Neurology Clinics, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus.
The Cyprus School of Molecular Medicine, The Cyprus Institute of Neurology and Genetics, Nicosia 2371, Cyprus.
Genes (Basel). 2021 Aug 20;12(8):1278. doi: 10.3390/genes12081278.
Parkinson's disease (PD) is a neurodegenerative disorder, and literature suggests that genetics and lifestyle/environmental factors may play a key role in the triggering of the disease. This study aimed to evaluate the predictive performance of a 12-Single Nucleotide Polymorphisms (SNPs) polygenic risk score (PRS) in combination with already established PD-environmental/lifestyle factors.
Genotypic and lifestyle/environmental data on 235 PD-patients and 464 controls were obtained from a previous study carried out in the Cypriot population. A PRS was calculated for each individual. Univariate logistic-regression analysis was used to assess the association of PRS and each risk factor with PD-status. Stepwise-regression analysis was used to select the best predictive model for PD combining genetic and lifestyle/environmental factors.
The 12-SNPs PRS was significantly increased in PD-cases compared to controls. Furthermore, univariate analyses showed that age, head injury, family history, depression, and Body Mass Index (BMI) were significantly associated with PD-status. Stepwise-regression suggested that a model which includes PRS and seven other independent lifestyle/environmental factors is the most predictive of PD in our population.
These results suggest an association between both genetic and environmental factors and PD, and highlight the potential for the use of PRS in combination with the classical risk factors for risk prediction of PD.
帕金森病（PD）是一种神经退行性疾病，文献表明遗传和生活方式/环境因素可能在触发疾病方面发挥关键作用。本研究旨在评估 12 个单核苷酸多态性（SNP）多基因风险评分（PRS）与已确定的 PD 环境/生活方式因素相结合的预测性能。
从之前在塞浦路斯人群中进行的一项研究中获得了 235 名 PD 患者和 464 名对照者的基因型和生活方式/环境数据。为每个个体计算 PRS。使用单变量逻辑回归分析评估 PRS 和每个风险因素与 PD 状态的关联。逐步回归分析用于选择结合遗传和生活方式/环境因素的最佳 PD 预测模型。
12-SNP PRS 在 PD 病例中明显高于对照组。此外，单变量分析表明，年龄、头部损伤、家族史、抑郁和体重指数（BMI）与 PD 状态显著相关。逐步回归表明，包含 PRS 和其他七个独立生活方式/环境因素的模型是我们人群中 PD 最具预测性的模型。
这些结果表明遗传和环境因素与 PD 之间存在关联，并强调了 PRS 与经典风险因素结合用于 PD 风险预测的潜力。
