Center for Global Health and Disease, Case Western Reserve University School of Medicine, Wolstein Research Building, 4-125, Cleveland, Ohio 44106-7286, USA.
BMC Genet. 2010 Jun 29;11:57. doi: 10.1186/1471-2156-11-57.
Diagnosis of infectious diseases now benefits from advancing technology to perform multiplex analysis of a growing number of variables. These advances enable simultaneous surveillance of markers characterizing species and strain complexity, mutations associated with drug susceptibility, and antigen-based polymorphisms in relation to evaluation of vaccine effectiveness. We have recently developed assays detecting single nucleotide polymorphisms (SNPs) in the P. falciparum genome that take advantage of post-PCR ligation detection reaction and fluorescent microsphere labeling strategies. Data from these assays produce a spectrum of outcomes showing that infections result from single to multiple strains. Traditional methods for distinguishing true positive signal from background can cause false positive diagnoses leading to incorrect interpretation of outcomes associated with disease treatment.
Following analysis of Plasmodium falciparum dihydrofolate reductase SNPs associated with resistance to a commonly used antimalarial drug, Fansidar (Sulfadoxine/pyrimethamine), and presumably neutral SNPs for parasite strain differentiation, we first evaluated our data after setting a background signal based on the mean plus three standard deviations for known negative control samples. Our analysis of single allelic controls suggested that background for the absent allele increased as the concentration of the target allele increased. To address this problem, we introduced a simple change of variables from customary (X,Y) (Cartesian) coordinates to planar polar coordinates (X = rcos(theta), Y = rsin(theta)). Classification of multidimensional fluorescence signals based on histograms of angular and radial data distributions proved more effective than classification based on Cartesian thresholds. Comparison with known diallelic dilution controls suggests that histogram-based classification is effective for major:minor allele concentration ratios as high as 10:1.
We have observed that the diallelic SNP data resulting from analysis of P. falciparum mutations is more accurately diagnosed when a simple polar transform of the (X,Y) data into (r,theta) is used. The development of high through-put methods for genotyping P. falciparum SNPs and the refinement of analytical approaches for evaluating these molecular diagnostic results significantly advance the evaluation of parasite population diversity and antimalarial drug resistance.
现在,传染病的诊断得益于技术的进步,可以对越来越多的变量进行多重分析。这些进展使我们能够同时监测反映物种和菌株复杂性的标志物、与药物敏感性相关的突变以及与评估疫苗效果相关的基于抗原的多态性。我们最近开发了检测恶性疟原虫基因组中单核苷酸多态性(SNP)的检测方法,该方法利用了 PCR 后连接检测反应和荧光微球标记策略。这些检测方法的数据产生了一系列结果,表明感染是由单一菌株到多种菌株引起的。从背景中区分真正阳性信号的传统方法可能导致假阳性诊断,从而导致对与疾病治疗相关的结果的错误解释。
在分析与抗疟药物 Fansidar(磺胺多辛/乙胺嘧啶)耐药相关的恶性疟原虫二氢叶酸还原酶 SNP 以及寄生虫株分化的假定中性 SNP 之后,我们首先根据已知阴性对照样本的平均值加三个标准差来设置背景信号,然后对数据进行分析。我们对单一等位基因对照的分析表明,随着目标等位基因浓度的增加,缺失等位基因的背景增加。为了解决这个问题,我们将变量从惯用的(X,Y)(笛卡尔)坐标转换为平面极坐标(X = rcos(theta),Y = rsin(theta))。基于角度和径向数据分布的直方图对多维荧光信号的分类比基于笛卡尔阈值的分类更有效。与已知的二态稀释对照的比较表明,基于直方图的分类对于高达 10:1 的主要:次要等位基因浓度比是有效的。
我们观察到,当将(X,Y)数据简单地转换为(r,theta)时,分析恶性疟原虫突变产生的二态 SNP 数据可以更准确地诊断。高通量方法的开发用于恶性疟原虫 SNP 的基因分型以及评估这些分子诊断结果的分析方法的改进极大地促进了对寄生虫种群多样性和抗疟药物耐药性的评估。