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研究生: 李佩芬
Lee, Pei-Fen
論文名稱: 探勘突變熱點以發掘慢性B型肝炎之臨床生物標記
Discovering Clinical Biomarkers of Chronic Hepatitis B by Mining Mutation Hotspots
指導教授: 曾新穆
Tseng, Vincent S.
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 醫學資訊研究所
Institute of Medical Informatics
論文出版年: 2011
畢業學年度: 99
語文別: 英文
論文頁數: 83
中文關鍵詞: 共變異網路單點突變核前/核心蛋白B型肝炎病毒e抗原突變熱點
外文關鍵詞: covariance network, point mutation, HBeAg, Hepatitis B virus, precore/core protein, mutation hotspot
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  • B型肝炎病毒是最常見的DNA病毒,可能會導致肝炎、肝硬化以及肝癌的發生。近幾十年來,肝癌是造成人類死亡的主要癌症之一。儘管人類仍持續感染B型肝炎病毒,但血清中的病毒量以及宿主的免疫反應會因人而異。越來越多有關B型肝炎病毒的研究宣稱由核前/核心開放閱讀框架轉譯而來的B型肝炎e抗原和核心抗原與病毒的複製有關,進而導致宿主免疫產生反應和感染。由於高頻率的突變發生在B型肝炎病毒的核前/核心蛋白質序列上可能會改變蛋白質的表現與功能,然而要如何正確地分析這些序列是一個挑戰,因此本研究將探討序列上的突變熱點以發掘慢性B型肝炎臨床特徵之生物。我們收集了23位感染慢性B型肝炎病毒長達一年且e抗原陽性的病人,依照每個月所測得血清中的ALT、DNA以及e抗原的量,這段期間至少包含4個具代表性的時間點,可將病人分為不同的群體。接著將B型肝炎病毒的核前/核心DNA序列以人為方式轉譯成胺基酸序列,並分析核前/核心蛋白質序列上的突變與臨床以及血清結果的關係。我們利用一個結合共變異網路與單點突變規則的方法找到在核前/核心蛋白質序列上具代表性的突變點。利用文獻驗證的結果顯示這些突變與病毒動力學、是否有e抗原血清轉換、病毒基因型以及胺基酸屬性的改變有高度的相關性。除此之外,我們發展了一個高覆蓋率的特徵樹,可以提供臨床醫師給予在早期受到感染的病人一個較好的療程,縱使這些病人尚未有明顯的臨床病徵。再者,當病人被分為e抗原血清轉換與否時,我們在B型肝炎病毒基因型C之核前/核心胺基酸序列中,我們發現胺基酸位置116與126存在一個顯著差異的胺基酸轉換。

    Hepatitis B virus (HBV) is the most common DNA virus that may cause hepatitis, cirrhosis and hepatocellular carcinoma (HCC). In recent decades, HCC is one of major causes of cancer death worldwide. Although many people are persistently infected with HBV, the serum viral load and host immune response varies from person to person. An increasing number of research articles on chronic hepatitis B have claimed that the activities of two proteins, hepatitis B e antigen (HBeAg) and core antigen (HBcAg), encoded by precore/core open reading frame (ORF), are associated with the DNA replication of HBV, in turn leading to the host immune response and infection. Because the high rate of mutations in HBV precore/core protein sequences during infection will alter the protein expression and/or function, how to properly analyze these sequences is a challenge. Therefore, these studies discovered clinical biomarkers of chronic hepatitis B patients by mining mutation hotspots. We collected a one year follow-up study with a total number of 23 patients with HBeAg-positive chronic hepatitis B. Serum alanine aminotransferase, HBV DNA and HBeAg levels were measured monthly and used as the criteria for clustering the patients into different subgroups. Using monthly derived precore/core ORF sequences from HBV genomic DNA, sequenced and artificially translated into amino acid sequences from each patient at least four representative time points, we analyzed the amino acid mutations within HBV precore/core proteins responsible for serologic and clinical outcome in each subgroup. Using a combination of covariance networks and point mutation rules, we identified different discriminative mutations within precore/core protein sequences. Validation with literature-curated mutation hotspots showed that these discriminative mutations were strongly associated with the patterns of viral kinetics, presence of HBeAg-seroconversion in sera, HBV genotypes and changes in amino acid properties. In addition, we developed a feature tree with high coverage rates, which is applicable for clinicians to prescribe patients a suitable treatment at early stage of HBV infection even though the patients exhibit no obvious symptoms. Furthermore, when patients were divided into two subgroups – HBeAg-seroconversion and HBeAg-nonseroconversion, we further discovered a significant alteration of amino acids at HBV genotype C precore/core position 116 and 126.

    摘要 I Abstract II 誌謝 IV 1. Introduction 1 1.1 Background 1 1.1.1 Hepatitis B Virus 1 1.1.2 Clinical Feature and Natural Course of Hepatitis B Virus 4 1.2 Motivation 6 1.3 Contribution 7 1.4 Thesis Organization 8 2. Related Work 9 2.1 Covariance Network 9 2.2 Point mutation 10 3. Materials and Methods 12 3.1 Schematic Overview of Data Processing 12 3.2 Patients and Study Design 13 3.3 Polymerase Chain Reaction Amplification of The Precore/core ORF and Genotyping 14 3.4 Cloning Process 15 3.5 An Illustration of Computational Methods Applied on Sequence Data 16 3.6 Statistical Analysis 17 4. Experimental Results 18 4.1 A Significant Improvement to Increase The Proportion of Mutation Hotspots Within Networks 18 4.2 Informative Networks Correspond to Clinical Signatures 20 4.3 HBV Genotype C Infections Accompanied with A Cyclic Process of Point Mutation 21 4.4 Analyzing Networks Between All Patient Subgroups at Early Stage During HBV Infection 22 4.5 Development of a Feature Tree 23 4.6 Identification of Potential Biomarkers for The Prediction of HBeAg-seroconversion 24 4.7 Alteration of Amino Acids at HBV Precore/core 116 and 126 is Associated with Genotype C HBeAg-seroconversion 25 5. Conclusions and Future Work 27 5.1 Conclusions 27 5.2 Future Work 33 6. References 35 VITA 83

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