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深度 GWAS 分析确定了阿尔茨海默病的潜在风险基因和风险变异,为其疾病机制提供了新的见解。

Deep post-GWAS analysis identifies potential risk genes and risk variants for Alzheimer's disease, providing new insights into its disease mechanisms.

机构信息

College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.

Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA.

出版信息

Sci Rep. 2021 Oct 15;11(1):20511. doi: 10.1038/s41598-021-99352-3.

Abstract

Alzheimer's disease (AD) is a genetically complex, multifactorial neurodegenerative disease. It affects more than 45 million people worldwide and currently remains untreatable. Although genome-wide association studies (GWAS) have identified many AD-associated common variants, only about 25 genes are currently known to affect the risk of developing AD, despite its highly polygenic nature. Moreover, the risk variants underlying GWAS AD-association signals remain unknown. Here, we describe a deep post-GWAS analysis of AD-associated variants, using an integrated computational framework for predicting both disease genes and their risk variants. We identified 342 putative AD risk genes in 203 risk regions spanning 502 AD-associated common variants. 246 AD risk genes have not been identified as AD risk genes by previous GWAS collected in GWAS catalogs, and 115 of 342 AD risk genes are outside the risk regions, likely under the regulation of transcriptional regulatory elements contained therein. Even more significantly, for 109 AD risk genes, we predicted 150 risk variants, of both coding and regulatory (in promoters or enhancers) types, and 85 (57%) of them are supported by functional annotation. In-depth functional analyses showed that AD risk genes were overrepresented in AD-related pathways or GO terms-e.g., the complement and coagulation cascade and phosphorylation and activation of immune response-and their expression was relatively enriched in microglia, endothelia, and pericytes of the human brain. We found nine AD risk genes-e.g., IL1RAP, PMAIP1, LAMTOR4-as predictors for the prognosis of AD survival and genes such as ARL6IP5 with altered network connectivity between AD patients and normal individuals involved in AD progression. Our findings open new strategies for developing therapeutics targeting AD risk genes or risk variants to influence AD pathogenesis.

摘要

阿尔茨海默病(AD)是一种遗传复杂、多因素的神经退行性疾病。它影响着全球超过 4500 万人,目前仍然无法治愈。尽管全基因组关联研究(GWAS)已经确定了许多与 AD 相关的常见变异,但目前已知只有约 25 个基因会影响 AD 的发病风险,尽管 AD 具有高度多基因性。此外,GWAS 中 AD 关联信号的风险变异仍不清楚。在这里,我们描述了 AD 相关变异的深度 GWAS 后分析,使用了一个集成的计算框架来预测疾病基因及其风险变异。我们在 203 个风险区域中确定了 342 个可能的 AD 风险基因,这些区域跨越了 502 个与 AD 相关的常见变异。246 个 AD 风险基因在之前收集在 GWAS 目录中的 GWAS 中尚未被确定为 AD 风险基因,而 342 个 AD 风险基因中有 115 个不在风险区域内,可能受其中包含的转录调控元件的调控。更重要的是,对于 109 个 AD 风险基因,我们预测了 150 个风险变异,包括编码和调控(启动子或增强子)类型,其中 85 个(57%)得到了功能注释的支持。深入的功能分析表明,AD 风险基因在 AD 相关途径或 GO 术语中过度表达,例如补体和凝血级联以及免疫反应的磷酸化和激活,它们的表达在人类大脑中的小胶质细胞、内皮细胞和周细胞中相对富集。我们发现了九个 AD 风险基因,例如 IL1RAP、PMAIP1、LAMTOR4,作为 AD 生存预后的预测因子,以及 ARL6IP5 等基因,它们在 AD 患者和正常个体之间的网络连通性发生改变,与 AD 进展有关。我们的发现为开发针对 AD 风险基因或风险变异的治疗方法提供了新的策略,以影响 AD 的发病机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd5c/8519945/24b9bd8e7700/41598_2021_99352_Fig1_HTML.jpg

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