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基于蛋白质基因组学的网络分析揭示了帕金森病中失调的机制和潜在的介质。

Proteogenomic network analysis reveals dysregulated mechanisms and potential mediators in Parkinson's disease.

机构信息

Population Analytics & Insights, AI/ML, Data Science & Digital Health, Janssen Research & Development, LLC, Spring House, PA, USA.

Neuroscience Data Science, Janssen Pharmaceutica NV, Beerse, Belgium.

出版信息

Nat Commun. 2024 Jul 31;15(1):6430. doi: 10.1038/s41467-024-50718-x.

Abstract

Parkinson's disease is highly heterogeneous across disease symptoms, clinical manifestations and progression trajectories, hampering the identification of therapeutic targets. Despite knowledge gleaned from genetics analysis, dysregulated proteome mechanisms stemming from genetic aberrations remain underexplored. In this study, we develop a three-phase system-level proteogenomic analytical framework to characterize disease-associated proteins and dysregulated mechanisms. Proteogenomic analysis identified 577 proteins that enrich for Parkinson's disease-related pathways, such as cytokine receptor interactions and lysosomal function. Converging lines of evidence identified nine proteins, including LGALS3, CSNK2A1, SMPD3, STX4, APOA2, PAFAH1B3, LDLR, HSPB1, BRK1, with potential roles in disease pathogenesis. This study leverages the largest population-scale proteomics dataset, the UK Biobank Pharma Proteomics Project, to characterize genetically-driven protein disturbances associated with Parkinson's disease. Taken together, our work contributes to better understanding of genome-proteome dynamics in Parkinson's disease and sets a paradigm to identify potential indirect mediators connected to GWAS signals for complex neurodegenerative disorders.

摘要

帕金森病在疾病症状、临床表现和进展轨迹上高度异质,这阻碍了治疗靶点的确定。尽管从遗传学分析中获得了知识,但源自遗传异常的失调蛋白质组机制仍未得到充分探索。在这项研究中,我们开发了一个三阶段的系统水平蛋白质组学分析框架,以描述与疾病相关的蛋白质和失调机制。蛋白质组学分析鉴定了 577 种蛋白质,这些蛋白质富集了与帕金森病相关的途径,如细胞因子受体相互作用和溶酶体功能。多种证据表明,包括 LGALS3、CSNK2A1、SMPD3、STX4、APOA2、PAFAH1B3、LDLR、HSPB1 和 BRK1 在内的 9 种蛋白质可能在疾病发病机制中发挥作用。本研究利用了最大的人群规模蛋白质组学数据集——英国生物银行制药蛋白质组学项目,来描述与帕金森病相关的遗传驱动的蛋白质紊乱。总之,我们的工作有助于更好地理解帕金森病中的基因组-蛋白质组动态,并为识别与复杂神经退行性疾病的 GWAS 信号相关的潜在间接介质设定了范例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3697/11289099/0c4457677a7a/41467_2024_50718_Fig1_HTML.jpg

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