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Sequence Ambiguity Determined from Routine Pol Sequencing Is a Reliable Tool for Real-Time Surveillance of HIV Incidence Trends

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Sequence Ambiguity Determined from Routine Pol Sequencing Is a Reliable Tool for Real-Time Surveillance of HIV Incidence Trends Infection, Genetics and Evolution 69 (2019) 146–152 Contents lists available at ScienceDirect Infection, Genetics and Evolution journal homepage: www.elsevier.com/locate/meegid Research paper Sequence ambiguity determined from routine pol sequencing is a reliable T tool for real-time surveillance of HIV incidence trends ⁎ Maja M. Lunara, Snježana Židovec Lepejb, Mario Poljaka, a Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Zaloška 4, Ljubljana 1105, Slovenia b Dr. Fran Mihaljevič University Hospital for Infectious Diseases, Mirogojska 8, Zagreb 10000, Croatia ARTICLE INFO ABSTRACT Keywords: Identifying individuals recently infected with HIV has been of great significance for close monitoring of HIV HIV-1 epidemic dynamics. Low HIV sequence ambiguity (SA) has been described as a promising marker of recent Incidence infection in previous studies. This study explores the utility of SA defined as a proportion of ambiguous nu- Sequence ambiguity cleotides detected in baseline pol sequences as a tool for routine real-time surveillance of HIV incidence trends at Mixed base calls a national level. Surveillance A total of 353 partial HIV-1 pol sequences obtained from persons diagnosed with HIV infection in Slovenia from 2000 to 2012 were studied, and SA was reported as a percentage of ambiguous base calls. Patients were characterized as recently infected by examining anti-HIV serological patterns and/or using commercial HIV-1 incidence assays (BED and/or LAg-Avidity assay). A mean SA of 0.29%, 0.14%, and 0.19% was observed for infections classified as recent by BED, LAg, or anti-HIV serological results, respectively. Welch's t-test showed a significant difference in the SA of recent versus long-standing infections (p < 0.001). CD4+ T-cell counts≤250 cells/mm3 significantly correlated with higher SA (p < 0.001), whereas the homo/bisexual transmission route significantly correlated with lower SA (p = 0.005). When the LAg-assay was used as an indicator ofrecent infection, a receiver operating characteristic curve with the largest area under the curve (0.896) was observed for SA (sensitivity and specificity of 79%), indicating the best correlation of the data. A reliable estimation ofthe trends of HIV incident infection could be inferred from measuring SA irrespective of the cutoff used; however, in Slovenia it seems that lower cutoffs are more appropriate. Our data suggest that SA could be used as a real-time surveillance tool for close monitoring of HIV incidence trends, especially in countries where baseline HIV resistance genotyping is performed routinely, rendering this approach cost-effective. 1. Introduction Seroconversion (STARHS) (Murphy and Parry, 2008). Two of the more widely used assays are the BED test, which quantifies normalized op- Surveillance of the HIV epidemic and monitoring its dynamics re- tical density (ODn) resulting from the proportion of HIV-specific IgG quires reliable differentiation of individuals infected with HIV recently antibodies (Calypte Biomedical Corporation, 2008; Parekh et al., 2002), (RI) from individuals with a long-standing infection (LSI). This can best and the LAG assay, which measures the avidity of HIV antibodies and be achieved in prospective cohort studies, in which HIV-negative per- expresses it as ODn (Duong et al., 2012; Kassanjee et al., 2016; Sedia sons are monitored longitudinally for HIV seroconversion, or less ide- Biosciences Corporation, 2016). However, the STARHS assays are ally retrospectively in a cross-sectional design by using assays able to known to have several limitations: the HIV-1 subtype and even clade reliably discriminate RI from LSI in a single specimen as combined can affect the window period, and low CD4+ T-cell count oranti- under the generic term Serological Testing Algorithm for Recent HIV retroviral therapy has been shown to yield false-recent Abbreviations: AUC, area under the curve; BED, Aware BED EIA HIV-1 incidence test (Calypte Biomedical Corporation, Portland, Oregon); DR, drug-resistant; HIV, human immunodeficiency virus; IDU, injecting drug use; LAG, LAg-Avidity assay (Sedia Biosciences Corporation, Portland, Oregon); LSI, long-standing infection; MDRI, mean duration of recent infection; MSM, men who have sex with men; NGS, next-generation sequencing; ODn, normalized optical density; pol, polymerase gene; RI, recent infection; ROC, receiver operating characteristic; SA, sequence ambiguity; SER, serological pattern supporting HIV seroconversion; SD, standard deviation; SE, standard error; STARHS, Serological Testing Algorithm for Recent HIV Seroconversion; TDR, transmitted drug resistance ⁎ Corresponding author at: Institute of Microbiology and Immunology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia. E-mail address: [email protected] (M. Poljak). https://doi.org/10.1016/j.meegid.2019.01.015 Received 31 October 2018; Received in revised form 9 January 2019; Accepted 13 January 2019 Available online 22 January 2019 1567-1348/ © 2019 Published by Elsevier B.V. M.M. Lunar et al. Infection, Genetics and Evolution 69 (2019) 146–152 Table 1 Baseline characteristics of patients included in the evaluation of SA as a method of differentiating RI from LSI when BED, LAG, or SER were used as the gold standard. Characteristic BED n (%) LAG n (%) SER n (%) Sex Male 233 (89.6) 102 (89.5) 314 (89.2) Female 27 (10.4) 12 (10.5) 38 (10.8) HIV transmission MSM 192 (73.8) 78 (68.4) 256 (72.7) Heterosexual/IDU 53 (20.4) 30 (26.3) 76 (21.6) Unknown 15 (5.8) 6 (5.3) 20 (5.7) HIV subtype Subtype B 227 (87.3) 92 (80.7) 301 (85.5) Other 33 (12.7) 22 (19.3) 51 (14.5) HIV viral load (log copies/ml ± SD) 4.97 ± 0.94 4.93 ± 1.07 4.97 ± 0.96 CD4 cell count (mm3 ± SD) 309 ± 221 312 ± 247 313 ± 228 SA, sequence ambiguity method; RI, recent HIV infection; LSI, long-standing HIV infection; BED, the BED test; LAG, the LAg-Avidity assay; SER, anti-HIV serological patterns; MSM, men having sex with men; IDU, injecting drug use; SD, standard deviation. misclassifications (Murphy and Parry, 2008). Several accuracy im- drug resistance testing of newly diagnosed HIV individuals is not per- provements have been proposed in the last decade, the most significant formed routinely, with few exceptions: for pregnant women and in- being the inclusion of low viral load criteria for the characterization of dividuals suspected of acquiring HIV infection abroad. Even so, partial LSI (Kassanjee et al., 2016). pol sequences have been collected in over half of newly diagnosed In addition to the STARHS assays, HIV diversity has been proposed persons since 2000 as part of the SPREAD study of TDR in Europe as a promising indicator of RI; it is determined either by sequencing (Babič et al., 2006b; Lunar et al., 2013; Lunar et al., 2018). (Sanger or next-generation) or by assays such as high-resolution This study explores the utility of HIV diversity observed in baseline melting assay and heteroduplex mobility assay (Cousins et al., 2011; pol sequences for estimating the duration of patients' HIV infection and Delwart et al., 1997). When analyzing sequences obtained by Sanger thereby HIV incidence at a national level. We also tested whether the population sequencing, the chromatograms can exhibit two or more SA method could be used as a real-time surveillance tool for close different peaks on one nucleotide position. This can be due to sequen- monitoring of HIV incidence trends. cing error or is caused by the presence of more than one HIV variant. If these mixed (ambiguous) nucleotide codons are confirmed in the 2. Material and methods chromatograms generated in the forward and reverse manner, these are typically true indicators of sequence ambiguity (SA) and thus genetic 2.1. Study samples diversity of the virus in question. SA is typically expressed as a pro- portion of ambiguous base calls in the sequence assessed and as such Slovenia is a country with a centralized system of HIV diagnostics, has been examined as a marker of RI (Kouyos et al., 2011). This ap- monitoring, and clinical care. Confirmation of HIV infection and proach is based on the fact that HIV is normally transmitted by a single monitoring of all HIV patients in the country are performed exclusively viral variant (founder virus) because of the genetic bottleneck (Carlson at the Slovenian HIV Reference Center at the Institute of Microbiology et al., 2014; Keele et al., 2008). Soon after infection, due to the high and Immunology, Faculty of Medicine, University of Ljubljana. Clinical mutation rate of the HIV-1 reverse transcriptase (3.4 × 10−5 mutations care for all HIV-positive persons is provided at the Department of per base pair per generation), the HIV population gradually diversifies Infectious Diseases, Ljubljana University Medical Center. Therefore, the in the form of genetic variants, known as quasispecies (Domingo and clinical and laboratory data collected for this study by the two in- Holland, 1997; Mansky and Temin, 1995). It has been shown that SA stitutions mentioned above are representative of the entire national HIV increases linearly by approximately 0.2% each year in the first 8 years cohort. A total of 353 partial HIV-1 pol sequences were included in this of HIV infection, followed by a plateau, and then decreases in the study. Sequences were obtained from the same number of treatment- terminal phase of the disease, thus representing a promising marker for naive persons newly diagnosed with HIV from 2000 to 2016 in estimating the duration of HIV infection (Kouyos et al., 2011). Slovenia, representing 56% (353/628) of all individuals diagnosed HIV diversity was estimated in previous studies from the proportion during those 17 years. The individuals included were mostly men who of ambiguous base calls determined in routinely genotyped HIV se- have sex with men (MSM) infected with HIV-1 subtype B (Table 1).
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