High-Accuracy Identification of Incident HIV-1 Infections Using a Sequence Clustering Based Diversity Measure

<div><p>Accurate estimates of HIV-1 incidence are essential for monitoring epidemic trends and evaluating intervention efforts. However, the long asymptomatic stage of HIV-1 infection makes it difficult to effectively distinguish incident infections from chronic ones. Current incidence assays based on serology or viral sequence diversity are both still lacking in accuracy. In the present work, a sequence clustering based diversity (SCBD) assay was devised by utilizing the fact that viral sequences derived from each transmitted/founder (T/F) strain tend to cluster together at early stage, and that only the intra-cluster diversity is correlated with the time since HIV-1 infection. The dot-matrix pairwise alignment was used to eliminate the disproportional impact of insertion/deletions (indels) and recombination events, and so was the proportion of clusterable sequences (<i>P_c</i>) as an index to identify late chronic infections with declined viral genetic diversity. Tested on a dataset containing 398 incident and 163 chronic infection cases collected from the Los Alamos HIV database (last modified 2/8/2012), our SCBD method achieved 99.5% sensitivity and 98.8% specificity, with an overall accuracy of 99.3%. Further analysis and evaluation also suggested its performance was not affected by host factors such as the viral subtypes and transmission routes. The SCBD method demonstrated the potential of sequencing based techniques to become useful for identifying incident infections. Its use may be most advantageous for settings with low to moderate incidence relative to available resources. The online service is available at <a href="http://www.bioinfo.tsinghua.edu.cn:8080/SCBD/index.jsp" target="_blank">http://www.bioinfo.tsinghua.edu.cn:8080/SCBD/index.jsp</a>.</p></div

Flowchart for identifying incident from chronic HIV-1 infections using the sequence clustering-based diversity (SCBD) assay.

<p>Flowchart for identifying incident from chronic HIV-1 infections using the sequence clustering-based diversity (SCBD) assay.</p

The SCBD dynamics and distribution of D561.

<p>(A) The SCBD dynamics in D561. Black diamonds denote subtype B samples, red dots denote subtype C samples, and blue triangles denote samples with other or unknown subtypes. (B) The distribution of the SCBD values in D561. The black histogram denotes the 398 incident infections (including 295 single- and 103 multiple-strain infections), and the red represents the other 163 chronic samples. (C) The distribution of the HD Q₁₀ values in D561. (D) The red histogram represents the 4 misclassified samples by our SCBD method, including 2 false positive incident infections and 2 false negatives; the black histogram denotes the 45 misclassified samples by the HD Q₁₀ method, including 5 false positives and 40 false negatives.</p

Partial alignment of two sequences from sample ID 1811 (A), along with the sample’s pairwise HD distribution (B).

<p>(A) Partial alignment of two sequences from sample ID 1811. Red and blue letters highlight differences in nucleotides. (B) The pairwise HD distribution of sequences from sample ID 1811, which was misclassified as a chronic case by the HD Q₁₀ assay (HD Q₁₀ = 1). The sample comprised of 11 sequences and was obtained at Fiebig stage VI.</p

Influence of viral subtype and transmission route over the SCBD assay’s performance on the dataset D561.

<p>Influence of viral subtype and transmission route over the SCBD assay’s performance on the dataset D561.</p

Performance of the SCBD, HD Q₁₀, and Pattern-based assays.

<p>Performance of the SCBD, HD Q₁₀, and Pattern-based assays.</p

Homologous clusters identification for cases in datasets D225 and D561.

<p>*Homologous clusters identified by the SCBD assay.</p><p>‘S’: single; ‘M’: multiple; ‘D’: declined; ‘-’: null.</p><p>**Incident infections were identified either as ‘single’ or ‘multiple’ infected according to resource information.</p

Estimated geographic distribution of the four major HIV-1 genotypes in China.

<p>Prevalence of the four major HIV-1 genotypes, including CRF07_BC (A), CRF08_AE (B), CRF01_AE (C) and subtype B' (D), is estimated for each province by the methods described in Methods. Corrected prevalence is color-coded as indicated in the inset.</p

HIV case report in 2006 and sample collection.

*<p>see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0047289#pone.0047289.s001" target="_blank">Table S1</a>. (d) indicates the summation of the reported cases in the risk groups where the samples for genotyping were available. No. of reported cases in the risk groups from which the samples were not available were excluded from the analysis in this study.</p

Distribution of HIV-1 genotypes in different risk groups in China^*.

*<p>Numbers in parentheses and square brackets indicate the proportion of the HIV-infected in each subgroup as a percentage of the national total for that risk group and genotype, respectively. The estimation was done, assuming that HIV case reports reflect the actual prevalence of HIV infection in the respective risk groups and provinces (see Methods).</p