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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 林慧玲(Fe-Lin Lin Wu) | |
dc.contributor.author | Chun-Ming Wen | en |
dc.contributor.author | 温俊銘 | zh_TW |
dc.date.accessioned | 2021-07-09T15:51:55Z | - |
dc.date.available | 2023-10-11 | |
dc.date.copyright | 2018-10-11 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-08-08 | |
dc.identifier.citation | 1. Johnson HJS KS. Solid-organ transplantation. In: DiPiro JTT, R.L.; Yee, G.C., ed. Pharmacotherapy. 6 ed. New York: McGraw-Hill; 2005.
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/76406 | - |
dc.description.abstract | 臨床觀察發現腎臟移植的病人,即便使用相同劑量的tacrolimus(TAC),個體間的血中濃度變異還是很大。過去研究發現有許多臨床因素以及基因多型性可能會影響TAC的血中濃度,然而所獲得的結果缺乏一致性。本研究是第一個將所有可能影響TAC血中濃度的因素納入分析,探討各種因素對臺灣腎臟移植病人TAC血中濃度影響的研究。本研究於2008年1月1日至2015年7月31日所有在本醫學中心接受腎臟移植的病人中,選取移植後使用TAC作為免疫抑制劑且持續服用至少6個月,移植時的年齡介於20到65歲的病人。排除條件包含再移植或多重器官移植、非臺灣人以及人類免疫缺乏病毒反應呈陽性的病人。將研究期間仍持續追蹤並同意參與此臨床試驗,簽署受試者知情同意書(informed consent)後,取得檢體進行基因多型性分析的病人納入本研究。本研究中TAC主要以劑量調整谷濃度(dose normalized trough concentrations,dnC0;與dosing weight and dose normalized trough concentrations,dnC0/DW)作為藥動學參數,並在迴歸分析時進行對數轉換,確保資料符合常態分布。使用三個評估點:腎臟移植出院前、移植後3個月以及移植後6個月。統計方法在挑選候選因子以及綜合臨床及基因多型性因素分析時分別使用單變項及多元迴歸分析,連續性資料使用獨立樣本t檢定或曼恩-惠尼U檢定,同一病人在不同時間點的TAC濃度資料與檢驗數值使用單因子重複量測變異數分析、類別資料如性別及基因多型性等則使用Chi-squared test以及Fisher’s exact test。本研究納入98個腎臟移植病人,經多元迴歸分析,發現CYP3A5*3基因型在3個時間點皆為影響TAC ln dnC0或ln dnC0/DW最重要的因子,R2值介於0.35至0.45,且隨著時間增加。其他有顯著影響力的基因型包括ABCB1 (C3435T)以及ABCB1 (G2677T/A),但解釋力不高。ABCB1 (C3435T)基因型在移植手術出院前和移植後6個月的R2值分別為0.05和0.02;ABCB1 (G2677T/A) 基因型移植後3個月的R2值為0.05。顯著影響TAC ln dnC0或ln dnC0/DW的臨床因素則在3個時間點間各有差異,解釋能力較低,總和的R2值介於0.10至0.15。在移植手術出院前重要的臨床因素有mycophenolate mofetil(MMF)或mycophenolate sodium(MPS)的每日劑量、移植時的年齡以及direct bilirubin(D-bil)。在移植後3個月為total bilirubin(T-bil)、類固醇的每日劑量、性別以及移植時的年齡;在移植後6個月為有無使用MMF或MPS、類固醇的每日劑量、D-bil以及hematocrit(Hct)。在次族群分析中,發現CYP3A5不表現者會更容易受到其他基因多型性的影響,包括ABCB1 (C3435T)以及ABCB1 (G2677T/A),其R2值在3個評估點單變項分析相較於全體病人分析時的0.02-0.07增加至0.15-0.20。此外,在CYP3A5表現者中,有高達82.2 %的病人同時帶有CYP3A4*1G變異,此變異同樣會使TAC的代謝增加;反之,在CYP3A5不表現者中,有92.2 %的病人未帶有CYP3A4*1G變異。顯示兩基因多型性在分配上有顯著相關。最後,比較移植後抗排斥藥物組合,發現有使用MMF或MPS的病人相對於未使用MMF或MPS的病人(二重療法),在移植後6個月內的3個評估點,其TAC dnC0有較高的趨勢,但未達到統計顯著。本研究也提供了完整的臺灣族群TAC相關代謝途徑的基因多型性分布頻率資料。其中,CYP3A5表現者與不表現者的比例分別為47 %及53 %。在腎臟移植的病人,CYP3A5*3基因型在移植後的六個月內都是影響TAC ln dnC0或ln dnC0/DW的最重要因素。因此,建議在發生TAC劑量調整困難的病人,可以考慮檢測病人的CYP3A5*3基因,作為未來TAC劑量調整的參考。影響TAC ln dnC0或ln dnC0/DW的臨床因素會隨著手術後時間而有些變化,當上述因子有顯著改變時,需要密切監測病人的TAC血中濃度。在次族群分析中發現CYP3A5不表現者會更容易受到其他基因多型性的影響,包括ABCB1 (C3435T)以及ABCB1 (G2677T/A),且CYP3A5*3與CYP3A4*1G兩個基因多型性在分配上有顯著相關。因此臨床上在參考及應用病人基因多型性資料時也應注意多個基因多型性之間的關連性。MMF及MPS兩個藥品對TAC藥動學的影響可能需要未來更多研究來解答。 | zh_TW |
dc.description.abstract | Large interindividual and intraindividual variations of tacrolimus (TAC) pharmacokinetics (PK) exist in renal transplant recipients. Many factors were reported to influence the PK of TAC. However, there are limited studies explored the influence of both clinical and genetic factors, esp. in Taiwanese renal transplant patients. This is the first study investigated both genetic and clinical factors that significantly influenced TAC PK in Taiwanese at three different time points after renal transplantation. This study recruited all the candidates from kidney transplant recipients who underwent transplantations in our medical center between January 1, 2008, and July 31, 2015, received TAC as immunosuppressant for at least 6 months, and transplanted at the age of 20 to 65 years. Exclusion criteria were retransplantation, multiorgan transplantation, non-Taiwanese subjects and human immunodeficiency virus (HIV) positive patients. All patients enrolled were followed up during study period and their blood samples were taken for genetic study after signing informed consent. The concentrations of TAC were dose normalized, including dnC0 (dose normalized trough concentrations) and dnC0/DW (dosing weight and dose normalized trough concentrations). These two variables were log-transformed in regression analyses to ensure a normal distribution. This study evaluated the dnC0 and dnC0/DW of TAC at three time points: the last steady state C0 before discharge for transplant surgery, 3 months after transplant and 6 months after transplant. Univariate and multiple regression were used to select the candidate independent variables and to identify the significant factors that influenced the ln dnC0 and ln dnC0/DW. Independent t-test or Mann-Whitney U test were used for continuous data. One-way Repeated Measurement ANOVA (analysis of variance) was used to compare lab data and TAC C0 within the same patient at different time points. Chi-squared test and Fisher's exact test were used for categorical data. A total of 98 kidney transplant recipients were enrolled in the study. At all time points, CYP3A5*3 polymorphism was the most significant factor associated with TAC ln dnC0 or ln dnC0/DW, with a R2 of 0.35-0.45, which increased over time. Other significant SNPs included ABCB1 (C3435T) and ABCB1 (G2677T/A), but the impact was small. The R2 of ABCB1 (C3435T) polymorphism at the time before discharge after transplantation and 6 months after transplant were 0.05 and 0.02, respectively. The R2 of ABCB1 (G2677T/A) polymorphism at three months after transplant was 0.05. Significant clinical factors varied at different time points, and only had a total R2 of 0.10-0.15. Before discharge after transplantation, age, mycophenolate mofetil (MMF) or mycophenolate sodium (MPS) daily dose and direct bilirubin were significantly associated with TAC ln dnC0 or ln dnC0/DW. Significant clinical factor at 3 months after transplant included age, sex, daily dose of steroids and total bilirubin (T-bil); While at 6 months after transplant included MMF or MPS use, daily dose of steroids, direct bilirubin (D-bil) and hematocrit. In subgroup analyses, CYP3A5 nonexpressers were found to be more sensitive to other SNPs, including ABCB1 (C3435T) and ABCB1 (G2677T/A). Their R2 in univariate regression analysis at 3 time points increased from 0.02-0.07 to 0.15-0.20. We also found that 82.2 % of CYP3A5 expressers had at least one CYP3A4*1G mutation. In contrast, 92.2 % of CYP3A5 nonexpressers did not have CYP3A4*1G mutation. CYP3A4*1G polymorphism was strongly linked with the CYP3A5*3 polymorphism. Last but not least, the present study found that patients receiving MMF or MPS had higher TAC dnC0 compared to non-users (dual therapy) at all three time points, although the differences were not statistically significant. This study also provided comprehensive gene distribution data of SNPs related to TAC metabolism pathway in Taiwanese. The proportions CYP3A5 expressers and nonexpressers are 47 % and 53 % respectively. CYP3A5*3 polymorphism is the most important factor that influenced TAC ln dnC0 or ln dnC0/DW in renal transplant patients within 6 months after transplant. Thus, testing CYP3A5*3 polymorphism could serve as a reference for dosage adjustments in patients with difficulty in achieving TAC target concentration. The significant clinical factors varied at different time points and played a minimum role. TAC C0 should be closely monitored when there is a significant change in the factors mentioned above. This study showed that CYP3A5 nonexpressers were more sensitive to other SNPs, including ABCB1 (C3435T) and ABCB1 (G2677T/A). In addition, CYP3A4*1G polymorphism was strongly linked with the CYP3A5*3 polymorphism. The relationship between different SNPs should be considered when we apply patients’ genetic data on TAC dosage adjustments. Finally, future studies are needed to elucidate the influence of MMF/MPS on TAC PK. | en |
dc.description.provenance | Made available in DSpace on 2021-07-09T15:51:55Z (GMT). No. of bitstreams: 1 ntu-107-R05451008-1.pdf: 3529413 bytes, checksum: a3c2c7bfc4bd3897aec34d80223f5246 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 論文口試委員審定書 i
致謝 ii 縮寫表 iii 中文摘要 v Abstract viii 目錄 xi 圖目錄 xvi 表目錄 xvii 第一章、前言 1 第二章、文獻探討 3 2.1 腎臟移植的免疫抑制劑使用情形 3 2.2 Tacrolimus簡介 3 2.2.1 Tacrolimus的作用機制 4 2.2.2 Tacrolimus的毒性 5 2.3 Tacrolimus的藥動學特性 7 2.3.1 吸收 7 2.3.2 分布 7 2.3.3 代謝及排除 8 2.4 臨床因素對tacrolimus藥動學的影響 9 2.4.1 年齡 9 2.4.2 性別 10 2.4.3 移植後天數(post-operative day,POD) 10 2.4.4 肝功能 11 2.4.5 HBV(hepatitis B virus)與HCV(hepatitis C virus) 11 2.4.6 腎功能 12 2.4.7 白蛋白(Alb)與總蛋白(TP) 12 2.4.8 血紅素(hemoglobin,Hb)與血比容(Hct) 12 2.4.9 TAC製劑Prograf ®與Advagraf ® 13 2.4.10 糖尿病(diabetes mellitus,DM) 13 2.4.11 感染 13 2.5 藥品對tacrolimus藥動學的影響 14 2.6 基因多型性(gene polymorphism)對tacrolimus藥動學的影響 14 2.6.1 CYP3A5 15 2.6.2 CYP3A4 16 2.6.3 POR*28 17 2.6.4 ABCB1 17 2.7 與tacrolimus藥動學相關SNP之基因分布 18 2.7.1 CYP3A5 19 2.7.2 CYP3A4 20 2.7.3 POR*28 21 2.7.4 ABCB1 21 第三章、研究目的及方法 23 3.1 研究目的 23 3.2 研究方法 23 3.2.1 研究架構 23 3.2.2 病人 23 3.2.3 臨床資訊收集之流程 24 3.2.4 TAC穩定狀態之C0 25 3.2.5 給藥體重(dosing weight,DW)定義 25 3.2.6 TAC劑量校正C0(dose normalized C0,dnC0)定義 25 3.2.7 TAC納入分析之時間點(data collection) 25 3.2.8其它檢驗數據(laboratory data)之採檢日期 26 3.2.9併用藥品(concurrent medication)定義 26 3.2.10 TAC血中濃度檢驗方法 27 3.2.11 Genotyping方法 27 3.2.12其它定義 27 3.2.13統計分析 28 第四章、研究結果 31 4.1 病人篩選流程 31 4.2 病人人口學資料 31 4.3 TAC劑量與血中濃度變化 31 4.4 免疫抑制劑與併用藥品 32 4.5 病人基因型分布 33 4.6 生化檢驗值的變化 33 4.7 臨床因素與基因多型性單變項分析 34 4.7.1 移植手術出院前 34 4.7.2 移植後3個月 35 4.7.3 移植後6個月 35 4.7.4 CYP3A5表現者與不表現者基因多型性單變項分析 36 4.8 多變項分析 37 4.8.1 移植手術出院前 37 4.8.2 移植後3個月 37 4.8.3 移植後6個月 38 4.9 CYP3A5表現者與不表現者比較 39 4.9.1 移植手術出院前 39 4.9.2 移植後3個月 39 4.9.3 移植後6個月 40 4.10 免疫抑制劑組合分析 40 4.10.1 MPS vs. EVL 40 4.10.2 MMF vs. EVL 41 4.10.3 MMF/MPS vs. EVL 42 4.10.4 MPS vs. MMF 43 4.10.5 MMF/MPS user vs. non-user 44 第五章、討論 45 5.1 性別 45 5.2 年齡 46 5.3 類固醇每日劑量 47 5.4 MMF/MPS 48 5.5 T-bil/D-bil 49 5.6 Hb/Hct 50 5.7 基因多型性 50 5.7.1 CYP3A5*3 50 5.7.2 ABCB1 51 5.8 研究優勢與限制 52 第六章、結論 54 參考文獻 56 圖表 83 | |
dc.language.iso | zh-TW | |
dc.title | 基因多型性及臨床因素對腎臟移植病人tacrolimus血中濃度之影響 | zh_TW |
dc.title | The influence of genetic and clinical factors on tacrolimus blood concentration in renal transplant patients | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 蔡孟昆(Meng-Kun Tsai),胡瑞恒(Rey-Heng Hu) | |
dc.contributor.oralexamcommittee | 沈麗娟(Li-Jiuan Shen) | |
dc.subject.keyword | tacrolimus,腎臟移植,藥品動態學,藥品交互作用,臨床因素,基因多型性, | zh_TW |
dc.subject.keyword | tacrolimus,kidney transplantation,pharmacokinetics,drug interactions,clinical factors,genetic polymorphism, | en |
dc.relation.page | 172 | |
dc.identifier.doi | 10.6342/NTU201802661 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2018-08-08 | |
dc.contributor.author-college | 醫學院 | zh_TW |
dc.contributor.author-dept | 臨床藥學研究所 | zh_TW |
dc.date.embargo-lift | 2023-10-11 | - |
顯示於系所單位: | 臨床藥學研究所 |
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