Suppr超能文献

通过肽核酸(PNA)介导的PCR钳夹技术进行简单可靠的凝血因子V基因分型

Simple and reliable factor V genotyping by PNA-mediated PCR clamping.

作者信息

Behn M, Schuermann M

机构信息

Zentrum für Innere Medizin, Abteilung Hämatologie/Onkologie, Phillips-Universität Marburg, Germany.

出版信息

Thromb Haemost. 1998 Apr;79(4):773-7.

PMID:9569191
Abstract

Resistance to activated protein C (APC resistance) is the most common cause of thrombophilia and linked to a single point mutation in the factor V gene (G-->A transition at nucleotide 1691). In the past, several PCR based methods have been proposed to determine the allelostatus of individual patients from small amounts of blood DNA including PCR followed by restriction fragment length polymorphism detection (PCR-RFLP), PCR using sequence-specific primers (PCR-SSP) and oligonucleotide ligation assay (OLA). Here, we present a novel approach based on the method of peptide nucleic acid(PNA)-mediated PCR clamping which is extremely sensitive to base pair mismatches. If PNAs specific for the two allelic variants are applied separately in each case a clear discrimination between a heterozygous or homozygous normal or homozygous Factor V Leiden status is possible and no further confirmation step is required. In a prospective study, 60 patients with suspected venous thrombosis events were tested and compared to the conventional PCR-RFLP technique. The concordance between both methods was 100%. PNA-based factor V genotyping, therefore, should be considered for large scale screening of those patients considered to be at risk for deep venous thrombosis.

摘要

对活化蛋白C的抵抗(APC抵抗)是血栓形成倾向最常见的原因,并且与因子V基因中的单点突变(核苷酸1691处的G→A转换)有关。过去,已经提出了几种基于PCR的方法来从少量血液DNA中确定个体患者的等位基因状态,包括PCR后进行限制性片段长度多态性检测(PCR-RFLP)、使用序列特异性引物的PCR(PCR-SSP)和寡核苷酸连接测定(OLA)。在此,我们提出了一种基于肽核酸(PNA)介导的PCR钳制方法的新方法,该方法对碱基对错配极其敏感。如果在每种情况下分别应用针对两种等位基因变体的PNA,则可以明确区分杂合子或纯合子正常或纯合子因子V莱顿状态,并且无需进一步的确认步骤。在一项前瞻性研究中,对60例疑似静脉血栓形成事件的患者进行了检测,并与传统的PCR-RFLP技术进行了比较。两种方法之间的一致性为100%。因此,对于那些被认为有深静脉血栓形成风险的患者,基于PNA的因子V基因分型应被考虑用于大规模筛查。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验