Zhou Xiaopu, Li Yolanda Y T, Fu Amy K Y, Ip Nancy Y
Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Hong Kong, China.
Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China.
Front Neurosci. 2021 Mar 29;15:650220. doi: 10.3389/fnins.2021.650220. eCollection 2021.
The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.
阿尔茨海默病(AD)在老年人群中的高患病率及其缺乏有效治疗方法,使得这种疾病成为对人类健康的重大威胁。最近的流行病学和遗传学研究揭示了该疾病的多基因性质,这可能可以通过考虑多种遗传风险的多基因评分模型来解释。在此,我们系统地综述了用于构建研究AD的多基因评分模型的基本原理和方法。我们还讨论了多基因风险评分(PRSs)与临床结局、脑成像结果以及来自大脑和外周系统的生化生物标志物之间的关联。最后,我们讨论了将多基因评分模型纳入研究和临床实践的可能性以及潜在挑战。