Bordeaux Population Health Research Center, Inserm U1219, University of Bordeaux, Bordeaux, France.
Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA.
Nat Rev Neurol. 2022 Feb;18(2):84-101. doi: 10.1038/s41582-021-00592-8. Epub 2022 Jan 5.
Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI but does not manifest as clinical stroke, is highly prevalent in the general population, particularly with increasing age. Advances in technologies and collaborative work have led to substantial progress in the identification of common genetic variants that are associated with cSVD-related stroke (ischaemic and haemorrhagic) and MRI-defined covert cSVD. In this Review, we provide an overview of collaborative studies - mostly genome-wide association studies (GWAS) - that have identified >50 independent genetic loci associated with the risk of cSVD. We describe how these associations have provided novel insights into the biological mechanisms involved in cSVD, revealed patterns of shared genetic variation across cSVD traits, and shed new light on the continuum between rare, monogenic and common, multifactorial cSVD. We consider how GWAS summary statistics have been leveraged for Mendelian randomization studies to explore causal pathways in cSVD and provide genetic evidence for drug effects, and how the combination of findings from GWAS with gene expression resources and drug target databases has enabled identification of putative causal genes and provided proof-of-concept for drug repositioning potential. We also discuss opportunities for polygenic risk prediction, multi-ancestry approaches and integration with other omics data.
脑小血管病 (cSVD) 是缺血性和出血性中风的主要原因,也是痴呆的主要病因。脑磁共振成像 (MRI) 可检测到但不会表现为临床中风的隐匿性 cSVD 在普通人群中非常普遍,尤其是随着年龄的增长。技术的进步和合作工作推动了识别与 cSVD 相关中风(缺血性和出血性)和 MRI 定义的隐匿性 cSVD 相关常见遗传变异的研究取得了实质性进展。在这篇综述中,我们概述了大多数全基因组关联研究 (GWAS) 的合作研究,这些研究已经确定了 >50 个与 cSVD 风险相关的独立遗传位点。我们描述了这些关联如何为 cSVD 涉及的生物学机制提供新的见解,揭示了 cSVD 特征之间共享遗传变异的模式,并为罕见的单基因和常见的多因素 cSVD 之间的连续体提供了新的认识。我们考虑了如何利用 GWAS 汇总统计数据进行孟德尔随机化研究,以探索 cSVD 中的因果途径,并提供药物作用的遗传证据,以及如何将 GWAS 结果与基因表达资源和药物靶点数据库相结合,以识别潜在的因果基因,并为药物重新定位潜力提供概念验证。我们还讨论了多基因风险预测、多祖裔方法以及与其他组学数据的整合的机会。