DRD and GRIN2B polymorphisms and their association with the development of impulse control behaviour among Malaysian Parkinson’s disease patients

This study involved samples from 91 PD patients obtained from two larger clinical studies on ICB among PD patients, in two tertiary centres in Kuala Lumpur [Universiti Kebangsaan Malaysia Medical Centre (UKMMC) and Universiti Malaya Medical Centre (UMMC)]. In both centres, patients with idiopathic PD (H&Y Stages I-IV), diagnosed by two movement disorder neurologists (NMI and SYL), and on dopaminergic medications were screened for ICB using the QUIP questionnaire. The diagnosis of ICB was based on previously established criteria published elsewhere [28]. The QUIP questionnaire is a validated questionnaire for the detection of ICB in PD. It consists of 3 sections: Section 1 assesses ICDs (sexual, gambling, eating, and buying behaviour), Section 2 assesses other compulsive behaviours, such as compulsive buying, hypersexuality, punding, hobbyism, and walkabout, and Section 3 assesses compulsive medication use [28]. Cases and controls were determined based on QUIP positivity. Fifty-two cases (QUIP positive or PD-ICB) and 39 controls (QUIP negative) were selected randomly for this study. This study was conducted in accordance with the Declaration of Helsinki and was approved by Institutional Ethics Committee from both centres (UKM-DLP-2011-048 for UKMMC and MEC No: 745.81 for UMMC). Written informed consent for participation in the study was obtained from all recruited participants.

Genomic DNA from blood samples was extracted from buffy coat leukocytes using a QiaAmp DNA Blood Mini Kit (Qiagen, Limburg, The Netherlands) according to the manufacturer’s protocol. The concentration and purity (1.7–1.9) of DNA samples were measured using NanoVue™ Plus (GE Healthcare, Berkshire, UK), and the integrity of DNA was analysed using 0.8% agarose gel electrophoresis.

Ten primer sets were designed using Primer3Plus to detect 11 polymorphic loci in DRD1 (rs4532 and rs4867798), DRD2 (ANKK1 rs1800497, rs104894220, and rs144999500), DRD3 (rs3732783 and rs6280), DRD4 rs1800443, DRD5 rs144132215 and GRIN2B rs7301328, which were mined from the National Center for Biotechnology Information (NCBI) database. The primer set for DRD1 rs265981 was synthesized based on a previous study [29]. Secondary structure was predicted using DINAMelts software, which also was used to calculate the melting temperature [30]. All primers were optimized using gradient polymerase chain reaction (PCR) and real-time PCR prior to HRM analysis. Primer sequences and properties are detailed in Table 1.

The HRM analysis was carried out in 10 μl reaction volumes containing 30 ng genomic DNA, 0.7 μM primers, and 1× Type-It HRM-PCR master mix (HotStarTaq Plus DNA Polymerase, EvaGreen Dye, and an optimized concentration of Q-solution, dNTPs, and MgCl₂; Qiagen). The primer pairs used for HRM analysis are summarised in Table 1. Reactions were run on a 5-plex HRM real-time PCR machine (Rotor-Gene™ 6000, Qiagen) consisting of 95°C for 5 min for initial denaturation, 45 cycles of 95°C for 10 sec and 60°C for 30 sec followed by a high resolution melting phase (65-90°C for 2 sec). Data were analysed using Rotor-Gene 6000 Series Software 1.7. To ensure accuracy, raw data were selected according to the following criteria.

A total of 17% of samples were selected for DNA sequencing analysis to confirm the HRM genotyping results. Samples selected from each variant cluster were purified using a Fragment DNA purification kit (Intron Biotechnology, South Korea) followed by Sanger sequencing analysis to confirm the nucleotide polymorphisms. Sequences were analysed and alignments were performed using DNA Baser v3.5.4 software [31]. A Phred score of 20 or greater was used to indicate high quality sequencing results.

SNPStats [32] was used to assess genotypic frequencies, Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium (LD) among PD patients with or without ICB. The HWE test was performed to examine the genotypic distributions of polymorphisms in PD-ICB patients. The HWE deviation of allele and genotype frequencies was assessed by Fisher’s exact analysis. The logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI) for associations between each locus and the presence of PD-ICB. The analysis was used to estimate the regression coefficient and the association in the log odds of the subject with a polymorphism. The association with disease is modelled depending on the response variable. The variable response was defined as a binary response (categorical variable) and logistic regression was used to assess the proportion of variation in the response between the polymorphisms and other factors such as gender, age, ethnicity, dosage of medication and duration of PD. The association was based on co-dominant, dominant, recessive, overdominant, and log-additive models between each polymorphism in PD-ICB patients. The right model was selected based on the significant p value and the lowest Bayesian Information Criterion (BIC) score. Pair-wise LD statistics (D’ and r²) were used to determine the robustness of LD between polymorphisms. In all statistical analyses, comparisons were considered to be significant when p < 0.0167 after Bonferroni correction for multiple comparisons [33].

A total of 91 PD patients with (QUIP positive or cases; n = 52) and without ICB (QUIP negative or controls; n = 39) were recruited from a total of 280 PD patients from two medical centres and were analysed. Comparison between the cases and controls in terms of age, sex and racial distribution is presented in Table 2. The mean disease duration for the cases and controls were 8.2 ± 0.7 and 5.8 ± 0.7 years, respectively. Most PD-ICB patients received a combination therapy consisting of levodopa and dopamine agonist (54%) followed by levodopa monotherapy (29%). In the control group, 39% of patients received levodopa alone whereas 36% of patient received a combination of levodopa and dopamine agonist. The other control (15%) and PD-ICB (13%) patients received dopamine agonist alone. The mean daily levadopa dose and dopamine agonist dose were higher in the cases than the controls (Table 2).

In this study, 11 polymorphisms were analysed, but only 7 polymorphisms showed allelic variation [DRD1 (rs4532, rs4867798, rs265981), DRD2/ANKK1 rs1800497, DRD3 (rs3732783 and rs6280), and GRIN2B rs7301328] (Figure 1). The other 4 polymorphisms [DRD2 (rs104894220 and rs144999500), DRD4 rs1800443, and DRD5 rs144132215] screened were found to be monomorphic (Additional file 1: Figure S1). We have successfully established 11 HRM assays for the detection of polymorphisms in DRD1-5 and GRIN2B. The HRM assays were very efficient, sensitive, and specific in identifying nucleotide transitions (C > T or T > C) and transversions (G > C) in our samples. Approximately 17% of the total numbers of HRM reactions were sequenced and the results were 100% in agreement with the HRM profiles. The differential melting curves for the 7 corresponding polymorphisms (C > T, T > C, or G > C) clearly distinguished the wild-type from the variant genotypes. The amplicons derived from the DRD1 rs4532, DRD2/ANKK1 rs1800497, and DRD3 rs6280 mutant alleles showed a single nucleotide change from C to T. Polymorphisms in DRD1 rs4867798, DRD1 rs265981, and DRD3 rs3732783 showed a single nucleotide change from T to C. Analysis of the amplicons derived from GRIN2B rs7301328 showed a single nucleotide change from G to C. All analysed SNPs were deposited in dbSNP build B145 (http://​www.​ncbi.​nlm.​nih.​gov/​SNP/​) with the following accession numbers; ss1713988434 (rs265981), ss1713988435 (rs4532), ss1713988436 (rs4867798), ss1713988437 (rs104894220), ss1713988438 (rs144999500), ss1713988439 (rs1800497), ss1713988440 (rs3732783), ss1713988441 (rs6280), ss1713988442 (rs1800443), ss1713988443 (rs144132215) and ss1713988444 (rs7301328).

No significant deviation was observed in the distribution of genotype and allele frequencies for all polymorphisms (except for DRD3 rs3732783) based on HWE analysis between the case and control groups (Table 3). The frequency of the C allele for DRD3 rs3732783 was significantly higher (p < 0.01) in the PD population. Moreover, pair-wise LD measurements between polymorphisms in DRD1 based on the Dʹ statistic showed no difference in LD among the polymorphisms (rs4532, rs4867798, and rs265981). By contrast, as expected, DRD3 showed strong LD (D′ > 0.99) between polymorphisms (rs3732783 and rs6280) that could be observed using multiple-SNP analysis (Table 4). In multiple haplotype analysis of DRD1 and DRD3, we detected low frequencies for all alleles (Additional file 2: Table S1).

We evaluated the associations between polymorphisms in DRD and GRIN2B with ICB risk among Malaysian PD patients (Table 5). Among the 7 polymorphisms examined, only 4 were associated with the development of ICB among PD patients. Logistic regression analysis (adjusted for gender, age, ethnicity, dosage of medication and duration of PD) showed that there was a significantly higher risk of ICB that was associated with the DRD1 rs4867798 C allele (OR = 24.53; 95% CI, 1.68-357.28; p = 0.0054) and the GRIN2B rs7301328 C allele (OR = 25.07; 95% CI, 1.30-483.41; p = 0.0097). Similarly, the DRD1 rs4532 T allele (OR = 21.33; 95% CI, 1.97-230.64; p = 0.0024) and T allele in DRD2/ANKK1 rs1800497 (OR = 3.77; 95% CI, 1.38–10.30; p = 0.0044) were significantly associated with a higher risk of developing ICB in PD patients. The DRD1 rs4867798 and GRIN2B rs7301328 polymorphisms showed a recessive mode of inheritance, suggesting that the dominant allele has an advantage over the recessive allele. Notably, DRD1 rs4532 showed an overdominant mode of inheritance in which heterozygous patients (TC) have an increased risk of ICB compared to homozygous patients (CC or TT). By contrast, the T allele in DRD2/ANKK1 rs1800497 was shown to have an additive genetic effect, whereby the risk of a patient with 2 copies of the T allele doubles compared to a heterozygous patient. No association was detected between the other polymorphisms and ICB in PD patients.