A microarray-based system for the simultaneous analysis of single nucleotide polymorphisms in human genes involved in the metabolism of anti-malarial drugs.

A microarray-based system for the simultaneous analysis of single nucleotide polymorphisms in human genes involved in the metabolism of anti-malarial drugs.
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DOI:
10.1186/1475-2875-8-285
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发表时间:
2009-12-09
期刊:
影响因子:
3
通讯作者:
Beck HP
Beck HP
中科院分区:
医学3区
文献类型:
--
作者:
Hodel EM;Ley SD;Qi W;Ariey F;Genton B;Beck HP

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为了提供一个具有成本效益的工具来分析疟疾治疗中的药物遗传学标记,DNA微阵列技术与聚合酶链反应(PCR)片段测序进行了比较,以检测单核苷酸多态性(SNP)在大量的样本。开发该微阵列是为了以经济实惠的方式生成编码人类细胞色素P450酶家族(CYP)和N-乙酰转移酶-2(NAT 2)的基因的SNP数据,这些基因参与抗疟疾药物代谢并具有已知多态性,即CYP 2A 6、CYP 2B 6、CYP 2C 8、CYP 2C 9、CYP 2C 19、CYP 2D 6、CYP 3A 4、CYP 3A 5和NAT 2。对于某些SNP,即CYP 2A 6 *2、CYP 2B 6 *5、CYP 2C 8 *3、CYP 2C 9 *3/*5、CYP 2C 19 *3、CYP 2D 6 *4和NAT 2 *6/*7/*14,两种技术之间的一致性范围从实质性到几乎完美(卡帕指数在0.61和1.00之间),而对于其他SNP,从轻微一致到基本一致的较大变异性(kappa指数在0.39和1.00之间),例如CYP 2D 6 *17(2850 C>T)、CYP 3A 4 *1B和CYP 3A 5 *3。用于此目的的微阵列技术的主要限制是缺乏鲁棒性并且具有大量缺失数据或具有不正确的特异性。
In order to provide a cost-effective tool to analyse pharmacogenetic markers in malaria treatment, DNA microarray technology was compared with sequencing of polymerase chain reaction (PCR) fragments to detect single nucleotide polymorphisms (SNPs) in a larger number of samples. The microarray was developed to affordably generate SNP data of genes encoding the human cytochrome P450 enzyme family (CYP) and N-acetyltransferase-2 (NAT2) involved in anti-malarial drug metabolisms and with known polymorphisms, i.e. CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, and NAT2. For some SNPs, i.e. CYP2A6*2, CYP2B6*5, CYP2C8*3, CYP2C9*3/*5, CYP2C19*3, CYP2D6*4 and NAT2*6/*7/*14, agreement between both techniques ranged from substantial to almost perfect (kappa index between 0.61 and 1.00), whilst for other SNPs a large variability from slight to substantial agreement (kappa index between 0.39 and 1.00) was found, e.g. CYP2D6*17 (2850C>T), CYP3A4*1B and CYP3A5*3. The major limit of the microarray technology for this purpose was lack of robustness and with a large number of missing data or with incorrect specificity.
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