Meixenberger Karolin, Hauser Andrea, Jansen Klaus, Yousef Kaveh Pouran, Fiedler Stefan, von Kleist Max, Norley Stephen, Somogyi Sybille, Hamouda Osamah, Bannert Norbert, Bartmeyer Barbara, Kücherer Claudia
HIV and Other Retroviruses, Robert Koch Institute, Berlin, Germany
HIV and Other Retroviruses, Robert Koch Institute, Berlin, Germany.
J Clin Microbiol. 2014 Aug;52(8):2977-83. doi: 10.1128/JCM.03289-13. Epub 2014 Jun 11.
An increase in the proportion of ambiguous base calls in HIV-1 pol population sequences during the course of infection has been demonstrated in different study populations, and sequence ambiguity thresholds to classify infections as recent or nonrecent have been suggested. The aim of our study was to evaluate sequence ambiguities as a candidate biomarker for use in an HIV-1 incidence assay using samples from antiretroviral treatment-naive seroconverters with known durations of infection (German HIV-1 Seroconverter Study). We used 2,203 HIV-1 pol population sequences derived from 1,334 seroconverters to assess the sequence ambiguity method (SAM). We then compared the serological incidence BED capture enzyme immunoassay (BED-CEIA) with the SAM for a subset of 723 samples from 495 seroconverters and evaluated a multianalyte algorithm that includes BED-CEIA results, SAM results, viral loads, and CD4 cell counts for 453 samples from 325 seroconverters. We observed a significant increase in the proportion of sequence ambiguities with the duration of infection. A sequence ambiguity threshold of 0.5% best identified recent infections with 76.7% accuracy. The mean duration of recency was determined to be 208 (95% confidence interval, 196 to 221) days. In the subset analysis, BED-CEIA achieved a significantly higher accuracy than the SAM (84.6 versus 75.5%, P < 0.001) and results were concordant for 64.2% (464/723) of the samples. Also, the multianalyte algorithm did not show better accuracy than the BED-CEIA (83.4 versus 84.3%, P = 0.786). In conclusion, the SAM and the multianalyte algorithm including SAM were inferior to the BED-CEIA, and the proportion of sequence ambiguities is therefore not a preferable biomarker for HIV-1 incidence testing.
在不同的研究人群中,均已证实在HIV-1感染过程中,pol基因群体序列中碱基错配比例会增加,并且已经提出了将感染分类为近期感染或非近期感染的序列错配阈值。我们研究的目的是使用来自已知感染持续时间的未接受过抗逆转录病毒治疗的血清转化者的样本,评估序列错配作为HIV-1发病率检测中候选生物标志物的情况(德国HIV-1血清转化者研究)。我们使用了来自1334名血清转化者的2203条HIV-1 pol基因群体序列来评估序列错配方法(SAM)。然后,我们将血清学发病率BED捕获酶免疫测定法(BED-CEIA)与495名血清转化者的723个样本子集的SAM进行了比较,并评估了一种多分析物算法,该算法包括325名血清转化者的453个样本的BED-CEIA结果、SAM结果、病毒载量和CD4细胞计数。我们观察到序列错配比例随感染持续时间显著增加。序列错配阈值为0.5%时,对近期感染的识别准确率最高,为76.7%。确定近期感染的平均持续时间为208天(95%置信区间,196至221天)。在子集分析中,BED-CEIA的准确率显著高于SAM(84.6%对75.5%,P<0.001),64.(464/723)的样本结果一致。此外,多分析物算法的准确率并不比BED-CEIA高(83.4%对84.3%,P = 0.786)。总之,SAM和包括SAM的多分析物算法均不如BED-CEIA,因此序列错配比例不是HIV-1发病率检测的理想生物标志物。