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Basic and Translational Science

Characteristics of Transmitted Drug-Resistant HIV-1 in Recently Infected Treatment-Naive Patients in Japan

Hattori, Junko PhD; Shiino, Teiichiro PhD; Gatanaga, Hiroyuki MD, PhD; Mori, Haruyo PhD; Minami, Rumi MD, PhD; Uchida, Kazue PhD; Sadamasu, Kenji PhD; Kondo, Makiko PhD; Sugiura, Wataru MD, PhD the Japanese Drug Resistance HIV-1 Surveillance Network

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: April 1, 2016 - Volume 71 - Issue 4 - p 367-373
doi: 10.1097/QAI.0000000000000861

Abstract

INTRODUCTION

Most HIV cases treated with combination antiretroviral therapy (cART) and more potent antiretrovirals have HIV viral loads below detection limits and low mortality rates.1,2 A major drawback of these treatments, however, is the development of drug resistance, often because of poor adherence.3–5 Unfortunately, drug-resistant HIV can be transmitted to treatment-naive individuals, thus limiting the choice of first-line antiretroviral drugs.6,7 The prevalence of drug-resistant HIV among treatment-naive individuals varies widely,8–14 from a low of 10% to a high of 20% in high-income countries because of the availability of more antiretrovirals and higher cART coverage.

In Japan, the prevalence of drug-resistant HIV among newly diagnosed treatment-naive individuals in 2008 was 8.3%,15 lower than that reported from other developed countries.11,12,16 However, the annual prevalence in Japan showed an increasing trend from 5.9% in 2003 to 8.3% in 200815 with fluctuations in between, which raises concerns about an ongoing spread of drug-resistant HIV.

HIV/AIDS is a reportable disease in Japan; thus, physicians must report to the Ministry of Health, Labour and Welfare when an individual is first diagnosed and/or first admitted to a hospital. Among 21,425 individuals reported as diagnosed with HIV/AIDS by the end of 2012, 49.3% (n = 10,553) reported transmission through male-to-male sexual contact [men who have sex with men (MSM)].17,18 Although the numbers of newly diagnosed individuals are reported and epidemiological studies are often based on the year of diagnosis, the duration of infection before diagnosis remains unknown.

Distinguishing recent from established infections provides important information for monitoring the HIV epidemic and is essential to estimate HIV incidence and track the spread of HIV. Careful incidence analysis is also necessary to evaluate the effectiveness of new HIV-prevention programs, such as preexposure and postexposure prophylaxis. Recent HIV infections can be distinguished from established infections by assays that rely on differences in characteristics of anti-HIV antibodies, such as specificity, avidity, or titer.19–22

One of these assays, the BED capture enzyme immunoassay or BED assay,22 has become commercially available and is commonly used worldwide. The BED assay identifies recently acquired HIV-1 subtype B, AE, or D infections (<6 months) by measuring the proportion of HIV-1–specific IgG antibody to total IgG; this proportion increases in long-standing infection. In this study, we used the BED assay to distinguish recently and long-term HIV-infected individuals to characterize those with recent HIV incidence. We then sought to determine the trend in prevalence of transmitted drug-resistant (TDR) HIV in recently infected individuals newly diagnosed between 2007 and 2012 in Japan.

MATERIALS AND METHODS

Study Participants and Samples

Participants were enrolled if they were diagnosed as HIV seropositive in any hospital, HIV clinic, or public health diagnostic laboratory participating in our Japanese Drug-Resistance HIV Surveillance Network between January 2007 and December 2012. On obtaining a participant's informed consent, peripheral blood was drawn in an EDTA-added vacutainer tube and plasma samples were aliquoted and stored at −80°C until use. Participants' demographic information (sex, age, nationality, and risk behavior) was collected through either a doctor or a counselor's interview. Clinical information, such as CD4+ T cell count and viral load, was collected for analyses where available.

Ethics Statement

This study was conducted according to principles in the Declaration of Helsinki. The study was approved by the human subject research committee at Nagoya Medical Center, Japan. All patients provided written informed consent for the collection of samples and subsequent analyses.

Drug-Resistance Genotypic Testing and Determination of Drug-Resistant HIV

Drug-resistance genotypic testing was performed as described.15 In brief, RNA extracted from patient plasma samples was applied in reverse transcription/nested polymerase chain reaction to amplify protease (PR) and the N-terminal portion of reverse transcriptase (RT) genes. The amplified polymerase chain reaction products were then purified and sequenced using an automated DNA sequencer. After analyzing the output electropherograms using commercially available software, nucleotide sequences and amino acid sequences were obtained and amino acid substitutions by comparing with a reference sequence of HXB2 (accession no. K03455). TDR mutations were identified by comparison with the World Health Organization's list of transmitted surveillance drug-resistance mutations.23 The sequences reported in this study have been deposited in the DNA Data Bank of Japan (Accession numbers: AB863785 to AB863881, AB863906 to AB863951, AB864073 to AB864579, AB864599 to AB864639, AB864861 to AB865818, AB865826 to AB865881, AB865899 to AB865912, AB865913 to AB866408, AB866456 to AB866552, AB866694 to AB867194, AB867297 to AB867547, and AB442228 to AB442360).

Phylogenetic Tree Analyses and Determination of HIV Subtypes

Nucleotide sequences obtained in drug-resistance genotypic testing were aligned with 21 reference sequences from the Los Alamos HIV database,24 including HIV-1 subtypes A, B, D, CRF01_AE, and J as outgroup, using ClustalW. Codons associated with drug resistance were removed from the alignment. Phylogenetic trees were constructed using a maximum likelihood (ML), distance-matrix–based neighbor-joining (NJ), and Bayesian coalescent Markov chain Monte Carlo (MCMC) approaches. The best-fit model for nucleotide substitution was evaluated by the hierarchical likelihood ratio test using PAUP v4.0 with MrModeltest. The general time-reversible model with gamma-distributed site heterogeneity and invariant sites (GTR+G + I) and Tamura and Nei method were adopted for ML, Bayesian MCMC, and NJ trees, respectively. The statistical robustness of the ML and NJ tree clusters was evaluated by bootstrap analyses and the interior branch test with 1000 replicates, respectively.

Evolutionary parameters and chronological maximum clade credibility phylogeny of Bayesian MCMC approach were inferred by BEAST v1.8.25 The sequences were partitioned into 3 codon positions. To select a model for population growth and the molecular clock, we used Bayesian factor comparison with the marginal likelihood estimated26 using Tracer v.1.5 and selected strict clock with logistic growth model as the best-fit models. The convergence of parameters was inspected using Tracer v.1.5 with uncertainties depicted as 95% highest probability density intervals. The effective sample size of each parameter calculated in this inference was above 200. Tree samples in the MCMC were used to generate a maximum clade credibility tree using TreeAnnotator v.1.5.4 with a burn-in of first 20,000,000 states. The tree clusters were defined as significant when identical topologies were determined by 3 different inference methods: NJ, ML, and maximum clade credibility tree in Bayesian MCMC.

BED Assay

Although the BED assay is one of the most commonly used assays to identify recently seroconverted cases (within 6 months), it has been reported to overestimate the recent incidence by misclassification.27,28 To reduce the false-recent rate, we excluded cases with factors known to cause misclassification as follows; (1) subtypes were other than B, AE, or D, (2) having <50 CD4+ T cells/μL, suggestive of advanced HIV/AIDS status29,30 or no available data, and (3) HIV RNA level of <1000 copies per milliliter for the possibilities of being an elite controller or taking antiretrovirals. The remaining samples were subjected for the BED assay and further analyses.

BED assay was performed according to the manufacturer's instructions (Calypte HIV-1 BED Incidence EIA; BioRad, Tokyo, Japan). Briefly, 101× diluted plasma samples were added to microplate wells coated with antihuman IgG and incubated at 37°C. HIV-specific and HIV-nonspecific IgG antibodies were captured on the solid phase. After washing, synthetic peptides containing Gp41 epitopes of HIV-1 subtypes B, E, and D were added and incubated at 37°C. After washing, streptavidin-horseradish peroxidase conjugate was added and incubated at 37°C. After washing, tetramethylbenzidine substrate followed by stop solution was added and development of color was read at 450 nm wavelength. Optical density values were normalized (ODn) to decrease run-to-run variability, and each run was validated using controls and calibrating. Samples with ODn ≤0.8 were interpreted as “recent” seroconverters (RS) and ODn >0.8 as “long-term” seroconverters (LTS).

Statistical Analyses

Statistical analyses were performed using R software. Associations among patients' demographic characteristics, nationality, BED assay results, and transmission of drug resistance were determined by χ2 or Fisher exact probability.

RESULTS

Newly Diagnosed HIV-Infected Cases in Japan are Predominantly Japanese, MSM, and Infected With Subtype B

During the study period, 3904 newly diagnosed HIV-seropositive individuals were enrolled. The study population was primarily male (n = 3687, 94.4%) and Japanese (n = 3571, 91.5%), with a median age of 37 years. Most was MSM (n = 2588, 66.3%) (Table 1). Non-Japanese cases accounted for less than 10% of all cases and included individuals from countries such as Brazil, Thailand, China, the United States, Peru, Indonesia, Myanmar, and Korea.

TABLE 1
TABLE 1:
Case Demographics and HIV-1 Subtype Distribution (n = 3904)

PR and RT genes were successfully amplified in 3862 (98.9%) and 3849 (98.6%) of 3904 samples, respectively. Analysis of nucleotide sequences from the PR-RT regions showed that 89.4% of cases were infected with subtype B (Table 1), among which 94.8% were Japanese. The most common non-B subtype was CRF01_AE, accounting for 7.0% (n = 270). Various other subtypes were detected in small fractions, as follows: C (n = 48, 1.2%), CRF02_AG (32, 0.8%), F (16, 0.4%), A (15, 0.4%), G (15, 0.4%), and D (4, 0.1%). As for risk behaviors, 66.3% of cases were infected with HIV through MSM, 7.9% by heterosexual contact, 4.9% either male-to-male or unspecified sexual contact, and 0.7% intravenous drug use. Thus, excluding those with unspecified risk behaviors, HIV was sexually transmitted among 98.8% of our study population.

The overall prevalence of TDR HIV among the study population of 3904 cases was 9.1%. Annually, the prevalence increased from 9.8% in 2007 to 12.5% in 2010, and after the peak, it leveled off at 8.3% in the next 2 years (Fig. 1A). Most detected drug-resistance mutations were single mutations (7.9%) or those conferring resistance to a single class of antiretrovirals (8.7%), with dual-class and triple-class drug-resistance mutations detected only in 0.5% and 0.05%, respectively (see Table S1, Supplemental Digital Content, http://links.lww.com/QAI/A756).

FIGURE 1
FIGURE 1:
Annual prevalence of TDR HIV and prevalence of detected mutations by antiviral drug class between 2007 and 2012. Changes in the annual prevalence of TDR HIV among (A) all treatment-naive cases (n = 3904) and (B) recently seroconverted cases (n = 468). Line graphs indicate the proportion of cases with drug-resistant HIV. The dashed line in panel B indicates the regression curve. Histograms represent the prevalence of drug-resistance–associated mutations by antiviral drug class: nucleoside reverse transcriptase inhibitor (NRTI) (open bars), nonnucleoside reverse transcriptase inhibitor (NNRTI) (gray bars), and protease inhibitor (PI) (solid bars).

One Third of the Study Population Was Recently Seroconverted

Among 3904 newly diagnosed treatment-naive cases, plasma samples from 2700 cases were available for testing with the BED assay. To avoid misclassification, 104 cases were excluded because their subtypes were other than B, AE, or D, 1193 cases were excluded for having <50 CD4+ T cells per microliter and/or HIV RNA level of <1000 copies per milliliter. The remaining 1403 samples were subjected to the BED assay. Although the annual prevalence of RS cases showed a decreasing trend from 40.5% in 2007 to 41.1% in 2008, 33.2% in 2009, 31.4% in 2010, 30.3% in 2011, and 27.4% in 2012, approximately 1/3 of 1403 samples were identified as RS cases (n = 468, 33.4%) in the 6-year study period by BED assay.

Japanese MSM Tend to be Diagnosed Early

We characterized the population of recently diagnosed cases by comparing their prevalence among different characteristics, including sex, nationality, and risk factor (Table 2). By sex, significantly more males were recently seroconverted (33.9%) than females (15.4%; P = 0.02). Similarly, significantly more Japanese (34.2%) and MSM (35.6%) were recently seroconverted than non-Japanese (22.0%; P = 0.02) and those with other risk behaviors (24.1%; P < 0.001), respectively, suggesting that significantly more Japanese and MSM are diagnosed early in their infections.

TABLE 2
TABLE 2:
Prevalence of Recent and LTS Cases by Various Characteristics

Annual Prevalence of TDR HIV Among RS is Slightly Increasing

Among the 468 RS cases, 40 (8.5%) harbored drug-resistant HIV, with 5.8, 0.4, and 3.6% harboring nucleoside reverse transcriptase inhibitor, nonnucleoside reverse transcriptase inhibitor, and protease inhibitor–resistant viruses, respectively (Table 2). The annual prevalence of TDR HIV increased only slightly, with much fluctuation in the 6-year study period (slope = 0.0035, Fig. 1B). T215 revertants and M46I/L mutations were detected consistently over the study period (see Table S2A, Supplemental Digital Content, http://links.lww.com/QAI/A756). Other drug-resistance-associated mutations, however, were observed only sporadically, for example nonnucleoside reverse transcriptase inhibitor–resistant virus carrying K103N/P225H and protease inhibitor–resistant virus with D30N/N88D were detected in only 1 case each but both in 2011.

The Prevalence of TDR HIV-1 Did Not Differ Significantly Between RS and LTS Groups

The prevalence of TDR HIV-1 in RS cases was 8.5% and 9.2% in LTS cases (P = 0.68, Table 2). Eleven drug resistance–associated amino acid mutation sites were detected in the RS group and 20 in the LTS group (see Table S2A and B, Supplemental Digital Content, http://links.lww.com/QAI/A756). Strains with T215 revertants and M46I/L mutations similar to the RS group and K103N/S mutation in the LTS group were consistently detected over the study period (see Table S2B, Supplemental Digital Content, http://links.lww.com/QAI/A756), suggesting that these mutations have little or no effect on the replication capacity of HIV strains carrying them, and that these strains are already stabilized and circulating among high-risk groups.

To explore whether the RS and LTS groups were correlated in any way, a ML phylogenetic tree was constructed using nucleotide sequences with drug-resistance–associated sites removed. Samples from both the RS and LTS groups were evenly distributed, intermingled with one another, and no relationships were observed in the tree (Fig. 2). Moreover, sequences of both RS and LTS groups with certain drug-resistance mutations formed distinct clusters (Fig. 2; see Figure S1, Supplemental Digital Content, http://links.lww.com/QAI/A756), and the genetic relatedness of these clusters was confirmed by NJ and Bayesian analysis by a posterior probability of ≥0.95 (see Figure S2, Supplemental Digital Content, http://links.lww.com/QAI/A756); 27 of 31 cases with the M46I mutation (Fig. 3A; see Figure S2A, Supplemental Digital Content, http://links.lww.com/QAI/A756), 9 of 13 cases with M46L (Fig. 3B; see Figure S2B, Supplemental Digital Content, http://links.lww.com/QAI/A756), and all 4 samples expressing both D30N and N88D mutations (see Figures S1A, S2C, Supplemental Digital Content, http://links.lww.com/QAI/A756) in the PR gene. Similarly, 26 of 46 samples with T215X formed 3 separate clusters; 1 cluster consisting of 5 sequences with T215E mutation and 2 clusters with T215D and E (Fig. 2; see Figures S1B, S2D, Supplemental Digital Content, http://links.lww.com/QAI/A756), and 4 of 16 cases with K103N mutation formed a cluster (see Figures S1C, S2E, Supplemental Digital Content, http://links.lww.com/QAI/A756).

FIGURE 2
FIGURE 2:
Maximum-likelihood tree of recent and LTS (n = 1403). RS are shown in red branches and LTSs in black. Sequences with drug-resistance mutations are shown as symbols in different colors by antiretroviral class: nucleoside reverse transcriptase inhibitor (NRTI)-resistance mutations in blue circles, nonnucleoside reverse transcriptase inhibitor (NNRTI)-resistance mutations in green circles, protease inhibitor (PI)-resistance mutations in orange circles, NRTI/NNRTI-resistance mutations in blue green squares, NRTI/PI-resistance mutations in light blue squares, and NNRTI/PI-resistance mutations in light green squares. References are marked in yellow squares. Bootstrap values greater than 70 are shown.
FIGURE 3
FIGURE 3:
Subtrees in which sequences with protease inhibitor (PI)-resistance mutations, M46I or M46L, are concentrated. Partial trees of cluster consisting of PI-resistant HIV sequences are separated from Figure 2. A, a subtree comprising 27/31 sequences with the M46I mutation and (B) 9/13 sequences with the M46L mutation. RS are shown in red branches and LTSs in black. Asterisks depict sequences in which the M46I mutation was not detected. Het: heterosexual risk behavior; MSM: men who have sex with men; Sexual: nonspecified sexual risk behavior.

DISCUSSION

During this study, we sought to determine the prevalence of TDR in Japan. We found that the prevalence among recently seroconverted HIV cases (within 6 months) increased slightly (slope of 0.0035) between 2007 and 2012, whereas the plateaued prevalence (slope of −0.0001) was seen in our overall study population consisting both RS and LTS cases.

In terms of the characteristics of drug-resistant HIV, we found that HIV strains carrying high-level resistance mutations did not spread. The 2 major strains consistently detected over the study period were those with low-level resistance mutations, M46I/L in PR or T215X in RT. This result contradicts our finding on the increasing prevalence of TDR HIV among newly diagnosed cases because this prevalence reflects the number of patients on cART with acquired drug resistance and recently developed antiretrovirals has enabled better control of HIV infections. This contradiction indicates that drug-resistant HIV is transmitted in the treatment-naive population not only from on-treatment patients with acquired resistance but also from treatment-naive patients with TDR. Little et al,31 reported that the replication capacities of drug-resistant variants were not significantly lower than wild-type virus, and the time it takes for the drug-resistant variants to become undetectable by bulk sequencing ranged from 4.1 years to lifetime. Viruses with either the M46I/L or T215X mutations conveying only low-level resistance are no exception. As these mutations do not confer deleterious effect on HIV replication, they have become widely circulated, especially among the MSM population, and are seen as clusters in phylogenetic analyses. Interestingly, the annual prevalence of TDR HIV in our study population comprising cases with both recent and long-standing infection seemed fairly stable (7–10% each year), except for 2010 (12.5%). The stable prevalence rate is reasonable, considering that cases in the LTS group harbor HIV strains that evolved to better fit drug-free conditions although they circulate with drug-resistance mutations.

Among the cases found to be RS, approximately one third of the study population significantly more were Japanese, male, and/or MSM than were non-Japanese, female, and/or infected by other risk behaviors. Our finding that HIV was sexually transmitted among 98.9% of our study population is consistent with our nationwide surveillance of drug-resistant HIV in 2003 to 2008 in Japan.15 In Japan, anonymous HIV tests are given for free at public health institutes and walk-in testing centers. This strategy encourages frequent testing because early diagnosis is important in controlling viral replication by early initiation of antiretroviral treatment to prevent transmission. In addition, the MSM community has been targeted by HIV-prevention events held in urban areas of Japan, where attendees are counseled and educated about the consequences of HIV infection and danger of other sexually transmitted diseases. Besides HIV, free testing is also offered for hepatitis B virus, hepatitis C virus, and syphilis. These prevention efforts may have led the Japanese MSM population to gain awareness of their risks for acquiring HIV. However, women and high-risk heterosexual men neglect the risks of HIV infection and tend not to find out their HIV status until other occasion, for instance, a routine pregnancy or presurgical screening. As for the non-Japanese HIV-infected patients, some of them came to Japan seeking treatment after their HIV infections were well established. Therefore, it is not surprising that the proportions of RS cases in females, high-risk heterosexual males, and non-Japanese populations are small. In this study, we found that the proportion of those who were diagnosed within 6 months of HIV incidence was decreasing annually, which may be interpreted as the reduced awareness of high-risk population toward the HIV. However, according to the Annual Report on Trend of AIDS Incidence in Japan, the numbers of newly diagnosed HIV cases and those who have already developed AIDS at diagnosis continued to rise until around 2007 and have leveled off thereafter.17,18 This suggests that the decreasing rate of RS cases is the indication that the increasing numbers of individuals well aware of HIV infection use preventive measures, hence, do not get infected, whereas those who acquire HIV are individuals neglecting the risk. Therefore, stronger prevention strategies targeting both men and women, especially of sexually active ages, must be implemented to reduce further the number of new HIV cases.

For epidemiological analysis, drug-resistance tests are strongly recommended on HIV diagnosis not only as a guide to choose antiretrovirals but also to understand the trend in transmission of drug-resistant HIV and to study transmission networks. Thus, drug-resistance testing and methods to estimate the time of infection continue to be important tools in epidemiological studies to assess the prevalence of drug-resistant HIV and to measure the effectiveness of preventive efforts.

ACKNOWLEDGMENTS

The authors are grateful to all the patients who participated in our surveillance study. The authors thank the members of Japanese Drug Resistance HIV-1 Surveillance Network for their support and helpful discussions: Yoshiaki Ishigatsubo, Masahiro Fujii, Teruhisa Fujii, Keiko Ido, Shingo Kato, Ichiro Koga, Yoko Kojima, Masayasu Oie, Yasuo Ota, Seiji Saito, Takuma Shirasaka, Kouichirou Suemori, Kiyonori Takada, Noboru Takata, Yoshinari Tanabe, Masao Tateyama, Atsuhisa Ueda, Mikio Ueda, and Dai Watanabe. The authors also thank Claire Baldwin for her help in preparing the article.

REFERENCES

1. Ray M, Logan R, Sterne JA, et al.. The effect of combined antiretroviral therapy on the overall mortality of HIV-infected individuals. AIDS. 2010;24:123–137.
2. Sterne JA, Hernán MA, Ledergerber B, et al.. Long-term effectiveness of potent antiretroviral therapy in preventing AIDS and death: a prospective cohort study. Lancet. 2005;366:378–384.
3. Gardner EM, Hullsiek KH, Telzak EE, et al.. Antiretroviral medication adherence and class-specific resistance in a large prospective clinical trial. AIDS. 2010;24:395–403.
4. Pham PA. Antiretroviral adherence and pharmacokinetics: review of their roles in sustained virologic suppression. AIDS Patient Care STDS. 2009;23:803–807.
5. Maggiolo F, Airoldi M, Kleinloog HD, et al.. Effect of adherence to HAART on virologic outcome and on the selection of resistance-conferring mutations in NNRTI- or PI-treated patients. HIV Clin Trials. 2007;8:282–292.
6. Wittkop L, Günthard HF, de Wolf F, et al.. Effect of transmitted drug resistance on virological and immunological response to initial combination antiretroviral therapy for HIV (EuroCoord-CHAIN joint project): a European multicohort study. Lancet Infect Dis. 2011;11:363–371.
7. Fox J, Dustan S, McClure M, et al.. Transmitted drug-resistant HIV-1 in primary HIV-1 infection; incidence, evolution and impact on response to antiretroviral therapy. HIV Med. 2006;7:477–483.
8. The HIV Drug Resistance Report-2012. World Health Organization; 2012. Available at: http://www.who.int/hiv/pub/drugresistance/report2012. Accessed July 5, 2014.
9. Aghokeng AF, Kouanfack C, Laurent C, et al.. Scale-up of antiretroviral treatment in sub-Saharan Africa is accompanied by increasing HIV-1 drug resistance mutations in drug-naive patients. AIDS. 2011;25:2183–2188.
10. Dean J, Ta Thi TH, Dunford L, et al.. Prevalence of HIV type 1 antiretroviral drug resistance mutations in Vietnam: a multicenter study. AIDS Res Hum Retroviruses. 2011;27:797–801.
11. Callegaro A, Svicher V, Alteri C, et al.. Epidemiological network analysis in HIV-1 B infected patients diagnosed in Italy between 2000 and 2008. Infect Genet Evol. 2011;11:624–632.
12. Chan PA, Tashima K, Cartwright CP, et al.. Short communication: transmitted drug resistance and molecular epidemiology in antiretroviral naive HIV type 1-infected patients in Rhode Island. AIDS Res Hum Retroviruses. 2011;27:275–281.
13. Bartmeyer B, Kuecherer C, Houareau C, et al.. Prevalence of transmitted drug resistance and impact of transmitted resistance on treatment success in the German HIV-1 Seroconverter Cohort. PLoS One. 2010;5:e12718.
14. Wensing AM, van de Vijver DA, Angarano G, et al.. Prevalence of drug-resistant HIV-1 variants in untreated individuals in Europe: implications for clinical management. J Infect Dis. 2005;192:958–966.
15. Hattori J, Shiino T, Gatanaga H, et al.. Trends in transmitted drug-resistant HIV-1 and demographic characteristics of newly diagnosed patients: nationwide surveillance from 2003 to 2008 in Japan. Antivir Res. 2010;88:72–79.
16. Bonura F, Tramuto F, Vitale F, et al.. Transmission of drug-resistant HIV type 1 strains in HAART-naive patients: a 5-year retrospective study in Sicily, Italy. AIDS Res Hum Retroviruses. 2010;26:961–965.
17. Annual Report on Trend of AIDS Incidence in Japan. National AIDS Surveillance Committee, Specific Disease Control Division, Ministry of Health, Labour and Welfare. 2013. Available at: http://api-net.jfap.or.jp/status/2013/13nenpo/nenpo_menu.htm. Accessed February 14, 2015.
18. 2014 UNGASS Country Progress Reports. HIV/AIDS Trends in Japan. 2014. Available at: http://www.unaids.org/sites/default/files/en/dataanalysis/knowyourresponse/countryprogressreports/2014countries/JPN_narrative_report_2014.pdf. Accessed February 14, 2015.
19. Parekh BS, Kennedy MS, Dobbs T, et al.. Quantitative detection of increasing HIV type 1 antibodies after seroconversion: a simple assay for detecting recent HIV infection and estimating incidence. AIDS Res Hum Retroviruses. 2002;18:295–307.
20. Chawla A, Murphy G, Donnelly C, et al.. Human immunodeficiency virus (HIV) antibody avidity testing to identify recent infection in newly diagnosed HIV type 1 (HIV-1)-seropositive persons infected with diverse HIV-1 subtypes. J Clin Microbiol. 2007;45:415–420.
21. Janssen RS, Satten GA, Stramer SL, et al.. New testing strategy to detect early HIV-1 infection for use in incidence estimates and for clinical and prevention purposes. JAMA. 1998;280:42–48.
22. Hargrove JW, Humphrey JH, Mutasa K, et al.. Improved HIV-1 incidence estimates using the BED capture enzyme immunoassay. AIDS. 2008;22:511–518.
23. Bennett DE, Camacho RJ, Otelea D, et al.. Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update. PLoS One. 2009;4:e4724.
24. HIV Sequence Alignments. Los Alamos, NM: National Laboratory. Available at: http://www.hiv.lanl.gov/. Accessed May 25, 2014.
25. Drummond AJ, Rambaut A. BEAST: bayesian evolutionary analysis by sampling trees. BMC Evol Biol. 2007;7:214.
26. Xie W, Lewis PO, Fan Y, et al.. Improving marginal likelihood estimation for bayesian phylogenetic model selection. Syst Biol. 2011;60:150–160.
27. Centers for Disease Control and Prevention (CDC). Interim Recommendations for the Use of the BED Capture Enzyme Immunoassay for Incidence Estimation and Surveillance. Statement from the Surveillance and Survey and the Laboratory Working Groups to the Office of the Global AIDS Coordinator. Atlanta, Georgia: CDC; 2006. Available at: http://www.cdc.gov/globalAIDS/docs/surveillance/Interim%20Recommendations%20for%20the%20use%20of%20the%20BED%20capture%20enzyme%20immunoassay%20for%20incidence%20estimation%20and%20surveillance%20Approved%20November%2021%202006%20%282%29.pdf. Accessed December 17, 2012.
28. Technical Update on HIV Incidence Assays for Surveillance and Monitoring Purposes. UNAIDS; 2015. Available at: http://www.unaids.org/sites/default/files/media_asset/HIVincidenceassayssurveillancemonitoring_en.pdf. Accessed February 14, 2015.
29. Marinda ET, Hargrove J, Preiser W, et al.. Significantly diminished long-term specificity of the BED capture enzyme immunoassay among patients with HIV-1 with very low CD4 counts and those on antiretroviral therapy. J Acquir Immune Defic Syndr. 2010;53:496–499.
30. Hladik W, Olara D, Mermin J, et al.. Effect of CD4+ T cell count and antiretroviral treatment on two serological HIV incidence assays. AIDS Res Hum Retroviruses. 2012;28:95–99.
31. Little SJ, Frost SD, Wong JK, et al.. Persistence of transmitted drug resistance among subjects with primary human immunodeficiency virus infection. J Virol. 2008;82:5510–5518.
Keywords:

transmitted drug-resistant HIV; Japan; BED assay; recent infection

Supplemental Digital Content

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