Wiita Arun P, Schrijver Iris
Department of Laboratory Medicine, University of California, San Francisco, CA, USA;
Pharmgenomics Pers Med. 2011;4:109-21. doi: 10.2147/PGPM.S15302. Epub 2011 Sep 8.
Genetic analysis is one of the fastest-growing areas of clinical diagnostics. Fortunately, as our knowledge of clinically relevant genetic variants rapidly expands, so does our ability to detect these variants in patient samples. Increasing demand for genetic information may necessitate the use of high throughput diagnostic methods as part of clinically validated testing. Here we provide a general overview of our current and near-future abilities to perform large-scale genetic testing in the clinical laboratory. First we review in detail molecular methods used for high throughput mutation detection, including techniques able to monitor thousands of genetic variants for a single patient or to genotype a single genetic variant for thousands of patients simultaneously. These methods are analyzed in the context of pharmacogenomic testing in the clinical laboratories, with a focus on tests that are currently validated as well as those that hold strong promise for widespread clinical application in the near future. We further discuss the unique economic and clinical challenges posed by pharmacogenomic markers. Our ability to detect genetic variants frequently outstrips our ability to accurately interpret them in a clinical context, carrying implications both for test development and introduction into patient management algorithms. These complexities must be taken into account prior to the introduction of any pharmacogenomic biomarker into routine clinical testing.
基因分析是临床诊断领域中发展最快的领域之一。幸运的是,随着我们对临床相关基因变异的了解迅速扩展,我们在患者样本中检测这些变异的能力也在增强。对基因信息的需求不断增加,可能需要使用高通量诊断方法作为临床验证检测的一部分。在此,我们概述了目前以及不久的将来在临床实验室进行大规模基因检测的能力。首先,我们详细回顾用于高通量突变检测的分子方法,包括能够为单个患者监测数千个基因变异或同时为数千名患者对单个基因变异进行基因分型的技术。在临床实验室的药物基因组学检测背景下对这些方法进行分析,重点关注目前已验证的检测以及那些在不久的将来有望广泛应用于临床的检测。我们进一步讨论药物基因组学标志物带来的独特经济和临床挑战。我们检测基因变异的能力常常超过我们在临床背景下准确解读它们的能力,这对检测开发以及引入患者管理算法都有影响。在将任何药物基因组学生物标志物引入常规临床检测之前,必须考虑这些复杂性。