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姓名	彭奕憲(Yi-Shian Peng)  查詢紙本館藏	畢業系所	系統生物與生物資訊研究所
論文名稱	基因體功能統合分析在阿茲海默症和大腦老化－近年阿茲海默症研發藥物失敗的理論問題探討 (Commentary on recent Alzheimer’s trial failures: comparative functional genomic meta-analysis of Alzheimer’s affected and naturally aging brains)
相關論文	★ 人類陰道滴蟲之Myb2蛋白質動態性質研究 ★ 分析原核生物基因體複製起點與終點的反向對偶對稱現象 ★ 分析基因體拷貝數變異所使用的兩種方法比較：隱藏馬可夫模型與成對高斯合併法 ★ 使用兩種方法偵測基因體拷貝數變異：成對高斯合併法與隱藏馬可夫模型 ★ 以整體晶片數據為母體應用於分析基因差異表達的z檢定方法 ★ GSLHC － 運用基因組及層次類聚以生物功能群將有生物活性的複合物定性的方法 ★ 一個檢定測量微晶片基因表達數據靈敏度的全統計計算法 ★ 運用嶄新抗體固著策略發展及驗證新式抗體微晶片平台 ★ Drug-resistant colon cancer cells produce high carcinoembryonic antigen and might not be cancer-initiating cells ★ 創傷性關節炎軟骨之退化進程－ 大鼠模型基因體圖譜研究 ★ 運用時間序列微陣列資料來預測調控基因 ★ 以大鼠嗜鉻性瘤細胞株建立神經訊號傳遞之細胞分子生物學模型 ★ 一種找尋再利用藥物複合物來系統性治療複雜疾病的架構：大腸直腸腺瘤的應用 ★ 以上皮細胞間質化與增生相關功能來描述癌症幹細胞之基因型 ★ 從共表達差異基因對導出正常腦老化及因阿茲海默症特定腦區導致在功能性基因途徑與樞紐基因子網絡之變化 ★ 以疾病進展趨勢挑選基因法識別正常腦老化與阿爾茨海默氏症在特定腦區引發的關鍵功能路徑與調節路徑之變化
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摘要(中)	阿茲海默症是一種普遍的、隨著時間惡化的人類神經退化性疾病，其主要病徵是因腦中不正常的β澱粉樣蛋白(Aβ)聚集堆積所導致。人們對Aβ致病性的肇因尚不清楚。在過去的幾年中，基於阿茲海默症的Aβ假說而設計的,幾種被認為非常有潛力的抗失智症藥物，包括四種用抗體結合Aβ以防止其聚集的藥物，皆在藥物試驗後期階段失敗。在藥物抗體策略中的研究假設是減少Aβ在細胞間隙中繼續累積。我們使用全基因體的基因表達數據 (取自正常老化腦組織和阿茲海默症病人死後大腦樣本)，與過去許多發現完全吻合，提及兩點作為討論: (1) 阿茲海默症致病基因與癌症之間呈現反向表現關係; (2) 微生物感染可能與阿茲海默症有關。我們最重要的推測是蛋白體酶和氧化磷酸化可能是阿茲海默症病患中受損最嚴重的兩個功能;這個狀況在病人大腦的海馬迴和後扣帶回區域最明顯。我們的研究結果顯示在阿茲海默症五個腦區的差異以及與老化的關連性，並推論出可能的標靶基因。這些結果可能有助於應用於阿茲海默症的診斷和治療。
摘要(英)	Alzheimer′s disease (AD) is a prevalent progressive neurodegenerative human disease. Several initially highly hopeful anti-AD drugs based on the amyloid-β (Aβ) hypothesis of AD have failed recent late-phase tests, and the cause of AD remains unclear. Natural aging (AG) is a high risk factor for AD. Here, five sets of gene expression microarray data from different regions of AD affected brain, and one of AG, were analyzed for identifying putatively disrupted biological pathways or functions and their abnormal molecular contents. Brain-region specificity among AD cases and AG-AD differences in KEGG-termed function disruption were identified. AG was significantly more at risk to cancer than was AD; hippocampus, the region with the strongest AD signatures, showed no risk to cancer. Our results also showed that microbial related KEGG terms were enriched in five AD affected brain regions, especially in E. coli infection Pathway. Oxidative phosphorylation (OXPHOS; Fisher’s exact test p=1.1E-20) and proteasome (p=2.0E-18) were found to be the most putatively disrupted functions and 24 new target genes were identified. Our results highlighted the heterogeneity of AD in the five brain regions, and indicated a possible AG-AD connection. These may be useful in devising strategies for the early detection of AD. Based on our results we comment on a number of recent late-phase failures of anti-AD drug trials.
關鍵字(中)	★ 阿茲海默症 ★ 老化 ★ 蛋白質體酶 ★ 氧化磷酸化 ★ 類澱粉蛋白 ★ 細菌感染	關鍵字(英)	★ Alzheimer′s disease ★ aging ★ proteasome ★ oxidative phosphorylation ★ amyloid-β ★ E. coli infection
論文目次	中文摘要 i Abstract ii Contents iv Tables of Contents v Figures of Contents v Notation Illustration vi Chapter 1. Background 1 Chapter 2. Materials and Methods 7 2.1 Gene expression microarray data source 7 2.2 Database on protein-protein interaction 8 2.3 KEGG database on biological functions and pathways 8 2.4 Databases on two type of known AD target genes 8 2.5 Computational software 9 2.6 Quality screening of data and differentially expressed genes (DEGs) 9 2.7 Selection of differentially co-expressed gene (DCE) pairs 9 2.8 Construction of networks from interacting differentially co-expressed gene (IDCE) pairs 10 2.9 Functional Profiling of the DEGs and the IGNs 11 Chapter 3. Results 12 3.1 Properties of curated gene lists 12 3.2 Thirteen genes were conspicuous in the curated gene sets 14 3.3 Five major AD culprit genes were not prominent in the curated gene sets 17 3.4 KEGG terms were enriched heterogeneously in curated gene sets 17 3.5 Oxidative phosphorylation (OXPHOS) pathway (KEGG hsa00190, 130 genes) 21 3.6 Proteasome (KEGG has03050, 47 genes) 21 3.7 Ubiquitin mediated proteolysis pathway (KEGG hsa04120, 137 genes) 21 3.8 Alzheimer’s disease pathway (KEGG has05010, 163 genes) 22 3.9 Pathogenic Escherichia coli infection pathway (KEGG hsa05130, 57 genes) 22 3.10 Pathways in cancer (KEGG hsa05200, 328 genes) 22 3.11 Thirteen genes were “AD-only” hits and ten genes were “double” hits 23 Chapter 4. Discussion 24 Chapter 5. Summary 31 Reference 32 Supplementary Figures 43 Supplementary Tables 46
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指導教授	李弘謙(Hoong-Chien Lee)	審核日期	2019-8-22
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