社團法人臺灣臨床藥學會

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【綜合評述】亞洲人藥物代謝酵素基因多型性與抗結核藥物引起之肝毒性
Drug Metabolizing Enzyme Polymorphisms and Antituberculosis Drug-Induced Hepatotoxicity in Asian Population
肺結核、代謝酵素基因多形性、肝毒性、Tuberculosis, Metabolizing Enzyme Polymorphisms, Hepatotoxicity
蕭惠娟Hui-Chuan Hsiao 、陳崇鈺Chung-Yu Chen 、沈玫秋Mei-Chiou Shen*
1高雄醫學大學附設中和紀念醫院藥劑部
結核病是全球一個很重要的健康問題,其標準治療為isoniazid、rifampicin 及pyrazinamide 等多種藥物的合併使用。這些藥物常見之嚴重副作用為肝毒性,而針對抗結核藥物引起之肝毒性與藥物代謝酵素基因多型性在亞洲人種之相關研究,目前有第二型氮-乙醯氨基轉移酵素(hepatic type 2 N-acetyl transferase enzymes, NAT2) 、細胞色素P450 2E1 (cytochrome P450 2E1, CYP2E1) 及麩胺基硫轉移酵素(glutathione S-transferase, GST) 等基因型。本文以關鍵字drug-metabolising enzymes、antitubercular agents、druginduced hepatotoxicity、drug-induced liver injury、genetic polymorphism、arylamine N-acetyltransferase、glutathione-S-transferase、cytochrome P450 2E1 搜尋2009 年至2014 年刊登在PubMed 資料庫文獻,人種限定亞洲人,其中基因型表現為NAT2 慢乙醯化、CYP2E1 c1/c1 及GSTM1 之亞洲人會增加抗結核藥物引起肝毒性之風險。因此,為達最佳之治療成果,依據病人之基因特性給予個人化之抗結核藥物治療劑量將是未來的趨勢。
 
Tuberculosis is an important global public health problem. The standard therapeutic regimen includes a combination of isoniazid, rifampicin, pyrazinamide, and so on. One of the most frequent and serious side effects of these drugs is hepatotoxicity. Several studies in Asian populations have identified genetic risk factors for the development of antituberculosis drug-induced hepatotoxicity, such as drug metabolizing enzyme polymorphisms in hepatic type 2 N-acetyl transferase enzymes (NAT2), Cytochrome P450 2E1 (CYP2E1) and glutathione S-transferase (GST) genes. In this paper, we searched 2009 ~ 2014 data published in PubMed with keywords of drug-metabolising enzymes, antitubercular agents, drug-induced hepatotoxicity, drug-induced liver injury, genetic polymorphism, arylamine N-acetyltransferase , glutathione-S-transferase, cytochrome P450 2E1 and ethnic Asians limited. Antituberculosis drug-induced hepatotoxicity are higher with NAT2 slow acetylators , CYP2E1 c1/c1 and GSTM1 genotype in Asians. In addition, the individualized therapeutic doses of anti-tuberculosis drugs are needed in the future based on genetic information to achieve the greatest success outcome for each patient.
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