臺灣博碩士論文加值系統

目前已知許多人類疾病的生成，如各種癌症、代謝性疾病、神經學疾病、以及自體免疫疾病等，與DNA甲基化有密切的相關。芳香烴受體阻遏物(aryl hydrocarbon receptor repressor, AHRR) 基因的cg05575921位點與吸菸和肺癌的風險有關，而SOX2 (SRY (sex determining region Y)-box 2) 啟動子甲基化也與肺癌風險相關。吸菸以及空氣中的顆粒物質 (particulate matter) 皆是人體暴露到多環芳香烴 (polycyclic aromatic hydrocarbon, PAH) 的重要途徑。除了吸菸之外，顯少有文獻探討AHRR基因cg05575921位點甲基化與其他多環芳香烴暴露來源的相關性。此外，對於生活在空氣污染程度不同地區的居民，尤其是PM2. 5的污染與SOX2啟動子甲基化的研究也是非常少的。本研究目的是在探討臺灣非吸菸成年人，居住在空氣污染程度不同地區的居民，其AHRR基因cg05575921位點的甲基化程度以及SOX2啟動子甲基化程度是否有所差異。本研究資料取自2008-2015年臺灣人體生物資料庫，研究參與者年齡介於30-70歲，且排除不具本國籍或經醫生確診罹患癌症者。研究資料包含甲基化資料、吸菸行為、居住地、年齡、及二手菸暴露等資料。我們排除目前仍在吸菸、曾經吸菸以及資料不完整的樣本，最後共有708名參與者，包括279名男性和429名女性納入cg05575921(AHRR)甲基化程度和PM2.5的相關性分析。由於臺灣PM2.5濃度由北向南逐漸遞增，因此，本研究將研究區域劃分為北部、中北部、中部和南部地區。另外，關於SOX2啟動子甲基化程度與PM2.5之間的關聯，共有461名參與者，包含176名男性和285名女性，我們將參與者的現住地區分為北部和中南部地區進行分析。在cg05575921(AHRR)甲基化程度和PM2.5的研究結果顯示，居住在中北部、中部和南部地區的居民，其cg05575921位點的甲基化程度是低於北部地區。雖然只有在中部(β = − 0.01003, P = 0.009) 和南部地區 (β = − 0.01480, P < 0.001) 有達到統計顯著差異，但是在整體的趨勢上，可以看到cg05575921位點的甲基化程度隨著愈往南部地區下降的幅度愈大，且呈現線性趨勢 (P trend < 0.001) 。除此之外，我們亦將空氣中PM2.5的濃度納入回歸分析時，PM2.5的濃度愈高cg05575921位點的甲基化程度也有愈低的趨勢 (β = -0.00115, P < 0.001) 。另外，在SOX2啟動子甲基化程度和PM2.5的研究結果顯示，中南部地區無論男性 (β = 0.00331，P = 0.026) 或女性 (β = 0.00514，P < .001) ，SOX2啟動子區域的甲基化程度顯著高於北部地區。結論，本研究發現在不同的PM2.5污染地區，居民體內cg05575921(AHRR)位點甲基化程度與PM2.5污染程度呈現負相關，居住在南部地區的居民AHRR甲基化程度最低，其次是中部及中北部地區。我們另外將空氣中PM2.5污染濃度帶入回歸模型中，也發現PM2.5濃度和cg05575921位點甲基化程度呈負相關。同時，我們也發現無論男性或女性，居住在中南部地區的居民，其SOX2啟動子甲基化程度顯著高於北部地區。對非吸菸族群而言，cg05575921(AHRR)位點及SOX2啟動子的甲基化程度可能代表著PM2.5的暴露程度，同時也反映出與PM2.5相關疾病的易感受性。因此，cg05575921(AHRR)位點及SOX2啟動子的甲基化程度對於看似健康的非吸菸者而言，也許可以做為臨床鑑定或癌症的早期診斷指標。

DNA methylation is associated with cancer, metabolic, neurological, and autoimmune disorders. Hypomethylation of the gene, aryl hydrocarbon receptor repressor (AHRR) especially at cg05575921 is associated with smoking and lung cancer. SOX2 promoter methylation is also associated with lung cancer risk. Both smoking and particulate matter (PM) are sources of polycyclic aromatic hydrocarbon (PAH). Studies on the association between AHRR methylation at cg05575921 and sources of polycyclic aromatic hydrocarbon (PAH) other than smoking are limited. In addition, little has been done to assess SOX2 promoter methylation in individuals living in areas with different levels of air pollution, especially particulate matter with diameter < 2.5 μm (PM2.5). The aim of this study was to assess the DNA methylation patterns at cg05575921 (AHRR) and promoter region of SOX2 in non-smoking Taiwanese adults living in areas with different levels of PM2.5. Data on cg05575921 (AHRR) and SOX2 promoter methylation, smoking, residence, age, and exposure to second-hand smoke (SHS) among others were extracted from the Taiwan Biobank Dataset (2008-2015). Current and former smokers, as well as individuals with incomplete information, were excluded from the study. The study participants were between the ages of 30 and 70 years. To determine the association between cg05575921 (AHRR) and PM2.5, a total of 708 participants comprising 279 men and 429 women were included in the analysis. Since PM2.5 levels have been shown to increase as one moves from the north through the center towards the southern parts of Western Taiwan, the study areas were categorized into northern, north-central, central, and southern regions. To determine the association between SOX2 promoter methylation and PM2.5, a total of 461 non-smokers consisting of 176 men and 285 women were included in the analysis. Participants’ residences were grouped under northern and central/southern areas. Compared with the northern area (reference area), living in north-central, central, and southern areas was associated with lower methylation levels at cg05575921. However, these associations were significant only in those living in central and southern areas were significant (β = − 0.01003, P = 0.009 and β = − 0.01480, P < 0.001, respectively. Even though methylation levels in those living in the north-central areas were not statistically significant, the test for linear trend was significant (P < 0.001). When PM2.5 was included in the regression model, a unit increase in PM2.5 was associated with 0.00115 lower cg05575921 methylation levels (β = -0.00115, P < 0.001). Compared with the northern areas, SOX2 promoter region was significantly hypermethylated in both men and women living in the central and southern areas. The regression coefficient (β) was 0.00331 (P = 0.026) in men and 0.00514 (P < .001) in women. In conclusion, living in PM2.5 areas was inversely associated with AHRR methylation levels at cg05575921. The methylation levels were lowest in participants residing in southern areas, followed by central and north-central areas. Moreover, the inclusion of PM2.5 in the regression model yielded an inverse association between methylation levels at cg05575921 and PM2.5. SOX2 was significantly hypermethylated in both men and women residing in central and southern areas. Methylation at cg05575921 (AHRR) and SOX2 promoter region in non-smokers might indicate different exposures to PM2.5. Moreover, it might reflect a predisposition to lung cancer which is a PM2.5-related disease. Hence, both cg05575921 (AHRR) and SOX2 promoter methylation in seemingly healthy non-smokers might be useful in the clinical identification or early diagnosis of cancer.

ACKNOWLEDGMENTS i
CHINESE ABSTRACT iii
ABSTRACT v
DEDICATION vii
TABLE OF CONTENTS xiii
LIST OF FIGURES xi
LIST OF TABLES xii
LIST OF ABBREVIATIONS xiii
LIST OF APPENDICES xv
CHAPTER ONE 1
1.0. INTRODUCTION 1
1.1. Background 1
1.2. Justification 4
1.3. Research objectives 6
1.3.1. Main objective 6
1.3.2. Specific objectives 6
CHAPTER TWO 7
2.0. LITERATURE REVIEW 7
2.1. Clinical importance of DNA methylation 7
2.1.1. Early diagnosis of cancer 7
2.1.2. Monitoring cancer prognosis 8
2.1.3. Cancer therapy 9
2.2. Hypomethylation and hypermethylation 9
2.3. Role of hypomethylation and hypermethylation in gene expression and cancer 10
2.3.1. AHRR gene 11
2.3.2. SOX2 gene 13
2.4. Factors associated with DNA methylation 15
2.4.1. Environmental factors 15
2.5. Air pollution in Taiwan 20
CHAPTER THREE 22
3.0. MATERIALS AND METHODS 22
3.1. Data sources 22
3.1.1. Taiwan Biobank 22
3.1.2. Taiwan Air Quality Monitoring Network 23
3.2. Data collection 24
3.2.1. Determination DNA of methylation 25
3.2.2. Study areas and PM2.5 26
3.3. Study participants 26
3.4. Statistical analysis 27
CHAPTER FOUR 29
4.0. RESULTS 29
4.1. AHRR (cg05575921) methylation 29
4.1.1. Basic characteristics 29
4.1.2. PM2.5 concentrations 30
4.1.3. Association between living in PM2.5 areas and AHRR (cg05575921) methylation 30
4.1.4. Association between mean PM2.5 concentrations and AHRR (cg05575921) methylation 31
4.2. SOX2 promoter methylation 32
4.2.1. Basic characteristics 32
4.2.2. PM2.5 concentrations 33
4.2.3. Association between living in PM2.5 areas and SOX2 promoter methylation 34
4.2.4. Association between mean PM2.5 concentrations and SOX2 promoter methylation 35
CHAPTER FIVE 37
5.0. DISCUSSION 37
5.1. Association between AHRR (cg05575921) methylation and PM2.5 37
5.2. Association between SOX2 promoter methylation and PM2.5 39
5.3. Strengths and limitations 41
CHAPTER SIX 43
6.0. CONCLUSIONS AND RECOMMENDATIONS 43
6.1. Conclusions 43
6.1.1. Association between AHRR (cg05575921) methylation and PM2.5 43
6.1. 2. Association between SOX2 methylation and PM2.5 43
6.2. Recommendations 44
REFERENCES 45
APPENDICES 74

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