant association was found between
CYP3A4*22 polymorphism and the mean difference between the
second and the first given dose (P=0.034). In order to eliminate the
confounder’s effect of the patient’s body weight, the difference
between the second and first doses was calculated.
Limited studies are available regarding the effect of CYP3A4*22
on either CsA’s PK parameters or the difference between the given
doses. Many studies concentrated on the effect of genotypes on actual
given doses, which was thought to be highly influenced by body
weight, were excluded from this study. This was shown by von Ah-
sen et al. (2001), who failed to show any significant association be-
tween CYP3A4*1B genotypes and given doses when a study was
conducted on 124 renal transplant patients [23].
In the case of CYP3A5*3, the minor allele (G allele) frequency
in our study, was found to be 0.271. It had a P-value of 0.000 when
compared to previous studies among Jordanians [40], and a P-value
of 0.001 when compared to Caucasians in a different study with an
allele frequency of 0.094 [48]. This variation in minor allele fre-
quency has also been observed among Koreans (P=0.795 vs. P=0,
respectively) [46, 49] which could have been attributed to different
patient sample selection criteria among different studies of different
ethnic groups.
The results of this study did not show any significant correla-
tion of this allele on CsA’s PK parameters which differed from
Haufroid et al. (2004), who observed a 1.6-fold higher dose-
adjusted trough levels in CYP3A5 non-expressers among 50 stable
kidney transplant patients when compared to CYP3A5 expressers
[57]. Similarly, Tang et al. (2010) observed an increased dose-
adjusted C0 concentration for CYP3A5 non-expressers among 1821
renal transplant patients [16].
Regarding genotypes and the prevalence of acute rejection, the
results of this study did not show any significant association be-

692 Current Drug Metabolism, 2019, Vol. 20, No. 8 El-Shair et al.
tween the four genotypes and acute rejection prevalence. These
observations differ from Crettol et a l. (2008) who observed a
significant association between CYP3A4*1B and the prevalence of
acute rejection [17]. However, Tang et al. (2010), Zhu et al. (2011)
and Qiu et al. (2011) all failed to reveal any significant effect of
CYP3A5*3 genotypes on the prevalence of acute rejection [16, 47,
58].
Lastly, this study has some limitations such as a relatively small
sample and the different cyclosporine sampling methods when
compared to different institutions.
CONCLUSION
There was a strong association between CYP3A4*22 and mean
difference between the second and first given doses (P=0.034).
There was a trend of significant difference between the mean of the
first C2 blood levels among heterozygous CYP3A4*22 patients
(P=0.063). Pharmacogenomics may hold promise in assisting the
prediction of the best cyclosporine dose and C2 blood level among
Jordanian kidney transplant patients.
LIST OF ABBREVIATIONS
AE = Adverse Events
AUC0-4 = Area Under the Curve from 0 to 4 Hours
Bp = Base Pair
C0 = Cyclosporine trough Concentration at Zero Hour
C2 = 2-hours post-dose Cyclosporine Blood Concentra-
tion
Cmax = Maximum Plasma Concentration
CsA = Cyclosporine
CYP-450 = Cytochrome P-450
DDI = Drug-Drug Interaction
EDTA = Ethylene Diamine Tetra-acetic Acid
PCR = Polymerase Chain Reaction
PD = Pharmacodynamics
PG = Pharmacogenomics
PK = Pharmacokinetics
RFLPs-PCR = Restriction Fragment Length Polymorphism-
polymerase Chain Reaction
RRT = Renal Replacement Therapy
S.D. = Standard Deviation
SNP = Single Nucleotide Polymorphism
SPSS = Statistical Package for Social Science
St. Err = Standard Error
TDM = Therapeutic Drug Monitoring
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
Ethical approval of IRB at Prince Hamzah Hospital was granted
on 17/Dec/2018 (Ref. No.: (3309/32).
HUMAN AND ANIMAL RIGHTS
The reported experiments were in accordance with the ethical
standards of the committee responsible for human experimentation
(institutional and national), and with the Helsinki Declaration of
1975, as revised in 2013 (http://ethics.iit.edu/ecodes/node/3931).
CONSENT FOR PUBLICATION
Approved by the Institutional Review Board of Prince Hamzah
Hos-pital, Jordan.
AVAILABILITY OF DATA AND MATERIALS
Not applicable.
FUNDING
This work was supported by the Pharmacology Dept. at the
University of Jordan and Deanship of Scientific and Academic
Research at the University of Jordan.
CONFLICT OF INTEREST
The authors declare no conflict of interest, financial or other-
wise.
ACKNOWLEDGEMENTS
We thank Dr. Rula Saeed (Jordan Hospital). We also thank Dr.
Elias Turk, Nurse Diyaa Fahjan, Nurse Mohammad Khdour, Nurse
Mahmoud Nababteh, staff members of Nephrology and Kidney
Transplantation Clinic and all staff members of Prince Hamzah
Hospital.
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