Identification of genetic correlates of response to Risperidone: Findings of a multicentric schizophrenia study from India

Asian Journal of Psychiatry 29 (2017) 174–182

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Identification of genetic correlates of response to Risperidone: Findings of a multicentric schizophrenia study from India

MARK

Gurjit Kaura, Deepti Guptab, Bir Singh Chavanc, Vikas Sinhmarb, Rajendra Prasadd, Adarsh Tripathie, P.D. Gargf, Rajiv Guptag, Hitesh Khuranag, Shiv Gautamh, ⁎ Mushtaq Ahmed Margoobi, Jitender Anejac, a

Department of Physiology, Government Medical College & Hospital, Sector 32, Chandigarh, India Genetic Centre, Government Medical College & Hospital, Sector 32, Chandigarh, India c Department of Psychiatry, Government Medical College & Hospital, Sector 32, Chandigarh, India d Department of Biochemistry, Postgraduate Institute of Medical Education & Research, Sector 12, Chandigarh, India e Department of Psychiatry, King George’s Medical University, Lucknow, Uttar Pradesh, India f Department of Psychiatry, Government Medical College, Amritsar, Punjab, India g Department of Psychiatry, Postgraduate Institute of Medical Sciences, Rohtak, Haryana, India h Department of Psychiatry, SMS Medical College, Jaipur, Rajasthan, India i Department of Psychiatry, Government Medical College, Srinagar, Jammu & Kashmir, India b

A R T I C L E I N F O

A B S T R A C T

Keywords: 5-HT2A CYP2D6 DRD2 Genetic polymorphism Risperidone Schizophrenia

Risperidone is most commonly used as an antipsychotic in India for treatment of schizophrenia. However, the response to treatment with risperidone is affected by many factors, genetic factors being one of them. So, we attempted to evaluate the association between dopamine D2 (DRD2) receptor, serotonergic (5HT2A) receptor and CYP2D6 gene polymorphisms and response to treatment with risperidone in persons with schizophrenia from North India. It was a multicentric 12-weeks prospective study, undertaken in patients diagnosed with schizophrenia according to International Classification of Diseases 10th revision, Diagnostic Criteria for Research module (ICD-10 DCR). Patients were treated with incremental dosages of risperidone. Nine gene polymorphisms from three genes viz. DRD2, 5-HT2A and CYP2D6 along with socio-demographical and clinical variables were analyzed to ascertain the association in response to risperidone treatment. The change in the Positive and Negative Syndrome Scale (PANSS) was used to measure the outcome. Significant differences in the frequencies of single nucleotide proteins (SNPs) rs180498 (Taq1D) and rs 6305 (C516T) polymorphisms were found amongst the groups defined according to percent decline in PANSS. The CYP2D6*4 polymorphism differed significantly when drop outs were excluded from analysis. Presence of DRD2 Taq 1 D2D2 and 5-HT2A C516T CT genotypes in patients were more likely to be associated with non-response to risperidone. Ser311Cys (rs1801028) mutation was absent in the North Indian patients suffering from schizophrenia.

1. Introduction Schizophrenia, a multifactorial psychiatric disorder involves both environmental and genetic factors as etio-pathological mechanisms (Cardno and Gottesman, 2000). Risperidone, an atypical anti-psychotic drug is widely used in treatment of schizophrenia across the globe. It acts mainly through selective antagonism of dopaminergic (D2) receptors and serotonergic (5-HT2A) receptors, as well as alpha (1 & 2) adreno-receptors (Leysen et al., 1988). Risperidone is metabolized in the liver by cytochrome P450 isoenzymes (CYP2D6, CYP3A4, CYP3A5),

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Corresponding author. E-mail address: [email protected] (J. Aneja).

http://dx.doi.org/10.1016/j.ajp.2017.07.026 Received 8 November 2016; Received in revised form 30 May 2017; Accepted 4 July 2017 1876-2018/ © 2017 Elsevier B.V. All rights reserved.

and also involves some transporter proteins like Adenosine triphosphate- binding cassette subfamily B member 1 (ABCB1) and Multi-drug resistant gene (MDR1) (Leon et al., 2007; Xiang et al., 2010). However, all patients do not respond to treatment with risperidone which is influenced by a range of factors that includes various clinical, demographic, environmental and genetic factors (Gupta et al., 2006). In the last two decades, significant work has been done which demonstrated the genetic factors involved in schizophrenia, the association of various genetic polymorphisms of dopaminergic and serotonergic receptors with schizophrenia as well as response to treatment

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patients.

with a range of antipsychotic drugs. For example, heterozygosity for the Taq1A allele of DRD2 has been shown to be associated with favorable short-term response to haloperidol (Schafer et al., 2001). Similarly, in another study (Lane et al., 2004) the Ser311Cys polymorphism of DRD2 gene was shown to play a role in risperidone efficacy for positive, negative, and cognitive symptoms. In a South Indian study, Vijayan et al. (2007) reported that the H313C, Taq1A2A2, Taq1D1D1 genotypes were significantly associated with positive treatment response in persons suffering from schizophrenia. The 5-HTR2A gene (located at chromosome 13q14-q21) has been shown to be associated with negative symptoms of schizophrenia. It has been reported that C allele of T102 (rs6313) and G allele of A-1438G (rs 6311) may cause lower promoter activity and reduced 5-HT2A receptor density in some brain areas (Parsons et al., 2004). Many studies have elicited the association of T102C and drug response to different second generation antipsychotics. A meta-analysis reported higher prevalence of C allele of T102C in non-responders to clozapine but it did not reach significance when one study was excluded as well as in the later publications (Masellis et al., 1998; Lin et al., 1999). Similarly, it has been suggested that A1438G polymorphism alters promoter activity and expression of 5-HT2A receptors and might be responsible for association with schizophrenia and the drug response (Penas-Lledo et al., 2007). Reynolds et al. (2006) investigated the −759C/T polymorphism of the serotonin 5-HT2C and antipsychotic drug response and found significant effect on the negative, but not the positive symptoms scores on PANSS. The CYP2D6 enzyme has a diverse genetic variability with more than 80 allele variants reported till date (Zanger et al., 2004). This leads to variation in the response to treatment with risperidone amongst different ethnic populations. Previous studies have shown that about fewer than 1% of Asians lack CYP2D6 enzymatic activity which is upto 10% in Caucasians due to encoding of 2 null alleles. Individual with CYP2D6*9, *10, *17, *37 and *41 mutant alleles have been shown to have reduced activity while those with CYP2D6 *3, *4, *5, *6, *8, *11 and many other mutants completely lack enzymatic activity (Cartwright et al., 2013). Most of the earlier studies, done in Western, Japanese and Chinese populations have shown varying levels of association between efficacy of treatment with risperidone and CYP2D6 polymorphism. Also, the methods of assessment of impact of CYP2D6 polymorphism and response to treatment varied across studies with some measuring allele frequencies and other’s plasma levels of risperidone and its active metabolites too (Bartecek et al., 2012). A range of single nucleotide polymorphisms (SNP) of various dopamine receptor gene (DRD1-4) and serotonin receptor gene, CYP2D6 genes and their effect on the pharmaco-genetics of various commonly used antipsychotic drugs have been investigated. But, the gene frequencies are different across ethnic populations which makes it difficult to generalize the findings of such studies. Also, ethnicity is a significant factor that modulates the response to psychotropic medications. Although, a significant amount of research is available that has shown the association of genetic polymorphism of dopaminergic and serotonergic receptors and schizophrenia but association studies with antipsychotic response are scarce. In Indian context, that has a wide variation in ethnicity and thus significant genetic differences, pharmaco-genetic research in field of schizophrenia has been done in selected group of populations only (Vijayan et al., 2007; Kaur et al., 2014; Sujitha et al., 2014; Jajodia et al., 2015). So, it becomes imperative to undertake pharmaco-genetic research that may uncover underlying genetic factors which may affect response to treatment in ethnic population suffering from schizophrenia. With this background, the index study was aimed to investigate the association between genetic polymorphism of DRD2, 5HT2A and CYP2D6 receptor genes and response to treatment with risperidone in persons suffering from schizophrenia from North India region. We also analyzed the findings of this study to ascertain the association of polymorphism of the studied genes with clinical characteristics of

2. Methodology 2.1. Selection of subjects This study was sponsored by the Indian Medical Council of Medical Research (ICMR), New Delhi and was carried out in accordance with the guidelines of Central Ethics Committee on Biomedical research in humans. It was a multi-centric study that was carried out at Government Medical College and Hospital, Chandigarh, Government Medical College, Amritsar, Post Graduate Institute of Medical Sciences, Rohtak, Govt. Medical College, Srinagar, King George's Medical University, Lucknow and Swai Mann Singh Medical College, Jaipur. The study period spanned through April 2011 to March 2014. During this period all the consecutive patients suffering from schizophrenia who consulted in the Department of Psychiatry of aforementioned institutes in the Northern part of India were approached to participate in this study. The patients between ages 18–55 years, who consented to participate in this study, met the diagnosis of schizophrenia according to ICD-10 DCR, and had a family member/caregiver who could monitor the drug compliance, were included. The patients with additional Axis I diagnosis, mental retardation, substance use disorder other than tobacco abuse or dependence, receiving long acting antipsychotic agents, metabolic syndrome, with any comorbid severe medical or surgical illness or genetic syndrome and those who did not consent were excluded from the study. Respective institutional ethics committees approved the study. 2.2. Control sample One hundred and fifty healthy controls were recruited for the purpose of genetic analysis. The healthy controls were selected from unrelated accomplices of either the patients or relatives of other clients of genetic center at Government Medical College & Hospital, Chandigarh. They consented to participate in the study and agreed to provide blood samples for genetic analysis and other laboratory investigations. No benefits in any form were given to the healthy controls. 2.3. Dosing schedule During the study period only anticholinergic drugs (trihexyphenidyl) and benzodiazepines (lorazepam or diazepam) were permitted for control of extrapyramidal symptoms and sleep disturbance. The drug naive patients were straight way included into the study after taking their consent. The patients who were receiving other antipsychotic drugs and still symptomatic were switched to risperidone. A wash- out period of 7 days was given prior to switching to risperidone, which was increased by 1 mg/week starting from day 1 of inclusion into the study to 12 mg at week 12. All the patients were given oral form of risperidone, by same manufacturer (to avoid different bioavailability of risperidone). Risperidone for present study was procured by the coordinating Centre and distributed free of cost. The procurement of risperidone was done according to the institutional guidelines and the manufacturer did not have any role in any form in this study. At the Chandigarh Centre, additionally the plasma concentration of risperidone and its metabolite 9-hydroxyrisperidone was measured at start of treatment, at week 6 and 12 of study period. 2.4. Clinical assessments The severity of illness was assessed at baseline by applying Positive and Negative Syndrome Scale (PANSS) (Kay et al., 1987). Ratings on PANSS were done by trained psychiatrists (senior residents or participating consultants) every week till week 12 of study period. The procedure of enrollment and assessment of patients on a weekly basis was 175

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supervised/done by the participating authors at their respective institutes who in turn provided feedback to the primary investigators every month. Detailed information about the patient and the history of the disease that included personal details, clinical details, symptoms, socio-demographic details and relevant investigations were recorded on a proforma devised for this project.

Table 1 Socio-demographic and clinical profile of study participants.

2.5. Clinical and laboratory assessments The pulse rate, blood pressure (BP), waist circumference and weight and body mass index (BMI) were assessed at baseline and then weekly. Physical investigations in form of complete blood count, liver function tests, fasting blood sugar and lipid profile were assessed at baseline and at 6 and 12 weeks of treatment. 2.6. Genetic analysis Five milliliter of blood sample from schizophrenic patients was collected in EDTA vacutainers on the day one of treatment and from control subjects for genetic analysis of DRD2 [Taq1A (rs1800497), Taq1B (rs1079597), Taq1D (rs180498), Ser311C (rs1801028)], 5-HT2A [T102C (rs6313), A1438G (rs6311), 516 C > T (rs6305)] and CYP2D6 [*4 (1846 G > A; db ANP rs3892097), *10 (rs106585)] gene polymorphisms using PCR based Restriction Fragment Length Polymorphism (RFLP). DNA was isolated using standard protocol of sodium perchlorate method (Johns and Paulus-Thomas, 1989). DNA fragmentation was checked by agarose gel electrophoresis. The genes were amplified with appropriate primers using polymerase chain reaction (PCR) as done in previous studies (Vijayan et al., 2007; Semwal et al., 2002). During PCR and RFLP the pre-amplification area was separated from post-amplification area to avoid contamination. Negative controls were included in every set of reactions for quality control purposes. Wild type genotypes were assigned based on the size of the respective DNA fragments as done in previous studies (Vijayan et al., 2007; Bertola et al., 2007; Correa et al., 2007; Herken et al., 2003; Spurlock et al., 1998; Yamanouchi et al., 2003). A base- pair marker or DNA molecular weight marker was included during gel electrophoresis in each run for assurance. Another four ml of blood sample was collected separately in a heparinized vacutainer from the subjects at Chandigarh Center for the measurement of plasma level of risperidone and 9-hydroxyrisperidone (using High Performance Liquid Chromatography; HPLC) at baseline, week 6 and 12. 2.3. Outcome measures

Variable

N (%)/Mean (Std. dev.)

Gender Male Female Age (years) Duration of illness (in months)

262 (62.5%) 157 (37.5%) 31.36 (9.56) 46.92 (49.71)

Marital Status Single Married Divorced Separated due to mental illness Separated due to other reasons

180 (42.9%) 221 (52.6%) 8 (1.9%) 9 (2.1%) 1 (0.2%)

Occupation Student Regular employment Daily wager Housewife Unemployed

37 (8.8%) 41 (9.8%) 27 (6.4%) 76 (18.1%) 235 (56%)

Education Illiterate Upto Matric Graduate Post-graduate

78 (18.6%) 290 (69.5%) 42 (10%) 9 (2.1%)

Education Discontinued due to mental illness Yes No Not known

59 (14.08%) 339 (80.90%) 21 (5.2%)

Family type Nuclear Extended Joint

175 (41.7%) 53 (12.6%) 190 (45.2%)

Locality Urban Rural

135 (32.4%) 284 (67.6%)

Onset of illness Abrupt Acute Subacute Insidious Not known

42 (10%) 157 (37.4%) 67 (16%) 131 (31.2%) 22 (5.5%)

Course of illness Continuous Episodic with complete interepidsodic recovery Episodic with partial inter-episodic recovery Incomplete remission Not known

331 (78.8%) 23 (5.5%) 37 (8.8%) 5 (1.2%) 23 (5.7%)

Nicotine use Present Absent Past Treatment Yes No Information not available

The percentage reduction in PANSS score was used to measure response to treatment. The patients who had a reduction of less than 25%, 25–50% and > 50% in PANSS score from baseline to 6 weeks and 12 weeks of study period were labeled as non-responders, partial responders and responders, respectively. For some of the analyses we opted the standard measure of response in form of efficacy index i.e. percentage change in PANSS scores at baseline, at week 6 and 12 with a cutoff of > 50% improvement for responders while rest were classified as non-responders. The patients enrolled in the study were contacted telephonically in case they missed the scheduled appointment and efforts were made by respective investigators at their centers to reduce drop outs to minimum. However, if the patients did not turn up despite two telephonic communications, no further efforts were made. No systematic recording of the reasons of drop outs was done in the present study. The participants whose baseline details and blood samples for genetic analysis were available but did not complete treatment till 12 weeks were considered to be drop outs. 2.4. Statistical analysis Statistical analyses were done using the Statistical Package for 176

125 (29.7%) 294 (60.3%) 143 (34%) 250 (59.5%) 26 (6.2%)

History of mental illness in family Yes No

39 (9.3%) 380 (90.7%)

Responder status at 6 weeks Non-responder Partial Responder Responder Drop outs

77 (18.4%) 250 (59.7%) 14 (3.3%) 78 (18.6%)

Response status at 12 weeks Non-responder Partial responder Responder Drop out

17 (4.1%) 114 (27.2%) 200 (47%) 88 (21%)

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Table 2 Relation between response status at 6weeks and clinical variables. Response Status at 6 weeks

Age (in years) Duration of illness (in months) Dose of risperidone at week 1 (mg) Dose of risperidone at week 6 (mg) PANSS P score at baseline PANSS PANSS PANSS PANSS

N score at baseline G at baseline Total at baseline P at 6 weeks

PANSS N at 6 weeks PANSS G at 6weeks PANSS Total at 6 weeks

Non-responder

Partial responder

Responder

Drop Out

(N = 77)

(N = 250)

(N = 14)

(N = 78)

Mean (Std Dev.)

Mean (Std Dev.)

Mean (Std Dev.)

Mean (Std Dev.)

33.26 (8.48) (n = 77) 62.75 (58.11) (n = 70) 3.65 (2.01) (n = 77) 5.26 (1.51) (n = 76) 23.19 (7.60) (n = 77) 22.51 (7.95) 40.47 (11.97) 86.06 (21.48) 18.68 (6.77) (n = 77) 19.01 (6.61) 34.08 (10.01) 71.90 (18.62)

30.77 (9.18) (n = 250) 42.36 (46.74) (n = 244) 4.07 (1.70) (n = 250) 5.15 (1.47) (n = 248) 27.56 (6.12) (n = 250) 27.17 (7.78) 50.44 (15.09) 105.04 (23.47) 17.46 (5.87) (n = 250) 17.89 (4.80) 32.52 (8.89) 67.60 (15.85)

27.57 (11.33) (n = 14) 38.50 (44.38) (n = 14) 3.57 (1.78) (n = 14) 4.57 (1.39) (n = 14) 28.71 (8.11) (n = 14) 31.07 (5.85) 49.71 (16.44) 109.50 (23.87) 12.36 (5.70) (n = 14) 16.50 (5.14) 25.50 (5.66) 47.57 (9.80)

32.05 (11.09) (n = 78) 48.61 (49.34) (n = 72) 3.97 (1.73) (n = 78) 5.29 (1.25) (n = 7) 25.46 (6.98) (n = 78) 24.88 (7.87) 49.33 (15.78) 99.88 (26.73) 15.33 (11.15) (n = 3) 19.67 (6.35) 35.67 (17.95) 111.00(NA) (n = 1)

F value/P value

2.21/0.08 3.26/0.02* 1.29/0.276 0.88/0.451 9.06/ < 0.001*** 9.56/ < 0.001*** 9.16/ < 0.001*** 13.17/ < 0.001*** 4.36/0.005** 1.41/0.23 3.61/0.01** 11.10/ < 0.001***

*p value significant at < 0.05, **p value significant at ≤0.01, ***p value significant at < 0.001. PANSS P, N & G are Positive and Negative Syndrome Scale’s Positive, Negative and Psychopathology scores, respectively. The significant p values have been shown in bold font. Table 3 Relation between response status at 12 weeks and clinical variables. Response Status at 12 weeks

Age (in years) Duration of illness (in months) Dose of risperidone at week 1 (mg) Dose of risperidone at week 6 (mg) Dose of risperidone at week 12 (mg) PANSS P score at baseline PANSS PANSS PANSS PANSS

N at baseline G at baseline Total at baseline P at 6 weeks

PANSS N at 6 weeks PANSS G at 6 weeks PANSS Total at 6 weeks PANSS P at 12 weeks PANSS N at 12 weeks PANSS G at 12 weeks PANSS Total at 12 weeks

Non-responder

Partial responder

Responder

Drop Out

F value/P value

(N = 17)

(N = 114)

(N = 200)

(N = 88)

Mean (Std Dev.)

Mean (Std Dev.)

Mean (Std Dev.)

Mean (Std Dev.)

33.71 (8.32) (n = 17) 71.18 (54.32) (n = 16) 3.71 (1.68) (n = 17) 5.41 (1.54) (n = 17) 6.53 (1.87) (n = 17) 20.76 (8.72) (n = 17) 21.29 (7.54) 37.94 (11.03) 79.76 (21.71) 17.12 (7.47) (n = 17) 17.71 (7.29) 33.18 (9.73) 68.47 (18.65) (n = 17) 15.24 (6.39) (n = 17) 16.71 (6.18) 29.12 (7.79) 65.18 (19.25) (n = 17)

32.32 (9.09) (n = 113) 51.11 (52.02) (n = 104) 3.15 (1.45) (n = 114) 5.04 (1.68) (n = 114) 6.10 (1.61) (n = 112) 23.83 (7.27) (n = 114) 22.64 (8.08) 38.91 (10.32) 85.25 (19.40) 16.36 (5.77) (n = 114) 17.42 (6.29) 29.92 (8.20) 62.82 (17.08) (n = 114) 12.09 (4.43) (n = 114) 14.25 (5.37) 25.58 (7.01) 51.89 (14.27) (n = 114)

30.07 (9.09) (n = 199) 40.31 (45.85) (n = 198) 4.39 (1.73) (n = 200) 5.20 (1.37) (n = 199) 5.51 (1.36) (n = 197) 28.69 (5.52) (n = 200) 28.88 (7.03) 54.54 (14.47) 111.99 (21.04) 18.30 (6.27) (n = 200) 18.59 (4.44) 34.28 (9.43) 70.81 (16.32) (n = 200) 10.18 (2.70) (n = 200) 11.19 (2.76) 21.72 (5.86) 42.29 (7.06) (n = 200)

32.62 (11.14) (n = 88) 52.83 (52.85) (n = 82) 4.07 (2.00) (n = 88) 5.27 (1.10) (n = 15) -NA-

2.46/0/0.06

25.65 (6.74) (n = 88) 24.78 (7.78) 48.66 (15.50) 99.30 (25.91) 16.00 (6.13) (n = 13) 17.08 (4.46) 29.69 (8.43) 65.91 (16.91) (n = 11) –

19.19/ < 0.001**

21.65/ < 0.001**

– – –

30.26/ < 0.001** 20.40/ < 0.001** 23.13/ < 0.001**

3.12/0.02* 12.79/ < 0.001** 0.49/0.68 7.94/ < 0.001**

20.43/ < 0.001** 35.51/ < 0.001** 20.09/ < 0.001** 2.68/0.04* 1.394/0.24 6.11/ < 0.001** 10.67/ < 0.001**

*p value significant at < 0.05, ** p value significant at < 0.001.

regression using enter method was carried out with percentage change in PANSS at baseline and 12 weeks as dependent variable and genetic markers with adjustments made for age and gender.

Social Sciences (SPSS version 15, Chicago). Means and frequencies were calculated for continuous and categorical data respectively and comparison between groups done by Pearson Chi square (with-/without Yates correction) and Fischer’s exact test. Kolmogorov-Smirnov test was used to assess normal distribution of data. Paired t-test was used to compare the PANSS score at baseline, 6 and 12 weeks. Logistic bivariate 177

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Table 4 Relationship of plasma risperidone and 9-hydroxyrisperidone concentration and dose of risperidone at Chandigarh Centre. Response status at 6 weeks

Non-responder (N = 36) (Mean/SD)

Partial responder (N = 43) (Mean/SD)

Responder (N = 1) (Mean/SD)

Drop-out (N = 29) (Mean/SD)

F value/p- value

Risperidone levels at 6 weeks

26.58 (14.47) 15.57 (8.46) 42.07 (8.16) 20.14 (4.55) 2.69 (1.11) 4.8 (1.56) 6.47 (1.57) Non-responder (N = 9) 26.67 (13.79) 16.16 (5.79) 41.36 (8.83) 20.68 (3.09) 2.22 (0.83) 4 (1.63) 5.43 (1.92)

34.02 (16.27) 16.4 (7.20) 43.25 (12.09) 22.78 (6.72) 3.09 (1.04) 5.83 (1.76) 6.86 (1.64) Partial responder (N = 52) 31.47 (17.18) 16.28 (8.44) 44.06 (10.13) 22.15 (6.32) 3.04 (1.12) 5.61 (1.75) 7.02 (1.50)

13.06 (N/A) 9.14 (N/A) 22.41 (N/A) 12.37 (N/A) 2 (N/A) 4 (N/A) 8 (N/A) Responder (N = 19) 29.26 (13.32) 14.88 (6.73) 38.61 (12.08) 18.97 (4.79) 2.84 (1.01) 4.38 (1.32) 5.54 (1.66)

N/A

2.90/0.06

N/A

0.49/0.79

N/A

1.97/0.14

N/A

3.38/0.04

2.97 (1.11) 4.38 (1.32) 5.54 (1.66) Drop-out (N = 29) N/A

1.13/0.34

9-hydroxyrisperidone level at 6 weeks Risperidone levels at 12 weeks 9-hydroxyrisperidone level at 12 weeks Dose of Risperidone at week 1 Dose of Risperidone at week 6 Dose of Risperidone at week 12 Response status at 12 weeks Risperidone levels at 6 weeks 9-hydroxyrisperidone level at 6 weeks Risperidone levels at 12 weeks 9-hydroxyrisperidone level at 12 weeks Dose of Risperidone at week 1 Dose of Risperidone at week 6 Dose of Risperidone at week 12

3.69/0.015 2.41/0.07 F value/p- value 0.41/0.66

N/A

0.23/0.79

N/A

1.93/0.15

N/A

2.18/0.12

2.97 (1.11) 4.38 (1.32) 5.54 (1.66)

1.50/0.22 3.26/0.026 4.40/0.007

Dose of risperidone is in mg; concentration of risperidone and 9-hydroxyrisperidone is mentioned as ng/ml. The significant p values have been shown in bold font.

3. Results

The socio-demographic details of study participants have been provided in Table 1. At the end of 6 weeks of treatment, only 3.3% had more than 50% reduction in PANSS score, 59.7% had up to 25–50% reduction in PANSS score, and 18.4% did not respond to treatment while 78 patients (18.6%) dropped out of treatment during this period. At the end of 12 weeks of study period, 200 patients (47%) showed more than 50% decline in PANSS score, 27.2% had up to 25–50% reduction and only 4.1% were non-responders (if cut off of < 25% on PANSS is taken). Further, 10 more participants dropped out of treatment during this period.

well as week 12 (71.17 months; SD = 54.32) of treatment. At the start of study, mean dose of risperidone was highest in the responder group, however, at week 12 it was maximum for the non-responder group. It is an expected finding, as those who respond to treatment do it at initial stages and require lower dosages as compared to the non-responders (Kinon et al., 2010). The extra-pyramidal symptoms arising due to risperidone were treated with trihexyphenidyl and we did not find any patient who developed intolerable adverse effects leading or drug toxicity (Tables 2 and 3). With respect to the assessment on PANSS scale, the scores on positive, negative, general psychopathology and total PANSS scale were highest at baseline and lowest at 6 weeks of treatment for the responder group. Even at the end of 12 weeks of treatment, these were significantly lower in the responder group. Paired t-test was used to compare PANSS score for whole study group (excluding drop outs) at baseline, week 6 and 12 and we found significant differences between scores at baseline vs week 6 (p < 0.001), week 6 vs week 12 (p < 0.001) and baseline vs week 12 (p < 0.001). At the Chandigarh centre, we evaluated the plasma concentration of the risperidone and its metabolite 9-hydroxyrisperidone. However, no significant differences were found with respect to plasma drug concentration and response to treatment with risperidone (Table 4).

3.2. Relationship between response to treatment and clinical variables

3.3. Genetic analysis

As mentioned earlier, we measured the response to treatment by change in PANSS score from baseline to that at 6 and 12 weeks. Based on this, we had four groups’ viz. non-responders, partial responders, responders and drop outs. The clinical variables like duration of illness, dose of risperidone, scores on PANSS showed significant differences amongst these groups. The duration of illness was significantly higher in the non-responder group at week 6 (62.75 months; SD = 58.11) as

We compared the various genetic polymorphism evaluated in the index study with 150 healthy controls (unrelated to patients) and these were found in Hardy Weinberg Equilibrium (data not shown). We found significant differences in the frequency of SNPs rs180498 (Taq1D) polymorphism (p = 0.01) and 516C > T (rs 6305; p = 0.001) across the groups (Table 5). As shown in Table 6, when the drop outs were excluded and comparisons were done between responders and non-

A total 443 patients suffering from schizophrenia were included in present study across the centers. Twenty- four patients were not included in the study for analysis due to lack of sufficient records or blood samples and 88 patients dropped out at various stages. Since we had complete genetic data of the dropped out patients, so, they were included in the genetic analysis. However, while analyzing PANSS score from baseline to end of 12 weeks, we excluded the drop outs. 3.1. Socio-demographic profile of participants

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binds strongly with the alpha-adrenergic receptors (α −1 & - 2) and some affinity for the histaminergic (H1) receptors (Leysen et al., 1988; Mauri et al., 2014). Furthermore, the differential action of risperidone on the D2 and 5-HT2A receptors in various brain areas leads to the atypical clinical effects. To elaborate, 5-HT2A antagonism in the nigrostriatal pathway leads to release of dopamine, which in turn competes with risperidone to reverse the dopaminergic receptor blockade and thus has lesser potential to cause extrapyramidal side effects. However, in the meso-cortical pathway, where the 5-HT2A receptor are denser, their blockade leads to again release of dopamine which in turn is beneficial for negative symptoms. Similarly, in the tubero-infundibular pathway, 5- HT2A antagonism may theoretically prevent prolactin release caused by dopamine receptor blockade by the antipsychotic agent. In the mesolimbic pathway, serotonin antagonism is unable to reverse the dopamine receptor antagonism, so, risperidone is able to reduce positive symptoms of psychosis. The present study demonstrated significant differences for the DRD2 Taq1D polymorphism and 5-HT2A 516C > T gene polymorphism across the groups based on response to risperidone treatment. Additional significance in gene polymorphism of CYP2D6*4 was noted if drop outs were excluded from analysis. Non-responders had more number of T alleles for 5 HT2A receptor (516C > T) gene. The Taq1D2D2 and C516T-CT genotypes are more likely to be associated with poorer response to risperidone. The dopaminergic D2 receptor is located on chromosome 11q22 consisting of eight exons separated by seven introns with several SNPs with variable frequencies in different populations. Earlier studies have shown that the clinical efficacy of antipsychotics is highly correlated with their binding affinity with DRD2 receptor (Kapur and Mamo, 2003). Some of studies have shown A1 allele carriers of DRD2 Taq1A (rs1800497) gene to respond well to antipsychotics, while others have reported A2/A2 genotypes to be associated with larger reductions in PANSS score (Suzuki et al., 2000; Vijayan et al., 2007; Zhang et al., 2010). Similarly, contradictory findings have been reported with respect to Taq1 B (rs1079597) gene in which the B2 (T) allele was associated with higher response rate to clozapine in African American patients (Hwang et al., 2005), although negative results were found in another studies (Dahmen et al., 2001; Xing et al., 2007). In our study, we did not find any association of Taq1A or B polymorphism and response to treatment with risperidone, instead we found significant difference in Taq1D polymorphism amongst the different groups which is in consonance with previous study from South India (Vijayan et al., 2007). The D1D1 genotype was associated with better response to treatment with antipsychotic in the index study as well as earlier South Indian study but unlike the latter we did not find significant association of D1D2 genotype with the response and it did not fit into recessive or dominant model. The Ser311Cys (rs1801028) mutation at codon 311 in exonic region of DRD2 receptor gene has half the affinity for dopamine in comparison to wild variant. There are contrasting results of association of the Cys 311 allele with schizophrenia with some showing positive association (Glatt et al., 2003) while most of others with negative results (Chen et al., 1996; Alenius et al., 2008). The Cys 311 allele frequency also varies across ethnic populations with a range of 0.01–0.05 in Europeans and 0.00–0.06 in Asians. Interestingly, the previous study from India reported a higher frequency of Cys 311 allele (0.11 in patients) that was completely absent in our study participants. Vijayan et al. (2007) concluded it to be due to ethnic bias in South Indian population rather than any association with schizophrenia and like in our study no association with response to treatment was found. The 5HT2A gene consists of at least seven SNPs in the coding region with five of them leading to mutations in amino acid sequence and two of them viz. T102C and C516T being silent mutations (Davis et al., 2006; Bertola et al., 2007). Although, studies have shown association of these two genes with schizophrenia but research is scarce with respect to association with response to treatment with antipsychotics (Bertola

Table 5 Frequencies of genetic markers in study participants. Response status at 12 weeks

Taq1A A1A1 A1A2 A2A2 Taq1B B1B1 B1B2 B2B2 Taq1D D1D1 D1D2 D2D2 Ser311Cys exon 7 Ser/Ser A1438G AA AG GG 516C > T CC TC TT 5-HT2A 102T > C TT TC CC CYP2D6*4 wt/wt wt/m m/m CYP2D6*10 wt/wt wt/m m/m

Nonresponders

Partial responders

Responders

Drop Outs

(n = 17)

(n = 114)

(n = 200)

(n = 88)

3 (0.18) 7 (0.41) 7 (0.41)

9 (0.08) 52 (0.46) 53 (0.46)

18 (0.09) 96 (0.48) 86 (0.43)

5 (0.0.06) 38 (0.43) 45 (0.51)

2 (0.11) 5 (0.29) 10 (0.58)

4 (0.03) 54 (0.47) 56 (0.49)

20 (0.10) 89 (0.45) 91 (0.46)

4 (0.04) 33 (0.37) 51 (0.58)

Chi square/ p value

5.08/0.82

9.87/0.13

16.31/ 0.01** 2 (0.11) 9 (0.52) 7 (0.41)

13 (0.11) 64 (0.56) 37 (0.32)

31 (0.16) 70 (0.35) 99 (0.49)

16 (0.18) 31 (0.35) 41 (0.47) NA

17 (1.00)

114 (1.00)

200 (1.00)

88 (1.00)

3 (0.18) 5 (0.29) 9 (0.52)

14 (0.12) 72 (0.63) 28 (0.24)

29 (0.14) 106 (0.53) 65 (0.33)

15 (0.17) 48 (0.54) 25 (0.28)

8.97/0.17

22.71/ 0.001** 15 (0.88) 2 (0.11) 0 (0)

102 (0.89) 12 (0.11) 0 (0)

197 (0.98) 3 (0.01) 0 (0)

83 (0.94) 3 (0.03) 2 (0.02) 1.70/0.94

3 (0.18) 9 (0.52) 5 (0.29)

16 (0.14) 61 (0.53) 37 (0.32)

37 (0.18) 108 (0.54) 55 (0.28)

15 (0.17) 45 (0.51) 28 (0.32)

11 (0.64) 5 (0.29) 1 (0.05)

77 (0.67) 34 (0.29) 3 (0.02)

158 (0.79) 34 (0.17) 8 (0.04)

64 (0.72) 22 (0.25) 2 (0.02)

15 (0.88) 2 (0.11) 0 (0)

89 (0.78) 25 (0.21) 0 (0)

172 (0.86) 27 (0.13) 1 (0.005)

76 (0.86) 11 (0.12) 1 (0.01)

8.55/0.20

6.31/0.38

*p value significant at < 0.05, ** p value significant at ≤0.01, *** p value significant at < 0.001

responders at 12 weeks of treatment, the aforementioned differences still persisted and additionally, the frequency of CYP2D6*4 (rs3892097) gene polymorphism showed significant difference between the two groups (p = 0.02). However, these differences in genetic polymorphism did not follow dominant or recessive models for respective genes. The 516T allele in 5HT2A receptor gene was more frequently observed in non-responders. The significant associations were additionally analyzed using bivariate logistic regression analysis with dependent variable being response status at end of 12 weeks and drop outs excluded from the analyses. Initially, each independent variable was analyzed and than adjustments were done for age and gender to generate a goodness of fit model. As shown in Table 7, DRD2 Taq 1 D2D2 and 5HT2A- C516T CT genotype predicted poorer response as compared to D1D1 and C516T CC genotype. The CYP2D6*4 genotype did not show significant association in this model.

4. Discussion Risperidone, an atypical antipsychotic, is a benzisoxazole derivative which has affinity for both dopaminergic and serotonergic receptors. It has strong affinity for D2- dopaminergic receptors which is almost three times higher as compared to D3 and D4 dopaminergic receptors. Risperidone also strongly binds to 5-HT2A as well as 5-HT7 receptors and the affinity ratio for 5-HT2A/D2 receptors is almost 20. It also 179

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Table 6 Association between genetic markers and response status at 12 weeks. Response status at 12 weeks

Taq1A A1A1 A1A2 A2A2 Taq1B B1B1 B1B2 B2B2 Taq1D D1D1 D1D2 D2D2 Ser311Cys exon 7 Ser/Ser 5-HT2A A1438G AA AG GG 516C > T CC TC TT 102T > C TT TC CC CYP2D6*4 wt/wt m/wt m/m CYP2D6*10 wt/wt m/wt m/m

Genotype frequency

p value

Responders (n = 200)

Non-responders (n = 131)

18 (0.09) 96 (0.48) 86 (0.43)

12 (0.09) 59 (0.45) 60 (0.46)

20 (0.10) 89 (0.45) 91 (0.46)

6 (0.04) 59 (0.45) 66 (0.50)

31 (0.16) 70 (0.35) 99 (0.49)

15 (0.11) 73 (0.56) 43 (0.32)

0.10*** < 0.001 0.04* < 0.001** 0.90***

200

131

NA

29 (0.14) 106 (0.53) 65 (0.33)

17 (0.13) 77 (0.58) 37 (0.28)

197 (0.98) 3 (0.02) 0 (0)

117 (0.89) 14 (0.11) 0 (0)

37 (0.18) 108 (0.54) 55 (0.28)

19 (0.14) 70 (0.53) 42 (0.32)

158 (0.79) 34 (0.17) 8 (0.04)

88 (0.67) 39 (0.29) 4 (0.03)

172 (0.86) 27 (0.13) 1 (0.005)

104 (0.79) 27 (0.20) 0 (0)

0.86 0.99* 0.67** 0.92*** 0.18 0.15* 0.78

**

0.58 0.64* 0.40**

0.91*** < 0.001 < 0.001* NA** NA*** 0.51 0.57* 0.60

**

0.33*** 0.02 0.01# 0.32## 0.89### 0.17 0.12# NA## NA###

Allele frequency

p- value

Responders (n = 200)

Non- responders (n = 131)

A1 = 132 (0.33) A2 = 268 (0.67)

A1 = 83 (0.0.32)

0.78

A2 = 179 (0.68) 0.18 B1 = 129 (0.32) B2 = 271 (0.68)

B1 = 71 (0.27) B2 = 191 (0.73)

D1 = 132 (0.33) D2 = 268 (0.67)

D1 = 103 (0.39) D2 = 159 (0.61)

A = 164 (0.41) G = 236 (0.59)

A = 111 (0.42) G = 151 (0.38)

C = 397 (0.99) T = 3 (0.007)

C = 248 (0.95) T = 14(0.05)

T = 182 (0.46) C = 218 (0.54)

T = 108 (0.41) C = 154 (0.59)

wt = 350 (0.88) m = 50 (0.12)

wt = 215 (0.83) m = 47 (0.17)

wt = 371 (0.93) m = 29 (0.07)

wt = 235 (0.90) m = 27 (0.10)

0.11

0.78

< 0.001

0.31

0.06

0.21

p values for chi square/Fischer exact test for *Wild vs Hetero, **Hetero vs Homo, ***Wild vs Homo. For the CYP2D6 genotype- Wt- wild type, m- mutant and #wild/wild vs mutant/wild, ## mutant/wild vs mutant/mutant, ### mutant/mutant vs wild/wild. The significant p values have been shown in bold font.

antipsychotics while others reported that those with acute exacerbations of schizophrenia and negative symptoms responded better if patients had C/C genotype (Lane et al., 2002) and T/T genotype of T102C polymorphism, respectively (Kim et al., 2008). However, we did not find any association of T102C gene polymorphism and treatment response that is in accordance with some other research (Masellis et al., 1998; Lin et al., 1999; Alenius et al., 2008) but in contradiction to few others which reported significant response in those with the C/C genotype (Lane et al., 2002; Kim et al., 2008). Interestingly, we found significant association of C516T gene polymorphism and non- response to risperidone treatment. In the logistic regression model too, the CT genotype was more often associated with non-response. No previous study had reported such a finding. For the A-1438G SNP consistent positive findings had been reported where G/G genotype was associated with low response rates (Kakihara et al., 2005) but it was not so in index study. With respect to CYP2D6 gene polymorphisms, significant differences were found for CYP2D6*4 genotype and response to risperidone, but it did not persist in the regression model. No associations were noted for CYP2D6*10 genotypes and treatment response. These results are in contradiction with previous studies but its difficult to compare with many others which used combinations of genotypes or different definitions (Bartecek et al., 2012; ; Kahihara et al., 2005; Jovanovic et al., 2010). Although, at the Chandigarh Center the plasma concentrations of risperidone and its active metabolites were measured and correlated with CYP2D6 polymorphisms, but that is out of purview of

Table 7 Logistic Regression analysis showing association between response at 12 weeks and genetic variables. Variable

B

Standard Error (B)

Odds Ratio

C.I.

p- value

Age (in years) Gender Female (Ref) Male Taq1D D1D1 (ref) D1D2 D2D2 C516T CC (ref) CT CYP2D6*4 Wt/wt (ref) Wt/m m/m

−0.027

0.013

0.973

0.949–0.999

0.042

0.616

0.256

1 1.851

1.121–3.059

0.016

−0.025 −0.824

0.386 0.261

1 0.976 0.439

0.458–2.078 0.263–0.733

0.949 0.002

−2.242

0.664

1 0.106

0.029–0.390

0.001

−0.389 −1.191

0.697 0.731

1 0.678 0.304

0.173–2.658 0.073–1.272

0.577 0.103

Logistic regression analysis done with dependent variable- Response status at 12 weeks of treatment (Non-response-0, response = 1), independent variables- age in years, gender (male = 1, female = 2), Taq1 D, C516T and CYP2D6*4 gene polymorphisms.

et al., 2007). Joober et al. (1999) reported that persons suffering from schizophrenia, who were treatment resistant and had C/C genotype for T102C gene showed poor response to clozapine as well as typical 180

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this paper. In this paper, we tried to explore the genetic variants, using the candidate genes implicated in schizophrenia, which can effect the treatment response with risperidone in an Indian setting. Previous pharmaco-genetic research has consistently implicated some of gene polymorphisms in dopaminergic, serotonergic receptors, and enzymes metabolizing antipsychotic drugs (like CYP2D6) with the clinical efficacy as well as adverse drug effects. Unlike most of previous studies we attempted to analyze multiple SNPs at different candidate genes and report some of the findings to be in congruence with earlier research, while others in contradiction to the previous findings of studies including those from India. At present, though it is difficult to utilize the findings of index study into clinical practice, but it adds to our understanding of the complex interactions of the genetic polymorphism and the phenotypic expression in form of clinical response to antipsychotic drugs in persons with schizophrenia. The selection of a large cohort and multi-center involvement in the index study are strengths of study. Another strength was the conduction of genetic analysis at one center with stringent control of procedures. The selection of multiple SNPs of different implicated genes in schizophrenia and metabolism of risperidone is a strength of this study on one hand, but, in the present era of genome wide association studies, it is a weakness too. However, the repeated use of same outcome measure by same observer could have led to some bias which was not taken care of in study. The only use of symptom scale (PANSS) instead of using an additional scale to assess functional outcome is also a limitation. 5. Conclusion In the present study, which is one of largest pharmaco-genetic studies from India, significantly different results are reported from non-/ Indian studies like absence of Ser311Cys mutations, significant relationship of Taq 1D2D2 genotype, and non- sense mutation of C516T with non-response to treatment with risperidone. We also observed that a large number of patients who respond partially at early stage of treatments may respond to risperidone at later stages of treatment. It is emphasized that further pharmaco-genetic research with established genotypes as well as novel biomarkers and their association with response to antipsychotic treatment in Indian context shall be undertaken. It will have its clinical implications in form of selection of suitable antipsychotic according to genotype as well as avoidance of adverse drug effects in ethnic populations. Conflict of interest None. Acknowledgement This study was supported by a research grant from the Indian Council of Medical Research (ICMR), New Delhi, India (Ref. No. 58/27/ 2008-BMS dated 24.03.2011). References Alenius, M., Wadelius, M., Dahl, M.L., Hartvig, P., Lindstrom, L., Hammarlund-Udenaes, M., 2008. Gene polymorphism influencing treatment response in psychotic patients in a naturalistic setting. J. Psychiatr. Res. 42, 884–893. Bartecek, R., Jurica, J., Zrustova, J., Kasparek, T., Pindurova, E., Zourkova, A., 2012. Relevance of CYP2D6 variability in first-episode schizophrenia patients treated with risperidone. Neuro. Endocrinol. Lett. 33, 236–244. Bertola, V., Cordeiro, Q., Zung, S., Miracca, E.C., Vallada, H., 2007. Association analysis between the C516T polymorphism in the 5-HT2A receptor gene and schizophrenia. Arq. Neuropsiquiatr. 65, 11–14. Cardno, A.G., Gottesman, I.I., 2000. Twin studies of schizophrenia: from bow-and- arrow concordances to star wars Mx and functional genomics. Am. J. Med. Genet. 9, 12–17. Cartwright, A., Wilby, K.J., Corrigan, S., Ensom, M.H., 2013. Pharmacogenetics of risperidone: a systematic review of the clinical effects of CYP2D6 polymorphisms. Ann. Pharmacother. 47, 350–360.

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