臺灣博碩士論文加值系統

背景
嚴重急性呼吸道症候群 (SARS) 與多數傳染病一樣，感染後的嚴重程度含括自限性的類流感症狀至死亡；從傳染病的角度而言，這是病毒 (如：感染的病毒量、病毒株)、宿主 (如：二次免疫力、宿主基因型) 與環境 (如：感染方式、醫療) 的交互作用結果。而由於SARS為興新傳染病，個體間不存在二次免疫的差異，且無證據指出不同的病毒變異株或不同的感染方式會導致發病嚴重度有所差異。已知的危險因子主要是老年、同時帶有其他疾病 (如B型肝炎、糖尿病…)、發病初期具有高病毒量…等等。除此之外，嚴重程度的差異也可能是由於被感染者的基因多型性所致，因此本研究欲探討各階段免疫反應過程中所參與的基因之單一核苷酸多型性對SARS嚴重程度影響。

方法
本研究為一以族群為基礎的病例對照研究，共有108位自願參與的SARS確診病患與282位自國家基因體中心「超級對照組基因資料庫」(Super Control Genomic Database)中隨機選取的健康對照族群。根據已知與抗病毒感染相關之免疫基因，共選取分屬於64個基因上的276個單一核苷酸多型性。各基因多型性與SARS嚴重程度之關係先以精確Mantel-Haenszel卡方檢定之，再以累積邏輯斯迴歸模式估算危險對比值與95％信賴區間。最後對可能存在交互作用的因子再進行分層分析。SARS病人嚴重程度依照病程長短分為輕微(<15天)、中度(15-28天)及嚴重(>28天)。

結果
重症的SARS感染分別與TLR3(C6300T) ,TRAF6(A-9423C)及HO-1(T-495A) 3個SNP顯著相關。在調整年齡的影響後，帶有TLR3(C6300T) 基因型TT或是TRAF6(A-9423C)基因型CC/AC的人相對於完全不具有這些危險基因型的人，成為重症患者的危險性是4.06倍；而帶有HO-1(T-495A)基因型AA/AT的人相對於帶基因型TT的人則有2.77倍的危險性。基因與年齡的交互作用顯示它們的影響是獨立作用的，但在低年齡層的人，基因的影響比在高年齡層來得大。

結論
雖然已知TLR3可負責抗原辨識(dsRNA)並啟動適應性免疫反應，且TRAF6為其訊息傳導路徑中的必要蛋白，而HO-1則是一重要的抗發炎反應調控蛋白，但對於這些基因的多型性在傳染病的病理機轉上所扮演的角色並不清楚。或許這些SNP所造成的改變很輕微，但些許的差異經過一連串的訊息傳遞後也可能造成極大的影響，尤其當這些改變的標靶為平常含量極低微的細胞激素。因此探討宿主基因多型性對於病程發展的影響除了有助於釐清各種免疫反應所扮演的角色、致病機制及免疫反應和病理機轉之間的關係外，更有助於藥物的設計與研發。

Background – Patients with severe acute respiratory syndrome (SARS) exhibits signs and symptoms of respiratory and systemic infection that follows with clinical course of varying severity, including death due to acute respiratory distress syndrome (ARDS). In addition to advanced age, comorbidity, and high viral load, genetic predisposition has been postulated to influence the immune response and clinical course. This study aims to identify potential genetic effectors involved in the pathogenesis of SARS.

Method – This is a population-based case-control study that enrolled 108 unrelated laboratory-confirmed SARS patients and 333 healthy Taiwanese as reference. Gene products that are known or predicted to be involved in host response were selected for study of polymorphism. SARS patients are divided into 3 groups based on the duration of illness as index for severity: <15 days for mild, 15~28 days for intermediate, and >28 days for severe case.

Result – Clinical severity was significantly associated with certain genotype of three SNPs: a nonsynonymous substitution in the coding region of Toll-like receptor 3, TLR3(L412F) and in the promoter regions of TNF receptor-associated factor 6- TRAF6 (A-9423C) and heme oxygenase-1 - HO-1(T-495A). TLR3 is directly upstream to TRAF6 in the interferon-inducing pathway, and the joint effect of TLR3 or TRAF6 in the pathway was considered, termed TLR3-TRAF6. The severe SARS patients had 4.06-folds (95% CI=1.69~9.74, p=0.002) increased odds of possessing any susceptible genotypes of TLR3-TRAF6 (TLR3(6300T/T), TRAF6(-9423C/C) or (A/C)) and 2.77-folds (95% CI=1.69~9.74, p=0.002) of possessing susceptible genotype of HO-1 (HO-1(-495A/A) or (A/T)) than patients with shorter clinical course in a cumulative logit model. This genetic effect is more profound for the younger SARS patients (<40 yr) than the elder group.

Conclusion - TLR3 recognizes double-stranded RNA, and together with TRAF6, activates interferon production; HO-1 can protect tissues from immune-mediated injury. Along with our previous report of two interferon-γ- inducible genes, FGL2 - a prothrombinase and CXCL10 - a chemokine activating TH1 response, our results strongly support the hypothesis that genetic predisposition to certain host responses participate in the pathogenesis of severe SARS-CoV infection. Identifying pathways participating in viral pathogenesis can provide insights to formulating therapeutic interventions for SARS, and probably ARDS from other causes.

Abstract Ⅰ
Abstract (in Chinese) Ⅲ
Content Ⅳ
List of tables Ⅴ

Introduction 1
Methods
Study subjects 3
Selection of genes and SNPs 4
SNP Genotyping 5
Statistical analyses 5
Results
Characteristics of study subjects 7
SNPs associated with severity of SARS 7
Combined effect of TLR3 and TRAF6 10
The interaction between gene and age 11
The interaction between genes 12
Multifactorial analysis in a stepwise selection model 13
Discussion 14
References 20
Appendices
Ⅰ.Supplement tables 30
Ⅱ.Gene map of TLR3 35
Ⅲ.LD map of TLR3 36

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