EPB41L4A and LEP gene polymorphisms are associated with antipsychotic-induced QTc interval prolongation in Han Chinese

Psychiatry Research 286 (2020) 112851

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EPB41L4A and LEP gene polymorphisms are associated with antipsychoticinduced QTc interval prolongation in Han Chinese

T

Haiyan Caoa,#, Shen Lia,b,#, Ying Gaoa, Yanyan Maa, Lili Wanga, Bing Chena, Rui Jianga, ⁎ ⁎ Yuan Zhangc, Weidong Lic, , Jie Lia, a

Institute of Mental Health, Tianjin Anding Hospital, Tianjin Medical University, 13 Liulin Rd., Hexi District, Tianjin, 300222, China Department of Psychiatry, College of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China c Department of Genetics, College of Basic Medical Sciences, Tianjin Medical University, 22 Qixiangtai Rd., Heping District, Tianjin, 300070, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: QTc interval prolongation Atypical antipsychotics Schizophrenia Single nucleotide polymorphisms

To identify the genetic factors related to antipsychotic-induced QTc interval prolongation (AIQTIP), we analyzed the associations between single nucleotide polymorphisms (SNPs) of candidate genes and quantitative traits of AIQTIP in a Han Chinese population. In total, we collected 112 hospitalized patients suffered from schizophrenia meeting the entry criteria, including 34 first-episode drug-naïve patients (FENP). All patients were treated with a single atypical antipsychotic drug (AAPD) for 4 weeks. We analyzed the quantitative genetic association between 10 SNPs in 8 candidate genes and AIQTIP using PLINK software. After 4 weeks of treatment, QTc interval of all patients was significantly prolonged and QTc interval of female patients was significantly longer compared with baseline. Antipsychotics have different effects on the prolongation of QTc. Quetiapine had the most distinct effect on AIQTIP. In all subjects, we found a significant association between the EPB41L4A gene SNP rs7732687 and AIQTIP. In male patients, we also found a significant association between the EPB41L4A gene SNP rs7732687 and AIQTIP. In female patients, we found the LEP gene SNP rs7799039 was significantly associated with AIQTIP. Our results provide preliminary evidence to support the genetic role of EPB41L4A and LEP in AIQTIP.

1. Introduction Schizophrenia is a chronic and serious psychiatric disorder, and the life expectancy of patients with schizophrenia is 15 years shorter than that of the general population (Hjorthoj et al., 2017). Compared with the general population, the overall mortality rate of patients with schizophrenia is higher, and the risk of death from cardiovascular disease is especially increased (Druss, 2018). This may be related to metabolic changes caused by increased risks of obesity, weight gain, dyslipidemia and type 2 diabetes of patients with schizophrenia, some of which may be relevant to antipsychotic drugs (Li et al., 2018; Polcwiartek et al., 2016). It is well known that antipsychotics could induce QT interval prolongation (Beach et al., 2013), and antipsychoticinduced QT interval prolongation (AIQTIP) is associated with an increased risk of arrhythmias. QT interval prolongation is a high risk for ventricular tachycardia or torsade de pointes (TDP), if it not be managed immediately, which can eventually deteriorate into fatal ventricular fibrillation or even sudden cardiac death (SCD) (Antoniou et al.,

2017; Nielsen et al., 2011). QT interval measured on the electrocardiogram (ECG) represents ventricular depolarization and repolarization. Because the heart rate affects the duration of the QT interval, the formula of Bazett (QTc = QT/RR0.5) is usually used to correct the QT interval for heart rate (Luo et al., 2004). Normally, for adult men the average heart ratecorrected QT interval (QTc) is approximately 410–430 ms, and for adult women 420–430 ms. A prolonged QTc is usually defined as>450 ms for men and>470 ms for women (Rijnbeek et al., 2014). QTc interval above 500 ms is associated with a twofold to threefold increase in the risk of TDP (Cohagan and Brandis, 2019). Therefore, this threshold has been advised for drug discontinuation for both men and women (Becker et al., 1998). QTc interval prolongation can be divided into congenital and acquired. The congenital QTc interval prolongation is caused by Mendelian genetic disorders, known as long QTc syndromes (Niemeijer et al., 2015). Acquired QTc interval prolongation is related to many factors, such as age, gender, electrolyte disturbance,

⁎

Corresponding authors. E-mail addresses: [email protected] (W. Li), [email protected] (J. Li). # Haiyan Cao, Shen Li contributed equally to this work. https://doi.org/10.1016/j.psychres.2020.112851 Received 2 November 2019; Received in revised form 21 January 2020; Accepted 4 February 2020 Available online 05 February 2020 0165-1781/ © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).

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first-episode drug-naïve patients (FENP). All the patients were unrelated Han Chinese hospitalized in the Tianjin Mental Health Center. The entry criteria for this study were as follows:(1) The patients were independently diagnosed with schizophrenia according to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-Ⅳ) by two psychiatrists. (2) The patients were 18–60 years old, regardless of gender. (3) The patients were FENP or have not taken any antipsychotic drugs for at least 4 weeks before enrollment. (4) The subjects were physically healthy, hematological and biochemical parameters were normal, and the ECGs were normal. Exclusion criteria consisted of a gender-specific QTc prolongation (male > 450 ms, female > 470 ms), a history of QTc prolongation, a recent myocardial infarction, a history of sustained cardiac arrhythmia, uncompensated congestive heart failure, and other ECG abnormalities. Furthermore, subjects with substance abuse, significant medical abnormalities (uncontrolled hypertension, cerebrovascular diseases, pulmonary diseases, thyroid diseases, diabetes, epilepsy, unstable somatic conditions, etc.), pregnancy and lactation were excluded from the study. All patients gave written informed consent prior to this research. This study followed the basic principles of the Helsinki Declaration. The study was approved by the Human Ethics Committee of Tianjin Anding Hospital. All patients received a single atypical antipsychotic drug (AAPD) treatment according to clinical treatment needs, allowing symptomatic treatment with corresponding drugs due to physical diseases. The main antipsychotic drugs in present research were olanzapine, risperidone, clozapine, quetiapine, aripiprazole and palipiperone. The choice of therapeutic drugs should be based on the patient's compliance with drugs, curative effect, tolerance, long-term treatment plan, previous treatment experience, age, gender and economic status, etc. Adverse reactions of different kinds of antipsychotic drugs are quite different, and whether individuals are willing to tolerate adverse reactions is also different. After comprehensive consideration of the above factors, the competent psychiatrists choose drugs suitable for patients. In the course of treatment, if the patient's treatment response is not satisfactory, we will also switch to other drugs. These patients will be excluded because of that, their treatment did not conform to single atypical antipsychotic treatment. The dosage of antipsychotic drugs is given flexibly according to the patient's condition, and is appropriately adjusted based on the patient's own conditions such as drug reaction and drug tolerance. The choice and dosage of drugs are determined by the competent psychiatrists according to the needs of each patient's condition. At the same time, we give corresponding medication according to the patient's symptoms. For patients with sleep disorders, sedative and hypnotic drugs such as zolpidem and zopiclone are allowed to be taken for treatment; for patients with anxiety, lorazepam and other drugs are allowed for treatment; for patients with extrapyramidal side effects, benazepine is allowed for symptomatic treatment. The treatment was observed for 4 weeks. All patients were recorded with age, course of disease, family history of mental diseases, antipsychotic drugs taken before. All patients were measured for height, body weight, systolic blood pressure, diastolic blood pressure, triglyceride (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), total cholesterol (CHOL), urea, creatinine, fasting blood glucose (FPG). The electrocardiograph used in this research is CM100, which is manufactured by China Shenzhen COMEN Medical Equipment Co., Ltd. The standardized resting ECG examination was performed at baseline and 4 weeks after treatment, heart rate was recorded, and QT interval was measured. The ECG was visually evaluated for recording errors. QTc was automatically calculated according to Bazett formula (QTc = QT/RR 0.5). QTc was calculated before treatment and 4 weeks after treatment.

bradycardia, coronary heart disease, heart failure, drug and genetic susceptibility, etc (Drew et al., 2010). Female is a well known risk factor (Khan et al., 2019). The susceptibility of acquired QTc interval prolongation to pharmacological therapy can be affected by genetic variation (Strauss et al., 2017). About 30–40% of QTc interval variation is heritable (Hong et al., 2001). Acquired QTc interval prolongation is mainly caused by drugs. A series of drugs can lead to QTc interval prolongation, including cardiac drugs, typical and atypical antipsychotics, antidepressants, antibiotics, etc (Roden, 2016). AIQTIP has long been recognized (Takeuchi et al., 2015). In recent years, the prolongation of QTc interval has become a problem that we must pay more attention to when prescribing psychotropic drugs (Nielsen et al., 2011). QTc interval prolongation is one of the main reasons for drugs to withdraw from the market, although they may be beneficial to some patients but not harmful to all patients (Niemeijer et al., 2015). Identifying the genetic factors related to AIQTIP may reduce the risk of AIQTIP, and avoid unnecessary withdrawal of some effective drugs from the market. With the development of pharmacogenetics, a number of genes related to QTc interval prolongation induced by antipsychotics have been identified. Most of these studies are based on candidate gene approach, such as KCNH2 (Atalar et al., 2010; Corponi et al., 2019), CACNA1C (Fabbri et al., 2017), NOS1AP (Corponi et al., 2019), KCNE1 (Weeke et al., 2014), NDRG4 (Watanabe et al., 2017), PLN (Watanabe et al., 2017), ABCB1 (Corponi et al., 2019; Suzuki et al., 2014), ACN9 (Weeke et al., 2014). Among these genes, NOS1AP (Corponi et al., 2019), KCNH2 (Atalar et al., 2010; Corponi et al., 2019), ABCB1 (Corponi et al., 2019; Suzuki et al., 2014) are frequently replicated for variations. Up to now, there are two genome-wide association studies (GWAS) of AIQTP, which found associations on SLC22A23 (Aberg et al., 2012), CERKL, SLCO3A1, BRUNOL4, NRG3, NUBPL and PALLD genes polymorphisms (Volpi et al., 2009). As the GWAS study requires a very large sample size to obtain sufficient power, candidate gene approach enabled us to use increased statistical power to perform association study for prioritized genes. Up to now it is still unclear whether specific genetic polymorphisms mediate AIQTIP. These studies that identified genes associated with AIQTIP are mostly of Caucasians, and many results are inconsistent (Fabbri et al., 2017; Spellmann et al., 2018). There are few studies on Asian population, up to now, there is only one study on 66 Japanese patients with schizophrenia (Suzuki et al., 2014), and there is no study on Chinese population. And this kind of research mainly focuses on genes related to cardiac ion channels (Atalar et al., 2010; Corponi et al., 2019; Fabbri et al., 2017; Weeke et al., 2014), cardiac signal conduction (Corponi et al., 2019), cardiac relaxation and contraction (Watanabe et al., 2017) and enzymes involved in pharmacokinetics of drugs (Llerena et al., 2004). As cardiovascular disease is the leading cause of death for schizophrenia patients (Druss, 2018), which is closely associated with metabolic changes of schizophrenia patients (Polcwiartek et al., 2016), at present, there is no research to explore the relationship between AIQTIP and metabolism-related genes. This study is the first to explore changes in QTc intervals in Chinese patients with schizophrenia after receiving single atypical antipsychotics, and this study is also the first to study the genes related to AIQTIP in Chinese patients suffered from schizophrenia. In this study, our objective is to identify the metabolism-related genes associated with AIQTIP in Chinese patients suffered from schizophrenia by analyzing quantitative associations between single nucleotide polymorphisms (SNPs) of candidate genes and AIQTIP. 2. Materials and methods 2.1. Subjects and design In this study, we collected a total of 280 patients suffered from schizophrenia and 112 cases met the inclusion criteria, including 34 2

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Table 1 Candidate genes and SNPs genotyped in this study. MAF(CHB)*, minor allele frequencies, taken from dbSNP; CHB, Han Chinese. Chromosome

SNP-ID

Base-pair position

Gene

HWE(P)

MAF(CHB)*

Location

1 5 7 11 14 16 16 18 18 22

rs1137101 rs7732687 rs7799039 rs6265 rs7141420 rs9939609 rs1558902 rs6567160 rs489693 rs4680

66058513 111571642 127878783 27679916 79899454 53820527 53803574 57829135 57882787 19951271

LEPR EPB41L4A LEP BDNF NRXN3 FTO FTO MC4R MC4R COMT

0.321 0.935 0.865 0.930 0.829 0.517 0.246 0.271 0.057 0.444

0.11(A) 0.47(C) 0.23(G) 0.37(G) 0.36(T) 0.12(T) 0.12(A) 0.14(C) 0.19(A) 0.31(A)

Intron Intron Intergenic Unknown Intron Intron Intron Intergenic Intergenic Intragenic

schizophrenia, and 112 cases met the inclusion criteria, including 34 FENP. The data of 112 patients (40 males and 72 females), mean age 37.65 (SD 10.85) years, average age of onset 30.05 (SD 10.91) years were analyzed in the study. All patients were the Han population. The average QTc interval at baseline was 420.66 ± 17.59 ms. None of the patients enrolled in this study had a gender-specific abnormal QTc interval (male > 450 ms, female > 470 ms) before treatment. Thus, 48 patients were treated with olanzapine, 36 with risperidone, 5 with clozapine, 11 with quetiapine, 5 with aripiprazole and 7 with palipiperone. The clinical characteristics of subjects were shown in Table 2.

2.2. Genotyping and SNP selection Peripheral venous blood was extracted with 5 ml EDTA anticoagulant tube, plasma was stored in refrigerator at 4°C, and genomic DNA was extracted within one week. All samples in this study were deposited and processed in the Molecular and Genetics Center of the Tianjin Medical University. Gene detection was carried out through primer extension of multiple products and matrix-assisted laser desorption time-of-flight mass spectrometry. 10% of the samples were randomly resequenced for quality control and 100% were consistent. All genotyping was performed without knowing the clinical data of the subjects. Based on literature and our previous studies, 10 SNPs in 8 candidate genes closely related to metabolism were selected, respectively: rs1137101(LEPR), rs7732687(EPB41L4A), rs7799039(LEP), rs6265(BDNF), rs7141420(NRXN3), rs9939609(FTO), rs1558902(FTO), rs6567160(MC4R), rs489693(MC4R), and rs4680(COMT) (Table 1).

3.2. Changes of QTc interval after 4 weeks of treatment Compared with the baseline, the QTc interval was generally prolonged after 4 weeks of treatment, and the difference was statistically significant (t = 2.748, P = 0.07). After 4 weeks of treatment, the QTc interval of female patients was longer than that of the baseline, and the difference was statistically significant (t = 2.460, P = 0.016). For male patients, the QTc interval was also prolonged after 4 weeks of treatment, but there was no statistical significance compared with the baseline (t = 1.494, P = 0.143). There was no significant difference in the prolongation of QTc interval between male and female patients before and after treatment (t = 0.334, P = 0.739). Comparisons of QTc interval at baseline and at week 4 were shown in Table 3 .

2.3. Statistical analysis SPSS 23.0 was used to perform statistical analysis. The counting data were expressed as percentages, and the descriptive data were expressed as means and standard deviations (x ± s). All the demographic data, ECG indexes, hematological indicators and the QTc intervals showed normal distribution in patients (Kolmogorov–Smirnov test for one-sample, all P > 0.05). The comparisons of demographic data, ECG indexes, hematological indicators and QTc intervals of the whole sample before and after treatment were analyzed by using paired t test for continuous variables. The comparisons of QTc intervals of male and female patients before and after treatment were respectively analyzed by paired t test for continuous variables. The changes of QTc interval between male and female patients before and after treatment were compared by using independent samples t-tests for continuous variables. Paired t tests were respectively calculated for each medication to compare the QTc interval at baseline and after 4 weeks of treatment. We compared QTc interval changes before and after treatment for three genotypes or different subgroups by using one-way analysis of variance. The association between the selected SNPs and several phenotypes was analyzed by using linear regression model in PLINK, where the changes of QTc were used as phenotypes for the quantitative trait locus analysis. We used PLINK to perform pairwise gene-gene interaction analysis (epistasis) among selected gene SNPs in all patients, male patients and female patients. All P values were 2 tailed, and the significant level was 0.05.

3.3. Changes of QTc interval after different antipsychotic drugs treatment Antipsychotics showed different effects on the prolongation of QTc. Quetiapine had the most distinct effect on QTc interval prolongation, followed by olanzapine and risperidone. After 4 weeks of treatment, the QTc interval of aripiprazole and clozapine group was shorter than that Table 2 Clinical characteristics of subjects. Characteristic Gender Male Female Age (years) Age of onset(years) First-episode patients (FEPs) systolic blood pressure(mmHg) diastolic blood pressure(mmHg) Medication Olanzapine Risperidone Clozapine Quetiapine Aripiprazole Palipiperone

3. Results 3.1. Sample and baseline characteristics In total, we collected 280 hospitalized patients suffered from 3

N (%)/Mean ± SD

40(35.71) 72(64.29) 37.65 ± 10.85 30.05 ± 10.91 34(30.36) 122.46 ± 13.87 77.75 ± 8.00 48(42.86) 36(32.14) 5(4.46) 11(9.82) 5(4.46) 7(6.25)

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Table 3 Comparison of clinical data before treatment (baseline) and at week 4. Parameter

Baseline

Week 4

t

P

Heart rate PR(ms) QRS(ms) QTc-All subjects(ms) QTc-male(ms) QTc-female(ms) QTc-Olanzapine(ms) QTc-Risperidone(ms) QTc-Clozapine(ms) QTc-Quetiapine(ms) QTc-Aripiprazole(ms) QTc-Palipiperone(ms) Weight(kg) BMI TG(mmol/L) HDL(mmol/L) LDL(mmol/L) CHOL(mmol/L) UREA(mmol/L) CRE(mmol/L) FPG(mmol/L)

78.24 ± 11.43 127.54 ± 50.04 89.17 ± 9.84 420.66 ± 17.59 416.60 ± 17.52 422.92 ± 17.33 422.08 ± 20.37 419.89 ± 13.93 432.20 ± 19.84 414.18 ± 13.98 410.40 ± 15.01 424.14 ± 17.04 64.40 ± 12.23 23.12 ± 3.60 1.12 ± 0.93 1.30 ± 0.27 2.64 ± 0.83 4.49 ± 0.91 3.82 ± 1.47 62.91 ± 14.82 5.05 ± 1.25

81.11 ± 13.61* 132.54 ± 46.96 88.86 ± 8.93 426.80 ± 24.85* 423.75 ± 30.88 428.50 ± 20.82* 429.13 ± 27.05 425.89 ± 24.62 430.80 ± 13.83 429.73 ± 22.46* 404.40 ± 22.26 424.14 ± 18.77 66.71 ± 12.27* 23.96 ± 3.53* 1.60 ± 0.89* 1.26 ± 0.36 2.85 ± 0.77* 4.73 ± 0.95* 4.00 ± 4.63 63.01 ± 12.31 4.48 ± 0.55

−2.086 −0.831 0.601 2.748 1.494 2.460 1.858 1.582 0.164 2.431 1.126 0.000 −9.652 −9.591 −5.496 1.352 −2.848 −2.599 −0.434 −0.442 4.874

0.039 0.408 0.549 0.007 0.143 0.016 0.069 0.123 0.878 0.035 0.323 1.000 0.000 0.000 0.000 0.179 0.005 0.011 0.665 0.659 0.000

Table 4 Quantitative association analysis of candidate genes and QTc changes in phenotype at 4 weeks. SNP All patients rs1137101 rs7732687 rs7799039 rs7141420 rs6265 rs9939609 rs1558902 rs6567160 rs489693 rs4680 Male patients rs1137101 rs7732687 rs7799039 rs7141420 rs6265 rs9939609 rs1558902 rs6567160 rs489693 rs4680 Female patients rs1137101 rs7732687 rs7799039 rs7141420 rs6265 rs9939609 rs1558902 rs6567160 rs489693 rs4680

§Abbreviations: PR, PR interval; QRS, QRS interval; QTc, corrected QT interval; BMI, body mass index; TG, triglyceride; HDL, high density lipoprotein; LDL, low density lipoprotein; CHOL, cholesterol; UREA, Urea nitrogen; CRE, Creatinine; FPG, fasting plasma glucose. Continuous variables were analyzed by Student's t test. ⁎ Compared to the parameters at baseline, P < 0.05.

of baseline, and the difference was not statistically significant. After 4 weeks of treatment, the QTc interval had no difference compared with baseline in paliperidone treatment group. A gender-specific abnormal QTc interval (male > 450 ms, female > 470 ms) was observed in four male patients with olanzapine and one female patient with risperidone after 4 weeks of treatment. After 4 weeks of treatment with AAPDs, two patients had a QTc interval > 500 ms, including one male patient taking olanzapine with a QTc of 518 ms and another female patient taking risperidone with a QTc of 504 ms. For the treatment of the two patients, the drugs were stopped immediately and switched to other antipsychotic drugs. Administered drugs and QTc interval at baseline and at week 4 were shown in Table 3.

Gene

Risk allele

P

P (adjusteda)

LEPR EPB41L4A LEP NRXN3 BDNF FTO FTO MC4R MC4R COMT

A C G T G T A C A A

0.492 0.042 0.096 0.221 0.128 0.348 0.440 0.739 0.932 0.224

0.483 0.042 0.094 0.236 0.134 0.355 0.433 0.734 0.922 0.236

LEPR EPB41L4A LEP NRXN3 BDNF FTO FTO MC4R MC4R COMT

A C G T G T A C A A

0.653 0.034 0.626 0.417 0.439 0.549 0.929 0.752 0.992 0.922

— — — — — — — — — —

LEPR EPB41L4A LEP NRXN3 BDNF FTO FTO MC4R MC4R COMT

A C G T G T A C A A

0.117 0.485 0.004 0.393 0.154 0.501 0.176 0.377 0.862 0.076

— — — — — — — — — —

Table 5 Quantitative gene-gene interaction analysis of AIQTIP (ΔQTc). Gene 1 All patients NRXN3 FTO Male patients LEP FTO Female patients NRXN3 FTO

3.4. Genotypes Candidate genes and SNPs genotyped in this study are showed in Table 1. All the SNPs we analyzed are in Hardy-Weinberg equilibrium. Table 4 shows the results of quantitative association analysis of candidate genes and QTc changes in phenotypes at 4 weeks. In all subjects, we found a significant association between the EPB41L4A SNP rs7732687 and AIQTIP (P = 0.042). In male patients, we also found a significant association between the EPB41L4A SNP rs7732687 and AIQTIP (P = 0.034). In female patients, the LEP SNP rs7799039 was significantly associated with AIQTIP (P = 0.004). For LEPR (rs1137101), BDNF (rs6265), NRXN3 (rs7141420), FTO (rs9939609), FTO (rs1558902), MC4R (rs6567160), MC4R (rs489693), and COMT (rs4680) no significant associations could be found between AIQTIP and SNPs. Table 5 shows the results of quantitative gene-gene interaction analysis of AIQTIP (ΔQTc) . The results showed significant epistasis between NRXN3 and FTO, FTO and NRXN3, and FTO and COMT gene SNPs for AIQTIP (ΔQTc) in all patients. We found significant epistasis between LEP and NRXN3, and FTO and NRXN3 gene SNPs for AIQTIP (ΔQTc) in male patients. We also found significant epistasis between NRXN3 and COMT, and FTO and COMT gene SNPs for AIQTIP (ΔQTc) in female patients.

SNP1

Gene 2

SNP2

P

P (adjusteda)

rs7141420 rs1558902

FTO COMT

rs9939609 rs4680

0.038 0.038

0.038 0.038

rs7799039 rs9939609

NRXN3 NRXN3

rs7141420 rs7141420

0.038 0.019

— —

rs7141420 rs1558902

COMT COMT

rs4680 rs4680

0.019 0.038

— —

Compared with patients that carried EPB41L4A rs7732687 genotypes TC and CC, QTc interval of patients with the TT genotype prolonged significantly after 4 weeks of treatment (P < 0.05).

4. Discussion AIQTIP is believed to be affected by many factors, including drugs and genes. Several risk factors combined may contribute to AIQTIP. Some gene variations will increase the risk of AIQTIP. With the development of pharmacogenetics, many genes associated with AIQTIP have been discovered. However, so far, no gene test of AIQTIP has been approved for clinical application. Although there have been many important discoveries about genes associated with AIQTIP, but the most consistent and reproducible findings are with NOS1AP (Aberg et al., 2012; Corponi et al., 2019), KCNH2 (Atalar et al., 2010; Corponi et al., 2019), ABCB1 (Corponi et al., 2019; Suzuki et al., 2014) genes. Moreover, the results of many studies are inconsistent (Fabbri et al., 2017; Spellmann et al., 2018), because of different admission criteria, 4

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SNP of EPB41L4A gene, which is rs7732687. Our research showed that the EPB41L4A SNP rs7732687 was significantly associated with AIQTIP (P = 0.042). The QTc intervals of patients carrying EPB41L4A rs7732687 TT genotype were significantly longer than that of patients with TC and CC genotypes after 4 weeks of AAPD therapy. Therefore the T allele increased the risk of AIQTIP. After grouping according to gender, SNP in EPB41L4A yielded significant association for AIQTIP in male patients, and SNP in LEP yielded significant association for AIQTIP in female patients. In our study, the LEP quantitative association with AIQTIP was first discovered. LEP encoding leptin on chromosome 7 is associated with the presence of SNPs, which can regulate the concentration of this adipokine in blood circulation. As the most studied SNP, rs7799039 is located in the promoter region of LEP gene (de Faria et al., 2017). In our study, we tested one SNP of LEP gene, that is rs7799039. LEP is associated with blood pressure, obesity, and sympathetic hyperactivity. Leptin regulates food intake by suppressing appetite. The high level of Leptin in serum is related to the development of inflammation, insulin resistance, and oxidative stress (Katsiki et al., 2018). These may be related to the occurrence and development of cardiovascular diseases including QTc interval prolongation and arrhythmia. As a result, for LEPR (rs1137101), BDNF (rs6265), NRXN3 (rs7141420), FTO (rs9939609), FTO (rs1558902), MC4R (rs6567160), MC4R (rs489693) and COMT (rs4680), we did not find significant associations between AIQTIP and SNPs. The results of quantitative genegene interaction analysis of AIQTIP (ΔQTc) showed significant epistasis between NRXN3 and FTO, FTO and NRXN3, and FTO and COMT gene SNPs for AIQTIP (ΔQTc) in all patients. We found significant epistasis between LEP and NRXN3, and FTO and NRXN3 gene SNPs for AIQTIP (ΔQTc) in male patients. We also found significant epistasis between NRXN3 and COMT, and FTO and COMT gene SNPs for AIQTIP (ΔQTc) in female patients. In this study, we explored the quantitative association between SNPs of candidate genes and AIQTIP to find AIQTIP genetic markers in Han Chinese patients suffered from schizophrenia. This study is the first to explore the effect of single atypical antipsychotic drug therapy on QTc interval in Chinese schizophrenia patients, and for the first time we have studied AIQTIP associated genes in the Han Chinese population. This is also the first time we have studied the association between AIQTIP and metabolism-related genes. In addition, in order to eliminate the environmental factors that may affect AIQTIP, we chose a sample of hospitalized patients whose lifestyle, diet and exercise are under the unified management of the hospital to reduce heterogeneity. In conclusion, our research has provided useful information for finding genetic variations involved in the AIQTIP. Our research has some limitations. Multiple risk factors combined may affect AIQTIP, and the effect of a single SNP on AIQTIP may be too small to be detected. At the same time, this effect may be easily overlapped by other clinical factors. For example, we didn't take account of dyslipidemia, obesity, hypertension, diabetes, smoking, alcohol, poor diet and so on. And our sample size is relatively small. In addition, the heterogeneity of antipsychotic drugs and schizophrenic patients still exist. Therefore, further association research is needed to confirm our discovery. In conclusion, atypical antipsychotic drugs can significantly prolong QTc interval in schizophrenic patients in short-term therapy, and there are gender differences. Different drugs have different effects on QTc interval prolongation. The EPB41L4A SNP rs7732687 is associated with AIQTIP in male patients, and the LEP SNP rs7799039 is associated with AIQTIP in female patients.

different ethnic groups, or poor statistical efficiency. In the past, most researches have mainly focused on genes associated with cardiac ion channels (Atalar et al., 2010; Corponi et al., 2019; Fabbri et al., 2017; Weeke et al., 2014), cardiac diastolic and systolic function (Watanabe et al., 2017), cardiac signal transduction (Corponi et al., 2019), and enzymes related to pharmacokinetics of drugs (Llerena et al., 2004). As the main cause of death in patients with schizophrenia is cardiovascular disease (Druss, 2018). This is closely related to metabolic changes caused by increased risks of dyslipidemia, weight gain, obesity, type 2 diabetes of schizophrenic patients, and some of which may be related to the use of antipsychotic drugs (Polcwiartek et al., 2016). Up to now, there is no study on the association between AIQTIP and metabolism-related genes. In this study, we analyzed the association between 10 SNPs in 8 candidate genes closely related to metabolism and AIQTIP by using candidate gene approach. The 10 SNPs in 8 candidate genes closely related to metabolism were selected, respectively: rs1137101 (LEPR), rs7732687 (EPB41L4A), rs7799039 (LEP), rs6265 (BDNF), rs7141420 (NRXN3), rs9939609 (FTO), rs1558902 (FTO), rs6567160 (MC4R), rs489693 (MC4R), and rs4680 (COMT). Prolongation of QTc interval induced by antipsychotic drugs is well known (Beach et al., 2013). In this study, we found that after 4 weeks of AAPD treatment, the QTc interval was generally prolonged as compared with the baseline in all subjects. After grouping according to gender, the QTc interval of female patients was also prolonged after 4 weeks of treatment. For male patients, the QTc interval was also longer than that of the baseline after 4 weeks of treatment, but there was no statistical significance compared with the baseline. This is consistent with the research results of Suzuki et al. (2013). And it is well known that female gender is a risk factor for drug induced QTc interval prolongation (Khan et al., 2019). Women are more sensitive to QTc interval prolonging medications than men (Ravens, 2018; Trojak et al., 2009). In addition, different antipsychotics showed different effects on the prolongation of QTc interval, of which quetiapine has the most distinct effect. And this is consistent with the meta-analysis results of Leucht et al. (2013). A gender-specific abnormal QTc interval (male > 450 ms, female > 470 ms) was observed in four male patients with olanzapine and one female patient with risperidone after 4 weeks of treatment. After 4 weeks of treatment with AAPDs, two patients’ QTc intervals were greater than 500 ms, one of whom was male patient taking olanzapine, and QTc was 518 ms, the other one was female patient taking risperidone, and QTc was 504 ms. For the treatment of these two patients, we immediately stopped the drugs and switched to other antipsychotic drugs. This study showed that after 4 weeks of AAPD treatment, the QTc interval was generally prolonged in all subjects, and more seriously, the QTc interval of individual patients were greater than 500 ms, which is associated with a twofold to threefold increase in the risk of torsade de pointes (Cohagan and Brandis, 2019). This result reminded us that even in the short-term treatment of AAPD therapy, we should pay close attention to AIQTIP in patients suffered from schizophrenia, especially in female patients. In our study, SNP in EPB41L4A yielded significant association for AIQTIP. EPB41L4A-AS1 is located in the 5q22.2 region, which is closely related to tumorigenesis because of frequent DNA deletions. It is well known that EPB41L4A-AS1 inhibits tumor proliferation and is associated with many solid tumors (Xu et al., 2016), such as breast cancer (Xu et al., 2016), non-small cell lung cancer (Shu et al., 2018), hepatocellular carcinoma (Wang et al., 2019), colorectal cancer(He et al., 2019). However, its role in cancer is unclear (Liao et al., 2019). At present, no research has found that EPB4A is related to AIQTIP. A basic research has found that EPB4A is related to regulating glycolysis and glutamine hydrolysis (Liao et al., 2019). It has been reported that glycolysis is increased and QTc interval is prolonged in patients with right ventricular hypertrophy (Piao et al., 2010). Therefore, EPB4A may prolong QTc interval by affecting glycolysis. In this study, we tested 1

CRediT authorship contribution statement Haiyan Cao: Formal analysis, Writing - original draft. Shen Li: Data curation, Formal analysis, Writing - original draft. Ying Gao: Data curation. Yanyan Ma: Data curation. Lili Wang: Data curation. Bing 5

Psychiatry Research 286 (2020) 112851

H. Cao, et al.

Chen: Data curation. Rui Jiang: Data curation. Yuan Zhang: Formal analysis. Weidong Li: Conceptualization, Supervision. Jie Li: Conceptualization, Writing - original draft, Supervision.

Formos. Med. Assoc. 118 (1 Pt 1), 109–115. Leucht, S., Cipriani, A., Spineli, L., Mavridis, D., Orey, D., Richter, F., Samara, M., Barbui, C., Engel, R.R., Geddes, J.R., Kissling, W., Stapf, M.P., Lassig, B., Salanti, G., Davis, J.M., 2013. Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. Lancet 382 (9896), 951–962. Li, S., Gao, Y., Lv, H., Zhang, M., Wang, L., Jiang, R., Xu, C., Wang, X., Gao, M., He, Y., Li, J., Li, W.D., 2018. T4 and waist:hip ratio as biomarkers of antipsychotic-induced weight gain in Han Chinese inpatients with schizophrenia. Psychoneuroendocrinology 88, 54–60. Liao, M., Liao, W., Xu, N., Li, B., Liu, F., Zhang, S., Wang, Y., Wang, S., Zhu, Y., Chen, D., Xie, W., Jiang, Y., Cao, L., Yang, B.B., Zhang, Y., 2019. LncRNA EPB41L4A-AS1 regulates glycolysis and glutaminolysis by mediating nucleolar translocation of HDAC2. EBioMedicine 41, 200–213. Llerena, A., Berecz, R., Dorado, P., de la Rubia, A., 2004. QTc interval, CYP2D6 and CYP2C9 genotypes and risperidone plasma concentrations. J. Psychopharmacol. 18 (2), 189–193. Luo, S., Michler, K., Johnston, P., Macfarlane, P.W., 2004. A comparison of commonly used QT correction formulae: the effect of heart rate on the QTc of normal ECGs. J. Electrocardiol. 37 (Suppl), 81–90. Nielsen, J., Graff, C., Kanters, J.K., Toft, E., Taylor, D., Meyer, J.M., 2011. Assessing QT interval prolongation and its associated risks with antipsychotics. CNS Drugs 25 (6), 473–490. Niemeijer, M.N., van den Berg, M.E., Eijgelsheim, M., Rijnbeek, P.R., Stricker, B.H., 2015. Pharmacogenetics of drug-induced QT interval prolongation: an update. Drug Saf. 38 (10), 855–867. Piao, L., Fang, Y.H., Cadete, V.J., Wietholt, C., Urboniene, D., Toth, P.T., Marsboom, G., Zhang, H.J., Haber, I., Rehman, J., Lopaschuk, G.D., Archer, S.L., 2010. The inhibition of pyruvate dehydrogenase kinase improves impaired cardiac function and electrical remodeling in two models of right ventricular hypertrophy: resuscitating the hibernating right ventricle. J. Mol. Med. (Berl.) 88 (1), 47–60. Polcwiartek, C., Kragholm, K., Schjerning, O., Graff, C., Nielsen, J., 2016. Cardiovascular safety of antipsychotics: a clinical overview. Expert Opin. Drug Saf. 15 (5), 679–688. Ravens, U., 2018. Sex differences in cardiac electrophysiology. Can. J. Physiol. Pharmacol. 96 (10), 985–990. Rijnbeek, P.R., van Herpen, G., Bots, M.L., Man, S., Verweij, N., Hofman, A., Hillege, H., Numans, M.E., Swenne, C.A., Witteman, J.C., Kors, J.A., 2014. Normal values of the electrocardiogram for ages 16-90 years. J. Electrocardiol. 47 (6), 914–921. Roden, D.M., 2016. Predicting drug-induced QT prolongation and torsades de pointes. J. Physiol. 594 (9), 2459–2468. Shu, J., Li, S., Chen, Y.B., Zhu, Q.F., Yu, X.H., 2018. Long non-coding RNA EPB41L4A-AS2 inhibited non-small cell lung cancer proliferation, invasion and promoted cell apoptosis. Neoplasma 65 (5), 664–672. Spellmann, I., Reinhard, M.A., Veverka, D., Zill, P., Obermeier, M., Dehning, S., Schennach, R., Muller, N., Moller, H.J., Riedel, M., Musil, R., 2018. QTc prolongation in short-term treatment of schizophrenia patients: effects of different antipsychotics and genetic factors. Eur. Arch. Psychiatry Clin. Neurosci. 268 (4), 383–390. Strauss, D.G., Vicente, J., Johannesen, L., Blinova, K., Mason, J.W., Weeke, P., Behr, E.R., Roden, D.M., Woosley, R., Kosova, G., Rosenberg, M.A., Newton-Cheh, C., 2017. Common genetic variant risk score is associated with drug-induced QT prolongation and torsade de pointes risk: a pilot study. Circulation 135 (14), 1300–1310. Suzuki, Y., Sugai, T., Fukui, N., Watanabe, J., Ono, S., Tsuneyama, N., Saito, M., Someya, T., 2013. Sex differences in the effect of four second-generation antipsychotics on QTc interval in patients with schizophrenia. Hum. Psychopharmacol. 28 (3), 215–219. Suzuki, Y., Tsuneyama, N., Fukui, N., Sugai, T., Watanabe, J., Ono, S., Saito, M., Inoue, Y., Someya, T., 2014. Effect of risperidone metabolism and P-glycoprotein gene polymorphism on QT interval in patients with schizophrenia. Pharmacogen. J. 14 (5), 452–456. Takeuchi, H., Suzuki, T., Remington, G., Uchida, H., 2015. Antipsychotic polypharmacy and corrected QT interval: a systematic review. Can. J. Psychiatry 60 (5), 215–222. Trojak, B., Astruc, K., Pinoit, J.M., Chauvet-Gelinier, J.C., Ponavoy, E., Bonin, B., Gisselmann, A., 2009. Hypokalemia is associated with lengthening of QT interval in psychiatric patients on admission. Psychiatry Res. 169 (3), 257–260. Volpi, S., Heaton, C., Mack, K., Hamilton, J.B., Lannan, R., Wolfgang, C.D., Licamele, L., Polymeropoulos, M.H., Lavedan, C., 2009. Whole genome association study identifies polymorphisms associated with QT prolongation during iloperidone treatment of schizophrenia. Mol. Psychiatry 14 (11), 1024–1031. Wang, Y.G., Wang, T., Shi, M., Zhai, B., 2019. Long noncoding RNA EPB41L4A-AS2 inhibits hepatocellular carcinoma development by sponging miR-301a-5p and targeting FOXL1. J. Exp. Clin. Cancer Res. 38 (1), 153. Watanabe, J., Fukui, N., Suzuki, Y., Sugai, T., Ono, S., Tsuneyama, N., Saito, M., Tajiri, M., Someya, T., 2017. Effect of GWAS-identified genetic variants on maximum QT interval in patients with schizophrenia receiving antipsychotic agents: a 24-hour Holter ECG study. J. Clin. Psychopharmacol. 37 (4), 452–455. Weeke, P., Mosley, J.D., Hanna, D., Delaney, J.T., Shaffer, C., Wells, Q.S., Van Driest, S., Karnes, J.H., Ingram, C., Guo, Y., Shyr, Y., Norris, K., Kannankeril, P.J., Ramirez, A.H., Smith, J.D., Mardis, E.R., Nickerson, D., George Jr., A.L., Roden, D.M., 2014. Exome sequencing implicates an increased burden of rare potassium channel variants in the risk of drug-induced long QT interval syndrome. J. Am. Coll. Cardiol. 63 (14), 1430–1437. Xu, S., Wang, P., You, Z., Meng, H., Mu, G., Bai, X., Zhang, G., Zhang, J., Pang, D., 2016. The long non-coding RNA EPB41L4A-AS2 inhibits tumor proliferation and is associated with favorable prognoses in breast cancer and other solid tumors. Oncotarget 7 (15), 20704–20717.

Declaration of Competing Interest The authors declare no conflict of interest. Acknowledgments This work was supported in part by National Key R&D Program of China (2016YFC1306800) by Ministry of Science and Technology of China, National Natural Science Foundation of China (81801323) and Tianjin Key Project for Chronic Diseases Prevention (2017ZXMFSY00070) by Tianjin Municipal Science and Technology Bureau. These sources had no further role in this study design, data collection and statistical analysis, drafting of the report, and submitting the paper for publication. We thank all of the study participants for their cooperation. Supplementary materials Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psychres.2020.112851. References Aberg, K., Adkins, D.E., Liu, Y., McClay, J.L., Bukszar, J., Jia, P., Zhao, Z., Perkins, D., Stroup, T.S., Lieberman, J.A., Sullivan, P.F., van den Oord, E.J., 2012. Genome-wide association study of antipsychotic-induced QTc interval prolongation. Pharmacog. J. 12 (2), 165–172. Antoniou, C.K., Dilaveris, P., Manolakou, P., Galanakos, S., Magkas, N., Gatzoulis, K., Tousoulis, D., 2017. QT prolongation and malignant arrhythmia: how serious a problem? Eur. Cardiol. 12 (2), 112–120. Atalar, F., Acuner, T.T., Cine, N., Oncu, F., Yesilbursa, D., Ozbek, U., Turkcan, S., 2010. Two four-marker haplotypes on 7q36.1 region indicate that the potassium channel gene HERG1 (KCNH2, Kv11.1) is related to schizophrenia: a case control study. Behav. Brain Funct. 6, 27. Beach, S.R., Celano, C.M., Noseworthy, P.A., Januzzi, J.L., Huffman, J.C., 2013. QTc prolongation, torsades de pointes, and psychotropic medications. Psychosomatics 54 (1), 1–13. Becker, L., Eisenberg, M., Fahrenbruch, C., Cobb, L., 1998. Public locations of cardiac arrest. Implications for public access defibrillation. Circulation 97 (21), 2106–2109. Cohagan, B., Brandis, D., 2019. Torsade de Pointes. StatPearls, Treasure Island (FL). Corponi, F., Fabbri, C., Boriani, G., Diemberger, I., Albani, D., Forloni, G., Serretti, A., 2019. Corrected QT interval prolongation in psychopharmacological treatment and its modulation by genetic variation. Neuropsychobiology 77 (2), 67–72. de Faria, A.P., Ritter, A.M., Sabbatini, A.R., Modolo, R., Moreno, H., 2017. Effects of leptin and leptin receptor SNPs on clinical- and metabolic-related traits in apparent treatment-resistant hypertension. Blood Press 26 (2), 74–80. Drew, B.J., Ackerman, M.J., Funk, M., Gibler, W.B., Kligfield, P., Menon, V., Philippides, G.J., Roden, D.M., Zareba, W., American Heart Association Acute Cardiac Care Committee of the Council on Clinical Cardiology, t.C.o.C.N., the American College of Cardiology, F., 2010. Prevention of torsade de pointes in hospital settings: a scientific statement from the American Heart Association and the American College of Cardiology Foundation. Circulation 121 (8), 1047–1060. Druss, B.G., 2018. Can better cardiovascular care close the mortality gap for people with schizophrenia? JAMA Psychiatry 75 (12), 1215–1216. Fabbri, C., Boriani, G., Diemberger, I., Filippi, M.G., Ravegnini, G., Hrelia, P., Minarini, A., Albani, D., Forloni, G., Angelini, S., Serretti, A., 2017. Electrocardiogram alterations associated with psychotropic drug use and CACNA1C gene variants in three independent samples. Basic Clin. Pharmacol. Toxicol. 120 (5), 482–490. He, M., Lin, Y., Xu, Y., 2019. Identification of prognostic biomarkers in colorectal cancer using a long non-coding RNA-mediated competitive endogenous RNA network. Oncol. Lett. 17 (3), 2687–2694. Hjorthoj, C., Sturup, A.E., McGrath, J.J., Nordentoft, M., 2017. Years of potential life lost and life expectancy in schizophrenia: a systematic review and meta-analysis. Lancet Psychiatry 4 (4), 295–301. Hong, Y., Rautaharju, P.M., Hopkins, P.N., Arnett, D.K., Djousse, L., Pankow, J.S., Sholinsky, P., Rao, D.C., Province, M.A., 2001. Familial aggregation of QT-interval variability in a general population: results from the NHLBI Family Heart Study. Clin. Genet. 59 (3), 171–177. Katsiki, N., Mikhailidis, D.P., Banach, M., 2018. Leptin, cardiovascular diseases and type 2 diabetes mellitus. Acta Pharmacol. Sin. 39 (7), 1176–1188. Khan, Q., Ismail, M., Haider, I., Ali, Z., 2019. Prevalence of the risk factors for QT prolongation and associated drug-drug interactions in a cohort of medical inpatients. J.

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