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蛋白质组、转录组联合分析及多性状分析以鉴定新的帕金森病风险基因。

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes.

作者信息

Shi Jing-Jing, Mao Cheng-Yuan, Guo Ya-Zhou, Fan Yu, Hao Xiao-Yan, Li Shuang-Jie, Tian Jie, Hu Zheng-Wei, Li Meng-Jie, Li Jia-Di, Ma Dong-Rui, Guo Meng-Nan, Zuo Chun-Yan, Liang Yuan-Yuan, Xu Yu-Ming, Yang Jian, Shi Chang-He

机构信息

Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China.

School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang, China.

出版信息

Aging (Albany NY). 2024 Jan 17;16(2):1555-1580. doi: 10.18632/aging.205444.

Abstract

Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (, , , , ) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.

摘要

全基因组关联研究(GWAS)已经确定了帕金森病(PD)的多个风险变异。然而,这些风险变异如何赋予帕金森病风险在很大程度上仍然未知。我们通过将帕金森病GWAS与来自人脑、血浆和脑脊液的蛋白质组和蛋白质定量性状位点(pQTL)数据相结合,进行了一项全蛋白质组关联研究(PWAS)和基于汇总数据的孟德尔随机化(SMR)分析。我们还进行了一项大型全转录组关联研究(TWAS)和因果基因集精细定位(FOCUS),利用2种组织的联合组织插补(JTI)预测模型来识别和优先排序可能的因果基因。我们进一步使用GWAS的多性状分析(MTAG)进行PWAS、SMR、TWAS和FOCUS,以识别更多的帕金森病风险基因,提高统计效力。在这项大规模研究中,我们确定了16个基因,其遗传调控的蛋白质丰度水平与帕金森病风险相关。我们通过TWAS和FOCUS研究对帕金森病及相关性状进行了大规模分析,发现了26个与帕金森病相关的因果基因,这些基因在以前的TWAS中尚未报道。5个基因(,,,,)在全蛋白质组和全转录组水平上均与帕金森病表现出显著关联。我们的研究为帕金森病的病因和潜在遗传结构提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/15d2/10866412/2c663eb6c320/aging-16-205444-g001.jpg

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