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Translational Research

Full-Genome Analysis of Hepatitis C Virus in Japanese and Non-Japanese Patients Coinfected With HIV-1 in Tokyo

Ishida, Yuki PhD*; Hayashida, Tsunefusa PhD*; Sugiyama, Masaya PhD; Tsuchiya, Kiyoto PhD*; Kikuchi, Yoshimi MD*; Mizokami, Masashi MD; Oka, Shinichi MD*; Gatanaga, Hiroyuki MD*

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: March 1, 2019 - Volume 80 - Issue 3 - p 350-357
doi: 10.1097/QAI.0000000000001919



Coinfection with hepatitis C virus (HCV) is a major comorbidity and associated with increased mortality rate in patients infected with HIV-1, which facilitates HCV-induced hepatic fibrosis and HCV disease progression.1 Both viruses are bloodborne, and therefore, coinfection is frequently identified in injection drug users (IDUs). Furthermore, sexual transmission of HCV has been reported recently among HIV-1–infected men who have sex with men (MSM).2–4 In Japan, although the HCV coinfection rate of 4%–5% among HIV-1–infected patients is higher than the estimated prevalence of HCV in the general population (less than 0.5%),5–7 the rate is lower compared with other countries because of the low prevalence of injection drug use (lifetime prevalence of illicit drug use as a whole in 2009 was only 2.9%).8 Recently, however, at our clinic, the AIDS Clinical Center, one of the largest referral centers for HIV-1 care in Japan, there has been a surge in the rate of acute HCV infection among HIV-1–infected MSM.8,9

For effective delivery of prevention programs for both viruses, epidemiological analysis of transmission dynamics of HCV and HIV-1 among high-risk groups is necessary. In this study, we analyzed the HCV full-genome using next-generation sequencing (NGS) in 88 coinfected patients and delineated the epidemiological status of HCV transmission among HIV-1–infected individuals in Tokyo, and combined this with phylogenetic analysis of HIV-1.


Patients and Clinical Samples

From 1997 to the end of 2015, a total of 4014 HIV-1–infected patients visited our Outpatient Clinic at the AIDS Clinical Center, National Center for Global Health and Medicine, Tokyo, which handled 46% of HIV-1–infected Tokyo patients diagnosed during the same period. They were interviewed at the first visit by clinical nurse specialists using structured questionnaire that included items on sexuality and injection drug use. Patients with history of drug injection were categorized as such IDU. Plasma samples were obtained periodically and stocked at −80°C under written informed consent for use for virological analysis. The ethics committee approved the sample collection and the analysis. Hemophiliac patients were excluded from this study because they acquired HCV/HIV-1 infection through contaminated blood products imported from the United States and their HCV was epidemiologically different from those of other infected patients.10,11 Of the remaining 3993 HIV-1–infected patients, 98 patients (2.5%) had detectable HCV RNA in plasma and their plasma samples had been stocked. For each patient, we selected the plasma sample with the highest HCV load, and used these samples for HCV full-genome amplification and sequence analysis. All the samples used for such analysis were obtained between 2001 and 2017, before commencement of HCV therapy, including direct-acting antivirals (DAAs). When a previously HCV-uninfected patient acquired new HCV infection, confirmed by HCV antibody seroconversion, during regular visits for HIV-1 follow-up, they were diagnosed as acute hepatitis C. After confirmation of the diagnosis of acute hepatitis C, the patient was interviewed about injection drug use. Patients diagnosed with acute hepatitis C during and after 2010 were defined as having recent HCV infection.

Amplification of HCV Full Genome

RNA was extracted from 140 μL of plasma with QIAamp viral RNA mini kit (Qiagen, Hilden, Germany) and divided into 8 aliquots. To synthesize cDNA, each aliquot of HCV RNA was reacted at 50°C for 25 minutes with a mixture of SuperScript IV Reverse Transcriptase (RT) (ThermoFisher Scientific, Waltham, MA) including Vir7,12 dNTPs, and betaine (Sigma Aldrich, St. Louis, MO). First-round polymerase chain reaction (PCR) was performed with a mixture of PrimeSTAR GXL (TaKaRa, Shiga, Japan) including forward and reverse primers, dNTPs and betaine. For each sample, each of the genotype-specific primer sets for HCV genotypes 1–6 described in Bull's report12 was used. The cycling condition was preincubated at 98°C for 2 minutes, 30 cycles at 98°C for 10 seconds, and at 68°C for 5 minutes. Nested PCR was subsequently performed with a mixture of PrimeSTAR GXL, including dNTP, betaine, and the reported primers.12 The cycling conditions were similar to those of the first-round PCR. Electrophoresis was performed to evaluate the length of the amplified HCV genome.

Next-Generation Sequencing

The amplified products were purified with PCR purification kit (Qiagen) following the instructions provided by the manufacturer. The purified nested PCR products were normalized at 0.2 ng/μL and tagmented with Nextera XT preparation kit and Nextera XT index kit (Illumina, San Diego, CA). To amplify the tagged fragments, the PCR was performed using the following cycling conditions: The first step was at 72°C for 3 minutes and 95°C for 10 seconds. The second step was 12 cycles at 95°C for 10 seconds, 55°C for 30 seconds, and 72°C for 30 seconds. The final step was at 72°C for 5 minutes. The amplified tagged fragments were purified with AMPure beads (ThermoFisher) and then their length was evaluated using Bioanalyzer (Agilent Technologies, Santa Clara, CA). They were normalized with beads contained in the Nextera XT preparation kit. Finally, all the samples were pooled to establish the library, and MiSeq was operated with MiSeq reagent Kit V3 (Illumina).

Determination of Consensus Sequences and HCV Genotypes

The data obtained from MiSeq were analyzed to determine the sequences of HCV full genome. The reads were quality checked with FASTX Tool Kit to remove those reads with quality score of less than 30 and also short-length reads that were below 150 nucleotides. Using the reads with high-quality score, approximately 9.2 kb single sequence was prepared by de novo assembly with VICUNA13 and defined as a reference sequence. The reads were mapped to the reference sequence with Burrows–Wheeler Aligner,14 and the mapping status was visualized with Integrative Genomics Viewer15 to generate consensus sequences. Mapping the reads and generating consensus sequences were repeated until the present consensus sequence was consistent with the previous one. When the sequence was consistent, it was defined as the consensus sequence. The context-based Modeling for Expeditious Typing (COMET)16 and the HCV Subtyping Tool at BioAfrica17 were used to determine the genotype of each of the consensus sequences.

Phylogenetic Analyses for All HCV Genotypes

The thus obtained cohort sequences were phylogenetically analyzed with reference sequences. The total number of our cohort sequences and the reference sequences was 314, which is the limit of our computer to analyze HCV full-genome sequences. The reference sequences were selected randomly from the Hepatitis Virus Database Server.18 Multiple alignments were performed using ClustalW19 through MEGA7. Phylogenetic trees were depicted with MEGA7 using the neighbor-jointing method. Bootstrap sampling was 1000 replicates, and bootstrap values at important positions were shown. When multiple sequences were located within 0.02 genetic distance with a bootstrap value higher than 99%, they were considered as putative clusters.

Phylogenetic Analyses for HCV Genotypes 1b and 2a

To determine whether the cohort sequences cluster each other, genotype-specific phylogenetic analysis was performed for genotypes 1b and 2a. In this analysis, we selected as many as possible HCV full-genome sequences that were highly similar to one of the clustered cohort sequences, using BLAST. These were used as the reference sequences. Multiple alignments were performed, and a phylogenetic tree was depicted by the same method described above.

Phylodynamic Analyses and Inference of Divergence Date

The time to the most recent common ancestor was estimated by maximum clade credibility tree analysis using the Bayesian Markov chain Monte Carlo method. The analysis was conducted by BEAST 2.4.320 with 100,000,000 states, logged every 10,000 states, and 10% burn-in. A general time reversible model with gamma distribution and invariant sites, relaxed clock log normal model, and coalescent Bayesian skyline model were adopted because of the favorable Bayes factor analyzed by Tracer 1.5.0 in the BEAST package. Bayesian skyline plot analysis was performed by BEAST, and then effective population size was illustrated by Tracer 1.5.0.

Phylogenetic Analyses of HIV-1 RT

To determine the possible relationship between transmission of HCV and that of HIV-1, HIV-1 RT sequences were determined by direct sequencing after RT-PCR,6,7 and phylogenetic analysis was performed by the same methods described above. Reference sequences for phylogenetic tree of HIV-1 RT sequences were derived from HCV-negative patients who visited the Outpatient Clinic of the AIDS Clinical Center, National Center for Global Health and Medicine in 2014.

Historical Data of Newly Diagnosed HIV-1–Infected Cases in Tokyo

The annual number of newly diagnosed HIV-1–infected cases from 1985 to 2016 was obtained from the statistical data reported by the National AIDS Surveillance Committee (the Ministry of Health, Labor, and Welfare of the Japanese Government).


HCV Full-Genome Amplification

We analyzed the plasma samples of 98 HCV/HIV-1–coinfected patients, and the HCV full-genome was successfully amplified in 88 (89.8%) of them, including 54 MSM, 17 IDU, and 17 heterosexual patients (drug-using MSM were part of the IDU group). The amplification rate was 98.8% in those with HCV-RNA levels higher than 105 copies/mL, and as low as 30.8% in those with HCV-RNA lower than 105 copies/mL, which seems to be the potential threshold for full-genome amplification by this method (Table 1). The sequences of the amplified HCV full-genome were determined with the NGS and registered in DNA Data Bank of Japan (LC368333-LC368345, LC368373-LC368381, LC368383-LC368447, and LC368449). HCV genotyping using COMET16 and HCV Subtyping Tool at BioAfrica17 were performed successfully, and the results of both methods were the same in all the 88 cases with amplified HCV full genome. HCV 1b was identified as the most frequent genotype, followed by 2a and 2b (Table 2). These results seem compatible with the genotype frequencies reported in Japan.21 Genotype 2c, which had never been reported previously in Japan, was identified in 2 Japanese MSM. HCV genotypes 1a, 3b, and 6 were identified in foreign patients other than Japanese, and genotype 4a was identified in one Japanese MSM.

Plasma HCV RNA Load and Amplification Success Rate
HCV Genotypes and Patients' Characteristics

Phylogenetic Analysis of HCV Full Genome

To delineate the HCV transmission status among HIV-infected individuals living in Tokyo, a phylogenetic tree was constructed using the 88 obtained HCV full-genome sequences and 226 reference sequences selected randomly from the Hepatitis Virus Database Server18 (Fig. 1). The sequences of each genotype converged together away from other genotypes, confirming the abovementioned genotypes determined using COMET16 and HCV Subtyping Tool at BioAfrica.17 The majority of the sequences of the study cohort were more than 0.02 genetic distance away from the other sequences. However, there were 3 dense clusters within 0.02 genetic distance with 100% bootstrap value; 2 in genotype 1b (clusters A and B) and one in genotype 2a (cluster C). To verify that the abovementioned sequences cluster with each other, 2 phylogenetic trees were reconstructed for genotypes 1b and 2a, respectively. In this analysis, highly similar (≥90%) HCV full-genome sequences (≥8500 base pairs) with one of the clustered sequences were selected using BLAST and used as reference sequences. For the analysis of genotype 1b, 59 cohort sequences and 255 reference sequences (highly similar to #025, total score ≥11,808 in BLAST) were used (see Figure 1, Supplemental Digital Content, For the analysis of genotype 2a, there were only 67 sequences with high similarity to #125 in BLAST (total score ≥11,375). All the 67 sequences were used as references and analyzed with 12 cohort sequences (see Figure 2, Supplemental Digital Content, We found no reference sequences located within clusters A, B, and C, indicating that these clusters were spread and locally established in Tokyo.

Phylogenetic tree of HCV full genome with 226 reference sequences. Study patients are coded by symbols with 3-digit numbers. The width of the triangle in the tree branch represents the number of references. The origins of the reference strains are indicated when known; CAN, Canada; CHN, China; EGY, Egypt; GBR, Great Britain; JPN, Japan; SUI, Switzerland.18 Bootstrap values at important positions are shown.

Genotype 1b included clusters A and B and many reference sequences that originated from Japan, United States, China, and EU (Fig. 1). Cluster A included 7 sequences, which were derived from MSM including 3 cases of confirmed recent HCV infection (#027, #038, and #105) (serologically confirmed acute hepatitis C cases during and after 2010), indicating that these viruses are currently being actively transmitted among MSM through homosexual contact. Cluster B included 24 sequences derived from 13 MSM, 10 IDU, and 1 heterosexually infected patient, and 12 of these were confirmed cases of recent HCV infection (#025, #026, #028, #029, #032, #033, #034, #035, #036, #037, #042, and #149), indicating that these viruses are currently being actively transmitted among MSM/IDU individuals. In addition to clusters A and B, few pairs of genetically close sequences were identified (#073 and #088, #077 and #096, #099 and #103) derived from MSM in genotype 1b.

Genotype 2a included cluster C and reference sequences that originated from Japan and China. Cluster C included 5 sequences derived from 2 MSM and 3 IDU, and 4 of these were confirmed cases of recent infection (#114, #125, #131, and #132), indicating that these viruses are currently being actively transmitted among MSM and IDU. Apart from cluster C, another genotype 2a sequence was identified in an MSM case of confirmed recent infection (#113). Genotype 2b included 5 sequences derived from 4 MSM and 1 heterosexually infected individual. There were 2 genotype 2c sequences derived from MSM, including one case of confirmed recent infection (#142).

Four, one, and 4 sequences were derived from foreign patients, included in genotype 1a, 3b, and 6, respectively, with reference sequences that originated from foreign countries, indicating that they had probably acquired HCV infection outside of Japan. One Japanese MSM-derived sequence (#112) was included in genotype 4a with reference sequences from foreign countries, suggesting that the patient could have acquired HCV infection from one foreign MSM. No recent infection cases were included in these genotypes, and no dense cluster was identified, indicating that these viruses were not actively being transmitted in Tokyo.

Phylodynamic Analysis of HCV Full Genome

To estimate the divergence time of the 3 dense clusters described above, a phylogenetic analysis of the maximum clade credibility molecular clock was performed using the HCV full-genome sequences. The most recent common ancestors of clusters A, B, and C were found in the year 1992.04, 2003.03 (see Figure 3, Supplemental Digital Content,, and 2010.08 (see Figure 4, Supplemental Digital Content,, respectively. The Bayesian skyline plot indicated gradual expansion of cluster B population from 2006 to 2008 (Fig. 2), during which the largest numbers of newly diagnosed HIV-1 infection cases were reported in Japanese men and Japanese MSM in Tokyo (see Figure 5, Supplemental Digital Content, The Bayesian skyline plot failed to reveal the populational growth of clusters A and C, most likely due to the small number of patients included in these clusters.

Effective population size of HCV cluster B. Bayesian skyline plot estimated from 24 HCV full-genome sequences in cluster B using BEAST 2.4.3. Thick black line: estimated effective number of infections over time, blue area: 95% highest posterior density confidence intervals of this estimate.

Drug-Resistance Mutations in Prevailing HCVs

Phylogenetic analysis showed active dominance of certain genetic clusters of HCV variants among MSM and IDU in Tokyo. In this regard, certain mutations that confer resistance to DAAs were reported to be prevalent in treatment-naive individuals.22–26 To delineate the drug susceptibility in the prevailing viruses, we analyzed the amino acid frequency at the drug mutation positions. No resistance-associated mutations were prevalent in cluster A (see Table 1, Supplemental Digital Content, All the sequences in cluster B harbored the combination of Y56F in NS3 and S556G in NS5B, suggesting possible altered susceptibility of these clustered viruses to HCV protease inhibitors and NS5B polymerase inhibitor (especially grazoprevir and dasabuvir) (see Table 1, Supplemental Digital Content,–38 The Y93H in NS5A, known as a polymorphic mutation associated with drug resistance,24,30–37 was identified only in one patient (3.6%) in genotype 1b, which was significantly lower than that reported in Japan (8.2%).26 Each of the V55A24,28,39 and Q80K24,31,40,41 in NS3, and Q30H24,29–32,34,36,37 in NS5A mutations were identified in one HCV 1a–infected patient (see Table 2, Supplemental Digital Content, No DAA resistance–associated mutations were detected in genotypes other than 1a and 1b.

Phylogenetic Analysis of HIV-1 RT Sequences

To determine the relation between the transmission of HCV and that of HIV-1, we determined the HIV-1 RT sequences by direct sequencing with RT-PCR for the patients with stocked plasma samples confirmed to have detectable HIV-1 loads.6,7 HIV-1 RT sequences were successfully obtained in 57 of the 88 (64.8%) HCV/HIV-1–coinfected patients, and phylogenetic analysis was performed using 105 reference sequences derived from HCV-negative HIV-1–infected patients (Fig. 3). The most frequent HIV-1 subtype was B (84.2%) followed by AE (12.3%), A (1.8%), and C (1.8%). Of the 51 HCV/HIV-1–coinfected Japanese patients, 47 (92.2%) were infected with HIV-1 subtype B, whereas the others (7.8%) were infected with subtype AE. All the 6 HCV/HIV-1–coinfected foreign patients were infected with subtypes other than B, with the exception of one patient (#102). These results suggest that the non-B subtype HIV-1–infected Japanese patients and the foreign patients had acquired HIV-1 infection outside of Japan, considering that these HIV-1 subtypes prevail in countries other than Japan.6,7 Their HCV sequences were not included in the dense clusters (Fig. 1) and no cases of confirmed recent HCV infection were included in this group, indicating that these patients are not currently transmitting their HCV and HIV-1 to others in Tokyo.

Phylogenetic tree of HIV-1 RT sequences. Halos, area of HIV-1 subtypes other than B; dark green, G; purple, F1; yellowish green, A; blue, AE; yellow, C; orange, BC; non-haloed area, subtype B; symbols and 3-digit numbers, study patients; black 4-digit numbers, reference sequences.

Interestingly, all patients infected with HCV included in the dense clusters (clusters A, B, and C) were infected with HIV-1 subtype B, which is the most actively transmitted HIV-1 subtype among MSM and IDU in Japan,6,7 suggesting that domestic transmission of HCV and HIV-1 occurs in the same risk groups in Japan. However, the HIV-1 RT sequences in patients infected with HCV in the same dense clusters did not converge together and did not form a cluster, but rather diverged in subtype B area in the phylogenetic tree, although there were 4 pairs phylogenetically linked in HIV-1 RT tree and included in the same dense cluster in HCV tree [#027 and #123 in cluster A (framed with a red box), #114 and #125 in cluster C (blue box), #141 and #149 in cluster B (green box), and #037 and #028 in cluster B (green box)]. There were 3 pairs of HCV/HIV-1–coinfected patients phylogenetically linked in the subtype B area of HIV-1 RT tree, although their HCV genotypes were different or included in different clusters in the HCV phylogenetic tree [#087 and #101 in genotypes 2a and 1b (connected with a black bracket), #034 and #123 in clusters B and A (black bracket), and #083 and #124 in nonclustered genotype 1b and cluster A (black bracket), respectively]. These results indicate that these patients acquired HCV infection from individuals different from those from whom they had acquired HIV infection from. The HIV-1 RT sequences derived from the cases of confirmed recent HCV infection were scattered in all the area of subtype B in the HIV-1 RT phylogenetic tree, suggesting that it is quite difficult to predict which HIV-infected individuals will acquire new HCV infection next.


In this study, HCV full genome was successfully amplified and analyzed in 88 HIV-1–coinfected individuals. Previous studies of HCV molecular epidemiology used only the sequences of nonstructural protein 5B (NS5B), which can be amplified with the same primer sets for different HCV genotypes.42,43 In these studies, the obtained results were limited because the used NS5B fragment is short (386 and 339 nucleotides, respectively42,43) and relatively conserved. In fact, when we used the same NS5B fragment,43 the margins of clusters A and B could be hardly recognized (see Figures 6 and 7, Supplemental Digital Content, and their bootstrap values were decreased from 100 to 68 and 64, respectively. On the other hand, our full-genome analysis showed phylogenetically converged HCV sequences and identified 3 dense clusters among the cases of MSM and IDU in Tokyo. Two of the 3 clusters were involved in genotype 1b and the other one was involved in genotype 2a, which is compatible with a recent report from Japan on HCV genotype prevalence.21 All the included cases were MSM in one cluster (cluster A) of HCV genotype 1b, and the majority and nearly half of the other 2 clusters (clusters B and C) were MSM, suggesting that these viruses were transmitted through homosexual activity. Phylodynamic analysis indicated population expansion of cluster B from 2006 to 2008, during which the largest numbers of HIV-1–infected MSM were diagnosed in Tokyo. Increasing numbers of acute hepatitis C cases were reported among HIV-1–infected MSM,2–4 although sexual transmission of HCV is generally believed to be inefficient.

The cases clustered in HCV phylogenetic tree did not form a cluster in HIV-1 RT phylogenetic tree, indicating that they had acquired HIV-1 and HCV infection from different persons. It is possible that MSM and IDU with high risk of infection change their sexual partners and drug-using groups, resulting in the spread of the viruses to a wider range of high-risk groups. The HIV-1 RT sequences of cases confirmed to have acute HCV infection diverged and spread in subtype B area, indicating that any person infected with subtype B HIV-1 could acquire new HCV infection and that it is quite difficult to stop the current HCV epidemic. Earlier use of HCV therapy with DAAs can perhaps prevent the spread of viruses in communities at high risk. However, if HCV strains with low susceptibility to DAAs are actively being transmitted, it could make a serious problem. The selection of inappropriate therapeutic regimen could result in the emergence of multiple drug-resistant viruses and their spread in high-risk groups. In this study, the HCV sequences in cluster B harbored common mutations associated with reduced drug susceptibility, although they were derived from DAA-naive patients. For patients infected with these viruses, careful selection of DAA regimen is of paramount importance.

This study has certain limitations. First, determination of the transmission route relied on the patients' self report at the interview with the clinical nurse specialist. The true transmission route cannot be verified, although the used questionnaire included items on sexuality and injection drug use. In fact, the HCV sequence of one heterosexual case (#035) was included in cluster B, in which the others were derived from MSM or IDU. This patient could be MSM or IDU. Furthermore, our questionnaire included an item on injection drug use but did not include items on noninjection drug use, which might have impact on HCV transmission. Noninjection drug users might be classified as MSM or heterosexuals in this study if they had not used injection drugs. Second, the success rate of HCV full-genome amplification depended on the viral load of the specimen. Therefore, cases with high HCV load (>105 copies/mL) were preferentially selected for analysis. Furthermore, if the patients were infected with multiple HCV strains, minor strains were probably not detected in our analysis. Third, the sampling time range for analyzed samples was as long as 17 years (from 2001 to 2017). This long range might have an impact on the definition of the clusters because genetic distance increases over time even within a single patient. Fourth, HIV-1 RT sequences were available only for 57 of the 88 (64.8%) coinfected cases whose HCV full genome was analyzed because most of the analyzed cases were successfully treated with antiretroviral therapy and their HIV-1 load was well suppressed. Because of that, our study could have underestimated the overlapping of HCV and HIV-1 clusters. Fifth, this is a single-center study. Our study patients do not properly reflect the whole HCV/HIV-1–coinfected patients in Tokyo. However, our facility is the largest referral center for HIV/AIDS care and 46% of the diagnosed HIV-1–infected patients in Tokyo had visited our clinic.

Despite the potential flaws discussed above, we successfully delineated active transmission of some clustered HCV strains among MSM and IDU. To effectively suppress the current epidemic of HCV infection, early diagnosis of HCV infection and early use of appropriate DAA regimens are critically important. Careful monitoring of high-risk individuals, including HIV-1–infected patients, and sequence analysis of transmitting HCV strains are warranted.


1. Bica I, McGovern B, Dhar R, et al. Increasing mortality due to end-stage liver disease in patients with human immunodeficiency virus infection. Clin Infect Dis. 2001;32:492–497.
2. van de Laar T, Pybus O, Bruisten S, et al. Evidence of a large, international network of HCV transmission in HIV-positive men who have sex with men. Gastroenterology. 2009;136:1609–1617.
3. Taylor LE, Swan T, Mayer KH. HIV coinfection with hepatitis C virus: evolving epidemiology and treatment paradigms. Clin Infect Dis. 2012;55:S33–S42.
4. Price H, Gilson R, Mercey D, et al. Hepatitis C in men who have sex with men in London-a community survey. HIV Med. 2013;14:578–580.
5. Tanaka J, Akita T, Ohisa M, et al. Trends in the total numbers of HBV and HCV carriers in Japan from 2000 to 2011. J Viral Hepat. 2018;25:363–372.
6. Gatanaga H, Ibe S, Matsuda M, et al. Drug-resistant HIV-1 prevalence in patients newly diagnosed with HIV/AIDS in Japan. Antivir Res. 2007;75:75–82.
7. 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.
8. Nishijima T, Shimbo T, Komatsu H, et al. Incidence and risk factors for incident hepatitis C infection among men who have sex with men with HIV-1 infection in a large urban HIV clinic in Tokyo. J Acquir Immune Defic Syndr. 2014;65:213–217.
9. Ishikane M, Watanabe K, Tsukada K, et al. Acute hepatitis C in HIV-1 infected Japanese cohort: single center retrospective cohort study. PLoS One. 2014;9:e100517.
10. Isobe K, Imoto M, Fukuda Y, et al. Hepatitis C virus infection and genotypes in Japanese hemophiliacs. Liver. 1995;15:131–134.
11. Takayama S, Taki M, Meguro T, et al. Virological characteristics of HCV infection in Japanese haemophiliacs. Haemophilia. 1997;3:131–136.
12. Bull RA, Eltahla AA, Rodrigo C, et al. A method for near full-length amplification and sequencing for six hepatitis C virus genotypes. BMC Genomics. 2016;17:247.
13. Yang X, Charlebois P, Gnerre S, et al. De novo assembly of highly diverse viral populations. BMC Genomics. 2012;13:475.
14. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler Transform. Bioinformatics. 2009;25:1754–1760.
15. Thorvaldsdóttir H, Robinson JT, Mesirov JP. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform. 2013;14:178–192.
16. Struck D, Lawyer G, Ternes AM, et al. COMET: adaptive context-based modeling for ultrafast HIV-1 subtype identification. Nucleic Acids Res. 2014;42:e144.
17. Alcantara LC, Cassol S, Libin P, et al. A standardized framework for accurate high-throughput genotyping of recombinant and non-recombinant viral sequences. Nucleic Acids Res. 2009;37:W634–W642.
18. Shin-I T, Tanaka Y, Tateno Y, et al. Development and public release of a comprehensive hepatitis virus database. Hepatol Res. 2008;38:234–243.
19. Thompson JD, Higgins DG, Gibson TJ, et al. Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22:4673–4680.
20. Bouckaert R, Heled J, Kuhnert D, et al. BEAST 2: a software platform for Bayesian evolutionary analysis. PLoS Comput Biol. 2014;10:e1003537.
21. Matsumura H, Moriyama M, Goto I, et al. Natural course of progression of liver fibrosis in Japanese patients with chronic liver disease type C—a study of 527 patients at one establishment. J Viral Hepat. 2000;7:268–275.
22. Costantino A, Spada E, Equestre M, et al. Naturally occurring mutations associated with resistance to HCV NS5B polymerase and NS3 protease inhibitors in treatment-naïve patients with chronic hepatitis C. Virol J. 2015;12:186.
23. Li Z, Zhang Y, Liu Y, et al. Naturally occurring drug resistance associated variants to hepatitis C virus direct-acting antiviral agents in treatment-naive HCV genotype 1b-infected patients in China. Medicine (Baltimore). 2017;96:e6830.
24. Patino-Galindo JA, Salvatierra K, Gonzalez-Candelas F, et al. Comprehensive screening for naturally occurring hepatitis C virus resistance to direct-acting antivirals in the NS3, NS5A, and NS5B genes in worldwide isolates of viral genotypes 1 to 6. Antimicrob Agents Chemother. 2016;60:2402–2416.
25. Zhou K, Liang Z, Wang C, et al. Natural polymorphisms conferring resistance to HCV protease and polymerase inhibitors in treatment-naïve HIV/HCV co-infected patients in China. PLoS One. 2016;11:e0157438.
26. Suzuki F, Sezaki H, Akuta N, et al. Prevalence of hepatitis C virus variants resistant to NS3 protease inhibitors or the NS5A inhibitor (BMS-790052) in hepatitis patients with genotype 1b. J Clin Virol. 2012;54:352–354.
27. Tong X, Bogen S, Chase R, et al. Characterization of resistance mutations against HCV ketoamide protease inhibitors. Antivir Res. 2008;77:177–185.
28. Susser S, Welsch C, Wang Y, et al. Characterization of resistance to the protease inhibitor boceprevir in hepatitis C virus-infected patients. Hepatology. 2009;50:1709–1718.
29. Karino Y, Toyota J, Ikeda K, et al. Characterization of virologic escape in hepatitis C virus genotype 1b patients treated with the direct-acting antivirals daclatasvir and asunaprevir. J Hepatol. 2013;58:646–654.
30. Bell AM, Wagner JL, Barber KE, et al. Elbasvir/Grazoprevir: a review of the latest agent in the fight against hepatitis C. Int J Hepatol. 2016;2016:3852126.
31. Dietz J, Susser S, Vermehren J, et al. Patterns of resistance-associated substitutions in patients with chronic HCV infection following treatment with direct-acting antivirals. Gastroenterology. 2018;154:976–988.
32. Fridell RA, Qiu D, Wang C, et al. Resistance analysis of the hepatitis C virus NS5A inhibitor BMS-790052 in an in vitro replicon system. Antimicrob Agents Chemother. 2010;54:3641–3650.
33. Fridell RA, Wang C, Sun JH, et al. Genotypic and phenotypic analysis of variants resistant to hepatitis C virus nonstructural protein 5A replication complex inhibitor BMS-790052 in humans: in vitro and in vivo correlations. Hepatology. 2011;54:1924–1935.
34. Gao M, Nettles RE, Belema M, et al. Chemical genetics strategy identifies an HCV NS5A inhibitor with a potent clinical effect. Nature. 2010;465:96–100.
35. Lemm JA, O'Boyle D II, Liu M, et al. Identification of hepatitis C virus NS5A inhibitors. J Virol. 2010;84:482–491.
36. Wang C, Huang H, Valera L, et al. Hepatitis C virus RNA elimination and development of resistance in replicon cells treated with BMS-790052. Antimicrob Agents Chemother. 2012;56:1350–1358.
37. Krishnan P, Beyer J, Mistry N, et al. In vitro and in vivo antiviral activity and resistance profile of ombitasvir, an inhibitor of hepatitis C virus NS5A. Antimicrob Agents Chemother. 2015;59:979–987.
38. Kati W, Koev G, Irvin M, et al. In vitro activity and resistance profile of dasabuvir, a nonnucleoside hepatitis C virus polymerase inhibitor. Antimicrob Agents Chemother. 2015;59:1505–1511.
39. Vermehren J, Susser S, lange CM, et al. Mutations selected in the hepatitis C virus NS3 protease domain during sequential treatment with boceprevir with and without pegylated interferon alfa-2b. J Viral Hepat. 2012;19:120–127.
40. Bae A, Sun SC, Qi X, et al. Susceptibility of treatment-naïve hepatitis C virus (HCV) clinical isolates to HCV protease inhibitors. Antimicrob Agents Chemother. 2010;54:5288–5297.
41. McPhee F, Friborg J, Levine S, et al. Resistance analysis of the hepatitis C virus NS3 protease inhibitor asunaprevir. Antimicrob Agents Chemother. 2012;56:3670–3681.
42. Chan DP, Lin AW, Wong KH, et al. Diverse origins of hepatitis C virus in HIV co-infected men who have sex with men in Hong Kong. Virol J. 2015;12:120.
43. Vanhommerig JW, Bezemer D, Molenkamp R, et al. Limited overlap between phylogenetic HIV and hepatitis C virus clusters illustrates the dynamic sexual network structure of Dutch HIV-infected MSM. AIDS. 2017;31:2147–2158.

HIV; HCV; men who have sex with men; injection drug users; phylogenetic analysis; epidemiology

Supplemental Digital Content

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