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Genetic polymorphisms involved in dopaminergic neurotransmission and risk for Parkinson's disease in a Japanese population.

ABSTRACT: BACKGROUND: Parkinson's disease (PD) is characterized by alterations in dopaminergic neurotransmission. Genetic polymorphisms involved in dopaminergic neurotransmission may influence susceptibility to PD. METHODS: We investigated the relationship of catechol-O-methyltransferase (COMT), monoamine oxidase B (MAOB), dopamine receptor (DR) D2 and DRD4 polymorphisms and PD risk with special attention to the interaction with cigarette smoking among 238 patients with PD and 369 controls in a Japanese population. RESULTS: Subjects with the AA genotype of MAOB rs1799836 showed a significantly increased risk of PD (odds ratio (OR) = 1.70, 95% confidence interval (CI) = 1.12 - 2.58) compared with the AG and GG genotypes combined. The AA genotype of COMT rs4680 was marginally associated with an increased risk of PD (OR = 1.86, 95% CI = 0.98 - 3.50) compared with the GG genotype. The DRD2 rs1800497 and DRD4 rs1800955 polymorphisms showed no association with PD. A COMT -smoking interaction was suggested, with the combined GA and AA genotypes of rs4680 and non-smoking conferring significantly higher risk (OR = 3.97, 95% CI = 2.13 - 7.41) than the AA genotype and a history of smoking (P for interaction = 0.061). No interactions of smoking with other polymorphisms were observed. CONCLUSIONS: The COMT rs4680 and MAOB rs1799836 polymorphisms may increase susceptibility to PD risk among Japanese. Future studies involving larger control and case populations and better pesticide exposure histories will undoubtedly lead to a more thorough understanding of the role of the polymorphisms involved in the dopamine pathway in PD.

SUBMITTER: Kiyohara C

PROVIDER: S-EPMC3199768 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Genetic polymorphisms involved in dopaminergic neurotransmission and risk for Parkinson's disease in a Japanese population.

Kiyohara Chikako C Miyake Yoshihiro Y Koyanagi Midori M Fujimoto Takahiro T Shirasawa Senji S Tanaka Keiko K Fukushima Wakaba W Sasaki Satoshi S Tsuboi Yoshio Y Yamada Tatsuo T Oeda Tomoko T Shimada Hiroyuki H Kawamura Nobutoshi N Sakae Nobutaka N Fukuyama Hidenao H Hirota Yoshio Y Nagai Masaki M

BMC neurology 20110725

<h4>Background</h4>Parkinson's disease (PD) is characterized by alterations in dopaminergic neurotransmission. Genetic polymorphisms involved in dopaminergic neurotransmission may influence susceptibility to PD.<h4>Methods</h4>We investigated the relationship of catechol-O-methyltransferase (COMT), monoamine oxidase B (MAOB), dopamine receptor (DR) D2 and DRD4 polymorphisms and PD risk with special attention to the interaction with cigarette smoking among 238 patients with PD and 369 controls in ...[more]

PMID: 21781348

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Project description:Assessing brain activity during complex voluntary motor behaviors that require the recruitment of multiple neural sites is a field of active research. Our current knowledge is primarily based on human brain imaging studies that have clear limitations in terms of temporal and spatial resolution. We developed a physiologically informed non-linear multi-compartment stochastic neural model to simulate functional brain activity coupled with neurotransmitter release during complex voluntary behavior, such as speech production. Due to its state-dependent modulation of neural firing, dopaminergic neurotransmission plays a key role in the organization of functional brain circuits controlling speech and language and thus has been incorporated in our neural population model. A rigorous mathematical proof establishing existence and uniqueness of solutions to the proposed model as well as a computationally efficient strategy to numerically approximate these solutions are presented. Simulated brain activity during the resting state and sentence production was analyzed using functional network connectivity, and graph theoretical techniques were employed to highlight differences between the two conditions. We demonstrate that our model successfully reproduces characteristic changes seen in empirical data between the resting state and speech production, and dopaminergic neurotransmission evokes pronounced changes in modeled functional connectivity by acting on the underlying biological stochastic neural model. Specifically, model and data networks in both speech and rest conditions share task-specific network features: both the simulated and empirical functional connectivity networks show an increase in nodal influence and segregation in speech over the resting state. These commonalities confirm that dopamine is a key neuromodulator of the functional connectome of speech control. Based on reproducible characteristic aspects of empirical data, we suggest a number of extensions of the proposed methodology building upon the current model.

Dataset Information

Genetic polymorphisms involved in dopaminergic neurotransmission and risk for Parkinson's disease in a Japanese population.

Publications

Genetic polymorphisms involved in dopaminergic neurotransmission and risk for Parkinson's disease in a Japanese population.

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