Zhang Mingming, Mu Hongbo, Shang Zhenwei, Kang Kai, Lv Hongchao, Duan Lian, Li Jin, Chen Xinren, Teng Yanbo, Jiang Yongshuai, Zhang Ruijie
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
College of Science, Northeast Forestry University, Harbin, China.
Neuroscience. 2017 Jan 6;340:398-410. doi: 10.1016/j.neuroscience.2016.11.004. Epub 2016 Nov 10.
Parkinson's disease (PD) is the second most common neurodegenerative disease. It is generally believed that it is influenced by both genetic and environmental factors, but the precise pathogenesis of PD is unknown to date. In this study, we performed a pathway analysis based on genome-wide association study (GWAS) to detect risk pathways of PD in three GWAS datasets. We first mapped all SNP markers to autosomal genes in each GWAS dataset. Then, we evaluated gene risk values using the minimum P-value of the tagSNPs. We took a pathway as a unit to identify the risk pathways based on the cumulative risks of the genes in the pathway. Finally, we combine the analysis results of the three datasets to detect the high risk pathways associated with PD. We found there were five same pathways in the three datasets. Besides, we also found there were five pathways which were shared in two datasets. Most of these pathways are associated with nervoussystem. Five pathways had been reported to be PD-related pathways in the previous literature. Our findings also implied that there was a close association between immune response and PD. Continued investigation of these pathways will further help us explain the pathogenesis of PD.
帕金森病(PD)是第二常见的神经退行性疾病。人们普遍认为它受遗传和环境因素的影响,但迄今为止,PD的确切发病机制尚不清楚。在本研究中,我们基于全基因组关联研究(GWAS)进行了通路分析,以检测三个GWAS数据集中PD的风险通路。我们首先将每个GWAS数据集中的所有单核苷酸多态性(SNP)标记映射到常染色体基因上。然后,我们使用标签SNP的最小P值评估基因风险值。我们以通路为单位,根据通路中基因的累积风险来识别风险通路。最后,我们结合三个数据集的分析结果来检测与PD相关的高风险通路。我们发现三个数据集中有五条相同的通路。此外,我们还发现有五条通路在两个数据集中共享。这些通路大多与神经系统有关。先前的文献中已有五条通路被报道为与PD相关的通路。我们的研究结果还表明免疫反应与PD之间存在密切关联。对这些通路的持续研究将进一步帮助我们解释PD的发病机制。