Genetics in Parkinson disease: Mendelian versus non-Mendelian inheritance

帕金森病遗传学:孟德尔遗传与非孟德尔遗传

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Abstract

Parkinson's disease is a common, progressive neurodegenerative disorder, affecting 3% of those older than 75 years of age. Clinically, Parkinson's disease (PD) is associated with resting tremor, postural instability, rigidity, bradykinesia, and a good response to levodopa therapy. Over the last 15 years, numerous studies have confirmed that genetic factors contribute to the complex pathogenesis of PD. Highly penetrant mutations producing rare, monogenic forms of the disease have been discovered in singular genes such as SNCA, Parkin, DJ-1, PINK 1, LRRK2, and VPS35. Unique variants with incomplete penetrance in LRRK2 and GBA have been shown to be strong risk factors for PD in certain populations. Additionally, over 20 common variants with small effect sizes are now recognized to modulate the risk for PD. Investigating Mendelian forms of PD has provided precious insight into the pathophysiology that underlies the more common idiopathic form of disease; however, no treatment methodologies have developed. Furthermore, for identified common risk alleles, the functional basis underlying risk principally remains unknown. The challenge over the next decade will be to strengthen the findings delivered through genetic discovery by assessing the direct, biological consequences of risk variants in tandem with additional high-content, integrated datasets. This review discusses monogenic risk factors and mechanisms of Mendelian inheritance of Parkinson disease. Highly penetrant mutations in SNCA, Parkin, DJ-1, PINK 1, LRRK2 and VPS35 produce rare, monogenic forms of the disease, while unique variants within LRRK2 and GBA show incomplete penetrance and are strong risk factors for PD. Additionally, over 20 common variants with small effect sizes modulate disease risk. The challenge over the next decade is to strengthen genetic findings by assessing direct, biological consequences of risk variants in tandem with high-content, integrated datasets. This article is part of a special issue on Parkinson disease.

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