Association between COMT Val158Met and Tobacco Smoking among Subjects with Schizophrenia and Bipolar Disorder: A Pilot Study

Research Article

J Schizophr Res. 2015; 2(3): 1017.

Association between COMT Val158Met and Tobacco Smoking among Subjects with Schizophrenia and Bipolar Disorder: A Pilot Study

Hirasawa-Fujita M¹, Bly MJ², Ellingrod VL², Dalack GW³, Pivac N4 and Domino EF¹*

¹Department of Pharmacology, University of Michigan, USA

²College of Pharmacy, University of Michigan, USA

³Department of Psychiatry, University of Michigan, USA

4Department of Rudjer Boskovic, University of Michigan, USA

*Corresponding author: Domino EF, Department of Pharmacology, University of Michigan, 1301 MSRB III, Ann Arbor, MI 48109, USA

Received: September 15, 2015; Accepted: November 05, 2015; Published: November 09, 2015

Abstract

Mentally ill patients are frequently tobacco smokers. This pilot study determined the association between the Catechol-O-Methyltransferase (COMT) Val158Met (rs4680) variants and smoking in patients with schizophrenia and bipolar disorder. The subjects were classified into current, former and neversmokers, and subdivided according to race gender and the genotype. The number of cigarettes smoked per day was used as the major parameter to assess their smoking behavior. Female schizophrenic smokers with the Met allele smoked significantly more cigarettes per day than males with the Val/ Val genotype and schizophrenia. This significance was detected among African American, but not Caucasian patients with schizophrenia. Especially in female African Americans, the Met allele carriers smoked significantly more cigarettes per day than the Val/Val carriers. No significant association between the COMT genotypes and smoking status was found in patients with schizophrenia or bipolar disorder. In addition, no significant genotype and sex-related differences were found in Caucasians with schizophrenia or bipolar disorder. The results demonstrate that the COMT Met allele affects the number of cigarettes smoked per day, but this effect was sex, ethnic, and mental diagnosis-specific.

Keywords: Genetics; Schizophrenia; Bipolar disorder; Smoking; Number of cigarettes/day

Abbreviations

SCZ: Subjects With Schizophrenia; BP: Subjects with Bipolar Disorder; COMT: Catechol-O-Methyltransferase; SCID: Structured Clinical Interview for DSM-IV; DIGS: Diagnostic Interview for Genetic Studies; PCR: Polymerase Chain Reaction; DA: Dopamine

Introduction

Mental disorders and smoking are commonly co-morbid [1- 5]. The Catechol-O-Methyltransferase (COMT) Val158Met variant (rs4680) has been considered as an important gene candidate for both mental disorders and tobacco smoking. Many studies evaluated the association between the COMT variant sand tobacco smoking cessation [6-10], smoking prevalence [11,12], risk of being heavy smoker [13] and nicotine dependence [14,15] in healthy control subjects (without mental disorders). However, less data are available for the association between the COMT polymorphism and mental disorders such as schizophrenia [16-18] and bipolar disorder [19-22].

COMT is a key enzyme involved in the metabolism of Catechol amines, especially Dopamine (DA) and nor epinephrine [23-26]. The Met variant has less enzyme thermos-stability which results in lower protein expression and lower enzymatic activity [27]. The differences induced by different COMT genotypes can be explained by the tonicphasic DA hypothesis, with complexities and limitations including sex and phenotype differences, and a range of endogenous and environmental factors [28]. Also gender and ethnic specific genotype differences were reported in nicotine dependence among control subjects and patients with panic disorder, respectively [29,30]. The Met allele frequency differs in various ethnic groups, and it was reported to be 0.4-0.5 in Caucasians, 0.5 in South-West Asians, 0.2 in pure African populations [31-33]. Furthermore, the homozygous Met allele frequency is much lower in Kenyan population (0.1) than in Caucasians (0.3) or Southwest Asians (0.3) [34].

Our study aimed to confirm two hypotheses; 1) the COMT genotype alters tobacco smoking behavior, and 2) the genotype differences are influenced by subject’s sex, race and type of mental illness.

Materials and Methods

Subjects

All participants (N=320) were recruited from local ambulatory care mental health clinics as described in a previous report [35]. They were included in a previous pharmacogenomic study related to atypical antipsychotics-associated metabolic complications [36]. Inclusion criteria were 1) DSM-IV diagnosis of schizophrenia, schizophreniform disorder, schizoaffective disorder, or bipolar disorder I or II; 2) =18 years old; and 3) stable pharmacologic mental health treatment for at least 6 months. The exclusion criterion was inability to provide informed consent (assessed using a short questionnaire with key questions about the study including drug abuse). All subjects gave informed consent. The study protocol was approved by the University of Michigan Institutional Review Board. A trained assistant completed a research assessment using either the Structured Clinical Interview for DSM-IV (SCID) [37], or the Diagnostic Interview for Genetic Studies (DIGS) [38] to confirm the psychiatric diagnosis. The euthymic state of the bipolar patients was assessed by the psychometric scales. This information was also confirmed by chart review when necessary. Different diagnostic instruments were used since subjects came from two different primary groups. The procedures used for gathering all other data were identical across subject groups. Subjects underwent a current and past medication history assessment, confirmed by a medical record review. Antipsychotic medication was determined using chlorpromazine equivalents [39]. A total of 320 patients with schizophrenia and bipolar disorder were recruited into this study and 28 patients with schizophrenia and 4 patients with bipolar disorder were excluded due to unavailable COMT genotype and smoking history.

Smoking status data collection

Life time smoking status was classified into current, former and never smokers. Current and former smokers provided information regarding the number of cigarettes smoked/day, age at initiation of smoking, and quit date (if applicable). The number of cigarettes smoked per day was reported by current and former smokers. For the former smokers, the number of cigarettes smoked per day was average number of cigarettes smoked in past.

Genotyping of the COMT Val 158Met (rs4680)

DNA was extracted from whole blood with Purgene kits (Qiagen, Valencia California). Genotyping of the COMT Val 158Met (rs4680) was done using polymerase chain reaction (PCR) and sequencing primers were designed by Pyrosequencing SNP Primer Design Version 1.01 software (https://www.pyrosequencing.com). The PCR were performed using One Taq 2X Master Mix with Standard Buffer (BiolabsInc) with the forward primer (5’-TCG TGG ACG CCG TGA TTC -3’) and biotinylated reverse primer (5’- /5Bio/ CAC AGC CGG CCC TTT TTC -3’) for COMT variant. The purity of PCR products were confirmed 1.8 % agarose gel electrophoresis. Pyrosequencing™ Technology was used to determine the genotype.

Statistical analysis

The COMT genotype was classified into two groups: Met allele carriers (the combined Val/Met and Met/Met genotypes), and the Val/Val genotype group. The number of cigarettes smoked per day was used as a major tobacco smoking parameter. Student’s t tests and one-way ANOVA were used to compare the number of cigarettes smoked/day. The life time smoking status was used to assess smoking prevalence. Chi-square test was used to assess the Hardy-Weinberg equilibrium, smoking prevalence and population/genotype analyses. Linear regression model was used to elucidate contributions of factors including the COMT genotype, race, sex and diagnosis. All statistical analyses included current, former and never smokers. All of the medication groups were included in the analyses. The data were analyzed with IBM SPSS (Statistic Package for Social Sciences) statistics version 21 for Windows. A p value was considered significant if p<0.05. Statistical power (designated to be more than 0.800) and required sample size (N=273) with small effect size (w=0.2) for Χ² test was calculated a priori by G* Power (https://www.gpower.hhu.de/).

Population characteristics

A total of 288 smoking and nonsmoking patients diagnosed with schizophrenia (n=172) and bipolar disorder (n=116) participated in this study. All of the bipolar patients were at euthymic state which was assessed by psychometric scales at the moment of data acquisition. Their age ranged between 19-71 years (45.0±11.6). The majority of the subjects were Caucasians (67.0 %) followed by African Americans (25.7 %) and others including Asians, Indian Americans and Hispanics (7.3 %). The ethnic distributions were significantly different across diagnoses (Χ² (2) =18.6, p< 0.0001). In the entire group, 133 (46.2 %) were current smokers, 62 (21.5 %) were former smokers and 93 (32.3 %) subjects had never smoked. The smoking status was significantly different between different diagnostic groups (Χ² (2) =22.3, p< 0.0001). Those who were current and former smokers smoked an average of 17.8±12.0 cigarettes per day. Their average ± SD pack year history was 19.9±22.1 (Table 1). Summarizes the demographic data of all subjects.