Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for Alzheimer’s disease

IF 31.7 1区 生物学 Q1 GENETICS & HEREDITY
Daniel Western, Jigyasha Timsina, Lihua Wang, Ciyang Wang, Chengran Yang, Bridget Phillips, Yueyao Wang, Menghan Liu, Muhammad Ali, Aleksandra Beric, Priyanka Gorijala, Pat Kohlfeld, John Budde, Allan I. Levey, John C. Morris, Richard J. Perrin, Agustin Ruiz, Marta Marquié, Mercè Boada, Itziar de Rojas, Jarod Rutledge, Hamilton Oh, Edward N. Wilson, Yann Le Guen, Lianne M. Reus, Betty Tijms, Pieter Jelle Visser, Sven J. van der Lee, Yolande A. L. Pijnenburg, Charlotte E. Teunissen, Marta del Campo Milan, Ignacio Alvarez, Miquel Aguilar, Michael D. Greicius, Pau Pastor, David J. Pulford, Laura Ibanez, Tony Wyss-Coray, Yun Ju Sung, Carlos Cruchaga
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Abstract

The integration of quantitative trait loci (QTLs) with disease genome-wide association studies (GWASs) has proven successful in prioritizing candidate genes at disease-associated loci. QTL mapping has been focused on multi-tissue expression QTLs or plasma protein QTLs (pQTLs). We generated a cerebrospinal fluid (CSF) pQTL atlas by measuring 6,361 proteins in 3,506 samples. We identified 3,885 associations for 1,883 proteins, including 2,885 new pQTLs, demonstrating unique genetic regulation in CSF. We identified CSF-enriched pleiotropic regions on chromosome (chr)3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron specificity and neurological development. We integrated our associations with Alzheimer’s disease (AD) through proteome-wide association study (PWAS), colocalization and Mendelian randomization and identified 38 putative causal proteins, 15 of which have drugs available. Finally, we developed a proteomics-based AD prediction model that outperforms genetics-based models. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits.

Abstract Image

人类脑脊液的蛋白质基因组分析确定了与神经系统相关的调控,并揭示了阿尔茨海默病的病因蛋白
事实证明,将定量性状位点(QTL)与疾病全基因组关联研究(GWAS)相结合,可以成功地优先确定疾病相关位点的候选基因。QTL图谱主要针对多组织表达QTL或血浆蛋白QTL(pQTL)。我们通过测量 3,506 份样本中的 6,361 种蛋白质,生成了脑脊液(CSF)pQTL 图谱。我们确定了 1,883 个蛋白质的 3,885 个关联,其中包括 2,885 个新的 pQTLs,显示了脑脊液中独特的遗传调控。我们在 OSTN 附近的染色体 (chr)3q28 和 APOE 附近的 chr19q13.32 上发现了 CSF 富集的多向性区域,这些区域富集了神经元特异性和神经系统发育。我们通过全蛋白质组关联研究(PWAS)、共聚焦和孟德尔随机化,整合了与阿尔茨海默病(AD)的关联,并确定了 38 种推测的致病蛋白,其中 15 种已有药物可用。最后,我们建立了一个基于蛋白质组学的AD预测模型,该模型优于基于遗传学的模型。这些发现将有助于进一步了解生物学,并确定大脑和神经特征的因果蛋白和可药用蛋白。
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来源期刊
Nature genetics
Nature genetics 生物-遗传学
CiteScore
43.00
自引率
2.60%
发文量
241
审稿时长
3 months
期刊介绍: Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation. Integrative genetic topics comprise, but are not limited to: -Genes in the pathology of human disease -Molecular analysis of simple and complex genetic traits -Cancer genetics -Agricultural genomics -Developmental genetics -Regulatory variation in gene expression -Strategies and technologies for extracting function from genomic data -Pharmacological genomics -Genome evolution
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