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以基因轉錄體的序列分析來解析阿茲海默症的致病機轉

Using Transcriptome Sequencing to Analyze the Pathogenic Mechanisms of Alzheimer's Disease

摘要


阿茲海默症(Alzheimer's disease, AD)在全世界的患病率迅速增加,並且造成經濟和社會的顯著影響。目前的治療並無法改變疾病的進程,這意味著如果要避免阿茲海默症的流行,我們需要新的治療方法。阿茲海默症的臨床表徵是由於有大腦皮質神經元的大量缺損。有效的神經保護策略是需要早期發現容易罹患者的臨床前標記,以及確定早期的致病機制,以作為治療的目標。因為生物標記物和致病機制可能相重複,因此要發現疾病的新致病元素,很可能需要新的方法。轉錄體的分析,它不預設也不排序任何病因假說,如此比較能夠去闡明像阿茲海默症這等複雜的疾病的致病機轉。使用核糖核酸定序(RNA-Seq)的方法,不僅非常適合於有複雜基因體的人腦組織的研究,而且它可以克服一些在神經退化性疾病的病例死後腦組織比較對照的潛在的技術問題。此外,RNA-seq能檢測到的訊息核糖核酸的種類及數量,超越所對應現有的基因組序列所預期的。利用這種技術,可以以單鹼基的解析率,識別轉錄邊界(transcription boundaries)的確切位置。這些特點使RNA-seq的技術,特別在研究人類大腦中發現的複雜的轉錄體,非常有用。

並列摘要


The increase of patients with Alzheimer's disease (AD) has a great impact on the social and economic status. Up to date, no effective treatment can alleviate the progress of AD suggesting an alternative strategy is mandatory to reduce its prevalence. Massive neuronal loss is evident in the pathology, of AD which leads to clinical manifestations. Thus, neuroprotection for preserving the neurons from damage depends on the identification of biomarkers which is capable of early detection of disease susceptibility. In order to identify the factors contributing to AD, new research strategies such as systems biology with whole genome coverage have been employed. Analysis of transcripts in whole genome which does not default to or sort by hypothesis of etiology may be appropriate to decipher the pathogenic mechanism for AD. Both single nucleotide changes and expression quantity differences from the whole transcriptome could be assessed by base-calling and numbers of reads, respectively. RNA-Seq is suitable for the complexity of the genome from brain tissue and is capable of solving the technique errors in comparison of the postmortem tissues of controls with those of patients with neurodegenerative disease. In addition, RNA-seq can detect the mRNA species with alternative splicing and assess their amount, which could provide much more information as compared to the genomic exon-predicting sequences. Furthermore, it can also accurately define the transcription boundary in single base resolution scale. These advantages render the RNA-Seq as a unique and efficient method for research into the human brain transcriptome.

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