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Research ArticleMetabolism, Transport, and Pharmacogenomics

Alterations in Xenobiotic-Metabolizing Enzyme Activities across Menstrual Cycle in Healthy Volunteers

E. Asprodini, V. Tsiokou, E. Begas, T. Kilindris, E. Kouvaras, M. Samara and I. Messinis
Journal of Pharmacology and Experimental Therapeutics February 2019, 368 (2) 262-271; DOI: https://doi.org/10.1124/jpet.118.254284
E. Asprodini
Laboratory of Pharmacology (E.A., V.T., E.B., E.K.), Medical Informatics (T.K.), Pathology (M.S.), and Department of Obstetrics and Gynecology (I.M.), Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
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V. Tsiokou
Laboratory of Pharmacology (E.A., V.T., E.B., E.K.), Medical Informatics (T.K.), Pathology (M.S.), and Department of Obstetrics and Gynecology (I.M.), Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
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E. Begas
Laboratory of Pharmacology (E.A., V.T., E.B., E.K.), Medical Informatics (T.K.), Pathology (M.S.), and Department of Obstetrics and Gynecology (I.M.), Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
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T. Kilindris
Laboratory of Pharmacology (E.A., V.T., E.B., E.K.), Medical Informatics (T.K.), Pathology (M.S.), and Department of Obstetrics and Gynecology (I.M.), Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
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E. Kouvaras
Laboratory of Pharmacology (E.A., V.T., E.B., E.K.), Medical Informatics (T.K.), Pathology (M.S.), and Department of Obstetrics and Gynecology (I.M.), Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
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M. Samara
Laboratory of Pharmacology (E.A., V.T., E.B., E.K.), Medical Informatics (T.K.), Pathology (M.S.), and Department of Obstetrics and Gynecology (I.M.), Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
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I. Messinis
Laboratory of Pharmacology (E.A., V.T., E.B., E.K.), Medical Informatics (T.K.), Pathology (M.S.), and Department of Obstetrics and Gynecology (I.M.), Faculty of Medicine, School of Health Sciences, University of Thessaly, Larissa, Greece
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  • Fig. 1.
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    Fig. 1.

    Sampling phases in experimental protocols studying enzyme activity during the menstrual cycle. (A) Schematic diagram of the experimental protocol followed in the present study across one menstrual cycle. Samples were collected at three sampling phases designated by the gray shaded areas: EFP, 2nd to 4th days; LFP, 10th to 12th days; and LP, 19th to 25th days post onset of menses. Blood and urine samples were collected at each phase 6 hours after the caffeine test, following 24-hour abstinence from caffeine-containing foods and beverages (box preceding coffee cup). Reference levels of estradiol, progesterone, LH, and FSH during menstrual cycle are shown in different line types. (B) Literature review of sample collection phases determining xanthine pharmacokinetics across menstrual cycle. Reduced CYP1A2 activity was reported in studies which included LFP sampling in their experimental protocol and compared EFP and LP to LFP. Conversely, no effect in enzyme activity was reported in studies which were designed to make comparisons between follicular and luteal phases.

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    Fig. 2.

    Metabolic pathways involved in caffeine metabolism in humans. The major pathway in the metabolism of caffeine is catalyzed by CYP1A2 and involves the N-1, N-3, and N-7 demethylations of caffeine [1,3,7-trimethylxanthine (137X)] to form theobromine [3,7-dimethylxanthine (37X)], paraxanthine [1,7-dimethylxanthine (17X)], and theophylline [1,3-dimethylxanthine (13X)], respectively (shown in blue), accounting for about 80%, 11%, and 4% of caffeine metabolism (heavy arrows) (Lelo et al., 1986; Gu et al., 1992). Dimethylxanthines are N-demethylated to the corresponding monomethylxanthine, 1-methylxanthine (1X), 3-methylxanthine (3X), and 7-methylxanthine (7X). Caffeine and xanthines are hydroxylated into their corresponding uric acids: 1,3,7-trimethyluric acid (137U), 1,3-dimethyluric acid (13U), 1,7-dimethyluric acid (17U), 3,7-dimethyluric acid (37U), 1-methyluric acid (1U), 3-methyluric acid (3U), and 7-methyluric acid (7U). CYP2A6 catalyzes the conversion of paraxanthine to 17U. The polymorphic enzyme NAT2 catalyzes the C8–N9 bond scission and the acetylation of paraxanthine to produce AFMU, which is then converted nonenzymatically into 5-acetylamino-6-amino-3-methyluracil (AAMU) in urine. XO is responsible for the conversion of 1X into 1U. Metabolites, enzymes, and metabolic molar ratios used as indices of enzyme activities in the present study are shown in red. Dashed arrows indicate minor metabolic pathways.

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    Fig. 3.

    Hormone levels during menstrual cycle. Individual data (A) and mean estimates (±S.E.) (B) of estradiol (E2), progesterone (PRG), LH, and FSH in 42 healthy volunteers (group 1: n = 21; Group 2: n = 15; Group 3: n = 6) at the three sampling phases (EFP, LFP, and LP). *EFP is different from LFP and LP; †LP is different from EFP and LFP. CMRs were compared across sampling phases at three levels (EFP, LFP, LP) using one-way repeated-measures ANOVA.

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    Fig. 4.

    CYP1A2 in vivo indices during menstrual cycle. (A) Individual data (upper graphs) and mean estimates (±S.E., lower graphs) of CYP1A2 CMRs in nonsmoking (straight lines) and smoking (dashed lines) volunteers measured in the three groups of volunteers (group 1: n = 21; group 2: n = 15; group 3: n = 6) at EFP, LFP, and LP. Thick solid lines in the lower graphs represent overall (nonsmoking and smoking) mean CYP1A2 CMR estimates (error bars denote 95% CIs). *The overall CYP1A2 CMR value in group 1 is significantly reduced at LFP compared with EFP (P = 0.002) and LP (P < 0.001) (one-way repeated-measures ANOVA); §Overall CYP1A2 CMR value in group 1 is reduced at LFP compared with EFP (P = 0.056) and LP (P = 0.003) (one-way repeated-measures ANOVA). Group 3 did not exhibit any significant difference in CYP1A2 CMRs among the three sampling phases. (B) PCR amplification products of genomic DNAs were extracted from peripheral blood (b1, left). M, 100-bp DNA ladder; NG, negative sample. PCR products were digested by PspOMI, and PCR restriction fragment length polymorphism of CYP1A2*1F (rs762551) were subjected to agarose gel electrophoresis (b1, right). A/A genotype: positions 1, 2, 3, 5, 7, 8; C/A genotype: positions 4, 6, 9. (b2) Scatter plot of CYP1A2 CMRs, considered at EFP, of all volunteers (n = 42) stratified by genotype and smoking. Mean CYP1A2 CMR values (horizontal lines) are higher in smokers compared with nonsmokers (P < 0.001; t test). Symbols for genotype are as follows: nonsmokers: diamonds for C/C (n = 1), filled circles for C/A (n = 15), open circles for A/A (n = 10); smokers: filled triangles for C/A (n = 9), open triangles for A/A (n = 7). (b3) Mean CYP1A2 CMR estimates (±S.E.) at EFP, LFP, and LP in group 1 (n = 21). Neither genotype nor smoking exhibited any significant interaction with sampling phase; straight lines, nonsmokers (n = 15); dashed lines, smokers (n = 6).

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    Fig. 5.

    CYP2A6, XO, and NAT2 in vivo indices during menstrual cycle. Individual data (A) and mean estimates (±S.E.) (B) of CMRs measured in the three groups of volunteers (group 1, n = 21; group 2, n = 15; group 3, n = 6) at EFP, LFP, and LP. *CYP2A6 CMR at LFP is significantly higher compared with EFP (P = 0.002) and LP (P = 0.009) (one-way repeated-measures ANOVA). Similarly, NAT2 CMR (slow acetylators) at LFP is significantly higher compared with EFP (P = 0.002) and LP (P = 0.002) (one-way repeated-measures ANOVA).

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    TABLE 1

    Demographic characteristics and biochemical data of the participants (n = 42; nonsmokers, n = 26; smokers, n = 16)

    VariableAllNonsmokersSmokersReference value
    MedianRangeMedianRangeMedianRange
    Age (years)30.518–453018–453218–44
    Weight (kg)6346–956246–956353–90
    Body mass index (kg/m2)22.417.5–40.621.917.5–40.622.818.6–33.9
    Duration of menstrual cycle (days)3027–332827–302828–35
    Sampling days
     EFP32–432–432–4
     LFP1110–121110–121110–12
     LP2219–252219–252220–24
    Aspartate aminotransferase (IU/l)15.09.0–32.015.010.0–24.018.09.0–32.05.0–32.0
    Alanine aminotransferase (IU/l)11.07.0–40.011.07.0–18.011.57.0–28.05.0–41.0
    Alkaline phosphatase (IU/l)57.539.0–84.055.035.0–84.063.540.0–78.040.0–129.0
    γ-Glutamyl transpeptidase (IU/l)11.07.0–23.09.07.0–19.012.58.0–23.05.0–39.0
    Serum creatinine (mg/dl)0.700.49–0.970.700.56–0.970.680.49–0.870.50–0.90
    Serum urea (mg/dl)22.014.0–43.026.014.0–43.021.514.0–27.015.0–50.0
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    TABLE 2

    Primers and PCR conditions used for CYP1A2 genotyping

    Single Nucleotide Polymorphism (SNP)Primer NameSequence 5′→ 3′PCR Program[Mg2+]PCR Product SizeRestriction EnzymeIncubation TemperatureGenotype Patterns
    mMbp°C
    rs2069514 (−3860 G→A)Forward 3, reverse 2 (Fw3Rv2)GCTACACATGATCGAGCTATAC(94°C 10 min) and 35× (94°C 30 s, 56°C 30 s, 72°C 1 min)2.0568BslI55G/G:343-132-93
    CAGGTCTCTTCACTGTAAAGTTAA/A:475-93
    rs762551 (−163 C→A)Forward 1, reverse 1 (Fw1Rv1)TGAGGCTCCTTTCCAGCTCTCA(94°C 10 min) and 35× (94°C 30 s, 60°C 30 s, 72°C 1 min)2.5265PspOMI37C/C:211-54
    AGAAGCTCTGTGGCCGAGAAGGA/A:265
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    TABLE 3

    Serum hormone concentrations and enzyme CMR values in all groups studied

    For each sampling phase, measured values are reported as parameter estimates (mean values ± S.E.) and model results as estimated marginal means with 95% CIs (in parentheses).

    Parameter measurednGroup 1 (n = 21)nGroup 2 (n = 15)nGroup 3 (n = 6)
    EFPLFPLPEFPLFPLPEFPLFPLP
    Estradiol (pg/ml)51.67 ± 4.70248.29 ± 20.10a121.67 ± 11.77b40.60 ± 5.6369.93 ± 7.95148.67 ± 25.96b29.67 ± 10.6649.63 ± 10.8349.67 ± 8.60
    Progesterone (ng/ml)0.55 ± 0.070.69 ± 0.0912.18 ± 1.49b0.60 ± 0.090.81 ± 0.2012.70 ± 1.85b0.50 ± 0.101.13 ± 0.660.98 ± 0.26
    LH (mIU/ml)5.30 ± 0.4017.25 ± 3.76a3.92 ± 0.455.00 ± 0.486.84 ± 0.636.28 ± 1.164.03 ± 0.516.38 ± 0.926.53 ± 1.04
    FSH (mIU/ml)7.71 ± 0.457.64 ± 1.313.17 ± 0.26b7.40 ± 0.676.18 ± 0.613.78 ± 0.39b6.82 ± 1.445.58 ± 0.545.17 ± 0.98
    CYP1A2
     All20c4.53
(3.93–5.13)3.49a
(3.09–3.88)a4.24
(3.80–4.68)154.31
(3.36–5.25)3.77d
(3.16–4.43)d4.35
(3.72–4.97)63.92
(3.03–4.80)4.12
(3.00–5.24)3.51
(2.81–4.22)
     Nonsmokers14c3.02 ± 0.172.61 ± 0.173.08 ± 0.2183.52 ± 0.532.95 ± 0.323.14 ± 0.3433.31 ± 0.333.10 ± 0.553.18 ± 0.32
     CYP1A2*1F C/A72.86 ± 0.262.46 ± 0.142.84 ± 0.1554.05 ± 0.763.23 ± 0.483.33 ± 0.5333.31 ± 0.333.10 ± 0.553.18 ± 0.32
     A/A73.17 ± 0212.76 ± 0.323.31 ± 0.4032.63 ± 0.212.49 ± 0.122.83 ± 0.19
     C/C11.791.921.75
     Smokers65.71 ± 0.834.32 ± 0.355.04 ± 0.5775.18 ± 0.594.90 ± 0.485.79 ± 0.4033.79 ± 0.924.11 ± 1.053.38 ± 0.62
     CYP1A2*1F C/A27.06 ± 2.224.47 ± 0.106.50 ± 0.9955.05 ± 0.845.19 ± 0.636.03 ± 0.5322.91 ± 0.493.06 ± 0.152.78 ± 0.23
     A/A45.04 ± 0.674.24 ± 0.554.31 ± 0.3525.49 ± 0.264.18 ± 0.105.20 ± 0.4515.546.204.59
    CYP2A6
     All210.60 ± 0.0270.70 ± 0.029a0.63 ± 0.028150.62 ± 0.0330.67 ± 0.028e0.56 ± 0.03060.57 ± 0.0470.65 ± 0.0340.68 ± 0.045
    XO
     All210.52 ± 0.0130.52 ± 0.0120.51 ± 0.010150.52 ± 0.0130.54 ± 0.0130.51 ± 0.01460.52 ± 0.0250.52 ± 0.0120.52 ± 0.028
    NAT2
     Slow110.074 ± 0.0070.090 ± 0.006a0.073 ± 0.006110.082 ± 0.0100.081 ± 0.0080.078 ± 0.00850.100 ± 0.0100.094 ± 0.0040.088 ± 0.010
     Fast100.36 ± 0.0160.38 ± 0.0190.36 ± 0.01440.41 ± 0.0310.38 ± 0.0250.37 ± 0.02910.410.370.40
    • ↵a LFP different from EFP (P < 0.01) and LP (P < 0.01).

    • ↵b LP different from EFP and LFP (P < 0.01).

    • ↵c C/C has been excluded from the model.

    • ↵d LFP different from LP (P < 0.01) (but not from EFP, P = 0.056).

    • ↵e LFP different from LP P = 0.027.

Additional Files

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      Supplemental methods and 1 table. 

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Journal of Pharmacology and Experimental Therapeutics: 368 (2)
Journal of Pharmacology and Experimental Therapeutics
Vol. 368, Issue 2
1 Feb 2019
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Research ArticleMetabolism, Transport, and Pharmacogenomics

Altered Xenobiotic Metabolic Enzymes across Menstrual Cycle

E. Asprodini, V. Tsiokou, E. Begas, T. Kilindris, E. Kouvaras, M. Samara and I. Messinis
Journal of Pharmacology and Experimental Therapeutics February 1, 2019, 368 (2) 262-271; DOI: https://doi.org/10.1124/jpet.118.254284

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Research ArticleMetabolism, Transport, and Pharmacogenomics

Altered Xenobiotic Metabolic Enzymes across Menstrual Cycle

E. Asprodini, V. Tsiokou, E. Begas, T. Kilindris, E. Kouvaras, M. Samara and I. Messinis
Journal of Pharmacology and Experimental Therapeutics February 1, 2019, 368 (2) 262-271; DOI: https://doi.org/10.1124/jpet.118.254284
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