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Canadian Journal of Physiology and Pharmacology

Predictive model of -induced toxicity in Japanese patients with pulmonary arterial

Journal: Canadian Journal of Physiology and Pharmacology

Manuscript ID cjpp-2019-0656.R1

Manuscript Type: Article

Date Submitted by the 24-Mar-2020 Author:

Complete List of Authors: Yorifuji, Kennosuke; Shinko Hospital Uemura, Yuko; Shinko Hospital Horibata, Shinji; Shinko Hospital Tsuji, Goh; Shinko Hospital Suzuki, Yoko;Draft Kobe Pharmaceutical University, Clinical Pharmaceutical Science Nakayama, Kazuhiko; Shinko Hospital Hatae, Takashi; Kobe Pharmaceutical University Kumagai, Shunichi; Shinko Hospital EMOTO, Noriaki; Kobe Pharmaceutical University, Clinical Pharmaceutical Science; Kobe University Graduate School of Medicine School of Medicine, Division of Cardiovascular Medicine

Is the invited manuscript for consideration in a Special ET-16 Kobe 2019 Issue:

bosentan, pulmonary arterial hypertension, pharmacogenetics, CHST3, Keyword: CHST13

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Predictive model of bosentan-induced liver toxicity in Japanese patients with pulmonary arterial hypertension

Kennosuke Yorifuji, M.Pharm.1, 2, 3; Yuko Uemura2; Shinji Horibata, M.Pharm.2, 3; Goh Tsuji, M.D., PhD.2, 4; Yoko Suzuki, M.Pharm.1, 5; Kazuhiko Nakayama, M.D., PhD.6; Takashi Hatae, PhD.7; Shunichi Kumagai, M.D., PhD.2, 4; Noriaki Emoto, M.D., PhD.1, 5

1Laboratory of Clinical Pharmaceutical Science, 7 Education and Research Center for Clinical Pharmacy, Kobe Pharmaceutical University, 4-19-1 Motoyama-kitamachi, Higashinada, Kobe 658-8558, Japan

2The Shinko Institute for Medical Research, 3Department of Pharmacy, and 4Center for Rheumatic Diseases, 6Depertment ofDraft Cardiovascular Medicine Shinko Hospital, 1-4-47, Wakinohama, Chuo, Kobe 651-0072, Japan

5Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe Graduate School of Medicine, 7-5-1 Kusunoki, Chuo, Kobe 650-0017, Japan

*To whom correspondence should be addressed: Noriaki Emoto, MD, PhD. Laboratory of Clinical Pharmaceutical Science, Kobe Pharmaceutical University 4-19-1, Motoyama-kitamachi, Higashinada, 658-8558 Kobe, Japan Tel. and Fax: +81-78-441-7536 E-mail: [email protected]

Keywords: Bosentan, Pulmonary arterial hypertension, Pharmacogenomics, CHST3,

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CHST13 Abstract Bosentan, an endothelin antagonist, has been widely used as a first-line medication for the treatment of pulmonary arterial hypertension (PAH). It has been shown to improve symptoms of hypertension, exercise capacity, and hemodynamics and prolong time to clinical worsening. However, liver dysfunction is a major side effect of bosentan treatment that could hamper the optimal management of patients with PAH. Previously, we demonstrated, using and transporters (DMET) analysis, that the carbohydrate sulfotransferase 3 (CHST3) and CHST13 alleles are significantly more frequent in patients with elevated amino-transferases during therapy with bosentan than they are in patients without liver toxicity. In addition, we constructed a pharmacogenomics model to predict bosentan-induced liver injury in patients with PAH using two single nucleotide polymorphisms (SNPs) and two non-genetic factors. The purpose of the present study was to Draftexternally validate the predictive model of bosentan- induced liver toxicity in Japanese patients. We evaluated five cases of patients treated with bosentan, and one presented with liver dysfunction. We applied mutation alleles of CHST3 and CHST13, serum creatinine, and age to our model to predict liver dysfunction. The sensitivity and specificity were calculated as 100% and 50%, respectively. Considering that PAH is a rare disease, multicenter collaboration would be necessary to validate our model.

Keywords: Bosentan, Pulmonary arterial hypertension, Pharmacogenomics, CHST3, CHST13

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Introduction Pulmonary arterial hypertension (PAH) is a rare disease with a high mortality rate (Galie N et al. 2016). Treatment options have improved in the last two decades including prostanoids, phosphodiesterase-5 (PDE-5) inhibitors, a soluble guanylate cyclase stimulator, and endothelin receptor antagonists (ERAs). Accordingly, the prognosis of PAH has improved dramatically. However, patients still die prematurely of right failure if left untreated or are inappropriately treated (Lau EMT et al. 2017). Currently, there are three ERAs available on the market for the treatment of PAH, bosentan, , and macitentan. Bosentan and macitentan are dual ERAs with

similar affinity for the endothelin A (ETA) and ETB receptors whereas ambrisentan has a

higher selectivity for the ETA receptor than for the ETB receptor (Vignon-Zellweger N et al. 2012). Bosentan is the first ERA approved for the clinical treatment of PAH, and it has been shown to improve clinical symptoms, exercise tolerance, and hemodynamic parameters and delay clinical progressionDraft of PAH (Miyagawa K and Emoto N. 2014). Furthermore, bosentan is approved for secondary prevention in patients with digital skin ulcers related to systemic sclerosis. Liver toxicity is the main adverse effect of bosentan, which is also associated with reversible, dose-dependent, and in most cases asymptomatic increase in aminotransferases. The reported annual rate of liver toxicity induced by bosentan was approximately 10% (Humbert M et al. 2007). The liver enzymes are elevated in the first six months of bosentan treatment but could also occur later on. Therefore, liver function monitoring is recommended monthly in patients receiving bosentan. Previously, we demonstrated that the carbohydrate sulfotransferase 3 (CHST3) and CHST13 alleles are significantly more frequent in patients with elevated amino- transferases during therapy with bosentan than they are in patients without liver toxicity using drug metabolism enzymes and transporters (DMET) analysis(Yorifuji K et al. 2018). Furthermore, we constructed a pharmacogenomics model to predict bosentan- induced liver injury in patients with PAH using two single nucleotide polymorphisms (SNPs) and two non-genetic factors (Yorifuji K et al. 2018). However, we cannot rule out the possibility that the results may be derived from random associations that occur to show the statistical significance. Thus, the implication of our model needs to be validated in an independent sample set. The primary aim of this study was to externally validate the predictive model of liver toxicity induced by bosentan treatment of Japanese patients.

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Methods 1. Patients We evaluated four patients with PAH and one with digital ulcer treated with bosentan in August 2016 at Shinko Hospital. The study protocols were approved by the Institutional Review Board of Shinko Hospital (number 1615). All patients provided written informed consent prior to participating in the study.

2. Blood sampling and processing for genotype analysis For the five enrolled patients, stored whole blood samples were archived and subjected to DNA extraction. Genomic DNA was isolated using the QuickGene DNA whole blood kit S (Kurabo Industries, Osaka, Japan) according to the manufacturer’s recommendations. The primer designDraft was based on published sequences of CHST3 and CHST13 to avoid the amplification of sequences from homologous genes. Genotyping was performed using the StepOnePlus real-time polymerase chain reaction (PCR) system (Applied Biosystems, USA, Ltd.). PCR was carried out in a total reaction volume of 10 µL with 20 ng DNA, 5 µL TaqMan® GTXpress™ master mix (Applied Biosystems Ltd.), a TaqMan genotyping assay mix customized for studying SNP (rs4148953) and (rs6783962), and 25 µL water. The default thermal cycling conditions (20 s at 95°C followed by 40 cycles for 3 s at 95°C plus 20 s at 60°C) were used.

3. Risk evaluation of bosentan-induced liver injury We evaluated the risk of bosentan-induced liver injury using our predictive model as previously described. The SNP information of patients was evaluated using genotype analysis. The probability was calculated by substituting w/w = 0, w/m = 1, and m/m = 2. A total P > 0.4942 was considered a high-risk group.

4. Statistical analysis For test power analysis, we used the free software G*power (G*Power 3.1.9.2) (Faul F et al. 2007).

Results

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1. Patient characteristics Table 1 shows the baseline characteristics of the five patients and the dosage of bosentan was 250 mg twice daily after a 4-week titration period (62.5 mg twice daily) in all cases. The underlining cause of PAH included systemic sclerosis (patients 1, 3, and 5), mixed connective tissue disease (patient 2), and congenital heart disease (patient 4). Patient 5 showed elevated transaminase levels 3 weeks after bosentan initiation. The aspartate transaminase (AST) and alanine transaminase (ALT) value were 2.74 × upper limit normal (ULN) and 1.94 × ULN, respectively. Treatment with ursodeoxycholic acid normalized the transaminase levels in 2 weeks without changing the bosentan dosage. Other patients did not show elevated aminotransferases for up to 1 year from bosentan initiation. Co-administered drugs and their dosages are listed in Table 2.

2. Genotype The results of genotype analysis ofDraft CHST3 (rs4148953) and CHST13 (rs6783962) are shown in Table 3 and the mutation allele frequency was 0.1000 and 0.3333 for CHST3 (rs4148953) and CHST13 (rs6783962), respectively. These values are in consistent with those obtained from National Center for Biotechnology Information (NCBI).

3. Predictive model score To validate our predictive model for bosentan-induced liver toxicity, we used mutation alleles of CHST3 (rs4148953) and CHST13 (rs6783962), serum creatinine, and age in our model. Total score and risk prediction are shown in Table 4. Two out of five patients (patient 1 and 4) were determined to be a low-risk group, and three (patients 2, 3, and 5) were determined to be a high-risk group. Four of the five patients (patients 1-4) did not show liver dysfunction for more than 1 year from the initiation of bosentan. In patient 5, elevation of transaminases was observed two days after bosentan induction. As a result, sensitivity and specificity were calculated to be 100% and 50%, respectively, in the investigation of five people. Positive predictive value and negative predictive value were calculated to be 33% and 100%, respectively.

Discussion

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In the present study, we validated the predictive model of bosentan-induced liver toxicity in treated Japanese patients. Two patients (1 and 4) were determined to be a low-risk group, and three (patients 2, 3, and 5) were determined as a high-risk group. Among the high-risk patients, one case presented with liver dysfunction while two did not. Thus, sensitivity and specificity were calculated to be 100% and 50%, respectively, in the present investigation of five cases. Obviously, the sample size used in the present study was too small to validate our proposed predict model. Based on the calculation of Cramer's coefficient of association using the chi-square test with our previous report data, at least 18 cases should be investigated to validate our predictive model (Faul F et al. 2007). The analysis of 18 cases would be expected to identify 2 cases of bosentan-induced liver injury. Thus, we would have to increase the sample number to validate our model. However, since PAH is a rare disease, a single center can only collect a limited number of samples. Therefore, multicenter collaboration would beDraft necessary to effectively investigate rare diseases including PAH. In the present study, two patients (2 and 3) did not present with liver dysfunction although our model predicted them as high-risk. Therefore, we considered that this result may have arisen from the interaction of co-administered drugs in these cases. Bosentan is transported to the liver by uptake transporters including organic anion transporting polypeptide 1B1 (OATP1B1) and OATP1B3 (Treiber A et al.2007). Bosentan is then metabolized by cytochrome P450 (CYP) 2C9 (CYP2C9) and CYP3A4 (Dingemanse J and van Giersbergen PL. 2004). Therefore, co-administration of a CYP2C9 or CYP3A4 inducer with bosentan would likely substantially decrease the plasma concentration of bosentan, which may mask the bosentan-induced liver injury. However, this appears not to be the case in this study because no medications with the propensity to decrease bosentan concentrations including or St. John’s wort were co-administered to patient 2 and 3. Nevertheless, we cannot rule out the possibility that a currently unknown drug-drug interaction may have affected the systemic concentration or liver exposure of bosentan. Recently, studies using a physiologically based pharmacokinetic (PBPK) model for bosentan incorporating its various PK properties have been reported (Li R et al. 2018; Yoshikado T et al. 2017). To accurately and precisely predict bosentan-induced liver injury, drug-drug interactions evaluated using defined PBPK models should be

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considered in addition to pharmacogenomic findings.

Acknowledgements This study was supported in part by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Numbers 26460213 (NE) and 16H00507 (KY).

Conflicts of Interest Shunichi Kumagai has been an adviser for Sysmex Corporation. The remaining authors have no conflicts of interest to be declared regarding the present study.

References Dingemanse J, van Giersbergen PL.: Clinical pharmacology of bosentan, a dual endothelin receptor antagonist. ClinDraft Pharmacokinet., 43(15), 1089-115, 2004.

Faul F, Erdfelder E, Lang AG, Buchner A.: G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods., 39(2), 175-191 2007.

Galie N, Humbert M, Vachiery JL, Gibbs S, Lang I, Torbicki A et al.: 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT). Eur Heart J., 37(1), 67-119, 2016.

Humbert M, Segal ES, Kiely DG, Carlsen J, Schwierin B, Hoeper MM.: Results of European post-marketing surveillance of bosentan in pulmonary hypertension. Eur Respir J., 30(2), 338-344, 2007.

Lau EMT, Giannoulatou E, Celermajer DS, Humbert M.: Epidemiology and treatment of pulmonary arterial hypertension. Nat Rev Cardiol., 14, 603-614, 2017.

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Li R, Niosi M, Johnson N, Tess DA, Kimoto E, Lin J et al.: A Study on of Bosentan with Systems Modeling, Part 1: Translating Systemic Plasma Concentration to Liver Exposure in Healthy Subjects. Drug Metab Dispos. , 46(4), 346-356, 2018.

Miyagawa K, Emoto N.: Current state of endothelin receptor antagonism in hypertension and pulmonary hypertension. Ther Adv Cardiovasc Dis. 8(5), 202-216, 2014.

Treiber A, Schneiter R, Hausler S, Stieger B.: Bosentan is a substrate of human OATP1B1 and OATP1B3: inhibition of hepatic uptake as the common mechanism of its interactions with cyclosporin A, rifampicin, and sildenafil. Drug Metab Dispos. , 35(8), 1400-1407, 2007. Draft

Vignon-Zellweger N, Heiden S, Miyauchi T, Emoto N.: Endothelin and endothelin receptors in the renal and cardiovascular systems. Life Sci. 91(13-14), 490-500, 2012.

Yorifuji K, Uemura Y, Horibata S, Tsuji G, Suzuki Y, Miyagawa K et al.: CHST3 and CHST13 polymorphisms as predictors of bosentan-induced liver toxicity in Japanese patients with pulmonary arterial hypertension. Pharmacol Res., 135, 259-264, 2018.

Yorifuji K, Uemura Y, Horibata S, Tsuji G, Suzuki Y, Miyagawa K et al.: Corrigendum to "CHST3 and CHST13 polymorphisms as predictors of bosentan-induced liver toxicity in Japanese patients with pulmonary arterial hypertension" [Pharmacol. Res. 135 (2018) 259-264]. Pharmacol Res. in press 2018

Yoshikado T, Maeda K, Kusuhara H, Furihata KI, Sugiyama Y.: Quantitative Analyses of the Influence of Parameters Governing Rate-Determining Process of Hepatic Elimination of Drugs on the Magnitudes of Drug-Drug Interactions via Hepatic OATPs and CYP3A Using Physiologically Based Pharmacokinetic Models. J Pharm Sci., 106(9), 2739-2750, 2017.

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Table 1. Patient characteristics

Patient characteristic Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Age (years) 35.0 76.1 76.4 81.8 65.6 Male/female patients M F F F F Body surface area (m2) 1.99 1.81 1.30 1.29 1.51 AST (IU/L) 16 15 17 30 17 ALT (IU/L) 17 14 12 22 15 BUN (mg/dl) 11.8 14.6 10 31.4 14.5 Serum creatinine (mg/dL) 0.56 0.72 0.63 1.0 0.66 eGFR (mL·min-1·1.73 m(2)-1) 131.9 59.3 68.6 40.6 68.2 BNP (pg/mL) 46.2 Draft92.9 186 571 81.2 CI (L·min-1·m(2)-1) 5.68 2.27 2.21 4.33 PVR (dyne*s/cm5) 176 251 325 mPAP (mmHg) 24 22 18 35 33 diagnosis SSC MCTD, PAH SSC, digital ulcer ASD, PAH SSC, PAH, PVOD Bosentan dosage (mg/day) 250 250 250 250 250

AST: aspartate aminotransferase, ALT: alanine aminotransferase, BUN: blood urea nitrogen, eGFR: estimate glomerular filtration rate, BNP: brain , CI: cardiac index, PVR: pulmonary vascular resistance, mPAP: mean pulmonary arterial pressure, Bosentan dosage: bosentan dosage at the point of one year from bosentan induction, SSC: systemic sclerosis, MCTD: mixed connective tissue disease, ASD: atrial septal defect, PAH: pulmonary arterial hypertension, PVOD: pulmonary veno-occlusive disease

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Table 2. Used drug and dosage at the induction of bosentan

Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Drug name Dosage Drug name Dosage Drug name Dosage Drug name Dosage Drug name Dosage /Day /Day /Day /Day /Day Sildenafil Citrate 60 mg Lansoprazole 15 mg Beraprost 120 µg Beraprost 20 µg Beraprost 60 µg Trimebutine 300 mg Furosemide 20 mg Bazedoxifene 20 mg Tadalafil 10 mg Maleate Acetate Levothyroxine 50 µg 25 mg Ranitidine 150 mg Warfarin 3 mg Sodium Hydrate Hydrochloride Potassium Eldecalcitol 0.75 µg RabeprazoleDraft 10 mg Celiprolol 100 mg Lansoprazole 15 mg Sodium Hydrochloride Benidipine 4 mg 2.5 mg Nitrendipine 10 mg Furosemide 20 mg Hydrochloride Prednisolone 15 mg Dried Ferrous 105 mg Aspirin, 81 mg Spironolactone 25 mg Sulfate Aluminum Glycinate Rabeprazole 20 mg Acetaminophen 1600 Ifenprodil 300 mg Sodium mg Tartrate Oxide 1500 mg Alfacalcidol 0.5 µg Sarpogrelate 300 mg Hydrochloride Mosapride Citrate 15 mg

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Hydrate Metoclopramide 15 mg Alendronate 35 mg Sodium Hydrate (once weekly)

Draft

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Table 3. Genotype identification

Patient characteristic Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Mutation Mutation allele allele frequency frequency in this referred by study database* CHST3 (rs4148953) G/G A/G G/G G/G G/G 0.1000 0.1106 CHST13 (rs6783962) G/T G/T T/T G/T T/T 0.3333 0.3173 * National Center for Biotechnology Information (NCBI) Draft

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Table 4. Score of the predictive model

Patient characteristic Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 CHST3 (rs4148953) 0 1 0 0 0 CHST13 (rs6783962) 1 1 0 1 0 Serum creatinine (mg/dL) 0.56 0.72 0.63 1.0 0.66 Age (years) 35.0 76.1 76.4 81.8 65.6 Total score 0.01099 0.7006 0.8768 0.2184 0.6800 Risk prediction Low-risk High-risk High-risk Low-risk High-risk Draft

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