Gao Chenhao, Zhou Haobin, Liang Weixuan, Wen Zhuofeng, Liao Wanzhe, Xie Zhixin, Liao Cailing, He Limin, Sun Jingzhang, Chen Zhilin, Li Duopin, Yuan Naijun, Huang Chuiguo, Zhang Jiewen
Department of Neurology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
The First School of Clinical Medicine, Guangzhou Medical University, Guangzhou, China.
CNS Neurosci Ther. 2025 Feb;31(2):e70294. doi: 10.1111/cns.70294.
To identify and validate causal protein targets that may serve as potential therapeutic interventions for both the onset and progression of Parkinson's disease (PD) through integrative proteomic and genetic analyses.
We utilized large-scale plasma and brain protein quantitative trait loci (pQTL) datasets from the deCODE Health study and the Religious Orders Study/Rush Memory and Aging Project (ROS/MAP), respectively. Proteome-wide association studies (PWAS) were conducted using the OTTERS framework for plasma proteins and the FUSION tool for brain proteins, examining associations with PD onset and three progression phenotypes: composite, motor, and cognitive. Significant protein associations (FDR-corrected p < 0.05) from PWAS were further validated using summary-based Mendelian randomization (SMR), colocalization analyses, and reverse Mendelian randomization (MR) to establish causality. Phenome-wide Mendelian randomization (PheW-MR) was performed to assess potential side effects across 679 disease traits when targeting these proteins to reduce PD-related phenotype risk by 20%. Additionally, we conducted cellular distribution-based clustering using gene expression data from the Allen Brain Atlas (ABA) to explore the distribution of key proteins across brain regions, constructed protein-protein interaction (PPI) networks via the STRING database to explore interactions among proteins, and evaluated the druggability of identified targets using the DrugBank database to identify opportunities for drug repurposing.
Our analyses identified 25 candidate proteins associated with PD phenotypes, including 16 plasma proteins linked to PD progression (10 cognitive, 4 motor, and 3 composite) and 9 plasma proteins associated with PD onset. Notably, GPNMB was implicated in both plasma and brain tissues for PD onset. PheW-MR revealed predominantly beneficial side effects for the identified targets, with 83.7% of associations indicating positive outcomes and 16.3% indicating adverse effects. Cellular clustering categorized candidate targets into three distinct expression profiles across brain cell types using ABA. PPI network analysis highlighted one key interaction cluster among the proteins for PD cognitive progression and PD onset. Druggability assessment revealed 15 out of 25 proteins had repurposing opportunities for PD treatment.
We have identified 25 causal protein targets associated with the onset and progression of PD, providing new insights into the research and development of treatment strategies for PD.
通过综合蛋白质组学和基因分析,识别并验证可能作为帕金森病(PD)发病和进展潜在治疗干预措施的因果蛋白靶点。
我们分别利用了来自deCODE健康研究以及宗教团体研究/拉什记忆与衰老项目(ROS/MAP)的大规模血浆和脑蛋白定量性状位点(pQTL)数据集。使用OTTERS框架对血浆蛋白进行全蛋白质组关联研究(PWAS),使用FUSION工具对脑蛋白进行研究,检测与PD发病以及三种进展表型(综合、运动和认知)的关联。来自PWAS的显著蛋白关联(经FDR校正的p < 0.05)通过基于汇总的孟德尔随机化(SMR)、共定位分析和反向孟德尔随机化(MR)进一步验证以确定因果关系。进行全表型孟德尔随机化(PheW-MR)以评估当靶向这些蛋白将PD相关表型风险降低20%时,在679种疾病性状中的潜在副作用。此外,我们利用来自艾伦脑图谱(ABA)的基因表达数据进行基于细胞分布的聚类,以探索关键蛋白在脑区的分布,通过STRING数据库构建蛋白质-蛋白质相互作用(PPI)网络以探索蛋白间的相互作用,并使用DrugBank数据库评估已识别靶点的可成药特性,以确定药物再利用的机会。
我们的分析确定了25种与PD表型相关联的候选蛋白,包括16种与PD进展相关的血浆蛋白(10种与认知相关、4种与运动相关、3种与综合相关)以及9种与PD发病相关的血浆蛋白。值得注意的是,GPNMB在PD发病的血浆和脑组织中均有涉及。PheW-MR显示所识别靶点的副作用主要为有益的,83.7%的关联表明为阳性结果,16.3%表明为不良反应。利用ABA进行的细胞聚类将候选靶点根据脑细胞类型分为三种不同的表达谱。PPI网络分析突出了PD认知进展和PD发病相关蛋白中的一个关键相互作用簇。可成药特性评估显示25种蛋白中有15种具有用于PD治疗的再利用机会。
我们已经确定了25种与PD发病和进展相关的因果蛋白靶点,为PD治疗策略的研发提供了新的见解。