Association between genetic variation in the dopamine system and motor recovery after stroke

Abstract

Background: The dopamine system plays a key role in motor learning and neuroplasticity. Several studies have studied the efficacy of dopaminergic drugs in enhancing motor recovery after stroke, but the effects are controversial. Although genetic variations in plasticity-related genes influence each individual’s capacity for recovery after stroke, limited studies have investigated the effects of polymorphism of dopamine-related genes.

Objective: We aimed to investigate the association between motor recovery in stroke patients and polymorphisms in the dopamine-related genes catechol-O-methyltransferase (COMT), dopamine receptor D1 (DRD1), DRD2, and DRD3.

Methods: We enrolled 74 patients with first-ever stroke (42 males, 32 females, mean age: 61.4±14.1 y). During admission, blood samples were collected, and the genotypes of COMT, DRD1, DRD2, and DRD3 were analyzed. The primary outcome was assessed with Fugl-Meyer Assessment (FMA) at 1 week, 3 months, and 6 months after stroke; secondary outcomes were assessed with Functional Independence Measure (FIM) and mini-mental state examination at 3 and 6 months after stroke. The association between polymorphisms and functional outcome was analyzed.

Results: There were no significant associations between COMT polymorphisms and FMA or FIM scores at 1 week after stroke or between DRD1, DRD2, or DRD3 genotypes and FMA or FIM scores at any point. COMT genotypes were significantly associated with FMA and FIM at 3 months (p < 0.01 and p < 0.05, respectively) and at 6 months (p < 0.01 and p < 0.05, respectively).

Conclusion: These data suggest that genetic variation of dopamine-related genes may affect motor recovery after stroke and that COMT polymorphism could be useful for predicting motor recovery.

Keywords

Stroke single-nucleotide polymorphism dopamine rehabilitation

1 Introduction

Stroke is the second most common cause of death worldwide and can lead to serious and long-term disability. When stroke occurs, recovery starts immediately and involves many biological factors, including when treatment starts after stroke and the location and size of the injured brain area (Zaleska et al., 2009). The genetic and epigenetic mechanisms behind such responses are receiving attention as potential treatment targets (Schweizer et al., 2013). Some of these genes, including variants of APOE ɛ4 (Cramer et al., 2012), IGF1 (rs7136446) (Aberg et al., 2013), COX-2 (rs5275), and GPIIIa (rs5981), among others, have been linked to functional recovery after stroke (Maguire et al., 2011).

Dopamine is a neurotransmitter that plays essential roles in diverse brain functions such as motor, reward, learning, and neuroplasticity (McAllister, 2009). Polymorphisms of the dopamine receptors (DR) and genes encoding dopamine-degrading enzymes cause individual differences in learning (Doll et al., 2011), and the prefrontal and striatal activation associated with cognitive flexibility and working memory is related to the diversity of dopaminergic gene expression (Krugel et al., 2009). If polymorphisms cause reduced dopamine transmission, learning and cognitive function deteriorates. In contrast, if dopamine transmission increases, many behaviors improve (Egan et al., 2008). Some studies have reported improved motor functioning in stroke patients upon treatment with dopamine (Floel et al., 2001), whereas other studies have reported no effect on motor outcome (Cramer et al., 2007).

It is speculated that understanding the genetic variations that affect motor learning and neuroplasticity could help predict motor recovery after stroke. Precise understanding of the various factors related to functional recovery and the response to drugs and therapies after stroke is crucial for developing rehabilitation treatment strategies for individual patients. To implement patient-specific treatment from many different viewpoints and to increase neural recovery in stroke patients, research on specific genes known to affect brain plasticity is needed. To date, most studies have focused on BDNF and APOE polymorphisms among genes with the potential to affect neural recovery after brain injury.

Considering the role of dopamine in motor learning and brain plasticity, dopamine-related gene polymorphisms might be useful biomarkers for stroke recovery. We hypothesized that genetic polymorphisms affecting dopamine neurotransmission influence motor learning and motor recovery after stroke and aimed herein, to evaluate the individual and combined effects of various polymorphisms by analyzing four dopamine-related genes:catechol-O-methyltransferase (COMT), DRD1, DRD2, and DRD3. To assess the utility of polymorphisms of these genes as biomarkers for stroke recovery, we analyzed the effects of individual gene polymorphisms on functional recovery in stroke patients.

2 Methods

2.1 Patient selection

Between January 2013 and April 2015, we enrolled 76 acute stroke patients who were diagnosed by brain magnetic resonance imaging or computed tomography and treated as in-patients at the Konkuk University Medical Center Department of Neurology or Neurosurgery. Patients were enrolled within 7 days after symptoms occurred and exhibited motor impairment (Fugl-Meyer Assessment [FMA] score < 100 at baseline assessment). The objectives and goals of the study were explained in detail to all participants, confidentiality was promised, and participants were notified of their right to withdraw; patients or their legal guardians voluntarily gave their written consent for genetic testing. Patients were excluded if they were younger than 18 years old; had a history of brain disease; were receiving therapies for a specific genetic disease or had a diagnosis requiring such therapies; showed aphasia, apraxia, or cognitive impairments at a level at which it was difficult to accurately perform functional tests; had diseases in peripheral nerves or muscles; or exhibited very severe motor impairment (FMA score≤36) (Duncan et al., 1994). The study was approved by the the Konkuk University Institutional Review Board.

2.2 Specimen handling

We collected ∼10 mL of blood from each participant. Blood samples were preprocessed to separate serum from whole blood, and 5 mL of serum and whole blood were separately stored. DNA was extracted from 5 mL of whole blood and stored at –70°C after confirming the DNA concentration, purity, and completeness.

2.3 Analysis of gene polymorphisms

Dopamine-related gene polymorphisms were analyzed by the polymerase chain reaction (PCR)-direct sequencing method using PCR amplification of the target gene loci and processing with the appropriate restriction enzymes. Primer sequences and restriction enzymes were chosen from previous reports for COMT rs4680 (Berthele et al., 2005), DRD1 rs4532 (Limosin et al., 2003), DRD2 rs1800497 (Noble et al., 1994), and DRD3 rs6280 (Woo et al., 2002). Details of the primer sequences are follows:

COMT: forward, 5′-ATCCAAGTTCCCCTCTCTCC-3′; reverse, 5′-GGGTTTTCAGTGAACGTGGT-3′

DRD1: forward, 5′-GGCTTTCTGGTGCCCAAGACAGTG-3′; reverse, 5′-AGCACAGACCAGCGTGTTCCCCA-3′

DRD2: forward, 5′-GAACATCACGCAAATGTCCA-3′; reverse, 5′-CCTTGCCCTCTAGGAAGGAC-3′

DRD3: forward, 5′-GCTCTATCTCCAACTCTCACA-3′; reverse, 5′-AAGTCTACTCACCTCCAGGTA-3′

From the sequencing results, genetic variant types were classified by comparing multiple nucleic acid sequences, and Sequencher 5.3 (Gene Code Corporation) was used to search for variants.

2.4 Functional assessment

Primary and secondary outcomes were measured by FMA and Functional Independence Measure (FIM), respectively. The severity at the initial stage was evaluated within 7 days after the occurrence of stroke using FMA, National Institutes of Health stroke scale (NIHSS), and Korean mini-mental state examination (K-MMSE). An occupational therapist blinded to the patient genotypes performed functional assessments at discharge and at 3 and 6 months post-stroke.

2.5 Statistical analysis

To compare the FMA and FIM scores based on individual gene polymorphisms, Mann-Whitney and Kruskal-Wallis tests were performed. Analysis of covariance was performed to determine single-nucleotide polymorphism (SNP)-related differences in motor and functional outcomes. Age, stroke type, and initial NIHSS score were used as covariates in order to adjust motor impairment and initial stroke severity at the time of admission. Genes that showed significant results were further analyzed using repeated measures analysis of variance (RM ANOVA) to examine SNP-related differences in motor and functional outcomes at different time points. Statistical analyses were performed with SPSS version 17 (SPSS Inc., Chicago, IL, USA), and statistical significance was defined as p < 0.05.

3 Results

3.1 Patient characteristics

Out of 76 patients who participated in the study, data were analyzed from 74 patients (32 females [43.2%] and 42 males [56.8%]) for whom complete extraction of DNA was successful. At 3 months post-stroke, functional testing was performed on 66 patients. At 6-months post-stroke, follow-up evaluation was conducted for 60 patients (Fig. 1). The average age was 61.4±14.1 years. Forty-six patients (62.2%) suffered a cerebral ischemia, and 28 patients (37.8%) suffered a cerebral hemorrhage. Stroke occurred on the right side in 45 patients (60.8%), on the left side in 27 (36.5%), and on both sides in two (2.7%; Table 1).

3.2 Genotypes and allele frequencies

Table 2 shows the results from the frequency analyses on the genotypes, alleles, and allele carriers for individual genes. The findings for COMT, DRD1, DRD2, and DRD3 are similar to previous reports on the frequency of genotype expression for individual genes in healthy Koreans (Forero et al., 2015; Lim et al., 2012).

3.3 Comparison of motor recovery with gene polymorphisms

There was no difference in the baseline characteristics and initial stroke severity based on allele-carrier type in any of the four individual genes (Table 3).

Additionally, for the COMT polymorphism, the Met(–) patient group showed higher FMA and FIM scores at discharge, and at 3- and 6-months post-stroke than the Met(+) group after adjusting for initial stroke severity, age and stroke type (Table 4). Moreover, the FMA and FIM scores based on the genotype were significantly different, as assessed by RM ANOVA, at all follow-up time points (p < 0.05).

No other individual alleles showed any effect on initial stroke severity or stroke recovery (Fig. 2).

4 Discussion

To our knowledge, this is the first study to examine the effects of diverse polymorphisms on recovery in stroke patients by analyzing the polymorphisms of four genes involved in dopamine neurotransmission, which affects neuroplasticity after stroke. The results showed that the Met allele of COMT was useful in predicting patient prognosis after stroke.

Cramer and colleagues (Cramer et al., 2012) reported that polymorphisms of dopamine genes (DRD1, DRD2, DRD3, COMT, and dopamine transporter gene [DAT1]) are associated with motor learning of healthy adults. In this study, we excluded DAT1, which is known to modify dopamine neurotransmission, because the minor allele of DAT1 is relatively rare in Korea (Shin et al., 2002).

A previous study reported that the motor recovery and activity of daily living were better during both initial stroke and at 6 months post-stroke for patients with the Val/Val alleles of COMT than for those with the Met/Met alleles (Liepert et al., 2013); this is consistent with our finding of better prognosis for patients with COMT Met (–) (Val/Val alleles), who showed improved motor function recovery and everyday activities at 3- and 6-months post-stroke. The previous study, however, was limited by differences in the baseline scores, whereas we observed no differences in the initial stroke severity level for patients with different COMT alleles. The severity of motor impairment at the time of stroke, age, corticospinal tract integrity, and type of stroke are considered poor prognostic factors (Kim et al., 2016; Olsen, 1990). However, there were significant differences in post-stroke outcomes according to COMT polymorphism after adjustment for the above factors. Therefore, we speculate that the Met allele has an additional negative effect on motor learning ability. COMT is an enzyme that facilitates dopamine breakdown in synaptic clefts, particularly in the prefrontal cortex (Meyer-Lindenberg et al., 2005); Val-to-Met substitution in the COMT 108/158 codon decreases enzyme activity 3–4-fold, which raises the base level of dopamine in the central nervous system (Lotta et al., 1995). Hence, our results suggest that increased dopamine levels in the prefrontal cortex inhibit recovery of motor function. The clinical significance of COMT polymorphism is still controversial. On one hand, some studies have reported that people with high activation levels of the Met allele have high levels of dopamine in the prefrontal cortex that correlated with higher working memory performance (Egan et al., 2003), better episodic memory recall, and more focused attention during a reaction time task than those for Val carriers (Heinz et al., 2006). On the other hand, other studies have reported that Val carriers exhibit excellent emotional communication skills and high levels of sustained attention and cognitive flexibility (Colzato et al., 2010; Lim et al., 2012).

Motor learning and motor cortical plasticity are directly correlated with dopamine levels (Flöel et al., 2005). However, these effects show an invertedU-shaped relationship (Thirugnanasambandam et al., 2011), and an excessive increase in dopamine can cause dyskinesia (Politis et al., 2012), decreased working memory (Mattay et al., 2003), impulsive antisocial personality disorder (Buckholtz et al., 2010), and impulse control disorders such as pathological gambling (Djamshidian et al., 2011).

The Val allele of COMT is associated with a lower dopamine level in the prefrontal cortex and, therefore, increased activation of phasic dopamine in the striatum (Bilder et al., 2004) (Grace, 1991), which is strongly associated with learning through error-anticipation (Schultz, 2013). We speculate that the COMT Val allele affects the ability to adapt readily to environmental changes and perform tasks faster with more flexibility, leading to better motor learning ability and motor recovery after stroke. Therefore, we hypothesize that the Met allele of COMT is linked with poor motor and functional outcome.

DRD1 is widely distributed in the brain, including in the cerebral cortex and basal ganglia on both sides, and the – 48 A/G SNP occurs in the 5′-untranslated region (Cichon et al., 1994). The G allele of DRD1 is associated with various disorders that increase dopamine neurotransmission in the brain, including alcoholism (Le Foll et al., 2009), bipolar disorder (Dmitrzak-Weglarz et al., 2006), compulsivebuying disorder, bulimia nervosa, and gambling disorder (Comings et al., 1997). Like DRD1, DRD2 is widely distributed in the brain, including the cerebral cortex and basal ganglia on both sides, and is located in chromosome 11q22-23. Since the TaqIA (rs1800497) polymorphism was reported (Grandy et al., 1989), several studies have examined its relationship with various mental disorders, and the scope of research is being expanded, including treatment response in schizophrenia (Suzuki et al., 2000), tic disorders (Lee et al., 2006), alcohol dependence (Grzywacz et al., 2012), panic disorder (Stochino et al., 2003), social phobia (Kim et al., 2007), and post-traumatic stress disorder (Duan et al., 2015). Unlike DRD1 and DRD2, DRD3 is mainly distributed in the dorsal striatum, and the polymorphism is a Ser-to-Gly substitution at position 9, which reportedly in-creases dopamine binding 4–5-fold (Jeanneteau et al., 2006). The Ser9Gly polymorphism also increases the risk of tardive dyskinesia, which is hypersensitive to dopamine (Bakker et al., 2006).

In this study, individual analysis of DRD1, DRD2, and DRD3 revealed no association with stroke recovery. Therefore, instead of the dopaminergic affinity of dopamine receptors, maintaining an appropriate level of dopamine appears to positively affect motor recovery after stroke, and we speculate that an ultimate decrease in the dopamine pathways involved in motor learning negatively influences motor recovery after stroke. Thus, additional research is needed to develop treatment options that appropriately increase activation in the dopamine-related motor learning pathways.

Our results for allele and allele-carrier frequencies of individual genes were similar to those reported previously among Koreans. Therefore, we proceeded with our analyses, treating the polymorphisms as prognosis-related factors. However, because gene polymorphisms could be related to the occurrence of stroke, the allele frequency could differ between healthy populations and stroke patients, and we were not able to accurately estimate the frequency of polymorphisms of individual genes in stroke patients. Thus, a future study will be needed to examine the frequency of dopamine-related gene polymorphisms with a large sample of stroke patients.

Additionally, the initial stroke volume was not analyzed. However, no significant differences were found in the initial stroke severity (NIHSS) and motor function of the upper and lower limbs (initial FMA score) according to the allele carrier of genes. Thus, we inferred that there was no significant difference in the initial stroke damage in motor function-related regions.

Finally, follow-up studies are needed to examine differences in neuroplasticity based on dopamine-related gene polymorphisms using different techniques. We expect that clinical studies with greater numbers of participants will allow identification of genes that can more accurately predict functional recovery after stroke.

5 Conclusion

In conclusion, our results suggest that COMT is useful in predicting good recovery after stroke. The findings in this study represent a step toward understanding individual differences in the dopamine neurotransmission system by utilizing different genetic information in stroke patients, which may prove useful in predicting patient prognosis and establishing rehabilitation treatment strategies appropriate to individual patients.

Footnotes

Acknowledgments

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2014R1A2A1A11050248) and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C2339).

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