RESEARCH ARTICLE Brazilian network for HIV Drug Resistance Surveillance (HIV-BresNet): a survey of treatment-naive individuals Monica B Arruda1, L�ıdia T Boullosa1, Cynthia C Cardoso1, Carolina M da Costa2, Carlos Brites3, Shirlene TS de Lima4, Helena T Kaminski5, Agdemir W Aleixo6, Ana OP Esposito7, Ana MS Cavalcanti8, Maristela Riedel9, Jos�e C Couto-Fernandez10, Selma B Ferreira11, Ivi CM de Oliveira12, Loreci E Portal13, Hilda HC Wolf14, Sandra B Fernandes15, Maria I de M. C. Pardini16, Manoel VC Feiteiro17, Fernanda M Tolentino18, Ricardo S Diaz19, Giselle ISL Lopes20, Roberta BL Francisco21, Nazle MC V�eras21, Ana F Pires21,22, Miriam Franchini21, F�abio Mesquita23, Amilcar Tanuri1 and HIV-BResNet* Corresponding author: Amilcar Tanuri, Departamento de Gen�etica, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil. Tel: +55 21 3938-6384. (atanuri@biologia.ufrj.br) *See the Appendix for members of HIV-BResNet. All authors cited in the HIV-BResNet group collaborated equally in the article. Correction note: The name of the fifth author was corrected on 8 May 2018. Abstract Introduction: In Brazil, more than 487,450 individuals are currently undergoing antiretroviral treatment. In order to monitor the transmission of drug-resistant strains and HIV subtype distribution in the country, this work aimed to estimate its preva- lence and to characterize the nationwide pretreatment drug resistance in individuals recently diagnosed with HIV between 2013 and 2015. Methods: The HIV threshold survey methodology (HIV-THS, WHO) targeting antiretroviral-naive individuals with recent HIV diagnosis was utilized, and subjects were selected from 51 highly populated cities in all five Brazilian macroregions. The HIV pol genotypic test was performed by genomic sequencing. Results: We analysed samples from 1568 antiretroviral-naive individuals recently diagnosed with HIV, and the overall trans- mitted drug resistance (TDR) prevalence was 9.5% (150 sequences). The regional prevalence of resistance according to Brazil- ian geographical regions was 9.4% in the northeast, 11.2% in the southeast, 6.8% in the central region, 10.2% in the north and 8.8% in the south. The inhibitor-specific TDR prevalence was 3.6% for nucleoside reverse transcriptase inhibitors (NRTIs), 5.8% for non-nucleoside reverse transcriptase inhibitors (NNRTIs) and 1.6% for protease inhibitors (PIs); 1.0% of individuals presented resistance to more than one class of inhibitors. Overall, subtype B was more prevalent in every region except for the southern, where subtype C prevails. Conclusions: To the best of our knowledge, this is the first TDR study conducted in Brazil with nationwide representative sampling. The TDR prevalence revealed a moderate rate in the five Brazilian geographical regions, although some cities pre- sented higher TDR prevalence rates, reaching 14% in S~ao Paulo, for example. These results further illustrate the importance of surveillance studies for designing future strategies in primary antiretroviral therapy, aiming to mitigate TDR, as well as for predicting future trends in other regions of the globe where mass antiretroviral (ARV) treatment was implemented. Keywords: HIV; HIV drug resistance; pretreatment HIV drug resistance; primary antiretroviral resistance; antiretroviral resistance; HIV Drug Resistance Surveillance Additional Supporting Information may be found online in the Supporting Information tab for this article. Received 5 December 2016; Accepted 14 November 2017 Copyright © 2018 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. 1 | INTRODUCTION The Brazilian Ministry of Health implemented, in 1996, a pioneering programme for the care and support of people liv- ing with HIV/AIDS, which encompasses free universal access to antiretroviral drugs for HIV-infected individuals. Besides the undoubted benefits of such policy, antiretroviral resistance remains one of the major obstacles to sustain HIV suppression during antiretroviral therapy (ART) [1,2]. Transmitted drug resistance (TDR), has been associated with first-line antiretro- viral virological failure in Brazil [3], and may as well compro- mise other therapeutic interventions, such as pre-exposure prophylaxis (PrEP), prevention of mother-to-child transmission (PMTCT) and post-exposed prophylaxis (PEP) [2]. Arruda MB et al. Journal of the International AIDS Society 2018, 21:e25032 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full | https://doi.org/10.1002/jia2.25032 1 http://orcid.org/0000-0003-0570-750X http://orcid.org/0000-0003-0570-750X http://orcid.org/0000-0003-0570-750X mailto:atanuri@biologia.ufrj.br http://creativecommons.org/licenses/by/4.0/ http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full https://doi.org/10.1002/jia2.25032 It is important to highlight that the treatment practices adopted by different countries can greatly influence TDR rates and substantial differences can be reported worldwide. In high-income countries, the number of newly infected patients that carry at least one major drug resistance muta- tion can vary from 7% to 17% [2,4,5]. A recent study analysed samples from 26 European countries and reported an overall prevalence of TDR of 8.3%. Countrywide studies identified TDR rates of 11.2% in the United States [6], 5.6% in Sweden [7], 14.7% in Romania [8] and 9.9% in Spain [9]. In middle- and low-income countries, the prevalence of TDR is around 7.0%, estimated at 6.3% in Latin America [4], 5.7% in India [10] and less than 5.0% in major African countries, including Angola, Botswana, South Africa, Uganda, Zimbabwe and Chad [11]. Brazil has recently adopted the Test and Treat policy and has an increasing number of patients in antiretroviral treat- ment at specialized AIDS clinics. In December 2015, more than 455,000 individuals were receiving antiretroviral treat- ment in Brazil, accounting for almost 68% of the HIV-infected individuals who are followed by the Brazilian Public Health System. In order to monitor the transmission of drug-resistant strains, as well as the HIV subtype distribution in Brazil, the Brazilian Ministry of Health has established the National Net- work for Drug Resistance Surveillance (HIV-BresNet). The first survey, conducted on 2001, showed an overall rate of trans- mitted resistance of 6.6%, with an even distribution of pro- tease and reverse transcriptase inhibitors resistance-related mutations [12]. In the second survey, carried out between 2007 and 2008, TDR mutations were found in 8.1% of the studied population, and an intermediate level of transmitted resistance (between 5% and 15%) was found in major Brazil- ian cities, such as Belem, Brasilia, S~ao Paulo and Rio de Janeiro [13]. Brazil is a continental country, and its different geographical regions have unique demographics as well as AIDS incidence. Therefore, determining a homogeneous picture of the Brazil- ian HIV/AIDS epidemic may be challenging. In order to pro- vide important data for the elaboration and revision of policies regarding prevention, treatment and care of HIV, this work aimed to estimate its prevalence and characterize the nationwide pretreatment drug resistance in individuals recently diagnosed with HIV, referred to as the first viral load test. 2 | METHODS 2.1 | Sampling A countrywide sampling was conducted in Brazil’s five major geographical regions: north, northeast, central-west, southeast and south. For this purpose, we have included 72 laboratories from the Brazilian Network for HIV Viral Load testing in 51 cities throughout the country. All patients were recently diag- nosed and samples were collected before ARV onset. Each region had probability proportional to size (PPS) sampling based on the information of the number of people who initi- ated ART in the previous time period. The standard sample size was 254, according to the WHO protocol for Surveillance of HIV drug resistance in adults initiating ART [14]. Based on it, at least 254 samples were collected per region and dis- tributed for each state maintaining the ratio of samples tested for viral load for the first time between 2013 and 2015. In view of the HIV/AIDS epidemic in Brazil, which is highly con- centrated in the southeast, the sample size was doubled to 508 in this region to prevent any sampling bias. The criteria for inclusion were: (i) 18 years old or older; (ii) first viral load at the Brazilian Ministry of Health National Network Labora- tories; and (iii) ART-naive individuals according to the Brazilian National System of Drugs Logistic Control (SICLOM). The eth- ical issues of this study were reviewed by UFRJ-IRB under # 30459614.9.0000.5257. This study was approved without the need for signed consent from volunteers, allowing the use of information available on the application form used for viral load exams only. 2.2 | Genotypic analyses Nineteen laboratories were responsible for running the HIV genotypic test using the TRUGENE� HIV-1 Genotyping Kit and the OpenGene� DNA Sequencing System (Siemens Healthcare Diagnostics, Tarrytown, NY, USA) and the quality of the test was assured using an external quality proficiency panel distributed by the Brazilian Ministry of Health, as previ- ously described [15]. Resistance mutations were assigned by the Calibrated Population Resistance (CPR) algorithm [16], which is based on the WHO drug resistance mutation list for surveillance of transmitted HIV-1 drug resistance [17]. Addi- tional analyses were conducted in order to verify pretreat- ment drug resistance, following WHO guidelines [14], using the HIVdb Program [18]. HIV-1 subtype assignments were defined according to the REGA HIV-1 Automated Subtyping Tool [19,20] and the HIVdb Program [18]. 2.3 | Statistical analysis Results of qualitative variables were represented as total counts and frequency and a Pearson’s Chi-squared test was applied for comparisons between genders, geographical regions and HIV subtypes. Results of quantitative variables (age and viral load) were represented as mean and standard deviation. Adherence to normal distribution was assessed using the Shapiro-Wilk test. A Kruskal-Wallis rank sum test was applied for overall comparisons of quantitative data between regions and a Dunn’s post hoc test was applied for pairwise comparisons with the Bonferroni adjustment. Age and viral load comparisons between genders were performed using a Mann-Whitney test. All analyses were performed using R for Windows 3.2.0 (R Development Core Team, Vienna, Austria). 3 | RESULTS 3.1 | Sampling In this study, samples were collected from October 2013 to January 2015, at the 72 viral load laboratories members of the Brazilian Ministry of Health National Network Laborato- ries. From this sampling, 1568 had the first 1000 nucleotides of pol region appropriately sequenced (GenBank accession numbers KX887502 to KX889067), attending the CPR algo- rithm. With the exception of the southeast region, which had Arruda MB et al. Journal of the International AIDS Society 2018, 21:e25032 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full | https://doi.org/10.1002/jia2.25032 2 http://www.ncbi.nlm.nih.gov/nuccore/KX887502 http://www.ncbi.nlm.nih.gov/nuccore/KX889067 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full https://doi.org/10.1002/jia2.25032 500 sequenced samples instead of the estimated number (508 samples), the sampling size inferred according to the PPS methodology was reached (see Supporting Information). Information concerning demographic parameters such as age and gender, as well as viral loads, was available for 1319 individuals. In general, the number of male samples (N = 919, 70%) was higher than female (N = 400, 30%), with the former composed of significantly younger individuals when compared to the latter (p < 0.0001). The viral load was also significantly higher in males (4.79 � 0.90 log10 copies/ml) than females (4.61 � 0.90 log10 copies/ml) (p < 0.001) (Table 1). Compar- isons of viral loads according to geographical region have also shown a statistically significant variation (p < 0.001; Kruskal- Wallis test). Results of post hoc comparisons have showed that viral loads were significantly lower in the southeast (4.602 � 0.876) as compared to the northeast (4.857 � 0.927) and southern (4.835 � 0.924) regions (p < 0.01). 3.2 | TDR analyses TDR analyses based on the CPR algorithm were conducted for each geographical region separately (see Supporting Infor- mation for details). The presence of any TDR in the analysed sequences from each Brazilian region varied from 6.8% (n = 18) in the central-west region to 11.2% (n = 56) in the southeast region. The prevalence of resistance to each drug class was similar in the different Brazilian regions (Table 2). When considering each antiretroviral class a higher preva- lence of TDR was identified for non-nucleoside reverse tran- scriptase inhibitors (NNRTIs), ranging from 4.5% (n = 12) in the northeast and central-west to 7.0% (n = 19) in the south (Table 2, Figure 1). Prevalence of TDR to NNRTIs was signifi- cantly higher than to nucleoside reverse transcriptase inhibi- tors (NRTIs) in an analysis considering subjects from all regions and also among subjects from the southern region (p < 0.01, both). As expected, prevalence of resistance to reverse transcriptase inhibitors (NRTI/NNRTI) was signifi- cantly higher than to protease inhibitors (PI; p < 0.01) in all Brazilian regions (Table 2). The north was the only region which showed one sequence with TDR to three antiretroviral classes (n = 1, 0.4%) (Figure 1). Concerning the NRTI mutations, M41L was the most preva- lent in the north (n = 7, 2.6%) and south (n = 2, 0.7%), whereas T215Y/D/S/E/I/V was highly prevalent in the north- east (n = 6, 2.3%), central-west (n = 5, 1.9%) and southeast (n = 7, 1.4%). Additional NNRTI mutations were identified at K65, D67, T69, K70, V75, M184 and L210 (Figure 2a). Regarding NNRTI-related mutations, K103N/S was the most prevalent variation in all regions: 4.2% in north (n = 11), 3.8% in the northeast (n = 10), 3.4% in the central-west (n = 9), 5.0% in the southeast (n = 25) and 5.5% in the south (n = 15). The NNRTI mutations were also identified at the positions L100, K101, V106, V179, Y181, Y188, G190 and P225 (Figure 2b). Regarding the PI mutations, M46I/L was the most prevalent in the north (n = 2, 0.8%), northeast (n = 4, 1.5%), central- west (n = 1, 0.4%), southeast (n = 4, 0.8%) and south (n = 2, 0.7%). V82A/L mutations were highly prevalent in the north- east (n = 4, 1.5%) and north (n = 4, 1.5%). PI mutations were also detected at L24, D30, V32, M46, I47, I50, F53, I54, V84, N88 and L90 (Figure 2c). 3.3 | HIV-1 subtyping assignment The HIV subtype characterization was evaluated for the 1568 analysed pol sequences using the REGA HIV-1 subtyping tool [19,20] and HIVdb Program [18]. With the exception of the south, the subtype B (n = 1045, 66.8%) remains the most prevalent in Brazil, followed by subtypes C (n = 223, 14.2%) and F (n = 156, 10%). We also found CRFs composed of sub- types B, C and F sequences spread throughout the regions. The CRF31 (B/C) was present in the southern region account- ing for 8.1% of all sequences analysed for this region, and the CRF31 variant was also found in the southeast (0.2%) and central-west (0.4%). In addition, CRF 12 and 29, composed of B and F sequences, were found in the central-west (0.4% Table 1. Distribution of age, gender and viral loads according to regiona Total North Northeast South Southeast Central-West Age (years)b 35 � 12 34 � 11 35 � 11 37 � 12 35 � 12 36 � 12 Male 34 � 11.5 34 � 11 34 � 12 35 � 12 34 � 11 35 � 11 Female 37 � 12.5 34 � 12 37 � 10 38 � 13 38 � 13 37 � 13 Genderc Male 919 (70) 168 (68) 119 (70) 153 (64) 336 (72) 143 (72) Female 400 (30) 78 (32) 52 (30) 86 (36) 129 (28) 55 (28) Viral load Maled 4.793 � 0.901 4.8 � 0.9 4.899 � 0.889 4.942 � 0.877 4.647 � 0.879 4.872 � 0.931 Female 4.614 � 0.896 4.684 � 0.846 4.762 � 1.012 4.652 � 0.977 4.483 � 0.862 4.634 � 0.768 Totale 4.739 � 0.903 4.763 � 0.898 4.857 � 0.927 4.835 � 0.924 4.602 � 0.876 4.805 � 0.892 aData is presented as N (%) for gender and mean � SD (standard deviation) for age and viral loads. bp < 0.0001 for comparisons according to regions (Kruskal-Wallis test). cTotal counts do not add up to the total number of subjects in this study (1319 against 1568 individuals) due to missing information. dp < 0.001 for comparisons of viral loads according to gender in the total sample (All) and p < 0.05 for the same comparison in the south and southeast regions (Mann-Whitney test). ep < 0.001 for comparisons of viral loads according to regions (Kruskal-Wallis test) and p < 0.01 for comparisons between southeast and north- east and between southeast and south regions (Dunn’s post hoc test). Arruda MB et al. Journal of the International AIDS Society 2018, 21:e25032 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full | https://doi.org/10.1002/jia2.25032 3 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full https://doi.org/10.1002/jia2.25032 CRF12 and 0.8% CRF29), southeast (0.6% CRF12 and 0.4% CRF29), south (0.4% CRF12 and 0.4% CRF29) and northeast regions, where only CRF12 was found (0.4%). CRF01_AE and CRF02_AG were identified in the central-west and northeast regions respectively (Figure 3). Unique recombinant forms (URFs) composed by complex subtype pattern between B, C, F and K sequences were found all over the country, account- ing for 6.3% of all isolates analysed. No differences between prevalence of TDR among different subtypes have been observed. Subtype C was the most prevalent in the south of Brazil (n = 147, 53.8%), followed by subtype B (n = 84, 30.8%), CRF31 (n = 22, 8.1%) and subtype F (n = 9, 3.3%) (Figure 3). 4 | DISCUSSION This is the first survey including samples from all Brazilian states, therefore truly representative of all five Brazilian geo- graphical macroregions, analysing 1568 samples of recently diagnosed individuals collected between 2013 and 2015. It is interesting to noticed that the majority of our subject included, young male, reflects the new HIV wave of epidemic affecting young MSM (http://unaids.org.br/estatisticas/). Our data enabled us to demonstrate the prevalence of TDR, varying from 6.8% (n = 18) in the central-west to 11.2% (n = 56) in the southeast. Based on the WHO HIVDR classifi- cation, all Brazilian macroregions showed intermediate level of resistance (5% to 15%). These prevalences are similar to the ones previously described in Brazil, as seen in Figure 1. How- ever, higher prevalence has occasionally been described in the cities of Salvador, located in the northeast region of Brazil (18.9% and 17.0%) [21,22] and Santos [23], in the southeast region of Brazil (29.2% and 17.0%) [22,24]. Our data is also consistent with other South American countries where mass treatments are provided. In a similar study done in Argentina, researchers found 14% of TDR and 11% of NNRTI DRM [25]. Although this study has not been designed to measure the transmitted resistance in each Brazilian state/city separately, we were able to observe that the state of S~ao Paulo has pre- sented higher levels of SDRM (surveillance drug-resistance mutation) than the other studied regions (data not shown), reaching 14% (28 resistant samples from 198 analysed). S~ao Paulo, the most populous state in Brazil, was the first to start treatment with antiretrovirals in the 1990s; more than 40% of patients receiving antiretroviral treatment in Brazil are in this state, whereas the city of S~ao Paulo alone is responsible for almost 25% of all antiretroviral treatment in Brazil. There- fore, it is conceivable that long-term exposure to antiretrovi- rals, which relates to sequential monotherapy and exposure to unboosted PIs, could increase the odds for antiretroviral fail- ure and consequent TDR. We observed a high prevalence of K103N – the NNRTI mutation – in recently diagnosed individuals in all regions of Brazil, ranging from 3.4 to 5.5%, compatible to world trends for this drug class [26]. There have been speculations that NNRTI mutations can be more readily transmitted due to the higher exposure to this drug class, as well as to its limited effect on the replicative capacity of the virus, therefore per- sisting for longer periods of time. This is a great concern in Brazil, since the protocol for initial treatment advocates theT ab le 2 . P re va le nc e o f dr ug re si st an ce ac co rd in g to re gi o n A ll (N = 1 5 6 8 )a N o rt h (N = 2 6 5 ) N o rt he as t (N = 2 6 5 ) So ut h (N = 2 7 3 )a So ut he as t (N = 5 0 0 ) C en tr al -W es t (N = 2 6 5 ) N R T I 5 7 (3 .6 ;2 .8 to 4 .7 ) 1 3 (4 .9 ; 2 .7 to 8 .4 ) 1 1 (4 .1 ; 2 .2 to 7 .5 ) 5 (1 .8 ; 0 .7 to 4 .5 ) 2 0 (4 ; 2 .5 to 6 .2 ) 8 (3 ; 1 .4 to 6 .1 ) N N R T I 9 1 (5 .8 ; 4 .7 to 7 .1 ) 1 4 (5 .3 ; 3 to 8 .9 ) 1 2 (4 .5 ; 2 .5 to 8 ) 1 9 (7 ; 4 .3 to 1 0 .8 ) 3 4 (6 .8 ; 4 .8 to 9 .5 ) 1 2 (4 .5 ; 2 .5 to 8 ) N R T I/ N N R T I 1 3 1 (8 .3 ; 7 to 1 0 ) 2 4 (9 ; 6 to 1 3 .3 ) 2 1 (7 .9 ; 5 .1 to 1 2 ) 2 1 (7 .7 ; 4 .9 to 1 1 .7 ) 4 9 (9 .8 ; 7 .4 to 1 2 .8 ) 1 6 (6 ; 3 .6 to 9 .8 ) P Ib 2 5 (1 .6 ; 1 to 2 .4 ) 6 (2 .2 ; 0 .9 to 5 .1 ) 6 (2 .2 ; 0 .9 to 5 .1 ) 3 (1 .1 ; 0 .3 to 3 .4 ) 9 (1 .8 ; 0 .9 to 3 .5 ) 1 (0 .4 ; 0 .0 2 to 2 .4 ) A ny re si st an ce 1 5 0 (9 .5 ; 8 .2 to 1 1 .1 ) 2 7 (1 0 .2 ; 6 .9 to 1 4 .6 ) 2 5 (9 .4 ; 6 .3 to 1 3 .8 ) 2 4 (8 .8 ; 5 .8 to 1 2 .9 ) 5 6 (1 1 .2 ; 8 .6 to 1 4 .4 ) 1 8 (6 .8 ; 4 .2 to 1 0 .7 ) R es ul ts ar e pr es en te d as N (% ; 9 5 % C I) .N R T I, nu cl eo si d e re ve rs e tr an sc ri pt as e in hi b it or ; N N R T I, no n- nu cl eo si d e re ve rs e tr an sc ri pt as e in hi b it or ; P I, pr ot ea se in hi b it or . a p < 0 .0 1 fo r co m pa ri so ns b et w ee n pr ev al en ce of re si st an ce to N N R T I an d N R T Is . b p < 0 .0 1 fo r co m pa ri so ns b et w ee n pr ev al en ce of re si st an ce to P Is an d N R T I/ N N R T I in th e en ti re sa m pl e (A ll) an d in ea ch re gi on se pa ra te ly . Arruda MB et al. Journal of the International AIDS Society 2018, 21:e25032 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full | https://doi.org/10.1002/jia2.25032 4 http://unaids.org.br/estatisticas/ http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full https://doi.org/10.1002/jia2.25032 fixed dose combination of tenofovir/3TC/efavirenz (http:// www.aids.gov.br/pcdt) [27]. It is also interesting to note that, as seen in Figure 2b, and in accordance to the frequent antiretroviral exposure in Brazil, the efavirenz related NNRTI pathway for resistance [25], which includes mutation at codons 103 associated to codons 100, and 225, is more fre- quently observed than the nevirapin pathway for resistance, which includes mutation at codons 181 and 101, the latter leading to cross-resistance to etravirine. Mutation at codon 103 was followed by NRTI mutations, with a high prevalence of the so-called T215 revertants (215 D/I/V/S, Figure 2a), which are products of the evolution of T215Y or T215F. Although the revertants per se do not present any level of phenotypic resistance [28], it is plausible that individuals har- bouring these revertants may also harbour the T215Y or T215F strains, which are associated with virological antiretro- viral failure [29]. Of course, it is theoretically possible that the revertants were transmitted rather than the original T215Y or T215F strains, and the analysis of minority HIV populations using next-generation sequencing techniques may be able to answer this important and interesting question. Again, in this study, the mutation at codon 184, generally the more preva- lent secondary resistance mutation, has a very low prevalence in this study, possibly related to the higher probability of this mutation to revert to a wild-type over time [27], which may be a note of caution among individuals presenting TDR muta- tions. The presence of minority HIV populations presenting M184V/I mutations among individuals already presenting TDR may also be a subject for future studies using next-generation sequencing techniques in TDR surveys. It is important to note in Figure 2 panel C that prevalence of PI related TDR is lower than previously documented in Bra- zil [13,30], possible related to a trend of increased use of boosted PIs over time which is also associated to a decreased prevalence of secondary PI resistance mutations over time in Brazil [30]. Nonetheless, it is also interesting to note that, mutations at protease codons 30, 88, 46 and 82, which relate to PIs such as nelfinavir, indinavir and ritonavir, which have not been used in Brazil for very long, are still being transmitted. This finding suggests that this TDR mutation has been occur- ring, unnoticed, from patient to patient for a very long time. In accordance to what has been previously shown in Brazil [31], the subtype C is more prevalent in the southern region, probably due to a founder effect, accounting for prevalence over 50%. Subtype C was also present in all regions of Brazil, in people who were recently diagnosed with HIV-1 infection, showing its spreading capacity. Together with subtype C, we found a substantial amount of CRF31 isolates in our sampling. This CRF was more present in the southern region; however, we encountered them throughout the central-west and south- east regions as well. According to predictions using the Baye- sian Markov chain Monte Carlo (MCMC) methods and the reversible-jump MCMC method, HIV-1 subtype B emerged in 1971, subtype F emerged in 1981, BF recombinants emerged in 1989, subtype C emerged in 1987 and BC recombinants emerged in 1992 [32–34]. This study also predicted that the basic reproductive number of secondary infections (R0 = 5 year interval) is 2.4 for Brazilian subtype B strains, 2.3 for subtype F and 4.6 for subtype C, warning for the faster expansion of this latter in the Brazilian epidemics [32]. It is also worth mentioning, that one study analysing phenotypic resis- tance in a limited number of samples from antiretroviral-naive individuals in Brazil revealed that some subtype C strains pre- sented phenotypic resistance no NRTIs and more frequently to NNRTIs without significant genotypic mutations, which sug- gests that the genotypic correlates of subtype C resistance might not yet be clearly defined, posing an additional problem related to the HIV-1 genetic diversity [35]. 5 | CONCLUSIONS In conclusion, we believe that the sampling technique used herein provides, for the first time, results on TDR that are truly representative of Brazil. The results presented reveal a moderate rate of primary prevalence of TDR in the five Brazil- ian macroregions. These results further illustrate the impor- tance of surveillance studies in the development of future strategies for mitigating TDR or initial treatment-related strategies, as well as for helping to predict future trends in other regions of the globe, where mass ARV treatment was implemented. 0.0 2.0 4.0 6.0 8.0 10.0 12.0 North Northeast Central-west Southeast South Fr eq ue nc y of S eq ue nc es (% ) Sequences with any SDRM PR: Sequences with any PI SDRM RT: Sequences with any NRTI SDRM RT: Sequences with any NNRTI SDRM RT: Sequences with any NRTI + any NNRTI SDRM PR/RT: Sequences with any NRTI + any NNRTI + PI SDRM Figure 1. Prevalence of sequences with any SDRM (surveillance drug-resistance mutation), any nucleoside reverse transcriptase inhibitors (NRTI) SDRM, any non-nucleoside reverse transcriptase inhibitors (NNRTI) SDRM and protease inhibitors (PI) SDRM distributed throughout all five geographical regions in Brazil: north, northeast, central-west, southeast, and south. Arruda MB et al. Journal of the International AIDS Society 2018, 21:e25032 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full | https://doi.org/10.1002/jia2.25032 5 http://www.aids.gov.br/pcdt http://www.aids.gov.br/pcdt http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full https://doi.org/10.1002/jia2.25032 AUTHORS ’ AFF I L IAT IONS 1Laborat�orio de Virologia Molecular, Departamento de Gen�etica-IB, Universi- dade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil; 2Fundac�~ao de Medic- ina Tropical do Amazonas, Manaus, AM, Brazil; 3Laborat�orio de Pesquisa, LAPI Universidade Federal da Bahia, Hospital Universit�ario “Prof. Edgar Santos”, Sal- vador, BA, Brazil; 4Laborat�orio Central de Sa�ude P�ublica do Cear�a (Lacen-CE), Fortaleza, CE, Brazil; 5Laborat�orio Central de Sa�ude P�ublica do Distrito Federal, Setor de Grandes Areas Norte (SGAN) 601, Brasilia, DF, Brazil; 6Faculdade de Medicina, Laborat�orio de Imunologia e Biologia Molecular (DIP), Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG, Brazil; 7Laborat�orio Central de Sa�ude P�ublica de Mato Grosso do Sul, Campo Grande, MS, Brazil; 8Laborat�orio Central de Sa�ude P�ublica de Pernambuco, Recife, PE, Brazil; 9Labo- rat�orio Municipal de Curitiba, Curitiba, PR, Brazil; 10Laborat�orio de AIDS e Imunologia Molecular, Departamento de Imunologia, FIOCRUZ, Rio de Janeiro, RJ, Brazil; 11UFRJ, Laborat�orio de Carga Viral, Hospital Universit�ario Cle- mentino Fraga Filho, Rio de Janeiro, RJ, Brazil; 12Instituto de Biologia do Ex�ercito, Rio de Janeiro, RJ, Brazil; 13Laborat�orio Central de Sa�ude P�ublica do Rio Grande do Sul, Porto Algre, RS, Brazil; 14Laborat�orio do Hospital Nossa Sen- hora da Conceic�~ao, Porto Alegre, RS, Brazil; 15Laborat�orio Central de Sa�ude P�ublica de Santa Catarina, Florian�opolis, SC, Brazil; 16Laborat�orio de Biologia 0.0 0.5 1.0 1.5 2.0 2.5 3.0 Fr eq ue nc y (% ) Mutations NRTIs North Northeast Central-west Southeast South M41L K65R D67N T69D K70R V75M/T M184V/I L210W T215 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Fr eq ue nc y (% ) Mutations PI L24I D30N V32I M46I/L I47V I50L F53Y/L I54V V82A/L I84V N88D/S L90M North Northeast Central-west South Southeast 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Fr eq ue nc y (% ) Mutations NNRTIs L100I K101E/P K103N/S V106M V179F Y181C Y188L/C G190A/S/E P225H North Northeast Central-west Southeast South (a) (b) (c) Figure 2. Prevalence of drug resistance mutations by drug class in antiretroviral drug-naive patients in each of the five geographical regions. (a) nucleoside reverse transcriptase inhibitors (NRTI) (b) non-nucleoside reverse transcriptase inhibitors (NNRTI) and (c) protease inhibitors (PI). Arruda MB et al. Journal of the International AIDS Society 2018, 21:e25032 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full | https://doi.org/10.1002/jia2.25032 6 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full https://doi.org/10.1002/jia2.25032 Molecular do Hemocentro de Botucatu, Faculdade de Medicina, UNESP, Botu- catu, SP, Brazil; 17Laborat�orio de Pesquisa em AIDS-Hospital de Cl�ıncas da UNI- CAMP, Campinas, SP, Brazil; 18Laborat�orio de Biologia Molecular-Instituto Adolfo Lutz de S~ao Jos�e do Rio Preto, S~ao Jos�e do Rio Preto, SP, Brazil; 19Escola Paulista de Medicina, Laborat�orio de Retrovirologia, Universidade Fed- eral de S~ao Paulo (UNIFESP), S~ao Paulo, SP, Brazil; 20Laborat�orio de Retrov�ırus, N�ucleo de Doenc�as Sangu�ıneas e Sexuais, Centro de Virologia, Instituto Adolfo Lutz Central, S~ao Paulo, SP, Brazil; 21Departamento de Vigilância, Prevenc�~ao e Controle das DST, AIDS e Hepatites, Setor Administrativo Federal Sul (SAFS) 02, Secretaria de Vigilância em Sa�ude, Minist�erio da Sa�ude, Bras�ılia, DF, Brazil; 22Programa de P�os Graduac�~ao em Sa�ude Coletiva, Faculdade de Medicina, Fac- uldade de Ciências de Sa�ude, Universidade de Bras�ılia, Bras�ılia, DF, Brazil; 23Fac- uldade de Medicina, Universidade de S~ao Paulo, S~ao Paulo, SP, Brazil COMPET ING INTERESTS The authors have no competing interests to declare. 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APPENDIX Other members of HIV-BResNet Andrea de Melo Xavier Shimizu (Fundac�~ao Medicina Tropical do Amazonas), C�elia Regina Mayoral Pedroso Jorge PhD (Lab- orat�orio de Pesquisa - LAPI Universidade Federal da Bahia - Hospital Universit�ario”Prof. Edgar Santos”), Leda Maria Sim~oes Mello, MSc (LACEN/CE), Eider Gurgel de Freitas (LACEN/ DF), Una�ı Tupinamb�as, PhD (Universidade Federal de Minas Gerais - UFMG, Faculdade de Medicina - Laborat�orio de Imunologia e Biologia Molecular - DIP), Dijane Cristina de Bar- ros Rosa Costa, BSc (LACEN/MS), Sirleide Pereira da Silva, BSc (LACEN/PE), Maria da Grac�a Winhescki, BSc. (Laborat�orio Municipal de Curitiba), Carlos Silva de Jesus (Laborat�orio de AIDS e Imunologia Molecular - Departamento de Imunologia - FIOCRUZ), �Erica Ramos dos Santos Nascimento, BSc. (Hospi- tal Universit�ario Clementino Fraga Filho), Fatima Erc�ılia de Oliveira Prazim, BSc (Instituto de Biologia do Ex�ercito), Mar- ilda Tereza Mar da Rosa (LACEN/RS), Karina Salvador, BSc (Laborat�orio do Hospital Nossa Senhora da Conceic�~ao), Senele Ana de Alcântara Belettini, BSc (LACEN/SC), Rejane Maria Tommasini Grotto, PhD (Laborat�orio de Carga Viral, Hemo- centro de Botucatu - UNESP), Paulo Henrique de Oliveira, BSc (Laborat�orio de Pesquisa em AIDS-Hospital de Cl�ıncas da UNICAMP), �Erica Valessa Ramos Gomes (Laborat�orio de Biologia Molecular-Instituto Adolfo Lutz de S~ao Jos�e do Rio Preto), Danilo Araujo Dias, BSc and Juliana Galinskas, MSc (Laborat�orio de Retrovirologia-UNIFESP, Escola Paulista de Medicina), Norberto Camilo Campos, BSc (Laborat�orio de Ret- rov�ırus. Instituto Adolfo Lutz Central - S~ao Paulo), Jos�e Boul- losa Alonso Neto (Minist�erio da Sa�ude - Secretaria de Vigilância em Sa�ude - Departamento de Vigilância, Prevenc�~ao e Controle das DST, AIDS e Hepatites). SUPPORTING INFORMATION Additional Supporting Information may be found in the online version of this article: Table S1. Distribution of samples stratified in Brazil’s five major geographical regions Table S2. Prevalence of drug resistance according to State Arruda MB et al. Journal of the International AIDS Society 2018, 21:e25032 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full | https://doi.org/10.1002/jia2.25032 8 http://onlinelibrary.wiley.com/doi/10.1002/jia2.25032/full https://doi.org/10.1002/jia2.25032 Outline placeholder tbl1 tbl2 bib1 bib2 bib3 bib4 bib5 bib6 bib7 bib8 bib9 bib10 bib11 bib12 bib13 bib14 bib15 bib16 bib17 bib18 bib19 bib20 bib21 bib22 bib23 bib24 bib25 bib26 bib27 bib28 bib29 bib30 bib31 bib32 bib33 bib34 bib35 bib36