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研究生:張筑婷
研究生(外文):Chu-Ting Chang
論文名稱:血釩、喝豆漿、基因型rs1160312和家族遺傳與雄性禿之相關探討
論文名稱(外文):Blood Vanadium, soybean milk intake, genotype rs1160312 and family history are associated with Androgenetic Alopecia
指導教授:朱基銘朱基銘引用關係賴錦皇賴錦皇引用關係
指導教授(外文):Chi-Ming ChuChing-Huang Lai
學位類別:碩士
校院名稱:國防醫學院
系所名稱:公共衛生學研究所
學門:醫藥衛生學門
學類:公共衛生學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:中文
論文頁數:119
中文關鍵詞:雄性禿血釩豆漿基因型家族史
外文關鍵詞:Blood Vanadiumsoybean milk intakegenotypeAndrogenetic AlopeciaAndrogenetic AlopeciaSoybean milk intakeBlood VanadiumGenotypeFamily history
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研究背景
雄性禿(Androgenetic alopecia)不僅和許多慢性病有相關性,在藥物經濟中,治療雄性禿的相關藥物扮演著重要的角色。但目前沒有針對台灣的族群做雄性禿全面的研究;在遺傳方面,更沒有探討過亞洲人與雄性禿有關的基因。因此本研究將針對環境、生活型態以及基因三方面進行研究探討。
材料與方法
研究樣本來自台中縣現住人口資料檔,依其年齡及遷入時間隨機篩選出符合本研究條件者,事先郵寄問卷和人體試驗同意書至研究對象家中,並與研究對象約定特定時間至當地衛生所進行健康檢查及檢體收集。問卷回收後,以SPSS 17.0 版統計軟體進行統計分析。檢體以感應耦合電漿質譜儀(ICP-Mass)來血液與尿液中金屬元素濃度。基因部分以TaqMan SNP Genotyping Assays進行單一核甘酸多型性基因型鑑定,利用Stata加上網路的軟體(Biostatistical Resources Stata Programs)判斷是否符合哈溫平衡定律及用WHAP進行單套型分析進行Omnibus 檢定,並以卡方檢定進行單套型比例分佈情形的上是否達到統計學上顯著差異。採用多變項邏輯式迴歸分析(Multiple logistic regression analyses),以校正干擾因子進行模型統計分析。
結果
調整年齡和家族史後達統計上的顯著相關者,分別為居住在空氣污染地區有中重度雄性禿的風險為3.04倍(P= 0.03),睡眠時數不足六小時有中重度雄性禿的風險為4.47倍 (P= 0.04),頭皮經常出油者有中重度雄性禿的風險是非油性者的4.12倍(P< 0.01);再將血液中重金屬濃度相互調整,釩為中重度雄性禿的保護因子(P= 0.04);rs1998076的對偶基因為A型得到中重度雄性禿的風險為0.52倍[95% CI,0.31-0.85], rs913063的對偶基因為A型得到雄性禿的風險為1.67倍[95% CI, 1.05-2.65],rs1160312的對偶基因為A型得到雄性禿的風險為1.71倍[95% CI, 1.08-2.71], rs201571的對偶基因為T型得到雄性禿的風險為1.87倍[95% CI, 1.17-2.98]。邏輯斯迴歸模型為模型置入喝豆漿、rs1160312、血釩和家族史以檢驗中重度雄性禿時,AUC值達90%。
結論
我們的研究中發現,居住的區域、血液中的重金屬釩濃度、睡眠時間、頭皮狀態和喝豆漿都與中重度雄性禿有密不可分的關係,除此之外,以SNP做為遺傳標記,篩選出有效的臨床檢測基因,不但可提供雄性禿之風險評估,也可做為預測雄性禿嚴重程度及其預後之指標。
Background
Androgenetic alopecia (AGA) is a complex disease, which is one of most common types of hair loss and a progressive hair losing. Androgenetic alopecia (AGA) is associated to many kinds of chronic diseases and estimated to affect 40-50% of adult men and women who are also suffered by psychologically detrimental and negative body-image perception. Moreover, AGA-related treatments are a major player in the pharmaceutical economics. However, there was no study published about all factors of genetics, environment exposure and life style. The more comprehensive AGA–associated factors of life style, environmental exposures and pathogenic nucleotide polymorphisms were investigated in the study.
Methods and Materials
The study population in this study selected the residents who living in Taichung County for five years with a population household registry of Taichung County at that time, and eligible samples that were selected according to their age, the move-in date and the residence place of Township. We mailed a questionnaire and informed consent to each participant, and then recalled the questionnaires, informed consent, and with informed consent took scalp photos and blood sample by public health nurses in the local public health center in a specific day. A health screening process was done to ensure the health of the participant.
We divided the region of air pollution into the exposed area and non-exposed area, in addition to we took the venous blood sample for a measurement of heavy metals in the used of ICP-MASS. Genotyping was performed using TaqMan® Assays commercially available Pre-made TaqMan® Genotyping assays.
The data of environmental exposure and life style were drawn from the questionnaire during the cross-sectional step. Collection for genetic polymorphisms was a matched case-control study. Age, villages, and smoking status are matched. Genetic analysis was used gene counting method to estimate the genotype frequencies of single nucleotide polymorphism. Genotype frequencies of samples were tested with Hardy-Weinberg equilibrium.
We would estimate odds ratios of AGA–associated factors using multiple logistic regression analyses, and adjust the confounding factors. The statistical software SPSS ver. 16.0 was used to analyze the data.

Results
The personal characteristics of sleeping hours, oily scalp and consuming soy milk were significantly different between 2 groups of AGA I-III and IV-VII, adjusting age and family AGA. The blood vanadium concentration was significantly different between 2 groups of AGA I-III and IV-VII, adjusting age, family AGA and other 10 concentrations of blood metals. The mutant allele of SNP rs1998076 was protective effect with odds ratio (OR) 0.52 [95% CI, 0.31–0.85] to AGA. Other SNPs (rs913063, rs1160312 and rs201571) were risk with ORs 1.67 (1.05-2.65), 1.71 (1.08-2.71) and 1.87 (1.17-2.98), respectively. The haplotypes ACG and GTA of rs1998076, rs201571 and rs1160312 were significantly different from the wild type GCG. Meanwhile, comparing to GCG, ACG was protective OR 0.62 (0.41-0.93) and GTA was risk OR 1.48 (1.01-2.17).
Conclusion
The present study is the first inclusive attempt to estimate multiple factors of AGA in Taiwanese men. Results of the study determine 4 factors of consuming soy milk, blood vanadium, SNP rs1160312 and family AGA by matching age, which can correspond to environmental, life.
目 錄
摘要 I
ABSTRACT III
目 錄 V
第一章 緒論 - 1 -
第一節 研究背景及動機 - 1 -
第二節 研究之必要性與重要性 - 4 -
第三節 研究目的 - 5 -
第二章 文獻回顧 - 6 -
第一節 空氣污染影響禿頭 - 6 -
2.1.1 空氣污染造成體內重金屬殘留 - 6 -
2.1.2 禿頭與體內重金屬 - 6 -
第二節 生活型態與雄性禿的關係 - 8 -
2.2.1 相關的危險因子 - 8 -
2.2.2 生活壓力的測量工具 - 8 -
第三節 雄性禿的易感性基因 - 10 -
第三章 研究方法與步驟 - 11 -
第一節 研究對象 - 11 -
第二節 名詞解釋 - 13 -
3.2.1 雄性禿(Androgenetic alopecia) - 13 -
3.2.2 空氣污染 - 14 -
3.2.3 生活型態 - 14 -
3.2.4 易感性基因 - 15 -
第三節 研究變項操作型定義 - 24 -
3.3.1自變項 - 24 -
3.3.2依變項 - 27 -
第四節 研究架構與研究假設 - 28 -
3.4.1 研究架構 - 28 -
3.4.2 研究假設 - 29 -
第五節 研究工具 - 30 -
第六節 資料收集方法與步驟 - 31 -
第七節 實驗方法 - 32 -
3.7.1 重金屬檢測之實驗原理與流程 - 32 -
3.7.2 相關易感性基因檢測流程 - 39 -
第八節 資料處理方法 - 46 -
3.8.1 樣本大小與檢力 - 46 -
3.8.2 相關因素探討 - 46 -
3.8.3 重金屬分析探討 - 47 -
3.8.4 基因型分析探討 - 47 -
3.8.5 研究假設與各統計分析方法 - 48 -
第九節 研究流程 - 49 -
第十節 研究計畫流程表 - 50 -
第四章、結果 - 51 -
第一節 在各年齡層的男性雄性禿之分布情形 - 51 -
第二節 空氣污染區與雄性禿的關係 - 52 -
第三節 體內重金屬與雄性禿的關係 - 53 -
4.3.1 體內重金屬濃度連續值 - 53 -
4.3.2 體內重金屬濃度四分位類別 - 54 -
4.3.3 人體必需之微量元素 - 56 -
第四節 生活型態與雄性禿的關係 - 58 -
第五節 單核苷酸多態性與雄性禿的關係 - 60 -
4.5.1 rs1998076 - 61 -
4.5.2 rs913063 - 62 -
4.5.3 rs1160312 - 63 -
4.5.4 rs201571 - 64 -
4.5.5 單套型分析 - 65 -
第六節 建立雄性禿與各相關危險因子的參考模式 - 67 -
第五章、討論 92
第一節 與雄性禿相關之危險因子 92
5.1.1 空氣污染地區與重金屬濃度的相關性 92
5.1.2 體內重金屬濃度與雄性禿者的相關性 93
5.1.3 生活型態與雄性禿者的相關性 95
5.1.4基因遺傳與雄性禿的相關性 97
第二節 最適模式 99
第六章、結論與未來展望 100
參考文獻 101
附錄 106


表目錄
表一、綜合各研究與雄性禿相關之SNP位點 - 19 -
表二、挑選與雄性禿相關之各研究的SNP位點 - 22 -
表三、GENOTYPE DETAIL - 23 -
表四、使用卡方檢定驗證參與者與非參與者之性別分布情形 - 70 -
表五、男性在各年齡別的雄性禿分布情形 - 71 -
表六、空氣污染區與雄性禿之相關檢定 - 73 -
表七、體內重金屬濃度與雄性禿之相關檢定 - 74 -
表八、體內重金屬濃度(四分位分組)與雄性禿之相關檢定 76
表九、人體必需之微量元素與雄性禿之相關檢定 80
表十、生活型態與雄性禿之相關檢定 82
表十一、男性的GENOTYPES和RISK-ALLELE FREQUECCE與雄性禿之相關檢定 84
表十二、RS1998076、RS201571和RS1160312與雄性禿之單套型分析檢定 88
表十三、最適模式與雄性禿之相關檢定 89
表十四、整題模型與雄性禿之AREA UNDER THE CURVE分析 90


圖目錄
圖一、HAMILTON- NORWOOD分類法 - 13 -
圖二、LUDWIG 分類法 - 14 -
圖三、OMIM (ONLINE MENDELIAN INHERITANCE IN MAN DATABASE) - 16 -
圖四、研究架構圖 - 28 -
圖五、感應耦合電漿分析儀測定流程圖 - 38 -
圖六、研究流程圖 - 49 -
圖七、研究計畫流程表(甘梯圖) - 50 -
圖八、男性之雄性禿的年齡別盛行率 - 72 -
圖九、使用HAPLOVIEW 4.2 SOFTWARE進行LD PLOT 86
圖十、使用HAPLOVIEW 4.2 SOFTWARE進行HAPMAP中(漢+日本)4個SNP資訊所計算的R2 87
圖十一、利用本研究4個SNP的實際資料所計算的R2 87
圖十二、模型與雄性禿之ROC CURVE 91


附錄目錄
附錄一. 十一個重金屬間的PEARSON相關 106
附錄二.1 挑選最適模式的參考準則 - 107 -
附錄二.2 挑選最適模式的參考準則 - 108 -
附錄二.3 挑選最適模式的參考準則 - 109 -
附錄二.4 挑選最適模式的參考準則 - 111 -
附錄二.5 挑選最適模式的參考準則 - 112 -
附錄二.6 挑選最適模式的參考準則 - 113 -
附錄二.7 挑選最適模式的參考準則 - 114 -
附錄二.8 挑選最適模式的參考準則 - 115 -
附錄二.9 挑選最適模式的參考準則 - 116 -
附錄二.10 最適模式的參考準則 - 117 -
附錄三. 最適模式之建立比較表 - 118 -
附錄四. 調查員間的相關矩陣 - 119 -
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