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迈向阿尔茨海默病的个性化干预

Towards Personalized Intervention for Alzheimer's Disease.

作者信息

Peng Xing, Xing Peiqi, Li Xiuhui, Qian Ying, Song Fuhai, Bai Zhouxian, Han Guangchun, Lei Hongxing

机构信息

CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; Cunji Medical School, University of Chinese Academy of Sciences, Beijing 100049, China.

CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.

出版信息

Genomics Proteomics Bioinformatics. 2016 Oct;14(5):289-297. doi: 10.1016/j.gpb.2016.01.006. Epub 2016 Sep 28.

Abstract

Alzheimer's disease (AD) remains to be a grand challenge for the international community despite over a century of exploration. A key factor likely accounting for such a situation is the vast heterogeneity in the disease etiology, which involves very complex and divergent pathways. Therefore, intervention strategies shall be tailored for subgroups of AD patients. Both demographic and in-depth information is needed for patient stratification. The demographic information includes primarily APOE genotype, age, gender, education, environmental exposure, life style, and medical history, whereas in-depth information stems from genome sequencing, brain imaging, peripheral biomarkers, and even functional assays on neurons derived from patient-specific induced pluripotent cells (iPSCs). Comprehensive information collection, better understanding of the disease mechanisms, and diversified strategies of drug development would help with more effective intervention in the foreseeable future.

摘要

尽管经过了一个多世纪的探索,阿尔茨海默病(AD)仍然是国际社会面临的巨大挑战。导致这种情况的一个关键因素可能是该疾病病因的巨大异质性,这涉及非常复杂且不同的途径。因此,干预策略应针对AD患者的亚组进行定制。患者分层既需要人口统计学信息,也需要深入信息。人口统计学信息主要包括载脂蛋白E(APOE)基因型、年龄、性别、教育程度、环境暴露、生活方式和病史,而深入信息则来自基因组测序、脑成像、外周生物标志物,甚至是对源自患者特异性诱导多能干细胞(iPSC)的神经元进行的功能测定。在可预见的未来,全面的信息收集、对疾病机制的更好理解以及多样化的药物开发策略将有助于更有效地进行干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/16ad/5093853/d02e2e500fe4/gr1.jpg

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