Nalls Mike A, Blauwendraat Cornelis, Sargent Lana, Vitale Dan, Leonard Hampton, Iwaki Hirotaka, Song Yeajin, Bandres-Ciga Sara, Menden Kevin, Faghri Faraz, Heutink Peter, Cookson Mark R, Singleton Andrew B
Center for Alzheimer's and Related Dementias, National Institutes of Health, Bethesda, MD 20892, USA.
Data Tecnica International LLC, Glen Echo, MD 20812, USA.
Brain Commun. 2021 May 1;3(2):fcab095. doi: 10.1093/braincomms/fcab095. eCollection 2021.
Previous research using genome-wide association studies has identified variants that may contribute to lifetime risk of multiple neurodegenerative diseases. However, whether there are common mechanisms that link neurodegenerative diseases is uncertain. Here, we focus on one gene, , encoding progranulin, and the potential mechanistic interplay between genetic risk, gene expression in the brain and inflammation across multiple common neurodegenerative diseases. We utilized genome-wide association studies, expression quantitative trait locus mapping and Bayesian colocalization analyses to evaluate potential causal and mechanistic inferences. We integrate various molecular data types from public resources to infer disease connectivity and shared mechanisms using a data-driven process. Expression quantitative trait locus analyses combined with genome-wide association studies identified significant functional associations between increasing genetic risk in the region and decreased expression of the gene in Parkinson's, Alzheimer's and amyotrophic lateral sclerosis. Additionally, colocalization analyses show a connection between blood-based inflammatory biomarkers relating to platelets and expression in the frontal cortex. expression mediates neuroinflammation function related to multiple neurodegenerative diseases. This analysis suggests shared mechanisms for Parkinson's, Alzheimer's and amyotrophic lateral sclerosis.
以往使用全基因组关联研究的研究已经确定了可能导致多种神经退行性疾病终生风险的变异。然而，神经退行性疾病之间是否存在共同机制尚不确定。在这里，我们聚焦于一个基因，即编码前颗粒蛋白的基因，以及多种常见神经退行性疾病中遗传风险、大脑中的基因表达和炎症之间潜在的机制相互作用。我们利用全基因组关联研究、表达定量性状位点定位和贝叶斯共定位分析来评估潜在的因果和机制推断。我们整合来自公共资源的各种分子数据类型，通过数据驱动的过程推断疾病的关联性和共同机制。表达定量性状位点分析与全基因组关联研究相结合，确定了该区域遗传风险增加与帕金森病、阿尔茨海默病和肌萎缩侧索硬化症中该基因表达降低之间的显著功能关联。此外，共定位分析显示与血小板相关的血液炎症生物标志物与额叶皮质中的该基因表达之间存在联系。该基因表达介导了与多种神经退行性疾病相关的神经炎症功能。这一分析表明帕金森病、阿尔茨海默病和肌萎缩侧索硬化症存在共同机制。
